From 0d344b8c6fd995e9f0193d639613e049f5b69f74 Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Sun, 31 May 2026 13:34:26 +0300 Subject: [PATCH 01/20] recovered regr_smlp/data/smlp_toy_num_resp_noknobs.csv and regr_smlp/specs/smlp_toy_num_resp_noknobs_verify.spec --- regr_smlp/data/smlp_toy_num_resp_noknobs.csv | 12 ++++++++++++ .../specs/smlp_toy_num_resp_noknobs_verify.spec | 8 ++++++++ 2 files changed, 20 insertions(+) create mode 100644 regr_smlp/data/smlp_toy_num_resp_noknobs.csv create mode 100644 regr_smlp/specs/smlp_toy_num_resp_noknobs_verify.spec diff --git a/regr_smlp/data/smlp_toy_num_resp_noknobs.csv b/regr_smlp/data/smlp_toy_num_resp_noknobs.csv new file mode 100644 index 00000000..7a4c8240 --- /dev/null +++ b/regr_smlp/data/smlp_toy_num_resp_noknobs.csv @@ -0,0 +1,12 @@ +categ,y1,y2,x0,x1,x2 +c14,5,9,10.0,2.0,3 +c15,9,9,12.0,,4 +c1,5,9,,3.0,4 +c9,5,5,11.0,2.0,6 +c5,9,5,10.0,2.0,8 +c10,9,9,9.0,4.0,7 +c13,5,5,9.0,3.0,6 +c4,5,5,10.0,3.0,4 +c15,9,9,11.0,4.0,4 +c11,5,5,12.0,2.0,7 +c19,9,5,10.0,3.0,7 diff --git a/regr_smlp/specs/smlp_toy_num_resp_noknobs_verify.spec b/regr_smlp/specs/smlp_toy_num_resp_noknobs_verify.spec new file mode 100644 index 00000000..88dab785 --- /dev/null +++ b/regr_smlp/specs/smlp_toy_num_resp_noknobs_verify.spec @@ -0,0 +1,8 @@ +{"version": "1.1", + "spec":[ + {"label": "y1", "type": "response", "range": "float"}, + {"label": "y2", "type": "response", "range": "float"}, + {"label": "x0", "type": "input", "range": "float", "bounds": [0,10]}, + {"label": "x1", "type": "input", "range": "float", "bounds": [0,10]}, + {"label": "x2", "type": "input", "range": "float", "bounds": [3,7]}], + "alpha": "x1==1 or x1==4 or x1==7"} From 756f25885fc09b9010a3ea109f02822f2ac7cabe Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 00:14:08 +0300 Subject: [PATCH 02/20] added smlp_toy_num_resp_noknobs_pred_labeled.csv and masters for Test57 and Test61 --- ...smlp_toy_num_resp_noknobs_pred_labeled.csv | 10 + .../Test57_smlp_toy_num_resp_noknobs.txt | 262 ++++++++++++++++++ ...smlp_toy_num_resp_noknobs_data_bounds.json | 22 ++ ...resp_noknobs_dt_sklearn_model_complete.pkl | Bin 0 -> 1881 bytes ...num_resp_noknobs_dt_sklearn_tree_rules.txt | 10 + ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 714 bytes ..._noknobs_labeled_prediction_precisions.csv | 3 + ...sp_noknobs_labeled_predictions_summary.csv | 12 + ..._num_resp_noknobs_missing_values_dict.json | 8 + ..._num_resp_noknobs_model_features_dict.json | 12 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 661 bytes ...num_resp_noknobs_smlp_full_model_term.json | 1 + ..._toy_num_resp_noknobs_smlp_model_term.json | 1 + ...esp_noknobs_test_prediction_precisions.csv | 3 + ..._resp_noknobs_test_predictions_summary.csv | 4 + ...Test57_smlp_toy_num_resp_noknobs_trace.csv | 9 + ...noknobs_training_prediction_precisions.csv | 3 + ...p_noknobs_training_predictions_summary.csv | 9 + ...p_toy_num_resp_noknobs_verify_results.json | 23 ++ .../master/Test61_smlp_toy_num_resp_mult.txt | 248 +++++++++++++++++ ...61_smlp_toy_num_resp_mult_data_bounds.json | 22 ++ ...smlp_toy_num_resp_mult_features_scaler.pkl | Bin 0 -> 714 bytes ...esp_mult_labeled_prediction_precisions.csv | 3 + ..._resp_mult_labeled_predictions_summary.csv | 12 + ...toy_num_resp_mult_missing_values_dict.json | 8 + ...smlp_toy_num_resp_mult_model_checkpoint.h5 | Bin 0 -> 45160 bytes ...toy_num_resp_mult_model_features_dict.json | 12 + ...st61_smlp_toy_num_resp_mult_model_gen.json | 1 + ...p_toy_num_resp_mult_model_levels_dict.json | 1 + ...y_num_resp_mult_nn_keras_model_complete.h5 | Bin 0 -> 45160 bytes ...mlp_toy_num_resp_mult_responses_scaler.pkl | Bin 0 -> 661 bytes ...mlp_toy_num_resp_mult_smlp_model_term.json | 1 + ...m_resp_mult_test_prediction_precisions.csv | 3 + ...num_resp_mult_test_predictions_summary.csv | 4 + ...sp_mult_training_prediction_precisions.csv | 3 + ...resp_mult_training_predictions_summary.csv | 9 + ...smlp_toy_num_resp_mult_verify_results.json | 23 ++ .../Test61_smlp_toy_num_resp_noknobs.txt | 248 +++++++++++++++++ ...smlp_toy_num_resp_noknobs_data_bounds.json | 22 ++ ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 714 bytes ..._noknobs_labeled_prediction_precisions.csv | 3 + ...sp_noknobs_labeled_predictions_summary.csv | 12 + ..._num_resp_noknobs_missing_values_dict.json | 8 + ...p_toy_num_resp_noknobs_model_checkpoint.h5 | Bin 0 -> 45160 bytes ..._num_resp_noknobs_model_features_dict.json | 12 + ...1_smlp_toy_num_resp_noknobs_model_gen.json | 1 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ...um_resp_noknobs_nn_keras_model_complete.h5 | Bin 0 -> 45160 bytes ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 661 bytes ..._toy_num_resp_noknobs_smlp_model_term.json | 1 + ...esp_noknobs_test_prediction_precisions.csv | 3 + ..._resp_noknobs_test_predictions_summary.csv | 4 + ...noknobs_training_prediction_precisions.csv | 3 + ...p_noknobs_training_predictions_summary.csv | 9 + ...p_toy_num_resp_noknobs_verify_results.json | 23 ++ 56 files changed, 1093 insertions(+) create mode 100644 regr_smlp/data/smlp_toy_num_resp_noknobs_pred_labeled.csv create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs.txt create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_data_bounds.json create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_features_scaler.pkl create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_missing_values_dict.json create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_model_features_dict.json create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_model_levels_dict.json create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_responses_scaler.pkl create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_smlp_full_model_term.json create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_smlp_model_term.json create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_trace.csv create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_verify_results.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult.txt create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_data_bounds.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_features_scaler.pkl create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_missing_values_dict.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_model_checkpoint.h5 create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_model_features_dict.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_model_gen.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_model_levels_dict.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_nn_keras_model_complete.h5 create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_responses_scaler.pkl create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_smlp_model_term.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_verify_results.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs.txt create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_data_bounds.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_features_scaler.pkl create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_missing_values_dict.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_checkpoint.h5 create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_features_dict.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_gen.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_levels_dict.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_nn_keras_model_complete.h5 create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_responses_scaler.pkl create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_smlp_model_term.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_verify_results.json diff --git a/regr_smlp/data/smlp_toy_num_resp_noknobs_pred_labeled.csv b/regr_smlp/data/smlp_toy_num_resp_noknobs_pred_labeled.csv new file mode 100644 index 00000000..2b0ea3c0 --- /dev/null +++ b/regr_smlp/data/smlp_toy_num_resp_noknobs_pred_labeled.csv @@ -0,0 +1,10 @@ +categ,y1,y2,x0,x1,x2 +c0,5,9,10.0,2.0,3 +c12,9,9,12.0,,4 +c2,5,9,,3.0,4 +c17,5,5,11.0,2.0,6 +c18,9,5,10.0,2.0,8 +c8,9,9,9.0,4.0,7 +c7,5,5,9.0,3.0,6 +c3,5,5,10.0,3.0,4 +c12,9,9,11.0,4.0,4 diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs.txt new file mode 100644 index 00000000..b42d7da2 --- /dev/null +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs.txt @@ -0,0 +1,262 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt_y1: y1*2+x0<=5 and y1<=10 + +smlp_logger - INFO - Assertion asrt_y2: -2*y2-1<10-x2 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x0 x1 x2 y1 y2 +0 0.333333 0.0 0.0 0.0 1.0 +1 1.000000 0.0 0.2 1.0 1.0 +2 0.333333 0.5 0.2 0.0 1.0 +3 0.666667 0.0 0.6 0.0 0.0 +4 0.333333 0.0 1.0 1.0 0.0 +5 0.000000 1.0 0.8 1.0 1.0 +6 0.000000 0.5 0.6 0.0 0.0 +7 0.333333 0.5 0.2 0.0 0.0 +8 0.666667 1.0 0.2 1.0 1.0 +9 1.000000 0.0 0.8 0.0 0.0 +10 0.333333 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 3) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test57_smlp_toy_num_resp_noknobs_data_bounds.json + +smlp_logger - INFO - {'x0': {'min': 9.0, 'max': 12.0}, 'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./Test57_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./Test57_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test57_smlp_toy_num_resp_noknobs_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test57_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test57_smlp_toy_num_resp_noknobs_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test57_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on test data -- r2_score: 0.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test57_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test57_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 0.727 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.817 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt_y1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt_y2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt_y1 <-> y1*2+x0<=5 and y1<=10 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt_y1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt_y2 <-> -2*y2-1<10-x2 + +smlp_logger - INFO - The configuration is consistent with assertion asrt_y2 + +smlp_logger - INFO - Completed with result: PASS + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_data_bounds.json b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_data_bounds.json new file mode 100644 index 00000000..5df59662 --- /dev/null +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_data_bounds.json @@ -0,0 +1,22 @@ +{ + "x0": { + "min": 9.0, + "max": 12.0 + }, + "x1": { + "min": 2.0, + "max": 4.0 + }, + "x2": { + "min": 3.0, + "max": 8.0 + }, + "y1": { + "min": 5.0, + "max": 9.0 + }, + "y2": { + "min": 5.0, + "max": 9.0 + } +} \ No newline at end of file diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl new file mode 100644 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67108864))) (<= |:0| (/ 23488103 33554432))) 0 (ite (and (> |:0| (/ 53687093 134217728)) (> |:2| (/ 3 4))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (> |:0| (/ 23488103 33554432))) 1 0))))) 4) 5))))>, 'y2': |:1| (/ 44739243 67108864))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (<= |:0| (/ 23488103 33554432))) 0 (ite (and (> |:0| (/ 53687093 134217728)) (> |:2| (/ 3 4))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (> |:0| (/ 23488103 33554432))) 0 0))))) 4) 5))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_smlp_model_term.json b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_smlp_model_term.json new file mode 100644 index 00000000..ea7ac531 --- /dev/null +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': x_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> p2_scaled (/ 53687093 134217728)) (<= p1_scaled (/ 3 4))) (<= x_scaled (/ 33554433 67108864))) (<= p2_scaled (/ 23488103 33554432))) 0 (ite (and (> p2_scaled (/ 53687093 134217728)) (> p1_scaled (/ 3 4))) 1 (ite (and (and (and (> p2_scaled (/ 53687093 134217728)) (<= p1_scaled (/ 3 4))) (<= x_scaled (/ 33554433 67108864))) (> p2_scaled (/ 23488103 33554432))) 1 0)))))>, 'y2_scaled': x_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> p2_scaled (/ 53687093 134217728)) (<= p1_scaled (/ 3 4))) (<= x_scaled (/ 33554433 67108864))) (<= p2_scaled (/ 23488103 33554432))) 0 (ite (and (> p2_scaled (/ 53687093 134217728)) (> p1_scaled (/ 3 4))) 1 (ite (and (and (and (> p2_scaled (/ 53687093 134217728)) (<= p1_scaled (/ 3 4))) (<= x_scaled (/ 33554433 67108864))) (> p2_scaled (/ 23488103 33554432))) 0 0)))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv new file mode 100644 index 00000000..ec56b74c --- /dev/null +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_test_predictions_summary.csv new file mode 100644 index 00000000..3477d51d --- /dev/null +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,5.0,9.0 +2,5.0,9.0,5.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_trace.csv new file mode 100644 index 00000000..bd573129 --- /dev/null +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_trace.csv @@ -0,0 +1,9 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,7,3 +model_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +ca,unsat +ce,sat,0,1,7,9,5 +ca,sat,0,7,671088649/134217728,5,9 +ce,unsat diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_verify_results.json new file mode 100644 index 00000000..cc3c4b12 --- /dev/null +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_verify_results.json @@ -0,0 +1,23 @@ +{ + "asrt_y1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x0": 0.0, + "x1": 1.0, + "y1": 9.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "asrt_y2": { + "configuration_consistent": "true", + "assertion_status": "PASS", + "counter_example": null, + "assertion_feasible": true + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult.txt b/regr_smlp/master/Test61_smlp_toy_num_resp_mult.txt new file mode 100644 index 00000000..147f3959 --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_mult.txt @@ -0,0 +1,248 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'p1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'p2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'p1==1 or p1==4 or p1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : p1==1 or p1==4 or p1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt_y1: not(p25 and y1<=10) + +smlp_logger - INFO - Assertion asrt_y2: -2*y2-1<10-p2 and p2>5 and p2<8 + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x p1 p2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x p1 p2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x p1 p2 y1 y2 +0 10.0 2.0 3.0 5.0 9.0 +1 12.0 2.0 4.0 9.0 9.0 +2 10.0 3.0 4.0 5.0 9.0 +3 11.0 2.0 6.0 5.0 5.0 +4 10.0 2.0 8.0 9.0 5.0 +5 9.0 4.0 7.0 9.0 9.0 +6 9.0 3.0 6.0 5.0 5.0 +7 10.0 3.0 4.0 5.0 5.0 +8 11.0 4.0 4.0 9.0 9.0 +9 12.0 2.0 7.0 5.0 5.0 +10 10.0 3.0 7.0 9.0 5.0 + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x p1 p2 y1 y2 +0 10.0 2.0 3.0 5.0 9.0 +1 12.0 2.0 4.0 9.0 9.0 +2 10.0 3.0 4.0 5.0 9.0 +3 11.0 2.0 6.0 5.0 5.0 +4 10.0 2.0 8.0 9.0 5.0 +5 9.0 4.0 7.0 9.0 9.0 +6 9.0 3.0 6.0 5.0 5.0 +7 10.0 3.0 4.0 5.0 5.0 +8 11.0 4.0 4.0 9.0 9.0 +9 12.0 2.0 7.0 5.0 5.0 +10 10.0 3.0 7.0 9.0 5.0 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x p1 p2 y1 y2 +0 0.333333 0.0 0.0 0.0 1.0 +1 1.000000 0.0 0.2 1.0 1.0 +2 0.333333 0.5 0.2 0.0 1.0 +3 0.666667 0.0 0.6 0.0 0.0 +4 0.333333 0.0 1.0 1.0 0.0 +5 0.000000 1.0 0.8 1.0 1.0 +6 0.000000 0.5 0.6 0.0 0.0 +7 0.333333 0.5 0.2 0.0 0.0 +8 0.666667 1.0 0.2 1.0 1.0 +9 1.000000 0.0 0.8 0.0 0.0 +10 0.333333 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 3) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test61_smlp_toy_num_resp_mult_data_bounds.json + +smlp_logger - INFO - {'x': {'min': 9.0, 'max': 12.0}, 'p1': {'min': 2.0, 'max': 4.0}, 'p2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - keras_main: start + +smlp_logger - INFO - _keras_train_multi_response: start + +smlp_logger - INFO - building NN model using Keras Functional API + +smlp_logger - INFO - layers_spec_list [1, 2.0, 1.0] + +smlp_logger - INFO - input layer of size 3 + +smlp_logger - INFO - dense layer of size 6 + +smlp_logger - INFO - dense layer of size 3 + +smlp_logger - INFO - _keras_train_multi_response: end + +smlp_logger - INFO - keras_main: end + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 5.791 + +smlp_logger - INFO - Prediction on training data -- r2_score: -0.488 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 6.635 + +smlp_logger - INFO - Prediction on test data -- r2_score: -0.866 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test61_smlp_toy_num_resp_mult_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test61_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 6.021 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: -0.518 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x': {'range': 'float', 'interval': [0, 10]}, 'p1': {'range': 'float', 'interval': [0, 10]}, 'p2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x': {'min': 0, 'max': 10}, 'p1': {'min': 0, 'max': 10}, 'p2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= p1 1) (= p1 4)) (= p1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x 0) (<= x 10))) (and (>= p1 0) (<= p1 10))) (and (>= p2 3) (<= p2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x 0) (<= x 10))) (and (>= p1 0) (<= p1 10))) (and (>= p2 3) (<= p2 7))) (or (or (= p1 1) (= p1 4)) (= p1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt_y1 <-> not(p25 and y1<=10) + +smlp_logger - INFO - The configuration is consistent with assertion asrt_y1 + +smlp_logger - INFO - Completed with result: PASS + +smlp_logger - INFO - Verifying assertion asrt_y2 <-> -2*y2-1<10-p2 and p2>5 and p2<8 + +smlp_logger - INFO - The configuration is consistent with assertion asrt_y2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_data_bounds.json b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_data_bounds.json new file mode 100644 index 00000000..c3f3c0b3 --- 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|:2| 0))) (let ((|:4| (+ (+ (+ (* x_scaled (/ 12212227 16777216)) (* p1_scaled (/ 13212577 134217728))) (* p2_scaled (/ 16241617 134217728))) (/ 11776873 134217728)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x_scaled (/ 710205 4194304)) (* p1_scaled (/ 1014123 8388608))) (* p2_scaled (/ (- 11073897) 16777216))) (/ (- 7254327) 134217728)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x_scaled (/ 4704661 33554432)) (* p1_scaled (/ (- 6233549) 8388608))) (* p2_scaled (/ 4785015 8388608))) (/ (- 4773853) 67108864)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x_scaled (/ 12316703 16777216)) (* p1_scaled (/ 2069995 16777216))) (* p2_scaled (/ (- 335261) 524288))) (/ (- 4510373) 67108864)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 2045741 67108864)) (* |:3| (/ 9001505 33554432))) (* |:5| (/ (- 4253115) 8388608))) (* |:7| (/ 11755105 16777216))) (* |:9| (/ 2348089 4194304))) (* |:11| (/ 11766505 16777216))) (/ (- 8711947) 134217728)))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 9041845) 67108864)) (* |:3| (/ (- 7472907) 33554432))) (* |:5| (/ 9650993 268435456))) (* |:7| (/ (- 15252035) 1073741824))) (* |:9| (/ 6924703 16777216))) (* |:11| (/ (- 3496069) 16777216))) (/ (- 8998365) 134217728)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 4912199) 8388608)) (* |:3| (/ 677045 2097152))) (* |:5| (/ (- 8260447) 16777216))) (* |:7| (/ (- 481099) 1048576))) (* |:9| (/ (- 3619967) 8388608))) (* |:11| (/ (- 5030151) 16777216))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ (- 7714595) 16777216)) (* (ite (>= |:13| 0) |:13| 0) (/ 1166761 8388608))) (* (ite (>= |:14| 0) |:14| 0) (/ 1706327 4194304))) (/ 1543007 16777216)))))))))))))))))>, 'y2_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x_scaled (/ 14333415 33554432)) (* p1_scaled (/ (- 3173377) 4194304))) (* p2_scaled (/ (- 11989195) 16777216))) (/ (- 9690501) 134217728)))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x_scaled (/ 12212227 16777216)) (* p1_scaled (/ 13212577 134217728))) (* p2_scaled (/ 16241617 134217728))) (/ 11776873 134217728)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x_scaled (/ 710205 4194304)) (* p1_scaled (/ 1014123 8388608))) (* p2_scaled (/ (- 11073897) 16777216))) (/ (- 7254327) 134217728)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x_scaled (/ 4704661 33554432)) (* p1_scaled (/ (- 6233549) 8388608))) (* p2_scaled (/ 4785015 8388608))) (/ (- 4773853) 67108864)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x_scaled (/ 12316703 16777216)) (* p1_scaled (/ 2069995 16777216))) (* p2_scaled (/ (- 335261) 524288))) (/ (- 4510373) 67108864)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 2045741 67108864)) (* |:3| (/ 9001505 33554432))) (* |:5| (/ (- 4253115) 8388608))) (* |:7| (/ 11755105 16777216))) (* |:9| (/ 2348089 4194304))) (* |:11| (/ 11766505 16777216))) (/ (- 8711947) 134217728)))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 9041845) 67108864)) (* |:3| (/ (- 7472907) 33554432))) (* |:5| (/ 9650993 268435456))) (* |:7| (/ (- 15252035) 1073741824))) (* |:9| (/ 6924703 16777216))) (* |:11| (/ (- 3496069) 16777216))) (/ (- 8998365) 134217728)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 4912199) 8388608)) (* |:3| (/ 677045 2097152))) (* |:5| (/ (- 8260447) 16777216))) (* |:7| (/ (- 481099) 1048576))) (* |:9| (/ (- 3619967) 8388608))) (* |:11| (/ (- 5030151) 16777216))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ 6139899 16777216)) (* (ite (>= |:13| 0) |:13| 0) (/ (- 12016607) 16777216))) (* (ite (>= |:14| 0) |:14| 0) (/ 8852893 8388608))) (/ 3189679 33554432)))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv new file mode 100644 index 00000000..25a6c190 --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,4.487652267232382,-0.26215220015910745 +y2,8.783304804871781,-1.4703044763701882 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv new file mode 100644 index 00000000..d7e99979 --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_nn_keras,y2_nn_keras +7,5.0,5.0,5.367882,5.3802395 +2,5.0,9.0,5.367882,5.3802395 +8,9.0,9.0,5.367882,5.3802395 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv new file mode 100644 index 00000000..f6e8a3ab --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,6.692210216292125,-0.6730525540730312 +y2,4.888843185538093,-0.30369151614349144 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv new file mode 100644 index 00000000..1575caab --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_nn_keras,y2_nn_keras +3,5.0,5.0,5.4227495,5.097694 +4,9.0,5.0,5.443091,4.8975835 +5,9.0,9.0,5.367882,5.3802395 +0,5.0,9.0,5.367882,5.3802395 +10,9.0,5.0,5.367882,5.3802395 +9,5.0,5.0,5.451473,4.94978 +6,5.0,5.0,5.367882,5.3802395 +1,9.0,9.0,5.2786703,5.4512405 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_verify_results.json b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_verify_results.json new file mode 100644 index 00000000..73293bbf --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_verify_results.json @@ -0,0 +1,23 @@ +{ + "asrt_y1": { + "configuration_consistent": "skipped", + "assertion_status": "PASS", + "counter_example": null, + "assertion_feasible": true + }, + "asrt_y2": { + "configuration_consistent": "skipped", + "assertion_status": "FAIL", + "counter_example": { + "y2": 5.380239367485046, + "y1": 5.367881536483765, + "p2": 3.363086516639646, + "p1": 1.0, + "x": 4.1667309548392275 + }, + "assertion_feasible": true + }, + "smlp_execution": "completed", + "interface_consistent": "skipped", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs.txt new file mode 100644 index 00000000..147f3959 --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs.txt @@ -0,0 +1,248 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'p1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'p2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'p1==1 or p1==4 or p1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : p1==1 or p1==4 or p1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt_y1: not(p25 and y1<=10) + +smlp_logger - INFO - Assertion asrt_y2: -2*y2-1<10-p2 and p2>5 and p2<8 + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x p1 p2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x p1 p2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x p1 p2 y1 y2 +0 10.0 2.0 3.0 5.0 9.0 +1 12.0 2.0 4.0 9.0 9.0 +2 10.0 3.0 4.0 5.0 9.0 +3 11.0 2.0 6.0 5.0 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training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 3) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test61_smlp_toy_num_resp_mult_data_bounds.json + +smlp_logger - INFO - {'x': {'min': 9.0, 'max': 12.0}, 'p1': {'min': 2.0, 'max': 4.0}, 'p2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - keras_main: start + +smlp_logger - INFO - _keras_train_multi_response: start + +smlp_logger - INFO - building NN model using Keras Functional API + +smlp_logger - INFO - layers_spec_list [1, 2.0, 1.0] + +smlp_logger - INFO - input layer of size 3 + +smlp_logger - INFO - dense layer of size 6 + +smlp_logger - INFO - dense layer of size 3 + +smlp_logger - INFO - _keras_train_multi_response: end + +smlp_logger - INFO - keras_main: end + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 5.791 + +smlp_logger - INFO - Prediction on training data -- r2_score: -0.488 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 6.635 + +smlp_logger - INFO - Prediction on test data -- r2_score: -0.866 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test61_smlp_toy_num_resp_mult_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test61_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 6.021 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: -0.518 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x': {'range': 'float', 'interval': [0, 10]}, 'p1': {'range': 'float', 'interval': [0, 10]}, 'p2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x': {'min': 0, 'max': 10}, 'p1': {'min': 0, 'max': 10}, 'p2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= p1 1) (= p1 4)) (= p1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x 0) (<= x 10))) (and (>= p1 0) (<= p1 10))) (and (>= p2 3) (<= p2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x 0) (<= x 10))) (and (>= p1 0) (<= p1 10))) (and (>= p2 3) (<= p2 7))) (or (or (= p1 1) (= p1 4)) (= p1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt_y1 <-> not(p25 and y1<=10) + +smlp_logger - INFO - The configuration is consistent with assertion asrt_y1 + +smlp_logger - INFO - Completed with result: PASS + +smlp_logger - 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134217728)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x_scaled (/ 4704661 33554432)) (* p1_scaled (/ (- 6233549) 8388608))) (* p2_scaled (/ 4785015 8388608))) (/ (- 4773853) 67108864)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x_scaled (/ 12316703 16777216)) (* p1_scaled (/ 2069995 16777216))) (* p2_scaled (/ (- 335261) 524288))) (/ (- 4510373) 67108864)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 2045741 67108864)) (* |:3| (/ 9001505 33554432))) (* |:5| (/ (- 4253115) 8388608))) (* |:7| (/ 11755105 16777216))) (* |:9| (/ 2348089 4194304))) (* |:11| (/ 11766505 16777216))) (/ (- 8711947) 134217728)))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 9041845) 67108864)) (* |:3| (/ (- 7472907) 33554432))) (* |:5| (/ 9650993 268435456))) (* |:7| (/ (- 15252035) 1073741824))) (* |:9| (/ 6924703 16777216))) (* |:11| (/ (- 3496069) 16777216))) (/ (- 8998365) 134217728)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 4912199) 8388608)) (* |:3| (/ 677045 2097152))) (* |:5| (/ (- 8260447) 16777216))) (* |:7| (/ (- 481099) 1048576))) (* |:9| (/ (- 3619967) 8388608))) (* |:11| (/ (- 5030151) 16777216))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ (- 7714595) 16777216)) (* (ite (>= |:13| 0) |:13| 0) (/ 1166761 8388608))) (* (ite (>= |:14| 0) |:14| 0) (/ 1706327 4194304))) (/ 1543007 16777216)))))))))))))))))>, 'y2_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x_scaled (/ 14333415 33554432)) (* p1_scaled (/ (- 3173377) 4194304))) (* p2_scaled (/ (- 11989195) 16777216))) (/ (- 9690501) 134217728)))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x_scaled (/ 12212227 16777216)) (* p1_scaled (/ 13212577 134217728))) (* p2_scaled (/ 16241617 134217728))) (/ 11776873 134217728)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x_scaled (/ 710205 4194304)) (* p1_scaled (/ 1014123 8388608))) (* p2_scaled (/ (- 11073897) 16777216))) (/ (- 7254327) 134217728)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x_scaled (/ 4704661 33554432)) (* p1_scaled (/ (- 6233549) 8388608))) (* p2_scaled (/ 4785015 8388608))) (/ (- 4773853) 67108864)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x_scaled (/ 12316703 16777216)) (* p1_scaled (/ 2069995 16777216))) (* p2_scaled (/ (- 335261) 524288))) (/ (- 4510373) 67108864)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 2045741 67108864)) (* |:3| (/ 9001505 33554432))) (* |:5| (/ (- 4253115) 8388608))) (* |:7| (/ 11755105 16777216))) (* |:9| (/ 2348089 4194304))) (* |:11| (/ 11766505 16777216))) (/ (- 8711947) 134217728)))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 9041845) 67108864)) (* |:3| (/ (- 7472907) 33554432))) (* |:5| (/ 9650993 268435456))) (* |:7| (/ (- 15252035) 1073741824))) (* |:9| (/ 6924703 16777216))) (* |:11| (/ (- 3496069) 16777216))) (/ (- 8998365) 134217728)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 4912199) 8388608)) (* |:3| (/ 677045 2097152))) (* |:5| (/ (- 8260447) 16777216))) (* |:7| (/ (- 481099) 1048576))) (* |:9| (/ (- 3619967) 8388608))) (* |:11| (/ (- 5030151) 16777216))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ 6139899 16777216)) (* (ite (>= |:13| 0) |:13| 0) (/ (- 12016607) 16777216))) (* (ite (>= |:14| 0) |:14| 0) (/ 8852893 8388608))) (/ 3189679 33554432)))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv new file mode 100644 index 00000000..25a6c190 --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,4.487652267232382,-0.26215220015910745 +y2,8.783304804871781,-1.4703044763701882 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv new file mode 100644 index 00000000..d7e99979 --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_nn_keras,y2_nn_keras +7,5.0,5.0,5.367882,5.3802395 +2,5.0,9.0,5.367882,5.3802395 +8,9.0,9.0,5.367882,5.3802395 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv new file mode 100644 index 00000000..f6e8a3ab --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,6.692210216292125,-0.6730525540730312 +y2,4.888843185538093,-0.30369151614349144 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv new file mode 100644 index 00000000..1575caab --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_nn_keras,y2_nn_keras +3,5.0,5.0,5.4227495,5.097694 +4,9.0,5.0,5.443091,4.8975835 +5,9.0,9.0,5.367882,5.3802395 +0,5.0,9.0,5.367882,5.3802395 +10,9.0,5.0,5.367882,5.3802395 +9,5.0,5.0,5.451473,4.94978 +6,5.0,5.0,5.367882,5.3802395 +1,9.0,9.0,5.2786703,5.4512405 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_verify_results.json new file mode 100644 index 00000000..73293bbf --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_verify_results.json @@ -0,0 +1,23 @@ +{ + "asrt_y1": { + "configuration_consistent": "skipped", + "assertion_status": "PASS", + "counter_example": null, + "assertion_feasible": true + }, + "asrt_y2": { + "configuration_consistent": "skipped", + "assertion_status": "FAIL", + "counter_example": { + "y2": 5.380239367485046, + "y1": 5.367881536483765, + "p2": 3.363086516639646, + "p1": 1.0, + "x": 4.1667309548392275 + }, + "assertion_feasible": true + }, + "smlp_execution": "completed", + "interface_consistent": "skipped", + "model_consistent": "true" +} \ No newline at end of file From fbba95ca756262c5204cbfdde232ef7b55e391bc Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 10:12:50 +0300 Subject: [PATCH 03/20] updated master files for test 62 --- .../Test62_smlp_toy_num_resp_noknobs.txt | 305 ++++++++++++++++++ ...smlp_toy_num_resp_noknobs_data_bounds.json | 22 ++ ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 714 bytes ..._noknobs_labeled_prediction_precisions.csv | 3 + ...sp_noknobs_labeled_predictions_summary.csv | 12 + ..._num_resp_noknobs_missing_values_dict.json | 8 + ...p_toy_num_resp_noknobs_model_checkpoint.h5 | Bin 0 -> 33224 bytes ..._num_resp_noknobs_model_features_dict.json | 12 + ...2_smlp_toy_num_resp_noknobs_model_gen.json | 1 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ...um_resp_noknobs_nn_keras_model_complete.h5 | Bin 0 -> 33224 bytes ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 661 bytes ...num_resp_noknobs_smlp_full_model_term.json | 1 + ..._toy_num_resp_noknobs_smlp_model_term.json | 1 + ...esp_noknobs_test_prediction_precisions.csv | 3 + ..._resp_noknobs_test_predictions_summary.csv | 4 + ...Test62_smlp_toy_num_resp_noknobs_trace.csv | 7 + ...noknobs_training_prediction_precisions.csv | 3 + ...p_noknobs_training_predictions_summary.csv | 9 + ...p_toy_num_resp_noknobs_verify_results.json | 23 ++ 20 files changed, 415 insertions(+) create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs.txt create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_data_bounds.json create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_features_scaler.pkl create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_missing_values_dict.json create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_model_checkpoint.h5 create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_model_features_dict.json create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_model_gen.json create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_model_levels_dict.json create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_nn_keras_model_complete.h5 create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_responses_scaler.pkl create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_smlp_full_model_term.json create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_smlp_model_term.json create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_trace.csv create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_verify_results.json diff --git a/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs.txt new file mode 100644 index 00000000..8a018ce0 --- /dev/null +++ b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs.txt @@ -0,0 +1,305 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt_y1: not(x25 and y1<=10) + +smlp_logger - INFO - Assertion asrt_y2: -2*y2-1<10-x2 and x2>5 and x2<8 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x0 x1 x2 y1 y2 +0 0.333333 0.0 0.0 0.0 1.0 +1 1.000000 0.0 0.2 1.0 1.0 +2 0.333333 0.5 0.2 0.0 1.0 +3 0.666667 0.0 0.6 0.0 0.0 +4 0.333333 0.0 1.0 1.0 0.0 +5 0.000000 1.0 0.8 1.0 1.0 +6 0.000000 0.5 0.6 0.0 0.0 +7 0.333333 0.5 0.2 0.0 0.0 +8 0.666667 1.0 0.2 1.0 1.0 +9 1.000000 0.0 0.8 0.0 0.0 +10 0.333333 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 3) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test62_smlp_toy_num_resp_noknobs_data_bounds.json + +smlp_logger - INFO - {'x0': {'min': 9.0, 'max': 12.0}, 'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - keras_main: start + +smlp_logger - INFO - _keras_train_multi_response: start + +smlp_logger - INFO - layers_spec_list [2.0, 1.0] + +smlp_logger - INFO - building NN model using Keras Sequential API + +smlp_logger - INFO - input layer of size 3 + +smlp_logger - INFO - dense layer of size 6 + +smlp_logger - INFO - dense layer of size 3 + +smlp_logger - INFO - output layer of size 2 + +smlp_logger - INFO - model summary: start + +smlp_logger - INFO - Model: "sequential" +_________________________________________________________________ + Layer (type) Output Shape Param # +================================================================= + dense (Dense) (None, 6) 24 + + dense_1 (Dense) (None, 3) 21 + + dense_2 (Dense) (None, 2) 8 + +================================================================= +Total params: 53 (212.00 Byte) +Trainable params: 53 (212.00 Byte) +Non-trainable params: 0 (0.00 Byte) +_________________________________________________________________ + + +smlp_logger - INFO - Optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} + +smlp_logger - INFO - Learning rate: 0.001 + +smlp_logger - INFO - Loss function: mse + +smlp_logger - INFO - Metrics: ['mse'] + +smlp_logger - INFO - Model configuration: {'name': 'sequential', 'layers': [{'module': 'keras.layers', 'class_name': 'InputLayer', 'config': {'batch_input_shape': (None, 3), 'dtype': 'float32', 'sparse': False, 'ragged': False, 'name': 'dense_input'}, 'registered_name': None}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'dense', 'trainable': True, 'dtype': 'float32', 'batch_input_shape': (None, 3), 'units': 6, 'activation': 'relu', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 3)}}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'dense_1', 'trainable': True, 'dtype': 'float32', 'units': 3, 'activation': 'relu', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 6)}}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'dense_2', 'trainable': True, 'dtype': 'float32', 'units': 2, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 3)}}]} + +smlp_logger - INFO - Epochs: 100 + +smlp_logger - INFO - Batch size: 200 + +smlp_logger - INFO - Callbacks: [""] + +smlp_logger - INFO - model summary: end + +smlp_logger - INFO - _keras_train_multi_response: end + +smlp_logger - INFO - keras_main: end + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test62_smlp_toy_num_resp_noknobs_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test62_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 5.344 + +smlp_logger - INFO - Prediction on training data -- r2_score: -0.378 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test62_smlp_toy_num_resp_noknobs_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test62_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 6.431 + +smlp_logger - INFO - Prediction on test data -- r2_score: -0.809 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test62_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test62_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 5.640 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: -0.422 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 256, 'mul': 472, 'ite': 39, 'prop': 39, 'const': 846, 'sub': 216, 'var': 216} + +smlp_logger - INFO - Model operator counts for y2: {'add': 256, 'mul': 472, 'ite': 39, 'prop': 39, 'const': 846, 'sub': 216, 'var': 216} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt_y1 <-> not(x25 and y1<=10) + +smlp_logger - INFO - The configuration is consistent with assertion asrt_y1 + +smlp_logger - INFO - Completed with result: PASS + +smlp_logger - 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33554432))) 0))) (let ((|:6| (ite (>= |:5| 0) |:5| 0))) (let ((|:7| (+ (+ (+ (* |:0| (/ 9900335 16777216)) (* |:1| (/ (- 5448211) 16777216))) (* |:2| (/ 12339293 16777216))) (/ 12035361 268435456)))) (let ((|:8| (ite (>= |:7| 0) |:7| 0))) (let ((|:9| (+ (+ (+ (* |:0| (/ 11088463 134217728)) (* |:1| (/ 211449 4194304))) (* |:2| (/ 12447363 16777216))) (/ (- 12828253) 134217728)))) (let ((|:10| (ite (>= |:9| 0) |:9| 0))) (let ((|:11| (+ (+ (+ (* |:0| (/ 10855307 67108864)) (* |:1| (/ 965293 2097152))) (* |:2| (/ (- 15015817) 268435456))) (/ 8969903 4294967296)))) (let ((|:12| (ite (>= |:11| 0) |:11| 0))) (let ((|:13| (+ (+ (+ (* |:0| (/ 1208381 2097152)) (* |:1| (/ 2938155 4194304))) (* |:2| (/ (- 10195595) 33554432))) (/ 3298773 33554432)))) (let ((|:14| (ite (>= |:13| 0) |:13| 0))) (let ((|:15| (+ (+ (+ (+ (+ (+ (* |:4| (/ 1958803 8388608)) (* |:6| (/ 3285671 8388608))) (* |:8| (/ (- 1798427) 8388608))) (* |:10| (/ (- 14391915) 33554432))) (* |:12| (/ (- 5538481) 8388608))) (* |:14| (/ (- 11806169) 33554432))) 0))) (let ((|:16| (+ (+ (+ (+ (+ (+ (* |:4| (/ 10348145 16777216)) (* |:6| (/ 2493617 16777216))) (* |:8| (/ 14212267 16777216))) (* |:10| (/ (- 5570941) 8388608))) (* |:12| (/ (- 11410359) 16777216))) (* |:14| (/ (- 15592633) 33554432))) (/ 5899637 134217728)))) (let ((|:17| (+ (+ (+ (+ (+ (+ (* |:4| (/ (- 13799583) 33554432)) (* |:6| (/ (- 214595) 4194304))) (* |:8| (/ (- 4053207) 16777216))) (* |:10| (/ 315509 8388608))) (* |:12| (/ (- 10656705) 16777216))) (* |:14| (/ 4727225 8388608))) 0))) (+ (* (+ (+ (+ (* (ite (>= |:15| 0) |:15| 0) (/ (- 4882399) 8388608)) (* (ite (>= |:16| 0) |:16| 0) (/ 4987691 8388608))) (* (ite (>= |:17| 0) |:17| 0) (/ (- 1315209) 8388608))) (/ 12647359 134217728)) 4) 5)))))))))))))))))))>, 'y2': = |:3| 0) |:3| 0))) (let ((|:5| (+ (+ (+ (* |:0| (/ (- 12675489) 16777216)) (* |:1| (/ (- 15700433) 33554432))) (* |:2| (/ (- 14143067) 33554432))) 0))) (let ((|:6| (ite (>= |:5| 0) |:5| 0))) (let ((|:7| (+ (+ (+ (* |:0| (/ 9900335 16777216)) (* |:1| (/ (- 5448211) 16777216))) (* |:2| (/ 12339293 16777216))) (/ 12035361 268435456)))) (let ((|:8| (ite (>= |:7| 0) |:7| 0))) (let ((|:9| (+ (+ (+ (* |:0| (/ 11088463 134217728)) (* |:1| (/ 211449 4194304))) (* |:2| (/ 12447363 16777216))) (/ (- 12828253) 134217728)))) (let ((|:10| (ite (>= |:9| 0) |:9| 0))) (let ((|:11| (+ (+ (+ (* |:0| (/ 10855307 67108864)) (* |:1| (/ 965293 2097152))) (* |:2| (/ (- 15015817) 268435456))) (/ 8969903 4294967296)))) (let ((|:12| (ite (>= |:11| 0) |:11| 0))) (let ((|:13| (+ (+ (+ (* |:0| (/ 1208381 2097152)) (* |:1| (/ 2938155 4194304))) (* |:2| (/ (- 10195595) 33554432))) (/ 3298773 33554432)))) (let ((|:14| (ite (>= |:13| 0) |:13| 0))) (let ((|:15| (+ (+ (+ (+ (+ (+ (* |:4| (/ 1958803 8388608)) (* |:6| (/ 3285671 8388608))) (* |:8| (/ (- 1798427) 8388608))) (* |:10| (/ (- 14391915) 33554432))) (* |:12| (/ (- 5538481) 8388608))) (* |:14| (/ (- 11806169) 33554432))) 0))) (let ((|:16| (+ (+ (+ (+ (+ (+ (* |:4| (/ 10348145 16777216)) (* |:6| (/ 2493617 16777216))) (* |:8| (/ 14212267 16777216))) (* |:10| (/ (- 5570941) 8388608))) (* |:12| (/ (- 11410359) 16777216))) (* |:14| (/ (- 15592633) 33554432))) (/ 5899637 134217728)))) (let ((|:17| (+ (+ (+ (+ (+ (+ (* |:4| (/ (- 13799583) 33554432)) (* |:6| (/ (- 214595) 4194304))) (* |:8| (/ (- 4053207) 16777216))) (* |:10| (/ 315509 8388608))) (* |:12| (/ (- 10656705) 16777216))) (* |:14| (/ 4727225 8388608))) 0))) (+ (* (+ (+ (+ (* (ite (>= |:15| 0) |:15| 0) (/ (- 4231593) 4194304)) (* (ite (>= |:16| 0) |:16| 0) (/ (- 11739661) 1073741824))) (* (ite (>= |:17| 0) |:17| 0) (/ 373001 1048576))) (/ 12626933 134217728)) 4) 5)))))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_smlp_model_term.json b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_smlp_model_term.json new file mode 100644 index 00000000..63876226 --- /dev/null +++ b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x_scaled (/ 7129195 16777216)) (* p1_scaled (/ (- 3173377) 4194304))) (* p2_scaled (/ (- 1507521) 2097152))) (/ (- 9039983) 134217728)))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x_scaled (/ 6085083 8388608)) (* p1_scaled (/ 8547843 33554432))) (* p2_scaled (/ 1156295 4194304))) (/ 5601651 67108864)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x_scaled (/ 5701855 33554432)) (* p1_scaled (/ 1014123 8388608))) (* p2_scaled (/ (- 87407) 131072))) (/ (- 9709993) 268435456)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x_scaled (/ 3941617 16777216)) (* p1_scaled (/ (- 9218095) 16777216))) (* p2_scaled (/ 6471843 8388608))) (/ 6353857 67108864)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x_scaled (/ 6298177 8388608)) (* p1_scaled (/ 2069995 16777216))) (* p2_scaled (/ (- 1381511) 2097152))) (/ (- 8020837) 268435456)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 9771097 268435456)) (* |:3| (/ 277685 1048576))) (* |:5| (/ (- 2139615) 4194304))) (* |:7| (/ 370801 524288))) (* |:9| (/ 8876881 16777216))) (* |:11| (/ 5884667 8388608))) (/ (- 578721) 8388608)))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 15143387) 268435456)) (* |:3| (/ (- 16131283) 134217728))) (* |:5| (/ 13650361 67108864))) (* |:7| (/ 9505931 268435456))) (* |:9| (/ 4875377 8388608))) (* |:11| (/ (- 5969259) 67108864))) (/ 767863 8388608)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 4912199) 8388608)) (* |:3| (/ 677045 2097152))) (* |:5| (/ (- 8260447) 16777216))) (* |:7| (/ (- 481099) 1048576))) (* |:9| (/ (- 3619967) 8388608))) (* |:11| (/ (- 5030151) 16777216))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ (- 3314721) 8388608)) (* (ite (>= |:13| 0) |:13| 0) (/ 15707487 33554432))) (* (ite (>= |:14| 0) |:14| 0) (/ (- 4204853) 8388608))) (/ 5704721 67108864)))))))))))))))))>, 'y2_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x_scaled (/ 7129195 16777216)) (* p1_scaled (/ (- 3173377) 4194304))) (* p2_scaled (/ (- 1507521) 2097152))) (/ (- 9039983) 134217728)))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x_scaled (/ 6085083 8388608)) (* p1_scaled (/ 8547843 33554432))) (* p2_scaled (/ 1156295 4194304))) (/ 5601651 67108864)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x_scaled (/ 5701855 33554432)) (* p1_scaled (/ 1014123 8388608))) (* p2_scaled (/ (- 87407) 131072))) (/ (- 9709993) 268435456)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x_scaled (/ 3941617 16777216)) (* p1_scaled (/ (- 9218095) 16777216))) (* p2_scaled (/ 6471843 8388608))) (/ 6353857 67108864)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x_scaled (/ 6298177 8388608)) (* p1_scaled (/ 2069995 16777216))) (* p2_scaled (/ (- 1381511) 2097152))) (/ (- 8020837) 268435456)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 9771097 268435456)) (* |:3| (/ 277685 1048576))) (* |:5| (/ (- 2139615) 4194304))) (* |:7| (/ 370801 524288))) (* |:9| (/ 8876881 16777216))) (* |:11| (/ 5884667 8388608))) (/ (- 578721) 8388608)))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 15143387) 268435456)) (* |:3| (/ (- 16131283) 134217728))) (* |:5| (/ 13650361 67108864))) (* |:7| (/ 9505931 268435456))) (* |:9| (/ 4875377 8388608))) (* |:11| (/ (- 5969259) 67108864))) (/ 767863 8388608)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 4912199) 8388608)) (* |:3| (/ 677045 2097152))) (* |:5| (/ (- 8260447) 16777216))) (* |:7| (/ (- 481099) 1048576))) (* |:9| (/ (- 3619967) 8388608))) (* |:11| (/ (- 5030151) 16777216))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ 4702433 33554432)) (* (ite (>= |:13| 0) |:13| 0) (/ (- 7604097) 536870912))) (* (ite (>= |:14| 0) |:14| 0) (/ 749555 1048576))) (/ 12798267 134217728)))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv new file mode 100644 index 00000000..548a4088 --- /dev/null +++ b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,4.659619170345347,-0.31051789165962873 +y2,8.202680134315264,-1.3070037877761678 diff --git a/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_test_predictions_summary.csv new file mode 100644 index 00000000..6d1abd75 --- /dev/null +++ b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_nn_keras,y2_nn_keras +7,5.0,5.0,5.3453274,5.447993 +2,5.0,9.0,5.3453274,5.447993 +8,9.0,9.0,5.2932014,5.5662575 diff --git a/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_trace.csv new file mode 100644 index 00000000..b5273590 --- /dev/null +++ b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_trace.csv @@ -0,0 +1,7 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,1,3 +model_consistency,sat,261883486167499698105216642400862340458138394084543237885/31340228987215820383455797183353559624951130557732186588,1,8688539606169875102404717560343127792337865336711965626729/1755052823284085941473524642267799338997263311233002448928,12567405957774479498123961652388806459074484532944246565515593654197303735848017/2072000657085627475393660876033817188258433515229246863924477250810420471529472,1422526987207249054062366449963394559765302063278719596268623270213357716086410281/265216084106960316850388592132328600097079489949343598582333088103733820355772416 +ca,sat,10,1,153562766297259232748364195706153/42322327018717815907958469730581,580608788002547407578679690268863/84644654037435631815916939461162,972313279725170195827177542822426133850125/181773010436010199177230173619051326078976 +ce,unsat +ca,sat,64840907984950032/10310323707469465,1,7,543958032077180794443143919398674132621/97378254207380196436658695762639585280,66964662649893619329048400007942715335429/12464416538544665143892313057617866915840 +ce,sat,10,1,5,255823182664445314955/36893488147419103232,25253694072079228291923/4722366482869645213696 diff --git a/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv new file mode 100644 index 00000000..c2d1fbd7 --- /dev/null +++ b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,5.652843508337298,-0.4132108770843246 +y2,5.034594632149151,-0.34255856857310696 diff --git a/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_training_predictions_summary.csv new file mode 100644 index 00000000..5f6b275f --- /dev/null +++ b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_nn_keras,y2_nn_keras +3,5.0,5.0,6.6467576,5.3529615 +4,9.0,5.0,6.6339836,5.3531966 +5,9.0,9.0,5.3769207,5.376312 +0,5.0,9.0,5.8426776,5.3677473 +10,9.0,5.0,5.3769207,5.376312 +9,5.0,5.0,7.063879,5.345291 +6,5.0,5.0,5.3769207,5.376312 +1,9.0,9.0,6.644639,5.3530006 diff --git a/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_verify_results.json new file mode 100644 index 00000000..8905a7bd --- /dev/null +++ b/regr_smlp/master/Test62_smlp_toy_num_resp_noknobs_verify_results.json @@ -0,0 +1,23 @@ +{ + "asrt_y1": { + "configuration_consistent": "skipped", + "assertion_status": "PASS", + "counter_example": null, + "assertion_feasible": true + }, + "asrt_y2": { + "configuration_consistent": "skipped", + "assertion_status": "FAIL", + "counter_example": { + "x0": 10.0, + "x1": 1.0, + "y1": 6.934101260423692, + "x2": 5.0, + "y2": 5.34767772973293 + }, + "assertion_feasible": true + }, + "smlp_execution": "completed", + "interface_consistent": "skipped", + "model_consistent": "true" +} \ No newline at end of file From 04599815982565095ab7a9aa735a2e1c2599ee87 Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 11:58:12 +0300 Subject: [PATCH 04/20] added Test65 and Test66 master files and test65_model master and model files --- .../Test65_smlp_toy_num_resp_noknobs.txt | 262 ++++++++++++++++++ ..._noknobs_labeled_prediction_precisions.csv | 3 + ...sp_noknobs_labeled_predictions_summary.csv | 12 + ..._num_resp_noknobs_missing_values_dict.json | 8 + ...esp_noknobs_test_prediction_precisions.csv | 3 + ..._resp_noknobs_test_predictions_summary.csv | 4 + ...noknobs_training_prediction_precisions.csv | 3 + ...p_noknobs_training_predictions_summary.csv | 9 + ...p_toy_num_resp_noknobs_verify_results.json | 23 ++ regr_smlp/master/Test66_test65_model.txt | 2 +- .../master/Test66_test65_model_trace.csv | 9 + .../Test66_test65_model_verify_results.json | 2 +- .../test65_model_smlp_full_model_term.json | 1 + .../master/test65_model_smlp_model_term.json | 2 +- .../test65_model_smlp_full_model_term.json | 1 + .../models/test65_model_smlp_model_term.json | 2 +- 16 files changed, 342 insertions(+), 4 deletions(-) create mode 100644 regr_smlp/master/Test65_smlp_toy_num_resp_noknobs.txt create mode 100644 regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_missing_values_dict.json create mode 100644 regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_verify_results.json create mode 100644 regr_smlp/master/Test66_test65_model_trace.csv create mode 100644 regr_smlp/master/test65_model_smlp_full_model_term.json create mode 100644 regr_smlp/models/test65_model_smlp_full_model_term.json diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs.txt new file mode 100644 index 00000000..39e87ea7 --- /dev/null +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs.txt @@ -0,0 +1,262 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: x0**2+y1>4.3 + +smlp_logger - INFO - Assertion asrt2: (y1+x2)/2<6 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x0 x1 x2 y1 y2 +0 0.333333 0.0 0.0 0.0 1.0 +1 1.000000 0.0 0.2 1.0 1.0 +2 0.333333 0.5 0.2 0.0 1.0 +3 0.666667 0.0 0.6 0.0 0.0 +4 0.333333 0.0 1.0 1.0 0.0 +5 0.000000 1.0 0.8 1.0 1.0 +6 0.000000 0.5 0.6 0.0 0.0 +7 0.333333 0.5 0.2 0.0 0.0 +8 0.666667 1.0 0.2 1.0 1.0 +9 1.000000 0.0 0.8 0.0 0.0 +10 0.333333 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 3) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./test65_model_data_bounds.json + +smlp_logger - INFO - {'x0': {'min': 9.0, 'max': 12.0}, 'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./test65_model_dt_sklearn_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./test65_model_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test65_smlp_toy_num_resp_noknobs_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test65_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test65_smlp_toy_num_resp_noknobs_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test65_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on test data -- r2_score: 0.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test65_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test65_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 0.727 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.817 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> x0**2+y1>4.3 + +smlp_logger - INFO - The configuration is consistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: PASS + +smlp_logger - INFO - Verifying assertion asrt2 <-> (y1+x2)/2<6 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv new file mode 100644 index 00000000..cf088bcd --- /dev/null +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv new file mode 100644 index 00000000..2cce12ec --- /dev/null +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,5.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,5.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_missing_values_dict.json b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_missing_values_dict.json new file mode 100644 index 00000000..553bfe33 --- /dev/null +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_missing_values_dict.json @@ -0,0 +1,8 @@ +{ + "x1": [ + 1 + ], + "x0": [ + 2 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv new file mode 100644 index 00000000..ec56b74c --- /dev/null +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_test_predictions_summary.csv new file mode 100644 index 00000000..3477d51d --- /dev/null +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,5.0,9.0 +2,5.0,9.0,5.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_verify_results.json new file mode 100644 index 00000000..d670b00a --- /dev/null +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_verify_results.json @@ -0,0 +1,23 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "PASS", + "counter_example": null, + "assertion_feasible": true + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x0": 0.0, + "x1": 7.0, + "y1": 9.0, + "x2": 6.000000067055225, + "y2": 9.0 + }, + "assertion_feasible": true + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test66_test65_model.txt b/regr_smlp/master/Test66_test65_model.txt index 0903f300..ee73c4f2 100644 --- a/regr_smlp/master/Test66_test65_model.txt +++ b/regr_smlp/master/Test66_test65_model.txt @@ -24,7 +24,7 @@ smlp_logger - INFO - PREPARE DATA FOR MODELING smlp_logger - INFO - LOAD TRAINED MODEL -smlp_logger - INFO - Seving model rerun configuration in file ./../models/test65_model_rerun_model_config.json +smlp_logger - INFO - Seving model rerun configuration in file ../models/test65_model_rerun_model_config.json smlp_logger - INFO - Creating model exploration base components: Start diff --git a/regr_smlp/master/Test66_test65_model_trace.csv b/regr_smlp/master/Test66_test65_model_trace.csv new file mode 100644 index 00000000..eb2af845 --- /dev/null +++ b/regr_smlp/master/Test66_test65_model_trace.csv @@ -0,0 +1,9 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,7,3 +model_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +ca,sat,0,1,6,5,5 +ce,unsat +ca,sat,0,7,671088649/134217728,5,9 +ce,sat,0,7,805306377/134217728,9,9 diff --git a/regr_smlp/master/Test66_test65_model_verify_results.json b/regr_smlp/master/Test66_test65_model_verify_results.json index 1579ae5d..d670b00a 100644 --- a/regr_smlp/master/Test66_test65_model_verify_results.json +++ b/regr_smlp/master/Test66_test65_model_verify_results.json @@ -10,7 +10,7 @@ "assertion_status": "FAIL", "counter_example": { "x0": 0.0, - "x1": 4.0, + "x1": 7.0, "y1": 9.0, "x2": 6.000000067055225, "y2": 9.0 diff --git a/regr_smlp/master/test65_model_smlp_full_model_term.json b/regr_smlp/master/test65_model_smlp_full_model_term.json new file mode 100644 index 00000000..80c624e1 --- /dev/null +++ b/regr_smlp/master/test65_model_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': |:1| (/ 44739243 67108864))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (<= |:0| (/ 23488103 33554432))) 0 (ite (and (> |:0| (/ 53687093 134217728)) (> |:2| (/ 3 4))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (> |:0| (/ 23488103 33554432))) 1 0))))) 4) 5))))>, 'y2': |:1| (/ 44739243 67108864))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (<= |:0| (/ 23488103 33554432))) 0 (ite (and (> |:0| (/ 53687093 134217728)) (> |:2| (/ 3 4))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (> |:0| (/ 23488103 33554432))) 0 0))))) 4) 5))))>}" \ No newline at end of file diff --git a/regr_smlp/master/test65_model_smlp_model_term.json b/regr_smlp/master/test65_model_smlp_model_term.json index 3c75bd69..b6732e08 100644 --- a/regr_smlp/master/test65_model_smlp_model_term.json +++ b/regr_smlp/master/test65_model_smlp_model_term.json @@ -1 +1 @@ -"{'y1_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (<= x2_scaled (/ 23488103 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (> x2_scaled (/ 23488103 33554432))) 1 0)))))>, 'y2_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (<= x2_scaled (/ 23488103 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (> x2_scaled (/ 23488103 33554432))) 0 0)))))>}" \ No newline at end of file +"{'y1_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (<= x2_scaled (/ 23488103 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (> x2_scaled (/ 23488103 33554432))) 1 0)))))>, 'y2_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (<= x2_scaled (/ 23488103 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (> x2_scaled (/ 23488103 33554432))) 0 0)))))>}" \ No newline at end of file diff --git a/regr_smlp/models/test65_model_smlp_full_model_term.json b/regr_smlp/models/test65_model_smlp_full_model_term.json new file mode 100644 index 00000000..80c624e1 --- /dev/null +++ b/regr_smlp/models/test65_model_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': |:1| (/ 44739243 67108864))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (<= |:0| (/ 23488103 33554432))) 0 (ite (and (> |:0| (/ 53687093 134217728)) (> |:2| (/ 3 4))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (> |:0| (/ 23488103 33554432))) 1 0))))) 4) 5))))>, 'y2': |:1| (/ 44739243 67108864))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (<= |:0| (/ 23488103 33554432))) 0 (ite (and (> |:0| (/ 53687093 134217728)) (> |:2| (/ 3 4))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (> |:0| (/ 23488103 33554432))) 0 0))))) 4) 5))))>}" \ No newline at end of file diff --git a/regr_smlp/models/test65_model_smlp_model_term.json b/regr_smlp/models/test65_model_smlp_model_term.json index 3c75bd69..b6732e08 100644 --- a/regr_smlp/models/test65_model_smlp_model_term.json +++ b/regr_smlp/models/test65_model_smlp_model_term.json @@ -1 +1 @@ -"{'y1_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (<= x2_scaled (/ 23488103 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (> x2_scaled (/ 23488103 33554432))) 1 0)))))>, 'y2_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (<= x2_scaled (/ 23488103 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (> x2_scaled (/ 23488103 33554432))) 0 0)))))>}" \ No newline at end of file +"{'y1_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (<= x2_scaled (/ 23488103 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (> x2_scaled (/ 23488103 33554432))) 1 0)))))>, 'y2_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (<= x2_scaled (/ 23488103 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (> x2_scaled (/ 23488103 33554432))) 0 0)))))>}" \ No newline at end of file From 47736de5e04078f944a22472b6524c809ca89f8d Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 13:40:10 +0300 Subject: [PATCH 05/20] added master for tests 67 and 68 and test67_model files in master and models --- .../Test67_smlp_toy_num_resp_noknobs.txt | 264 ++++++++++++++++++ ..._noknobs_labeled_prediction_precisions.csv | 3 + ...sp_noknobs_labeled_predictions_summary.csv | 12 + ..._num_resp_noknobs_missing_values_dict.json | 8 + ...esp_noknobs_test_prediction_precisions.csv | 3 + ..._resp_noknobs_test_predictions_summary.csv | 4 + ...Test67_smlp_toy_num_resp_noknobs_trace.csv | 9 + ...noknobs_training_prediction_precisions.csv | 3 + ...p_noknobs_training_predictions_summary.csv | 9 + ...p_toy_num_resp_noknobs_verify_results.json | 23 ++ regr_smlp/master/Test68_test67_model.txt | 2 +- .../master/Test68_test67_model_trace.csv | 9 + .../Test68_test67_model_verify_results.json | 4 +- .../test67_model_dt_sklearn_y1_tree_rules.txt | 8 + .../test67_model_dt_sklearn_y2_tree_rules.txt | 7 + .../test67_model_y1_smlp_full_model_term.json | 1 + .../test67_model_y1_smlp_model_term.json | 1 + .../test67_model_y2_smlp_full_model_term.json | 1 + .../test67_model_y2_smlp_model_term.json | 1 + .../test67_model_dt_sklearn_tree_rules.txt | 6 +- .../test67_model_dt_sklearn_y1_tree_rules.txt | 8 + .../test67_model_dt_sklearn_y2_tree_rules.txt | 7 + .../models/test67_model_smlp_model_term.json | 2 +- .../test67_model_y1_smlp_full_model_term.json | 1 + .../test67_model_y1_smlp_model_term.json | 1 + .../test67_model_y2_smlp_full_model_term.json | 1 + .../test67_model_y2_smlp_model_term.json | 1 + 27 files changed, 392 insertions(+), 7 deletions(-) create mode 100644 regr_smlp/master/Test67_smlp_toy_num_resp_noknobs.txt create mode 100644 regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_missing_values_dict.json create mode 100644 regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_trace.csv create mode 100644 regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_verify_results.json create mode 100644 regr_smlp/master/Test68_test67_model_trace.csv create mode 100644 regr_smlp/master/test67_model_dt_sklearn_y1_tree_rules.txt create mode 100644 regr_smlp/master/test67_model_dt_sklearn_y2_tree_rules.txt create mode 100644 regr_smlp/master/test67_model_y1_smlp_full_model_term.json create mode 100644 regr_smlp/master/test67_model_y1_smlp_model_term.json create mode 100644 regr_smlp/master/test67_model_y2_smlp_full_model_term.json create mode 100644 regr_smlp/master/test67_model_y2_smlp_model_term.json create mode 100644 regr_smlp/models/test67_model_dt_sklearn_y1_tree_rules.txt create mode 100644 regr_smlp/models/test67_model_dt_sklearn_y2_tree_rules.txt create mode 100644 regr_smlp/models/test67_model_y1_smlp_full_model_term.json create mode 100644 regr_smlp/models/test67_model_y1_smlp_model_term.json create mode 100644 regr_smlp/models/test67_model_y2_smlp_full_model_term.json create mode 100644 regr_smlp/models/test67_model_y2_smlp_model_term.json diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs.txt new file mode 100644 index 00000000..fc976c8f --- /dev/null +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs.txt @@ -0,0 +1,264 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: x0**2+y1>4.3 + +smlp_logger - INFO - Assertion asrt2: (y1+x2)/2<6 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x0 x1 x2 y1 y2 +0 0.333333 0.0 0.0 0.0 1.0 +1 1.000000 0.0 0.2 1.0 1.0 +2 0.333333 0.5 0.2 0.0 1.0 +3 0.666667 0.0 0.6 0.0 0.0 +4 0.333333 0.0 1.0 1.0 0.0 +5 0.000000 1.0 0.8 1.0 1.0 +6 0.000000 0.5 0.6 0.0 0.0 +7 0.333333 0.5 0.2 0.0 0.0 +8 0.666667 1.0 0.2 1.0 1.0 +9 1.000000 0.0 0.8 0.0 0.0 +10 0.333333 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 3) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./test67_model_data_bounds.json + +smlp_logger - INFO - {'x0': {'min': 9.0, 'max': 12.0}, 'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./test67_model_dt_sklearn_y1_tree_rules.txt + +smlp_logger - INFO - Writing tree rules into file ./test67_model_dt_sklearn_y2_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./test67_model_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test67_smlp_toy_num_resp_noknobs_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test67_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test67_smlp_toy_num_resp_noknobs_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test67_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 5.333 + +smlp_logger - INFO - Prediction on test data -- r2_score: -0.500 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test67_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test67_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 1.455 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.633 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 7, 'ite': 3, 'and': 3, 'prop': 6, 'const': 24, 'sub': 6, 'var': 6} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 4, 'ite': 2, 'and': 1, 'prop': 3, 'const': 14, 'sub': 3, 'var': 3} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> x0**2+y1>4.3 + +smlp_logger - INFO - The configuration is consistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: PASS + +smlp_logger - INFO - Verifying assertion asrt2 <-> (y1+x2)/2<6 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv new file mode 100644 index 00000000..2e84754b --- /dev/null +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,1.4545454545454546,0.6333333333333333 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv new file mode 100644 index 00000000..07968f7f --- /dev/null +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,5.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,5.0,9.0 +8,9.0,9.0,5.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_missing_values_dict.json b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_missing_values_dict.json new file mode 100644 index 00000000..553bfe33 --- /dev/null +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_missing_values_dict.json @@ -0,0 +1,8 @@ +{ + "x1": [ + 1 + ], + "x0": [ + 2 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv new file mode 100644 index 00000000..0a5511cf --- /dev/null +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,5.333333333333333,-0.5 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_test_predictions_summary.csv new file mode 100644 index 00000000..fec92c00 --- /dev/null +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,5.0,9.0 +2,5.0,9.0,5.0,9.0 +8,9.0,9.0,5.0,9.0 diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_trace.csv new file mode 100644 index 00000000..1c931f44 --- /dev/null +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_trace.csv @@ -0,0 +1,9 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,7,3 +model_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +ca,sat,0,1,27/4,9,5 +ce,unsat +ca,sat,0,1,1140850697/201326592,5,5 +ce,sat,0,1,7,9,5 diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_verify_results.json new file mode 100644 index 00000000..b85d3149 --- /dev/null +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_verify_results.json @@ -0,0 +1,23 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "PASS", + "counter_example": null, + "assertion_feasible": true + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x0": 0.0, + "x1": 1.0, + "y1": 9.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": true + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test68_test67_model.txt b/regr_smlp/master/Test68_test67_model.txt index 86c49469..bbdc4544 100644 --- a/regr_smlp/master/Test68_test67_model.txt +++ b/regr_smlp/master/Test68_test67_model.txt @@ -24,7 +24,7 @@ smlp_logger - INFO - PREPARE DATA FOR MODELING smlp_logger - INFO - LOAD TRAINED MODEL -smlp_logger - INFO - Seving model rerun configuration in file ./../models/test67_model_rerun_model_config.json +smlp_logger - INFO - Seving model rerun configuration in file ../models/test67_model_rerun_model_config.json smlp_logger - INFO - Creating model exploration base components: Start diff --git a/regr_smlp/master/Test68_test67_model_trace.csv b/regr_smlp/master/Test68_test67_model_trace.csv new file mode 100644 index 00000000..1c931f44 --- /dev/null +++ b/regr_smlp/master/Test68_test67_model_trace.csv @@ -0,0 +1,9 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,7,3 +model_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +ca,sat,0,1,27/4,9,5 +ce,unsat +ca,sat,0,1,1140850697/201326592,5,5 +ce,sat,0,1,7,9,5 diff --git a/regr_smlp/master/Test68_test67_model_verify_results.json b/regr_smlp/master/Test68_test67_model_verify_results.json index 1029a19f..b85d3149 100644 --- a/regr_smlp/master/Test68_test67_model_verify_results.json +++ b/regr_smlp/master/Test68_test67_model_verify_results.json @@ -10,10 +10,10 @@ "assertion_status": "FAIL", "counter_example": { "x0": 0.0, - "x1": 7.0, + "x1": 1.0, "y1": 9.0, "x2": 7.0, - "y2": 9.0 + "y2": 5.0 }, "assertion_feasible": true }, diff --git a/regr_smlp/master/test67_model_dt_sklearn_y1_tree_rules.txt b/regr_smlp/master/test67_model_dt_sklearn_y1_tree_rules.txt new file mode 100644 index 00000000..f1ff1d7a --- /dev/null +++ b/regr_smlp/master/test67_model_dt_sklearn_y1_tree_rules.txt @@ -0,0 +1,8 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.7000000178813934) and (x0 <= 0.6666666716337204) then (y1 = 1.0) | based on 3 samples +if (x2 <= 0.7000000178813934) and (x0 <= 0.8333333432674408) then (y1 = 0.0) | based on 3 samples +if (x2 > 0.7000000178813934) and (x0 > 0.6666666716337204) then (y1 = 0.0) | based on 1 samples +if (x2 <= 0.7000000178813934) and (x0 > 0.8333333432674408) then (y1 = 1.0) | based on 1 samples diff --git a/regr_smlp/master/test67_model_dt_sklearn_y2_tree_rules.txt b/regr_smlp/master/test67_model_dt_sklearn_y2_tree_rules.txt new file mode 100644 index 00000000..5015336b --- /dev/null +++ b/regr_smlp/master/test67_model_dt_sklearn_y2_tree_rules.txt @@ -0,0 +1,7 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.4000000134110451) and (x1 <= 0.75) then (y2 = 0.0) | based on 5 samples +if (x2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/master/test67_model_y1_smlp_full_model_term.json b/regr_smlp/master/test67_model_y1_smlp_full_model_term.json new file mode 100644 index 00000000..b383dbe4 --- /dev/null +++ b/regr_smlp/master/test67_model_y1_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': |:1| (/ 27962027 33554432))) 1 (ite (and (> |:0| (/ 23488103 33554432)) (> |:1| (/ 44739243 67108864))) 0 (ite (and (<= |:0| (/ 23488103 33554432)) (<= |:1| (/ 27962027 33554432))) 0 1))) 4) 5)))>}" \ No newline at end of file diff --git a/regr_smlp/master/test67_model_y1_smlp_model_term.json b/regr_smlp/master/test67_model_y1_smlp_model_term.json new file mode 100644 index 00000000..e69e78f6 --- /dev/null +++ b/regr_smlp/master/test67_model_y1_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': x0_scaled (/ 27962027 33554432))) 1 (ite (and (> x2_scaled (/ 23488103 33554432)) (> x0_scaled (/ 44739243 67108864))) 0 (ite (and (<= x2_scaled (/ 23488103 33554432)) (<= x0_scaled (/ 27962027 33554432))) 0 1)))>}" \ No newline at end of file diff --git a/regr_smlp/master/test67_model_y2_smlp_full_model_term.json b/regr_smlp/master/test67_model_y2_smlp_full_model_term.json new file mode 100644 index 00000000..cc8b6220 --- /dev/null +++ b/regr_smlp/master/test67_model_y2_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y2': |:0| (/ 53687093 134217728)) (> (* (/ 1 2) (- x1 2)) (/ 3 4))) 1 (ite (<= |:0| (/ 53687093 134217728)) 1 0)) 4) 5))>}" \ No newline at end of file diff --git a/regr_smlp/master/test67_model_y2_smlp_model_term.json b/regr_smlp/master/test67_model_y2_smlp_model_term.json new file mode 100644 index 00000000..56c332c4 --- /dev/null +++ b/regr_smlp/master/test67_model_y2_smlp_model_term.json @@ -0,0 +1 @@ +"{'y2_scaled': x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (<= x2_scaled (/ 53687093 134217728)) 1 0))>}" \ No newline at end of file diff --git a/regr_smlp/models/test67_model_dt_sklearn_tree_rules.txt b/regr_smlp/models/test67_model_dt_sklearn_tree_rules.txt index 5015336b..30a6a1be 100644 --- a/regr_smlp/models/test67_model_dt_sklearn_tree_rules.txt +++ b/regr_smlp/models/test67_model_dt_sklearn_tree_rules.txt @@ -2,6 +2,6 @@ #Number of trees: 1 #TREE 0 -if (x2 > 0.4000000134110451) and (x1 <= 0.75) then (y2 = 0.0) | based on 5 samples -if (x2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples -if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y2 = 1.0) | based on 1 samples +if (p2 > 0.4000000134110451) and (p1 <= 0.75) then (y2 = 0.0) | based on 5 samples +if (p2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples +if (p2 > 0.4000000134110451) and (p1 > 0.75) then (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/models/test67_model_dt_sklearn_y1_tree_rules.txt b/regr_smlp/models/test67_model_dt_sklearn_y1_tree_rules.txt new file mode 100644 index 00000000..f1ff1d7a --- /dev/null +++ b/regr_smlp/models/test67_model_dt_sklearn_y1_tree_rules.txt @@ -0,0 +1,8 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.7000000178813934) and (x0 <= 0.6666666716337204) then (y1 = 1.0) | based on 3 samples +if (x2 <= 0.7000000178813934) and (x0 <= 0.8333333432674408) then (y1 = 0.0) | based on 3 samples +if (x2 > 0.7000000178813934) and (x0 > 0.6666666716337204) then (y1 = 0.0) | based on 1 samples +if (x2 <= 0.7000000178813934) and (x0 > 0.8333333432674408) then (y1 = 1.0) | based on 1 samples diff --git a/regr_smlp/models/test67_model_dt_sklearn_y2_tree_rules.txt b/regr_smlp/models/test67_model_dt_sklearn_y2_tree_rules.txt new file mode 100644 index 00000000..5015336b --- /dev/null +++ b/regr_smlp/models/test67_model_dt_sklearn_y2_tree_rules.txt @@ -0,0 +1,7 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.4000000134110451) and (x1 <= 0.75) then (y2 = 0.0) | based on 5 samples +if (x2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/models/test67_model_smlp_model_term.json b/regr_smlp/models/test67_model_smlp_model_term.json index dd21c3ce..475d42a2 100644 --- a/regr_smlp/models/test67_model_smlp_model_term.json +++ b/regr_smlp/models/test67_model_smlp_model_term.json @@ -1 +1 @@ -"{'y2_scaled': x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (<= x2_scaled (/ 53687093 134217728)) 1 0))>}" \ No newline at end of file +"{'y2_scaled': p2_scaled (/ 53687093 134217728)) (> p1_scaled (/ 3 4))) 1 (ite (<= p2_scaled (/ 53687093 134217728)) 1 0))>}" \ No newline at end of file diff --git a/regr_smlp/models/test67_model_y1_smlp_full_model_term.json b/regr_smlp/models/test67_model_y1_smlp_full_model_term.json new file mode 100644 index 00000000..b383dbe4 --- /dev/null +++ b/regr_smlp/models/test67_model_y1_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': |:1| (/ 27962027 33554432))) 1 (ite (and (> |:0| (/ 23488103 33554432)) (> |:1| (/ 44739243 67108864))) 0 (ite (and (<= |:0| (/ 23488103 33554432)) (<= |:1| (/ 27962027 33554432))) 0 1))) 4) 5)))>}" \ No newline at end of file diff --git a/regr_smlp/models/test67_model_y1_smlp_model_term.json b/regr_smlp/models/test67_model_y1_smlp_model_term.json new file mode 100644 index 00000000..e69e78f6 --- /dev/null +++ b/regr_smlp/models/test67_model_y1_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': x0_scaled (/ 27962027 33554432))) 1 (ite (and (> x2_scaled (/ 23488103 33554432)) (> x0_scaled (/ 44739243 67108864))) 0 (ite (and (<= x2_scaled (/ 23488103 33554432)) (<= x0_scaled (/ 27962027 33554432))) 0 1)))>}" \ No newline at end of file diff --git a/regr_smlp/models/test67_model_y2_smlp_full_model_term.json b/regr_smlp/models/test67_model_y2_smlp_full_model_term.json new file mode 100644 index 00000000..cc8b6220 --- /dev/null +++ b/regr_smlp/models/test67_model_y2_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y2': |:0| (/ 53687093 134217728)) (> (* (/ 1 2) (- x1 2)) (/ 3 4))) 1 (ite (<= |:0| (/ 53687093 134217728)) 1 0)) 4) 5))>}" \ No newline at end of file diff --git a/regr_smlp/models/test67_model_y2_smlp_model_term.json b/regr_smlp/models/test67_model_y2_smlp_model_term.json new file mode 100644 index 00000000..56c332c4 --- /dev/null +++ b/regr_smlp/models/test67_model_y2_smlp_model_term.json @@ -0,0 +1 @@ +"{'y2_scaled': x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (<= x2_scaled (/ 53687093 134217728)) 1 0))>}" \ No newline at end of file From 489bb6132a0e02942cc8578f7e9adad54c1975aa Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 15:26:54 +0300 Subject: [PATCH 06/20] added masters for test 71 and 72 and test71_model files to masters and models --- .../Test71_smlp_toy_num_resp_noknobs.txt | 359 ++++++++++++++++++ ..._noknobs_labeled_prediction_precisions.csv | 3 + ...sp_noknobs_labeled_predictions_summary.csv | 12 + ..._num_resp_noknobs_missing_values_dict.json | 8 + ...esp_noknobs_test_prediction_precisions.csv | 3 + ..._resp_noknobs_test_predictions_summary.csv | 4 + ...Test71_smlp_toy_num_resp_noknobs_trace.csv | 6 + ...noknobs_training_prediction_precisions.csv | 3 + ...p_noknobs_training_predictions_summary.csv | 9 + ...p_toy_num_resp_noknobs_verify_results.json | 17 + regr_smlp/master/Test72_test71_model.txt | 2 +- .../master/Test72_test71_model_trace.csv | 6 + .../master/test71_model_model_checkpoint.h5 | Bin 33000 -> 33000 bytes ...test71_model_y1_nn_keras_model_complete.h5 | Bin 33000 -> 33000 bytes .../test71_model_y1_smlp_full_model_term.json | 1 + .../test71_model_y1_smlp_model_term.json | 1 + ...test71_model_y2_nn_keras_model_complete.h5 | Bin 33000 -> 33000 bytes .../test71_model_y2_smlp_full_model_term.json | 1 + .../test71_model_y2_smlp_model_term.json | 1 + .../models/test71_model_model_checkpoint.h5 | Bin 33000 -> 33000 bytes .../models/test71_model_smlp_model_term.json | 2 +- ...test71_model_y1_nn_keras_model_complete.h5 | Bin 33000 -> 33000 bytes .../test71_model_y1_smlp_full_model_term.json | 1 + .../test71_model_y1_smlp_model_term.json | 1 + ...test71_model_y2_nn_keras_model_complete.h5 | Bin 33000 -> 33000 bytes .../test71_model_y2_smlp_full_model_term.json | 1 + .../test71_model_y2_smlp_model_term.json | 1 + 27 files changed, 440 insertions(+), 2 deletions(-) create mode 100644 regr_smlp/master/Test71_smlp_toy_num_resp_noknobs.txt create mode 100644 regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_missing_values_dict.json create mode 100644 regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_trace.csv create mode 100644 regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_verify_results.json create mode 100644 regr_smlp/master/Test72_test71_model_trace.csv create mode 100644 regr_smlp/master/test71_model_y1_smlp_full_model_term.json create mode 100644 regr_smlp/master/test71_model_y1_smlp_model_term.json create mode 100644 regr_smlp/master/test71_model_y2_smlp_full_model_term.json create mode 100644 regr_smlp/master/test71_model_y2_smlp_model_term.json create mode 100644 regr_smlp/models/test71_model_y1_smlp_full_model_term.json create mode 100644 regr_smlp/models/test71_model_y1_smlp_model_term.json create mode 100644 regr_smlp/models/test71_model_y2_smlp_full_model_term.json create mode 100644 regr_smlp/models/test71_model_y2_smlp_model_term.json diff --git a/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs.txt new file mode 100644 index 00000000..267d8b07 --- /dev/null +++ b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs.txt @@ -0,0 +1,359 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: (y1**3+x2)/2<6 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x0 x1 x2 y1 y2 +0 0.333333 0.0 0.0 0.0 1.0 +1 1.000000 0.0 0.2 1.0 1.0 +2 0.333333 0.5 0.2 0.0 1.0 +3 0.666667 0.0 0.6 0.0 0.0 +4 0.333333 0.0 1.0 1.0 0.0 +5 0.000000 1.0 0.8 1.0 1.0 +6 0.000000 0.5 0.6 0.0 0.0 +7 0.333333 0.5 0.2 0.0 0.0 +8 0.666667 1.0 0.2 1.0 1.0 +9 1.000000 0.0 0.8 0.0 0.0 +10 0.333333 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 3) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./test71_model_data_bounds.json + +smlp_logger - INFO - {'x0': {'min': 9.0, 'max': 12.0}, 'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - keras_main: start + +smlp_logger - INFO - _keras_train_multi_response: start + +smlp_logger - INFO - layers_spec_list [2.0, 1.0] + +smlp_logger - INFO - building NN model using Keras Functional API + +smlp_logger - INFO - input layer of size 3 + +smlp_logger - INFO - dense layer of size 6 + +smlp_logger - INFO - dense layer of size 3 + +smlp_logger - INFO - output layer of size 1 + +smlp_logger - INFO - model summary: start + +smlp_logger - INFO - Model: "model" +_________________________________________________________________ + Layer (type) Output Shape Param # +================================================================= + input_1 (InputLayer) [(None, 3)] 0 + + dense (Dense) (None, 6) 24 + + dense_1 (Dense) (None, 3) 21 + + y1 (Dense) (None, 1) 4 + +================================================================= +Total params: 49 (196.00 Byte) +Trainable params: 49 (196.00 Byte) +Non-trainable params: 0 (0.00 Byte) +_________________________________________________________________ + + +smlp_logger - INFO - Optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} + +smlp_logger - INFO - Learning rate: 0.001 + +smlp_logger - INFO - Loss function: mse + +smlp_logger - INFO - Metrics: ['mse'] + +smlp_logger - INFO - Model configuration: {'name': 'model', 'trainable': True, 'layers': [{'module': 'keras.layers', 'class_name': 'InputLayer', 'config': {'batch_input_shape': (None, 3), 'dtype': 'float32', 'sparse': False, 'ragged': False, 'name': 'input_1'}, 'registered_name': None, 'name': 'input_1', 'inbound_nodes': []}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'dense', 'trainable': True, 'dtype': 'float32', 'units': 6, 'activation': 'relu', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 3)}, 'name': 'dense', 'inbound_nodes': [[['input_1', 0, 0, {}]]]}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'dense_1', 'trainable': True, 'dtype': 'float32', 'units': 3, 'activation': 'relu', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 6)}, 'name': 'dense_1', 'inbound_nodes': [[['dense', 0, 0, {}]]]}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'y1', 'trainable': True, 'dtype': 'float32', 'units': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 3)}, 'name': 'y1', 'inbound_nodes': [[['dense_1', 0, 0, {}]]]}], 'input_layers': [['input_1', 0, 0]], 'output_layers': [['y1', 0, 0]]} + +smlp_logger - INFO - Epochs: 20 + +smlp_logger - INFO - Batch size: 200 + +smlp_logger - INFO - Callbacks: [""] + +smlp_logger - INFO - model summary: end + +smlp_logger - INFO - _keras_train_multi_response: end + +smlp_logger - INFO - _keras_train_multi_response: start + +smlp_logger - INFO - layers_spec_list [2.0, 1.0] + +smlp_logger - INFO - building NN model using Keras Functional API + +smlp_logger - INFO - input layer of size 3 + +smlp_logger - INFO - dense layer of size 6 + +smlp_logger - INFO - dense layer of size 3 + +smlp_logger - INFO - output layer of size 1 + +smlp_logger - INFO - model summary: start + +smlp_logger - INFO - Model: "model_1" +_________________________________________________________________ + Layer (type) Output Shape Param # +================================================================= + input_2 (InputLayer) [(None, 3)] 0 + + dense_2 (Dense) (None, 6) 24 + + dense_3 (Dense) (None, 3) 21 + + y2 (Dense) (None, 1) 4 + +================================================================= +Total params: 49 (196.00 Byte) +Trainable params: 49 (196.00 Byte) +Non-trainable params: 0 (0.00 Byte) +_________________________________________________________________ + + +smlp_logger - INFO - Optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} + +smlp_logger - INFO - Learning rate: 0.001 + +smlp_logger - INFO - Loss function: mse + +smlp_logger - INFO - Metrics: ['mse'] + +smlp_logger - INFO - Model configuration: {'name': 'model_1', 'trainable': True, 'layers': [{'module': 'keras.layers', 'class_name': 'InputLayer', 'config': {'batch_input_shape': (None, 3), 'dtype': 'float32', 'sparse': False, 'ragged': False, 'name': 'input_2'}, 'registered_name': None, 'name': 'input_2', 'inbound_nodes': []}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'dense_2', 'trainable': True, 'dtype': 'float32', 'units': 6, 'activation': 'relu', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 3)}, 'name': 'dense_2', 'inbound_nodes': [[['input_2', 0, 0, {}]]]}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'dense_3', 'trainable': True, 'dtype': 'float32', 'units': 3, 'activation': 'relu', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 6)}, 'name': 'dense_3', 'inbound_nodes': [[['dense_2', 0, 0, {}]]]}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'y2', 'trainable': True, 'dtype': 'float32', 'units': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 3)}, 'name': 'y2', 'inbound_nodes': [[['dense_3', 0, 0, {}]]]}], 'input_layers': [['input_2', 0, 0]], 'output_layers': [['y2', 0, 0]]} + +smlp_logger - INFO - Epochs: 20 + +smlp_logger - INFO - Batch size: 200 + +smlp_logger - INFO - Callbacks: [""] + +smlp_logger - INFO - model summary: end + +smlp_logger - INFO - _keras_train_multi_response: end + +smlp_logger - INFO - keras_main: end + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test71_smlp_toy_num_resp_noknobs_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test71_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 10.617 + +smlp_logger - INFO - Prediction on training data -- r2_score: -1.737 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test71_smlp_toy_num_resp_noknobs_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test71_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 7.020 + +smlp_logger - INFO - Prediction on test data -- r2_score: -0.974 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test71_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test71_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 9.636 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: -1.429 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 256, 'mul': 472, 'ite': 39, 'prop': 39, 'const': 846, 'sub': 216, 'var': 216} + +smlp_logger - INFO - Model operator counts for y2: {'add': 256, 'mul': 472, 'ite': 39, 'prop': 39, 'const': 846, 'sub': 216, 'var': 216} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y1**3+x2)/2<6 + +smlp_logger - INFO - The configuration is consistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv new file mode 100644 index 00000000..b9f8b97d --- /dev/null +++ b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,9.459757099022092,-1.3846471020451525 +y2,9.812356030356097,-1.4735314159855997 diff --git a/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv new file mode 100644 index 00000000..f613999e --- /dev/null +++ b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_nn_keras,y2_nn_keras +0,5.0,9.0,4.5473785,4.5473723 +1,9.0,9.0,2.800819,2.7999172 +2,5.0,9.0,5.1303916,5.130361 +3,5.0,5.0,3.789467,3.786426 +4,9.0,5.0,5.0789886,5.0787845 +5,9.0,9.0,5.0789886,5.0787845 +6,5.0,5.0,5.0789886,5.0787845 +7,5.0,5.0,5.1303916,5.130361 +8,9.0,9.0,5.3193283,5.3193192 +9,5.0,5.0,2.9392607,2.9352548 +10,9.0,5.0,5.0789886,5.0787845 diff --git a/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_missing_values_dict.json b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_missing_values_dict.json new file mode 100644 index 00000000..553bfe33 --- /dev/null +++ b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_missing_values_dict.json @@ -0,0 +1,8 @@ +{ + "x1": [ + 1 + ], + "x0": [ + 2 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv new file mode 100644 index 00000000..fb32d32f --- /dev/null +++ b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,4.527116013680067,-0.2732513788475188 +y2,9.512836725921185,-1.6754853291653333 diff --git a/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_test_predictions_summary.csv new file mode 100644 index 00000000..181af7c0 --- /dev/null +++ b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_nn_keras,y2_nn_keras +7,5.0,5.0,5.1303916,5.130361 +2,5.0,9.0,5.1303916,5.130361 +8,9.0,9.0,5.3193283,5.3193192 diff --git a/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_trace.csv new file mode 100644 index 00000000..7bd72ced --- /dev/null +++ b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_trace.csv @@ -0,0 +1,6 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,1,3 +model_consistency,sat,335865014418181538/39045391051627415,1,7,10651411/2097152,681662925/134217728 +witness_consistency,sat,335865014418181538/39045391051627415,1,7,10651411/2097152,681662925/134217728 +ca,sat,6620280383692978272588900391513/2792544730528104800601395382730,1,149829899645819429662281060723/42962226623509304624636852042,1139036899059459709076824500537/558508946105620960120279076546,320594959794944162063971076295705147292952553/157206292597772686818588679219324560317874176 +ce,sat,335865014418181538/39045391051627415,1,7,10651411/2097152,681662925/134217728 diff --git a/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv new file mode 100644 index 00000000..f7c3418d --- /dev/null +++ b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,11.309497506025352,-1.827374376506338 +y2,9.92467576951919,-1.6465802052051175 diff --git a/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_training_predictions_summary.csv new file mode 100644 index 00000000..0a8836f5 --- /dev/null +++ b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_nn_keras,y2_nn_keras +3,5.0,5.0,3.789467,3.786426 +4,9.0,5.0,5.0789886,5.0787845 +5,9.0,9.0,5.0789886,5.0787845 +0,5.0,9.0,4.5473785,4.5473723 +10,9.0,5.0,5.0789886,5.0787845 +9,5.0,5.0,2.9392607,2.9352548 +6,5.0,5.0,5.0789886,5.0787845 +1,9.0,9.0,2.800819,2.7999172 diff --git a/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_verify_results.json new file mode 100644 index 00000000..4fd78e0c --- /dev/null +++ b/regr_smlp/master/Test71_smlp_toy_num_resp_noknobs_verify_results.json @@ -0,0 +1,17 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x0": 8.601911912575982, + "x1": 1.0, + "y1": 5.078988552093506, + "x2": 7.0, + "y2": 5.078784562647343 + }, + "assertion_feasible": true + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test72_test71_model.txt b/regr_smlp/master/Test72_test71_model.txt index 559fc640..73e18ff3 100644 --- a/regr_smlp/master/Test72_test71_model.txt +++ b/regr_smlp/master/Test72_test71_model.txt @@ -22,7 +22,7 @@ smlp_logger - INFO - PREPARE DATA FOR MODELING smlp_logger - INFO - LOAD TRAINED MODEL -smlp_logger - INFO - Seving model rerun configuration in file ./../models/test71_model_rerun_model_config.json +smlp_logger - INFO - Seving model rerun configuration in file ../models/test71_model_rerun_model_config.json smlp_logger - INFO - Creating model exploration base components: Start diff --git a/regr_smlp/master/Test72_test71_model_trace.csv b/regr_smlp/master/Test72_test71_model_trace.csv new file mode 100644 index 00000000..8505b93b --- /dev/null +++ b/regr_smlp/master/Test72_test71_model_trace.csv @@ -0,0 +1,6 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,1,3 +model_consistency,sat,335865014418181538/39045391051627415,1,7,10651411/2097152,681662925/134217728 +witness_consistency,sat,335865014418181538/39045391051627415,1,7,10651411/2097152,681662925/134217728 +ca,sat,2667259409273942388800059527240/1128310361942258882860728781499,1,7871388943134865479425804482739/2256620723884517765721457562998,43410663863828084895832108655730768149724434467026753/21313180142042565894459826814567808118043982184841216,9191496317309957574808691076171/4513241447769035531442915125996 +ce,sat,335865014418181538/39045391051627415,1,7,10651411/2097152,681662925/134217728 diff --git a/regr_smlp/master/test71_model_model_checkpoint.h5 b/regr_smlp/master/test71_model_model_checkpoint.h5 index f62b6a099ca143e717ae9088a30452d2c7aeca84..840f24be2a68b9b6d1fdc6d274883a750fa26b3e 100644 GIT binary patch delta 409 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(ite (>= |:9| 0) |:9| 0))) (let ((|:11| (+ (+ (+ (* |:0| (/ 13268843 134217728)) (* |:1| (/ 965293 2097152))) (* |:2| (/ 5006791 536870912))) (/ 329869 16777216)))) (let ((|:12| (ite (>= |:11| 0) |:11| 0))) (let ((|:13| (+ (+ (+ (* |:0| (/ 16774547 33554432)) (* |:1| (/ 2938155 4194304))) (* |:2| (/ (- 6516567) 16777216))) (/ 10549879 536870912)))) (let ((|:14| (ite (>= |:13| 0) |:13| 0))) (let ((|:15| (+ (+ (+ (+ (+ (+ (* |:4| (/ 1958803 8388608)) (* |:6| (/ 3285671 8388608))) (* |:8| (/ (- 1798427) 8388608))) (* |:10| (/ (- 14391915) 33554432))) (* |:12| (/ (- 5538481) 8388608))) (* |:14| (/ (- 11806169) 33554432))) 0))) (let ((|:16| (+ (+ (+ (+ (+ (+ (* |:4| (/ 2850953 4194304)) (* |:6| (/ 2493617 16777216))) (* |:8| (/ 13211545 16777216))) (* |:10| (/ (- 12550421) 16777216))) (* |:12| (/ (- 10076651) 16777216))) (* |:14| (/ (- 12590041) 33554432))) (/ (- 658205) 33554432)))) (let ((|:17| (+ (+ (+ (+ (+ (+ (* |:4| (/ (- 13799583) 33554432)) (* |:6| (/ (- 214595) 4194304))) (* |:8| (/ (- 4053207) 16777216))) (* |:10| (/ 315509 8388608))) (* |:12| (/ (- 10656705) 16777216))) (* |:14| (/ 4727225 8388608))) 0))) (+ (* (+ (+ (+ (* (ite (>= |:15| 0) |:15| 0) (/ (- 21323) 32768)) (* (ite (>= |:16| 0) |:16| 0) (/ (- 9302501) 8388608))) (* (ite (>= |:17| 0) |:17| 0) (/ 2984211 4194304))) (/ 165651 8388608)) 4) 5)))))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/master/test71_model_y1_smlp_model_term.json b/regr_smlp/master/test71_model_y1_smlp_model_term.json new file mode 100644 index 00000000..5535cf73 --- /dev/null +++ b/regr_smlp/master/test71_model_y1_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x0_scaled (/ (- 12675489) 16777216)) (* x1_scaled (/ (- 15700433) 33554432))) (* x2_scaled (/ (- 14143067) 33554432))) 0))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x0_scaled (/ 1386949 2097152)) (* x1_scaled (/ (- 5448211) 16777216))) (* x2_scaled (/ 1350605 2097152))) (/ (- 5256753) 268435456)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x0_scaled (/ 9167379 268435456)) (* x1_scaled (/ 211449 4194304))) (* x2_scaled (/ 6971083 8388608))) (/ 10550525 536870912)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x0_scaled (/ 13268843 134217728)) (* x1_scaled (/ 965293 2097152))) (* x2_scaled (/ 5006791 536870912))) (/ 329869 16777216)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x0_scaled (/ 16774547 33554432)) (* x1_scaled (/ 2938155 4194304))) (* x2_scaled (/ (- 6516567) 16777216))) (/ 10549879 536870912)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 1958803 8388608)) (* |:3| (/ 3285671 8388608))) (* |:5| (/ (- 1798427) 8388608))) (* |:7| (/ (- 14391915) 33554432))) (* |:9| (/ (- 5538481) 8388608))) (* |:11| (/ (- 11806169) 33554432))) 0))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ 2850953 4194304)) (* |:3| (/ 2493617 16777216))) (* |:5| (/ 13211545 16777216))) (* |:7| (/ (- 12550421) 16777216))) (* |:9| (/ (- 10076651) 16777216))) (* |:11| (/ (- 12590041) 33554432))) (/ (- 658205) 33554432)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 13799583) 33554432)) (* |:3| (/ (- 214595) 4194304))) (* |:5| (/ (- 4053207) 16777216))) (* |:7| (/ 315509 8388608))) (* |:9| (/ (- 10656705) 16777216))) (* |:11| (/ 4727225 8388608))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ (- 21323) 32768)) (* (ite (>= |:13| 0) |:13| 0) (/ (- 9302501) 8388608))) (* (ite (>= |:14| 0) |:14| 0) (/ 2984211 4194304))) (/ 165651 8388608)))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/master/test71_model_y2_nn_keras_model_complete.h5 b/regr_smlp/master/test71_model_y2_nn_keras_model_complete.h5 index f62b6a099ca143e717ae9088a30452d2c7aeca84..840f24be2a68b9b6d1fdc6d274883a750fa26b3e 100644 GIT binary patch delta 409 zcmaFS$n>I-X@dX@WAtP}7JtU2n-f{yGc!hS4&ZDMIjK1d#>Hy5Zkz8Io8J{6`r4X9R3K?#dw?POI!6&_^UCO2}5PtFyT z*t}5i2;=4q;Q(eP55|of?HD&nT;O4xJNcrDIpeX(oT|GuT7%>4*k1VUyD>#|U&PVF zdnYYfzl zf&DX`HtY*H=V=3y4Y}85lQ%il=EY(mo1%}QVAGr@2de2aCQNQr6KDBI-X@dX@pH>q$O7LzMo@xb>6EQk& zl`&aRO-Ic?bIf6mheBpZ6K%_e_xs?CeVLN-MoL&2uGOb%4jXH1;j ws3y+Ba68F*;zkk1q{$oA#2ITRpH$NqZQ8VJA4o3&*))TauSN(P*0HUR9{Qv*} diff --git a/regr_smlp/master/test71_model_y2_smlp_full_model_term.json b/regr_smlp/master/test71_model_y2_smlp_full_model_term.json new file mode 100644 index 00000000..94c17030 --- /dev/null +++ b/regr_smlp/master/test71_model_y2_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y2': = |:3| 0) |:3| 0))) (let ((|:5| (+ (+ (+ (* |:0| (/ (- 12675489) 16777216)) (* |:1| (/ (- 15700433) 33554432))) (* |:2| (/ (- 14143067) 33554432))) 0))) (let ((|:6| (ite (>= |:5| 0) |:5| 0))) (let ((|:7| (+ (+ (+ (* |:0| (/ 5547791 8388608)) (* |:1| (/ (- 5448211) 16777216))) (* |:2| (/ 2702563 4194304))) (/ (- 2628463) 134217728)))) (let ((|:8| (ite (>= |:7| 0) |:7| 0))) (let ((|:9| (+ (+ (+ (* |:0| (/ 9167453 268435456)) (* |:1| (/ 211449 4194304))) (* |:2| (/ 6968413 8388608))) (/ 5275359 268435456)))) (let ((|:10| (ite (>= |:9| 0) |:9| 0))) (let ((|:11| (+ (+ (+ (* |:0| (/ 13268893 134217728)) (* |:1| (/ 965293 2097152))) (* |:2| (/ 4836293 536870912))) (/ 10556057 536870912)))) (let ((|:12| (ite (>= |:11| 0) |:11| 0))) (let ((|:13| (+ (+ (+ (* |:0| (/ 8387941 16777216)) (* |:1| (/ 2938155 4194304))) (* |:2| (/ (- 6516551) 16777216))) (/ 10604597 536870912)))) (let ((|:14| (ite (>= |:13| 0) |:13| 0))) (let ((|:15| (+ (+ (+ (+ (+ (+ (* |:4| (/ 1958803 8388608)) (* |:6| (/ 3285671 8388608))) (* |:8| (/ (- 1798427) 8388608))) (* |:10| (/ (- 14391915) 33554432))) (* |:12| (/ (- 5538481) 8388608))) (* |:14| (/ (- 11806169) 33554432))) 0))) (let ((|:16| (+ (+ (+ (+ (+ (+ (* |:4| (/ 11402887 16777216)) (* |:6| (/ 2493617 16777216))) (* |:8| (/ 13213105 16777216))) (* |:10| (/ (- 12546881) 16777216))) (* |:12| (/ (- 5037737) 8388608))) (* |:14| (/ (- 786973) 2097152))) (/ (- 10531581) 536870912)))) (let ((|:17| (+ (+ (+ (+ (+ (+ (* |:4| (/ (- 13799583) 33554432)) (* |:6| (/ (- 214595) 4194304))) (* |:8| (/ (- 4053207) 16777216))) (* |:10| (/ 315509 8388608))) (* |:12| (/ (- 10656705) 16777216))) (* |:14| (/ 4727225 8388608))) 0))) (+ (* (+ (+ (+ (* (ite (>= |:15| 0) |:15| 0) (/ (- 21323) 32768)) (* (ite (>= |:16| 0) |:16| 0) (/ (- 4650829) 4194304))) (* (ite (>= |:17| 0) |:17| 0) (/ 2984211 4194304))) (/ 10574285 536870912)) 4) 5)))))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/master/test71_model_y2_smlp_model_term.json b/regr_smlp/master/test71_model_y2_smlp_model_term.json new file mode 100644 index 00000000..ae859b9f --- /dev/null +++ b/regr_smlp/master/test71_model_y2_smlp_model_term.json @@ -0,0 +1 @@ +"{'y2_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x0_scaled (/ (- 12675489) 16777216)) (* x1_scaled (/ (- 15700433) 33554432))) (* x2_scaled (/ (- 14143067) 33554432))) 0))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x0_scaled (/ 5547791 8388608)) (* x1_scaled (/ (- 5448211) 16777216))) (* x2_scaled (/ 2702563 4194304))) (/ (- 2628463) 134217728)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x0_scaled (/ 9167453 268435456)) (* x1_scaled (/ 211449 4194304))) (* x2_scaled (/ 6968413 8388608))) (/ 5275359 268435456)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x0_scaled (/ 13268893 134217728)) (* x1_scaled (/ 965293 2097152))) (* x2_scaled (/ 4836293 536870912))) (/ 10556057 536870912)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x0_scaled (/ 8387941 16777216)) (* x1_scaled (/ 2938155 4194304))) (* x2_scaled (/ (- 6516551) 16777216))) (/ 10604597 536870912)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 1958803 8388608)) (* |:3| (/ 3285671 8388608))) (* |:5| (/ (- 1798427) 8388608))) (* |:7| (/ (- 14391915) 33554432))) (* |:9| (/ (- 5538481) 8388608))) (* |:11| (/ (- 11806169) 33554432))) 0))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ 11402887 16777216)) (* |:3| (/ 2493617 16777216))) (* |:5| (/ 13213105 16777216))) (* |:7| (/ (- 12546881) 16777216))) (* |:9| (/ (- 5037737) 8388608))) (* |:11| (/ (- 786973) 2097152))) (/ (- 10531581) 536870912)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 13799583) 33554432)) (* |:3| (/ (- 214595) 4194304))) (* |:5| (/ (- 4053207) 16777216))) (* |:7| (/ 315509 8388608))) (* |:9| (/ (- 10656705) 16777216))) (* |:11| (/ 4727225 8388608))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ (- 21323) 32768)) (* (ite (>= |:13| 0) |:13| 0) (/ (- 4650829) 4194304))) (* (ite (>= |:14| 0) |:14| 0) (/ 2984211 4194304))) (/ 10574285 536870912)))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/models/test71_model_model_checkpoint.h5 b/regr_smlp/models/test71_model_model_checkpoint.h5 index f62b6a099ca143e717ae9088a30452d2c7aeca84..840f24be2a68b9b6d1fdc6d274883a750fa26b3e 100644 GIT binary patch delta 409 zcmaFS$n>I-X@dX@WAtP}7JtU2n-f{yGc!hS4&ZDMIjK1d#>Hy5Zkz8Io8J{6`r4X9R3K?#dw?POI!6&_^UCO2}5PtFyT z*t}5i2;=4q;Q(eP55|of?HD&nT;O4xJNcrDIpeX(oT|GuT7%>4*k1VUyD>#|U&PVF zdnYYfzl zf&DX`HtY*H=V=3y4Y}85lQ%il=EY(mo1%}QVAGr@2de2aCQNQr6KDBI-X@dX@pH>q$O7LzMo@xb>6EQk& zl`&aRO-Ic?bIf6mheBpZ6K%_e_xs?CeVLN-MoL&2uGOb%4jXH1;j ws3y+Ba68F*;zkk1q{$oA#2ITRpH$NqZQ8VJA4o3&*))TauSN(P*0HUR9{Qv*} diff --git a/regr_smlp/models/test71_model_smlp_model_term.json b/regr_smlp/models/test71_model_smlp_model_term.json index 1689b2b1..f0a5a188 100644 --- a/regr_smlp/models/test71_model_smlp_model_term.json +++ b/regr_smlp/models/test71_model_smlp_model_term.json @@ -1 +1 @@ -"{'y2_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x0_scaled (/ (- 12675489) 16777216)) (* x1_scaled (/ (- 15700433) 33554432))) (* x2_scaled (/ (- 14143067) 33554432))) 0))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x0_scaled (/ 5547791 8388608)) (* x1_scaled (/ (- 5448211) 16777216))) (* x2_scaled (/ 2702563 4194304))) (/ (- 2628463) 134217728)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x0_scaled (/ 9167453 268435456)) (* x1_scaled (/ 211449 4194304))) (* x2_scaled (/ 6968413 8388608))) (/ 5275359 268435456)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x0_scaled (/ 6634447 67108864)) (* x1_scaled (/ 965293 2097152))) (* x2_scaled (/ 4836293 536870912))) (/ 10556057 536870912)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x0_scaled (/ 8387941 16777216)) (* x1_scaled (/ 2938155 4194304))) (* x2_scaled (/ (- 6516551) 16777216))) (/ 10604597 536870912)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 1958803 8388608)) (* |:3| (/ 3285671 8388608))) (* |:5| (/ (- 1798427) 8388608))) (* |:7| (/ (- 14391915) 33554432))) (* |:9| (/ (- 5538481) 8388608))) (* |:11| (/ (- 11806169) 33554432))) 0))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ 11402887 16777216)) (* |:3| (/ 2493617 16777216))) (* |:5| (/ 13213105 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zm2&cniZDMIjK1d#>Hy5Zkz8Io8J{6`r4XAcl1DW5E> zTF&dkCuILnjAMW4^_%-1OpC6s&K(`$V^;$0Id+knA@>NBixMjQ4-}!N0$TziHox1D-Y@@n@IXZ2q>V+LX@{ zvQeJwsU|PE(bW&E10;J<=#?Fa27&0wjcWS5LSeJP`amM9C+}4gS9PDU*b2l0flJSd S;Ch);FT+)GZ2qbCJ`w;QXOct! delta 436 zcmaFS$n>I-X@dX@VX4 zva6s9uWxEeQD$;@QDQ+sYSH9+PVvb-f)cDc3QB2tlLZCEH!l%9!niqAIGC9!f^p+U zKgLB8yt4hLC2ZE+JGO6o;(|RO^OJKH?D_j=fz1NJg*FwFWmU_0effm!ABu78FTH+q z--F2uRnWYy%oYT~LMGZtHccpz}$SrJ?>W9ntNO7_h^)!s(} E0DRYsbN~PV diff --git a/regr_smlp/models/test71_model_y1_smlp_full_model_term.json b/regr_smlp/models/test71_model_y1_smlp_full_model_term.json new file mode 100644 index 00000000..3b060676 --- /dev/null +++ b/regr_smlp/models/test71_model_y1_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': = |:3| 0) |:3| 0))) (let ((|:5| (+ (+ (+ (* |:0| (/ (- 12675489) 16777216)) (* |:1| (/ (- 15700433) 33554432))) (* |:2| (/ (- 14143067) 33554432))) 0))) (let ((|:6| (ite (>= |:5| 0) |:5| 0))) (let ((|:7| (+ (+ (+ (* |:0| (/ 1386949 2097152)) (* |:1| (/ (- 5448211) 16777216))) (* |:2| (/ 1350605 2097152))) (/ (- 5256753) 268435456)))) (let ((|:8| (ite (>= |:7| 0) |:7| 0))) (let ((|:9| (+ (+ (+ (* |:0| (/ 9167379 268435456)) (* |:1| (/ 211449 4194304))) (* |:2| (/ 6971083 8388608))) (/ 10550525 536870912)))) (let ((|:10| (ite (>= |:9| 0) |:9| 0))) (let ((|:11| (+ (+ (+ (* |:0| (/ 13268843 134217728)) (* |:1| (/ 965293 2097152))) (* |:2| (/ 5006791 536870912))) (/ 329869 16777216)))) (let ((|:12| (ite (>= |:11| 0) |:11| 0))) (let ((|:13| (+ (+ (+ (* |:0| (/ 16774547 33554432)) (* |:1| (/ 2938155 4194304))) (* |:2| (/ (- 6516567) 16777216))) (/ 10549879 536870912)))) (let ((|:14| (ite (>= |:13| 0) |:13| 0))) (let ((|:15| (+ (+ (+ (+ (+ (+ (* |:4| (/ 1958803 8388608)) (* |:6| (/ 3285671 8388608))) (* |:8| (/ (- 1798427) 8388608))) (* |:10| (/ (- 14391915) 33554432))) (* |:12| (/ (- 5538481) 8388608))) (* |:14| (/ (- 11806169) 33554432))) 0))) (let ((|:16| (+ (+ (+ (+ (+ (+ (* |:4| (/ 2850953 4194304)) (* |:6| (/ 2493617 16777216))) (* |:8| (/ 13211545 16777216))) (* |:10| (/ (- 12550421) 16777216))) (* |:12| (/ (- 10076651) 16777216))) (* |:14| (/ (- 12590041) 33554432))) (/ (- 658205) 33554432)))) (let ((|:17| (+ (+ (+ (+ (+ (+ (* |:4| (/ (- 13799583) 33554432)) (* |:6| (/ (- 214595) 4194304))) (* |:8| (/ (- 4053207) 16777216))) (* |:10| (/ 315509 8388608))) (* |:12| (/ (- 10656705) 16777216))) (* |:14| (/ 4727225 8388608))) 0))) (+ (* (+ (+ (+ (* (ite (>= |:15| 0) |:15| 0) (/ (- 21323) 32768)) (* (ite (>= |:16| 0) |:16| 0) (/ (- 9302501) 8388608))) (* (ite (>= |:17| 0) |:17| 0) (/ 2984211 4194304))) (/ 165651 8388608)) 4) 5)))))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/models/test71_model_y1_smlp_model_term.json b/regr_smlp/models/test71_model_y1_smlp_model_term.json new file mode 100644 index 00000000..5535cf73 --- /dev/null +++ b/regr_smlp/models/test71_model_y1_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x0_scaled (/ (- 12675489) 16777216)) (* x1_scaled (/ (- 15700433) 33554432))) (* x2_scaled (/ (- 14143067) 33554432))) 0))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x0_scaled (/ 1386949 2097152)) (* x1_scaled (/ (- 5448211) 16777216))) (* x2_scaled (/ 1350605 2097152))) (/ (- 5256753) 268435456)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x0_scaled (/ 9167379 268435456)) (* x1_scaled (/ 211449 4194304))) (* x2_scaled (/ 6971083 8388608))) (/ 10550525 536870912)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x0_scaled (/ 13268843 134217728)) (* x1_scaled (/ 965293 2097152))) (* x2_scaled (/ 5006791 536870912))) (/ 329869 16777216)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x0_scaled (/ 16774547 33554432)) (* x1_scaled (/ 2938155 4194304))) (* x2_scaled (/ (- 6516567) 16777216))) (/ 10549879 536870912)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 1958803 8388608)) (* |:3| (/ 3285671 8388608))) (* |:5| (/ (- 1798427) 8388608))) (* |:7| (/ (- 14391915) 33554432))) (* |:9| (/ (- 5538481) 8388608))) (* |:11| (/ (- 11806169) 33554432))) 0))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ 2850953 4194304)) (* |:3| (/ 2493617 16777216))) (* |:5| (/ 13211545 16777216))) (* |:7| (/ (- 12550421) 16777216))) (* |:9| (/ (- 10076651) 16777216))) (* |:11| (/ (- 12590041) 33554432))) (/ (- 658205) 33554432)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 13799583) 33554432)) (* |:3| (/ (- 214595) 4194304))) (* |:5| (/ (- 4053207) 16777216))) (* |:7| (/ 315509 8388608))) (* |:9| (/ (- 10656705) 16777216))) (* |:11| (/ 4727225 8388608))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ (- 21323) 32768)) (* (ite (>= |:13| 0) |:13| 0) (/ (- 9302501) 8388608))) (* (ite (>= |:14| 0) |:14| 0) (/ 2984211 4194304))) (/ 165651 8388608)))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/models/test71_model_y2_nn_keras_model_complete.h5 b/regr_smlp/models/test71_model_y2_nn_keras_model_complete.h5 index f62b6a099ca143e717ae9088a30452d2c7aeca84..840f24be2a68b9b6d1fdc6d274883a750fa26b3e 100644 GIT binary patch delta 409 zcmaFS$n>I-X@dX@WAtP}7JtU2n-f{yGc!hS4&ZDMIjK1d#>Hy5Zkz8Io8J{6`r4X9R3K?#dw?POI!6&_^UCO2}5PtFyT z*t}5i2;=4q;Q(eP55|of?HD&nT;O4xJNcrDIpeX(oT|GuT7%>4*k1VUyD>#|U&PVF zdnYYfzl zf&DX`HtY*H=V=3y4Y}85lQ%il=EY(mo1%}QVAGr@2de2aCQNQr6KDBI-X@dX@pH>q$O7LzMo@xb>6EQk& zl`&aRO-Ic?bIf6mheBpZ6K%_e_xs?CeVLN-MoL&2uGOb%4jXH1;j ws3y+Ba68F*;zkk1q{$oA#2ITRpH$NqZQ8VJA4o3&*))TauSN(P*0HUR9{Qv*} diff --git a/regr_smlp/models/test71_model_y2_smlp_full_model_term.json b/regr_smlp/models/test71_model_y2_smlp_full_model_term.json new file mode 100644 index 00000000..94c17030 --- /dev/null +++ b/regr_smlp/models/test71_model_y2_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y2': = |:3| 0) |:3| 0))) (let ((|:5| (+ (+ (+ (* |:0| (/ (- 12675489) 16777216)) (* |:1| (/ (- 15700433) 33554432))) (* |:2| (/ (- 14143067) 33554432))) 0))) (let ((|:6| (ite (>= |:5| 0) |:5| 0))) (let ((|:7| (+ (+ (+ (* |:0| (/ 5547791 8388608)) (* |:1| (/ (- 5448211) 16777216))) (* |:2| (/ 2702563 4194304))) (/ (- 2628463) 134217728)))) (let ((|:8| (ite (>= |:7| 0) |:7| 0))) (let ((|:9| (+ (+ (+ (* |:0| (/ 9167453 268435456)) (* |:1| (/ 211449 4194304))) (* |:2| (/ 6968413 8388608))) (/ 5275359 268435456)))) (let ((|:10| (ite (>= |:9| 0) |:9| 0))) (let ((|:11| (+ (+ (+ (* |:0| (/ 13268893 134217728)) (* |:1| (/ 965293 2097152))) (* |:2| (/ 4836293 536870912))) (/ 10556057 536870912)))) (let ((|:12| (ite (>= |:11| 0) |:11| 0))) (let ((|:13| (+ (+ (+ (* |:0| (/ 8387941 16777216)) (* |:1| (/ 2938155 4194304))) (* |:2| (/ (- 6516551) 16777216))) (/ 10604597 536870912)))) (let ((|:14| (ite (>= |:13| 0) |:13| 0))) (let ((|:15| (+ (+ (+ (+ (+ (+ (* |:4| (/ 1958803 8388608)) (* |:6| (/ 3285671 8388608))) (* |:8| (/ (- 1798427) 8388608))) (* |:10| (/ (- 14391915) 33554432))) (* |:12| (/ (- 5538481) 8388608))) (* |:14| (/ (- 11806169) 33554432))) 0))) (let ((|:16| (+ (+ (+ (+ (+ (+ (* |:4| (/ 11402887 16777216)) (* |:6| (/ 2493617 16777216))) (* |:8| (/ 13213105 16777216))) (* |:10| (/ (- 12546881) 16777216))) (* |:12| (/ (- 5037737) 8388608))) (* |:14| (/ (- 786973) 2097152))) (/ (- 10531581) 536870912)))) (let ((|:17| (+ (+ (+ (+ (+ (+ (* |:4| (/ (- 13799583) 33554432)) (* |:6| (/ (- 214595) 4194304))) (* |:8| (/ (- 4053207) 16777216))) (* |:10| (/ 315509 8388608))) (* |:12| (/ (- 10656705) 16777216))) (* |:14| (/ 4727225 8388608))) 0))) (+ (* (+ (+ (+ (* (ite (>= |:15| 0) |:15| 0) (/ (- 21323) 32768)) (* (ite (>= |:16| 0) |:16| 0) (/ (- 4650829) 4194304))) (* (ite (>= |:17| 0) |:17| 0) (/ 2984211 4194304))) (/ 10574285 536870912)) 4) 5)))))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/models/test71_model_y2_smlp_model_term.json b/regr_smlp/models/test71_model_y2_smlp_model_term.json new file mode 100644 index 00000000..ae859b9f --- /dev/null +++ b/regr_smlp/models/test71_model_y2_smlp_model_term.json @@ -0,0 +1 @@ +"{'y2_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x0_scaled (/ (- 12675489) 16777216)) (* x1_scaled (/ (- 15700433) 33554432))) (* x2_scaled (/ (- 14143067) 33554432))) 0))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x0_scaled (/ 5547791 8388608)) (* x1_scaled (/ (- 5448211) 16777216))) (* x2_scaled (/ 2702563 4194304))) (/ (- 2628463) 134217728)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x0_scaled (/ 9167453 268435456)) (* x1_scaled (/ 211449 4194304))) (* x2_scaled (/ 6968413 8388608))) (/ 5275359 268435456)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x0_scaled (/ 13268893 134217728)) (* x1_scaled (/ 965293 2097152))) (* x2_scaled (/ 4836293 536870912))) (/ 10556057 536870912)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x0_scaled (/ 8387941 16777216)) (* x1_scaled (/ 2938155 4194304))) (* x2_scaled (/ (- 6516551) 16777216))) (/ 10604597 536870912)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 1958803 8388608)) (* |:3| (/ 3285671 8388608))) (* |:5| (/ (- 1798427) 8388608))) (* |:7| (/ (- 14391915) 33554432))) (* |:9| (/ (- 5538481) 8388608))) (* |:11| (/ (- 11806169) 33554432))) 0))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ 11402887 16777216)) (* |:3| (/ 2493617 16777216))) (* |:5| (/ 13213105 16777216))) (* |:7| (/ (- 12546881) 16777216))) (* |:9| (/ (- 5037737) 8388608))) (* |:11| (/ (- 786973) 2097152))) (/ (- 10531581) 536870912)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 13799583) 33554432)) (* |:3| (/ (- 214595) 4194304))) (* |:5| (/ (- 4053207) 16777216))) (* |:7| (/ 315509 8388608))) (* |:9| (/ (- 10656705) 16777216))) (* |:11| (/ 4727225 8388608))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ (- 21323) 32768)) (* (ite (>= |:13| 0) |:13| 0) (/ (- 4650829) 4194304))) (* (ite (>= |:14| 0) |:14| 0) (/ 2984211 4194304))) (/ 10574285 536870912)))))))))))))))))>}" \ No newline at end of file From 1e8d5defe0467d901faa06371e585b25f432d4bb Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 16:00:02 +0300 Subject: [PATCH 07/20] added masters for test 61 and test 65 trace file --- .../master/Test61_smlp_toy_num_resp_mult.txt | 248 ------------------ ...61_smlp_toy_num_resp_mult_data_bounds.json | 22 -- ...smlp_toy_num_resp_mult_features_scaler.pkl | Bin 714 -> 0 bytes ...esp_mult_labeled_prediction_precisions.csv | 3 - ..._resp_mult_labeled_predictions_summary.csv | 12 - ...toy_num_resp_mult_missing_values_dict.json | 8 - ...smlp_toy_num_resp_mult_model_checkpoint.h5 | Bin 45160 -> 0 bytes ...toy_num_resp_mult_model_features_dict.json | 12 - ...st61_smlp_toy_num_resp_mult_model_gen.json | 1 - ...p_toy_num_resp_mult_model_levels_dict.json | 1 - ...y_num_resp_mult_nn_keras_model_complete.h5 | Bin 45160 -> 0 bytes ...mlp_toy_num_resp_mult_responses_scaler.pkl | Bin 661 -> 0 bytes ...mlp_toy_num_resp_mult_smlp_model_term.json | 1 - ...m_resp_mult_test_prediction_precisions.csv | 3 - ...num_resp_mult_test_predictions_summary.csv | 4 - ...sp_mult_training_prediction_precisions.csv | 3 - ...resp_mult_training_predictions_summary.csv | 9 - ...smlp_toy_num_resp_mult_verify_results.json | 23 -- .../Test61_smlp_toy_num_resp_noknobs.txt | 175 ++++++++---- ...smlp_toy_num_resp_noknobs_data_bounds.json | 6 +- ..._noknobs_labeled_prediction_precisions.csv | 4 +- ...sp_noknobs_labeled_predictions_summary.csv | 22 +- ..._num_resp_noknobs_missing_values_dict.json | 4 +- ..._num_resp_noknobs_model_features_dict.json | 12 +- ...1_smlp_toy_num_resp_noknobs_model_gen.json | 2 +- ...num_resp_noknobs_smlp_full_model_term.json | 1 + ...esp_noknobs_test_prediction_precisions.csv | 4 +- ..._resp_noknobs_test_predictions_summary.csv | 6 +- ...Test61_smlp_toy_num_resp_noknobs_trace.csv | 7 + ...noknobs_training_prediction_precisions.csv | 4 +- ...p_noknobs_training_predictions_summary.csv | 16 +- ...p_toy_num_resp_noknobs_verify_results.json | 10 +- ...Test65_smlp_toy_num_resp_noknobs_trace.csv | 9 + 33 files changed, 181 insertions(+), 451 deletions(-) delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult.txt delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_data_bounds.json delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_features_scaler.pkl delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_labeled_predictions_summary.csv delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_missing_values_dict.json delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_model_checkpoint.h5 delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_model_features_dict.json delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_model_gen.json delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_model_levels_dict.json delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_nn_keras_model_complete.h5 delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_responses_scaler.pkl delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_smlp_model_term.json delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv delete mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_mult_verify_results.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_smlp_full_model_term.json create mode 100644 regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_trace.csv create mode 100644 regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_trace.csv diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult.txt b/regr_smlp/master/Test61_smlp_toy_num_resp_mult.txt deleted file mode 100644 index 147f3959..00000000 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_mult.txt +++ /dev/null @@ -1,248 +0,0 @@ - -smlp_logger - INFO - Model exploration specification: -{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'p1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'p2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'p1==1 or p1==4 or p1==7'} - -smlp_logger - INFO - Executing run_smlp.py script: Start - -smlp_logger - INFO - Computed spec global constraint expressions: - -smlp_logger - INFO - Global alpha : p1==1 or p1==4 or p1==7 - -smlp_logger - INFO - Global beta : None - -smlp_logger - INFO - Radii theta : {} - -smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} - -smlp_logger - INFO - Assertion asrt_y1: not(p25 and y1<=10) - -smlp_logger - INFO - Assertion asrt_y2: -2*y2-1<10-p2 and p2>5 and p2<8 - -smlp_logger - INFO - Running SMLP in mode "verify": Start - -smlp_logger - INFO - PREPARE DATA FOR MODELING - -smlp_logger - INFO - Preparing training data for modeling: start - -smlp_logger - INFO - loading training data - -smlp_logger - INFO - data summary - y1 y2 x p1 p2 -count 11.000000 11.000000 10.000000 10.000000 11.000000 -mean 6.818182 6.818182 10.400000 2.800000 5.454545 -std 2.088932 2.088932 1.074968 0.788811 1.694912 -min 5.000000 5.000000 9.000000 2.000000 3.000000 -25% 5.000000 5.000000 10.000000 2.000000 4.000000 -50% 5.000000 5.000000 10.000000 3.000000 6.000000 -75% 9.000000 9.000000 11.000000 3.000000 7.000000 -max 9.000000 9.000000 12.000000 4.000000 8.000000 - -smlp_logger - INFO - training data - categ y1 y2 x p1 p2 -0 c14 5 9 10.0 2.0 3 -1 c15 9 9 12.0 NaN 4 -2 c1 5 9 NaN 3.0 4 -3 c9 5 5 11.0 2.0 6 -4 c5 9 5 10.0 2.0 8 -5 c10 9 9 9.0 4.0 7 -6 c13 5 5 9.0 3.0 6 -7 c4 5 5 10.0 3.0 4 -8 c15 9 9 11.0 4.0 4 -9 c11 5 5 12.0 2.0 7 -10 c19 9 5 10.0 3.0 7 - -smlp_logger - INFO - training data after imputing missing values - x p1 p2 y1 y2 -0 10.0 2.0 3.0 5.0 9.0 -1 12.0 2.0 4.0 9.0 9.0 -2 10.0 3.0 4.0 5.0 9.0 -3 11.0 2.0 6.0 5.0 5.0 -4 10.0 2.0 8.0 9.0 5.0 -5 9.0 4.0 7.0 9.0 9.0 -6 9.0 3.0 6.0 5.0 5.0 -7 10.0 3.0 4.0 5.0 5.0 -8 11.0 4.0 4.0 9.0 9.0 -9 12.0 2.0 7.0 5.0 5.0 -10 10.0 3.0 7.0 9.0 5.0 - -smlp_logger - INFO - training data after encoding levels of categorical features with integers - x p1 p2 y1 y2 -0 10.0 2.0 3.0 5.0 9.0 -1 12.0 2.0 4.0 9.0 9.0 -2 10.0 3.0 4.0 5.0 9.0 -3 11.0 2.0 6.0 5.0 5.0 -4 10.0 2.0 8.0 9.0 5.0 -5 9.0 4.0 7.0 9.0 9.0 -6 9.0 3.0 6.0 5.0 5.0 -7 10.0 3.0 4.0 5.0 5.0 -8 11.0 4.0 4.0 9.0 9.0 -9 12.0 2.0 7.0 5.0 5.0 -10 10.0 3.0 7.0 9.0 5.0 - -smlp_logger - INFO - training data after scaling (normalizing) features and responses - x p1 p2 y1 y2 -0 0.333333 0.0 0.0 0.0 1.0 -1 1.000000 0.0 0.2 1.0 1.0 -2 0.333333 0.5 0.2 0.0 1.0 -3 0.666667 0.0 0.6 0.0 0.0 -4 0.333333 0.0 1.0 1.0 0.0 -5 0.000000 1.0 0.8 1.0 1.0 -6 0.000000 0.5 0.6 0.0 0.0 -7 0.333333 0.5 0.2 0.0 0.0 -8 0.666667 1.0 0.2 1.0 1.0 -9 1.000000 0.0 0.8 0.0 0.0 -10 0.333333 0.5 0.8 1.0 0.0 - -smlp_logger - INFO - Sampling from training data: start - -smlp_logger - INFO - Sampling from training data: end - -smlp_logger - INFO - X_train after sampling: (8, 3) - -smlp_logger - INFO - y_train after sampling: (8, 2) - -smlp_logger - INFO - Preparing training data for modeling: end - -smlp_logger - INFO - Saving data bounds into file:./Test61_smlp_toy_num_resp_mult_data_bounds.json - -smlp_logger - INFO - {'x': {'min': 9.0, 'max': 12.0}, 'p1': {'min': 2.0, 'max': 4.0}, 'p2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} - -smlp_logger - INFO - TRAIN MODEL - -smlp_logger - INFO - Model training: start - -smlp_logger - INFO - keras_main: start - -smlp_logger - INFO - _keras_train_multi_response: start - -smlp_logger - INFO - building NN model using Keras Functional API - -smlp_logger - INFO - layers_spec_list [1, 2.0, 1.0] - -smlp_logger - INFO - input layer of size 3 - -smlp_logger - INFO - dense layer of size 6 - -smlp_logger - INFO - dense layer of size 3 - -smlp_logger - INFO - _keras_train_multi_response: end - -smlp_logger - INFO - keras_main: end - -smlp_logger - INFO - Model training: end - -smlp_logger - INFO - PREDICT ON TRAINING DATA - -smlp_logger - INFO - Model prediction: start - -smlp_logger - INFO - Model prediction: end - -smlp_logger - INFO - Reporting prediction results: start - -smlp_logger - INFO - Saving predictions summary into file: -./Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv - -smlp_logger - INFO - Saving prediction precisions into file: -./Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv - -smlp_logger - INFO - Prediction on training data -- msqe: 5.791 - -smlp_logger - INFO - Prediction on training data -- r2_score: -0.488 - -smlp_logger - INFO - Reporting prediction results: end - -smlp_logger - INFO - PREDICT ON TEST DATA - -smlp_logger - INFO - Model prediction: start - -smlp_logger - INFO - Model prediction: end - -smlp_logger - INFO - Reporting prediction results: start - -smlp_logger - INFO - Saving predictions summary into file: -./Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv - -smlp_logger - INFO - Saving prediction precisions into file: -./Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv - -smlp_logger - INFO - Prediction on test data -- msqe: 6.635 - -smlp_logger - INFO - Prediction on test data -- r2_score: -0.866 - -smlp_logger - INFO - Reporting prediction results: end - -smlp_logger - INFO - PREDICT ON LABELED DATA - -smlp_logger - INFO - Model prediction: start - -smlp_logger - INFO - Model prediction: end - -smlp_logger - INFO - Reporting prediction results: start - -smlp_logger - INFO - Saving predictions summary into file: -./Test61_smlp_toy_num_resp_mult_labeled_predictions_summary.csv - -smlp_logger - INFO - Saving prediction precisions into file: -./Test61_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv - -smlp_logger - INFO - Prediction on labeled data -- msqe: 6.021 - -smlp_logger - INFO - Prediction on labeled data -- r2_score: -0.518 - -smlp_logger - INFO - Reporting prediction results: end - -smlp_logger - INFO - Creating model exploration base components: Start - -smlp_logger - INFO - Parsing the SPEC: Start - -smlp_logger - INFO - Parsing the SPEC: End - -smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x': {'range': 'float', 'interval': [0, 10]}, 'p1': {'range': 'float', 'interval': [0, 10]}, 'p2': {'range': 'float', 'interval': [3, 7]}} - -smlp_logger - INFO - Input bounds (alpha): {'x': {'min': 0, 'max': 10}, 'p1': {'min': 0, 'max': 10}, 'p2': {'min': 3, 'max': 7}} - -smlp_logger - INFO - Knob bounds (eta): {} - -smlp_logger - INFO - Knob grids (eta): {} - -smlp_logger - INFO - Alpha global constraints: (or (or (= p1 1) (= p1 4)) (= p1 7)) - -smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x 0) (<= x 10))) (and (>= p1 0) (<= p1 10))) (and (>= p2 3) (<= p2 7))) - -smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x 0) (<= x 10))) (and (>= p1 0) (<= p1 10))) (and (>= p2 3) (<= p2 7))) (or (or (= p1 1) (= p1 4)) (= p1 7))) - -smlp_logger - INFO - Beta global constraints: true - -smlp_logger - INFO - Eta ranges constraints: true - -smlp_logger - INFO - Eta grid constraints: true - -smlp_logger - INFO - Eta global constraints: true - -smlp_logger - INFO - Eta combined constraints: true - -smlp_logger - INFO - Creating model exploration base components: End - -smlp_logger - INFO - Input and knob interface constraints are consistent - -smlp_logger - INFO - Building model terms: Start - -smlp_logger - INFO - Building model terms: End - -smlp_logger - INFO - Model interface constraints are consistent - -smlp_logger - INFO - Verifying assertion asrt_y1 <-> not(p25 and y1<=10) - -smlp_logger - INFO - The configuration is consistent with assertion asrt_y1 - -smlp_logger - INFO - Completed with result: PASS - -smlp_logger - INFO - Verifying assertion asrt_y2 <-> -2*y2-1<10-p2 and p2>5 and p2<8 - -smlp_logger - INFO - The configuration is consistent with assertion asrt_y2 - -smlp_logger - INFO - Completed with result: FAIL - -smlp_logger - INFO - Running SMLP in mode "verify": End - -smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_data_bounds.json b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_data_bounds.json deleted file mode 100644 index c3f3c0b3..00000000 --- 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zBTfH&<}mc1%TIz3PbM=UrN$%GK9V?aWyO5@_zVI*XP158{7BMt=SS5yIHH;T+=rfh rAP%^{QRmaer&V4jmh4h(ipb*mGzP zPi`#i5(Z0XJi{Z@MQKEE7%_qvregwT&QxANXqF#LVJ@rd1h5d5O&7%;;mDx~#4(M$ zU}{)CBZe2bp@SL2QyGL9v3$xy7FnST68WSN!~q?qElU|QgRU}wSGb0{shH{v?2^b2 z!)ZWbM7=tP#XSAGCzJ>1_xqQh@+1$l9l~I7EA2ITbyMof(gGsiiX)0L*HqI~MVTUw zy}*^?oDivQ7Q{Y}=YYU2+T~cru57EE2zB&B;Nq7+E*9wO>EJ)wn+mak=EdXr`{Kqo zv|gpqdX+$j@siNL$Z97gtDS8UPj+Y4GP0JEg(NfC`)*dxSUqKRl>Kbzo-pqCRIa&c KoEa^M2F4dZ0_isZ diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_smlp_model_term.json b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_smlp_model_term.json deleted file mode 100644 index 4ec3f4c4..00000000 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_smlp_model_term.json +++ /dev/null @@ -1 +0,0 @@ -"{'y1_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x_scaled (/ 14333415 33554432)) (* p1_scaled (/ (- 3173377) 4194304))) (* p2_scaled (/ (- 11989195) 16777216))) (/ (- 9690501) 134217728)))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x_scaled (/ 12212227 16777216)) (* p1_scaled (/ 13212577 134217728))) (* p2_scaled (/ 16241617 134217728))) (/ 11776873 134217728)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x_scaled (/ 710205 4194304)) (* p1_scaled (/ 1014123 8388608))) (* p2_scaled (/ (- 11073897) 16777216))) (/ (- 7254327) 134217728)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x_scaled (/ 4704661 33554432)) (* p1_scaled (/ (- 6233549) 8388608))) (* p2_scaled (/ 4785015 8388608))) (/ (- 4773853) 67108864)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x_scaled (/ 12316703 16777216)) (* p1_scaled (/ 2069995 16777216))) (* p2_scaled (/ (- 335261) 524288))) (/ (- 4510373) 67108864)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 2045741 67108864)) (* |:3| (/ 9001505 33554432))) (* |:5| (/ (- 4253115) 8388608))) (* |:7| (/ 11755105 16777216))) (* |:9| (/ 2348089 4194304))) (* |:11| (/ 11766505 16777216))) (/ (- 8711947) 134217728)))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 9041845) 67108864)) (* |:3| (/ (- 7472907) 33554432))) (* |:5| (/ 9650993 268435456))) (* |:7| (/ (- 15252035) 1073741824))) (* |:9| (/ 6924703 16777216))) (* |:11| (/ (- 3496069) 16777216))) (/ (- 8998365) 134217728)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 4912199) 8388608)) (* |:3| (/ 677045 2097152))) (* |:5| (/ (- 8260447) 16777216))) (* |:7| (/ (- 481099) 1048576))) (* |:9| (/ (- 3619967) 8388608))) (* |:11| (/ (- 5030151) 16777216))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ (- 7714595) 16777216)) (* (ite (>= |:13| 0) |:13| 0) (/ 1166761 8388608))) (* (ite (>= |:14| 0) |:14| 0) (/ 1706327 4194304))) (/ 1543007 16777216)))))))))))))))))>, 'y2_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x_scaled (/ 14333415 33554432)) (* p1_scaled (/ (- 3173377) 4194304))) (* p2_scaled (/ (- 11989195) 16777216))) (/ (- 9690501) 134217728)))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x_scaled (/ 12212227 16777216)) (* p1_scaled (/ 13212577 134217728))) (* p2_scaled (/ 16241617 134217728))) (/ 11776873 134217728)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x_scaled (/ 710205 4194304)) (* p1_scaled (/ 1014123 8388608))) (* p2_scaled (/ (- 11073897) 16777216))) (/ (- 7254327) 134217728)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x_scaled (/ 4704661 33554432)) (* p1_scaled (/ (- 6233549) 8388608))) (* p2_scaled (/ 4785015 8388608))) (/ (- 4773853) 67108864)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x_scaled (/ 12316703 16777216)) (* p1_scaled (/ 2069995 16777216))) (* p2_scaled (/ (- 335261) 524288))) (/ (- 4510373) 67108864)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 2045741 67108864)) (* |:3| (/ 9001505 33554432))) (* |:5| (/ (- 4253115) 8388608))) (* |:7| (/ 11755105 16777216))) (* |:9| (/ 2348089 4194304))) (* |:11| (/ 11766505 16777216))) (/ (- 8711947) 134217728)))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 9041845) 67108864)) (* |:3| (/ (- 7472907) 33554432))) (* |:5| (/ 9650993 268435456))) (* |:7| (/ (- 15252035) 1073741824))) (* |:9| (/ 6924703 16777216))) (* |:11| (/ (- 3496069) 16777216))) (/ (- 8998365) 134217728)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 4912199) 8388608)) (* |:3| (/ 677045 2097152))) (* |:5| (/ (- 8260447) 16777216))) (* |:7| (/ (- 481099) 1048576))) (* |:9| (/ (- 3619967) 8388608))) (* |:11| (/ (- 5030151) 16777216))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ 6139899 16777216)) (* (ite (>= |:13| 0) |:13| 0) (/ (- 12016607) 16777216))) (* (ite (>= |:14| 0) |:14| 0) (/ 8852893 8388608))) (/ 3189679 33554432)))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv deleted file mode 100644 index 25a6c190..00000000 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv +++ /dev/null @@ -1,3 +0,0 @@ -response,msqe,r2_score -y1,4.487652267232382,-0.26215220015910745 -y2,8.783304804871781,-1.4703044763701882 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv deleted file mode 100644 index d7e99979..00000000 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv +++ /dev/null @@ -1,4 +0,0 @@ -,y1,y2,y1_nn_keras,y2_nn_keras -7,5.0,5.0,5.367882,5.3802395 -2,5.0,9.0,5.367882,5.3802395 -8,9.0,9.0,5.367882,5.3802395 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv deleted file mode 100644 index f6e8a3ab..00000000 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv +++ /dev/null @@ -1,3 +0,0 @@ -response,msqe,r2_score -y1,6.692210216292125,-0.6730525540730312 -y2,4.888843185538093,-0.30369151614349144 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv deleted file mode 100644 index 1575caab..00000000 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv +++ /dev/null @@ -1,9 +0,0 @@ -,y1,y2,y1_nn_keras,y2_nn_keras -3,5.0,5.0,5.4227495,5.097694 -4,9.0,5.0,5.443091,4.8975835 -5,9.0,9.0,5.367882,5.3802395 -0,5.0,9.0,5.367882,5.3802395 -10,9.0,5.0,5.367882,5.3802395 -9,5.0,5.0,5.451473,4.94978 -6,5.0,5.0,5.367882,5.3802395 -1,9.0,9.0,5.2786703,5.4512405 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_verify_results.json b/regr_smlp/master/Test61_smlp_toy_num_resp_mult_verify_results.json deleted file mode 100644 index 73293bbf..00000000 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_mult_verify_results.json +++ /dev/null @@ -1,23 +0,0 @@ -{ - "asrt_y1": { - "configuration_consistent": "skipped", - "assertion_status": "PASS", - "counter_example": null, - "assertion_feasible": true - }, - "asrt_y2": { - "configuration_consistent": "skipped", - "assertion_status": "FAIL", - "counter_example": { - "y2": 5.380239367485046, - "y1": 5.367881536483765, - "p2": 3.363086516639646, - "p1": 1.0, - "x": 4.1667309548392275 - }, - "assertion_feasible": true - }, - "smlp_execution": "completed", - "interface_consistent": "skipped", - "model_consistent": "true" -} \ No newline at end of file diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs.txt index 147f3959..40d27133 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs.txt +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs.txt @@ -1,12 +1,14 @@ smlp_logger - INFO - Model exploration specification: -{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'p1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'p2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'p1==1 or p1==4 or p1==7'} +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} smlp_logger - INFO - Executing run_smlp.py script: Start +smlp_logger - INFO - Running SMLP in mode "verify": Start + smlp_logger - INFO - Computed spec global constraint expressions: -smlp_logger - INFO - Global alpha : p1==1 or p1==4 or p1==7 +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 smlp_logger - INFO - Global beta : None @@ -14,11 +16,9 @@ smlp_logger - INFO - Radii theta : {} smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} -smlp_logger - INFO - Assertion asrt_y1: not(p25 and y1<=10) - -smlp_logger - INFO - Assertion asrt_y2: -2*y2-1<10-p2 and p2>5 and p2<8 +smlp_logger - INFO - Assertion asrt_y1: not(x25 and y1<=10) -smlp_logger - INFO - Running SMLP in mode "verify": Start +smlp_logger - INFO - Assertion asrt_y2: -2*y2-1<10-x2 and x2>5 and x2<8 smlp_logger - INFO - PREPARE DATA FOR MODELING @@ -27,7 +27,7 @@ smlp_logger - INFO - Preparing training data for modeling: start smlp_logger - INFO - loading training data smlp_logger - INFO - data summary - y1 y2 x p1 p2 + y1 y2 x0 x1 x2 count 11.000000 11.000000 10.000000 10.000000 11.000000 mean 6.818182 6.818182 10.400000 2.800000 5.454545 std 2.088932 2.088932 1.074968 0.788811 1.694912 @@ -38,7 +38,7 @@ min 5.000000 5.000000 9.000000 2.000000 3.000000 max 9.000000 9.000000 12.000000 4.000000 8.000000 smlp_logger - INFO - training data - categ y1 y2 x p1 p2 + categ y1 y2 x0 x1 x2 0 c14 5 9 10.0 2.0 3 1 c15 9 9 12.0 NaN 4 2 c1 5 9 NaN 3.0 4 @@ -52,35 +52,49 @@ smlp_logger - INFO - training data 10 c19 9 5 10.0 3.0 7 smlp_logger - INFO - training data after imputing missing values - x p1 p2 y1 y2 -0 10.0 2.0 3.0 5.0 9.0 -1 12.0 2.0 4.0 9.0 9.0 -2 10.0 3.0 4.0 5.0 9.0 -3 11.0 2.0 6.0 5.0 5.0 -4 10.0 2.0 8.0 9.0 5.0 -5 9.0 4.0 7.0 9.0 9.0 -6 9.0 3.0 6.0 5.0 5.0 -7 10.0 3.0 4.0 5.0 5.0 -8 11.0 4.0 4.0 9.0 9.0 -9 12.0 2.0 7.0 5.0 5.0 -10 10.0 3.0 7.0 9.0 5.0 + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 smlp_logger - INFO - training data after encoding levels of categorical features with integers - x p1 p2 y1 y2 -0 10.0 2.0 3.0 5.0 9.0 -1 12.0 2.0 4.0 9.0 9.0 -2 10.0 3.0 4.0 5.0 9.0 -3 11.0 2.0 6.0 5.0 5.0 -4 10.0 2.0 8.0 9.0 5.0 -5 9.0 4.0 7.0 9.0 9.0 -6 9.0 3.0 6.0 5.0 5.0 -7 10.0 3.0 4.0 5.0 5.0 -8 11.0 4.0 4.0 9.0 9.0 -9 12.0 2.0 7.0 5.0 5.0 -10 10.0 3.0 7.0 9.0 5.0 + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 smlp_logger - INFO - training data after scaling (normalizing) features and responses - x p1 p2 y1 y2 + x0 x1 x2 y1 y2 0 0.333333 0.0 0.0 0.0 1.0 1 1.000000 0.0 0.2 1.0 1.0 2 0.333333 0.5 0.2 0.0 1.0 @@ -103,9 +117,9 @@ smlp_logger - INFO - y_train after sampling: (8, 2) smlp_logger - INFO - Preparing training data for modeling: end -smlp_logger - INFO - Saving data bounds into file:./Test61_smlp_toy_num_resp_mult_data_bounds.json +smlp_logger - INFO - Saving data bounds into file:./Test61_smlp_toy_num_resp_noknobs_data_bounds.json -smlp_logger - INFO - {'x': {'min': 9.0, 'max': 12.0}, 'p1': {'min': 2.0, 'max': 4.0}, 'p2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} +smlp_logger - INFO - {'x0': {'min': 9.0, 'max': 12.0}, 'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} smlp_logger - INFO - TRAIN MODEL @@ -115,9 +129,9 @@ smlp_logger - INFO - keras_main: start smlp_logger - INFO - _keras_train_multi_response: start -smlp_logger - INFO - building NN model using Keras Functional API +smlp_logger - INFO - layers_spec_list [2.0, 1.0] -smlp_logger - INFO - layers_spec_list [1, 2.0, 1.0] +smlp_logger - INFO - building NN model using Keras Functional API smlp_logger - INFO - input layer of size 3 @@ -125,6 +139,51 @@ smlp_logger - INFO - dense layer of size 6 smlp_logger - INFO - dense layer of size 3 +smlp_logger - INFO - output layer of size 1 + +smlp_logger - INFO - output layer of size 1 + +smlp_logger - INFO - model summary: start + +smlp_logger - INFO - Model: "model" +__________________________________________________________________________________________________ + Layer (type) Output Shape Param # Connected to +================================================================================================== + input_1 (InputLayer) [(None, 3)] 0 [] + + dense (Dense) (None, 6) 24 ['input_1[0][0]'] + + dense_1 (Dense) (None, 3) 21 ['dense[0][0]'] + + y1 (Dense) (None, 1) 4 ['dense_1[0][0]'] + + y2 (Dense) (None, 1) 4 ['dense_1[0][0]'] + +================================================================================================== +Total params: 53 (212.00 Byte) +Trainable params: 53 (212.00 Byte) +Non-trainable params: 0 (0.00 Byte) +__________________________________________________________________________________________________ + + +smlp_logger - INFO - Optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} + +smlp_logger - INFO - Learning rate: 0.001 + +smlp_logger - INFO - Loss function: mse + +smlp_logger - INFO - Metrics: ['mse'] + +smlp_logger - INFO - Model configuration: {'name': 'model', 'trainable': True, 'layers': [{'module': 'keras.layers', 'class_name': 'InputLayer', 'config': {'batch_input_shape': (None, 3), 'dtype': 'float32', 'sparse': False, 'ragged': False, 'name': 'input_1'}, 'registered_name': None, 'name': 'input_1', 'inbound_nodes': []}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'dense', 'trainable': True, 'dtype': 'float32', 'units': 6, 'activation': 'relu', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 3)}, 'name': 'dense', 'inbound_nodes': [[['input_1', 0, 0, {}]]]}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'dense_1', 'trainable': True, 'dtype': 'float32', 'units': 3, 'activation': 'relu', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 6)}, 'name': 'dense_1', 'inbound_nodes': [[['dense', 0, 0, {}]]]}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'y1', 'trainable': True, 'dtype': 'float32', 'units': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 3)}, 'name': 'y1', 'inbound_nodes': [[['dense_1', 0, 0, {}]]]}, {'module': 'keras.layers', 'class_name': 'Dense', 'config': {'name': 'y2', 'trainable': True, 'dtype': 'float32', 'units': 1, 'activation': 'linear', 'use_bias': True, 'kernel_initializer': {'module': 'keras.initializers', 'class_name': 'GlorotUniform', 'config': {'seed': None}, 'registered_name': None}, 'bias_initializer': {'module': 'keras.initializers', 'class_name': 'Zeros', 'config': {}, 'registered_name': None}, 'kernel_regularizer': None, 'bias_regularizer': None, 'activity_regularizer': None, 'kernel_constraint': None, 'bias_constraint': None}, 'registered_name': None, 'build_config': {'input_shape': (None, 3)}, 'name': 'y2', 'inbound_nodes': [[['dense_1', 0, 0, {}]]]}], 'input_layers': [['input_1', 0, 0]], 'output_layers': [['y1', 0, 0], ['y2', 0, 0]]} + +smlp_logger - INFO - Epochs: 100 + +smlp_logger - INFO - Batch size: 200 + +smlp_logger - INFO - Callbacks: [""] + +smlp_logger - INFO - model summary: end + smlp_logger - INFO - _keras_train_multi_response: end smlp_logger - INFO - keras_main: end @@ -140,14 +199,14 @@ smlp_logger - INFO - Model prediction: end smlp_logger - INFO - Reporting prediction results: start smlp_logger - INFO - Saving predictions summary into file: -./Test61_smlp_toy_num_resp_mult_training_predictions_summary.csv +./Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv smlp_logger - INFO - Saving prediction precisions into file: -./Test61_smlp_toy_num_resp_mult_training_prediction_precisions.csv +./Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv -smlp_logger - INFO - Prediction on training data -- msqe: 5.791 +smlp_logger - INFO - Prediction on training data -- msqe: 5.824 -smlp_logger - INFO - Prediction on training data -- r2_score: -0.488 +smlp_logger - INFO - Prediction on training data -- r2_score: -0.493 smlp_logger - INFO - Reporting prediction results: end @@ -160,14 +219,14 @@ smlp_logger - INFO - Model prediction: end smlp_logger - INFO - Reporting prediction results: start smlp_logger - INFO - Saving predictions summary into file: -./Test61_smlp_toy_num_resp_mult_test_predictions_summary.csv +./Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv smlp_logger - INFO - Saving prediction precisions into file: -./Test61_smlp_toy_num_resp_mult_test_prediction_precisions.csv +./Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv -smlp_logger - INFO - Prediction on test data -- msqe: 6.635 +smlp_logger - INFO - Prediction on test data -- msqe: 5.280 -smlp_logger - INFO - Prediction on test data -- r2_score: -0.866 +smlp_logger - INFO - Prediction on test data -- r2_score: -0.485 smlp_logger - INFO - Reporting prediction results: end @@ -180,14 +239,14 @@ smlp_logger - INFO - Model prediction: end smlp_logger - INFO - Reporting prediction results: start smlp_logger - INFO - Saving predictions summary into file: -./Test61_smlp_toy_num_resp_mult_labeled_predictions_summary.csv +./Test61_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv smlp_logger - INFO - Saving prediction precisions into file: -./Test61_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv +./Test61_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv -smlp_logger - INFO - Prediction on labeled data -- msqe: 6.021 +smlp_logger - INFO - Prediction on labeled data -- msqe: 5.676 -smlp_logger - INFO - Prediction on labeled data -- r2_score: -0.518 +smlp_logger - INFO - Prediction on labeled data -- r2_score: -0.431 smlp_logger - INFO - Reporting prediction results: end @@ -197,19 +256,19 @@ smlp_logger - INFO - Parsing the SPEC: Start smlp_logger - INFO - Parsing the SPEC: End -smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x': {'range': 'float', 'interval': [0, 10]}, 'p1': {'range': 'float', 'interval': [0, 10]}, 'p2': {'range': 'float', 'interval': [3, 7]}} +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} -smlp_logger - INFO - Input bounds (alpha): {'x': {'min': 0, 'max': 10}, 'p1': {'min': 0, 'max': 10}, 'p2': {'min': 3, 'max': 7}} +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} smlp_logger - INFO - Knob bounds (eta): {} smlp_logger - INFO - Knob grids (eta): {} -smlp_logger - INFO - Alpha global constraints: (or (or (= p1 1) (= p1 4)) (= p1 7)) +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) -smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x 0) (<= x 10))) (and (>= p1 0) (<= p1 10))) (and (>= p2 3) (<= p2 7))) +smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) -smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x 0) (<= x 10))) (and (>= p1 0) (<= p1 10))) (and (>= p2 3) (<= p2 7))) (or (or (= p1 1) (= p1 4)) (= p1 7))) +smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) smlp_logger - INFO - Beta global constraints: true @@ -227,17 +286,21 @@ smlp_logger - INFO - Input and knob interface constraints are consistent smlp_logger - INFO - Building model terms: Start +smlp_logger - INFO - Model operator counts for y1: {'add': 256, 'mul': 472, 'ite': 39, 'prop': 39, 'const': 846, 'sub': 216, 'var': 216} + +smlp_logger - INFO - Model operator counts for y2: {'add': 256, 'mul': 472, 'ite': 39, 'prop': 39, 'const': 846, 'sub': 216, 'var': 216} + smlp_logger - INFO - Building model terms: End smlp_logger - INFO - Model interface constraints are consistent -smlp_logger - INFO - Verifying assertion asrt_y1 <-> not(p25 and y1<=10) +smlp_logger - INFO - Verifying assertion asrt_y1 <-> not(x25 and y1<=10) smlp_logger - INFO - The configuration is consistent with assertion asrt_y1 smlp_logger - INFO - Completed with result: PASS -smlp_logger - INFO - Verifying assertion asrt_y2 <-> -2*y2-1<10-p2 and p2>5 and p2<8 +smlp_logger - INFO - Verifying assertion asrt_y2 <-> -2*y2-1<10-x2 and x2>5 and x2<8 smlp_logger - INFO - The configuration is consistent with assertion asrt_y2 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_data_bounds.json b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_data_bounds.json index c3f3c0b3..5df59662 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_data_bounds.json +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_data_bounds.json @@ -1,13 +1,13 @@ { - "x": { + "x0": { "min": 9.0, "max": 12.0 }, - "p1": { + "x1": { "min": 2.0, "max": 4.0 }, - "p2": { + "x2": { "min": 3.0, "max": 8.0 }, diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv index 87fd7929..b86651fc 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv @@ -1,3 +1,3 @@ response,msqe,r2_score -y1,6.090967139275832,-0.5354312996924493 -y2,5.950969081720007,-0.5001401226835853 +y1,6.276045441340474,-0.5820864550045779 +y2,5.07613741261209,-0.27960963942929795 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv index 8209ec28..219f12ea 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv @@ -1,12 +1,12 @@ ,y1,y2,y1_nn_keras,y2_nn_keras -0,5.0,9.0,5.367882,5.3802395 -1,9.0,9.0,5.2786703,5.4512405 -2,5.0,9.0,5.367882,5.3802395 -3,5.0,5.0,5.4227495,5.097694 -4,9.0,5.0,5.443091,4.8975835 -5,9.0,9.0,5.367882,5.3802395 -6,5.0,5.0,5.367882,5.3802395 -7,5.0,5.0,5.367882,5.3802395 -8,9.0,9.0,5.367882,5.3802395 -9,5.0,5.0,5.451473,4.94978 -10,9.0,5.0,5.367882,5.3802395 +0,5.0,9.0,5.342773,5.4558725 +1,9.0,9.0,4.8616014,5.949031 +2,5.0,9.0,5.4982963,5.6901507 +3,5.0,5.0,5.342773,5.4558725 +4,9.0,5.0,5.342773,5.4558725 +5,9.0,9.0,5.342773,5.4558725 +6,5.0,5.0,5.342773,5.4558725 +7,5.0,5.0,5.4982963,5.6901507 +8,9.0,9.0,5.7109795,6.0105333 +9,5.0,5.0,5.342773,5.4558725 +10,9.0,5.0,5.342773,5.4558725 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_missing_values_dict.json b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_missing_values_dict.json index 922efaec..553bfe33 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_missing_values_dict.json +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_missing_values_dict.json @@ -1,8 +1,8 @@ { - "p1": [ + "x1": [ 1 ], - "x": [ + "x0": [ 2 ] } \ No newline at end of file diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_features_dict.json b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_features_dict.json index 8f402da5..8e6a1c9a 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_features_dict.json +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_features_dict.json @@ -1,12 +1,12 @@ { "y1": [ - "x", - "p1", - "p2" + "x0", + "x1", + "x2" ], "y2": [ - "x", - "p1", - "p2" + "x0", + "x1", + "x2" ] } \ No newline at end of file diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_gen.json b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_gen.json index ccb9f7b2..18ffb149 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_gen.json +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_model_gen.json @@ -1 +1 @@ -{"train": {"epochs": 100, "batch-size": 200, "optimizer": "adam", "hid_activation": "relu", "out_activation": "linear", "seed": 10}} \ No newline at end of file +{"train": {"layers": "2,1", "epochs": 100, "batch-size": 200, "optimizer": "adam", "learning_rate": 0.001, "loss_function": "mse", "hid_activation": "relu", "out_activation": "linear", "sequential_api": false, "seed": 10}} \ No newline at end of file diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_smlp_full_model_term.json b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_smlp_full_model_term.json new file mode 100644 index 00000000..1e427884 --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': = |:3| 0) |:3| 0))) (let ((|:5| (+ (+ (+ (* |:0| (/ (- 12675489) 16777216)) (* |:1| (/ (- 15700433) 33554432))) (* |:2| (/ (- 14143067) 33554432))) 0))) (let ((|:6| (ite (>= |:5| 0) |:5| 0))) (let ((|:7| (+ (+ (+ (* |:0| (/ 10432239 16777216)) (* |:1| (/ (- 5448211) 16777216))) (* |:2| (/ 10235885 16777216))) (/ (- 7545327) 134217728)))) (let ((|:8| (ite (>= |:7| 0) |:7| 0))) (let ((|:9| (+ (+ (+ (* |:0| (/ 634497 8388608)) (* |:1| (/ 211449 4194304))) (* |:2| (/ 14539073 16777216))) (/ 15597927 268435456)))) (let ((|:10| (ite (>= |:9| 0) |:9| 0))) (let ((|:11| (+ (+ (+ (* |:0| (/ 73847 524288)) (* |:1| (/ 965293 2097152))) (* |:2| (/ 12164893 268435456))) (/ 7862711 134217728)))) (let ((|:12| (ite (>= |:11| 0) |:11| 0))) (let ((|:13| (+ (+ (+ (* |:0| (/ 9113453 16777216)) (* |:1| (/ 2938155 4194304))) (* |:2| (/ (- 5855175) 16777216))) (/ 8139523 134217728)))) (let ((|:14| (ite (>= |:13| 0) |:13| 0))) (let ((|:15| (+ (+ (+ (+ (+ (+ (* |:4| (/ 1958803 8388608)) (* |:6| (/ 3285671 8388608))) (* |:8| (/ (- 1798427) 8388608))) (* |:10| (/ (- 14391915) 33554432))) (* |:12| (/ (- 5538481) 8388608))) (* |:14| (/ (- 11806169) 33554432))) 0))) (let ((|:16| (+ (+ (+ (+ (+ (+ (* |:4| (/ 2695065 4194304)) (* |:6| (/ 2493617 16777216))) (* |:8| (/ 12598207 16777216))) (* |:10| (/ (- 13203831) 16777216))) (* |:12| (/ (- 2752055) 4194304))) (* |:14| (/ (- 14256635) 33554432))) (/ (- 15332351) 268435456)))) (let ((|:17| (+ (+ (+ (+ (+ (+ (* |:4| (/ (- 13799583) 33554432)) (* |:6| (/ (- 214595) 4194304))) (* |:8| (/ (- 4053207) 16777216))) (* |:10| (/ 315509 8388608))) (* |:12| (/ (- 10656705) 16777216))) (* |:14| (/ 4727225 8388608))) 0))) (+ (* (+ (+ (+ (* (ite (>= |:15| 0) |:15| 0) (/ (- 21323) 32768)) (* (ite (>= |:16| 0) |:16| 0) (/ (- 1127807) 1048576))) (* (ite (>= |:17| 0) |:17| 0) (/ 2984211 4194304))) (/ 11501553 134217728)) 4) 5)))))))))))))))))))>, 'y2': = |:3| 0) |:3| 0))) (let ((|:5| (+ (+ (+ (* |:0| (/ (- 12675489) 16777216)) (* |:1| (/ (- 15700433) 33554432))) (* |:2| (/ (- 14143067) 33554432))) 0))) (let ((|:6| (ite (>= |:5| 0) |:5| 0))) (let ((|:7| (+ (+ (+ (* |:0| (/ 10432239 16777216)) (* |:1| (/ (- 5448211) 16777216))) (* |:2| (/ 10235885 16777216))) (/ (- 7545327) 134217728)))) (let ((|:8| (ite (>= |:7| 0) |:7| 0))) (let ((|:9| (+ (+ (+ (* |:0| (/ 634497 8388608)) (* |:1| (/ 211449 4194304))) (* |:2| (/ 14539073 16777216))) (/ 15597927 268435456)))) (let ((|:10| (ite (>= |:9| 0) |:9| 0))) (let ((|:11| (+ (+ (+ (* |:0| (/ 73847 524288)) (* |:1| (/ 965293 2097152))) (* |:2| (/ 12164893 268435456))) (/ 7862711 134217728)))) (let ((|:12| (ite (>= |:11| 0) |:11| 0))) (let ((|:13| (+ (+ (+ (* |:0| (/ 9113453 16777216)) (* |:1| (/ 2938155 4194304))) (* |:2| (/ (- 5855175) 16777216))) (/ 8139523 134217728)))) (let ((|:14| (ite (>= |:13| 0) |:13| 0))) (let ((|:15| (+ (+ (+ (+ (+ (+ (* |:4| (/ 1958803 8388608)) (* |:6| (/ 3285671 8388608))) (* |:8| (/ (- 1798427) 8388608))) (* |:10| (/ (- 14391915) 33554432))) (* |:12| (/ (- 5538481) 8388608))) (* |:14| (/ (- 11806169) 33554432))) 0))) (let ((|:16| (+ (+ (+ (+ (+ (+ (* |:4| (/ 2695065 4194304)) (* |:6| (/ 2493617 16777216))) (* |:8| (/ 12598207 16777216))) (* |:10| (/ (- 13203831) 16777216))) (* |:12| (/ (- 2752055) 4194304))) (* |:14| (/ (- 14256635) 33554432))) (/ (- 15332351) 268435456)))) (let ((|:17| (+ (+ (+ (+ (+ (+ (* |:4| (/ (- 13799583) 33554432)) (* |:6| (/ (- 214595) 4194304))) (* |:8| (/ (- 4053207) 16777216))) (* |:10| (/ 315509 8388608))) (* |:12| (/ (- 10656705) 16777216))) (* |:14| (/ 4727225 8388608))) 0))) (+ (* (+ (+ (+ (* (ite (>= |:15| 0) |:15| 0) (/ (- 1922803) 4194304)) (* (ite (>= |:16| 0) |:16| 0) (/ 9247207 8388608))) (* (ite (>= |:17| 0) |:17| 0) (/ 8990739 8388608))) (/ 15296551 134217728)) 4) 5)))))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv index 25a6c190..2c6d8bc4 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -1,3 +1,3 @@ response,msqe,r2_score -y1,4.487652267232382,-0.26215220015910745 -y2,8.783304804871781,-1.4703044763701882 +y1,3.77141814289295,-0.06071135268864225 +y2,6.789440377906885,-0.9095301062863115 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv index d7e99979..107ed38e 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -1,4 +1,4 @@ ,y1,y2,y1_nn_keras,y2_nn_keras -7,5.0,5.0,5.367882,5.3802395 -2,5.0,9.0,5.367882,5.3802395 -8,9.0,9.0,5.367882,5.3802395 +7,5.0,5.0,5.4982963,5.6901507 +2,5.0,9.0,5.4982963,5.6901507 +8,9.0,9.0,5.7109795,6.0105333 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_trace.csv new file mode 100644 index 00000000..05070776 --- /dev/null +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_trace.csv @@ -0,0 +1,7 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,1,3 +model_consistency,sat,518763182342818807/59767095804418640,1,7,179273713/33554432,183068711/33554432 +ca,sat,676369427545304779759800936665/71922027751977055989612412928,1,1314087680626428725153770109981/287688111007908223958449651712,179273713/33554432,183068711/33554432 +ce,unsat +ca,sat,725886971/84503260,1,7,179273713/33554432,183068711/33554432 +ce,sat,139131163646518853343267/14978445805719660789760,1,7358368615260560938285/1497844580571966078976,179273713/33554432,183068711/33554432 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv index f6e8a3ab..d398630f 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -1,3 +1,3 @@ response,msqe,r2_score -y1,6.692210216292125,-0.6730525540730312 -y2,4.888843185538093,-0.30369151614349144 +y1,7.215280678258296,-0.8038201695645739 +y2,4.433648800626543,-0.1823063468337447 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv index 1575caab..9a705e18 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -1,9 +1,9 @@ ,y1,y2,y1_nn_keras,y2_nn_keras -3,5.0,5.0,5.4227495,5.097694 -4,9.0,5.0,5.443091,4.8975835 -5,9.0,9.0,5.367882,5.3802395 -0,5.0,9.0,5.367882,5.3802395 -10,9.0,5.0,5.367882,5.3802395 -9,5.0,5.0,5.451473,4.94978 -6,5.0,5.0,5.367882,5.3802395 -1,9.0,9.0,5.2786703,5.4512405 +3,5.0,5.0,5.342773,5.4558725 +4,9.0,5.0,5.342773,5.4558725 +5,9.0,9.0,5.342773,5.4558725 +0,5.0,9.0,5.342773,5.4558725 +10,9.0,5.0,5.342773,5.4558725 +9,5.0,5.0,5.342773,5.4558725 +6,5.0,5.0,5.342773,5.4558725 +1,9.0,9.0,4.8616014,5.949031 diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_verify_results.json index 73293bbf..fd37778a 100644 --- a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_verify_results.json +++ b/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_verify_results.json @@ -9,11 +9,11 @@ "configuration_consistent": "skipped", "assertion_status": "FAIL", "counter_example": { - "y2": 5.380239367485046, - "y1": 5.367881536483765, - "p2": 3.363086516639646, - "p1": 1.0, - "x": 4.1667309548392275 + "x0": 9.288758356583985, + "x1": 1.0, + "y1": 5.342772990465164, + "x2": 4.912638274159725, + "y2": 5.455872744321823 }, "assertion_feasible": true }, diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_trace.csv new file mode 100644 index 00000000..eb2af845 --- /dev/null +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_trace.csv @@ -0,0 +1,9 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,7,3 +model_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +ca,sat,0,1,6,5,5 +ce,unsat +ca,sat,0,7,671088649/134217728,5,9 +ce,sat,0,7,805306377/134217728,9,9 From 7e6e4c4425c07ea7c31f9a81c82aa476c818234f Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 17:16:56 +0300 Subject: [PATCH 08/20] added masters for test 73 and 74 and masters and models for test73_model files --- ...smlp_toy_num_resp_noknobs_pred_labeled.txt | 392 ++++++++++++++++++ ..._labeled_labeled_prediction_precisions.csv | 3 + ...ed_labeled_labeled_predictions_summary.csv | 12 + ...nobs_pred_labeled_missing_values_dict.json | 5 + ...pred_labeled_new_prediction_precisions.csv | 3 + ...s_pred_labeled_new_predictions_summary.csv | 10 + ...red_labeled_test_prediction_precisions.csv | 3 + ..._pred_labeled_test_predictions_summary.csv | 4 + ...oy_num_resp_noknobs_pred_labeled_trace.csv | 12 + ...labeled_training_prediction_precisions.csv | 3 + ...d_labeled_training_predictions_summary.csv | 9 + ...p_noknobs_pred_labeled_verify_results.json | 38 ++ ...smlp_toy_num_resp_noknobs_pred_labeled.txt | 207 +++++++++ ...nobs_pred_labeled_missing_values_dict.json | 5 + ...pred_labeled_new_prediction_precisions.csv | 3 + ...s_pred_labeled_new_predictions_summary.csv | 10 + ...oy_num_resp_noknobs_pred_labeled_trace.csv | 12 + ...p_noknobs_pred_labeled_verify_results.json | 38 ++ .../test73_model_dt_sklearn_y1_tree_rules.txt | 10 + .../test73_model_dt_sklearn_y2_tree_rules.txt | 7 + .../test73_model_y1_smlp_full_model_term.json | 1 + .../test73_model_y1_smlp_model_term.json | 1 + .../test73_model_y2_smlp_full_model_term.json | 1 + .../test73_model_y2_smlp_model_term.json | 1 + .../test73_model_dt_sklearn_tree_rules.txt | 6 +- .../test73_model_dt_sklearn_y1_tree_rules.txt | 10 + .../test73_model_dt_sklearn_y2_tree_rules.txt | 7 + .../models/test73_model_smlp_model_term.json | 2 +- .../test73_model_y1_smlp_full_model_term.json | 1 + .../test73_model_y1_smlp_model_term.json | 1 + .../test73_model_y2_smlp_full_model_term.json | 1 + .../test73_model_y2_smlp_model_term.json | 1 + 32 files changed, 815 insertions(+), 4 deletions(-) create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json create mode 100644 regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt create mode 100644 regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json create mode 100644 regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv create mode 100644 regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv create mode 100644 regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv create mode 100644 regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json create mode 100644 regr_smlp/master/test73_model_dt_sklearn_y1_tree_rules.txt create mode 100644 regr_smlp/master/test73_model_dt_sklearn_y2_tree_rules.txt create mode 100644 regr_smlp/master/test73_model_y1_smlp_full_model_term.json create mode 100644 regr_smlp/master/test73_model_y1_smlp_model_term.json create mode 100644 regr_smlp/master/test73_model_y2_smlp_full_model_term.json create mode 100644 regr_smlp/master/test73_model_y2_smlp_model_term.json create mode 100644 regr_smlp/models/test73_model_dt_sklearn_y1_tree_rules.txt create mode 100644 regr_smlp/models/test73_model_dt_sklearn_y2_tree_rules.txt create mode 100644 regr_smlp/models/test73_model_y1_smlp_full_model_term.json create mode 100644 regr_smlp/models/test73_model_y1_smlp_model_term.json create mode 100644 regr_smlp/models/test73_model_y2_smlp_full_model_term.json create mode 100644 regr_smlp/models/test73_model_y2_smlp_model_term.json diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt new file mode 100644 index 00000000..34dc0611 --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt @@ -0,0 +1,392 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 + +smlp_logger - INFO - Assertion asrt2: y1>=9 + +smlp_logger - INFO - Assertion asrt3: y2<0 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - MRMR feature selection for response y1 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y1 : + Feature Score +0 x1 1.115702 +1 x2 0.944056 + +smlp_logger - INFO - MRMR feature selection for response y1 : end + +smlp_logger - INFO - MRMR feature selection for response y2 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y2 : + Feature Score +1 x2 4.950294 +0 x1 1.115702 + +smlp_logger - INFO - MRMR feature selection for response y2 : end + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 +9 2.0 7 5 5 +10 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 +9 0.0 0.8 0.0 0.0 +10 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 2) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./test73_model_data_bounds.json + +smlp_logger - INFO - {'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - Preparing new data for modeling: start + +smlp_logger - INFO - loading new data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 9.000000 9.000000 8.000000 8.000000 9.000000 +mean 6.777778 7.222222 10.250000 2.875000 5.111111 +std 2.108185 2.108185 1.035098 0.834523 1.691482 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 9.750000 2.000000 4.000000 +50% 5.000000 9.000000 10.000000 3.000000 4.000000 +75% 9.000000 9.000000 11.000000 3.250000 6.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - new data + categ y1 y2 x0 x1 x2 +0 c0 5 9 10.0 2.0 3 +1 c12 9 9 12.0 NaN 4 +2 c2 5 9 NaN 3.0 4 +3 c17 5 5 11.0 2.0 6 +4 c18 9 5 10.0 2.0 8 +5 c8 9 9 9.0 4.0 7 +6 c7 5 5 9.0 3.0 6 +7 c3 5 5 10.0 3.0 4 +8 c12 9 9 11.0 4.0 4 + +smlp_logger - INFO - new data after imputing missing values + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after processing responses + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 + +smlp_logger - INFO - Preparing new data for modeling: end + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./test73_model_dt_sklearn_y1_tree_rules.txt + +smlp_logger - INFO - Writing tree rules into file ./test73_model_dt_sklearn_y2_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./test73_model_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 8.000 + +smlp_logger - INFO - Prediction on test data -- r2_score: -1.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 2.182 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.450 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON NEW DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv + +smlp_logger - INFO - Prediction on new data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on new data -- r2_score: 0.325 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 4, 'ite': 2, 'and': 1, 'prop': 3, 'const': 14, 'sub': 3, 'var': 3} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv new file mode 100644 index 00000000..7d143a2f --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,2.909090909090909,0.2666666666666666 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv new file mode 100644 index 00000000..7a649b6a --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json new file mode 100644 index 00000000..6e4f6879 --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json @@ -0,0 +1,5 @@ +{ + "x1": [ + 1 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv new file mode 100644 index 00000000..951115f0 --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,3.5555555555555554,0.10000000000000009 +y2,1.7777777777777777,0.55 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv new file mode 100644 index 00000000..3ba8f5c9 --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv @@ -0,0 +1,10 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv new file mode 100644 index 00000000..fd947921 --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,10.666666666666666,-2.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv new file mode 100644 index 00000000..3bb69252 --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv new file mode 100644 index 00000000..fd9015b8 --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,7,3 +model_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +ca,unsat +ce,sat,4,6,5,9 +ca,sat,7,452984835/67108864,9,9 +ce,sat,1,805306377/134217728,5,5 +ca,unsat +ce,sat,1,7,5,5 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json new file mode 100644 index 00000000..6fb0d0ac --- /dev/null +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -0,0 +1,38 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 4.0, + "y1": 5.0, + "x2": 6.0, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 5.0 + }, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt new file mode 100644 index 00000000..2598ff98 --- /dev/null +++ b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt @@ -0,0 +1,207 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 + +smlp_logger - INFO - Assertion asrt2: y1>=9 + +smlp_logger - INFO - Assertion asrt3: y2<0 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing new data for modeling: start + +smlp_logger - INFO - loading new data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 9.000000 9.000000 8.000000 8.000000 9.000000 +mean 6.777778 7.222222 10.250000 2.875000 5.111111 +std 2.108185 2.108185 1.035098 0.834523 1.691482 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 9.750000 2.000000 4.000000 +50% 5.000000 9.000000 10.000000 3.000000 4.000000 +75% 9.000000 9.000000 11.000000 3.250000 6.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - new data + categ y1 y2 x0 x1 x2 +0 c0 5 9 10.0 2.0 3 +1 c12 9 9 12.0 NaN 4 +2 c2 5 9 NaN 3.0 4 +3 c17 5 5 11.0 2.0 6 +4 c18 9 5 10.0 2.0 8 +5 c8 9 9 9.0 4.0 7 +6 c7 5 5 9.0 3.0 6 +7 c3 5 5 10.0 3.0 4 +8 c12 9 9 11.0 4.0 4 + +smlp_logger - INFO - new data after imputing missing values + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after processing responses + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 + +smlp_logger - INFO - Preparing new data for modeling: end + +smlp_logger - INFO - LOAD TRAINED MODEL + +smlp_logger - INFO - Seving model rerun configuration in file ../models/test73_model_rerun_model_config.json + +smlp_logger - INFO - PREDICT ON NEW DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv + +smlp_logger - INFO - Prediction on new data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on new data -- r2_score: 0.325 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 4, 'ite': 2, 'and': 1, 'prop': 3, 'const': 14, 'sub': 3, 'var': 3} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json new file mode 100644 index 00000000..6e4f6879 --- /dev/null +++ b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json @@ -0,0 +1,5 @@ +{ + "x1": [ + 1 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv new file mode 100644 index 00000000..951115f0 --- /dev/null +++ b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,3.5555555555555554,0.10000000000000009 +y2,1.7777777777777777,0.55 diff --git a/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv new file mode 100644 index 00000000..3ba8f5c9 --- /dev/null +++ b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv @@ -0,0 +1,10 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv new file mode 100644 index 00000000..fd9015b8 --- /dev/null +++ b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,7,3 +model_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +ca,unsat +ce,sat,4,6,5,9 +ca,sat,7,452984835/67108864,9,9 +ce,sat,1,805306377/134217728,5,5 +ca,unsat +ce,sat,1,7,5,5 diff --git a/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json new file mode 100644 index 00000000..6fb0d0ac --- /dev/null +++ b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -0,0 +1,38 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 4.0, + "y1": 5.0, + "x2": 6.0, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 5.0 + }, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/test73_model_dt_sklearn_y1_tree_rules.txt b/regr_smlp/master/test73_model_dt_sklearn_y1_tree_rules.txt new file mode 100644 index 00000000..9f2dbad2 --- /dev/null +++ b/regr_smlp/master/test73_model_dt_sklearn_y1_tree_rules.txt @@ -0,0 +1,10 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) | based on 2 samples +if (x2 <= 0.7000000178813934) and (x2 > 0.4000000134110451) then (y1 = 0.0) | based on 2 samples +if (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 > 0.9000000059604645) then (y1 = 1.0) | based on 1 samples +if (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 <= 0.9000000059604645) then (y1 = 0.0) | based on 1 samples +if (x2 <= 0.7000000178813934) and (x2 <= 0.4000000134110451) and (x2 > 0.10000000149011612) then (y1 = 1.0) | based on 1 samples +if (x2 <= 0.7000000178813934) and (x2 <= 0.4000000134110451) and (x2 <= 0.10000000149011612) then (y1 = 0.0) | based on 1 samples diff --git a/regr_smlp/master/test73_model_dt_sklearn_y2_tree_rules.txt b/regr_smlp/master/test73_model_dt_sklearn_y2_tree_rules.txt new file mode 100644 index 00000000..5015336b --- /dev/null +++ b/regr_smlp/master/test73_model_dt_sklearn_y2_tree_rules.txt @@ -0,0 +1,7 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.4000000134110451) and (x1 <= 0.75) then (y2 = 0.0) | based on 5 samples +if (x2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/master/test73_model_y1_smlp_full_model_term.json b/regr_smlp/master/test73_model_y1_smlp_full_model_term.json new file mode 100644 index 00000000..3c7d4f33 --- /dev/null +++ b/regr_smlp/master/test73_model_y1_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': |:0| (/ 13421773 134217728))) 1 (ite (and (and (> |:0| (/ 23488103 33554432)) (<= |:1| (/ 1 4))) (<= |:0| (/ 30198989 33554432))) 0 (ite (and (and (> |:0| (/ 23488103 33554432)) (<= |:1| (/ 1 4))) (> |:0| (/ 30198989 33554432))) 1 (ite (and (<= |:0| (/ 23488103 33554432)) (> |:0| (/ 53687093 134217728))) 0 1))))) 4) 5)))>}" \ No newline at end of file diff --git a/regr_smlp/master/test73_model_y1_smlp_model_term.json b/regr_smlp/master/test73_model_y1_smlp_model_term.json new file mode 100644 index 00000000..d4363137 --- /dev/null +++ b/regr_smlp/master/test73_model_y1_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 1 (ite (and (<= x2_scaled (/ 23488103 33554432)) (> x2_scaled (/ 53687093 134217728))) 0 1)))))>}" \ No newline at end of file diff --git a/regr_smlp/master/test73_model_y2_smlp_full_model_term.json b/regr_smlp/master/test73_model_y2_smlp_full_model_term.json new file mode 100644 index 00000000..cc8b6220 --- /dev/null +++ b/regr_smlp/master/test73_model_y2_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y2': |:0| (/ 53687093 134217728)) (> (* (/ 1 2) (- x1 2)) (/ 3 4))) 1 (ite (<= |:0| (/ 53687093 134217728)) 1 0)) 4) 5))>}" \ No newline at end of file diff --git a/regr_smlp/master/test73_model_y2_smlp_model_term.json b/regr_smlp/master/test73_model_y2_smlp_model_term.json new file mode 100644 index 00000000..56c332c4 --- /dev/null +++ b/regr_smlp/master/test73_model_y2_smlp_model_term.json @@ -0,0 +1 @@ +"{'y2_scaled': x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (<= x2_scaled (/ 53687093 134217728)) 1 0))>}" \ No newline at end of file diff --git a/regr_smlp/models/test73_model_dt_sklearn_tree_rules.txt b/regr_smlp/models/test73_model_dt_sklearn_tree_rules.txt index 5015336b..30a6a1be 100644 --- a/regr_smlp/models/test73_model_dt_sklearn_tree_rules.txt +++ b/regr_smlp/models/test73_model_dt_sklearn_tree_rules.txt @@ -2,6 +2,6 @@ #Number of trees: 1 #TREE 0 -if (x2 > 0.4000000134110451) and (x1 <= 0.75) then (y2 = 0.0) | based on 5 samples -if (x2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples -if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y2 = 1.0) | based on 1 samples +if (p2 > 0.4000000134110451) and (p1 <= 0.75) then (y2 = 0.0) | based on 5 samples +if (p2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples +if (p2 > 0.4000000134110451) and (p1 > 0.75) then (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/models/test73_model_dt_sklearn_y1_tree_rules.txt b/regr_smlp/models/test73_model_dt_sklearn_y1_tree_rules.txt new file mode 100644 index 00000000..9f2dbad2 --- /dev/null +++ b/regr_smlp/models/test73_model_dt_sklearn_y1_tree_rules.txt @@ -0,0 +1,10 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) | based on 2 samples +if (x2 <= 0.7000000178813934) and (x2 > 0.4000000134110451) then (y1 = 0.0) | based on 2 samples +if (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 > 0.9000000059604645) then (y1 = 1.0) | based on 1 samples +if (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 <= 0.9000000059604645) then (y1 = 0.0) | based on 1 samples +if (x2 <= 0.7000000178813934) and (x2 <= 0.4000000134110451) and (x2 > 0.10000000149011612) then (y1 = 1.0) | based on 1 samples +if (x2 <= 0.7000000178813934) and (x2 <= 0.4000000134110451) and (x2 <= 0.10000000149011612) then (y1 = 0.0) | based on 1 samples diff --git a/regr_smlp/models/test73_model_dt_sklearn_y2_tree_rules.txt b/regr_smlp/models/test73_model_dt_sklearn_y2_tree_rules.txt new file mode 100644 index 00000000..5015336b --- /dev/null +++ b/regr_smlp/models/test73_model_dt_sklearn_y2_tree_rules.txt @@ -0,0 +1,7 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.4000000134110451) and (x1 <= 0.75) then (y2 = 0.0) | based on 5 samples +if (x2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/models/test73_model_smlp_model_term.json b/regr_smlp/models/test73_model_smlp_model_term.json index dd21c3ce..475d42a2 100644 --- a/regr_smlp/models/test73_model_smlp_model_term.json +++ b/regr_smlp/models/test73_model_smlp_model_term.json @@ -1 +1 @@ -"{'y2_scaled': x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (<= x2_scaled (/ 53687093 134217728)) 1 0))>}" \ No newline at end of file +"{'y2_scaled': p2_scaled (/ 53687093 134217728)) (> p1_scaled (/ 3 4))) 1 (ite (<= p2_scaled (/ 53687093 134217728)) 1 0))>}" \ No newline at end of file diff --git a/regr_smlp/models/test73_model_y1_smlp_full_model_term.json b/regr_smlp/models/test73_model_y1_smlp_full_model_term.json new file mode 100644 index 00000000..3c7d4f33 --- /dev/null +++ b/regr_smlp/models/test73_model_y1_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': |:0| (/ 13421773 134217728))) 1 (ite (and (and (> |:0| (/ 23488103 33554432)) (<= |:1| (/ 1 4))) (<= |:0| (/ 30198989 33554432))) 0 (ite (and (and (> |:0| (/ 23488103 33554432)) (<= |:1| (/ 1 4))) (> |:0| (/ 30198989 33554432))) 1 (ite (and (<= |:0| (/ 23488103 33554432)) (> |:0| (/ 53687093 134217728))) 0 1))))) 4) 5)))>}" \ No newline at end of file diff --git a/regr_smlp/models/test73_model_y1_smlp_model_term.json b/regr_smlp/models/test73_model_y1_smlp_model_term.json new file mode 100644 index 00000000..d4363137 --- /dev/null +++ b/regr_smlp/models/test73_model_y1_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 1 (ite (and (<= x2_scaled (/ 23488103 33554432)) (> x2_scaled (/ 53687093 134217728))) 0 1)))))>}" \ No newline at end of file diff --git a/regr_smlp/models/test73_model_y2_smlp_full_model_term.json b/regr_smlp/models/test73_model_y2_smlp_full_model_term.json new file mode 100644 index 00000000..cc8b6220 --- /dev/null +++ b/regr_smlp/models/test73_model_y2_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y2': |:0| (/ 53687093 134217728)) (> (* (/ 1 2) (- x1 2)) (/ 3 4))) 1 (ite (<= |:0| (/ 53687093 134217728)) 1 0)) 4) 5))>}" \ No newline at end of file diff --git a/regr_smlp/models/test73_model_y2_smlp_model_term.json b/regr_smlp/models/test73_model_y2_smlp_model_term.json new file mode 100644 index 00000000..56c332c4 --- /dev/null +++ b/regr_smlp/models/test73_model_y2_smlp_model_term.json @@ -0,0 +1 @@ +"{'y2_scaled': x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (<= x2_scaled (/ 53687093 134217728)) 1 0))>}" \ No newline at end of file From 422423303f39bfa504f381f03d906f506ccb8553 Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 17:34:39 +0300 Subject: [PATCH 09/20] added test 75 masters --- ...smlp_toy_num_resp_noknobs_pred_labeled.txt | 207 ++++++++++++++++++ ...nobs_pred_labeled_missing_values_dict.json | 5 + ...pred_labeled_new_prediction_precisions.csv | 3 + ...s_pred_labeled_new_predictions_summary.csv | 10 + ...oy_num_resp_noknobs_pred_labeled_trace.csv | 12 + ...p_noknobs_pred_labeled_verify_results.json | 38 ++++ 6 files changed, 275 insertions(+) create mode 100644 regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt create mode 100644 regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json create mode 100644 regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv create mode 100644 regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv create mode 100644 regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv create mode 100644 regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json diff --git a/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt new file mode 100644 index 00000000..f327d37d --- /dev/null +++ b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt @@ -0,0 +1,207 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 + +smlp_logger - INFO - Assertion asrt2: y1>=9 + +smlp_logger - INFO - Assertion asrt3: y2<0 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing new data for modeling: start + +smlp_logger - INFO - loading new data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 9.000000 9.000000 8.000000 8.000000 9.000000 +mean 6.777778 7.222222 10.250000 2.875000 5.111111 +std 2.108185 2.108185 1.035098 0.834523 1.691482 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 9.750000 2.000000 4.000000 +50% 5.000000 9.000000 10.000000 3.000000 4.000000 +75% 9.000000 9.000000 11.000000 3.250000 6.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - new data + categ y1 y2 x0 x1 x2 +0 c0 5 9 10.0 2.0 3 +1 c12 9 9 12.0 NaN 4 +2 c2 5 9 NaN 3.0 4 +3 c17 5 5 11.0 2.0 6 +4 c18 9 5 10.0 2.0 8 +5 c8 9 9 9.0 4.0 7 +6 c7 5 5 9.0 3.0 6 +7 c3 5 5 10.0 3.0 4 +8 c12 9 9 11.0 4.0 4 + +smlp_logger - INFO - new data after imputing missing values + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after processing responses + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 + +smlp_logger - INFO - Preparing new data for modeling: end + +smlp_logger - INFO - LOAD TRAINED MODEL + +smlp_logger - INFO - Seving model rerun configuration in file ../models/test73_model_rerun_model_config.json + +smlp_logger - INFO - PREDICT ON NEW DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv + +smlp_logger - INFO - Prediction on new data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on new data -- r2_score: 0.325 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 4, 'ite': 2, 'and': 1, 'prop': 3, 'const': 14, 'sub': 3, 'var': 3} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json new file mode 100644 index 00000000..6e4f6879 --- /dev/null +++ b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json @@ -0,0 +1,5 @@ +{ + "x1": [ + 1 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv new file mode 100644 index 00000000..951115f0 --- /dev/null +++ b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,3.5555555555555554,0.10000000000000009 +y2,1.7777777777777777,0.55 diff --git a/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv new file mode 100644 index 00000000..3ba8f5c9 --- /dev/null +++ b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv @@ -0,0 +1,10 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv new file mode 100644 index 00000000..fd9015b8 --- /dev/null +++ b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,7,3 +model_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +ca,unsat +ce,sat,4,6,5,9 +ca,sat,7,452984835/67108864,9,9 +ce,sat,1,805306377/134217728,5,5 +ca,unsat +ce,sat,1,7,5,5 diff --git a/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json new file mode 100644 index 00000000..6fb0d0ac --- /dev/null +++ b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -0,0 +1,38 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 4.0, + "y1": 5.0, + "x2": 6.0, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 5.0 + }, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file From 172b2d6acc4e6d9b410e92f51c1d52f394a94e44 Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 18:16:01 +0300 Subject: [PATCH 10/20] added masters for tests 76 and 77 and some of test76_model files to masters and models --- .../Test76_smlp_toy_num_resp_noknobs.txt | 293 ++++++++++++++++++ ..._noknobs_labeled_prediction_precisions.csv | 3 + ...sp_noknobs_labeled_predictions_summary.csv | 12 + ..._num_resp_noknobs_missing_values_dict.json | 8 + ...esp_noknobs_test_prediction_precisions.csv | 3 + ..._resp_noknobs_test_predictions_summary.csv | 4 + ...Test76_smlp_toy_num_resp_noknobs_trace.csv | 12 + ...noknobs_training_prediction_precisions.csv | 3 + ...p_noknobs_training_predictions_summary.csv | 9 + ...p_toy_num_resp_noknobs_verify_results.json | 38 +++ regr_smlp/master/Test77_test76_model.txt | 2 +- .../master/Test77_test76_model_trace.csv | 12 + .../Test77_test76_model_verify_results.json | 16 +- .../test76_model_dt_sklearn_tree_rules.txt | 2 +- .../test76_model_smlp_full_model_term.json | 1 + .../master/test76_model_smlp_model_term.json | 2 +- .../test76_model_dt_sklearn_tree_rules.txt | 2 +- .../test76_model_smlp_full_model_term.json | 1 + .../models/test76_model_smlp_model_term.json | 2 +- 19 files changed, 412 insertions(+), 13 deletions(-) create mode 100644 regr_smlp/master/Test76_smlp_toy_num_resp_noknobs.txt create mode 100644 regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_missing_values_dict.json create mode 100644 regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_trace.csv create mode 100644 regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_verify_results.json create mode 100644 regr_smlp/master/Test77_test76_model_trace.csv create mode 100644 regr_smlp/master/test76_model_smlp_full_model_term.json create mode 100644 regr_smlp/models/test76_model_smlp_full_model_term.json diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs.txt new file mode 100644 index 00000000..4d4eb429 --- /dev/null +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs.txt @@ -0,0 +1,293 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 + +smlp_logger - INFO - Assertion asrt2: y1>=9 + +smlp_logger - INFO - Assertion asrt3: y2<0 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - MRMR feature selection for response y1 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y1 : + Feature Score +0 x1 1.115702 +1 x2 0.944056 + +smlp_logger - INFO - MRMR feature selection for response y1 : end + +smlp_logger - INFO - MRMR feature selection for response y2 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y2 : + Feature Score +1 x2 4.950294 +0 x1 1.115702 + +smlp_logger - INFO - MRMR feature selection for response y2 : end + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 +9 2.0 7 5 5 +10 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 +9 0.0 0.8 0.0 0.0 +10 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 2) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./test76_model_data_bounds.json + +smlp_logger - INFO - {'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./test76_model_dt_sklearn_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./test76_model_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test76_smlp_toy_num_resp_noknobs_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test76_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test76_smlp_toy_num_resp_noknobs_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test76_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 8.000 + +smlp_logger - INFO - Prediction on test data -- r2_score: -1.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test76_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test76_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 2.182 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.450 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 21, 'ite': 6, 'and': 14, 'prop': 20, 'const': 69, 'sub': 20, 'var': 20} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 21, 'ite': 6, 'and': 14, 'prop': 20, 'const': 69, 'sub': 20, 'var': 20} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv new file mode 100644 index 00000000..7d143a2f --- /dev/null +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,2.909090909090909,0.2666666666666666 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv new file mode 100644 index 00000000..7a649b6a --- /dev/null +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_missing_values_dict.json b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_missing_values_dict.json new file mode 100644 index 00000000..553bfe33 --- /dev/null +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_missing_values_dict.json @@ -0,0 +1,8 @@ +{ + "x1": [ + 1 + ], + "x0": [ + 2 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv new file mode 100644 index 00000000..fd947921 --- /dev/null +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,10.666666666666666,-2.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_test_predictions_summary.csv new file mode 100644 index 00000000..3bb69252 --- /dev/null +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_trace.csv new file mode 100644 index 00000000..7d906b15 --- /dev/null +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,7,3 +model_consistency,sat,1,805306377/134217728,5,5 +witness_consistency,sat,1,805306377/134217728,5,5 +witness_consistency,sat,1,805306377/134217728,5,5 +witness_consistency,sat,1,805306377/134217728,5,5 +ca,unsat +ce,sat,4,6,9,9 +ca,sat,1,603979777/134217728,9,9 +ce,sat,1,805306377/134217728,5,5 +ca,unsat +ce,sat,1,805306377/134217728,5,5 diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_verify_results.json new file mode 100644 index 00000000..6e037ddd --- /dev/null +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_verify_results.json @@ -0,0 +1,38 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 4.0, + "y1": 9.0, + "x2": 6.0, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 5.0 + }, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test77_test76_model.txt b/regr_smlp/master/Test77_test76_model.txt index 289b9ae6..b9a2ef57 100644 --- a/regr_smlp/master/Test77_test76_model.txt +++ b/regr_smlp/master/Test77_test76_model.txt @@ -26,7 +26,7 @@ smlp_logger - INFO - PREPARE DATA FOR MODELING smlp_logger - INFO - LOAD TRAINED MODEL -smlp_logger - INFO - Seving model rerun configuration in file ./../models/test76_model_rerun_model_config.json +smlp_logger - INFO - Seving model rerun configuration in file ../models/test76_model_rerun_model_config.json smlp_logger - INFO - Creating model exploration base components: Start diff --git a/regr_smlp/master/Test77_test76_model_trace.csv b/regr_smlp/master/Test77_test76_model_trace.csv new file mode 100644 index 00000000..7d906b15 --- /dev/null +++ b/regr_smlp/master/Test77_test76_model_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,7,3 +model_consistency,sat,1,805306377/134217728,5,5 +witness_consistency,sat,1,805306377/134217728,5,5 +witness_consistency,sat,1,805306377/134217728,5,5 +witness_consistency,sat,1,805306377/134217728,5,5 +ca,unsat +ce,sat,4,6,9,9 +ca,sat,1,603979777/134217728,9,9 +ce,sat,1,805306377/134217728,5,5 +ca,unsat +ce,sat,1,805306377/134217728,5,5 diff --git a/regr_smlp/master/Test77_test76_model_verify_results.json b/regr_smlp/master/Test77_test76_model_verify_results.json index 87425ddb..6e037ddd 100644 --- a/regr_smlp/master/Test77_test76_model_verify_results.json +++ b/regr_smlp/master/Test77_test76_model_verify_results.json @@ -3,10 +3,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 1.0, - "y1": 5.0, - "x2": 6.75, - "y2": 5.0 + "x1": 4.0, + "y1": 9.0, + "x2": 6.0, + "y2": 9.0 }, "assertion_feasible": false }, @@ -16,7 +16,7 @@ "counter_example": { "x1": 1.0, "y1": 5.0, - "x2": 7.0, + "x2": 6.000000067055225, "y2": 5.0 }, "assertion_feasible": true @@ -25,10 +25,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 7.0, - "y1": 9.0, + "x1": 1.0, + "y1": 5.0, "x2": 6.000000067055225, - "y2": 9.0 + "y2": 5.0 }, "assertion_feasible": false }, diff --git a/regr_smlp/master/test76_model_dt_sklearn_tree_rules.txt b/regr_smlp/master/test76_model_dt_sklearn_tree_rules.txt index 5f89d9ed..59a1eff8 100644 --- a/regr_smlp/master/test76_model_dt_sklearn_tree_rules.txt +++ b/regr_smlp/master/test76_model_dt_sklearn_tree_rules.txt @@ -3,8 +3,8 @@ #TREE 0 if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 <= 0.7000000178813934) then (y1 = 0.0) and (y2 = 0.0) | based on 2 samples -if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 > 0.9000000059604645) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 <= 0.9000000059604645) then (y1 = 0.0) and (y2 = 0.0) | based on 1 samples if (x2 <= 0.4000000134110451) and (x2 > 0.10000000149011612) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/master/test76_model_smlp_full_model_term.json b/regr_smlp/master/test76_model_smlp_full_model_term.json new file mode 100644 index 00000000..d046fc1f --- /dev/null +++ b/regr_smlp/master/test76_model_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': |:0| (/ 13421773 134217728))) 1 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (<= |:0| (/ 30198989 33554432))) 0 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (> |:0| (/ 30198989 33554432))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (> |:1| (/ 1 4))) 1 (ite (and (> |:0| (/ 53687093 134217728)) (> |:1| (/ 3 4))) 1 0)))))) 4) 5)))>, 'y2': |:0| (/ 13421773 134217728))) 1 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (<= |:0| (/ 30198989 33554432))) 0 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (> |:0| (/ 30198989 33554432))) 0 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (> |:1| (/ 1 4))) 0 (ite (and (> |:0| (/ 53687093 134217728)) (> |:1| (/ 3 4))) 1 0)))))) 4) 5)))>}" \ No newline at end of file diff --git a/regr_smlp/master/test76_model_smlp_model_term.json b/regr_smlp/master/test76_model_smlp_model_term.json index 8fd79688..cd219aa4 100644 --- a/regr_smlp/master/test76_model_smlp_model_term.json +++ b/regr_smlp/master/test76_model_smlp_model_term.json @@ -1 +1 @@ -"{'y1_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 1 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (> x1_scaled (/ 1 4))) 1 0))))))>, 'y2_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (> x1_scaled (/ 1 4))) 0 0))))))>}" \ No newline at end of file +"{'y1_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (> x1_scaled (/ 1 4))) 1 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 0))))))>, 'y2_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (> x1_scaled (/ 1 4))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 0))))))>}" \ No newline at end of file diff --git a/regr_smlp/models/test76_model_dt_sklearn_tree_rules.txt b/regr_smlp/models/test76_model_dt_sklearn_tree_rules.txt index 5f89d9ed..59a1eff8 100644 --- a/regr_smlp/models/test76_model_dt_sklearn_tree_rules.txt +++ b/regr_smlp/models/test76_model_dt_sklearn_tree_rules.txt @@ -3,8 +3,8 @@ #TREE 0 if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 <= 0.7000000178813934) then (y1 = 0.0) and (y2 = 0.0) | based on 2 samples -if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 > 0.9000000059604645) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 <= 0.9000000059604645) then (y1 = 0.0) and (y2 = 0.0) | based on 1 samples if (x2 <= 0.4000000134110451) and (x2 > 0.10000000149011612) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/models/test76_model_smlp_full_model_term.json b/regr_smlp/models/test76_model_smlp_full_model_term.json new file mode 100644 index 00000000..d046fc1f --- /dev/null +++ b/regr_smlp/models/test76_model_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': |:0| (/ 13421773 134217728))) 1 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (<= |:0| (/ 30198989 33554432))) 0 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (> |:0| (/ 30198989 33554432))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (> |:1| (/ 1 4))) 1 (ite (and (> |:0| (/ 53687093 134217728)) (> |:1| (/ 3 4))) 1 0)))))) 4) 5)))>, 'y2': |:0| (/ 13421773 134217728))) 1 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (<= |:0| (/ 30198989 33554432))) 0 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (> |:0| (/ 30198989 33554432))) 0 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (> |:1| (/ 1 4))) 0 (ite (and (> |:0| (/ 53687093 134217728)) (> |:1| (/ 3 4))) 1 0)))))) 4) 5)))>}" \ No newline at end of file diff --git a/regr_smlp/models/test76_model_smlp_model_term.json b/regr_smlp/models/test76_model_smlp_model_term.json index 8fd79688..cd219aa4 100644 --- a/regr_smlp/models/test76_model_smlp_model_term.json +++ b/regr_smlp/models/test76_model_smlp_model_term.json @@ -1 +1 @@ -"{'y1_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 1 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (> x1_scaled (/ 1 4))) 1 0))))))>, 'y2_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (> x1_scaled (/ 1 4))) 0 0))))))>}" \ No newline at end of file +"{'y1_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (> x1_scaled (/ 1 4))) 1 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 0))))))>, 'y2_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (> x1_scaled (/ 1 4))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 0))))))>}" \ No newline at end of file From 16bd1437cade66aac21c67d1ae74819acabf9d4e Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 19:45:05 +0300 Subject: [PATCH 11/20] added masters for tests 78 and 84 --- .../Test78_smlp_toy_num_resp_noknobs.txt | 278 +++++++++++++++++ ..._noknobs_labeled_prediction_precisions.csv | 3 + ...sp_noknobs_labeled_predictions_summary.csv | 12 + ..._num_resp_noknobs_missing_values_dict.json | 8 + ...esp_noknobs_test_prediction_precisions.csv | 3 + ..._resp_noknobs_test_predictions_summary.csv | 4 + ...Test78_smlp_toy_num_resp_noknobs_trace.csv | 9 + ...noknobs_training_prediction_precisions.csv | 3 + ...p_noknobs_training_predictions_summary.csv | 9 + ...p_toy_num_resp_noknobs_verify_results.json | 22 ++ .../Test84_smlp_toy_num_resp_noknobs.txt | 293 ++++++++++++++++++ ...smlp_toy_num_resp_noknobs_data_bounds.json | 22 ++ ...resp_noknobs_dt_sklearn_model_complete.pkl | Bin 0 -> 2014 bytes ...num_resp_noknobs_dt_sklearn_tree_rules.txt | 10 + ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 663 bytes ..._noknobs_labeled_prediction_precisions.csv | 3 + ...sp_noknobs_labeled_predictions_summary.csv | 12 + ..._num_resp_noknobs_missing_values_dict.json | 8 + ..._num_resp_noknobs_model_features_dict.json | 12 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ...y_num_resp_noknobs_rerun_model_config.json | 172 ++++++++++ ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 661 bytes ...num_resp_noknobs_smlp_full_model_term.json | 1 + ..._toy_num_resp_noknobs_smlp_model_term.json | 1 + ...esp_noknobs_test_prediction_precisions.csv | 3 + ..._resp_noknobs_test_predictions_summary.csv | 4 + ...Test84_smlp_toy_num_resp_noknobs_trace.csv | 12 + ...noknobs_training_prediction_precisions.csv | 3 + ...p_noknobs_training_predictions_summary.csv | 9 + ...p_toy_num_resp_noknobs_verify_results.json | 35 +++ .../test78_model_dt_sklearn_tree_rules.txt | 2 +- .../test78_model_smlp_full_model_term.json | 1 + ...y_num_resp_noknobs_rerun_model_config.json | 172 ++++++++++ .../test78_model_dt_sklearn_tree_rules.txt | 2 +- 34 files changed, 1127 insertions(+), 2 deletions(-) create mode 100644 regr_smlp/master/Test78_smlp_toy_num_resp_noknobs.txt create mode 100644 regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_missing_values_dict.json create mode 100644 regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_trace.csv create mode 100644 regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_verify_results.json create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs.txt create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_data_bounds.json create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_features_scaler.pkl create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_missing_values_dict.json create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_model_features_dict.json create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_model_levels_dict.json create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_rerun_model_config.json create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_responses_scaler.pkl create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_smlp_full_model_term.json create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_smlp_model_term.json create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_trace.csv create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_verify_results.json create mode 100644 regr_smlp/master/test78_model_smlp_full_model_term.json create mode 100644 regr_smlp/models/Test84_smlp_toy_num_resp_noknobs_rerun_model_config.json diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs.txt new file mode 100644 index 00000000..dd941ff1 --- /dev/null +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs.txt @@ -0,0 +1,278 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: y1==9 + +smlp_logger - INFO - Assertion asrt2: y2>0 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - MRMR feature selection for response y1 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y1 : + Feature Score +0 x1 1.115702 + +smlp_logger - INFO - MRMR feature selection for response y1 : end + +smlp_logger - INFO - MRMR feature selection for response y2 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y2 : + Feature Score +0 x2 4.950294 + +smlp_logger - INFO - MRMR feature selection for response y2 : end + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 +9 2.0 7 5 5 +10 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 +9 0.0 0.8 0.0 0.0 +10 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 2) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./test78_model_data_bounds.json + +smlp_logger - INFO - {'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./test78_model_dt_sklearn_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./test78_model_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test78_smlp_toy_num_resp_noknobs_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test78_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test78_smlp_toy_num_resp_noknobs_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test78_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 8.000 + +smlp_logger - INFO - Prediction on test data -- r2_score: -1.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test78_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test78_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 2.182 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.450 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 21, 'ite': 6, 'and': 14, 'prop': 20, 'const': 69, 'sub': 20, 'var': 20} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 21, 'ite': 6, 'and': 14, 'prop': 20, 'const': 69, 'sub': 20, 'var': 20} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> y1==9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y2>0 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: PASS + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv new file mode 100644 index 00000000..7d143a2f --- /dev/null +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,2.909090909090909,0.2666666666666666 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv new file mode 100644 index 00000000..7a649b6a --- /dev/null +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_missing_values_dict.json b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_missing_values_dict.json new file mode 100644 index 00000000..553bfe33 --- /dev/null +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_missing_values_dict.json @@ -0,0 +1,8 @@ +{ + "x1": [ + 1 + ], + "x0": [ + 2 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv new file mode 100644 index 00000000..fd947921 --- /dev/null +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,10.666666666666666,-2.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_test_predictions_summary.csv new file mode 100644 index 00000000..3bb69252 --- /dev/null +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_trace.csv new file mode 100644 index 00000000..85e7bc4a --- /dev/null +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_trace.csv @@ -0,0 +1,9 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,7,3 +model_consistency,sat,1,805306377/134217728,5,5 +witness_consistency,sat,1,805306377/134217728,5,5 +witness_consistency,sat,1,805306377/134217728,5,5 +ca,sat,7,805306377/134217728,9,9 +ce,sat,7,3,5,9 +ca,sat,1,805306377/134217728,5,5 +ce,unsat diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_verify_results.json new file mode 100644 index 00000000..69481125 --- /dev/null +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_verify_results.json @@ -0,0 +1,22 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 7.0, + "y1": 5.0, + "x2": 3.0, + "y2": 9.0 + }, + "assertion_feasible": true + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "PASS", + "counter_example": null, + "assertion_feasible": true + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs.txt new file mode 100644 index 00000000..5be4da4e --- /dev/null +++ b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs.txt @@ -0,0 +1,293 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x2==7.0 and x0==0 and x1==2.5 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 + +smlp_logger - INFO - Assertion asrt2: y1>=9 + +smlp_logger - INFO - Assertion asrt3: y2<0 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - MRMR feature selection for response y1 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y1 : + Feature Score +0 x1 1.115702 +1 x2 0.944056 + +smlp_logger - INFO - MRMR feature selection for response y1 : end + +smlp_logger - INFO - MRMR feature selection for response y2 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y2 : + Feature Score +1 x2 4.950294 +0 x1 1.115702 + +smlp_logger - INFO - MRMR feature selection for response y2 : end + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x0 x1 x2 y1 y2 +0 0.333333 0.0 0.0 0.0 1.0 +1 1.000000 0.0 0.2 1.0 1.0 +2 0.333333 0.5 0.2 0.0 1.0 +3 0.666667 0.0 0.6 0.0 0.0 +4 0.333333 0.0 1.0 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+ +smlp_logger - INFO - Seving model in file ./Test84_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test84_smlp_toy_num_resp_noknobs_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test84_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test84_smlp_toy_num_resp_noknobs_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test84_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on test data -- r2_score: 0.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test84_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test84_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 0.727 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.817 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (and (and (= x2 7) (= x0 0)) (= x1 (/ 5 2))) + +smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (and (and (= x2 7) (= x0 0)) (= x1 (/ 5 2)))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: PASS + +smlp_logger - 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53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (> |:0| (/ 23488103 33554432))) 1 0))))) 4) 5))))>, 'y2': |:1| (/ 44739243 67108864))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (<= |:0| (/ 23488103 33554432))) 0 (ite (and (> |:0| (/ 53687093 134217728)) (> |:2| (/ 3 4))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (<= |:1| (/ 33554433 67108864))) (> |:0| (/ 23488103 33554432))) 0 0))))) 4) 5))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_smlp_model_term.json b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_smlp_model_term.json new file mode 100644 index 00000000..ea7ac531 --- /dev/null +++ b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': x_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> p2_scaled (/ 53687093 134217728)) (<= p1_scaled (/ 3 4))) (<= x_scaled (/ 33554433 67108864))) (<= p2_scaled (/ 23488103 33554432))) 0 (ite (and (> p2_scaled (/ 53687093 134217728)) (> p1_scaled (/ 3 4))) 1 (ite (and (and (and (> p2_scaled (/ 53687093 134217728)) (<= p1_scaled (/ 3 4))) (<= x_scaled (/ 33554433 67108864))) (> p2_scaled (/ 23488103 33554432))) 1 0)))))>, 'y2_scaled': x_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> p2_scaled (/ 53687093 134217728)) (<= p1_scaled (/ 3 4))) (<= x_scaled (/ 33554433 67108864))) (<= p2_scaled (/ 23488103 33554432))) 0 (ite (and (> p2_scaled (/ 53687093 134217728)) (> p1_scaled (/ 3 4))) 1 (ite (and (and (and (> p2_scaled (/ 53687093 134217728)) (<= p1_scaled (/ 3 4))) (<= x_scaled (/ 33554433 67108864))) (> p2_scaled (/ 23488103 33554432))) 0 0)))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv new file mode 100644 index 00000000..ec56b74c --- /dev/null +++ b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_test_predictions_summary.csv new file mode 100644 index 00000000..3477d51d --- /dev/null +++ b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,5.0,9.0 +2,5.0,9.0,5.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_trace.csv new file mode 100644 index 00000000..c7df48b0 --- /dev/null +++ b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,5/2,7 +model_consistency,sat,0,5/2,7,9,5 +witness_consistency,sat,0,5/2,7,9,5 +witness_consistency,sat,0,5/2,7,9,5 +witness_consistency,sat,0,5/2,7,9,5 +ca,unsat +ce,sat,0,5/2,7,9,5 +ca,sat,0,5/2,7,9,5 +ce,unsat +ca,unsat +ce,sat,0,5/2,7,9,5 diff --git a/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_verify_results.json new file mode 100644 index 00000000..df922ae4 --- /dev/null +++ b/regr_smlp/master/Test84_smlp_toy_num_resp_noknobs_verify_results.json @@ -0,0 +1,35 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x0": 0.0, + "x1": 2.5, + "y1": 9.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "PASS", + "counter_example": null, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x0": 0.0, + "x1": 2.5, + "y1": 9.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/test78_model_dt_sklearn_tree_rules.txt b/regr_smlp/master/test78_model_dt_sklearn_tree_rules.txt index 5f89d9ed..59a1eff8 100644 --- a/regr_smlp/master/test78_model_dt_sklearn_tree_rules.txt +++ b/regr_smlp/master/test78_model_dt_sklearn_tree_rules.txt @@ -3,8 +3,8 @@ #TREE 0 if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 <= 0.7000000178813934) then (y1 = 0.0) and (y2 = 0.0) | based on 2 samples -if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 > 0.9000000059604645) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 <= 0.9000000059604645) then (y1 = 0.0) and (y2 = 0.0) | based on 1 samples if (x2 <= 0.4000000134110451) and (x2 > 0.10000000149011612) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/master/test78_model_smlp_full_model_term.json b/regr_smlp/master/test78_model_smlp_full_model_term.json new file mode 100644 index 00000000..d046fc1f --- /dev/null +++ b/regr_smlp/master/test78_model_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': |:0| (/ 13421773 134217728))) 1 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (<= |:0| (/ 30198989 33554432))) 0 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (> |:0| (/ 30198989 33554432))) 1 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (> |:1| (/ 1 4))) 1 (ite (and (> |:0| (/ 53687093 134217728)) (> |:1| (/ 3 4))) 1 0)))))) 4) 5)))>, 'y2': |:0| (/ 13421773 134217728))) 1 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (<= |:0| (/ 30198989 33554432))) 0 (ite (and (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (> |:0| (/ 30198989 33554432))) 0 (ite (and (and (and (> |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (> |:1| (/ 1 4))) 0 (ite (and (> |:0| (/ 53687093 134217728)) (> |:1| (/ 3 4))) 1 0)))))) 4) 5)))>}" \ No newline at end of file diff --git a/regr_smlp/models/Test84_smlp_toy_num_resp_noknobs_rerun_model_config.json b/regr_smlp/models/Test84_smlp_toy_num_resp_noknobs_rerun_model_config.json new file mode 100644 index 00000000..c7a3a170 --- /dev/null +++ b/regr_smlp/models/Test84_smlp_toy_num_resp_noknobs_rerun_model_config.json @@ -0,0 +1,172 @@ +{ + "alpha": "x2==7.0 and x0==0 and x1==2.5", + "analytics_mode": "verify", + "approximate_fractions": true, + "assertions_expressions": "(y2**3+x2)/2<6;y1>=9;y2<0", + "assertions_names": "asrt1,asrt2,asrt3", + "beta": null, + "center_offset": "0", + "compress_rules": false, + "continuous_correlation_estimators": [ + "pearson", + "spearman" + ], + "correlations_and_mutual_information": true, + "data_scaler": "min_max", + "delta_absolute": 0.0, + "delta_relative": 0.01, + "discretization_algo": "uniform", + "discretization_bins": 10, + "discretization_labels": true, + "discretization_type": "category", + "discretize_numeric_features": null, + "doe_algo": null, + "doe_box_behnken_centers": 1, + "doe_central_composite_alpha": "o", + "doe_central_composite_center": "2,2", + "doe_central_composite_face": "ccf", + "doe_design_resolution": null, + "doe_factor_level_ranges": null, + "doe_num_samples": null, + "doe_prob_distribution": "Normal", + "doe_spec_file": null, + "dt_sklearn_ccp_alpha": 0.0, + "dt_sklearn_criterion": "squared_error", + "dt_sklearn_max_depth": 15, + "dt_sklearn_max_features": null, + "dt_sklearn_max_leaf_nodes": null, + "dt_sklearn_min_impurity_decrease": 0.0, + "dt_sklearn_min_samples_leaf": 1, + "dt_sklearn_min_samples_split": 2, + "dt_sklearn_min_weight_fraction_leaf": 0.0, + "dt_sklearn_random_state": null, + "dt_sklearn_splitter": "best", + "epsilon": 0.05, + "et_sklearn_bootstrap": true, + "et_sklearn_ccp_alpha": 0.0, + "et_sklearn_criterion": "squared_error", + "et_sklearn_max_depth": null, + "et_sklearn_max_features": 1.0, + "et_sklearn_max_leaf_nodes": null, + "et_sklearn_max_samples": null, + "et_sklearn_min_impurity_decrease": 0.0, + "et_sklearn_min_samples_leaf": 1, + "et_sklearn_min_samples_split": 2, + "et_sklearn_min_weight_fraction_leaf": 0.0, + "et_sklearn_n_estimators": 100, + "et_sklearn_random_state": null, + "et_sklearn_verbose": 0, + "et_sklearn_warm_start": false, + "eta": null, + "features": "x0,x1,x2", + "fraction_precision": 64, + "impute_responses": false, + "interactive_plots": false, + "keep_features": [], + "labeled_data": null, + "lemma_precision": 0, + "load_configuration": null, + "log_files_prefix": null, + "log_level": "info", + "log_mode": "w", + "log_time": false, + "model": "dt_sklearn", + "model_caret_cross_validation": true, + "model_caret_return_train_score": false, + "model_caret_verbose": true, + "model_name": null, + "model_per_response": false, + "mrmr_feat_count_for_correlation": 15, + "mrmr_feat_count_for_prediction": 2, + "mutual_information_method": "normalized", + "negative_value": 0, + "new_data": null, + "nn_keras_batch_size": 200, + "nn_keras_batches_grid": null, + "nn_keras_epochs": 2000, + "nn_keras_hid_activation": "relu", + "nn_keras_layers": "2,1", + "nn_keras_layers_grid": null, + "nn_keras_learning_rate": 0.001, + "nn_keras_learning_rates_grid": null, + "nn_keras_loss_function": "mse", + "nn_keras_loss_functions_grid": null, + "nn_keras_metrics": [ + "mse" + ], + "nn_keras_optimizer": "adam", + "nn_keras_out_activation": "linear", + "nn_keras_sequential_api": true, + "nn_keras_tuner_algo": null, + "nn_keras_weights_precision": null, + "nnet_encoding": "nested", + "objectives_expressions": null, + "objectives_names": "None", + "optimization_strategy": "eager", + "optimize_pareto": true, + "output_directory": "./", + "poly_sklearn_copy_X": true, + "poly_sklearn_degree": 2, + "poly_sklearn_fit_intercept": true, + "poly_sklearn_n_jobs": null, + "poly_sklearn_positive": false, + "positive_value": 1, + "prediction_plots": false, + "psg_max_dimension": 3, + "psg_quality_target": "Lift", + "psg_top_ranked": 15, + "query_expressions": null, + "query_names": "None", + "radius_absolute": null, + "radius_relative": null, + "response": "y1,y2", + "response_map": null, + "response_plots": false, + "response_to_bool": null, + "rf_sklearn_bootstrap": true, + "rf_sklearn_ccp_alpha": 0.0, + "rf_sklearn_criterion": "squared_error", + "rf_sklearn_max_depth": null, + "rf_sklearn_max_features": 1.0, + "rf_sklearn_max_leaf_nodes": null, + "rf_sklearn_max_samples": null, + "rf_sklearn_min_impurity_decrease": 0.0, + "rf_sklearn_min_samples_leaf": 1, + "rf_sklearn_min_samples_split": 2, + "rf_sklearn_min_weight_fraction_leaf": 0.0, + "rf_sklearn_n_estimators": 100, + "rf_sklearn_random_state": null, + "rf_sklearn_verbose": 0, + "rf_sklearn_warm_start": false, + "sample_weights_coef": 0, + "sample_weights_exponent": 0, + "sample_weights_intercept": 0, + "save_configuration": false, + "save_model": "false", + "save_model_rerun_configuration": true, + "scale_features": true, + "scale_objectives": true, + "scale_responses": true, + "seed": 10, + "setup_caret_data_split_shuffle": true, + "setup_caret_fold": 0, + "setup_caret_session_id": null, + "setup_caret_verbose": true, + "simplify_terms": false, + "solver": "z3", + "solver_logic": "ALL", + "solver_path": null, + "spec": "../specs/smlp_toy_num_resp_noknobs_verify.spec", + "split_test": 0.2, + "trace_anonymize": false, + "trace_precision": 0, + "trace_runtime": 0, + "train_first_n": 0, + "train_random_n": 0, + "train_uniform_n": 0, + "tree_encoding": "nested", + "tuner_caret_search_algorithm": "random", + "tuner_caret_tuner_verbose": true, + "use_model": "true", + "vacuity_check": true +} \ No newline at end of file diff --git a/regr_smlp/models/test78_model_dt_sklearn_tree_rules.txt b/regr_smlp/models/test78_model_dt_sklearn_tree_rules.txt index 5f89d9ed..59a1eff8 100644 --- a/regr_smlp/models/test78_model_dt_sklearn_tree_rules.txt +++ b/regr_smlp/models/test78_model_dt_sklearn_tree_rules.txt @@ -3,8 +3,8 @@ #TREE 0 if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 <= 0.7000000178813934) then (y1 = 0.0) and (y2 = 0.0) | based on 2 samples -if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 > 0.9000000059604645) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 <= 0.9000000059604645) then (y1 = 0.0) and (y2 = 0.0) | based on 1 samples if (x2 <= 0.4000000134110451) and (x2 > 0.10000000149011612) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples From 585456149d69d5dc5f4c66ed1d0e5152458de1a3 Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 20:21:57 +0300 Subject: [PATCH 12/20] added masters for tests 139 and 144 --- ...smlp_toy_num_resp_noknobs_data_bounds.json | 18 + ...resp_noknobs_dt_sklearn_model_complete.pkl | Bin 0 -> 2576 bytes ..._resp_noknobs_dt_sklearn_y1_tree_rules.txt | 10 + ..._resp_noknobs_dt_sklearn_y2_tree_rules.txt | 7 + ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 657 bytes ..._num_resp_noknobs_model_features_dict.json | 10 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ...y_num_resp_noknobs_rerun_model_config.json | 172 ++++++++ ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 657 bytes ...smlp_toy_num_resp_noknobs_pred_labeled.txt | 392 ++++++++++++++++++ ..._labeled_labeled_prediction_precisions.csv | 3 + ...ed_labeled_labeled_predictions_summary.csv | 12 + ...nobs_pred_labeled_missing_values_dict.json | 5 + ...pred_labeled_new_prediction_precisions.csv | 3 + ...s_pred_labeled_new_predictions_summary.csv | 10 + ...red_labeled_test_prediction_precisions.csv | 3 + ..._pred_labeled_test_predictions_summary.csv | 4 + ...oy_num_resp_noknobs_pred_labeled_trace.csv | 12 + ...labeled_training_prediction_precisions.csv | 3 + ...d_labeled_training_predictions_summary.csv | 9 + ...p_noknobs_pred_labeled_verify_results.json | 38 ++ ..._resp_noknobs_y1_smlp_full_model_term.json | 1 + ...y_num_resp_noknobs_y1_smlp_model_term.json | 1 + ..._resp_noknobs_y2_smlp_full_model_term.json | 1 + ...y_num_resp_noknobs_y2_smlp_model_term.json | 1 + .../Test144_smlp_toy_num_resp_noknobs.txt | 270 ++++++++++++ ...smlp_toy_num_resp_noknobs_data_bounds.json | 22 + ...num_resp_noknobs_dt_sklearn_tree_rules.txt | 10 + ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 702 bytes ..._noknobs_labeled_prediction_precisions.csv | 3 + ...sp_noknobs_labeled_predictions_summary.csv | 12 + ..._num_resp_noknobs_missing_values_dict.json | 8 + ..._num_resp_noknobs_model_features_dict.json | 12 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 657 bytes ...num_resp_noknobs_smlp_full_model_term.json | 1 + ..._toy_num_resp_noknobs_smlp_model_term.json | 1 + ...esp_noknobs_test_prediction_precisions.csv | 3 + ..._resp_noknobs_test_predictions_summary.csv | 4 + ...est144_smlp_toy_num_resp_noknobs_trace.csv | 9 + ...noknobs_training_prediction_precisions.csv | 3 + ...p_noknobs_training_predictions_summary.csv | 9 + ...p_toy_num_resp_noknobs_verify_results.json | 23 + 43 files changed, 1107 insertions(+) create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_data_bounds.json create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_features_scaler.pkl create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_model_features_dict.json create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_model_levels_dict.json create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_rerun_model_config.json create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_responses_scaler.pkl create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json create mode 100644 regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json create mode 100644 regr_smlp/master/Test144_smlp_toy_num_resp_noknobs.txt create mode 100644 regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_data_bounds.json create mode 100644 regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt create mode 100644 regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_features_scaler.pkl create mode 100644 regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv create mode 100644 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regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_verify_results.json diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_data_bounds.json b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_data_bounds.json new file mode 100644 index 00000000..510fd80e --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_data_bounds.json @@ -0,0 +1,18 @@ +{ + "x1": { + "min": 2.0, + "max": 4.0 + }, + "x2": { + "min": 3.0, + "max": 8.0 + }, + "y1": { + "min": 5.0, + "max": 9.0 + }, + "y2": { + "min": 5.0, + "max": 9.0 + } +} \ No newline at end of file diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl new file mode 100644 index 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selection for response y2 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y2 : + Feature Score +1 x2 4.950294 +0 x1 1.115702 + +smlp_logger - INFO - MRMR feature selection for response y2 : end + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 +9 2.0 7 5 5 +10 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 +9 0.0 0.8 0.0 0.0 +10 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 2) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test139_smlp_toy_num_resp_noknobs_data_bounds.json + +smlp_logger - INFO - {'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - Preparing new data for modeling: start + +smlp_logger - INFO - loading new data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 9.000000 9.000000 8.000000 8.000000 9.000000 +mean 6.777778 7.222222 10.250000 2.875000 5.111111 +std 2.108185 2.108185 1.035098 0.834523 1.691482 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 9.750000 2.000000 4.000000 +50% 5.000000 9.000000 10.000000 3.000000 4.000000 +75% 9.000000 9.000000 11.000000 3.250000 6.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - new data + categ y1 y2 x0 x1 x2 +0 c0 5 9 10.0 2.0 3 +1 c12 9 9 12.0 NaN 4 +2 c2 5 9 NaN 3.0 4 +3 c17 5 5 11.0 2.0 6 +4 c18 9 5 10.0 2.0 8 +5 c8 9 9 9.0 4.0 7 +6 c7 5 5 9.0 3.0 6 +7 c3 5 5 10.0 3.0 4 +8 c12 9 9 11.0 4.0 4 + +smlp_logger - INFO - new data after imputing missing values + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after processing responses + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 + +smlp_logger - INFO - Preparing new data for modeling: end + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./Test139_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt + +smlp_logger - INFO - Writing tree rules into file ./Test139_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./Test139_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 8.000 + +smlp_logger - INFO - Prediction on test data -- r2_score: -1.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 2.182 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.450 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON NEW DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv + +smlp_logger - INFO - Prediction on new data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on new data -- r2_score: 0.325 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 4, 'ite': 2, 'and': 1, 'prop': 3, 'const': 14, 'sub': 3, 'var': 3} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv new file mode 100644 index 00000000..7d143a2f --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,2.909090909090909,0.2666666666666666 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv new file mode 100644 index 00000000..7a649b6a --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json new file mode 100644 index 00000000..6e4f6879 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json @@ -0,0 +1,5 @@ +{ + "x1": [ + 1 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv new file mode 100644 index 00000000..951115f0 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,3.5555555555555554,0.10000000000000009 +y2,1.7777777777777777,0.55 diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv new file mode 100644 index 00000000..3ba8f5c9 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv @@ -0,0 +1,10 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv new file mode 100644 index 00000000..fd947921 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,10.666666666666666,-2.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv new file mode 100644 index 00000000..3bb69252 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv new file mode 100644 index 00000000..7e422b02 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y0,y1 +interface_consistency,sat,7.0,3.0 +model_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 +ca,unsat +ce,sat,4.0,6.0,5.0,9.0 +ca,sat,7.0,6.75,9.0,9.0 +ce,sat,1.0,6.0,5.0,5.0 +ca,unsat +ce,sat,1.0,7.0,5.0,5.0 diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json new file mode 100644 index 00000000..6fb0d0ac --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -0,0 +1,38 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 4.0, + "y1": 5.0, + "x2": 6.0, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 5.0 + }, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json new file mode 100644 index 00000000..3c7d4f33 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y1': |:0| (/ 13421773 134217728))) 1 (ite (and (and (> |:0| (/ 23488103 33554432)) (<= |:1| (/ 1 4))) (<= |:0| (/ 30198989 33554432))) 0 (ite (and (and (> |:0| (/ 23488103 33554432)) (<= |:1| (/ 1 4))) (> |:0| (/ 30198989 33554432))) 1 (ite (and (<= |:0| (/ 23488103 33554432)) (> |:0| (/ 53687093 134217728))) 0 1))))) 4) 5)))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json new file mode 100644 index 00000000..d4363137 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': x2_scaled (/ 13421773 134217728))) 1 (ite (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))) 0 (ite (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))) 1 (ite (and (<= x2_scaled (/ 23488103 33554432)) (> x2_scaled (/ 53687093 134217728))) 0 1)))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json new file mode 100644 index 00000000..cc8b6220 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'y2': |:0| (/ 53687093 134217728)) (> (* (/ 1 2) (- x1 2)) (/ 3 4))) 1 (ite (<= |:0| (/ 53687093 134217728)) 1 0)) 4) 5))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json new file mode 100644 index 00000000..56c332c4 --- /dev/null +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json @@ -0,0 +1 @@ +"{'y2_scaled': x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (<= x2_scaled (/ 53687093 134217728)) 1 0))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs.txt b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs.txt new file mode 100644 index 00000000..adfed295 --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs.txt @@ -0,0 +1,270 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: x0**2+y1>4.3 + +smlp_logger - INFO - Assertion asrt2: (y1+x2)/2<6 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x0 x1 x2 y1 y2 +0 0.333333 0.0 0.0 0.0 1.0 +1 1.000000 0.0 0.2 1.0 1.0 +2 0.333333 0.5 0.2 0.0 1.0 +3 0.666667 0.0 0.6 0.0 0.0 +4 0.333333 0.0 1.0 1.0 0.0 +5 0.000000 1.0 0.8 1.0 1.0 +6 0.000000 0.5 0.6 0.0 0.0 +7 0.333333 0.5 0.2 0.0 0.0 +8 0.666667 1.0 0.2 1.0 1.0 +9 1.000000 0.0 0.8 0.0 0.0 +10 0.333333 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 3) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test144_smlp_toy_num_resp_noknobs_data_bounds.json + +smlp_logger - INFO - {'x0': {'min': 9.0, 'max': 12.0}, 'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./Test144_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test144_smlp_toy_num_resp_noknobs_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test144_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test144_smlp_toy_num_resp_noknobs_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test144_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on test data -- r2_score: 0.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test144_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test144_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 0.727 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.817 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Tree rules (branches) antecedent compression statistics for response(s) y1_scaled,y2_scaled: + trees count in the model 1 + tree branches/rules count 6 + antecedent lengths before 17 + antecedent lengths after 16 + branch length counts before {3: 1, 4: 2, 2: 3} + branch length counts after {3: 2, 2: 3, 4: 1} + tree max depth before 4 + tree max depth after 4 + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 14, 'ite': 5, 'and': 8, 'prop': 13, 'const': 47, 'sub': 13, 'var': 13} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 14, 'ite': 5, 'and': 8, 'prop': 13, 'const': 47, 'sub': 13, 'var': 13} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> x0**2+y1>4.3 + +smlp_logger - INFO - The configuration is consistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: PASS + +smlp_logger - INFO - Verifying assertion asrt2 <-> (y1+x2)/2<6 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_data_bounds.json b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_data_bounds.json new file mode 100644 index 00000000..5df59662 --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_data_bounds.json @@ -0,0 +1,22 @@ +{ + "x0": { + "min": 9.0, + "max": 12.0 + }, + "x1": { + "min": 2.0, + "max": 4.0 + }, + "x2": { + "min": 3.0, + "max": 8.0 + }, + "y1": { + "min": 5.0, + "max": 9.0 + }, + "y2": { + "min": 5.0, + "max": 9.0 + } +} \ No newline at end of file diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt new file mode 100644 index 00000000..c3f3f68c --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt @@ -0,0 +1,10 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x0 > 0.5000000149011612) then (y1 = 0.0) and (y2 = 0.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x0 <= 0.5000000149011612) and (x2 > 0.7000000178813934) then (y1 = 1.0) and (y2 = 0.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x0 <= 0.5000000149011612) and (x2 <= 0.7000000178813934) then (y1 = 0.0) and (y2 = 0.0) | based on 1 samples +if (x2 <= 0.4000000134110451) and (x0 > 0.6666666716337204) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples +if (x2 <= 0.4000000134110451) and (x0 <= 0.6666666716337204) then (y1 = 0.0) and (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_features_scaler.pkl b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_features_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..d12c53994522ad0d816235e1252c93c64f21f62b GIT binary patch literal 702 zcma))%}T>S6ovb%mHN|yir_|ERTsh5E?fu|x-+zb;!=ibI<>)M5@r%I0zX*4AWx*X2MKfgUDE(--m&$j_t!x6hFHt zb_qu|MIaVv==y!b@)$AP&Kur+OQ*xmQ+41&I7C zW+{qcHK&;ta};sx`i>;$gh+NXFDAIU2n5~f?wq3O7QeDAid5$t!S)Y=gd(Uf9Y%Vt z=@)pZ-QOua)j*MCTy;;s4_KFGZOT3B`Zlg^D!q;)^OSlu^sj`~9i5PfYi{Rj0`C3I tP>P*}xUT4ge8dnf#@`va*!xK_uQLiL-b!>z7`Htt_n~Z5jS7S<;{)9H^A`XB literal 0 HcmV?d00001 diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv new file mode 100644 index 00000000..cf088bcd --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv new file mode 100644 index 00000000..2cce12ec --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,5.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,5.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_missing_values_dict.json b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_missing_values_dict.json new file mode 100644 index 00000000..553bfe33 --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_missing_values_dict.json @@ -0,0 +1,8 @@ +{ + "x1": [ + 1 + ], + "x0": [ + 2 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_model_features_dict.json b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_model_features_dict.json new file mode 100644 index 00000000..8e6a1c9a --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_model_features_dict.json @@ -0,0 +1,12 @@ +{ + "y1": [ + "x0", + "x1", + "x2" + ], + "y2": [ + "x0", + "x1", + "x2" + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_model_levels_dict.json b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_model_levels_dict.json new file mode 100644 index 00000000..9e26dfee --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_model_levels_dict.json @@ -0,0 +1 @@ +{} \ No newline at end of file diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_responses_scaler.pkl b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_responses_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..f2576be20c9aab6434a4d801eeba1b3a7478a6ac GIT binary patch literal 657 zcma))PfG$p7{=XAi%@d~>(b4WUKW%N9RdY!EgIB0hH)L;rQO+OW;a|YsDq|3H{U*w zU!f1<|VkXuiTTG(>q!a1b(r7^V{fM$S;?Ao8Z?N3f99v3*#I>Q+UuOE|JA0&z-1 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00000000..452ad7e2 --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (<= x2_scaled (/ 23488103 33554432)) (> x2_scaled (/ 53687093 134217728))) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) 1 0)))))>, 'y2_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (<= x2_scaled (/ 23488103 33554432)) (> x2_scaled (/ 53687093 134217728))) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) 0 0)))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv new file mode 100644 index 00000000..ec56b74c --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_test_predictions_summary.csv b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_test_predictions_summary.csv new file mode 100644 index 00000000..3477d51d --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,5.0,9.0 +2,5.0,9.0,5.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_trace.csv new file mode 100644 index 00000000..eb2af845 --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_trace.csv @@ -0,0 +1,9 @@ +stage,solver,x0,x1,x2,y1,y2 +interface_consistency,sat,0,7,3 +model_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +witness_consistency,sat,0,1,805306377/134217728,5,5 +ca,sat,0,1,6,5,5 +ce,unsat +ca,sat,0,7,671088649/134217728,5,9 +ce,sat,0,7,805306377/134217728,9,9 diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_training_predictions_summary.csv b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_verify_results.json new file mode 100644 index 00000000..d670b00a --- /dev/null +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_verify_results.json @@ -0,0 +1,23 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "PASS", + "counter_example": null, + "assertion_feasible": true + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x0": 0.0, + "x1": 7.0, + "y1": 9.0, + "x2": 6.000000067055225, + "y2": 9.0 + }, + "assertion_feasible": true + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file From 2e752cbb0474b0be8db15ac2901592eed0e0dceb Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 22:38:17 +0300 Subject: [PATCH 13/20] added masters for tests 162 and 163 --- ...smlp_toy_num_resp_noknobs_data_bounds.json | 18 + ...resp_noknobs_dt_sklearn_model_complete.pkl | Bin 0 -> 2576 bytes ..._resp_noknobs_dt_sklearn_y1_tree_rules.txt | 10 + ..._resp_noknobs_dt_sklearn_y2_tree_rules.txt | 7 + ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 657 bytes ..._num_resp_noknobs_model_features_dict.json | 10 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ...y_num_resp_noknobs_rerun_model_config.json | 172 ++++++++ ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 657 bytes ...smlp_toy_num_resp_noknobs_pred_labeled.txt | 392 ++++++++++++++++++ ..._labeled_labeled_prediction_precisions.csv | 3 + ...ed_labeled_labeled_predictions_summary.csv | 12 + ...nobs_pred_labeled_missing_values_dict.json | 5 + ...pred_labeled_new_prediction_precisions.csv | 3 + ...s_pred_labeled_new_predictions_summary.csv | 10 + ...red_labeled_test_prediction_precisions.csv | 3 + ..._pred_labeled_test_predictions_summary.csv | 4 + ...oy_num_resp_noknobs_pred_labeled_trace.csv | 12 + ...labeled_training_prediction_precisions.csv | 3 + ...d_labeled_training_predictions_summary.csv | 9 + ...p_noknobs_pred_labeled_verify_results.json | 38 ++ ..._resp_noknobs_y1_smlp_full_model_term.json | 1 + ...y_num_resp_noknobs_y1_smlp_model_term.json | 1 + ..._resp_noknobs_y2_smlp_full_model_term.json | 1 + ...y_num_resp_noknobs_y2_smlp_model_term.json | 1 + ...smlp_toy_num_resp_noknobs_data_bounds.json | 18 + ...resp_noknobs_dt_sklearn_model_complete.pkl | Bin 0 -> 2192 bytes ...num_resp_noknobs_dt_sklearn_tree_rules.txt | 11 + ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 657 bytes ..._num_resp_noknobs_model_features_dict.json | 10 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ...y_num_resp_noknobs_rerun_model_config.json | 172 ++++++++ ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 657 bytes ...num_resp_noknobs_smlp_full_model_term.json | 1 + ..._toy_num_resp_noknobs_smlp_model_term.json | 1 + ...smlp_toy_num_resp_noknobs_pred_labeled.txt | 388 +++++++++++++++++ ..._labeled_labeled_prediction_precisions.csv | 3 + ...ed_labeled_labeled_predictions_summary.csv | 12 + ...nobs_pred_labeled_missing_values_dict.json | 5 + ...pred_labeled_new_prediction_precisions.csv | 3 + ...s_pred_labeled_new_predictions_summary.csv | 10 + ...red_labeled_test_prediction_precisions.csv | 3 + ..._pred_labeled_test_predictions_summary.csv | 4 + ...oy_num_resp_noknobs_pred_labeled_trace.csv | 12 + ...labeled_training_prediction_precisions.csv | 3 + ...d_labeled_training_predictions_summary.csv | 9 + ...p_noknobs_pred_labeled_verify_results.json | 38 ++ 47 files changed, 1420 insertions(+) create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_data_bounds.json create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_features_scaler.pkl create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_model_features_dict.json create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_model_levels_dict.json create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_rerun_model_config.json create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_responses_scaler.pkl create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json create mode 100644 regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json create mode 100644 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(x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 <= 0.9000000059604645) then (y1 = 0.0) | based on 1 samples +if (x2 <= 0.7000000178813934) and (x2 <= 0.4000000134110451) and (x2 > 0.10000000149011612) then (y1 = 1.0) | based on 1 samples +if (x2 <= 0.7000000178813934) and (x2 <= 0.4000000134110451) and (x2 <= 0.10000000149011612) then (y1 = 0.0) | based on 1 samples diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt new file mode 100644 index 00000000..5015336b --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt @@ -0,0 +1,7 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.4000000134110451) and (x1 <= 0.75) then (y2 = 0.0) | based on 5 samples +if (x2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y2 = 1.0) | based on 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a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_responses_scaler.pkl b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_responses_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..f2576be20c9aab6434a4d801eeba1b3a7478a6ac GIT binary patch literal 657 zcma))PfG$p7{=XAi%@d~>(b4WUKW%N9RdY!EgIB0hH)L;rQO+OW;a|YsDq|3H{U*w zU!f1<|VkXuiTTG(>q!a1b(r7^V{fM$S;?Ao8Z?N3f99v3*#I>Q+UuOE|JA0&z-1 z*N=45V?=jDC$KSNIFd$)5!0hQV4)dEBT-0%AdcuLm8_)A40_5C-ryD*hGM8Qu*#w^ z3L>Axh=9 + +smlp_logger - INFO - Assertion asrt3: y2<0 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 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0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 +9 0.0 0.8 0.0 0.0 +10 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 2) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test162_smlp_toy_num_resp_noknobs_data_bounds.json + +smlp_logger - INFO - {'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - Preparing new data for modeling: start + +smlp_logger - INFO - loading new data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 9.000000 9.000000 8.000000 8.000000 9.000000 +mean 6.777778 7.222222 10.250000 2.875000 5.111111 +std 2.108185 2.108185 1.035098 0.834523 1.691482 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 9.750000 2.000000 4.000000 +50% 5.000000 9.000000 10.000000 3.000000 4.000000 +75% 9.000000 9.000000 11.000000 3.250000 6.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - new data + categ y1 y2 x0 x1 x2 +0 c0 5 9 10.0 2.0 3 +1 c12 9 9 12.0 NaN 4 +2 c2 5 9 NaN 3.0 4 +3 c17 5 5 11.0 2.0 6 +4 c18 9 5 10.0 2.0 8 +5 c8 9 9 9.0 4.0 7 +6 c7 5 5 9.0 3.0 6 +7 c3 5 5 10.0 3.0 4 +8 c12 9 9 11.0 4.0 4 + +smlp_logger - INFO - new data after imputing missing values + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after processing responses + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 + +smlp_logger - INFO - Preparing new data for modeling: end + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt + +smlp_logger - INFO - Writing tree rules into file ./Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./Test162_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 8.000 + +smlp_logger - INFO - Prediction on test data -- r2_score: -1.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 2.182 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.450 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON NEW DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv + +smlp_logger - INFO - Prediction on new data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on new data -- r2_score: 0.325 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for dt_sklearn_y1: {'or': 6, 'not': 6, 'and': 10, 'prop': 23, 'mul': 25, 'const': 71, 'sub': 24, 'var': 24} + +smlp_logger - INFO - Model operator counts for dt_sklearn_y2: {'or': 3, 'not': 3, 'and': 2, 'prop': 9, 'mul': 11, 'const': 29, 'sub': 10, 'var': 10} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv new file mode 100644 index 00000000..7d143a2f --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,2.909090909090909,0.2666666666666666 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv new file mode 100644 index 00000000..7a649b6a --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json new file mode 100644 index 00000000..6e4f6879 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json @@ -0,0 +1,5 @@ +{ + "x1": [ + 1 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv new file mode 100644 index 00000000..951115f0 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,3.5555555555555554,0.10000000000000009 +y2,1.7777777777777777,0.55 diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv new file mode 100644 index 00000000..3ba8f5c9 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv @@ -0,0 +1,10 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv new file mode 100644 index 00000000..fd947921 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,10.666666666666666,-2.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv new file mode 100644 index 00000000..3bb69252 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv new file mode 100644 index 00000000..b03b562a --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y0,y1 +interface_consistency,sat,7.0,3.0 +model_consistency,sat,7.0,6.0,5.0,9.0 +witness_consistency,sat,7.0,6.0,5.0,9.0 +witness_consistency,sat,7.0,6.0,5.0,9.0 +witness_consistency,sat,7.0,6.0,5.0,9.0 +ca,unsat +ce,sat,1.0,6.0,5.0,5.0 +ca,sat,7.0,6.75,9.0,9.0 +ce,sat,7.0,6.0,5.0,9.0 +ca,unsat +ce,sat,7.0,6.0,5.0,9.0 diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json new file mode 100644 index 00000000..bfbd8788 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -0,0 +1,38 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 6.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 7.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 9.0 + }, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 7.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json new file mode 100644 index 00000000..c5e5f9a9 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'dt_sklearn_y1': [ (* (/ 1 5) (- x2 3)) (/ 23488103 33554432)) (> (* (/ 1 2) (- x1 2)) (/ 1 4)))) (= (* (/ 1 4) (- tree_0_y1 5)) 1))>, |:0| (/ 53687093 134217728)))) (= (* (/ 1 4) (- tree_0_y1 5)) 0)))>, |:0| (/ 23488103 33554432)) (<= (* (/ 1 2) (- x1 2)) (/ 1 4))) (> |:0| (/ 30198989 33554432)))) (= (* (/ 1 4) (- tree_0_y1 5)) 1)))>, |:0| (/ 23488103 33554432)) (<= (* (/ 1 2) (- x1 2)) (/ 1 4))) (<= |:0| (/ 30198989 33554432)))) (= (* (/ 1 4) (- tree_0_y1 5)) 0)))>, |:0| (/ 13421773 134217728)))) (= (* (/ 1 4) (- tree_0_y1 5)) 1)))>, , ]}" \ No newline at end of file diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json new file mode 100644 index 00000000..813118b7 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json @@ -0,0 +1 @@ +"{'dt_sklearn_y1_scaled': [ x2_scaled (/ 23488103 33554432)) (> x1_scaled (/ 1 4)))) (= tree_0_y1_scaled 1))>, x2_scaled (/ 53687093 134217728)))) (= tree_0_y1_scaled 0))>, x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432)))) (= tree_0_y1_scaled 1))>, x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432)))) (= tree_0_y1_scaled 0))>, x2_scaled (/ 13421773 134217728)))) (= tree_0_y1_scaled 1))>, , ]}" \ No newline at end of file diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json new file mode 100644 index 00000000..a7291f60 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'dt_sklearn_y2': [ (* (/ 1 5) (- x2 3)) (/ 53687093 134217728)) (<= (* (/ 1 2) (- x1 2)) (/ 3 4)))) (= (* (/ 1 4) (- tree_0_y2 5)) 0))>, , (* (/ 1 5) (- x2 3)) (/ 53687093 134217728)) (> (* (/ 1 2) (- x1 2)) (/ 3 4)))) (= (* (/ 1 4) (- tree_0_y2 5)) 1))>, ]}" \ No newline at end of file diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json new file mode 100644 index 00000000..b51f2381 --- /dev/null +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json @@ -0,0 +1 @@ +"{'dt_sklearn_y2_scaled': [ x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4)))) (= tree_0_y2_scaled 0))>, , x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4)))) (= tree_0_y2_scaled 1))>, ]}" \ No newline at end of file diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_data_bounds.json b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_data_bounds.json new file mode 100644 index 00000000..510fd80e --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_data_bounds.json @@ -0,0 +1,18 @@ +{ + "x1": { + "min": 2.0, + "max": 4.0 + }, + "x2": { + "min": 3.0, + "max": 8.0 + }, + "y1": { + "min": 5.0, + "max": 9.0 + }, + "y2": { + "min": 5.0, + "max": 9.0 + } +} \ No newline at end of file diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl new file mode 100644 index 0000000000000000000000000000000000000000..7cef3b591fe95ec7f7a1596357c4b544c2a2852b GIT binary patch literal 2192 zcmd5;&x;&I6z=KW$a|Q`|7=K zdiIO?Z+1FPxzw__6f>Wv1IZa1&>;4OU;@z+wx9EiBG6eFHI+{c&6@HS(OwbYw z#8v%z6gf?SwA6|YUS-i{DCv~@fy9Ee+!nDV$Ps zpT2qKaeuZOnFp4Lj4)ao1##=DML$%5fl@w+g)3GW6-M6y5Q7)+Cl`v8G z2X~Gokq}Y3NjEbpGZf=g;$`$L-bY@IZiH_&ho*Z$oa+#t4KI)mT7tHZ_5*!#TI=Hz zPp%;H!|)+YuFd%fl zoy~sps_-wKd8ruG$)S00T=Rgb%4PGRb9*-X&YZvNS)73ljdir7>+6wm%>G@AtL4Se zLzCC}-{;$=z>+Q0uzz{$U;mDupS?qk_{z}ovGE17Z{z6Z)9IhyomY4M{`k%ho~={C zULG3wGxL91|Lj~2+k_3f=biZJGJd}I?0l;2&OZOH!7mzHmRiDy$j{~(YrO%%YH@8 z{A#Ac{jvX5Y1Xd+8;`c04L;3(=;^B$W7VhThl5^WT>o2vzjtecGlSDmj0gV$IK!;? literal 0 HcmV?d00001 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt new file mode 100644 index 00000000..59a1eff8 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt @@ -0,0 +1,11 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 <= 0.7000000178813934) then (y1 = 0.0) and (y2 = 0.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 > 0.9000000059604645) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 <= 0.9000000059604645) then (y1 = 0.0) and (y2 = 0.0) | based on 1 samples +if (x2 <= 0.4000000134110451) and (x2 > 0.10000000149011612) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples +if (x2 <= 0.4000000134110451) and (x2 <= 0.10000000149011612) then (y1 = 0.0) and (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_features_scaler.pkl b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_features_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..62adbe18d720f124ad6845781cc0dc4fb0753242 GIT binary patch literal 657 zcma))&r1S96vy37`+=GY)ul^Ey)0-RIs^*dS~RG04C6ZL((ddsvl|Kpb{d{?E?~_ksJrR{S8KJzTXxlMZp>fiu_ z$TV%*#Dhx%CdP-0V3asU5XYt0E36ZhQwAkco1_=6@eoh7H7gl2&2)+A5e)>zEQ1V7T9{OADU|zTJ8D7bUu2>lYq#sGBp$4H<`?8qOr|4ewDa}s(z+M3d9?V^ T&<$bS_NZKO*{B*72;0UNhrsLs literal 0 HcmV?d00001 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_model_features_dict.json b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_model_features_dict.json new file mode 100644 index 00000000..85782d17 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_model_features_dict.json @@ -0,0 +1,10 @@ +{ + "y1": [ + "x1", + "x2" + ], + "y2": [ + "x1", + "x2" + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_model_levels_dict.json b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_model_levels_dict.json new file mode 100644 index 00000000..9e26dfee --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_model_levels_dict.json @@ -0,0 +1 @@ +{} \ No newline at end of file diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_rerun_model_config.json b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_rerun_model_config.json new file mode 100644 index 00000000..af13eb36 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_rerun_model_config.json @@ -0,0 +1,172 @@ +{ + "alpha": null, + "analytics_mode": "verify", + "approximate_fractions": true, + "assertions_expressions": "(y2**3+x2)/2<6;y1>=9;y2<0", + "assertions_names": "asrt1,asrt2,asrt3", + "beta": null, + "center_offset": "0", + "compress_rules": false, + "continuous_correlation_estimators": [ + "pearson", + "spearman" + ], + "correlations_and_mutual_information": true, + "data_scaler": "min_max", + "delta_absolute": 0.0, + "delta_relative": 0.01, + "discretization_algo": "uniform", + "discretization_bins": 10, + "discretization_labels": true, + "discretization_type": "category", + "discretize_numeric_features": null, + "doe_algo": null, + "doe_box_behnken_centers": 1, + "doe_central_composite_alpha": "o", + "doe_central_composite_center": "2,2", + "doe_central_composite_face": "ccf", + "doe_design_resolution": null, + "doe_factor_level_ranges": null, + "doe_num_samples": null, + "doe_prob_distribution": "Normal", + "doe_spec_file": null, + "dt_sklearn_ccp_alpha": 0.0, + "dt_sklearn_criterion": "squared_error", + "dt_sklearn_max_depth": 15, + "dt_sklearn_max_features": null, + "dt_sklearn_max_leaf_nodes": null, + "dt_sklearn_min_impurity_decrease": 0.0, + "dt_sklearn_min_samples_leaf": 1, + "dt_sklearn_min_samples_split": 2, + "dt_sklearn_min_weight_fraction_leaf": 0.0, + "dt_sklearn_random_state": null, + "dt_sklearn_splitter": "best", + "epsilon": 0.05, + "et_sklearn_bootstrap": true, + "et_sklearn_ccp_alpha": 0.0, + "et_sklearn_criterion": "squared_error", + "et_sklearn_max_depth": null, + "et_sklearn_max_features": 1.0, + "et_sklearn_max_leaf_nodes": null, + "et_sklearn_max_samples": null, + "et_sklearn_min_impurity_decrease": 0.0, + "et_sklearn_min_samples_leaf": 1, + "et_sklearn_min_samples_split": 2, + "et_sklearn_min_weight_fraction_leaf": 0.0, + "et_sklearn_n_estimators": 100, + "et_sklearn_random_state": null, + "et_sklearn_verbose": 0, + "et_sklearn_warm_start": false, + "eta": null, + "features": "x0,x1,x2", + "fraction_precision": 64, + "impute_responses": false, + "interactive_plots": false, + "keep_features": [], + "labeled_data": null, + "lemma_precision": 0, + "load_configuration": null, + "log_files_prefix": null, + "log_level": "info", + "log_mode": "w", + "log_time": false, + "model": "dt_sklearn", + "model_caret_cross_validation": true, + "model_caret_return_train_score": false, + "model_caret_verbose": true, + "model_name": null, + "model_per_response": false, + "mrmr_feat_count_for_correlation": 15, + "mrmr_feat_count_for_prediction": 2, + "mutual_information_method": "normalized", + "negative_value": 0, + "new_data": null, + "nn_keras_batch_size": 200, + "nn_keras_batches_grid": null, + "nn_keras_epochs": 2000, + "nn_keras_hid_activation": "relu", + "nn_keras_layers": "2,1", + "nn_keras_layers_grid": null, + "nn_keras_learning_rate": 0.001, + "nn_keras_learning_rates_grid": null, + "nn_keras_loss_function": "mse", + "nn_keras_loss_functions_grid": null, + "nn_keras_metrics": [ + "mse" + ], + "nn_keras_optimizer": "adam", + "nn_keras_out_activation": "linear", + "nn_keras_sequential_api": true, + "nn_keras_tuner_algo": null, + "nn_keras_weights_precision": null, + "nnet_encoding": "nested", + "objectives_expressions": null, + "objectives_names": "None", + "optimization_strategy": "eager", + "optimize_pareto": true, + "output_directory": "./", + "poly_sklearn_copy_X": true, + "poly_sklearn_degree": 2, + "poly_sklearn_fit_intercept": true, + "poly_sklearn_n_jobs": null, + "poly_sklearn_positive": false, + "positive_value": 1, + "prediction_plots": false, + "psg_max_dimension": 3, + "psg_quality_target": "Lift", + "psg_top_ranked": 15, + "query_expressions": null, + "query_names": "None", + "radius_absolute": null, + "radius_relative": null, + "response": "y1,y2", + "response_map": null, + "response_plots": false, + "response_to_bool": null, + "rf_sklearn_bootstrap": true, + "rf_sklearn_ccp_alpha": 0.0, + "rf_sklearn_criterion": "squared_error", + "rf_sklearn_max_depth": null, + "rf_sklearn_max_features": 1.0, + "rf_sklearn_max_leaf_nodes": null, + "rf_sklearn_max_samples": null, + "rf_sklearn_min_impurity_decrease": 0.0, + "rf_sklearn_min_samples_leaf": 1, + "rf_sklearn_min_samples_split": 2, + "rf_sklearn_min_weight_fraction_leaf": 0.0, + "rf_sklearn_n_estimators": 100, + "rf_sklearn_random_state": null, + "rf_sklearn_verbose": 0, + "rf_sklearn_warm_start": false, + "sample_weights_coef": 0, + "sample_weights_exponent": 0, + "sample_weights_intercept": 0, + "save_configuration": false, + "save_model": "false", + "save_model_rerun_configuration": true, + "scale_features": true, + "scale_objectives": true, + "scale_responses": true, + "seed": 10, + "setup_caret_data_split_shuffle": true, + "setup_caret_fold": 0, + "setup_caret_session_id": null, + "setup_caret_verbose": true, + "simplify_terms": false, + "solver": "z3", + "solver_logic": "ALL", + "solver_path": null, + "spec": "../specs/smlp_toy_num_resp_noknobs_verify.spec", + "split_test": 0.2, + "trace_anonymize": true, + "trace_precision": 3, + "trace_runtime": 0, + "train_first_n": 0, + "train_random_n": 0, + "train_uniform_n": 0, + "tree_encoding": "flat", + "tuner_caret_search_algorithm": "random", + "tuner_caret_tuner_verbose": true, + "use_model": "true", + "vacuity_check": true +} \ No newline at end of file diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_responses_scaler.pkl b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_responses_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..f2576be20c9aab6434a4d801eeba1b3a7478a6ac GIT binary patch literal 657 zcma))PfG$p7{=XAi%@d~>(b4WUKW%N9RdY!EgIB0hH)L;rQO+OW;a|YsDq|3H{U*w zU!f1<|VkXuiTTG(>q!a1b(r7^V{fM$S;?Ao8Z?N3f99v3*#I>Q+UuOE|JA0&z-1 z*N=45V?=jDC$KSNIFd$)5!0hQV4)dEBT-0%AdcuLm8_)A40_5C-ryD*hGM8Qu*#w^ z3L>Axh |:0| (/ 53687093 134217728)) (<= (* (/ 1 2) (- x1 2)) (/ 3 4))) (<= |:0| (/ 23488103 33554432)))) (and (= (* (/ 1 4) (- tree_0_y1 5)) 0) (= (* (/ 1 4) (- tree_0_y2 5)) 0))))>, (* (/ 1 5) (- x2 3)) (/ 53687093 134217728)) (> (* (/ 1 2) (- x1 2)) (/ 3 4)))) (and (= (* (/ 1 4) (- tree_0_y1 5)) 1) (= (* (/ 1 4) (- tree_0_y2 5)) 1)))>, |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (> |:1| (/ 1 4)))) (and (= (* (/ 1 4) (- tree_0_y1 5)) 1) (= (* (/ 1 4) (- tree_0_y2 5)) 0)))))>, |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (> |:0| (/ 30198989 33554432)))) (and (= (* (/ 1 4) (- tree_0_y1 5)) 1) (= (* (/ 1 4) (- tree_0_y2 5)) 0)))))>, |:0| (/ 53687093 134217728)) (<= |:1| (/ 3 4))) (> |:0| (/ 23488103 33554432))) (<= |:1| (/ 1 4))) (<= |:0| (/ 30198989 33554432)))) (and (= (* (/ 1 4) (- tree_0_y1 5)) 0) (= (* (/ 1 4) (- tree_0_y2 5)) 0)))))>, |:0| (/ 13421773 134217728)))) (and (= (* (/ 1 4) (- tree_0_y1 5)) 1) (= (* (/ 1 4) (- tree_0_y2 5)) 1))))>, , , ]}" \ No newline at end of file diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_model_term.json b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_model_term.json new file mode 100644 index 00000000..1104cd11 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_model_term.json @@ -0,0 +1 @@ +"{'dt_sklearn': [ x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x2_scaled (/ 23488103 33554432)))) (and (= tree_0_y1_scaled 0) (= tree_0_y2_scaled 0)))>, x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4)))) (and (= tree_0_y1_scaled 1) (= tree_0_y2_scaled 1)))>, x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (> x1_scaled (/ 1 4)))) (and (= tree_0_y1_scaled 1) (= tree_0_y2_scaled 0)))>, x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432)))) (and (= tree_0_y1_scaled 1) (= tree_0_y2_scaled 0)))>, x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432)))) (and (= tree_0_y1_scaled 0) (= tree_0_y2_scaled 0)))>, x2_scaled (/ 13421773 134217728)))) (and (= tree_0_y1_scaled 1) (= tree_0_y2_scaled 1)))>, , , ]}" \ No newline at end of file diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt new file mode 100644 index 00000000..93b08c65 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt @@ -0,0 +1,388 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 + +smlp_logger - INFO - Assertion asrt2: y1>=9 + +smlp_logger - INFO - Assertion asrt3: y2<0 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - MRMR feature selection for response y1 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y1 : + Feature Score +0 x1 1.115702 +1 x2 0.944056 + +smlp_logger - INFO - MRMR feature selection for response y1 : end + +smlp_logger - INFO - MRMR feature selection for response y2 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y2 : + Feature Score +1 x2 4.950294 +0 x1 1.115702 + +smlp_logger - INFO - MRMR feature selection for response y2 : end + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 +9 2.0 7 5 5 +10 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 +9 0.0 0.8 0.0 0.0 +10 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 2) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test163_smlp_toy_num_resp_noknobs_data_bounds.json + +smlp_logger - INFO - {'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - Preparing new data for modeling: start + +smlp_logger - INFO - loading new data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 9.000000 9.000000 8.000000 8.000000 9.000000 +mean 6.777778 7.222222 10.250000 2.875000 5.111111 +std 2.108185 2.108185 1.035098 0.834523 1.691482 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 9.750000 2.000000 4.000000 +50% 5.000000 9.000000 10.000000 3.000000 4.000000 +75% 9.000000 9.000000 11.000000 3.250000 6.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - new data + categ y1 y2 x0 x1 x2 +0 c0 5 9 10.0 2.0 3 +1 c12 9 9 12.0 NaN 4 +2 c2 5 9 NaN 3.0 4 +3 c17 5 5 11.0 2.0 6 +4 c18 9 5 10.0 2.0 8 +5 c8 9 9 9.0 4.0 7 +6 c7 5 5 9.0 3.0 6 +7 c3 5 5 10.0 3.0 4 +8 c12 9 9 11.0 4.0 4 + +smlp_logger - INFO - new data after imputing missing values + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after processing responses + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 + +smlp_logger - INFO - Preparing new data for modeling: end + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./Test163_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./Test163_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 8.000 + +smlp_logger - INFO - Prediction on test data -- r2_score: -1.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 2.182 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.450 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON NEW DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv + +smlp_logger - INFO - Prediction on new data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on new data -- r2_score: 0.325 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for dt_sklearn: {'or': 7, 'not': 7, 'and': 23, 'prop': 39, 'mul': 43, 'const': 121, 'sub': 41, 'var': 41} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv new file mode 100644 index 00000000..7d143a2f --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,2.909090909090909,0.2666666666666666 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv new file mode 100644 index 00000000..7a649b6a --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json new file mode 100644 index 00000000..6e4f6879 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json @@ -0,0 +1,5 @@ +{ + "x1": [ + 1 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv new file mode 100644 index 00000000..951115f0 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,3.5555555555555554,0.10000000000000009 +y2,1.7777777777777777,0.55 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv new file mode 100644 index 00000000..3ba8f5c9 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv @@ -0,0 +1,10 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv new file mode 100644 index 00000000..fd947921 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,10.666666666666666,-2.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv new file mode 100644 index 00000000..3bb69252 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv new file mode 100644 index 00000000..d02bcf19 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y0,y1 +interface_consistency,sat,7.0,3.0 +model_consistency,sat,7.0,6.75,9.0,9.0 +witness_consistency,sat,7.0,6.75,9.0,9.0 +witness_consistency,sat,7.0,6.75,9.0,9.0 +witness_consistency,sat,7.0,6.75,9.0,9.0 +ca,unsat +ce,sat,1.0,6.0,5.0,5.0 +ca,sat,7.0,4.5,9.0,9.0 +ce,sat,7.0,3.0,5.0,9.0 +ca,unsat +ce,sat,7.0,3.0,5.0,9.0 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json new file mode 100644 index 00000000..ecf438cc --- /dev/null +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -0,0 +1,38 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 6.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 7.0, + "y1": 5.0, + "x2": 3.0, + "y2": 9.0 + }, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 7.0, + "y1": 5.0, + "x2": 3.0, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file From 88cdb5f75206bf55f03a434aa87b5bce910872a8 Mon Sep 17 00:00:00 2001 From: zurabksmlp Date: Mon, 1 Jun 2026 23:19:50 +0300 Subject: [PATCH 14/20] added masters for tests 184,185,186 --- ...smlp_toy_num_resp_noknobs_data_bounds.json | 18 + ...resp_noknobs_dt_sklearn_model_complete.pkl | Bin 0 -> 2576 bytes ..._resp_noknobs_dt_sklearn_y1_tree_rules.txt | 10 + ..._resp_noknobs_dt_sklearn_y2_tree_rules.txt | 7 + ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 657 bytes ..._num_resp_noknobs_model_features_dict.json | 10 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ...y_num_resp_noknobs_rerun_model_config.json | 172 ++++++++ ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 657 bytes ...smlp_toy_num_resp_noknobs_pred_labeled.txt | 410 ++++++++++++++++++ ..._labeled_labeled_prediction_precisions.csv | 3 + ...ed_labeled_labeled_predictions_summary.csv | 12 + ...nobs_pred_labeled_missing_values_dict.json | 5 + ...pred_labeled_new_prediction_precisions.csv | 3 + ...s_pred_labeled_new_predictions_summary.csv | 10 + ...red_labeled_test_prediction_precisions.csv | 3 + ..._pred_labeled_test_predictions_summary.csv | 4 + ...oy_num_resp_noknobs_pred_labeled_trace.csv | 12 + ...labeled_training_prediction_precisions.csv | 3 + ...d_labeled_training_predictions_summary.csv | 9 + ...p_noknobs_pred_labeled_verify_results.json | 38 ++ ..._resp_noknobs_y1_smlp_full_model_term.json | 1 + ...y_num_resp_noknobs_y1_smlp_model_term.json | 1 + ..._resp_noknobs_y2_smlp_full_model_term.json | 1 + ...y_num_resp_noknobs_y2_smlp_model_term.json | 1 + ...smlp_toy_num_resp_noknobs_data_bounds.json | 18 + ...resp_noknobs_dt_sklearn_model_complete.pkl | Bin 0 -> 2576 bytes ..._resp_noknobs_dt_sklearn_y1_tree_rules.txt | 10 + ..._resp_noknobs_dt_sklearn_y2_tree_rules.txt | 7 + ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 657 bytes ..._num_resp_noknobs_model_features_dict.json | 10 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ...y_num_resp_noknobs_rerun_model_config.json | 172 ++++++++ ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 657 bytes ...smlp_toy_num_resp_noknobs_pred_labeled.txt | 410 ++++++++++++++++++ ..._labeled_labeled_prediction_precisions.csv | 3 + ...ed_labeled_labeled_predictions_summary.csv | 12 + ...nobs_pred_labeled_missing_values_dict.json | 5 + ...pred_labeled_new_prediction_precisions.csv | 3 + ...s_pred_labeled_new_predictions_summary.csv | 10 + ...red_labeled_test_prediction_precisions.csv | 3 + ..._pred_labeled_test_predictions_summary.csv | 4 + ...oy_num_resp_noknobs_pred_labeled_trace.csv | 12 + ...labeled_training_prediction_precisions.csv | 3 + ...d_labeled_training_predictions_summary.csv | 9 + ...p_noknobs_pred_labeled_verify_results.json | 38 ++ ..._resp_noknobs_y1_smlp_full_model_term.json | 1 + ...y_num_resp_noknobs_y1_smlp_model_term.json | 1 + ..._resp_noknobs_y2_smlp_full_model_term.json | 1 + ...y_num_resp_noknobs_y2_smlp_model_term.json | 1 + ...smlp_toy_num_resp_noknobs_data_bounds.json | 18 + ...resp_noknobs_dt_sklearn_model_complete.pkl | Bin 0 -> 2192 bytes ...num_resp_noknobs_dt_sklearn_tree_rules.txt | 11 + ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 0 -> 657 bytes ..._num_resp_noknobs_model_features_dict.json | 10 + ...oy_num_resp_noknobs_model_levels_dict.json | 1 + ...y_num_resp_noknobs_rerun_model_config.json | 172 ++++++++ ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 0 -> 657 bytes ...num_resp_noknobs_smlp_full_model_term.json | 1 + ..._toy_num_resp_noknobs_smlp_model_term.json | 1 + ...smlp_toy_num_resp_noknobs_pred_labeled.txt | 404 +++++++++++++++++ ..._labeled_labeled_prediction_precisions.csv | 3 + ...ed_labeled_labeled_predictions_summary.csv | 12 + ...nobs_pred_labeled_missing_values_dict.json | 5 + ...pred_labeled_new_prediction_precisions.csv | 3 + ...s_pred_labeled_new_predictions_summary.csv | 10 + ...red_labeled_test_prediction_precisions.csv | 3 + ..._pred_labeled_test_predictions_summary.csv | 4 + ...oy_num_resp_noknobs_pred_labeled_trace.csv | 12 + ...labeled_training_prediction_precisions.csv | 3 + ...d_labeled_training_predictions_summary.csv | 9 + ...p_noknobs_pred_labeled_verify_results.json | 38 ++ 72 files changed, 2188 insertions(+) create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_data_bounds.json create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_features_scaler.pkl create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_model_features_dict.json create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_model_levels_dict.json create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_rerun_model_config.json create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_responses_scaler.pkl create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt create mode 100644 regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv create mode 100644 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a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt new file mode 100644 index 00000000..5015336b --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt @@ -0,0 +1,7 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.4000000134110451) and (x1 <= 0.75) then (y2 = 0.0) | based on 5 samples +if (x2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_features_scaler.pkl b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_features_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..62adbe18d720f124ad6845781cc0dc4fb0753242 GIT binary patch literal 657 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\ No newline at end of file diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_rerun_model_config.json b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_rerun_model_config.json new file mode 100644 index 00000000..4eeebbb7 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_rerun_model_config.json @@ -0,0 +1,172 @@ +{ + "alpha": null, + "analytics_mode": "verify", + "approximate_fractions": true, + "assertions_expressions": "(y2**3+x2)/2<6;y1>=9;y2<0", + "assertions_names": "asrt1,asrt2,asrt3", + "beta": null, + "center_offset": "0", + "compress_rules": false, + "continuous_correlation_estimators": [ + "pearson", + "spearman" + ], + "correlations_and_mutual_information": true, + "data_scaler": "min_max", + "delta_absolute": 0.0, + "delta_relative": 0.01, + "discretization_algo": "uniform", + "discretization_bins": 10, + "discretization_labels": true, + "discretization_type": "category", + "discretize_numeric_features": null, + "doe_algo": null, + "doe_box_behnken_centers": 1, + "doe_central_composite_alpha": "o", + "doe_central_composite_center": "2,2", + "doe_central_composite_face": "ccf", + "doe_design_resolution": null, + "doe_factor_level_ranges": null, + "doe_num_samples": null, + "doe_prob_distribution": "Normal", + "doe_spec_file": null, + "dt_sklearn_ccp_alpha": 0.0, + "dt_sklearn_criterion": "squared_error", + "dt_sklearn_max_depth": 15, + "dt_sklearn_max_features": null, + "dt_sklearn_max_leaf_nodes": null, + "dt_sklearn_min_impurity_decrease": 0.0, + "dt_sklearn_min_samples_leaf": 1, + "dt_sklearn_min_samples_split": 2, + "dt_sklearn_min_weight_fraction_leaf": 0.0, + "dt_sklearn_random_state": null, + "dt_sklearn_splitter": "best", + "epsilon": 0.05, + "et_sklearn_bootstrap": true, + "et_sklearn_ccp_alpha": 0.0, + "et_sklearn_criterion": "squared_error", + "et_sklearn_max_depth": null, + "et_sklearn_max_features": 1.0, + "et_sklearn_max_leaf_nodes": null, + "et_sklearn_max_samples": null, + "et_sklearn_min_impurity_decrease": 0.0, + "et_sklearn_min_samples_leaf": 1, + "et_sklearn_min_samples_split": 2, + "et_sklearn_min_weight_fraction_leaf": 0.0, + "et_sklearn_n_estimators": 100, + "et_sklearn_random_state": null, + "et_sklearn_verbose": 0, + "et_sklearn_warm_start": false, + "eta": null, + "features": "x0,x1,x2", + "fraction_precision": 64, + "impute_responses": false, + "interactive_plots": false, + "keep_features": [], + "labeled_data": null, + "lemma_precision": 0, + "load_configuration": null, + "log_files_prefix": null, + "log_level": "info", + "log_mode": "w", + "log_time": false, + "model": "dt_sklearn", + "model_caret_cross_validation": true, + "model_caret_return_train_score": false, + "model_caret_verbose": true, + "model_name": null, + "model_per_response": true, + "mrmr_feat_count_for_correlation": 15, + "mrmr_feat_count_for_prediction": 2, + "mutual_information_method": "normalized", + "negative_value": 0, + "new_data": null, + "nn_keras_batch_size": 200, + "nn_keras_batches_grid": null, + "nn_keras_epochs": 2000, + "nn_keras_hid_activation": "relu", + "nn_keras_layers": "2,1", + "nn_keras_layers_grid": null, + "nn_keras_learning_rate": 0.001, + "nn_keras_learning_rates_grid": null, + "nn_keras_loss_function": "mse", + "nn_keras_loss_functions_grid": null, + "nn_keras_metrics": [ + "mse" + ], + "nn_keras_optimizer": "adam", + "nn_keras_out_activation": "linear", + "nn_keras_sequential_api": true, + "nn_keras_tuner_algo": null, + "nn_keras_weights_precision": null, + "nnet_encoding": "nested", + "objectives_expressions": null, + "objectives_names": "None", + "optimization_strategy": "eager", + "optimize_pareto": true, + "output_directory": "./", + "poly_sklearn_copy_X": true, + "poly_sklearn_degree": 2, + "poly_sklearn_fit_intercept": true, + "poly_sklearn_n_jobs": null, + "poly_sklearn_positive": false, + "positive_value": 1, + "prediction_plots": false, + "psg_max_dimension": 3, + "psg_quality_target": "Lift", + "psg_top_ranked": 15, + "query_expressions": null, + "query_names": "None", + "radius_absolute": null, + "radius_relative": null, + "response": "y1,y2", + "response_map": null, + "response_plots": false, + "response_to_bool": null, + "rf_sklearn_bootstrap": true, + "rf_sklearn_ccp_alpha": 0.0, + "rf_sklearn_criterion": "squared_error", + "rf_sklearn_max_depth": null, + "rf_sklearn_max_features": 1.0, + "rf_sklearn_max_leaf_nodes": null, + "rf_sklearn_max_samples": null, + "rf_sklearn_min_impurity_decrease": 0.0, + "rf_sklearn_min_samples_leaf": 1, + "rf_sklearn_min_samples_split": 2, + "rf_sklearn_min_weight_fraction_leaf": 0.0, + "rf_sklearn_n_estimators": 100, + "rf_sklearn_random_state": null, + "rf_sklearn_verbose": 0, + "rf_sklearn_warm_start": false, + "sample_weights_coef": 0, + "sample_weights_exponent": 0, + "sample_weights_intercept": 0, + "save_configuration": false, + "save_model": "false", + "save_model_rerun_configuration": true, + "scale_features": true, + "scale_objectives": true, + "scale_responses": true, + "seed": 10, + "setup_caret_data_split_shuffle": true, + "setup_caret_fold": 0, + "setup_caret_session_id": null, + "setup_caret_verbose": true, + "simplify_terms": false, + "solver": "z3", + "solver_logic": "ALL", + "solver_path": null, + "spec": "../specs/smlp_toy_num_resp_noknobs_verify.spec", + "split_test": 0.2, + "trace_anonymize": true, + "trace_precision": 3, + "trace_runtime": 0, + "train_first_n": 0, + "train_random_n": 0, + "train_uniform_n": 0, + "tree_encoding": "branched", + "tuner_caret_search_algorithm": "random", + "tuner_caret_tuner_verbose": true, + "use_model": "true", + "vacuity_check": true +} \ No newline at end of file diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_responses_scaler.pkl b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_responses_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..f2576be20c9aab6434a4d801eeba1b3a7478a6ac GIT binary patch literal 657 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NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - MRMR feature selection for response y1 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y1 : + Feature Score +0 x1 1.115702 +1 x2 0.944056 + +smlp_logger - INFO - MRMR feature selection for response y1 : end + +smlp_logger - INFO - MRMR feature selection for response y2 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y2 : + Feature Score +1 x2 4.950294 +0 x1 1.115702 + +smlp_logger - INFO - MRMR feature selection for response y2 : end + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 +9 2.0 7 5 5 +10 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 +9 0.0 0.8 0.0 0.0 +10 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 2) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test184_smlp_toy_num_resp_noknobs_data_bounds.json + +smlp_logger - INFO - {'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - Preparing new data for modeling: start + +smlp_logger - INFO - loading new data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 9.000000 9.000000 8.000000 8.000000 9.000000 +mean 6.777778 7.222222 10.250000 2.875000 5.111111 +std 2.108185 2.108185 1.035098 0.834523 1.691482 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 9.750000 2.000000 4.000000 +50% 5.000000 9.000000 10.000000 3.000000 4.000000 +75% 9.000000 9.000000 11.000000 3.250000 6.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - new data + categ y1 y2 x0 x1 x2 +0 c0 5 9 10.0 2.0 3 +1 c12 9 9 12.0 NaN 4 +2 c2 5 9 NaN 3.0 4 +3 c17 5 5 11.0 2.0 6 +4 c18 9 5 10.0 2.0 8 +5 c8 9 9 9.0 4.0 7 +6 c7 5 5 9.0 3.0 6 +7 c3 5 5 10.0 3.0 4 +8 c12 9 9 11.0 4.0 4 + +smlp_logger - INFO - new data after imputing missing values + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after processing responses + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 + +smlp_logger - INFO - Preparing new data for modeling: end + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt + +smlp_logger - INFO - Writing tree rules into file ./Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./Test184_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 8.000 + +smlp_logger - INFO - Prediction on test data -- r2_score: -1.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 2.182 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.450 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON NEW DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv + +smlp_logger - INFO - Prediction on new data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on new data -- r2_score: 0.325 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_0: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_1: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_2: {'and': 5, 'or': 2, 'not': 2, 'prop': 8, 'var': 8, 'const': 20, 'mul': 6, 'sub': 6} + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_3: {'and': 5, 'or': 2, 'not': 2, 'prop': 8, 'var': 8, 'const': 20, 'mul': 6, 'sub': 6} + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_4: {'and': 5, 'or': 2, 'not': 2, 'prop': 8, 'var': 8, 'const': 20, 'mul': 6, 'sub': 6} + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_5: {'and': 5, 'or': 2, 'not': 2, 'prop': 8, 'var': 8, 'const': 20, 'mul': 6, 'sub': 6} + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 1, 'ite': 5, 'prop': 5, 'var': 5, 'const': 13} + +smlp_logger - INFO - Model operator counts for antecedent_y2_scaled_tree_0_rule_0: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for antecedent_y2_scaled_tree_0_rule_1: {'and': 1, 'or': 2, 'not': 2, 'prop': 4, 'var': 4, 'const': 8, 'mul': 2, 'sub': 2} + +smlp_logger - INFO - Model operator counts for antecedent_y2_scaled_tree_0_rule_2: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 1, 'ite': 2, 'prop': 2, 'var': 2, 'const': 7} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv new file mode 100644 index 00000000..7d143a2f --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,2.909090909090909,0.2666666666666666 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv new file mode 100644 index 00000000..7a649b6a --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json new file mode 100644 index 00000000..6e4f6879 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json @@ -0,0 +1,5 @@ +{ + "x1": [ + 1 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv new file mode 100644 index 00000000..951115f0 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,3.5555555555555554,0.10000000000000009 +y2,1.7777777777777777,0.55 diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv new file mode 100644 index 00000000..3ba8f5c9 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv @@ -0,0 +1,10 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv new file mode 100644 index 00000000..fd947921 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,10.666666666666666,-2.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv new file mode 100644 index 00000000..3bb69252 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv new file mode 100644 index 00000000..d7a466e1 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y0,y1 +interface_consistency,sat,7.0,3.0 +model_consistency,sat,1.0,6.0,5.0,5.0 +witness_consistency,sat,1.0,6.0,5.0,5.0 +witness_consistency,sat,1.0,6.0,5.0,5.0 +witness_consistency,sat,1.0,6.0,5.0,5.0 +ca,unsat +ce,sat,1.0,3.5,5.0,9.0 +ca,sat,4.0,4.5,9.0,9.0 +ce,sat,1.0,6.0,5.0,5.0 +ca,unsat +ce,sat,1.0,7.0,5.0,5.0 diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json new file mode 100644 index 00000000..12ff6934 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -0,0 +1,38 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 3.5, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 5.0 + }, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json new file mode 100644 index 00000000..05903661 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'antecedent_y1_scaled_tree_0_rule_0': = antecedent_y1_scaled_tree_0_rule_0 0))) (let ((|:1| (and (> (* (/ 1 5) (- x2 3)) (/ 23488103 33554432)) (> (* (/ 1 2) (- x1 2)) (/ 1 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_1': = antecedent_y1_scaled_tree_0_rule_1 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (<= |:1| (/ 23488103 33554432)) (> |:1| (/ 53687093 134217728))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'antecedent_y1_scaled_tree_0_rule_2': = antecedent_y1_scaled_tree_0_rule_2 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (and (> |:1| (/ 23488103 33554432)) (<= (* (/ 1 2) (- x1 2)) (/ 1 4))) (> |:1| (/ 30198989 33554432))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'antecedent_y1_scaled_tree_0_rule_3': = antecedent_y1_scaled_tree_0_rule_3 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (and (> |:1| (/ 23488103 33554432)) (<= (* (/ 1 2) (- x1 2)) (/ 1 4))) (<= |:1| (/ 30198989 33554432))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'antecedent_y1_scaled_tree_0_rule_4': = antecedent_y1_scaled_tree_0_rule_4 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (and (<= |:1| (/ 23488103 33554432)) (<= |:1| (/ 53687093 134217728))) (> |:1| (/ 13421773 134217728))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'antecedent_y1_scaled_tree_0_rule_5': = antecedent_y1_scaled_tree_0_rule_5 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (and (<= |:1| (/ 23488103 33554432)) (<= |:1| (/ 53687093 134217728))) (<= |:1| (/ 13421773 134217728))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'y1': = antecedent_y1_scaled_tree_0_rule_5 0) 0 (ite (>= antecedent_y1_scaled_tree_0_rule_4 0) 1 (ite (>= antecedent_y1_scaled_tree_0_rule_3 0) 0 (ite (>= antecedent_y1_scaled_tree_0_rule_2 0) 1 (ite (>= antecedent_y1_scaled_tree_0_rule_1 0) 0 1))))) 4) 5)>}" \ No newline at end of file diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json new file mode 100644 index 00000000..470d650f --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': = antecedent_y1_scaled_tree_0_rule_5 0) 0 (ite (>= antecedent_y1_scaled_tree_0_rule_4 0) 1 (ite (>= antecedent_y1_scaled_tree_0_rule_3 0) 0 (ite (>= antecedent_y1_scaled_tree_0_rule_2 0) 1 (ite (>= antecedent_y1_scaled_tree_0_rule_1 0) 0 1)))))>, 'antecedent_y1_scaled_tree_0_rule_0': = antecedent_y1_scaled_tree_0_rule_0 0))) (let ((|:1| (and (> x2_scaled (/ 23488103 33554432)) (> x1_scaled (/ 1 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_1': = antecedent_y1_scaled_tree_0_rule_1 0))) (let ((|:1| (and (<= x2_scaled (/ 23488103 33554432)) (> x2_scaled (/ 53687093 134217728))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_2': = antecedent_y1_scaled_tree_0_rule_2 0))) (let ((|:1| (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_3': = antecedent_y1_scaled_tree_0_rule_3 0))) (let ((|:1| (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_4': = antecedent_y1_scaled_tree_0_rule_4 0))) (let ((|:1| (and (and (<= x2_scaled (/ 23488103 33554432)) (<= x2_scaled (/ 53687093 134217728))) (> x2_scaled (/ 13421773 134217728))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_5': = antecedent_y1_scaled_tree_0_rule_5 0))) (let ((|:1| (and (and (<= x2_scaled (/ 23488103 33554432)) (<= x2_scaled (/ 53687093 134217728))) (<= x2_scaled (/ 13421773 134217728))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json new file mode 100644 index 00000000..41e3b5de --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'antecedent_y2_scaled_tree_0_rule_0': = antecedent_y2_scaled_tree_0_rule_0 0))) (let ((|:1| (and (> (* (/ 1 5) (- x2 3)) (/ 53687093 134217728)) (<= (* (/ 1 2) (- x1 2)) (/ 3 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y2_scaled_tree_0_rule_1': = antecedent_y2_scaled_tree_0_rule_1 0))) (let ((|:1| (<= (* (/ 1 5) (- x2 3)) (/ 53687093 134217728)))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y2_scaled_tree_0_rule_2': = antecedent_y2_scaled_tree_0_rule_2 0))) (let ((|:1| (and (> (* (/ 1 5) (- x2 3)) (/ 53687093 134217728)) (> (* (/ 1 2) (- x1 2)) (/ 3 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'y2': = antecedent_y2_scaled_tree_0_rule_2 0) 1 (ite (>= antecedent_y2_scaled_tree_0_rule_1 0) 1 0)) 4) 5)>}" \ No newline at end of file diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json new file mode 100644 index 00000000..e5382ce6 --- /dev/null +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json @@ -0,0 +1 @@ +"{'y2_scaled': = antecedent_y2_scaled_tree_0_rule_2 0) 1 (ite (>= antecedent_y2_scaled_tree_0_rule_1 0) 1 0))>, 'antecedent_y2_scaled_tree_0_rule_0': = antecedent_y2_scaled_tree_0_rule_0 0))) (let ((|:1| (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y2_scaled_tree_0_rule_1': = antecedent_y2_scaled_tree_0_rule_1 0))) (let ((|:1| (<= x2_scaled (/ 53687093 134217728)))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y2_scaled_tree_0_rule_2': = antecedent_y2_scaled_tree_0_rule_2 0))) (let ((|:1| (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_data_bounds.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_data_bounds.json new file mode 100644 index 00000000..510fd80e --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_data_bounds.json @@ -0,0 +1,18 @@ +{ + "x1": { + "min": 2.0, + "max": 4.0 + }, + "x2": { + "min": 3.0, + "max": 8.0 + }, + "y1": { + "min": 5.0, + "max": 9.0 + }, + "y2": { + "min": 5.0, + "max": 9.0 + } +} \ No newline at end of file diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl new file mode 100644 index 0000000000000000000000000000000000000000..9af00b41ee45c35d8ddb1e537c28916920bb6471 GIT binary patch literal 2576 zcmds2&2Jk;6kl)R#&*7(&_F;Ds)PgvglR&BDnPQ8AR%>N3lX$j=xDtjXIAW2XJ<<+ zfdq#ZBF(MCAvccv3*5>9l|zMcgc~Q+1Bd(tz?oA>7Te*5P0 z*{`b&D_@_De9rSkNYIyRH9|E68aHN-7pDA zigRCyY|$)Rp{9XE6|t_2pAdhKay($J#~~rkH{U8QVp(EA9X=o~&!9-@h$W>f9~{N~ z+_J#js2_(oKc2h!;mGXPL(VS5eI!rI?HQ zh09%utlM&@(vx4xUD-kvWZ#zbDN*h7VM0`hef6?D_^Q~Q5tUD+<2YCTgq8oG4wt=y zk5s4kq0{#MmLy;iOVJ3eyhOmh5#c!FNybyGP+u$~3Km;b6+PfKtCMt5R%o)~2-JgY z`Xt>@MboEE$rVtZ5w<^3=o?doTB^{UT1B^1f{H5Y1YjDSM>9|#bP{`U7IBH@0jj*Q zC$r7x*=DZ2dTERcea>l#MnDD}d(;p5Qp~fQPg!=3u9gt0sj*1+V z@H;hf9Xzkn8|VVacOkL`@;%Tmg4|UnWSbL^Ob{i{eff^eP#0L%RNdIVXIqwO$T{5@ zql20Z2ETO*^HHa!_X}~MYg9NQUsWwj@!uXE{-Wc5?9A%@LNvQZozZ{HekuN&!^7`J 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0.10000000149011612) then (y1 = 0.0) | based on 1 samples diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt new file mode 100644 index 00000000..5015336b --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt @@ -0,0 +1,7 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.4000000134110451) and (x1 <= 0.75) then (y2 = 0.0) | based on 5 samples +if (x2 <= 0.4000000134110451) then (y2 = 1.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_features_scaler.pkl b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_features_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..62adbe18d720f124ad6845781cc0dc4fb0753242 GIT binary patch literal 657 zcma))&r1S96vy37`+=GY)ul^Ey)0-RIs^*dS~RG04C6ZL((ddsvl|Kpb{d{?E?~_ksJrR{S8KJzTXxlMZp>fiu_ z$TV%*#Dhx%CdP-0V3asU5XYt0E36ZhQwAkco1_=6@eoh7H7gl2&2)+A5e)>zEQ1V7T9{OADU|zTJ8D7bUu2>lYq#sGBp$4H<`?8qOr|4ewDa}s(z+M3d9?V^ T&<$bS_NZKO*{B*72;0UNhrsLs literal 0 HcmV?d00001 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_model_features_dict.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_model_features_dict.json new file mode 100644 index 00000000..85782d17 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_model_features_dict.json @@ -0,0 +1,10 @@ +{ + "y1": [ + "x1", + "x2" + ], + "y2": [ + "x1", + "x2" + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_model_levels_dict.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_model_levels_dict.json new file mode 100644 index 00000000..9e26dfee --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_model_levels_dict.json @@ -0,0 +1 @@ +{} \ No newline at end of file diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_rerun_model_config.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_rerun_model_config.json new file mode 100644 index 00000000..4eeebbb7 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_rerun_model_config.json @@ -0,0 +1,172 @@ +{ + "alpha": null, + "analytics_mode": "verify", + "approximate_fractions": true, + "assertions_expressions": "(y2**3+x2)/2<6;y1>=9;y2<0", + "assertions_names": "asrt1,asrt2,asrt3", + "beta": null, + "center_offset": "0", + "compress_rules": false, + "continuous_correlation_estimators": [ + "pearson", + "spearman" + ], + "correlations_and_mutual_information": true, + "data_scaler": "min_max", + "delta_absolute": 0.0, + "delta_relative": 0.01, + "discretization_algo": "uniform", + "discretization_bins": 10, + "discretization_labels": true, + "discretization_type": "category", + "discretize_numeric_features": null, + "doe_algo": null, + "doe_box_behnken_centers": 1, + "doe_central_composite_alpha": "o", + "doe_central_composite_center": "2,2", + "doe_central_composite_face": "ccf", + "doe_design_resolution": null, + "doe_factor_level_ranges": null, + "doe_num_samples": null, + "doe_prob_distribution": "Normal", + "doe_spec_file": null, + "dt_sklearn_ccp_alpha": 0.0, + "dt_sklearn_criterion": "squared_error", + "dt_sklearn_max_depth": 15, + "dt_sklearn_max_features": null, + "dt_sklearn_max_leaf_nodes": null, + "dt_sklearn_min_impurity_decrease": 0.0, + "dt_sklearn_min_samples_leaf": 1, + "dt_sklearn_min_samples_split": 2, + "dt_sklearn_min_weight_fraction_leaf": 0.0, + "dt_sklearn_random_state": null, + "dt_sklearn_splitter": "best", + "epsilon": 0.05, + "et_sklearn_bootstrap": true, + "et_sklearn_ccp_alpha": 0.0, + "et_sklearn_criterion": "squared_error", + "et_sklearn_max_depth": null, + "et_sklearn_max_features": 1.0, + "et_sklearn_max_leaf_nodes": null, + "et_sklearn_max_samples": null, + "et_sklearn_min_impurity_decrease": 0.0, + "et_sklearn_min_samples_leaf": 1, + "et_sklearn_min_samples_split": 2, + "et_sklearn_min_weight_fraction_leaf": 0.0, + "et_sklearn_n_estimators": 100, + "et_sklearn_random_state": null, + "et_sklearn_verbose": 0, + "et_sklearn_warm_start": false, + "eta": null, + "features": "x0,x1,x2", + "fraction_precision": 64, + "impute_responses": false, + "interactive_plots": false, + "keep_features": [], + "labeled_data": null, + "lemma_precision": 0, + "load_configuration": null, + "log_files_prefix": null, + "log_level": "info", + "log_mode": "w", + "log_time": false, + "model": "dt_sklearn", + "model_caret_cross_validation": true, + "model_caret_return_train_score": false, + "model_caret_verbose": true, + "model_name": null, + "model_per_response": true, + "mrmr_feat_count_for_correlation": 15, + "mrmr_feat_count_for_prediction": 2, + "mutual_information_method": "normalized", + "negative_value": 0, + "new_data": null, + "nn_keras_batch_size": 200, + "nn_keras_batches_grid": null, + "nn_keras_epochs": 2000, + "nn_keras_hid_activation": "relu", + "nn_keras_layers": "2,1", + "nn_keras_layers_grid": null, + "nn_keras_learning_rate": 0.001, + "nn_keras_learning_rates_grid": null, + "nn_keras_loss_function": "mse", + "nn_keras_loss_functions_grid": null, + "nn_keras_metrics": [ + "mse" + ], + "nn_keras_optimizer": "adam", + "nn_keras_out_activation": "linear", + "nn_keras_sequential_api": true, + "nn_keras_tuner_algo": null, + "nn_keras_weights_precision": null, + "nnet_encoding": "nested", + "objectives_expressions": null, + "objectives_names": "None", + "optimization_strategy": "eager", + "optimize_pareto": true, + "output_directory": "./", + "poly_sklearn_copy_X": true, + "poly_sklearn_degree": 2, + "poly_sklearn_fit_intercept": true, + "poly_sklearn_n_jobs": null, + "poly_sklearn_positive": false, + "positive_value": 1, + "prediction_plots": false, + "psg_max_dimension": 3, + "psg_quality_target": "Lift", + "psg_top_ranked": 15, + "query_expressions": null, + "query_names": "None", + "radius_absolute": null, + "radius_relative": null, + "response": "y1,y2", + "response_map": null, + "response_plots": false, + "response_to_bool": null, + "rf_sklearn_bootstrap": true, + "rf_sklearn_ccp_alpha": 0.0, + "rf_sklearn_criterion": "squared_error", + "rf_sklearn_max_depth": null, + "rf_sklearn_max_features": 1.0, + "rf_sklearn_max_leaf_nodes": null, + "rf_sklearn_max_samples": null, + "rf_sklearn_min_impurity_decrease": 0.0, + "rf_sklearn_min_samples_leaf": 1, + "rf_sklearn_min_samples_split": 2, + "rf_sklearn_min_weight_fraction_leaf": 0.0, + "rf_sklearn_n_estimators": 100, + "rf_sklearn_random_state": null, + "rf_sklearn_verbose": 0, + "rf_sklearn_warm_start": false, + "sample_weights_coef": 0, + "sample_weights_exponent": 0, + "sample_weights_intercept": 0, + "save_configuration": false, + "save_model": "false", + "save_model_rerun_configuration": true, + "scale_features": true, + "scale_objectives": true, + "scale_responses": true, + "seed": 10, + "setup_caret_data_split_shuffle": true, + "setup_caret_fold": 0, + "setup_caret_session_id": null, + "setup_caret_verbose": true, + "simplify_terms": false, + "solver": "z3", + "solver_logic": "ALL", + "solver_path": null, + "spec": "../specs/smlp_toy_num_resp_noknobs_verify.spec", + "split_test": 0.2, + "trace_anonymize": true, + "trace_precision": 3, + "trace_runtime": 0, + "train_first_n": 0, + "train_random_n": 0, + "train_uniform_n": 0, + "tree_encoding": "branched", + "tuner_caret_search_algorithm": "random", + "tuner_caret_tuner_verbose": true, + "use_model": "true", + "vacuity_check": true +} \ No newline at end of file diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_responses_scaler.pkl b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_responses_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..f2576be20c9aab6434a4d801eeba1b3a7478a6ac GIT binary patch literal 657 zcma))PfG$p7{=XAi%@d~>(b4WUKW%N9RdY!EgIB0hH)L;rQO+OW;a|YsDq|3H{U*w zU!f1<|VkXuiTTG(>q!a1b(r7^V{fM$S;?Ao8Z?N3f99v3*#I>Q+UuOE|JA0&z-1 z*N=45V?=jDC$KSNIFd$)5!0hQV4)dEBT-0%AdcuLm8_)A40_5C-ryD*hGM8Qu*#w^ z3L>Axh=9 + +smlp_logger - INFO - Assertion asrt3: y2<0 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - MRMR feature selection for response y1 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y1 : + Feature Score +0 x1 1.115702 +1 x2 0.944056 + +smlp_logger - INFO - MRMR feature selection for response y1 : end + +smlp_logger - INFO - MRMR feature selection for response y2 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y2 : + Feature Score +1 x2 4.950294 +0 x1 1.115702 + +smlp_logger - INFO - MRMR feature selection for response y2 : end + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 +9 2.0 7 5 5 +10 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 +9 0.0 0.8 0.0 0.0 +10 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 2) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test185_smlp_toy_num_resp_noknobs_data_bounds.json + +smlp_logger - INFO - {'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - Preparing new data for modeling: start + +smlp_logger - INFO - loading new data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 9.000000 9.000000 8.000000 8.000000 9.000000 +mean 6.777778 7.222222 10.250000 2.875000 5.111111 +std 2.108185 2.108185 1.035098 0.834523 1.691482 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 9.750000 2.000000 4.000000 +50% 5.000000 9.000000 10.000000 3.000000 4.000000 +75% 9.000000 9.000000 11.000000 3.250000 6.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - new data + categ y1 y2 x0 x1 x2 +0 c0 5 9 10.0 2.0 3 +1 c12 9 9 12.0 NaN 4 +2 c2 5 9 NaN 3.0 4 +3 c17 5 5 11.0 2.0 6 +4 c18 9 5 10.0 2.0 8 +5 c8 9 9 9.0 4.0 7 +6 c7 5 5 9.0 3.0 6 +7 c3 5 5 10.0 3.0 4 +8 c12 9 9 11.0 4.0 4 + +smlp_logger - INFO - new data after imputing missing values + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after processing responses + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 + +smlp_logger - INFO - Preparing new data for modeling: end + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./Test185_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt + +smlp_logger - INFO - Writing tree rules into file ./Test185_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./Test185_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 8.000 + +smlp_logger - INFO - Prediction on test data -- r2_score: -1.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 2.182 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.450 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON NEW DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv + +smlp_logger - INFO - Prediction on new data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on new data -- r2_score: 0.325 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_0: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_1: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_2: {'and': 5, 'or': 2, 'not': 2, 'prop': 8, 'var': 8, 'const': 20, 'mul': 6, 'sub': 6} + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_3: {'and': 5, 'or': 2, 'not': 2, 'prop': 8, 'var': 8, 'const': 20, 'mul': 6, 'sub': 6} + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_4: {'and': 5, 'or': 2, 'not': 2, 'prop': 8, 'var': 8, 'const': 20, 'mul': 6, 'sub': 6} + +smlp_logger - INFO - Model operator counts for antecedent_y1_scaled_tree_0_rule_5: {'and': 5, 'or': 2, 'not': 2, 'prop': 8, 'var': 8, 'const': 20, 'mul': 6, 'sub': 6} + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 1, 'ite': 5, 'prop': 5, 'var': 5, 'const': 13} + +smlp_logger - INFO - Model operator counts for antecedent_y2_scaled_tree_0_rule_0: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for antecedent_y2_scaled_tree_0_rule_1: {'and': 1, 'or': 2, 'not': 2, 'prop': 4, 'var': 4, 'const': 8, 'mul': 2, 'sub': 2} + +smlp_logger - INFO - Model operator counts for antecedent_y2_scaled_tree_0_rule_2: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 1, 'ite': 2, 'prop': 2, 'var': 2, 'const': 7} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv new file mode 100644 index 00000000..7d143a2f --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,2.909090909090909,0.2666666666666666 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv new file mode 100644 index 00000000..7a649b6a --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json new file mode 100644 index 00000000..6e4f6879 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json @@ -0,0 +1,5 @@ +{ + "x1": [ + 1 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv new file mode 100644 index 00000000..951115f0 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,3.5555555555555554,0.10000000000000009 +y2,1.7777777777777777,0.55 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv new file mode 100644 index 00000000..3ba8f5c9 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv @@ -0,0 +1,10 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv new file mode 100644 index 00000000..fd947921 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,10.666666666666666,-2.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv new file mode 100644 index 00000000..3bb69252 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv new file mode 100644 index 00000000..d7a466e1 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y0,y1 +interface_consistency,sat,7.0,3.0 +model_consistency,sat,1.0,6.0,5.0,5.0 +witness_consistency,sat,1.0,6.0,5.0,5.0 +witness_consistency,sat,1.0,6.0,5.0,5.0 +witness_consistency,sat,1.0,6.0,5.0,5.0 +ca,unsat +ce,sat,1.0,3.5,5.0,9.0 +ca,sat,4.0,4.5,9.0,9.0 +ce,sat,1.0,6.0,5.0,5.0 +ca,unsat +ce,sat,1.0,7.0,5.0,5.0 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json new file mode 100644 index 00000000..12ff6934 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -0,0 +1,38 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 3.5, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 5.0 + }, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json new file mode 100644 index 00000000..05903661 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y1_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'antecedent_y1_scaled_tree_0_rule_0': = antecedent_y1_scaled_tree_0_rule_0 0))) (let ((|:1| (and (> (* (/ 1 5) (- x2 3)) (/ 23488103 33554432)) (> (* (/ 1 2) (- x1 2)) (/ 1 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_1': = antecedent_y1_scaled_tree_0_rule_1 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (<= |:1| (/ 23488103 33554432)) (> |:1| (/ 53687093 134217728))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'antecedent_y1_scaled_tree_0_rule_2': = antecedent_y1_scaled_tree_0_rule_2 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (and (> |:1| (/ 23488103 33554432)) (<= (* (/ 1 2) (- x1 2)) (/ 1 4))) (> |:1| (/ 30198989 33554432))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'antecedent_y1_scaled_tree_0_rule_3': = antecedent_y1_scaled_tree_0_rule_3 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (and (> |:1| (/ 23488103 33554432)) (<= (* (/ 1 2) (- x1 2)) (/ 1 4))) (<= |:1| (/ 30198989 33554432))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'antecedent_y1_scaled_tree_0_rule_4': = antecedent_y1_scaled_tree_0_rule_4 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (and (<= |:1| (/ 23488103 33554432)) (<= |:1| (/ 53687093 134217728))) (> |:1| (/ 13421773 134217728))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'antecedent_y1_scaled_tree_0_rule_5': = antecedent_y1_scaled_tree_0_rule_5 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (and (<= |:1| (/ 23488103 33554432)) (<= |:1| (/ 53687093 134217728))) (<= |:1| (/ 13421773 134217728))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'y1': = antecedent_y1_scaled_tree_0_rule_5 0) 0 (ite (>= antecedent_y1_scaled_tree_0_rule_4 0) 1 (ite (>= antecedent_y1_scaled_tree_0_rule_3 0) 0 (ite (>= antecedent_y1_scaled_tree_0_rule_2 0) 1 (ite (>= antecedent_y1_scaled_tree_0_rule_1 0) 0 1))))) 4) 5)>}" \ No newline at end of file diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json new file mode 100644 index 00000000..470d650f --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y1_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': = antecedent_y1_scaled_tree_0_rule_5 0) 0 (ite (>= antecedent_y1_scaled_tree_0_rule_4 0) 1 (ite (>= antecedent_y1_scaled_tree_0_rule_3 0) 0 (ite (>= antecedent_y1_scaled_tree_0_rule_2 0) 1 (ite (>= antecedent_y1_scaled_tree_0_rule_1 0) 0 1)))))>, 'antecedent_y1_scaled_tree_0_rule_0': = antecedent_y1_scaled_tree_0_rule_0 0))) (let ((|:1| (and (> x2_scaled (/ 23488103 33554432)) (> x1_scaled (/ 1 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_1': = antecedent_y1_scaled_tree_0_rule_1 0))) (let ((|:1| (and (<= x2_scaled (/ 23488103 33554432)) (> x2_scaled (/ 53687093 134217728))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_2': = antecedent_y1_scaled_tree_0_rule_2 0))) (let ((|:1| (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_3': = antecedent_y1_scaled_tree_0_rule_3 0))) (let ((|:1| (and (and (> x2_scaled (/ 23488103 33554432)) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_4': = antecedent_y1_scaled_tree_0_rule_4 0))) (let ((|:1| (and (and (<= x2_scaled (/ 23488103 33554432)) (<= x2_scaled (/ 53687093 134217728))) (> x2_scaled (/ 13421773 134217728))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y1_scaled_tree_0_rule_5': = antecedent_y1_scaled_tree_0_rule_5 0))) (let ((|:1| (and (and (<= x2_scaled (/ 23488103 33554432)) (<= x2_scaled (/ 53687093 134217728))) (<= x2_scaled (/ 13421773 134217728))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json new file mode 100644 index 00000000..41e3b5de --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y2_smlp_full_model_term.json @@ -0,0 +1 @@ +"{'antecedent_y2_scaled_tree_0_rule_0': = antecedent_y2_scaled_tree_0_rule_0 0))) (let ((|:1| (and (> (* (/ 1 5) (- x2 3)) (/ 53687093 134217728)) (<= (* (/ 1 2) (- x1 2)) (/ 3 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y2_scaled_tree_0_rule_1': = antecedent_y2_scaled_tree_0_rule_1 0))) (let ((|:1| (<= (* (/ 1 5) (- x2 3)) (/ 53687093 134217728)))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y2_scaled_tree_0_rule_2': = antecedent_y2_scaled_tree_0_rule_2 0))) (let ((|:1| (and (> (* (/ 1 5) (- x2 3)) (/ 53687093 134217728)) (> (* (/ 1 2) (- x1 2)) (/ 3 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'y2': = antecedent_y2_scaled_tree_0_rule_2 0) 1 (ite (>= antecedent_y2_scaled_tree_0_rule_1 0) 1 0)) 4) 5)>}" \ No newline at end of file diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json new file mode 100644 index 00000000..e5382ce6 --- /dev/null +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_y2_smlp_model_term.json @@ -0,0 +1 @@ +"{'y2_scaled': = antecedent_y2_scaled_tree_0_rule_2 0) 1 (ite (>= antecedent_y2_scaled_tree_0_rule_1 0) 1 0))>, 'antecedent_y2_scaled_tree_0_rule_0': = antecedent_y2_scaled_tree_0_rule_0 0))) (let ((|:1| (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y2_scaled_tree_0_rule_1': = antecedent_y2_scaled_tree_0_rule_1 0))) (let ((|:1| (<= x2_scaled (/ 53687093 134217728)))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_y2_scaled_tree_0_rule_2': = antecedent_y2_scaled_tree_0_rule_2 0))) (let ((|:1| (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_data_bounds.json b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_data_bounds.json new file mode 100644 index 00000000..510fd80e --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_data_bounds.json @@ -0,0 +1,18 @@ +{ + "x1": { + "min": 2.0, + "max": 4.0 + }, + "x2": { + "min": 3.0, + "max": 8.0 + }, + "y1": { + "min": 5.0, + "max": 9.0 + }, + "y2": { + "min": 5.0, + "max": 9.0 + } +} \ No newline at end of file diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl new file mode 100644 index 0000000000000000000000000000000000000000..7cef3b591fe95ec7f7a1596357c4b544c2a2852b GIT binary patch literal 2192 zcmd5;&x;&I6z=KW$a|Q`|7=K zdiIO?Z+1FPxzw__6f>Wv1IZa1&>;4OU;@z+wx9EiBG6eFHI+{c&6@HS(OwbYw z#8v%z6gf?SwA6|YUS-i{DCv~@fy9Ee+!nDV$Ps zpT2qKaeuZOnFp4Lj4)ao1##=DML$%5fl@w+g)3GW6-M6y5Q7)+Cl`v8G z2X~Gokq}Y3NjEbpGZf=g;$`$L-bY@IZiH_&ho*Z$oa+#t4KI)mT7tHZ_5*!#TI=Hz zPp%;H!|)+YuFd%fl zoy~sps_-wKd8ruG$)S00T=Rgb%4PGRb9*-X&YZvNS)73ljdir7>+6wm%>G@AtL4Se zLzCC}-{;$=z>+Q0uzz{$U;mDupS?qk_{z}ovGE17Z{z6Z)9IhyomY4M{`k%ho~={C zULG3wGxL91|Lj~2+k_3f=biZJGJd}I?0l;2&OZOH!7mzHmRiDy$j{~(YrO%%YH@8 z{A#Ac{jvX5Y1Xd+8;`c04L;3(=;^B$W7VhThl5^WT>o2vzjtecGlSDmj0gV$IK!;? literal 0 HcmV?d00001 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt new file mode 100644 index 00000000..59a1eff8 --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt @@ -0,0 +1,11 @@ +#Forest semantics: majority vote +#Number of trees: 1 + +#TREE 0 +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 <= 0.7000000178813934) then (y1 = 0.0) and (y2 = 0.0) | based on 2 samples +if (x2 > 0.4000000134110451) and (x1 > 0.75) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 > 0.25) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 > 0.9000000059604645) then (y1 = 1.0) and (y2 = 0.0) | based on 1 samples +if (x2 > 0.4000000134110451) and (x1 <= 0.75) and (x2 > 0.7000000178813934) and (x1 <= 0.25) and (x2 <= 0.9000000059604645) then (y1 = 0.0) and (y2 = 0.0) | based on 1 samples +if (x2 <= 0.4000000134110451) and (x2 > 0.10000000149011612) then (y1 = 1.0) and (y2 = 1.0) | based on 1 samples +if (x2 <= 0.4000000134110451) and (x2 <= 0.10000000149011612) then (y1 = 0.0) and (y2 = 1.0) | based on 1 samples diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_features_scaler.pkl b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_features_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..62adbe18d720f124ad6845781cc0dc4fb0753242 GIT binary patch literal 657 zcma))&r1S96vy37`+=GY)ul^Ey)0-RIs^*dS~RG04C6ZL((ddsvl|Kpb{d{?E?~_ksJrR{S8KJzTXxlMZp>fiu_ z$TV%*#Dhx%CdP-0V3asU5XYt0E36ZhQwAkco1_=6@eoh7H7gl2&2)+A5e)>zEQ1V7T9{OADU|zTJ8D7bUu2>lYq#sGBp$4H<`?8qOr|4ewDa}s(z+M3d9?V^ T&<$bS_NZKO*{B*72;0UNhrsLs literal 0 HcmV?d00001 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_model_features_dict.json b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_model_features_dict.json new file mode 100644 index 00000000..85782d17 --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_model_features_dict.json @@ -0,0 +1,10 @@ +{ + "y1": [ + "x1", + "x2" + ], + "y2": [ + "x1", + "x2" + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_model_levels_dict.json b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_model_levels_dict.json new file mode 100644 index 00000000..9e26dfee --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_model_levels_dict.json @@ -0,0 +1 @@ +{} \ No newline at end of file diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_rerun_model_config.json b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_rerun_model_config.json new file mode 100644 index 00000000..455b1f9d --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_rerun_model_config.json @@ -0,0 +1,172 @@ +{ + "alpha": null, + "analytics_mode": "verify", + "approximate_fractions": true, + "assertions_expressions": "(y2**3+x2)/2<6;y1>=9;y2<0", + "assertions_names": "asrt1,asrt2,asrt3", + "beta": null, + "center_offset": "0", + "compress_rules": false, + "continuous_correlation_estimators": [ + "pearson", + "spearman" + ], + "correlations_and_mutual_information": true, + "data_scaler": "min_max", + "delta_absolute": 0.0, + "delta_relative": 0.01, + "discretization_algo": "uniform", + "discretization_bins": 10, + "discretization_labels": true, + "discretization_type": "category", + "discretize_numeric_features": null, + "doe_algo": null, + "doe_box_behnken_centers": 1, + "doe_central_composite_alpha": "o", + "doe_central_composite_center": "2,2", + "doe_central_composite_face": "ccf", + "doe_design_resolution": null, + "doe_factor_level_ranges": null, + "doe_num_samples": null, + "doe_prob_distribution": "Normal", + "doe_spec_file": null, + "dt_sklearn_ccp_alpha": 0.0, + "dt_sklearn_criterion": "squared_error", + "dt_sklearn_max_depth": 15, + "dt_sklearn_max_features": null, + "dt_sklearn_max_leaf_nodes": null, + "dt_sklearn_min_impurity_decrease": 0.0, + "dt_sklearn_min_samples_leaf": 1, + "dt_sklearn_min_samples_split": 2, + "dt_sklearn_min_weight_fraction_leaf": 0.0, + "dt_sklearn_random_state": null, + "dt_sklearn_splitter": "best", + "epsilon": 0.05, + "et_sklearn_bootstrap": true, + "et_sklearn_ccp_alpha": 0.0, + "et_sklearn_criterion": "squared_error", + "et_sklearn_max_depth": null, + "et_sklearn_max_features": 1.0, + "et_sklearn_max_leaf_nodes": null, + "et_sklearn_max_samples": null, + "et_sklearn_min_impurity_decrease": 0.0, + "et_sklearn_min_samples_leaf": 1, + "et_sklearn_min_samples_split": 2, + "et_sklearn_min_weight_fraction_leaf": 0.0, + "et_sklearn_n_estimators": 100, + "et_sklearn_random_state": null, + "et_sklearn_verbose": 0, + "et_sklearn_warm_start": false, + "eta": null, + "features": "x0,x1,x2", + "fraction_precision": 64, + "impute_responses": false, + "interactive_plots": false, + "keep_features": [], + "labeled_data": 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0, + "train_uniform_n": 0, + "tree_encoding": "branched", + "tuner_caret_search_algorithm": "random", + "tuner_caret_tuner_verbose": true, + "use_model": "true", + "vacuity_check": true +} \ No newline at end of file diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_responses_scaler.pkl b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_responses_scaler.pkl new file mode 100644 index 0000000000000000000000000000000000000000..f2576be20c9aab6434a4d801eeba1b3a7478a6ac GIT binary patch literal 657 zcma))PfG$p7{=XAi%@d~>(b4WUKW%N9RdY!EgIB0hH)L;rQO+OW;a|YsDq|3H{U*w zU!f1<|VkXuiTTG(>q!a1b(r7^V{fM$S;?Ao8Z?N3f99v3*#I>Q+UuOE|JA0&z-1 z*N=45V?=jDC$KSNIFd$)5!0hQV4)dEBT-0%AdcuLm8_)A40_5C-ryD*hGM8Qu*#w^ z3L>Axh= antecedent_tree_0_rule_0 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (and (> |:1| (/ 53687093 134217728)) (<= (* (/ 1 2) (- x1 2)) (/ 3 4))) (<= |:1| (/ 23488103 33554432))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'antecedent_tree_0_rule_1': = antecedent_tree_0_rule_1 0))) (let ((|:1| (and (> (* (/ 1 5) (- x2 3)) (/ 53687093 134217728)) (> (* (/ 1 2) (- x1 2)) (/ 3 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_tree_0_rule_2': = antecedent_tree_0_rule_2 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (* (/ 1 2) (- x1 2)))) (let ((|:3| (and (and (and (> |:1| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (> |:1| (/ 23488103 33554432))) (> |:2| (/ 1 4))))) (and (or (not |:0|) |:3|) (or (not |:3|) |:0|))))))>, 'antecedent_tree_0_rule_3': = antecedent_tree_0_rule_3 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (* (/ 1 2) (- x1 2)))) (let ((|:3| (and (and (and (and (> |:1| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (> |:1| (/ 23488103 33554432))) (<= |:2| (/ 1 4))) (> |:1| (/ 30198989 33554432))))) (and (or (not |:0|) |:3|) (or (not |:3|) |:0|))))))>, 'antecedent_tree_0_rule_4': = antecedent_tree_0_rule_4 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (* (/ 1 2) (- x1 2)))) (let ((|:3| (and (and (and (and (> |:1| (/ 53687093 134217728)) (<= |:2| (/ 3 4))) (> |:1| (/ 23488103 33554432))) (<= |:2| (/ 1 4))) (<= |:1| (/ 30198989 33554432))))) (and (or (not |:0|) |:3|) (or (not |:3|) |:0|))))))>, 'antecedent_tree_0_rule_5': = antecedent_tree_0_rule_5 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (<= |:1| (/ 53687093 134217728)) (> |:1| (/ 13421773 134217728))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'antecedent_tree_0_rule_6': = antecedent_tree_0_rule_6 0))) (let ((|:1| (* (/ 1 5) (- x2 3)))) (let ((|:2| (and (<= |:1| (/ 53687093 134217728)) (<= |:1| (/ 13421773 134217728))))) (and (or (not |:0|) |:2|) (or (not |:2|) |:0|)))))>, 'y1': = antecedent_tree_0_rule_6 0) 0 (ite (>= antecedent_tree_0_rule_5 0) 1 (ite (>= antecedent_tree_0_rule_4 0) 0 (ite (>= antecedent_tree_0_rule_3 0) 1 (ite (>= antecedent_tree_0_rule_2 0) 1 (ite (>= antecedent_tree_0_rule_1 0) 1 0)))))) 4) 5)>, 'y2': = antecedent_tree_0_rule_6 0) 1 (ite (>= antecedent_tree_0_rule_5 0) 1 (ite (>= antecedent_tree_0_rule_4 0) 0 (ite (>= antecedent_tree_0_rule_3 0) 0 (ite (>= antecedent_tree_0_rule_2 0) 0 (ite (>= antecedent_tree_0_rule_1 0) 1 0)))))) 4) 5)>}" \ No newline at end of file diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_model_term.json b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_model_term.json new file mode 100644 index 00000000..3e5567c7 --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_model_term.json @@ -0,0 +1 @@ +"{'y1_scaled': = antecedent_tree_0_rule_6 0) 0 (ite (>= antecedent_tree_0_rule_5 0) 1 (ite (>= antecedent_tree_0_rule_4 0) 0 (ite (>= antecedent_tree_0_rule_3 0) 1 (ite (>= antecedent_tree_0_rule_2 0) 1 (ite (>= antecedent_tree_0_rule_1 0) 1 0))))))>, 'y2_scaled': = antecedent_tree_0_rule_6 0) 1 (ite (>= antecedent_tree_0_rule_5 0) 1 (ite (>= antecedent_tree_0_rule_4 0) 0 (ite (>= antecedent_tree_0_rule_3 0) 0 (ite (>= antecedent_tree_0_rule_2 0) 0 (ite (>= antecedent_tree_0_rule_1 0) 1 0))))))>, 'antecedent_tree_0_rule_0': = antecedent_tree_0_rule_0 0))) (let ((|:1| (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x2_scaled (/ 23488103 33554432))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_tree_0_rule_1': = antecedent_tree_0_rule_1 0))) (let ((|:1| (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_tree_0_rule_2': = antecedent_tree_0_rule_2 0))) (let ((|:1| (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (> x1_scaled (/ 1 4))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_tree_0_rule_3': = antecedent_tree_0_rule_3 0))) (let ((|:1| (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (> x2_scaled (/ 30198989 33554432))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_tree_0_rule_4': = antecedent_tree_0_rule_4 0))) (let ((|:1| (and (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (> x2_scaled (/ 23488103 33554432))) (<= x1_scaled (/ 1 4))) (<= x2_scaled (/ 30198989 33554432))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_tree_0_rule_5': = antecedent_tree_0_rule_5 0))) (let ((|:1| (and (<= x2_scaled (/ 53687093 134217728)) (> x2_scaled (/ 13421773 134217728))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>, 'antecedent_tree_0_rule_6': = antecedent_tree_0_rule_6 0))) (let ((|:1| (and (<= x2_scaled (/ 53687093 134217728)) (<= x2_scaled (/ 13421773 134217728))))) (and (or (not |:0|) |:1|) (or (not |:1|) |:0|))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt new file mode 100644 index 00000000..e53adb17 --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt @@ -0,0 +1,404 @@ + +smlp_logger - INFO - Model exploration specification: +{'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} + +smlp_logger - INFO - Executing run_smlp.py script: Start + +smlp_logger - INFO - Running SMLP in mode "verify": Start + +smlp_logger - INFO - Computed spec global constraint expressions: + +smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 + +smlp_logger - INFO - Global beta : None + +smlp_logger - INFO - Radii theta : {} + +smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} + +smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 + +smlp_logger - INFO - Assertion asrt2: y1>=9 + +smlp_logger - INFO - Assertion asrt3: y2<0 + +smlp_logger - INFO - PREPARE DATA FOR MODELING + +smlp_logger - INFO - Preparing training data for modeling: start + +smlp_logger - INFO - loading training data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 11.000000 11.000000 10.000000 10.000000 11.000000 +mean 6.818182 6.818182 10.400000 2.800000 5.454545 +std 2.088932 2.088932 1.074968 0.788811 1.694912 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 10.000000 2.000000 4.000000 +50% 5.000000 5.000000 10.000000 3.000000 6.000000 +75% 9.000000 9.000000 11.000000 3.000000 7.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - training data + categ y1 y2 x0 x1 x2 +0 c14 5 9 10.0 2.0 3 +1 c15 9 9 12.0 NaN 4 +2 c1 5 9 NaN 3.0 4 +3 c9 5 5 11.0 2.0 6 +4 c5 9 5 10.0 2.0 8 +5 c10 9 9 9.0 4.0 7 +6 c13 5 5 9.0 3.0 6 +7 c4 5 5 10.0 3.0 4 +8 c15 9 9 11.0 4.0 4 +9 c11 5 5 12.0 2.0 7 +10 c19 9 5 10.0 3.0 7 + +smlp_logger - INFO - training data after imputing missing values + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - training data after processing responses + x0 x1 x2 y1 y2 +0 10.0 2.0 3 5 9 +1 12.0 2.0 4 9 9 +2 10.0 3.0 4 5 9 +3 11.0 2.0 6 5 5 +4 10.0 2.0 8 9 5 +5 9.0 4.0 7 9 9 +6 9.0 3.0 6 5 5 +7 10.0 3.0 4 5 5 +8 11.0 4.0 4 9 9 +9 12.0 2.0 7 5 5 +10 10.0 3.0 7 9 5 + +smlp_logger - INFO - MRMR feature selection for response y1 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y1 : + Feature Score +0 x1 1.115702 +1 x2 0.944056 + +smlp_logger - INFO - MRMR feature selection for response y1 : end + +smlp_logger - INFO - MRMR feature selection for response y2 : start + +smlp_logger - INFO - MRMR selected feature scores (in the ranked order) for response y2 : + Feature Score +1 x2 4.950294 +0 x1 1.115702 + +smlp_logger - INFO - MRMR feature selection for response y2 : end + +smlp_logger - INFO - training data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 +9 2.0 7 5 5 +10 3.0 7 9 5 + +smlp_logger - INFO - training data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 +9 0.0 0.8 0.0 0.0 +10 0.5 0.8 1.0 0.0 + +smlp_logger - INFO - Sampling from training data: start + +smlp_logger - INFO - Sampling from training data: end + +smlp_logger - INFO - X_train after sampling: (8, 2) + +smlp_logger - INFO - y_train after sampling: (8, 2) + +smlp_logger - INFO - Preparing training data for modeling: end + +smlp_logger - INFO - Saving data bounds into file:./Test186_smlp_toy_num_resp_noknobs_data_bounds.json + +smlp_logger - INFO - {'x1': {'min': 2.0, 'max': 4.0}, 'x2': {'min': 3.0, 'max': 8.0}, 'y1': {'min': 5.0, 'max': 9.0}, 'y2': {'min': 5.0, 'max': 9.0}} + +smlp_logger - INFO - Preparing new data for modeling: start + +smlp_logger - INFO - loading new data + +smlp_logger - INFO - data summary + y1 y2 x0 x1 x2 +count 9.000000 9.000000 8.000000 8.000000 9.000000 +mean 6.777778 7.222222 10.250000 2.875000 5.111111 +std 2.108185 2.108185 1.035098 0.834523 1.691482 +min 5.000000 5.000000 9.000000 2.000000 3.000000 +25% 5.000000 5.000000 9.750000 2.000000 4.000000 +50% 5.000000 9.000000 10.000000 3.000000 4.000000 +75% 9.000000 9.000000 11.000000 3.250000 6.000000 +max 9.000000 9.000000 12.000000 4.000000 8.000000 + +smlp_logger - INFO - new data + categ y1 y2 x0 x1 x2 +0 c0 5 9 10.0 2.0 3 +1 c12 9 9 12.0 NaN 4 +2 c2 5 9 NaN 3.0 4 +3 c17 5 5 11.0 2.0 6 +4 c18 9 5 10.0 2.0 8 +5 c8 9 9 9.0 4.0 7 +6 c7 5 5 9.0 3.0 6 +7 c3 5 5 10.0 3.0 4 +8 c12 9 9 11.0 4.0 4 + +smlp_logger - INFO - new data after imputing missing values + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after processing responses + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after encoding levels of categorical features with integers + x1 x2 y1 y2 +0 2.0 3 5 9 +1 2.0 4 9 9 +2 3.0 4 5 9 +3 2.0 6 5 5 +4 2.0 8 9 5 +5 4.0 7 9 9 +6 3.0 6 5 5 +7 3.0 4 5 5 +8 4.0 4 9 9 + +smlp_logger - INFO - new data after scaling (normalizing) features and responses + x1 x2 y1 y2 +0 0.0 0.0 0.0 1.0 +1 0.0 0.2 1.0 1.0 +2 0.5 0.2 0.0 1.0 +3 0.0 0.6 0.0 0.0 +4 0.0 1.0 1.0 0.0 +5 1.0 0.8 1.0 1.0 +6 0.5 0.6 0.0 0.0 +7 0.5 0.2 0.0 0.0 +8 1.0 0.2 1.0 1.0 + +smlp_logger - INFO - Preparing new data for modeling: end + +smlp_logger - INFO - TRAIN MODEL + +smlp_logger - INFO - Model training: start + +smlp_logger - INFO - Writing tree rules into file ./Test186_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt + +smlp_logger - INFO - Model training: end + +smlp_logger - INFO - Seving model in file ./Test186_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl + +smlp_logger - INFO - PREDICT ON TRAINING DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv + +smlp_logger - INFO - Prediction on training data -- msqe: 0.000 + +smlp_logger - INFO - Prediction on training data -- r2_score: 1.000 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON TEST DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv + +smlp_logger - INFO - Prediction on test data -- msqe: 8.000 + +smlp_logger - INFO - Prediction on test data -- r2_score: -1.250 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON LABELED DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv + +smlp_logger - INFO - Prediction on labeled data -- msqe: 2.182 + +smlp_logger - INFO - Prediction on labeled data -- r2_score: 0.450 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - PREDICT ON NEW DATA + +smlp_logger - INFO - Model prediction: start + +smlp_logger - INFO - Model prediction: end + +smlp_logger - INFO - Reporting prediction results: start + +smlp_logger - INFO - Saving predictions summary into file: +./Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv + +smlp_logger - INFO - Saving prediction precisions into file: +./Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv + +smlp_logger - INFO - Prediction on new data -- msqe: 2.667 + +smlp_logger - INFO - Prediction on new data -- r2_score: 0.325 + +smlp_logger - INFO - Reporting prediction results: end + +smlp_logger - INFO - Creating model exploration base components: Start + +smlp_logger - INFO - Parsing the SPEC: Start + +smlp_logger - INFO - Parsing the SPEC: End + +smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} + +smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} + +smlp_logger - INFO - Knob bounds (eta): {} + +smlp_logger - INFO - Knob grids (eta): {} + +smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) + +smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) + +smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) + +smlp_logger - INFO - Beta global constraints: true + +smlp_logger - INFO - Eta ranges constraints: true + +smlp_logger - INFO - Eta grid constraints: true + +smlp_logger - INFO - Eta global constraints: true + +smlp_logger - INFO - Eta combined constraints: true + +smlp_logger - INFO - Creating model exploration base components: End + +smlp_logger - INFO - Input and knob interface constraints are consistent + +smlp_logger - INFO - Building model terms: Start + +smlp_logger - INFO - Model operator counts for antecedent_tree_0_rule_0: {'and': 5, 'or': 2, 'not': 2, 'prop': 8, 'var': 8, 'const': 20, 'mul': 6, 'sub': 6} + +smlp_logger - INFO - Model operator counts for antecedent_tree_0_rule_1: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for antecedent_tree_0_rule_2: {'and': 7, 'or': 2, 'not': 2, 'prop': 10, 'var': 10, 'const': 26, 'mul': 8, 'sub': 8} + +smlp_logger - INFO - Model operator counts for antecedent_tree_0_rule_3: {'and': 9, 'or': 2, 'not': 2, 'prop': 12, 'var': 12, 'const': 32, 'mul': 10, 'sub': 10} + +smlp_logger - INFO - Model operator counts for antecedent_tree_0_rule_4: {'and': 9, 'or': 2, 'not': 2, 'prop': 12, 'var': 12, 'const': 32, 'mul': 10, 'sub': 10} + +smlp_logger - INFO - Model operator counts for antecedent_tree_0_rule_5: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for antecedent_tree_0_rule_6: {'and': 3, 'or': 2, 'not': 2, 'prop': 6, 'var': 6, 'const': 14, 'mul': 4, 'sub': 4} + +smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 1, 'ite': 6, 'prop': 6, 'var': 6, 'const': 15} + +smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 1, 'ite': 6, 'prop': 6, 'var': 6, 'const': 15} + +smlp_logger - INFO - Building model terms: End + +smlp_logger - INFO - Model interface constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: + true + +smlp_logger - INFO - Input, knob and configuration constraints are consistent + +smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 + +smlp_logger - INFO - The configuration is consistent with assertion asrt2 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 + +smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 + +smlp_logger - INFO - Completed with result: FAIL + +smlp_logger - INFO - Running SMLP in mode "verify": End + +smlp_logger - INFO - Executing run_smlp.py script: End diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv new file mode 100644 index 00000000..7d143a2f --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,2.909090909090909,0.2666666666666666 +y2,1.4545454545454546,0.6333333333333333 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv new file mode 100644 index 00000000..7a649b6a --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv @@ -0,0 +1,12 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 +9,5.0,5.0,5.0,5.0 +10,9.0,5.0,9.0,5.0 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json new file mode 100644 index 00000000..6e4f6879 --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json @@ -0,0 +1,5 @@ +{ + "x1": [ + 1 + ] +} \ No newline at end of file diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv new file mode 100644 index 00000000..951115f0 --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,3.5555555555555554,0.10000000000000009 +y2,1.7777777777777777,0.55 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv new file mode 100644 index 00000000..3ba8f5c9 --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv @@ -0,0 +1,10 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +0,5.0,9.0,5.0,9.0 +1,9.0,9.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +6,5.0,5.0,5.0,5.0 +7,5.0,5.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv new file mode 100644 index 00000000..fd947921 --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,10.666666666666666,-2.0 +y2,5.333333333333333,-0.5 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv new file mode 100644 index 00000000..3bb69252 --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv @@ -0,0 +1,4 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +7,5.0,5.0,9.0,9.0 +2,5.0,9.0,9.0,9.0 +8,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv new file mode 100644 index 00000000..6950c9de --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -0,0 +1,12 @@ +stage,solver,x0,x1,x2,y0,y1 +interface_consistency,sat,7.0,3.0 +model_consistency,sat,7.0,6.0,9.0,9.0 +witness_consistency,sat,7.0,6.0,9.0,9.0 +witness_consistency,sat,7.0,6.0,9.0,9.0 +witness_consistency,sat,7.0,6.0,9.0,9.0 +ca,unsat +ce,sat,1.0,3.5,5.0,9.0 +ca,sat,7.0,4.5,9.0,9.0 +ce,sat,1.0,7.0,5.0,5.0 +ca,unsat +ce,sat,7.0,4.5,9.0,9.0 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv new file mode 100644 index 00000000..f0c58f67 --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv @@ -0,0 +1,3 @@ +response,msqe,r2_score +y1,0.0,1.0 +y2,0.0,1.0 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv new file mode 100644 index 00000000..74d164ca --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv @@ -0,0 +1,9 @@ +,y1,y2,y1_dt_sklearn,y2_dt_sklearn +3,5.0,5.0,5.0,5.0 +4,9.0,5.0,9.0,5.0 +5,9.0,9.0,9.0,9.0 +0,5.0,9.0,5.0,9.0 +10,9.0,5.0,9.0,5.0 +9,5.0,5.0,5.0,5.0 +6,5.0,5.0,5.0,5.0 +1,9.0,9.0,9.0,9.0 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json new file mode 100644 index 00000000..c0d0467c --- /dev/null +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -0,0 +1,38 @@ +{ + "asrt1": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 3.5, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "asrt2": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 1.0, + "y1": 5.0, + "x2": 7.0, + "y2": 5.0 + }, + "assertion_feasible": true + }, + "asrt3": { + "configuration_consistent": "true", + "assertion_status": "FAIL", + "counter_example": { + "x1": 7.0, + "y1": 9.0, + "x2": 4.500000007450581, + "y2": 9.0 + }, + "assertion_feasible": false + }, + "smlp_execution": "completed", + "interface_consistent": "true", + "model_consistent": "true" +} \ No newline at end of file From 35129d1a54c0fcdecc9b5ac421f417c3c19ddbc1 Mon Sep 17 00:00:00 2001 From: Dmitry Messerman Date: Tue, 2 Jun 2026 16:58:16 +0300 Subject: [PATCH 15/20] Fixed and added missing files in new tests --- regr_smlp/code/smlp_regr.csv | 212 ------------------ ...oy_num_resp_noknobs_pred_labeled_trace.csv | 2 +- ...p_noknobs_pred_labeled_verify_results.json | 2 +- ...est144_smlp_toy_num_resp_noknobs_trace.csv | 12 +- ...p_toy_num_resp_noknobs_verify_results.json | 2 +- ...oy_num_resp_noknobs_pred_labeled_trace.csv | 2 +- ...p_noknobs_pred_labeled_verify_results.json | 6 +- ...oy_num_resp_noknobs_pred_labeled_trace.csv | 2 +- ...p_noknobs_pred_labeled_verify_results.json | 6 +- ...oy_num_resp_noknobs_pred_labeled_trace.csv | 14 +- ...p_noknobs_pred_labeled_verify_results.json | 10 +- ...oy_num_resp_noknobs_pred_labeled_trace.csv | 14 +- ...p_noknobs_pred_labeled_verify_results.json | 10 +- ...oy_num_resp_noknobs_pred_labeled_trace.csv | 14 +- ...p_noknobs_pred_labeled_verify_results.json | 10 +- ...resp_noknobs_dt_sklearn_model_complete.pkl | Bin 1881 -> 2037 bytes ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 714 -> 702 bytes ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 661 -> 657 bytes ..._toy_num_resp_noknobs_smlp_model_term.json | 2 +- ...Test57_smlp_toy_num_resp_noknobs_trace.csv | 10 +- ...p_toy_num_resp_noknobs_verify_results.json | 6 +- ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 714 -> 702 bytes ...p_toy_num_resp_noknobs_model_checkpoint.h5 | Bin 45160 -> 43096 bytes ...um_resp_noknobs_nn_keras_model_complete.h5 | Bin 45160 -> 43096 bytes ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 661 -> 657 bytes ..._toy_num_resp_noknobs_smlp_model_term.json | 2 +- ...p_toy_num_resp_noknobs_features_scaler.pkl | Bin 714 -> 702 bytes ...p_toy_num_resp_noknobs_model_checkpoint.h5 | Bin 33224 -> 32192 bytes ...um_resp_noknobs_nn_keras_model_complete.h5 | Bin 33224 -> 32192 bytes ..._toy_num_resp_noknobs_responses_scaler.pkl | Bin 661 -> 657 bytes ..._toy_num_resp_noknobs_smlp_model_term.json | 2 +- ...Test65_smlp_toy_num_resp_noknobs_trace.csv | 12 +- ...p_toy_num_resp_noknobs_verify_results.json | 2 +- .../master/Test66_test65_model_trace.csv | 12 +- .../Test66_test65_model_verify_results.json | 2 +- ...Test67_smlp_toy_num_resp_noknobs_trace.csv | 12 +- ...p_toy_num_resp_noknobs_verify_results.json | 4 +- .../master/Test68_test67_model_trace.csv | 12 +- .../Test68_test67_model_verify_results.json | 4 +- .../master/Test72_test71_model_trace.csv | 2 +- ...oy_num_resp_noknobs_pred_labeled_trace.csv | 2 +- ...p_noknobs_pred_labeled_verify_results.json | 2 +- ...oy_num_resp_noknobs_pred_labeled_trace.csv | 2 +- ...p_noknobs_pred_labeled_verify_results.json | 2 +- ...oy_num_resp_noknobs_pred_labeled_trace.csv | 2 +- ...p_noknobs_pred_labeled_verify_results.json | 2 +- ...Test76_smlp_toy_num_resp_noknobs_trace.csv | 16 +- ...p_toy_num_resp_noknobs_verify_results.json | 16 +- ...Test78_smlp_toy_num_resp_noknobs_trace.csv | 10 +- 49 files changed, 122 insertions(+), 334 deletions(-) mode change 100755 => 100644 regr_smlp/code/smlp_regr.csv diff --git a/regr_smlp/code/smlp_regr.csv b/regr_smlp/code/smlp_regr.csv old mode 100755 new mode 100644 index 1bac58eb..d07272a3 --- a/regr_smlp/code/smlp_regr.csv +++ b/regr_smlp/code/smlp_regr.csv @@ -1,235 +1,23 @@ d,data,new_data,switches,description -1,smlp_toy_num_resp_mult,,"-mode train -resp y1 -feat x,p1,p2 -model dt_caret -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f",basic dt_caret training and test on labeled data with single numeric response -2,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f",basic rf_sklearn prediction test on labeled and new data with numeric labels -3,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_unlabeled,"-mode predict -resp y1 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic poly_sklearn prediction test on labeled and new data with numeric response in training/test data only -4,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nn_keras_weights_precision 2 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f",basic nn_keras prediction test on labeled and new data with numeric labels and one response -5,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model t -use_model f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_caret prediction test on labeled and new data with numeric labels -6,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test on labeled and new data with numeric labels -7,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic rf_sklearn prediction test on labeled and new data with numeric labels -8,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -nn_keras_epochs 20 -nn_keras_seq_api f -log_time f",basic nn_keras prediction test on labeled and new data with numeric labels and two responses -9,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -model_name test20_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -save_config t -save_model_config t",basic dt_sklearn prediction test on labeled and new data with numeric labels -10,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 15 -et_sklearn_bootstrap f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic et_sklearn prediction test on labeled and new data with numeric labels -11,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic poly_sklearn prediction test on labeled and new data with numeric labels -12,smlp_toy_basic,,"-mode train -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",EV-SI real life dt_sklearn predict test on labeled and new data with numeric labels -13,smlp_toy_basic,,"-mode train -resp y1,y2 -feat x1,x2,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",EV-SI real life nn_keras prediction test on labeled and new data with numeric labels -14,smlp_toy_basic,,"-mode train -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",EV-SI real life poly_sklearn prediction test on labeled and new data with numeric labels -15,Test5_smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_caret prediction test from saved model on new data with numeric labels -16,Test8_smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic nn_keras prediction test from saved model on new data with numeric labels and two responses -17,Test11_smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic poly_sklearn prediction test from saved model on new data with numeric labels and two responses -18,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test19_model -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 -19,test19_model,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels -20,test20_model,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test on labeled and new data with numeric labels -21,smlp_toy_num_metasymbol_mult_reg,smlp_toy_num_metasymbol_mult_reg_pred_labeled,"-mode predict -resp ""PF ,|PF |"" -model poly_sklearn -save_model t -use_model f -model_name test22_model -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f",test for illegal symbols in column names -22,test22_model,smlp_toy_num_metasymbol_mult_reg_pred_labeled,"-mode predict -resp ""PF ,|PF |"" -model poly_sklearn -save_model f -use_model t -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f",test for illegal symbols in column names -23,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test24_model -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 -24,test24_model,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels -25,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test26_model -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 -26,test26_model,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels -27,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t",checks nn_keras prediction with nn_keras_seq_api t, adapts test 4 which uses nn_keras_seq_api f -28,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -sw_coef 0.8",checks nn_keras prediction with sw_coef 0.8 and functional API, adapts test 4 -29,smlp_toy_cls_metasymbol_colnames_mult,,"-mode subgroups -psg_dim 3 -psg_top 10 -resp ""PF 1,PF#"" -plots t -seed 10 -log_time f",basic test for subgroup discovery for pass-fail responses -30,smlp_toy_num_resp_mult,,"-mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -feat x,p1,p2 -plots t -seed 10 -log_time f",basic test for subgroup discovery for numric responses -31,smlp_toy_num_resp_mult,,"-mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -resp2b ""y1<6;y2>6"" -feat x,p1,p2 -plots t -seed 10 -log_time f -save_config t",testing resp2b in subgroup discovery mode -32,test20_model,smlp_toy_num_resp_mult_pred_labeled,"-config test20_model_rerun_model_config.json", test reusing saved model by using configuration file -33,smlp_toy_num_resp_mult,,"-config Test31_smlp_toy_num_resp_mult_args_config.json",testing -config option with subgroups mode -34,doe_four_levels_real,,"-mode doe -doe_algo full_factorial -log_time f", doe test with four levels with full_factorial method -35,doe_four_levels_real,,"-mode doe -doe_algo plackett_burman -log_time f", doe test with four levels with plackett_burman -36,doe_four_levels_real,,"-mode doe -doe_algo sukharev_grid -doe_samples 125 -log_time f", doe test with four levels with sukharev_grid -37,doe_three_levels_real_nan,,"-mode doe -doe_algo box_behnken -log_time f", doe test with four levels with box_behnken -38,doe_two_levels,,"-mode doe -doe_algo box_wilson -doe_cc_face ccc -doe_cc_alpha r -doe_cc_center 2,3 -log_time f", doe test with four levels with box_wilson -39,doe_two_levels,,"-mode doe -doe_algo latin_hypercube -doe_prob_distr Exponential -doe_samples 30 -log_time f", doe test with four levels with latin_hypercube -40,doe_two_levels,,"-mode doe -doe_algo latin_hypercube_sf -doe_samples 20 -log_time f", doe test with four levels with latin_hypercube_space_filling -41,doe_two_levels,,"-mode doe -doe_algo random_k_means -doe_samples 20 -log_time f", doe test with four levels with random_k_means -42,doe_two_levels,,"-mode doe -doe_algo maximin_reconstruction -doe_samples 20 -log_time f", doe test with four levels with maximin_reconstruction -43,doe_two_levels,,"-mode doe -doe_algo halton_sequence -doe_samples 20 -log_time f", doe test with four levels with halton_sequence -44,doe_two_levels,,"-mode doe -doe_algo uniform_random_matrix -doe_samples 20 -log_time f", doe test with four levels with uniform_random_matrix -45,doe_two_levels_real,,"-mode doe -doe_algo fractional_factorial -doe_resolution 5 -log_time f", doe test with four levels with fractional_factorial -46,smlp_toy_pf_mult,smlp_toy_pf_mult,"-mode predict -resp ""PF,PF1"" -model poly_sklearn -save_model t -save_model_config f -use_model f -model_name test47_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests options -pos_val and -neg_val -47,test47_model,smlp_toy_pf_mult,"-mode predict -resp ""PF,PF1"" -model poly_sklearn -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests options -pos_val and -neg_val when re-using saved model -48,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options -49,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo quantile -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options -50,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo kmeans -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options -51,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo jenks -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options -52,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo jenks -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options -53,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo ordinals -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options -54,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo ordinals -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options -55,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo ranks -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options -56,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo ranks -discr_bins 6 -discr_labels f -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options 57,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""y1*2+x0<=5 and y1<=10;-2*y2-1<10-x2"" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn assertion verfication test with numeric labels and integer grid as domain -58,smlp_toy_num_resp_mult,,"-mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs ""y1;y2"" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn optimization test with numeric labels and integer grid as domain and without scaling objectives -59,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",basic nn_keras assertion verification test for functional nn_keras model -60,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",basic nn_keras assertion verification test for functional nn_keras model 61,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -nn_keras_epochs 100 -save_model_config f --spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""not(x25 and y1<=10);-2*y2-1<10-x2 and x2>5 and x2<8"" -vacuity f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_seq_api f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat", tests verificaion mode for NN with nn_keras_seq_api f 62,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -nn_keras_epochs 100 -nn_keras_seq_api t -save_model_config f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""not(x25 and y1<=10);-2*y2-1<10-x2 and x2>5 and x2<8"" -vacuity f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",tests verificaion mode for NN with nn_keras_seq_api t -63,smlp_toy_num_resp_mult,,"-mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test63_model -spec smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x/2+y1>4.3;(y1+p2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with numeric labels -64,test63_model,,"-mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x/2+y1>4.3;(y1+p2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with one numeric response 65,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test65_model -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x0**2+y1>4.3;(y1+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with numeric labels 66,test65_model,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x0**2+y1>4.3;(y1+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with one numeric response 67,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -model_per_response t -save_model t -use_model f -model_name test67_model -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x0**2+y1>4.3;(y1+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with numeric labels 68,test67_model,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -model_per_response t -save_model f -use_model t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x0**2+y1>4.3;(y1+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with one numeric response -69,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model t -use_model f -model_name test69_model -model_per_response t -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""(y2**3+p2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",nn_keras verification test with model_per_response training -70,test69_model,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""(y2**3+p2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",nn_keras verification test with re-using saved model_per_response trained model 71,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -save_model t -use_model f -model_name test71_model -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1 -asrt_exprs ""(y1**3+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",nn_keras verification test with model_per_response training 72,test71_model,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1 -asrt_exprs ""(y2**3+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",nn_keras verification test with re-using saved model_per_response trained model 73,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test73_model -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model 74,test73_model,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model. with separate model for each response 75,test73_model,smlp_toy_num_resp_noknobs_pred_labeled,"-config test73_model_rerun_model_config.json",verification test run using model_rerun config covering the case when mrmr selcts only a subset of features specified through the command line or config file 76,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test76_model -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model -77,test76_model,,"-config test76_model_rerun_model_config.json",verification test run using model_rerun config covering the case when mrmr selcts only a subset of features specified through the command line or config file 78,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test78_model -mrmr_pred 1 -model_per_response f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""y1==9;y2>0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model, with one model for all responses -79,smlp_toy_num_resp_mult,,"-mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult.spec -quer_names query1,query2,query3 -quer_exprs ""(y2**3+p2)/2<6;y1>=9;y2<0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in query mode to test stability (theta) and guard (eta) constraint generation -80,smlp_toy_num_resp_mult,,"-mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1 -objv_exprs ""(y1+y2)/2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives -81,smlp_toy_num_resp_mult,,"-mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1 -objv_exprs ""(y1+y2)/2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives -82,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1,objv2,objv3 -objv_exprs ""(y1+y2)/2;y1;y2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives -83,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -beta ""y1>7 and y2>6"" -objv_names obj1,objv2,objv3 -objv_exprs ""(y1+y2)/2;y1/2-y2;y2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn multi objective pareto optimization test with numeric labels and integer grid as domain and with scaling objectives 84,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -alpha ""x2==7.0 and x0==0 and x1==2.5"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests global alpha constraints specified using option -alpha on inputs -85,smlp_toy_num_resp_mult,,"-mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs ""(y1+y2)/2;y1"" -alpha ""p2<5 and x==10 and x<12"" -eta ""p1==4"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests alpha and eta constraints specified in command line in optimization mode -86,smlp_toy_num_resp_mult,,"-mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs ""(y1+y2)/2;y1"" -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+p2)/2<6;y1>=9;y2<0"" -alpha ""p2<5 and x==10 and x<12"" -eta ""p1==4"" -epsilon 0.05 -delta_rel 0.01 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests alpha,beta and eta constraints specified in command line in optimization mode -87,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_alpha_asrt_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests global alpha constraints and assertions specified in spec file, equivalent to test 84 where the same alpha and assertions are specified in command line -88,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn multi objective pareto optimization test with beta and objectives specified in spec file, must give same results as test 83 where same beta and objectives is specified in command line -89,smlp_toy_num_resp_mult,,"-mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in query mode to test stability (theta) and guard (eta) constraint generation -90,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test to detect contradictory constraints in optsyn mode -91,smlp_toy_num_resp_mult,,"-mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_query_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test to detect contradictory constraints in optimization mode due to contradictory alpha global and alpha bounds constraints on FMAX_xyx -92,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_verify_vacuous.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test to detect contradictory constraints in verification mode -93,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for mode optsyn -94,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for rf_sklearn in model exploration mode optsyn -95,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for dt_caret in model exploration mode optsyn -96,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for rf_sklearn in model exploration mode optsyn -97,smlp_toy_num_resp_mult,,"-mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for rf_sklearn in model exploration mode optsyn -98,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_caret in model exploration mode optsyn -99,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",testing that the response and feature names can be taken from spec file in model exploration modes when the responses and/or features are not specified in the command line -100,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for sat_threshold option enabing usage of objectve values in SAT assignments that prove optimization thresholds -101,smlp_toy_num_resp_mult,,"-mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test101_model -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs ""(y2**3+p2)/2<6;y1>=9;y2<20"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in certify mode to test stability (theta) and guard (eta) constraint generation -102,test101_model,,"-mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs ""(y2**3+p2)/2<6;y1>=9;y2<20"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in certify mode to test stability (theta) and guard (eta) constraint generation -103,smlp_toy_num_resp_mult,,"-mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test103_model -model_per_response f -spec smlp_toy_num_resp_mult_certify_witness.spec -quer_names valid_candidate,grid_conflict,range_conflict -quer_exprs ""True;True;True"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",,basic test in certify mode to test one valid witness and two conflicting witnesses for queries that are constant true -104,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""y1*2+x<=5 and y1<=10;-2*y2-1<10-p2"" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",assertion verfication test with wrong spec that does not assign a single value using a singleton grid or range with equal max and min -105,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_stable_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""y1*2+x<=5 and y1<=10;-2*y2-1<10-p2"" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn assertion verfication test with numeric labels and integer grid as domain -106,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_unsat_eta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""y1*2+x<=5 and y1<=10;-2*y2-1<10-p2"" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined -107,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_beta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""y1*2+x<=5 and y1<=10;-2*y2-1<10-p2"" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined -108,smlp_toy_num_resp_mult,,"-mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for dt_sklearn in model exploration mode synthesize where synthesis succeeds -109,smlp_toy_num_resp_mult,,"-mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_cannot_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for mode synthesize where synthesis fails -110,smlp_toy_basic,smlp_toy_basic_pred_unlabeled,"-mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model t -model_name test110_model -save_model_config t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",smlp toy basic example for predict mode from SMLP user manual -111,test110_model,smlp_toy_basic_pred_unlabeled,"-config test110_model_rerun_model_config.json",smlp toy basic test to rerun saved model using the model rerun config file saved during model training -112,test110_model,smlp_toy_basic_pred_unlabeled,"-mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -use_model t -save_model f",smlp toy basic test from SMLP manual, to rerun saved model without using the model rerun config file saved during model training and directly adding required options to command that match option values used during training -113,smlp_toy_basic,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model t -model_name test113_model -save_model_config t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec smlp_toy_basic.spec",smlp toy basic test for mode optimize from SMLP manual -114,smlp_toy_basic,,"-mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model f -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec smlp_toy_basic.spec",smlp toy basic test for mode optimize from SMLP manual without specifying resp and feat in command line -115,smlp_toy_basic,,"-mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_system.spec -quer_names query1,query2 -quer_exprs ""y1>0;y2<=0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in certify mode -116,smlp_toy_basic,,"-mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_system.spec -quer_names query1,query2 -quer_exprs ""y1>0;y2<=0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in certify mode when system is specified and is used as the model; p2 rel-rad needs to be 0 or very close to it the witness to first query to be stable -117,smlp_toy_basic,,"-mode certify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",certification test with knobs only where assertion is valid without stability and fails with stability -118,smlp_toy_basic,,"-mode verify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",verification test with knobs only where assertion is valid without stability and fails with stability -119,smlp_toy_basic,,"-mode query -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",query test with knobs only where query is satisfiable without stability and fails with stability -120,smlp_toy_basic,,"-mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_fail.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",synthesis test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible -121,smlp_toy_basic,,"-mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",synthesis test with constant knob and no inputs where synthesis is feasible -122,smlp_toy_basic,,"-mode optimize -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed -123,smlp_toy_basic,,"-mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed -124,smlp_toy_basic,,"-mode optsyn -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimized synthesis test with constant knob and no inputs where synthesis is not feasible because while beta constraint is feasible the assertion is not feasible therefore optimization is not performed -125,smlp_toy_basic,,"-mode optsyn -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimized synthesis test with constant knob and no inputs where synthesis is feasible and optimization is performed -126,smlp_toy_basic,,"-mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability -127,smlp_toy_basic,,"-mode certify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",certification example with knobs only and fictitious inputs with values fixed through their ranges, where query is valid without stability and fails with stability -128,smlp_toy_ctg_num_resp,,"-mode certify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model f -model_per_response f -spec smlp_toy_witness_certify.spec -quer_names query_stable_witness,query_grid_conflict,query_unstable_witness,query_infeasible_witness,query_poly_intercept_sensitive -quer_exprs ""y2<=90;y1>=9;y1>=(-13);y1>9;y1>=(-10)"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",Basic regression test in certify mode covering all four possible outcomes when certifying a witness for a query: the witness is stable, the witness is valid but not stable, the witness is invalid, and the constraints are conflicting. The fifth query and witness capture a scenario where the polynomial model conversion to terms was missing the intercepts. -129,smlp_toy_ctg_num_resp,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model f -model_per_response f -spec smlp_toy_configuration_verify.spec -asrt_names assert_stable_config,assert_grid_conflict,assert_unstable_config,assert_infeasible -asrt_exprs ""y2<=90;y1>=9;y1>=(-10);y1>20"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",verification example with demonstrating all basic result scenarious for assertions -130,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x1,x2,p1,p2 -resp y1,y2 -model dt_sklearn -tree_encoding nested -compress_rules f -spec smlp_toy_const_input.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",captures scenario that interface constraints are consistent but model constraints are (because y2 is declared as int and not as real) -- constant input x1 is dropped as constant feature since it does not occur in constraints -131,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x1,x2,p1,p2 -resp y1,y2 -model dt_sklearn -tree_encoding nested -compress_rules f -spec smlp_toy_const_input_const_range.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test where input x1 has a constant range 0 and in data it is also constant and it is dropped before building the model because it does not occur in constraints alpha, eta, beta -132,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x1,x2,p1,p2 -resp y1,y2 -model dt_sklearn -tree_encoding nested -compress_rules f -spec smlp_toy_const_input_alpha.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test where input x1 has a non-constant range 0 to 1 and in data it is constant and it is not dropped before building the model because its range is constrained to constant value through alpha constraint -133,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x2,p1,p2 -resp y1,y2 -model dt_sklearn -tree_encoding nested -compress_rules f -spec smlp_toy_const_input_dropped.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",captures scenario that interface constraints are consistent but model constraints are not (because y2 is declared as int and not as real) -- constant inut x1 is dropped explicitly using -feat option ; uses uses dt_sklearn -134,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x2,p1,p2 -resp y1,y2 -model system --spec smlp_toy_consistent_system.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test that model cnstraints are consistent with interface constraints when system is used as the model and output y2 is declared as int -- the model constraints are consistent because y2 is defined as p1+p2-x2 and due to constraints all these variables can assume only integer values thus u2 can also only be an integer -135,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x2,p1,p2 -resp y1,y2 -model nn_keras -nnet_encoding nested -nn_keras_epochs 20 -spec smlp_toy_const_input_dropped.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",captures scenario where interface constraints are consistent but model constraints are not (because y2 is declared as int and not as real) -- constant inut x1 is dropped explicitly using -feat option ; uses nn_keras model which is the only difference with test 133 but which model is used does not matter as the problem is in declaration of y2 as int -136,smlp_toy_num_resp_mult_compressed.csv.gz,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests usage of compressed data files as well as data files without .csv suffix -137,smlp_toy_num_resp_mult_compressed,smlp_toy_num_resp_mult_compressed.csv.bz2,"-mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model_config f -spec smlp_toy_num_resp_mult_synthesize.spec -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests usage of compressed data files as well as data files without .csv suffix -138,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x2,p1,p2 -resp y1,y2 -model system --spec smlp_toy_inconsistent_system.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",adapts test 134 by changing the system function for y2 to p1+p2-x2+0.01 so while p1,p2 and x2 can only assume int values y2 can become non-integer which violates the declartion of y2 as integer -- hence the conflict of the system/model constraints with alpha and eta constraits and variable domain declarations 139,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model -140,smlp_toy_basic,,"-mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_verify.spec -trace_prec 1 -trace_anonym t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability -141,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -pareto f -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -spec smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs ""y1;y2"" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for compress_rules option for dt_sklearn in optimization mode -142,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for compress_rules option for rf_sklearn in optsin mode -143,smlp_toy_num_resp_mult,,"-mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for compress_rules for et_sklearn in mode query 144,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -save_model f -use_model f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x0**2+y1>4.3;(y1+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic test for compress_rules for dt_sklearn in mode verify and re-using saved model -145,,,"-mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed -146,,,"-mode optimize -pareto t -opt_strategy lazy -model poly_sklearn -resp y1,y2 -feat p1,p2,x1,x2 -save_model t -use_model f -mrmr_pred 0 -model_per_response t -split 1 -spec smlp_toy_system.spec -doe_spec ../grids/explore_doe_two_levels.csv -doe_algo latin_hypercube -epsilon 0.99999999 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed -147,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8",checks nn_keras prediction with sw_coef 0.8 and sequential API, adapts test 28 -148,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8",checks nn_keras prediction with sw_coef 0.8 and sequential API, adapts test 28 to have two responses -149,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mae -sw_coef 0.8",tests the mae loss function MeanAbsoluteError and sample weoghts -150,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -sw_coef 0.8",tests the mape loss function MeanAbsolutePercentageError and sample weights -151,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss msle -sw_coef 3 -sw_exp 10 -sw_int 0",tests msle loss function MeanSquaredLogarithmicError and and sample weoghts -152,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss huber -sw_coef 8 -sw_exp 5 -sw_int 0.5",tests the huber loss function Huber and sample weights -153,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss logcosh -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mse",tests the logcosh loss function LogCosh and sample weights -154,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3,3,3"" -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5",basic nn_keras assertion verification test that uses keras tuner for functional model training -155,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3,3,3"" -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae",basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training -156,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3"" -save_model_config f -spec smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse",basic nn_keras assertion verification test that uses keras tuner for functional model training; adapts test 154 by consdering multiple responses -157,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 --model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3"" -save_model_config f -spec smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse,logcosh",basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training; adapts test 155 by consdering multiple responses -158,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -model_per_response t -sw_coef 8 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse",tests the mape loss function and sample weights with model_per_response t, adapts test 152 -159,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -model_per_response t -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae,cosine",tests the msle loss function and sample weights with model_per_response t, adapts test 153 -160,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -nn_keras_metrics msle -nn_keras_tuner bayesian -nn_keras_layers_grid ""2,3"" -nn_keras_losses_grid ""mse,mae,huber"" -model_per_response f -sw_coef 8 -sw_exp 5 -sw_int 0.5",tests nn keras tuner bayesian -161,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -nn_keras_metrics mape,logcosh -nn_keras_tuner random -nn_keras_lrates_grid ""0.01,0.001"" -nn_keras_batches_grid ""32,64"" -model_per_response f -sw_coef 4 -sw_exp 5 -sw_int 0.5",tests nn keras tuner bayesian 162,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term construction with flat_encoding of tress and model per reponse when mrmr_pred is activated and not all features are selected for training the model, adapts test 139 163,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model, adapts test 139 -164,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test for dt_sklearn multi objective pareto optimization -165,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding flat -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test for dt_caretin model exploration mode optsyn, model_per_response is forced to true for caret models, adapts test 95 -166,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn -167,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn, adapts test 94 and test 166 -168,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding flat -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for rf_caret with flat tree_encoding and modelper_response in model exploration mode optimize -169,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with flat tree_encoding and model_per_response t in model exploration mode optimize -170,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with flat tree_encoding and model_per_response f in model exploration mode optimize -171,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_caret with flat tree_encoding in model exploration mode optimize -172,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3,3,3"" -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -solver_path "mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"",basic test for nn_keras flat encoding for functional api, i, one response variable, adapts test 154 -173,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3,3,3"" -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae -solver_path "mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"",basic test for nn_keras flat encoding for sequential api, one response variable, adapts test 155 -174,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn -175,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn -176,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api f for nn_keras in model exploration mode optsyn -177,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn -178,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -scale_feat f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features are not scaled adapts test 177 -179,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_resp f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn when resposes are not scaled adapts test 174 -180,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_feat f -scale_resp f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features and responses are not scaled adapts test 175 -181,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_feat f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 -182,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path "mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"",basic flat tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 -183,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -scale_feat f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 184,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model adapts test 139 185,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term construction with branched_encoding of tress and model per reponse when mrmr_pred is activated and not all features are selected for training the model, adapts test 162 186,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model, adapts test 163 -187,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic branched tree encoding test for dt_sklearn multi objective pareto optimization adapts test 164 -188,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding branched -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic branched tree encoding test for dt_caretin model exploration mode optsyn, model_per_response is forced to true for caret models, adapts test 165 -189,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic branched tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn adapts test 166 -190,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding branched -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for rf_caret with branched tree_encoding and modelper_response in model exploration mode optimize adapts test 168 -191,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap t -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with branched tree_encoding and model_per_response t in model exploration mode optimize adapts test 169 -192,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results, cvc5 faild with incomparable ite tipes for if and else branches) -193,smlp_toy_num_resp_mult,,"-mode optimize -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_caret with branched tree_encoding in model exploration mode optimize adapts test 171 -194,smlp_toy_num_resp_mult,,"-mode optsyn -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic branched tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn, adapts test 94 and test 167 -195,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 192 by setting n_estimators 3 and then discrepancy between z3, mathsat and yices results disappear -196,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_feat f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 and test 181 -197,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path "mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"",basic branched tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 and test 182 -198,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -scale_feat f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 and test 183 -199,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test to demonstrate that in pareto optimization and optsyn modes with multiple objectives when beta constraints are not present SMLP results are not consistent when different solvers are used; this is due to fact that when a subset of objectoves are exemined in pareto algo, outputs not covered by the active objectives become don't cares (there are no contraints on then except model constraints) and this situation is likely not modeled in SMLP accurately; modifies test 192 to use z3 instead of mathsat -200,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results, cvc5 faild with incomparable ite tipes for if and else branches) -201,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_num_resp_mult_no_input_beta.spec -data_scaler min_max -objv_names obj1 -objv_exprs ""(y1+y2)/2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and there are beta constraints -202,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_num_resp_mult_no_input.spec -data_scaler min_max -objv_names obj1 -objv_exprs ""(y1+y2)/2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and no beta constraints -203,smlp_toy_basic,,"-mode optimize -pareto f -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with eager strategy and with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed adapts test 122 -204,smlp_toy_basic,,"-mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 123 -205,,,"-mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 145 -206,smlp_toy_basic,,"-mode optsyn -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimized synthesis test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 125 -207,smlp_toy_frontier_beta,,"-mode frontier -pareto t -resp y -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_beta.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for mode frontier -- selecting pareto frontier directly from data without building a model -208,smlp_toy_frontier_beta,,"-mode frontier -pareto t -resp y -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_real.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",testing unbounded knob and input domains for mode frontier when knob and input are of type real -- bounds inf and minus inf are specified in the spec file as null -209,smlp_toy_frontier_null_bounds_int,,"-mode frontier -pareto t -resp y -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_int.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",testing unbounded knob and input domains for mode frontier when knob and input are of typ eint -- bounds inf and minus inf are specified in the spec file as null -210,smlp_toy_frontier_null_bounds_empty,,"-mode frontier -pareto t -resp y1,y2 -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_empty_eta.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test for the frontier mode on data and spec such that no data points satisfy eta constrints, as a result the pareto frontier is empty -211,smlp_toy_frontier_null_bounds_empty,,"-mode frontier -pareto t -resp y1,y2 -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_empty_alpha.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test for the frontier mode on data and spec such that no data points satisfy eta constrints, as a result the pareto frontier is empty -212,smlp_toy_frontier_null_bounds_int,,"-mode optimize -pareto t -resp y -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_int.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",testing unbounded knob and input domains for optimization mode -- bounds inf and minus inf are specified in the spec file as null -213,smlp_toy_frontier_null_bounds_empty,,"-mode optimize -pareto t -resp y1,y2 -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_empty_eta.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test optimize mode on data and spec such that no data points satisfy eta constrints -214,smlp_toy_frontier_null_bounds_empty,,"-mode optimize -pareto t -resp y1,y2 -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_empty_alpha.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test for the frontier mode on data and spec such that no data points satisfy eta constrints, as a result the pareto frontier is empty -215,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type object -216,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode -217,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type category, adapts test 215 -218,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type ordered, adapts test 215 -219,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type integer -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features casted to integer, adapts test 215 -220,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type object and tests the normalized mutual information, adapts test 215 -221,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type object and tests the Shannon mutual information, adapts test 215 -222,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type object and tests the adjusted mutual information, adapts test 215 -223,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode and tests the normalized mutual information, adapts test 216 -224,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode and tests the Shannon mutual information, adapts test 216 -225,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode and tests the adjusted mutual information, adapts test 216 -226,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode -227,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode and tests the normalized mutual information, adapts test 216 and 223 -228,smlp_toy_basic,,"-mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_system_radii_update_certify.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test that radii specified in command line properly override the radii specified in the spec file. Here we override both ansolute and relative radii and one can observe that the certification results also change compared to test 116 -229,smlp_toy_basic,,"-mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_missing_radii.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for checking that each knob must have either absolute or relative radius specified in the spec file (even if radii are specified in the command line) -230,smlp_toy_monotone_basic.csv,,"-mode verify -spec smlp_toy_system_monotone_knob.05_verify.spec -model system -seed 10 -log_time f",tests that outputs in system specificaation might depend on different inuts (knobs and free inputs) -231,smlp_toy_monotone_basic.csv,,"-mode certify -spec smlp_toy_system_decreasing_knob.05_certify.spec -model system -seed 10 -log_time f",certification test with monotonicity query with a knob with a grid point -232,smlp_toy_system_running_example_certify,,"-mode certify -spec smlp_toy_system_running_example_certify.spec -model system -seed 10 -log_time f",running example from smlp manual, contains for witnesses to a query, covering all possible witness scenarios -- stable witness, unstable witness, and not a witness cases -233,smlp_toy_string_response,,"-mode subgroups -resp str_resp1 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f",tests subgroup discovery mode when the response has string values, e,g, yes/no, pass/fail -234,smlp_toy_string_response,,"-mode subgroups -resp str_resp1,str_resp2 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f",tests subgroup discovery mode when there are two responses with string values, e,g, yes/no, pass/fail \ No newline at end of file diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv index 7e422b02..12103ffa 100644 --- a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -7,6 +7,6 @@ witness_consistency,sat,1.0,7.0,5.0,5.0 ca,unsat ce,sat,4.0,6.0,5.0,9.0 ca,sat,7.0,6.75,9.0,9.0 -ce,sat,1.0,6.0,5.0,5.0 +ce,sat,1.0,7.0,5.0,5.0 ca,unsat ce,sat,1.0,7.0,5.0,5.0 diff --git a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json index 6fb0d0ac..10878543 100644 --- a/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json +++ b/regr_smlp/master/Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -16,7 +16,7 @@ "counter_example": { "x1": 1.0, "y1": 5.0, - "x2": 6.000000067055225, + "x2": 7.0, "y2": 5.0 }, "assertion_feasible": true diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_trace.csv index eb2af845..4c2323a8 100644 --- a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_trace.csv +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_trace.csv @@ -1,9 +1,9 @@ stage,solver,x0,x1,x2,y1,y2 interface_consistency,sat,0,7,3 -model_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -ca,sat,0,1,6,5,5 +model_consistency,sat,0,7,805306377/134217728,9,9 +witness_consistency,sat,0,7,805306377/134217728,9,9 +witness_consistency,sat,0,7,805306377/134217728,9,9 +ca,sat,1,1,27/4,9,5 ce,unsat -ca,sat,0,7,671088649/134217728,5,9 -ce,sat,0,7,805306377/134217728,9,9 +ca,sat,0,1,1140850697/201326592,5,5 +ce,sat,0,4,805306377/134217728,9,9 diff --git a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_verify_results.json index d670b00a..1579ae5d 100644 --- a/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_verify_results.json +++ b/regr_smlp/master/Test144_smlp_toy_num_resp_noknobs_verify_results.json @@ -10,7 +10,7 @@ "assertion_status": "FAIL", "counter_example": { "x0": 0.0, - "x1": 7.0, + "x1": 4.0, "y1": 9.0, "x2": 6.000000067055225, "y2": 9.0 diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv index b03b562a..48952dda 100644 --- a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -5,7 +5,7 @@ witness_consistency,sat,7.0,6.0,5.0,9.0 witness_consistency,sat,7.0,6.0,5.0,9.0 witness_consistency,sat,7.0,6.0,5.0,9.0 ca,unsat -ce,sat,1.0,6.0,5.0,5.0 +ce,sat,1.0,4.0,9.0,9.0 ca,sat,7.0,6.75,9.0,9.0 ce,sat,7.0,6.0,5.0,9.0 ca,unsat diff --git a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json index bfbd8788..bd094f27 100644 --- a/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json +++ b/regr_smlp/master/Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -4,9 +4,9 @@ "assertion_status": "FAIL", "counter_example": { "x1": 1.0, - "y1": 5.0, - "x2": 6.0, - "y2": 5.0 + "y1": 9.0, + "x2": 4.0, + "y2": 9.0 }, "assertion_feasible": false }, diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv index d02bcf19..af6fe955 100644 --- a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -5,7 +5,7 @@ witness_consistency,sat,7.0,6.75,9.0,9.0 witness_consistency,sat,7.0,6.75,9.0,9.0 witness_consistency,sat,7.0,6.75,9.0,9.0 ca,unsat -ce,sat,1.0,6.0,5.0,5.0 +ce,sat,1.0,4.0,9.0,9.0 ca,sat,7.0,4.5,9.0,9.0 ce,sat,7.0,3.0,5.0,9.0 ca,unsat diff --git a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json index ecf438cc..48d869a3 100644 --- a/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json +++ b/regr_smlp/master/Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -4,9 +4,9 @@ "assertion_status": "FAIL", "counter_example": { "x1": 1.0, - "y1": 5.0, - "x2": 6.0, - "y2": 5.0 + "y1": 9.0, + "x2": 4.0, + "y2": 9.0 }, "assertion_feasible": false }, diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv index d7a466e1..b94ebfd2 100644 --- a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -1,12 +1,12 @@ stage,solver,x0,x1,x2,y0,y1 interface_consistency,sat,7.0,3.0 -model_consistency,sat,1.0,6.0,5.0,5.0 -witness_consistency,sat,1.0,6.0,5.0,5.0 -witness_consistency,sat,1.0,6.0,5.0,5.0 -witness_consistency,sat,1.0,6.0,5.0,5.0 +model_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 ca,unsat ce,sat,1.0,3.5,5.0,9.0 -ca,sat,4.0,4.5,9.0,9.0 -ce,sat,1.0,6.0,5.0,5.0 +ca,sat,7.0,6.75,9.0,9.0 +ce,sat,7.0,6.0,5.0,9.0 ca,unsat -ce,sat,1.0,7.0,5.0,5.0 +ce,sat,7.0,6.0,5.0,9.0 diff --git a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json index 12ff6934..ad4bf886 100644 --- a/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json +++ b/regr_smlp/master/Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -14,10 +14,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 1.0, + "x1": 7.0, "y1": 5.0, "x2": 6.000000067055225, - "y2": 5.0 + "y2": 9.0 }, "assertion_feasible": true }, @@ -25,10 +25,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 1.0, + "x1": 7.0, "y1": 5.0, - "x2": 7.0, - "y2": 5.0 + "x2": 6.000000067055225, + "y2": 9.0 }, "assertion_feasible": false }, diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv index d7a466e1..b94ebfd2 100644 --- a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -1,12 +1,12 @@ stage,solver,x0,x1,x2,y0,y1 interface_consistency,sat,7.0,3.0 -model_consistency,sat,1.0,6.0,5.0,5.0 -witness_consistency,sat,1.0,6.0,5.0,5.0 -witness_consistency,sat,1.0,6.0,5.0,5.0 -witness_consistency,sat,1.0,6.0,5.0,5.0 +model_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 ca,unsat ce,sat,1.0,3.5,5.0,9.0 -ca,sat,4.0,4.5,9.0,9.0 -ce,sat,1.0,6.0,5.0,5.0 +ca,sat,7.0,6.75,9.0,9.0 +ce,sat,7.0,6.0,5.0,9.0 ca,unsat -ce,sat,1.0,7.0,5.0,5.0 +ce,sat,7.0,6.0,5.0,9.0 diff --git a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json index 12ff6934..ad4bf886 100644 --- a/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json +++ b/regr_smlp/master/Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -14,10 +14,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 1.0, + "x1": 7.0, "y1": 5.0, "x2": 6.000000067055225, - "y2": 5.0 + "y2": 9.0 }, "assertion_feasible": true }, @@ -25,10 +25,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 1.0, + "x1": 7.0, "y1": 5.0, - "x2": 7.0, - "y2": 5.0 + "x2": 6.000000067055225, + "y2": 9.0 }, "assertion_feasible": false }, diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv index 6950c9de..3b24cc62 100644 --- a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -1,12 +1,12 @@ stage,solver,x0,x1,x2,y0,y1 interface_consistency,sat,7.0,3.0 -model_consistency,sat,7.0,6.0,9.0,9.0 -witness_consistency,sat,7.0,6.0,9.0,9.0 -witness_consistency,sat,7.0,6.0,9.0,9.0 -witness_consistency,sat,7.0,6.0,9.0,9.0 +model_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 +witness_consistency,sat,1.0,7.0,5.0,5.0 ca,unsat ce,sat,1.0,3.5,5.0,9.0 -ca,sat,7.0,4.5,9.0,9.0 -ce,sat,1.0,7.0,5.0,5.0 +ca,sat,7.0,6.0,9.0,9.0 +ce,sat,1.0,6.0,5.0,5.0 ca,unsat -ce,sat,7.0,4.5,9.0,9.0 +ce,sat,1.0,6.0,5.0,5.0 diff --git a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json index c0d0467c..011e9613 100644 --- a/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json +++ b/regr_smlp/master/Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -16,7 +16,7 @@ "counter_example": { "x1": 1.0, "y1": 5.0, - "x2": 7.0, + "x2": 6.000000067055225, "y2": 5.0 }, "assertion_feasible": true @@ -25,10 +25,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 7.0, - "y1": 9.0, - "x2": 4.500000007450581, - "y2": 9.0 + "x1": 1.0, + "y1": 5.0, + "x2": 6.000000067055225, + "y2": 5.0 }, "assertion_feasible": false }, diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_dt_sklearn_model_complete.pkl index 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f92f3704e4cfa342b9f9ce374f180c11ee7ede02..d12c53994522ad0d816235e1252c93c64f21f62b 100644 GIT binary patch delta 39 tcmX@bx{sBmfo1CEi7dZ)nJNsX^e|Nzf(WC{5{#=E*-i9}rj#b>0RR$L4DA2_ delta 51 zcmdnTdWw~$fo1Cci7dY*Ioy05BjPJ6tETion2AZrQ+k*Rj5qTzu4ZI6&@-A+nxqE+ D*{Bgv diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_responses_scaler.pkl b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_responses_scaler.pkl index 07d03657639a6bc283b528a172eb78e8c71db4b4..f2576be20c9aab6434a4d801eeba1b3a7478a6ac 100644 GIT binary patch delta 33 pcmbQrI+2y7fn{pjM3&#|OqGUHdYCFVb1}9svYY4`O({*%0|2s53Ml{p delta 37 qcmbQpI+c~Bfn{pfM3&#&EP185hEsY#)Mhru7DjdhJ) x_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> p2_scaled (/ 53687093 134217728)) (<= p1_scaled (/ 3 4))) (<= x_scaled (/ 33554433 67108864))) (<= p2_scaled (/ 23488103 33554432))) 0 (ite (and (> p2_scaled (/ 53687093 134217728)) (> p1_scaled (/ 3 4))) 1 (ite (and (and (and (> p2_scaled (/ 53687093 134217728)) (<= p1_scaled (/ 3 4))) (<= 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0)))))>, 'y2_scaled': x0_scaled (/ 44739243 67108864))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (<= x2_scaled (/ 23488103 33554432))) 0 (ite (and (> x2_scaled (/ 53687093 134217728)) (> x1_scaled (/ 3 4))) 1 (ite (and (and (and (> x2_scaled (/ 53687093 134217728)) (<= x1_scaled (/ 3 4))) (<= x0_scaled (/ 33554433 67108864))) (> x2_scaled (/ 23488103 33554432))) 0 0)))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_trace.csv index bd573129..76dae09a 100644 --- a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_trace.csv +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_trace.csv @@ -1,9 +1,9 @@ stage,solver,x0,x1,x2,y1,y2 interface_consistency,sat,0,7,3 -model_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 +model_consistency,sat,0,7,805306377/134217728,9,9 +witness_consistency,sat,0,7,805306377/134217728,9,9 +witness_consistency,sat,0,7,805306377/134217728,9,9 ca,unsat -ce,sat,0,1,7,9,5 -ca,sat,0,7,671088649/134217728,5,9 +ce,sat,0,4,805306377/134217728,9,9 +ca,sat,0,1,805306377/134217728,5,5 ce,unsat diff --git a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_verify_results.json index cc3c4b12..65c62fc8 100644 --- a/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_verify_results.json +++ b/regr_smlp/master/Test57_smlp_toy_num_resp_noknobs_verify_results.json @@ -4,10 +4,10 @@ "assertion_status": "FAIL", "counter_example": { "x0": 0.0, - "x1": 1.0, + "x1": 4.0, "y1": 9.0, - "x2": 7.0, - "y2": 5.0 + "x2": 6.000000067055225, + "y2": 9.0 }, "assertion_feasible": false }, diff --git a/regr_smlp/master/Test61_smlp_toy_num_resp_noknobs_features_scaler.pkl 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((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x0_scaled (/ 1208381 2097152)) (* x1_scaled (/ 2938155 4194304))) (* x2_scaled (/ (- 10195595) 33554432))) (/ 3298773 33554432)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 1958803 8388608)) (* |:3| (/ 3285671 8388608))) (* |:5| (/ (- 1798427) 8388608))) (* |:7| (/ (- 14391915) 33554432))) (* |:9| (/ (- 5538481) 8388608))) (* |:11| (/ (- 11806169) 33554432))) 0))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ 10348145 16777216)) (* |:3| (/ 2493617 16777216))) (* |:5| (/ 14212267 16777216))) (* |:7| (/ (- 5570941) 8388608))) (* |:9| (/ (- 11410359) 16777216))) (* |:11| (/ (- 15592633) 33554432))) (/ 5899637 134217728)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 13799583) 33554432)) (* |:3| (/ (- 214595) 4194304))) (* |:5| (/ (- 4053207) 16777216))) (* |:7| (/ 315509 8388608))) (* |:9| (/ (- 10656705) 16777216))) (* |:11| (/ 4727225 8388608))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ (- 4882399) 8388608)) (* (ite (>= |:13| 0) |:13| 0) (/ 4987691 8388608))) (* (ite (>= |:14| 0) |:14| 0) (/ (- 1315209) 8388608))) (/ 12647359 134217728)))))))))))))))))>, 'y2_scaled': = |:0| 0) |:0| 0))) (let ((|:2| (+ (+ (+ (* x0_scaled (/ (- 12675489) 16777216)) (* x1_scaled (/ (- 15700433) 33554432))) (* x2_scaled (/ (- 14143067) 33554432))) 0))) (let ((|:3| (ite (>= |:2| 0) |:2| 0))) (let ((|:4| (+ (+ (+ (* x0_scaled (/ 9900335 16777216)) (* x1_scaled (/ (- 5448211) 16777216))) (* x2_scaled (/ 12339293 16777216))) (/ 12035361 268435456)))) (let ((|:5| (ite (>= |:4| 0) |:4| 0))) (let ((|:6| (+ (+ (+ (* x0_scaled (/ 11088463 134217728)) (* x1_scaled (/ 211449 4194304))) (* x2_scaled (/ 12447363 16777216))) (/ (- 12828253) 134217728)))) (let ((|:7| (ite (>= |:6| 0) |:6| 0))) (let ((|:8| (+ (+ (+ (* x0_scaled (/ 10855307 67108864)) (* x1_scaled (/ 965293 2097152))) (* x2_scaled (/ (- 15015817) 268435456))) (/ 8969903 4294967296)))) (let ((|:9| (ite (>= |:8| 0) |:8| 0))) (let ((|:10| (+ (+ (+ (* x0_scaled (/ 1208381 2097152)) (* x1_scaled (/ 2938155 4194304))) (* x2_scaled (/ (- 10195595) 33554432))) (/ 3298773 33554432)))) (let ((|:11| (ite (>= |:10| 0) |:10| 0))) (let ((|:12| (+ (+ (+ (+ (+ (+ (* |:1| (/ 1958803 8388608)) (* |:3| (/ 3285671 8388608))) (* |:5| (/ (- 1798427) 8388608))) (* |:7| (/ (- 14391915) 33554432))) (* |:9| (/ (- 5538481) 8388608))) (* |:11| (/ (- 11806169) 33554432))) 0))) (let ((|:13| (+ (+ (+ (+ (+ (+ (* |:1| (/ 10348145 16777216)) (* |:3| (/ 2493617 16777216))) (* |:5| (/ 14212267 16777216))) (* |:7| (/ (- 5570941) 8388608))) (* |:9| (/ (- 11410359) 16777216))) (* |:11| (/ (- 15592633) 33554432))) (/ 5899637 134217728)))) (let ((|:14| (+ (+ (+ (+ (+ (+ (* |:1| (/ (- 13799583) 33554432)) (* |:3| (/ (- 214595) 4194304))) (* |:5| (/ (- 4053207) 16777216))) (* |:7| (/ 315509 8388608))) (* |:9| (/ (- 10656705) 16777216))) (* |:11| (/ 4727225 8388608))) 0))) (+ (+ (+ (* (ite (>= |:12| 0) |:12| 0) (/ (- 4231593) 4194304)) (* (ite (>= |:13| 0) |:13| 0) (/ (- 11739661) 1073741824))) (* (ite (>= |:14| 0) |:14| 0) (/ 373001 1048576))) (/ 12626933 134217728)))))))))))))))))>}" \ No newline at end of file diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_trace.csv index eb2af845..4c2323a8 100644 --- a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_trace.csv +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_trace.csv @@ -1,9 +1,9 @@ stage,solver,x0,x1,x2,y1,y2 interface_consistency,sat,0,7,3 -model_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -ca,sat,0,1,6,5,5 +model_consistency,sat,0,7,805306377/134217728,9,9 +witness_consistency,sat,0,7,805306377/134217728,9,9 +witness_consistency,sat,0,7,805306377/134217728,9,9 +ca,sat,1,1,27/4,9,5 ce,unsat -ca,sat,0,7,671088649/134217728,5,9 -ce,sat,0,7,805306377/134217728,9,9 +ca,sat,0,1,1140850697/201326592,5,5 +ce,sat,0,4,805306377/134217728,9,9 diff --git a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_verify_results.json index d670b00a..1579ae5d 100644 --- a/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_verify_results.json +++ b/regr_smlp/master/Test65_smlp_toy_num_resp_noknobs_verify_results.json @@ -10,7 +10,7 @@ "assertion_status": "FAIL", "counter_example": { "x0": 0.0, - "x1": 7.0, + "x1": 4.0, "y1": 9.0, "x2": 6.000000067055225, "y2": 9.0 diff --git a/regr_smlp/master/Test66_test65_model_trace.csv b/regr_smlp/master/Test66_test65_model_trace.csv index eb2af845..4c2323a8 100644 --- a/regr_smlp/master/Test66_test65_model_trace.csv +++ b/regr_smlp/master/Test66_test65_model_trace.csv @@ -1,9 +1,9 @@ stage,solver,x0,x1,x2,y1,y2 interface_consistency,sat,0,7,3 -model_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -ca,sat,0,1,6,5,5 +model_consistency,sat,0,7,805306377/134217728,9,9 +witness_consistency,sat,0,7,805306377/134217728,9,9 +witness_consistency,sat,0,7,805306377/134217728,9,9 +ca,sat,1,1,27/4,9,5 ce,unsat -ca,sat,0,7,671088649/134217728,5,9 -ce,sat,0,7,805306377/134217728,9,9 +ca,sat,0,1,1140850697/201326592,5,5 +ce,sat,0,4,805306377/134217728,9,9 diff --git a/regr_smlp/master/Test66_test65_model_verify_results.json b/regr_smlp/master/Test66_test65_model_verify_results.json index d670b00a..1579ae5d 100644 --- a/regr_smlp/master/Test66_test65_model_verify_results.json +++ b/regr_smlp/master/Test66_test65_model_verify_results.json @@ -10,7 +10,7 @@ "assertion_status": "FAIL", "counter_example": { "x0": 0.0, - "x1": 7.0, + "x1": 4.0, "y1": 9.0, "x2": 6.000000067055225, "y2": 9.0 diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_trace.csv index 1c931f44..fa2d5f5f 100644 --- a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_trace.csv +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_trace.csv @@ -1,9 +1,9 @@ stage,solver,x0,x1,x2,y1,y2 interface_consistency,sat,0,7,3 -model_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -ca,sat,0,1,27/4,9,5 +model_consistency,sat,0,1,7,9,5 +witness_consistency,sat,0,1,7,9,5 +witness_consistency,sat,0,1,7,9,5 +ca,sat,1,1,4,5,9 ce,unsat -ca,sat,0,1,1140850697/201326592,5,5 -ce,sat,0,1,7,9,5 +ca,sat,0,7,218103811/33554432,5,9 +ce,sat,0,7,7,9,9 diff --git a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_verify_results.json index b85d3149..1029a19f 100644 --- a/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_verify_results.json +++ b/regr_smlp/master/Test67_smlp_toy_num_resp_noknobs_verify_results.json @@ -10,10 +10,10 @@ "assertion_status": "FAIL", "counter_example": { "x0": 0.0, - "x1": 1.0, + "x1": 7.0, "y1": 9.0, "x2": 7.0, - "y2": 5.0 + "y2": 9.0 }, "assertion_feasible": true }, diff --git a/regr_smlp/master/Test68_test67_model_trace.csv b/regr_smlp/master/Test68_test67_model_trace.csv index 1c931f44..fa2d5f5f 100644 --- a/regr_smlp/master/Test68_test67_model_trace.csv +++ b/regr_smlp/master/Test68_test67_model_trace.csv @@ -1,9 +1,9 @@ stage,solver,x0,x1,x2,y1,y2 interface_consistency,sat,0,7,3 -model_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -witness_consistency,sat,0,1,805306377/134217728,5,5 -ca,sat,0,1,27/4,9,5 +model_consistency,sat,0,1,7,9,5 +witness_consistency,sat,0,1,7,9,5 +witness_consistency,sat,0,1,7,9,5 +ca,sat,1,1,4,5,9 ce,unsat -ca,sat,0,1,1140850697/201326592,5,5 -ce,sat,0,1,7,9,5 +ca,sat,0,7,218103811/33554432,5,9 +ce,sat,0,7,7,9,9 diff --git a/regr_smlp/master/Test68_test67_model_verify_results.json b/regr_smlp/master/Test68_test67_model_verify_results.json index b85d3149..1029a19f 100644 --- a/regr_smlp/master/Test68_test67_model_verify_results.json +++ b/regr_smlp/master/Test68_test67_model_verify_results.json @@ -10,10 +10,10 @@ "assertion_status": "FAIL", "counter_example": { "x0": 0.0, - "x1": 1.0, + "x1": 7.0, "y1": 9.0, "x2": 7.0, - "y2": 5.0 + "y2": 9.0 }, "assertion_feasible": true }, diff --git a/regr_smlp/master/Test72_test71_model_trace.csv b/regr_smlp/master/Test72_test71_model_trace.csv index 8505b93b..dd5802bc 100644 --- a/regr_smlp/master/Test72_test71_model_trace.csv +++ b/regr_smlp/master/Test72_test71_model_trace.csv @@ -2,5 +2,5 @@ stage,solver,x0,x1,x2,y1,y2 interface_consistency,sat,0,1,3 model_consistency,sat,335865014418181538/39045391051627415,1,7,10651411/2097152,681662925/134217728 witness_consistency,sat,335865014418181538/39045391051627415,1,7,10651411/2097152,681662925/134217728 -ca,sat,2667259409273942388800059527240/1128310361942258882860728781499,1,7871388943134865479425804482739/2256620723884517765721457562998,43410663863828084895832108655730768149724434467026753/21313180142042565894459826814567808118043982184841216,9191496317309957574808691076171/4513241447769035531442915125996 +ca,sat,123722618417780711807298165032/54373292127912369088951862159,1,1139945589298010346211983867637/326239752767474214533711172954,6163226111796703126611665298945400963472615264808055/3081247347697599620049750445846427059655048291155968,2 ce,sat,335865014418181538/39045391051627415,1,7,10651411/2097152,681662925/134217728 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv index fd9015b8..69a38a5f 100644 --- a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -7,6 +7,6 @@ witness_consistency,sat,1,7,5,5 ca,unsat ce,sat,4,6,5,9 ca,sat,7,452984835/67108864,9,9 -ce,sat,1,805306377/134217728,5,5 +ce,sat,1,7,5,5 ca,unsat ce,sat,1,7,5,5 diff --git a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json index 6fb0d0ac..10878543 100644 --- a/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json +++ b/regr_smlp/master/Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -16,7 +16,7 @@ "counter_example": { "x1": 1.0, "y1": 5.0, - "x2": 6.000000067055225, + "x2": 7.0, "y2": 5.0 }, "assertion_feasible": true diff --git a/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv index fd9015b8..69a38a5f 100644 --- a/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv +++ b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -7,6 +7,6 @@ witness_consistency,sat,1,7,5,5 ca,unsat ce,sat,4,6,5,9 ca,sat,7,452984835/67108864,9,9 -ce,sat,1,805306377/134217728,5,5 +ce,sat,1,7,5,5 ca,unsat ce,sat,1,7,5,5 diff --git a/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json index 6fb0d0ac..10878543 100644 --- a/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json +++ b/regr_smlp/master/Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -16,7 +16,7 @@ "counter_example": { "x1": 1.0, "y1": 5.0, - "x2": 6.000000067055225, + "x2": 7.0, "y2": 5.0 }, "assertion_feasible": true diff --git a/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv index fd9015b8..69a38a5f 100644 --- a/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv +++ b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv @@ -7,6 +7,6 @@ witness_consistency,sat,1,7,5,5 ca,unsat ce,sat,4,6,5,9 ca,sat,7,452984835/67108864,9,9 -ce,sat,1,805306377/134217728,5,5 +ce,sat,1,7,5,5 ca,unsat ce,sat,1,7,5,5 diff --git a/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json index 6fb0d0ac..10878543 100644 --- a/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json +++ b/regr_smlp/master/Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json @@ -16,7 +16,7 @@ "counter_example": { "x1": 1.0, "y1": 5.0, - "x2": 6.000000067055225, + "x2": 7.0, "y2": 5.0 }, "assertion_feasible": true diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_trace.csv index 7d906b15..912b1a49 100644 --- a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_trace.csv +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_trace.csv @@ -1,12 +1,12 @@ stage,solver,x0,x1,x2,y1,y2 interface_consistency,sat,7,3 -model_consistency,sat,1,805306377/134217728,5,5 -witness_consistency,sat,1,805306377/134217728,5,5 -witness_consistency,sat,1,805306377/134217728,5,5 -witness_consistency,sat,1,805306377/134217728,5,5 +model_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 ca,unsat -ce,sat,4,6,9,9 -ca,sat,1,603979777/134217728,9,9 -ce,sat,1,805306377/134217728,5,5 +ce,sat,1,27/4,5,5 +ca,sat,7,805306377/134217728,9,9 +ce,sat,1,7,5,5 ca,unsat -ce,sat,1,805306377/134217728,5,5 +ce,sat,7,805306377/134217728,9,9 diff --git a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_verify_results.json b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_verify_results.json index 6e037ddd..87425ddb 100644 --- a/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_verify_results.json +++ b/regr_smlp/master/Test76_smlp_toy_num_resp_noknobs_verify_results.json @@ -3,10 +3,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 4.0, - "y1": 9.0, - "x2": 6.0, - "y2": 9.0 + "x1": 1.0, + "y1": 5.0, + "x2": 6.75, + "y2": 5.0 }, "assertion_feasible": false }, @@ -16,7 +16,7 @@ "counter_example": { "x1": 1.0, "y1": 5.0, - "x2": 6.000000067055225, + "x2": 7.0, "y2": 5.0 }, "assertion_feasible": true @@ -25,10 +25,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 1.0, - "y1": 5.0, + "x1": 7.0, + "y1": 9.0, "x2": 6.000000067055225, - "y2": 5.0 + "y2": 9.0 }, "assertion_feasible": false }, diff --git a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_trace.csv b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_trace.csv index 85e7bc4a..c22e67e6 100644 --- a/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_trace.csv +++ b/regr_smlp/master/Test78_smlp_toy_num_resp_noknobs_trace.csv @@ -1,9 +1,9 @@ stage,solver,x0,x1,x2,y1,y2 interface_consistency,sat,7,3 -model_consistency,sat,1,805306377/134217728,5,5 -witness_consistency,sat,1,805306377/134217728,5,5 -witness_consistency,sat,1,805306377/134217728,5,5 -ca,sat,7,805306377/134217728,9,9 +model_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +ca,sat,1,603979777/134217728,9,9 ce,sat,7,3,5,9 -ca,sat,1,805306377/134217728,5,5 +ca,sat,7,805306377/134217728,9,9 ce,unsat From 8e5af0a5249289080588e67266702b1af39993e7 Mon Sep 17 00:00:00 2001 From: Dmitry Messerman Date: Tue, 2 Jun 2026 16:59:57 +0300 Subject: [PATCH 16/20] Fixing issue in the previous checkin --- regr_smlp/code/smlp_regr.csv | 212 +++++++++++++++++++++++++++++++++++ 1 file changed, 212 insertions(+) mode change 100644 => 100755 regr_smlp/code/smlp_regr.csv diff --git a/regr_smlp/code/smlp_regr.csv b/regr_smlp/code/smlp_regr.csv old mode 100644 new mode 100755 index d07272a3..1bac58eb --- a/regr_smlp/code/smlp_regr.csv +++ b/regr_smlp/code/smlp_regr.csv @@ -1,23 +1,235 @@ d,data,new_data,switches,description +1,smlp_toy_num_resp_mult,,"-mode train -resp y1 -feat x,p1,p2 -model dt_caret -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f",basic dt_caret training and test on labeled data with single numeric response +2,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f",basic rf_sklearn prediction test on labeled and new data with numeric labels +3,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_unlabeled,"-mode predict -resp y1 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic poly_sklearn prediction test on labeled and new data with numeric response in training/test data only +4,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nn_keras_weights_precision 2 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f",basic nn_keras prediction test on labeled and new data with numeric labels and one response +5,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model t -use_model f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_caret prediction test on labeled and new data with numeric labels +6,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test on labeled and new data with numeric labels +7,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic rf_sklearn prediction test on labeled and new data with numeric labels +8,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -nn_keras_epochs 20 -nn_keras_seq_api f -log_time f",basic nn_keras prediction test on labeled and new data with numeric labels and two responses +9,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -model_name test20_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -save_config t -save_model_config t",basic dt_sklearn prediction test on labeled and new data with numeric labels +10,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 15 -et_sklearn_bootstrap f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic et_sklearn prediction test on labeled and new data with numeric labels +11,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic poly_sklearn prediction test on labeled and new data with numeric labels +12,smlp_toy_basic,,"-mode train -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",EV-SI real life dt_sklearn predict test on labeled and new data with numeric labels +13,smlp_toy_basic,,"-mode train -resp y1,y2 -feat x1,x2,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",EV-SI real life nn_keras prediction test on labeled and new data with numeric labels +14,smlp_toy_basic,,"-mode train -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",EV-SI real life poly_sklearn prediction test on labeled and new data with numeric labels +15,Test5_smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_caret prediction test from saved model on new data with numeric labels +16,Test8_smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic nn_keras prediction test from saved model on new data with numeric labels and two responses +17,Test11_smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic poly_sklearn prediction test from saved model on new data with numeric labels and two responses +18,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test19_model -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 +19,test19_model,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels +20,test20_model,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test on labeled and new data with numeric labels +21,smlp_toy_num_metasymbol_mult_reg,smlp_toy_num_metasymbol_mult_reg_pred_labeled,"-mode predict -resp ""PF ,|PF |"" -model poly_sklearn -save_model t -use_model f -model_name test22_model -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f",test for illegal symbols in column names +22,test22_model,smlp_toy_num_metasymbol_mult_reg_pred_labeled,"-mode predict -resp ""PF ,|PF |"" -model poly_sklearn -save_model f -use_model t -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f",test for illegal symbols in column names +23,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test24_model -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 +24,test24_model,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels +25,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test26_model -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 +26,test26_model,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels +27,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t",checks nn_keras prediction with nn_keras_seq_api t, adapts test 4 which uses nn_keras_seq_api f +28,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -sw_coef 0.8",checks nn_keras prediction with sw_coef 0.8 and functional API, adapts test 4 +29,smlp_toy_cls_metasymbol_colnames_mult,,"-mode subgroups -psg_dim 3 -psg_top 10 -resp ""PF 1,PF#"" -plots t -seed 10 -log_time f",basic test for subgroup discovery for pass-fail responses +30,smlp_toy_num_resp_mult,,"-mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -feat x,p1,p2 -plots t -seed 10 -log_time f",basic test for subgroup discovery for numric responses +31,smlp_toy_num_resp_mult,,"-mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -resp2b ""y1<6;y2>6"" -feat x,p1,p2 -plots t -seed 10 -log_time f -save_config t",testing resp2b in subgroup discovery mode +32,test20_model,smlp_toy_num_resp_mult_pred_labeled,"-config test20_model_rerun_model_config.json", test reusing saved model by using configuration file +33,smlp_toy_num_resp_mult,,"-config Test31_smlp_toy_num_resp_mult_args_config.json",testing -config option with subgroups mode +34,doe_four_levels_real,,"-mode doe -doe_algo full_factorial -log_time f", doe test with four levels with full_factorial method +35,doe_four_levels_real,,"-mode doe -doe_algo plackett_burman -log_time f", doe test with four levels with plackett_burman +36,doe_four_levels_real,,"-mode doe -doe_algo sukharev_grid -doe_samples 125 -log_time f", doe test with four levels with sukharev_grid +37,doe_three_levels_real_nan,,"-mode doe -doe_algo box_behnken -log_time f", doe test with four levels with box_behnken +38,doe_two_levels,,"-mode doe -doe_algo box_wilson -doe_cc_face ccc -doe_cc_alpha r -doe_cc_center 2,3 -log_time f", doe test with four levels with box_wilson +39,doe_two_levels,,"-mode doe -doe_algo latin_hypercube -doe_prob_distr Exponential -doe_samples 30 -log_time f", doe test with four levels with latin_hypercube +40,doe_two_levels,,"-mode doe -doe_algo latin_hypercube_sf -doe_samples 20 -log_time f", doe test with four levels with latin_hypercube_space_filling +41,doe_two_levels,,"-mode doe -doe_algo random_k_means -doe_samples 20 -log_time f", doe test with four levels with random_k_means +42,doe_two_levels,,"-mode doe -doe_algo maximin_reconstruction -doe_samples 20 -log_time f", doe test with four levels with maximin_reconstruction +43,doe_two_levels,,"-mode doe -doe_algo halton_sequence -doe_samples 20 -log_time f", doe test with four levels with halton_sequence +44,doe_two_levels,,"-mode doe -doe_algo uniform_random_matrix -doe_samples 20 -log_time f", doe test with four levels with uniform_random_matrix +45,doe_two_levels_real,,"-mode doe -doe_algo fractional_factorial -doe_resolution 5 -log_time f", doe test with four levels with fractional_factorial +46,smlp_toy_pf_mult,smlp_toy_pf_mult,"-mode predict -resp ""PF,PF1"" -model poly_sklearn -save_model t -save_model_config f -use_model f -model_name test47_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests options -pos_val and -neg_val +47,test47_model,smlp_toy_pf_mult,"-mode predict -resp ""PF,PF1"" -model poly_sklearn -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests options -pos_val and -neg_val when re-using saved model +48,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options +49,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo quantile -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options +50,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo kmeans -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options +51,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo jenks -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options +52,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo jenks -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options +53,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo ordinals -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options +54,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo ordinals -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options +55,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo ranks -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options +56,smlp_toy_mult_discr,,"-mode discretize -resp ""PF,PF1"" -discr_algo ranks -discr_bins 6 -discr_labels f -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",tests discretization options 57,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""y1*2+x0<=5 and y1<=10;-2*y2-1<10-x2"" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn assertion verfication test with numeric labels and integer grid as domain +58,smlp_toy_num_resp_mult,,"-mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs ""y1;y2"" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn optimization test with numeric labels and integer grid as domain and without scaling objectives +59,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",basic nn_keras assertion verification test for functional nn_keras model +60,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",basic nn_keras assertion verification test for functional nn_keras model 61,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -nn_keras_epochs 100 -save_model_config f --spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""not(x25 and y1<=10);-2*y2-1<10-x2 and x2>5 and x2<8"" -vacuity f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_seq_api f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat", tests verificaion mode for NN with nn_keras_seq_api f 62,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -nn_keras_epochs 100 -nn_keras_seq_api t -save_model_config f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""not(x25 and y1<=10);-2*y2-1<10-x2 and x2>5 and x2<8"" -vacuity f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",tests verificaion mode for NN with nn_keras_seq_api t +63,smlp_toy_num_resp_mult,,"-mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test63_model -spec smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x/2+y1>4.3;(y1+p2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with numeric labels +64,test63_model,,"-mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x/2+y1>4.3;(y1+p2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with one numeric response 65,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test65_model -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x0**2+y1>4.3;(y1+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with numeric labels 66,test65_model,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x0**2+y1>4.3;(y1+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with one numeric response 67,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -model_per_response t -save_model t -use_model f -model_name test67_model -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x0**2+y1>4.3;(y1+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with numeric labels 68,test67_model,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -model_per_response t -save_model f -use_model t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x0**2+y1>4.3;(y1+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic dt_sklearn assertion verification test on data with one numeric response +69,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model t -use_model f -model_name test69_model -model_per_response t -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""(y2**3+p2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",nn_keras verification test with model_per_response training +70,test69_model,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""(y2**3+p2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",nn_keras verification test with re-using saved model_per_response trained model 71,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -save_model t -use_model f -model_name test71_model -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1 -asrt_exprs ""(y1**3+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",nn_keras verification test with model_per_response training 72,test71_model,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1 -asrt_exprs ""(y2**3+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",nn_keras verification test with re-using saved model_per_response trained model 73,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test73_model -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model 74,test73_model,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model. with separate model for each response 75,test73_model,smlp_toy_num_resp_noknobs_pred_labeled,"-config test73_model_rerun_model_config.json",verification test run using model_rerun config covering the case when mrmr selcts only a subset of features specified through the command line or config file 76,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test76_model -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model +77,test76_model,,"-config test76_model_rerun_model_config.json",verification test run using model_rerun config covering the case when mrmr selcts only a subset of features specified through the command line or config file 78,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test78_model -mrmr_pred 1 -model_per_response f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""y1==9;y2>0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model, with one model for all responses +79,smlp_toy_num_resp_mult,,"-mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult.spec -quer_names query1,query2,query3 -quer_exprs ""(y2**3+p2)/2<6;y1>=9;y2<0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in query mode to test stability (theta) and guard (eta) constraint generation +80,smlp_toy_num_resp_mult,,"-mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1 -objv_exprs ""(y1+y2)/2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives +81,smlp_toy_num_resp_mult,,"-mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1 -objv_exprs ""(y1+y2)/2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives +82,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1,objv2,objv3 -objv_exprs ""(y1+y2)/2;y1;y2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives +83,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -beta ""y1>7 and y2>6"" -objv_names obj1,objv2,objv3 -objv_exprs ""(y1+y2)/2;y1/2-y2;y2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn multi objective pareto optimization test with numeric labels and integer grid as domain and with scaling objectives 84,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -alpha ""x2==7.0 and x0==0 and x1==2.5"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests global alpha constraints specified using option -alpha on inputs +85,smlp_toy_num_resp_mult,,"-mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs ""(y1+y2)/2;y1"" -alpha ""p2<5 and x==10 and x<12"" -eta ""p1==4"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests alpha and eta constraints specified in command line in optimization mode +86,smlp_toy_num_resp_mult,,"-mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs ""(y1+y2)/2;y1"" -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+p2)/2<6;y1>=9;y2<0"" -alpha ""p2<5 and x==10 and x<12"" -eta ""p1==4"" -epsilon 0.05 -delta_rel 0.01 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests alpha,beta and eta constraints specified in command line in optimization mode +87,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_alpha_asrt_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests global alpha constraints and assertions specified in spec file, equivalent to test 84 where the same alpha and assertions are specified in command line +88,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn multi objective pareto optimization test with beta and objectives specified in spec file, must give same results as test 83 where same beta and objectives is specified in command line +89,smlp_toy_num_resp_mult,,"-mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in query mode to test stability (theta) and guard (eta) constraint generation +90,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test to detect contradictory constraints in optsyn mode +91,smlp_toy_num_resp_mult,,"-mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_query_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test to detect contradictory constraints in optimization mode due to contradictory alpha global and alpha bounds constraints on FMAX_xyx +92,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_verify_vacuous.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test to detect contradictory constraints in verification mode +93,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for mode optsyn +94,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for rf_sklearn in model exploration mode optsyn +95,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for dt_caret in model exploration mode optsyn +96,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for rf_sklearn in model exploration mode optsyn +97,smlp_toy_num_resp_mult,,"-mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for rf_sklearn in model exploration mode optsyn +98,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_caret in model exploration mode optsyn +99,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",testing that the response and feature names can be taken from spec file in model exploration modes when the responses and/or features are not specified in the command line +100,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for sat_threshold option enabing usage of objectve values in SAT assignments that prove optimization thresholds +101,smlp_toy_num_resp_mult,,"-mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test101_model -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs ""(y2**3+p2)/2<6;y1>=9;y2<20"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in certify mode to test stability (theta) and guard (eta) constraint generation +102,test101_model,,"-mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs ""(y2**3+p2)/2<6;y1>=9;y2<20"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in certify mode to test stability (theta) and guard (eta) constraint generation +103,smlp_toy_num_resp_mult,,"-mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test103_model -model_per_response f -spec smlp_toy_num_resp_mult_certify_witness.spec -quer_names valid_candidate,grid_conflict,range_conflict -quer_exprs ""True;True;True"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",,basic test in certify mode to test one valid witness and two conflicting witnesses for queries that are constant true +104,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""y1*2+x<=5 and y1<=10;-2*y2-1<10-p2"" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",assertion verfication test with wrong spec that does not assign a single value using a singleton grid or range with equal max and min +105,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_stable_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""y1*2+x<=5 and y1<=10;-2*y2-1<10-p2"" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn assertion verfication test with numeric labels and integer grid as domain +106,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_unsat_eta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""y1*2+x<=5 and y1<=10;-2*y2-1<10-p2"" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined +107,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec smlp_toy_num_resp_mult_beta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr ""y1*2+x<=5 and y1<=10;-2*y2-1<10-p2"" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined +108,smlp_toy_num_resp_mult,,"-mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for dt_sklearn in model exploration mode synthesize where synthesis succeeds +109,smlp_toy_num_resp_mult,,"-mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_cannot_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for mode synthesize where synthesis fails +110,smlp_toy_basic,smlp_toy_basic_pred_unlabeled,"-mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model t -model_name test110_model -save_model_config t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",smlp toy basic example for predict mode from SMLP user manual +111,test110_model,smlp_toy_basic_pred_unlabeled,"-config test110_model_rerun_model_config.json",smlp toy basic test to rerun saved model using the model rerun config file saved during model training +112,test110_model,smlp_toy_basic_pred_unlabeled,"-mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -use_model t -save_model f",smlp toy basic test from SMLP manual, to rerun saved model without using the model rerun config file saved during model training and directly adding required options to command that match option values used during training +113,smlp_toy_basic,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model t -model_name test113_model -save_model_config t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec smlp_toy_basic.spec",smlp toy basic test for mode optimize from SMLP manual +114,smlp_toy_basic,,"-mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model f -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec smlp_toy_basic.spec",smlp toy basic test for mode optimize from SMLP manual without specifying resp and feat in command line +115,smlp_toy_basic,,"-mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_system.spec -quer_names query1,query2 -quer_exprs ""y1>0;y2<=0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in certify mode +116,smlp_toy_basic,,"-mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_system.spec -quer_names query1,query2 -quer_exprs ""y1>0;y2<=0"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test in certify mode when system is specified and is used as the model; p2 rel-rad needs to be 0 or very close to it the witness to first query to be stable +117,smlp_toy_basic,,"-mode certify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",certification test with knobs only where assertion is valid without stability and fails with stability +118,smlp_toy_basic,,"-mode verify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",verification test with knobs only where assertion is valid without stability and fails with stability +119,smlp_toy_basic,,"-mode query -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",query test with knobs only where query is satisfiable without stability and fails with stability +120,smlp_toy_basic,,"-mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_fail.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",synthesis test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible +121,smlp_toy_basic,,"-mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",synthesis test with constant knob and no inputs where synthesis is feasible +122,smlp_toy_basic,,"-mode optimize -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed +123,smlp_toy_basic,,"-mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed +124,smlp_toy_basic,,"-mode optsyn -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimized synthesis test with constant knob and no inputs where synthesis is not feasible because while beta constraint is feasible the assertion is not feasible therefore optimization is not performed +125,smlp_toy_basic,,"-mode optsyn -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimized synthesis test with constant knob and no inputs where synthesis is feasible and optimization is performed +126,smlp_toy_basic,,"-mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability +127,smlp_toy_basic,,"-mode certify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",certification example with knobs only and fictitious inputs with values fixed through their ranges, where query is valid without stability and fails with stability +128,smlp_toy_ctg_num_resp,,"-mode certify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model f -model_per_response f -spec smlp_toy_witness_certify.spec -quer_names query_stable_witness,query_grid_conflict,query_unstable_witness,query_infeasible_witness,query_poly_intercept_sensitive -quer_exprs ""y2<=90;y1>=9;y1>=(-13);y1>9;y1>=(-10)"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",Basic regression test in certify mode covering all four possible outcomes when certifying a witness for a query: the witness is stable, the witness is valid but not stable, the witness is invalid, and the constraints are conflicting. The fifth query and witness capture a scenario where the polynomial model conversion to terms was missing the intercepts. +129,smlp_toy_ctg_num_resp,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model f -model_per_response f -spec smlp_toy_configuration_verify.spec -asrt_names assert_stable_config,assert_grid_conflict,assert_unstable_config,assert_infeasible -asrt_exprs ""y2<=90;y1>=9;y1>=(-10);y1>20"" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",verification example with demonstrating all basic result scenarious for assertions +130,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x1,x2,p1,p2 -resp y1,y2 -model dt_sklearn -tree_encoding nested -compress_rules f -spec smlp_toy_const_input.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",captures scenario that interface constraints are consistent but model constraints are (because y2 is declared as int and not as real) -- constant input x1 is dropped as constant feature since it does not occur in constraints +131,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x1,x2,p1,p2 -resp y1,y2 -model dt_sklearn -tree_encoding nested -compress_rules f -spec smlp_toy_const_input_const_range.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test where input x1 has a constant range 0 and in data it is also constant and it is dropped before building the model because it does not occur in constraints alpha, eta, beta +132,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x1,x2,p1,p2 -resp y1,y2 -model dt_sklearn -tree_encoding nested -compress_rules f -spec smlp_toy_const_input_alpha.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test where input x1 has a non-constant range 0 to 1 and in data it is constant and it is not dropped before building the model because its range is constrained to constant value through alpha constraint +133,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x2,p1,p2 -resp y1,y2 -model dt_sklearn -tree_encoding nested -compress_rules f -spec smlp_toy_const_input_dropped.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",captures scenario that interface constraints are consistent but model constraints are not (because y2 is declared as int and not as real) -- constant inut x1 is dropped explicitly using -feat option ; uses uses dt_sklearn +134,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x2,p1,p2 -resp y1,y2 -model system --spec smlp_toy_consistent_system.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test that model cnstraints are consistent with interface constraints when system is used as the model and output y2 is declared as int -- the model constraints are consistent because y2 is defined as p1+p2-x2 and due to constraints all these variables can assume only integer values thus u2 can also only be an integer +135,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x2,p1,p2 -resp y1,y2 -model nn_keras -nnet_encoding nested -nn_keras_epochs 20 -spec smlp_toy_const_input_dropped.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",captures scenario where interface constraints are consistent but model constraints are not (because y2 is declared as int and not as real) -- constant inut x1 is dropped explicitly using -feat option ; uses nn_keras model which is the only difference with test 133 but which model is used does not matter as the problem is in declaration of y2 as int +136,smlp_toy_num_resp_mult_compressed.csv.gz,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests usage of compressed data files as well as data files without .csv suffix +137,smlp_toy_num_resp_mult_compressed,smlp_toy_num_resp_mult_compressed.csv.bz2,"-mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model_config f -spec smlp_toy_num_resp_mult_synthesize.spec -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests usage of compressed data files as well as data files without .csv suffix +138,smlp_toy_const_input,,"-mode optimize -opt_strategy lazy -feat x2,p1,p2 -resp y1,y2 -model system --spec smlp_toy_inconsistent_system.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",adapts test 134 by changing the system function for y2 to p1+p2-x2+0.01 so while p1,p2 and x2 can only assume int values y2 can become non-integer which violates the declartion of y2 as integer -- hence the conflict of the system/model constraints with alpha and eta constraits and variable domain declarations 139,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model +140,smlp_toy_basic,,"-mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_verify.spec -trace_prec 1 -trace_anonym t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability +141,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -pareto f -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -spec smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs ""y1;y2"" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for compress_rules option for dt_sklearn in optimization mode +142,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for compress_rules option for rf_sklearn in optsin mode +143,smlp_toy_num_resp_mult,,"-mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for compress_rules for et_sklearn in mode query 144,smlp_toy_num_resp_noknobs,,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -save_model f -use_model f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs ""x0**2+y1>4.3;(y1+x2)/2<6"" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f ",basic test for compress_rules for dt_sklearn in mode verify and re-using saved model +145,,,"-mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed +146,,,"-mode optimize -pareto t -opt_strategy lazy -model poly_sklearn -resp y1,y2 -feat p1,p2,x1,x2 -save_model t -use_model f -mrmr_pred 0 -model_per_response t -split 1 -spec smlp_toy_system.spec -doe_spec ../grids/explore_doe_two_levels.csv -doe_algo latin_hypercube -epsilon 0.99999999 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed +147,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8",checks nn_keras prediction with sw_coef 0.8 and sequential API, adapts test 28 +148,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8",checks nn_keras prediction with sw_coef 0.8 and sequential API, adapts test 28 to have two responses +149,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mae -sw_coef 0.8",tests the mae loss function MeanAbsoluteError and sample weoghts +150,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -sw_coef 0.8",tests the mape loss function MeanAbsolutePercentageError and sample weights +151,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss msle -sw_coef 3 -sw_exp 10 -sw_int 0",tests msle loss function MeanSquaredLogarithmicError and and sample weoghts +152,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss huber -sw_coef 8 -sw_exp 5 -sw_int 0.5",tests the huber loss function Huber and sample weights +153,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss logcosh -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mse",tests the logcosh loss function LogCosh and sample weights +154,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3,3,3"" -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5",basic nn_keras assertion verification test that uses keras tuner for functional model training +155,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3,3,3"" -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae",basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training +156,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3"" -save_model_config f -spec smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse",basic nn_keras assertion verification test that uses keras tuner for functional model training; adapts test 154 by consdering multiple responses +157,smlp_toy_num_resp_mult,,"-mode verify -resp y1,y2 -feat x,p1,p2 --model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3"" -save_model_config f -spec smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse,logcosh",basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training; adapts test 155 by consdering multiple responses +158,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -model_per_response t -sw_coef 8 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse",tests the mape loss function and sample weights with model_per_response t, adapts test 152 +159,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -model_per_response t -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae,cosine",tests the msle loss function and sample weights with model_per_response t, adapts test 153 +160,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -nn_keras_metrics msle -nn_keras_tuner bayesian -nn_keras_layers_grid ""2,3"" -nn_keras_losses_grid ""mse,mae,huber"" -model_per_response f -sw_coef 8 -sw_exp 5 -sw_int 0.5",tests nn keras tuner bayesian +161,smlp_toy_num_resp_mult,smlp_toy_num_resp_mult_pred_labeled,"-mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -nn_keras_metrics mape,logcosh -nn_keras_tuner random -nn_keras_lrates_grid ""0.01,0.001"" -nn_keras_batches_grid ""32,64"" -model_per_response f -sw_coef 4 -sw_exp 5 -sw_int 0.5",tests nn keras tuner bayesian 162,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term construction with flat_encoding of tress and model per reponse when mrmr_pred is activated and not all features are selected for training the model, adapts test 139 163,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model, adapts test 139 +164,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test for dt_sklearn multi objective pareto optimization +165,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding flat -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test for dt_caretin model exploration mode optsyn, model_per_response is forced to true for caret models, adapts test 95 +166,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn +167,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn, adapts test 94 and test 166 +168,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding flat -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for rf_caret with flat tree_encoding and modelper_response in model exploration mode optimize +169,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with flat tree_encoding and model_per_response t in model exploration mode optimize +170,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with flat tree_encoding and model_per_response f in model exploration mode optimize +171,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_caret with flat tree_encoding in model exploration mode optimize +172,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3,3,3"" -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -solver_path "mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"",basic test for nn_keras flat encoding for functional api, i, one response variable, adapts test 154 +173,smlp_toy_num_resp_mult,,"-mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid ""2,2;3,3,3"" -save_model_config f -spec smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs ""2*y2>1"" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae -solver_path "mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"",basic test for nn_keras flat encoding for sequential api, one response variable, adapts test 155 +174,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn +175,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn +176,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api f for nn_keras in model exploration mode optsyn +177,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn +178,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -scale_feat f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features are not scaled adapts test 177 +179,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_resp f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn when resposes are not scaled adapts test 174 +180,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_feat f -scale_resp f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features and responses are not scaled adapts test 175 +181,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_feat f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 +182,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path "mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"",basic flat tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 +183,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -scale_feat f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 184,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model adapts test 139 185,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term construction with branched_encoding of tress and model per reponse when mrmr_pred is activated and not all features are selected for training the model, adapts test 162 186,smlp_toy_num_resp_noknobs,smlp_toy_num_resp_noknobs_pred_labeled,"-mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs ""(y2**3+x2)/2<6;y1>=9;y2<0"" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",tests model term formation when mrmr_pred is activated and not all features are selected for training the model, adapts test 163 +187,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic branched tree encoding test for dt_sklearn multi objective pareto optimization adapts test 164 +188,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding branched -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic branched tree encoding test for dt_caretin model exploration mode optsyn, model_per_response is forced to true for caret models, adapts test 165 +189,smlp_toy_num_resp_mult,,"-mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic branched tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn adapts test 166 +190,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding branched -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for rf_caret with branched tree_encoding and modelper_response in model exploration mode optimize adapts test 168 +191,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap t -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with branched tree_encoding and model_per_response t in model exploration mode optimize adapts test 169 +192,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results, cvc5 faild with incomparable ite tipes for if and else branches) +193,smlp_toy_num_resp_mult,,"-mode optimize -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_caret with branched tree_encoding in model exploration mode optimize adapts test 171 +194,smlp_toy_num_resp_mult,,"-mode optsyn -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic branched tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn, adapts test 94 and test 167 +195,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 192 by setting n_estimators 3 and then discrepancy between z3, mathsat and yices results disappear +196,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_feat f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 and test 181 +197,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path "mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"",basic branched tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 and test 182 +198,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -scale_feat f -spec smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat",basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 and test 183 +199,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test to demonstrate that in pareto optimization and optsyn modes with multiple objectives when beta constraints are not present SMLP results are not consistent when different solvers are used; this is due to fact that when a subset of objectoves are exemined in pareto algo, outputs not covered by the active objectives become don't cares (there are no contraints on then except model constraints) and this situation is likely not modeled in SMLP accurately; modifies test 192 to use z3 instead of mathsat +200,smlp_toy_num_resp_mult,,"-mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0 -solver_path mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results, cvc5 faild with incomparable ite tipes for if and else branches) +201,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_num_resp_mult_no_input_beta.spec -data_scaler min_max -objv_names obj1 -objv_exprs ""(y1+y2)/2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and there are beta constraints +202,smlp_toy_num_resp_mult,,"-mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_num_resp_mult_no_input.spec -data_scaler min_max -objv_names obj1 -objv_exprs ""(y1+y2)/2"" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and no beta constraints +203,smlp_toy_basic,,"-mode optimize -pareto f -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with eager strategy and with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed adapts test 122 +204,smlp_toy_basic,,"-mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 123 +205,,,"-mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 145 +206,smlp_toy_basic,,"-mode optsyn -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",optimized synthesis test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 125 +207,smlp_toy_frontier_beta,,"-mode frontier -pareto t -resp y -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_beta.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for mode frontier -- selecting pareto frontier directly from data without building a model +208,smlp_toy_frontier_beta,,"-mode frontier -pareto t -resp y -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_real.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",testing unbounded knob and input domains for mode frontier when knob and input are of type real -- bounds inf and minus inf are specified in the spec file as null +209,smlp_toy_frontier_null_bounds_int,,"-mode frontier -pareto t -resp y -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_int.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",testing unbounded knob and input domains for mode frontier when knob and input are of typ eint -- bounds inf and minus inf are specified in the spec file as null +210,smlp_toy_frontier_null_bounds_empty,,"-mode frontier -pareto t -resp y1,y2 -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_empty_eta.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test for the frontier mode on data and spec such that no data points satisfy eta constrints, as a result the pareto frontier is empty +211,smlp_toy_frontier_null_bounds_empty,,"-mode frontier -pareto t -resp y1,y2 -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_empty_alpha.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test for the frontier mode on data and spec such that no data points satisfy eta constrints, as a result the pareto frontier is empty +212,smlp_toy_frontier_null_bounds_int,,"-mode optimize -pareto t -resp y -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_int.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",testing unbounded knob and input domains for optimization mode -- bounds inf and minus inf are specified in the spec file as null +213,smlp_toy_frontier_null_bounds_empty,,"-mode optimize -pareto t -resp y1,y2 -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_empty_eta.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test optimize mode on data and spec such that no data points satisfy eta constrints +214,smlp_toy_frontier_null_bounds_empty,,"-mode optimize -pareto t -resp y1,y2 -feat x,p -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec smlp_toy_frontier_null_bounds_empty_alpha.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test for the frontier mode on data and spec such that no data points satisfy eta constrints, as a result the pareto frontier is empty +215,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type object +216,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode +217,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type category, adapts test 215 +218,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type ordered, adapts test 215 +219,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type integer -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features casted to integer, adapts test 215 +220,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type object and tests the normalized mutual information, adapts test 215 +221,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type object and tests the Shannon mutual information, adapts test 215 +222,smlp_toy_mult_discr,,"-mode correlate -resp ""PF,PF1"" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass",basic test for correlate mode, contains correlations for categorical features of type object and tests the adjusted mutual information, adapts test 215 +223,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode and tests the normalized mutual information, adapts test 216 +224,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode and tests the Shannon mutual information, adapts test 216 +225,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode and tests the adjusted mutual information, adapts test 216 +226,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode +227,smlp_toy_basic,,"-mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f",basic test for correlate mode and tests the normalized mutual information, adapts test 216 and 223 +228,smlp_toy_basic,,"-mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_system_radii_update_certify.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",test that radii specified in command line properly override the radii specified in the spec file. Here we override both ansolute and relative radii and one can observe that the certification results also change compared to test 116 +229,smlp_toy_basic,,"-mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec smlp_toy_missing_radii.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f",basic test for checking that each knob must have either absolute or relative radius specified in the spec file (even if radii are specified in the command line) +230,smlp_toy_monotone_basic.csv,,"-mode verify -spec smlp_toy_system_monotone_knob.05_verify.spec -model system -seed 10 -log_time f",tests that outputs in system specificaation might depend on different inuts (knobs and free inputs) +231,smlp_toy_monotone_basic.csv,,"-mode certify -spec smlp_toy_system_decreasing_knob.05_certify.spec -model system -seed 10 -log_time f",certification test with monotonicity query with a knob with a grid point +232,smlp_toy_system_running_example_certify,,"-mode certify -spec smlp_toy_system_running_example_certify.spec -model system -seed 10 -log_time f",running example from smlp manual, contains for witnesses to a query, covering all possible witness scenarios -- stable witness, unstable witness, and not a witness cases +233,smlp_toy_string_response,,"-mode subgroups -resp str_resp1 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f",tests subgroup discovery mode when the response has string values, e,g, yes/no, pass/fail +234,smlp_toy_string_response,,"-mode subgroups -resp str_resp1,str_resp2 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f",tests subgroup discovery mode when there are two responses with string values, e,g, yes/no, pass/fail \ No newline at end of file From ad0c15e4acfa8ab5d8ce515a2c3294c9f5225ea7 Mon Sep 17 00:00:00 2001 From: Dmitry Messerman Date: Tue, 2 Jun 2026 18:04:21 +0300 Subject: [PATCH 17/20] Changing one more file - side effect of Test76 change --- regr_smlp/master/Test77_test76_model_trace.csv | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/regr_smlp/master/Test77_test76_model_trace.csv b/regr_smlp/master/Test77_test76_model_trace.csv index 7d906b15..912b1a49 100644 --- a/regr_smlp/master/Test77_test76_model_trace.csv +++ b/regr_smlp/master/Test77_test76_model_trace.csv @@ -1,12 +1,12 @@ stage,solver,x0,x1,x2,y1,y2 interface_consistency,sat,7,3 -model_consistency,sat,1,805306377/134217728,5,5 -witness_consistency,sat,1,805306377/134217728,5,5 -witness_consistency,sat,1,805306377/134217728,5,5 -witness_consistency,sat,1,805306377/134217728,5,5 +model_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 +witness_consistency,sat,1,7,5,5 ca,unsat -ce,sat,4,6,9,9 -ca,sat,1,603979777/134217728,9,9 -ce,sat,1,805306377/134217728,5,5 +ce,sat,1,27/4,5,5 +ca,sat,7,805306377/134217728,9,9 +ce,sat,1,7,5,5 ca,unsat -ce,sat,1,805306377/134217728,5,5 +ce,sat,7,805306377/134217728,9,9 From 75057b41f9e134ac4835ce0bf96df73890ae2bdc Mon Sep 17 00:00:00 2001 From: Dmitry Messerman Date: Tue, 2 Jun 2026 18:59:54 +0300 Subject: [PATCH 18/20] Adding file, missed in the previous commit --- .../Test77_test76_model_verify_results.json | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/regr_smlp/master/Test77_test76_model_verify_results.json b/regr_smlp/master/Test77_test76_model_verify_results.json index 6e037ddd..87425ddb 100644 --- a/regr_smlp/master/Test77_test76_model_verify_results.json +++ b/regr_smlp/master/Test77_test76_model_verify_results.json @@ -3,10 +3,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 4.0, - "y1": 9.0, - "x2": 6.0, - "y2": 9.0 + "x1": 1.0, + "y1": 5.0, + "x2": 6.75, + "y2": 5.0 }, "assertion_feasible": false }, @@ -16,7 +16,7 @@ "counter_example": { "x1": 1.0, "y1": 5.0, - "x2": 6.000000067055225, + "x2": 7.0, "y2": 5.0 }, "assertion_feasible": true @@ -25,10 +25,10 @@ "configuration_consistent": "true", "assertion_status": "FAIL", "counter_example": { - "x1": 1.0, - "y1": 5.0, + "x1": 7.0, + "y1": 9.0, "x2": 6.000000067055225, - "y2": 5.0 + "y2": 9.0 }, "assertion_feasible": false }, From 9fcf4b4070e02452d8b0304b51f87226b9497b0b Mon Sep 17 00:00:00 2001 From: Dmitry Messerman Date: Tue, 2 Jun 2026 19:39:15 +0300 Subject: [PATCH 19/20] Updated expected results for Docker --- .../run_smlp_regression_expected.log | 1927 +++++++++++------ ...n_smlp_regression_expected_diff_report.log | 414 +--- 2 files changed, 1269 insertions(+), 1072 deletions(-) diff --git a/tests/smlp_regression/run_smlp_regression_expected.log b/tests/smlp_regression/run_smlp_regression_expected.log index 1abcad8d..eab2d72a 100644 --- a/tests/smlp_regression/run_smlp_regression_expected.log +++ b/tests/smlp_regression/run_smlp_regression_expected.log @@ -1,830 +1,923 @@ Calling 8 workers for multiprocessing... Initiating 0 worker... -Running test 1 test type: train, description: basic dt_caret training and test on labeled data with single numeric response -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test1 -mode train -resp y1 -feat x,p1,p2 -model dt_caret -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f - Initiating 1 worker... -Running test 2 test type: prediction, description: basic rf_sklearn prediction test on labeled and new data with numeric labelsInitiating 2 worker... - -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test2 -mode predict -resp y1 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - +Initiating 2 worker... Initiating 3 worker... -Running test 3 test type: prediction, description: basic poly_sklearn prediction test on labeled and new data with numeric response in training/test data only -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test3 -mode predict -resp y1 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_unlabeled.csv" - Initiating 4 worker... Initiating 5 worker... -Running test 4 test type: prediction, description: basic nn_keras prediction test on labeled and new data with numeric labels and one response -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test4 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nn_keras_weights_precision 2 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - Initiating 6 worker... -Running test 6 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test6 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Initiating 7 worker... -Running test 5 test type: prediction, description: basic dt_caret prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test5 -mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model t -use_model f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 7 test type: prediction, description: basic rf_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test7 -mode predict -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 8 test type: prediction, description: basic nn_keras prediction test on labeled and new data with numeric labels and two responses -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test8 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -nn_keras_epochs 20 -nn_keras_seq_api f -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 9 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test9 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -model_name test20_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -save_config t -save_model_config t -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 10 test type: prediction, description: basic et_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test10 -mode predict -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 15 -et_sklearn_bootstrap f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 11 test type: prediction, description: basic poly_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test11 -mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 2 test type: prediction, description: basic rf_sklearn prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test2 -mode predict -resp y1 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" Running test 12 test type: train, description: EV-SI real life dt_sklearn predict test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test12 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -Running test 13 test type: train, description: EV-SI real life nn_keras prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test13 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -Running test 14 test type: train, description: EV-SI real life poly_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test14 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -Running test 15 test type: prediction, description: basic dt_caret prediction test from saved model on new data with numeric labels -../../src/run_smlp.py -model_name "../models/Test5_smlp_toy_num_resp_mult" -out_dir ./ -pref Test15 -mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 16 test type: prediction, description: basic nn_keras prediction test from saved model on new data with numeric labels and two responses -../../src/run_smlp.py -model_name "../models/Test8_smlp_toy_num_resp_mult" -out_dir ./ -pref Test16 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 17 test type: prediction, description: basic poly_sklearn prediction test from saved model on new data with numeric labels and two responses -../../src/run_smlp.py -model_name "../models/Test11_smlp_toy_num_resp_mult" -out_dir ./ -pref Test17 -mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 18 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test18 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test19_model -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 19 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels -../../src/run_smlp.py -model_name "../models/test19_model" -out_dir ./ -pref Test19 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test12 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f Running test 20 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -model_name "../models/test20_model" -out_dir ./ -pref Test20 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +smlp -model_name "../models/test20_model" -out_dir ./ -pref Test20 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 21 test type: prediction, description: test for illegal symbols in column names -../../src/run_smlp.py -data "../data/smlp_toy_num_metasymbol_mult_reg.csv" -out_dir ./ -pref Test21 -mode predict -resp "PF ,|PF |" -model poly_sklearn -save_model t -use_model f -model_name test22_model -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_metasymbol_mult_reg_pred_labeled.csv" - -Running test 22 test type: prediction, description: test for illegal symbols in column names -../../src/run_smlp.py -model_name "../models/test22_model" -out_dir ./ -pref Test22 -mode predict -resp "PF ,|PF |" -model poly_sklearn -save_model f -use_model t -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_metasymbol_mult_reg_pred_labeled.csv" - -Running test 23 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test23 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test24_model -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 28 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and functional API +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test28 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 24 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels -../../src/run_smlp.py -model_name "../models/test24_model" -out_dir ./ -pref Test24 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 35 test type: doe, description: doe test with four levels with plackett_burman +smlp -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test35 -mode doe -doe_algo plackett_burman -log_time f -Running test 25 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test25 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test26_model -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 42 test type: doe, description: doe test with four levels with maximin_reconstruction +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test42 -mode doe -doe_algo maximin_reconstruction -doe_samples 20 -log_time f -Running test 26 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels -../../src/run_smlp.py -model_name "../models/test26_model" -out_dir ./ -pref Test26 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 50 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test50 -mode discretize -resp "PF,PF1" -discr_algo kmeans -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -Running test 27 test type: prediction, description: checks nn_keras prediction with nn_keras_seq_api t -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test27 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_mult.spec +specs_path ../specs +Running test 58 test type: optimize, description: basic dt_sklearn optimization test with numeric labels and integer grid as domain and without scaling objectives +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test58 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs "y1;y2" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 28 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and functional API -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test28 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 66 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response +smlp -model_name "../models/test65_model" -out_dir ./ -pref Test66 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 29 test type: subgroups, description: basic test for subgroup discovery for pass-fail responses -../../src/run_smlp.py -data "../data/smlp_toy_cls_metasymbol_colnames_mult.csv" -out_dir ./ -pref Test29 -mode subgroups -psg_dim 3 -psg_top 10 -resp "PF 1,PF#" -plots t -seed 10 -log_time f +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 72 test type: verify, description: nn_keras verification test with re-using saved model_per_response trained model +smlp -model_name "../models/test71_model" -out_dir ./ -pref Test72 -mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -Running test 30 test type: subgroups, description: basic test for subgroup discovery for numric responses -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test30 -mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -feat x,p1,p2 -plots t -seed 10 -log_time f +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 78 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test78 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test78_model -mrmr_pred 1 -model_per_response f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "y1==9;y2>0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 31 test type: subgroups, description: testing resp2b in subgroup discovery mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test31 -mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -resp2b "y1<6;y2>6" -feat x,p1,p2 -plots t -seed 10 -log_time f -save_config t +spec_fn smlp_toy_num_resp_mult.spec +specs_path ../specs +Running test 85 test type: optimize, description: tests alpha and eta constraints specified in command line in optimization mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test85 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs "(y1+y2)/2;y1" -alpha "p2<5 and x==10 and x<12" -eta "p1==4" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 32 test type: unknown, description: test reusing saved model by using configuration file -../../src/run_smlp.py -model_name "../models/test20_model" -out_dir ./ -pref Test32 -config ../models/test20_model_rerun_model_config.json -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_mult_verify_vacuous.spec +specs_path ../specs +Running test 92 test type: verify, description: test to detect contradictory constraints in verification mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test92 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_verify_vacuous.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 33 test type: unknown, description: testing -config option with subgroups mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test33 -config ../models/Test31_smlp_toy_num_resp_mult_args_config.json +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +specs_path ../specs +Running test 100 test type: optimize, description: basic test for sat_threshold option enabing usage of objectve values in SAT assignments that prove optimization thresholds +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test100 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 34 test type: doe, description: doe test with four levels with full_factorial method -../../src/run_smlp.py -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test34 -mode doe -doe_algo full_factorial -log_time f +spec_fn smlp_toy_num_resp_mult.spec +specs_path ../specs +Running test 104 test type: verify, description: assertion verfication test with wrong spec that does not assign a single value using a singleton grid or range with equal max and min +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test104 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 35 test type: doe, description: doe test with four levels with plackett_burman -../../src/run_smlp.py -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test35 -mode doe -doe_algo plackett_burman -log_time f +spec_fn smlp_toy_num_resp_mult_cannot_synthesize.spec +specs_path ../specs +Running test 109 test type: synthesize, description: basic test for mode synthesize where synthesis fails +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test109 -mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_cannot_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 3 test type: prediction, description: basic poly_sklearn prediction test on labeled and new data with numeric response in training/test data only +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test3 -mode predict -resp y1 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_unlabeled.csv" -Running test 36 test type: doe, description: doe test with four levels with sukharev_grid -../../src/run_smlp.py -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test36 -mode doe -doe_algo sukharev_grid -doe_samples 125 -log_time f +Running test 9 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test9 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -model_name test20_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -save_config t -save_model_config t -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 37 test type: doe, description: doe test with four levels with box_behnken -../../src/run_smlp.py -doe_spec "../grids/doe_three_levels_real_nan.csv" -out_dir ./ -pref Test37 -mode doe -doe_algo box_behnken -log_time f +Running test 17 test type: prediction, description: basic poly_sklearn prediction test from saved model on new data with numeric labels and two responses +smlp -model_name "../models/Test11_smlp_toy_num_resp_mult" -out_dir ./ -pref Test17 -mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 38 test type: doe, description: doe test with four levels with box_wilson -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test38 -mode doe -doe_algo box_wilson -doe_cc_face ccc -doe_cc_alpha r -doe_cc_center 2,3 -log_time f +Running test 22 test type: prediction, description: test for illegal symbols in column names +smlp -model_name "../models/test22_model" -out_dir ./ -pref Test22 -mode predict -resp "PF ,|PF |" -model poly_sklearn -save_model f -use_model t -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_metasymbol_mult_reg_pred_labeled.csv" -Running test 39 test type: doe, description: doe test with four levels with latin_hypercube -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test39 -mode doe -doe_algo latin_hypercube -doe_prob_distr Exponential -doe_samples 30 -log_time f +Running test 32 test type: unknown, description: test reusing saved model by using configuration file +smlp -model_name "../models/test20_model" -out_dir ./ -pref Test32 -config ../models/test20_model_rerun_model_config.json -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" Running test 40 test type: doe, description: doe test with four levels with latin_hypercube_space_filling -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test40 -mode doe -doe_algo latin_hypercube_sf -doe_samples 20 -log_time f +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test40 -mode doe -doe_algo latin_hypercube_sf -doe_samples 20 -log_time f -Running test 41 test type: doe, description: doe test with four levels with random_k_means -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test41 -mode doe -doe_algo random_k_means -doe_samples 20 -log_time f +Running test 48 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test48 -mode discretize -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -Running test 42 test type: doe, description: doe test with four levels with maximin_reconstruction -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test42 -mode doe -doe_algo maximin_reconstruction -doe_samples 20 -log_time f +Running test 56 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test56 -mode discretize -resp "PF,PF1" -discr_algo ranks -discr_bins 6 -discr_labels f -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -Running test 43 test type: doe, description: doe test with four levels with halton_sequence -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test43 -mode doe -doe_algo halton_sequence -doe_samples 20 -log_time f +spec_fn smlp_toy_num_resp_mult_y1_verify.spec +specs_path ../specs +Running test 64 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response +smlp -model_name "../models/test63_model" -out_dir ./ -pref Test64 -mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x/2+y1>4.3;(y1+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 44 test type: doe, description: doe test with four levels with uniform_random_matrix -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test44 -mode doe -doe_algo uniform_random_matrix -doe_samples 20 -log_time f +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 71 test type: verify, description: nn_keras verification test with model_per_response training +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test71 -mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -save_model t -use_model f -model_name test71_model -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1 -asrt_exprs "(y1**3+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -Running test 45 test type: doe, description: doe test with four levels with fractional_factorial -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels_real.csv" -out_dir ./ -pref Test45 -mode doe -doe_algo fractional_factorial -doe_resolution 5 -log_time f +spec_fn smlp_toy_num_resp_mult_free_inps.spec +specs_path ../specs +Running test 81 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test81 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -Running test 46 test type: prediction, description: tests options -pos_val and -neg_val -../../src/run_smlp.py -data "../data/smlp_toy_pf_mult.csv" -out_dir ./ -pref Test46 -mode predict -resp "PF,PF1" -model poly_sklearn -save_model t -save_model_config f -use_model f -model_name test47_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass -new_dat "../data/smlp_toy_pf_mult.csv" +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +specs_path ../specs +Running test 88 test type: optimize, description: basic dt_sklearn multi objective pareto optimization test with beta and objectives specified in spec file +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test88 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 47 test type: prediction, description: tests options -pos_val and -neg_val when re-using saved model -../../src/run_smlp.py -model_name "../models/test47_model" -out_dir ./ -pref Test47 -mode predict -resp "PF,PF1" -model poly_sklearn -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass -new_dat "../data/smlp_toy_pf_mult.csv" +spec_fn smlp_toy_num_resp_mult_optsyn.spec +specs_path ../specs +Running test 93 test type: optsyn, description: basic test for mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test93 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 48 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test48 -mode discretize -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +spec_fn smlp_toy_num_resp_mult_witness.spec +specs_path ../specs +Running test 101 test type: certify, description: basic test in certify mode to test stability (theta) and guard (eta) constraint generation +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test101 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test101_model -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 49 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test49 -mode discretize -resp "PF,PF1" -discr_algo quantile -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +spec_fn smlp_toy_num_resp_mult_beta_verify.spec +specs_path ../specs +Running test 107 test type: verify, description: test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test107 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_beta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 50 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test50 -mode discretize -resp "PF,PF1" -discr_algo kmeans -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +spec_fn smlp_toy_basic.spec +specs_path ../specs +Running test 114 test type: optimize, description: smlp toy basic test for mode optimize from SMLP manual without specifying resp and feat in command line +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test114 -mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model f -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec ../specs/smlp_toy_basic.spec +Running test 4 test type: prediction, description: basic nn_keras prediction test on labeled and new data with numeric labels and one response +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test4 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nn_keras_weights_precision 2 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 51 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test51 -mode discretize -resp "PF,PF1" -discr_algo jenks -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 13 test type: train, description: EV-SI real life nn_keras prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test13 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 52 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test52 -mode discretize -resp "PF,PF1" -discr_algo jenks -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 24 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels +smlp -model_name "../models/test24_model" -out_dir ./ -pref Test24 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 53 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test53 -mode discretize -resp "PF,PF1" -discr_algo ordinals -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 31 test type: subgroups, description: testing resp2b in subgroup discovery mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test31 -mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -resp2b "y1<6;y2>6" -feat x,p1,p2 -plots t -seed 10 -log_time f -save_config t -Running test 54 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test54 -mode discretize -resp "PF,PF1" -discr_algo ordinals -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 39 test type: doe, description: doe test with four levels with latin_hypercube +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test39 -mode doe -doe_algo latin_hypercube -doe_prob_distr Exponential -doe_samples 30 -log_time f -Running test 55 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test55 -mode discretize -resp "PF,PF1" -discr_algo ranks -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 47 test type: prediction, description: tests options -pos_val and -neg_val when re-using saved model +smlp -model_name "../models/test47_model" -out_dir ./ -pref Test47 -mode predict -resp "PF,PF1" -model poly_sklearn -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass -new_dat "../data/smlp_toy_pf_mult.csv" -Running test 56 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test56 -mode discretize -resp "PF,PF1" -discr_algo ranks -discr_bins 6 -discr_labels f -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 55 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test55 -mode discretize -resp "PF,PF1" -discr_algo ranks -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_num_resp_mult_y1_verify.spec specs_path ../specs -Running test 58 test type: optimize, description: basic dt_sklearn optimization test with numeric labels and integer grid as domain and without scaling objectives -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test58 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs "y1;y2" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 63 test type: verify, description: basic dt_sklearn assertion verification test on data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test63 -mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test63_model -spec ../specs/smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x/2+y1>4.3;(y1+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 59 test type: verify, description: basic nn_keras assertion verification test for functional nn_keras model -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test59 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 69 test type: verify, description: nn_keras verification test with model_per_response training +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test69 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model t -use_model f -model_name test69_model -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult_y2_verify.spec +spec_fn smlp_toy_num_resp_mult.spec specs_path ../specs -Running test 60 test type: verify, description: basic nn_keras assertion verification test for functional nn_keras model -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test60 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 80 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test80 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_y1_verify.spec +spec_fn smlp_toy_num_resp_mult.spec specs_path ../specs -Running test 63 test type: verify, description: basic dt_sklearn assertion verification test on data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test63 -mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test63_model -spec ../specs/smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x/2+y1>4.3;(y1+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 86 test type: optimize, description: tests alpha +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test86 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs "(y1+y2)/2;y1" -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+p2)/2<6;y1>=9;y2<0" -alpha "p2<5 and x==10 and x<12" -eta "p1==4" -epsilon 0.05 -delta_rel 0.01 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_y1_verify.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 64 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response -../../src/run_smlp.py -model_name "../models/test63_model" -out_dir ./ -pref Test64 -mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x/2+y1>4.3;(y1+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 94 test type: optsyn, description: basic test for rf_sklearn in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test94 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_noknobs_verify.spec +spec_fn smlp_toy_num_resp_mult_witness.spec specs_path ../specs -Running test 66 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response -../../src/run_smlp.py -model_name "../models/test65_model" -out_dir ./ -pref Test66 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 102 test type: certify, description: basic test in certify mode to test stability (theta) and guard (eta) constraint generation +smlp -model_name "../models/test101_model" -out_dir ./ -pref Test102 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_noknobs_verify.spec +spec_fn smlp_toy_num_resp_mult_stable_verify.spec specs_path ../specs -Running test 68 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response -../../src/run_smlp.py -model_name "../models/test67_model" -out_dir ./ -pref Test68 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -model_per_response t -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 105 test type: verify, description: basic dt_sklearn assertion verfication test with numeric labels and integer grid as domain +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test105 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_stable_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_y2_verify.spec +Running test 112 test type: prediction, description: smlp toy basic test from SMLP manual +smlp -model_name "../models/test110_model" -out_dir ./ -pref Test112 -mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -use_model t -save_model f -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" + +spec_fn smlp_toy_system_stable_constant_query.spec specs_path ../specs -Running test 69 test type: verify, description: nn_keras verification test with model_per_response training -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test69 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model t -use_model f -model_name test69_model -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 119 test type: query, description: query test with knobs only where query is satisfiable without stability and fails with stability +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test119 -mode query -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 1 test type: train, description: basic dt_caret training and test on labeled data with single numeric response +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test1 -mode train -resp y1 -feat x,p1,p2 -model dt_caret -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f + +Running test 19 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels +smlp -model_name "../models/test19_model" -out_dir ./ -pref Test19 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +Running test 27 test type: prediction, description: checks nn_keras prediction with nn_keras_seq_api t +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test27 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +Running test 34 test type: doe, description: doe test with four levels with full_factorial method +smlp -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test34 -mode doe -doe_algo full_factorial -log_time f + +Running test 43 test type: doe, description: doe test with four levels with halton_sequence +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test43 -mode doe -doe_algo halton_sequence -doe_samples 20 -log_time f + +Running test 51 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test51 -mode discretize -resp "PF,PF1" -discr_algo jenks -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 70 test type: verify, description: nn_keras verification test with re-using saved model_per_response trained model -../../src/run_smlp.py -model_name "../models/test69_model" -out_dir ./ -pref Test70 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 59 test type: verify, description: basic nn_keras assertion verification test for functional nn_keras model +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test59 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 72 test type: verify, description: nn_keras verification test with re-using saved model_per_response trained model -../../src/run_smlp.py -model_name "../models/test71_model" -out_dir ./ -pref Test72 -mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 68 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response +smlp -model_name "../models/test67_model" -out_dir ./ -pref Test68 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -model_per_response t -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 77 test type: unknown, description: verification test run using model_rerun config covering the case when mrmr selcts only a subset of features specified through the command line or config file -../../src/run_smlp.py -model_name "../models/test76_model" -out_dir ./ -pref Test77 -config ../models/test76_model_rerun_model_config.json +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 74 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model. with separate model for each response +smlp -model_name "../models/test73_model" -out_dir ./ -pref Test74 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult.spec specs_path ../specs Running test 79 test type: query, description: basic test in query mode to test stability (theta) and guard (eta) constraint generation -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test79 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test79 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_num_resp_mult_query_vacuous.spec specs_path ../specs -Running test 80 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test80 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 91 test type: query, description: test to detect contradictory constraints in optimization mode due to contradictory alpha global and alpha bounds constraints on FMAX_xyx +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test91 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps.spec +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs -Running test 81 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test81 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 99 test type: optimize, description: testing that the response and feature names can be taken from spec file in model exploration modes when the responses and/or features are not specified in the command line +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test99 -mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps.spec +spec_fn smlp_toy_num_resp_mult_certify_witness.spec specs_path ../specs -Running test 82 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test82 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1,objv2,objv3 -objv_exprs "(y1+y2)/2;y1;y2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 103 test type: certify, description: +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test103 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test103_model -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_certify_witness.spec -quer_names valid_candidate,grid_conflict,range_conflict -quer_exprs "True;True;True" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps.spec -specs_path ../specs -Running test 83 test type: optimize, description: basic dt_sklearn multi objective pareto optimization test with numeric labels and integer grid as domain and with scaling objectives -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test83 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -beta "y1>7 and y2>6" -objv_names obj1,objv2,objv3 -objv_exprs "(y1+y2)/2;y1/2-y2;y2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 110 test type: prediction, description: smlp toy basic example for predict mode from SMLP user manual +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test110 -mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model t -model_name test110_model -save_model_config t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_system_stable_constant_certify.spec specs_path ../specs -Running test 85 test type: optimize, description: tests alpha and eta constraints specified in command line in optimization mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test85 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs "(y1+y2)/2;y1" -alpha "p2<5 and x==10 and x<12" -eta "p1==4" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 117 test type: certify, description: certification test with knobs only where assertion is valid without stability and fails with stability +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test117 -mode certify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_system_stable_constant_synth_feasible.spec specs_path ../specs -Running test 86 test type: optimize, description: tests alpha -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test86 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs "(y1+y2)/2;y1" -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+p2)/2<6;y1>=9;y2<0" -alpha "p2<5 and x==10 and x<12" -eta "p1==4" -epsilon 0.05 -delta_rel 0.01 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 123 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test123 -mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 8 test type: prediction, description: basic nn_keras prediction test on labeled and new data with numeric labels and two responses +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test8 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -nn_keras_epochs 20 -nn_keras_seq_api f -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_alpha_asrt_verify.spec +Running test 14 test type: train, description: EV-SI real life poly_sklearn prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test14 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +Running test 21 test type: prediction, description: test for illegal symbols in column names +smlp -data "../data/smlp_toy_num_metasymbol_mult_reg.csv" -out_dir ./ -pref Test21 -mode predict -resp "PF ,|PF |" -model poly_sklearn -save_model t -use_model f -model_name test22_model -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_metasymbol_mult_reg_pred_labeled.csv" + +Running test 29 test type: subgroups, description: basic test for subgroup discovery for pass-fail responses +smlp -data "../data/smlp_toy_cls_metasymbol_colnames_mult.csv" -out_dir ./ -pref Test29 -mode subgroups -psg_dim 3 -psg_top 10 -resp "PF 1,PF#" -plots t -seed 10 -log_time f + +Running test 38 test type: doe, description: doe test with four levels with box_wilson +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test38 -mode doe -doe_algo box_wilson -doe_cc_face ccc -doe_cc_alpha r -doe_cc_center 2,3 -log_time f + +Running test 45 test type: doe, description: doe test with four levels with fractional_factorial +smlp -doe_spec "../grids/doe_two_levels_real.csv" -out_dir ./ -pref Test45 -mode doe -doe_algo fractional_factorial -doe_resolution 5 -log_time f + +Running test 53 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test53 -mode discretize -resp "PF,PF1" -discr_algo ordinals -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 87 test type: verify, description: tests global alpha constraints and assertions specified in spec file -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test87 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_alpha_asrt_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 62 test type: verify, description: tests verificaion mode for NN with nn_keras_seq_api t +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test62 -mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -nn_keras_epochs 100 -nn_keras_seq_api t -save_model_config f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "not(x25 and y1<=10);-2*y2-1<10-x2 and x2>5 and x2<8" -vacuity f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +Running test 75 test type: unknown, description: verification test run using model_rerun config covering the case when mrmr selcts only a subset of features specified through the command line or config file +smlp -model_name "../models/test73_model" -out_dir ./ -pref Test75 -config ../models/test73_model_rerun_model_config.json -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" + +spec_fn smlp_toy_num_resp_mult_free_inps.spec specs_path ../specs -Running test 88 test type: optimize, description: basic dt_sklearn multi objective pareto optimization test with beta and objectives specified in spec file -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test88 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 82 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test82 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1,objv2,objv3 -objv_exprs "(y1+y2)/2;y1;y2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat spec_fn smlp_toy_num_resp_mult_query.spec specs_path ../specs Running test 89 test type: query, description: basic test in query mode to test stability (theta) and guard (eta) constraint generation -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test89 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test89 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn_vacuous.spec +spec_fn smlp_toy_num_resp_mult_query.spec specs_path ../specs -Running test 90 test type: optsyn, description: test to detect contradictory constraints in optsyn mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test90 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 97 test type: query, description: basic test for rf_sklearn in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test97 -mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_query_vacuous.spec +spec_fn smlp_toy_num_resp_mult_unsat_eta_verify.spec specs_path ../specs -Running test 91 test type: query, description: test to detect contradictory constraints in optimization mode due to contradictory alpha global and alpha bounds constraints on FMAX_xyx -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test91 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 106 test type: verify, description: test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test106 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_unsat_eta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_verify_vacuous.spec +spec_fn smlp_toy_basic.spec specs_path ../specs -Running test 92 test type: verify, description: test to detect contradictory constraints in verification mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test92 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_verify_vacuous.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 113 test type: optimize, description: smlp toy basic test for mode optimize from SMLP manual +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test113 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model t -model_name test113_model -save_model_config t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec ../specs/smlp_toy_basic.spec -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_system_stable_constant_synth_fail.spec specs_path ../specs -Running test 93 test type: optsyn, description: basic test for mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test93 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 120 test type: synthesize, description: synthesis test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test120 -mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_system_stable_certify.spec specs_path ../specs -Running test 94 test type: optsyn, description: basic test for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test94 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 127 test type: certify, description: certification example with knobs only and fictitious inputs with values fixed through their ranges +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test127 -mode certify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 95 test type: optsyn, description: basic test for dt_caret in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test95 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 142 test type: optsyn, description: basic test for compress_rules option for rf_sklearn in optsin mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test142 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 6 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test6 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_optsyn.spec -specs_path ../specs -Running test 96 test type: optsyn, description: basic test for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test96 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 11 test type: prediction, description: basic poly_sklearn prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test11 -mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_query.spec -specs_path ../specs -Running test 97 test type: query, description: basic test for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test97 -mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 16 test type: prediction, description: basic nn_keras prediction test from saved model on new data with numeric labels and two responses +smlp -model_name "../models/Test8_smlp_toy_num_resp_mult" -out_dir ./ -pref Test16 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_optsyn.spec -specs_path ../specs -Running test 98 test type: optsyn, description: basic test for et_caret in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test98 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 26 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels +smlp -model_name "../models/test26_model" -out_dir ./ -pref Test26 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec -specs_path ../specs -Running test 99 test type: optimize, description: testing that the response and feature names can be taken from spec file in model exploration modes when the responses and/or features are not specified in the command line -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test99 -mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 33 test type: unknown, description: testing -config option with subgroups mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test33 -config ../models/Test31_smlp_toy_num_resp_mult_args_config.json -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec -specs_path ../specs -Running test 100 test type: optimize, description: basic test for sat_threshold option enabing usage of objectve values in SAT assignments that prove optimization thresholds -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test100 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 41 test type: doe, description: doe test with four levels with random_k_means +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test41 -mode doe -doe_algo random_k_means -doe_samples 20 -log_time f -spec_fn smlp_toy_num_resp_mult_witness.spec -specs_path ../specs -Running test 101 test type: certify, description: basic test in certify mode to test stability (theta) and guard (eta) constraint generation -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test101 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test101_model -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 49 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test49 -mode discretize -resp "PF,PF1" -discr_algo quantile -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -spec_fn smlp_toy_num_resp_mult_witness.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 102 test type: certify, description: basic test in certify mode to test stability (theta) and guard (eta) constraint generation -../../src/run_smlp.py -model_name "../models/test101_model" -out_dir ./ -pref Test102 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 57 test type: verify, description: basic dt_sklearn assertion verfication test with numeric labels and integer grid as domain +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test57 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x0<=5 and y1<=10;-2*y2-1<10-x2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_certify_witness.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 103 test type: certify, description: -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test103 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test103_model -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_certify_witness.spec -quer_names valid_candidate,grid_conflict,range_conflict -quer_exprs "True;True;True" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 65 test type: verify, description: basic dt_sklearn assertion verification test on data with numeric labels +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test65 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test65_model -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 104 test type: verify, description: assertion verfication test with wrong spec that does not assign a single value using a singleton grid or range with equal max and min -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test104 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 70 test type: verify, description: nn_keras verification test with re-using saved model_per_response trained model +smlp -model_name "../models/test69_model" -out_dir ./ -pref Test70 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult_stable_verify.spec +Running test 77 test type: unknown, description: verification test run using model_rerun config covering the case when mrmr selcts only a subset of features specified through the command line or config file +smlp -model_name "../models/test76_model" -out_dir ./ -pref Test77 -config ../models/test76_model_rerun_model_config.json + +spec_fn smlp_toy_num_resp_mult_free_inps.spec specs_path ../specs -Running test 105 test type: verify, description: basic dt_sklearn assertion verfication test with numeric labels and integer grid as domain -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test105 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_stable_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 83 test type: optimize, description: basic dt_sklearn multi objective pareto optimization test with numeric labels and integer grid as domain and with scaling objectives +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test83 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -beta "y1>7 and y2>6" -objv_names obj1,objv2,objv3 -objv_exprs "(y1+y2)/2;y1/2-y2;y2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_unsat_eta_verify.spec +spec_fn smlp_toy_num_resp_mult_optsyn_vacuous.spec specs_path ../specs -Running test 106 test type: verify, description: test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test106 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_unsat_eta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 90 test type: optsyn, description: test to detect contradictory constraints in optsyn mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test90 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_beta_verify.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 107 test type: verify, description: test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test107 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_beta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 98 test type: optsyn, description: basic test for et_caret in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test98 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_synthesize.spec +spec_fn smlp_toy_system.spec specs_path ../specs -Running test 108 test type: synthesize, description: basic test for dt_sklearn in model exploration mode synthesize where synthesis succeeds -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test108 -mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 116 test type: certify, description: basic test in certify mode when system is specified and is used as the model; p2 rel-rad needs to be 0 or very close to it the witness to first query to be stable +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test116 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system.spec -quer_names query1,query2 -quer_exprs "y1>0;y2<=0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_cannot_synthesize.spec +spec_fn smlp_toy_witness_certify.spec specs_path ../specs -Running test 109 test type: synthesize, description: basic test for mode synthesize where synthesis fails -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test109 -mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_cannot_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 128 test type: certify, description: Basic regression test in certify mode covering all four possible outcomes when certifying a witness for a query: the witness is stable +smlp -data "../data/smlp_toy_ctg_num_resp.csv" -out_dir ./ -pref Test128 -mode certify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model f -model_per_response f -spec ../specs/smlp_toy_witness_certify.spec -quer_names query_stable_witness,query_grid_conflict,query_unstable_witness,query_infeasible_witness,query_poly_intercept_sensitive -quer_exprs "y2<=90;y1>=9;y1>=(-13);y1>9;y1>=(-10)" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 110 test type: prediction, description: smlp toy basic example for predict mode from SMLP user manual -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test110 -mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model t -model_name test110_model -save_model_config t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" +spec_fn smlp_toy_system_stable_constant_synth_feasible.specRunning test 5 test type: prediction, description: basic dt_caret prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test5 -mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model t -use_model f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 111 test type: unknown, description: smlp toy basic test to rerun saved model using the model rerun config file saved during model training -../../src/run_smlp.py -model_name "../models/test110_model" -out_dir ./ -pref Test111 -config ../models/test110_model_rerun_model_config.json -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" +Running test 18 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test18 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test19_model -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 112 test type: prediction, description: smlp toy basic test from SMLP manual -../../src/run_smlp.py -model_name "../models/test110_model" -out_dir ./ -pref Test112 -mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -use_model t -save_model f -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" +Running test 25 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test25 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test26_model -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_basic.spec -specs_path ../specs -Running test 113 test type: optimize, description: smlp toy basic test for mode optimize from SMLP manual -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test113 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model t -model_name test113_model -save_model_config t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec ../specs/smlp_toy_basic.spec +Running test 36 test type: doe, description: doe test with four levels with sukharev_grid +smlp -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test36 -mode doe -doe_algo sukharev_grid -doe_samples 125 -log_time f -spec_fn smlp_toy_basic.spec -specs_path ../specs -Running test 114 test type: optimize, description: smlp toy basic test for mode optimize from SMLP manual without specifying resp and feat in command line -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test114 -mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model f -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec ../specs/smlp_toy_basic.spec +Running test 44 test type: doe, description: doe test with four levels with uniform_random_matrix +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test44 -mode doe -doe_algo uniform_random_matrix -doe_samples 20 -log_time f -spec_fn smlp_toy_system.spec +Running test 52 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test52 -mode discretize -resp "PF,PF1" -discr_algo jenks -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 115 test type: certify, description: basic test in certify mode -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test115 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system.spec -quer_names query1,query2 -quer_exprs "y1>0;y2<=0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 60 test type: verify, description: basic nn_keras assertion verification test for functional nn_keras model +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test60 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_system.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 116 test type: certify, description: basic test in certify mode when system is specified and is used as the model; p2 rel-rad needs to be 0 or very close to it the witness to first query to be stable -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test116 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system.spec -quer_names query1,query2 -quer_exprs "y1>0;y2<=0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 67 test type: verify, description: basic dt_sklearn assertion verification test on data with numeric labels +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test67 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -model_per_response t -save_model t -use_model f -model_name test67_model -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_certify.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 117 test type: certify, description: certification test with knobs only where assertion is valid without stability and fails with stability -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test117 -mode certify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 73 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test73 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test73_model -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -spec_fn smlp_toy_system_stable_constant_verify.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 118 test type: verify, description: verification test with knobs only where assertion is valid without stability and fails with stability -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test118 -mode verify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 84 test type: verify, description: tests global alpha constraints specified using option -alpha on inputs +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test84 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -alpha "x2==7.0 and x0==0 and x1==2.5" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_query.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 119 test type: query, description: query test with knobs only where query is satisfiable without stability and fails with stability -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test119 -mode query -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 95 test type: optsyn, description: basic test for dt_caret in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test95 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_fail.spec +spec_fn smlp_toy_num_resp_mult_synthesize.spec specs_path ../specs -Running test 120 test type: synthesize, description: synthesis test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test120 -mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 108 test type: synthesize, description: basic test for dt_sklearn in model exploration mode synthesize where synthesis succeeds +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test108 -mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +spec_fn smlp_toy_system_stable_constant_verify.spec specs_path ../specs -Running test 121 test type: synthesize, description: synthesis test with constant knob and no inputs where synthesis is feasible -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test121 -mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 118 test type: verify, description: verification test with knobs only where assertion is valid without stability and fails with stability +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test118 -mode verify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_system_stable_constant_synth_fail.spec specs_path ../specs -Running test 122 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test122 -mode optimize -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 124 test type: optsyn, description: optimized synthesis test with constant knob and no inputs where synthesis is not feasible because while beta constraint is feasible the assertion is not feasible therefore optimization is not performed +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test124 -mode optsyn -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +spec_fn smlp_toy_system_stable_verify.spec specs_path ../specs -Running test 123 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test123 -mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 140 test type: verify, description: verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test140 -mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_verify.spec -trace_prec 1 -trace_anonym t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_fail.spec -specs_path ../specs -Running test 124 test type: optsyn, description: optimized synthesis test with constant knob and no inputs where synthesis is not feasible because while beta constraint is feasible the assertion is not feasible therefore optimization is not performed -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test124 -mode optsyn -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 147 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and sequential API +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test147 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 7 test type: prediction, description: basic rf_sklearn prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test7 -mode predict -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +Running test 10 test type: prediction, description: basic et_sklearn prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test10 -mode predict -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 15 -et_sklearn_bootstrap f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +Running test 15 test type: prediction, description: basic dt_caret prediction test from saved model on new data with numeric labels +smlp -model_name "../models/Test5_smlp_toy_num_resp_mult" -out_dir ./ -pref Test15 -mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +Running test 23 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test23 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test24_model -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +Running test 30 test type: subgroups, description: basic test for subgroup discovery for numric responses +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test30 -mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -feat x,p1,p2 -plots t -seed 10 -log_time f + +Running test 37 test type: doe, description: doe test with four levels with box_behnken +smlp -doe_spec "../grids/doe_three_levels_real_nan.csv" -out_dir ./ -pref Test37 -mode doe -doe_algo box_behnken -log_time f + +Running test 46 test type: prediction, description: tests options -pos_val and -neg_val +smlp -data "../data/smlp_toy_pf_mult.csv" -out_dir ./ -pref Test46 -mode predict -resp "PF,PF1" -model poly_sklearn -save_model t -save_model_config f -use_model f -model_name test47_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass -new_dat "../data/smlp_toy_pf_mult.csv" + +Running test 54 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test54 -mode discretize -resp "PF,PF1" -discr_algo ordinals -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 125 test type: optsyn, description: optimized synthesis test with constant knob and no inputs where synthesis is feasible and optimization is performed -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test125 -mode optsyn -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 61 test type: verify, description: tests verificaion mode for NN with nn_keras_seq_api f +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test61 -mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -nn_keras_epochs 100 -save_model_config f --spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "not(x25 and y1<=10);-2*y2-1<10-x2 and x2>5 and x2<8" -vacuity f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_system_stable_verify.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 126 test type: verify, description: verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test126 -mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 76 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test76 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test76_model -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_certify.spec +spec_fn smlp_toy_num_resp_mult_alpha_asrt_verify.spec specs_path ../specs -Running test 127 test type: certify, description: certification example with knobs only and fictitious inputs with values fixed through their ranges -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test127 -mode certify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 87 test type: verify, description: tests global alpha constraints and assertions specified in spec file +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test87 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_alpha_asrt_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_witness_certify.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 128 test type: certify, description: Basic regression test in certify mode covering all four possible outcomes when certifying a witness for a query: the witness is stable -../../src/run_smlp.py -data "../data/smlp_toy_ctg_num_resp.csv" -out_dir ./ -pref Test128 -mode certify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model f -model_per_response f -spec ../specs/smlp_toy_witness_certify.spec -quer_names query_stable_witness,query_grid_conflict,query_unstable_witness,query_infeasible_witness,query_poly_intercept_sensitive -quer_exprs "y2<=90;y1>=9;y1>=(-13);y1>9;y1>=(-10)" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 96 test type: optsyn, description: basic test for rf_sklearn in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test96 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_configuration_verify.spec +Running test 111 test type: unknown, description: smlp toy basic test to rerun saved model using the model rerun config file saved during model training +smlp -model_name "../models/test110_model" -out_dir ./ -pref Test111 -config ../models/test110_model_rerun_model_config.json -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" + +spec_fn smlp_toy_system.spec specs_path ../specs -Running test 129 test type: verify, description: verification example with demonstrating all basic result scenarious for assertions -../../src/run_smlp.py -data "../data/smlp_toy_ctg_num_resp.csv" -out_dir ./ -pref Test129 -mode verify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model f -model_per_response f -spec ../specs/smlp_toy_configuration_verify.spec -asrt_names assert_stable_config,assert_grid_conflict,assert_unstable_config,assert_infeasible -asrt_exprs "y2<=90;y1>=9;y1>=(-10);y1>20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 115 test type: certify, description: basic test in certify mode +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test115 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system.spec -quer_names query1,query2 -quer_exprs "y1>0;y2<=0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_system_stable_verify.spec specs_path ../specs -Running test 140 test type: verify, description: verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test140 -mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_verify.spec -trace_prec 1 -trace_anonym t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 126 test type: verify, description: verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test126 -mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult.spec specs_path ../specs Running test 141 test type: optimize, description: basic test for compress_rules option for dt_sklearn in optimization mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test141 -mode optimize -opt_strategy lazy -pareto f -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -spec ../specs/smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs "y1;y2" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test141 -mode optimize -opt_strategy lazy -pareto f -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -spec ../specs/smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs "y1;y2" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec -specs_path ../specs -Running test 142 test type: optsyn, description: basic test for compress_rules option for rf_sklearn in optsin mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test142 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 148 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and sequential API +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test148 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_query.spec +spec_fn smlp_toy_system_stable_constant_synth_fail.spec specs_path ../specs -Running test 143 test type: query, description: basic test for compress_rules for et_sklearn in mode query -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test143 -mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 122 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test122 -mode optimize -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 145 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed -../../src/run_smlp.py -out_dir ./ -pref Test145 -mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 139 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test139 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -spec_fn smlp_toy_system.spec -specs_path ../specs -Running test 146 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed -../../src/run_smlp.py -out_dir ./ -pref Test146 -mode optimize -pareto t -opt_strategy lazy -model poly_sklearn -resp y1,y2 -feat p1,p2,x1,x2 -save_model t -use_model f -mrmr_pred 0 -model_per_response t -split 1 -spec ../specs/smlp_toy_system.spec -doe_spec ../grids/explore_doe_two_levels.csv -doe_algo latin_hypercube -epsilon 0.99999999 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 149 test type: prediction, description: tests the mae loss function MeanAbsoluteError and sample weoghts +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test149 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mae -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 147 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and sequential API -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test147 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_mult_verify.spec +specs_path ../specs +Running test 156 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner for functional model training; adapts test 154 by consdering multiple responses +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test156 -mode verify -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse -Running test 148 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and sequential API -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test148 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 162 test type: verify, description: tests model term construction with flat_encoding of tress and model per reponse when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test162 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -Running test 149 test type: prediction, description: tests the mae loss function MeanAbsoluteError and sample weoghts -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test149 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mae -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_mult_optsyn.spec +specs_path ../specs +Running test 167 test type: optsyn, description: basic flat tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test167 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 150 test type: prediction, description: tests the mape loss function MeanAbsolutePercentageError and sample weights -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test150 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_mult_optsyn.spec +specs_path ../specs +Running test 171 test type: optimize, description: basic test for et_caret with flat tree_encoding in model exploration mode optimize +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test171 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 151 test type: prediction, description: tests msle loss function MeanSquaredLogarithmicError and and sample weoghts -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test151 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss msle -sw_coef 3 -sw_exp 10 -sw_int 0 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_mult_optsyn.spec +specs_path ../specs +Running test 176 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api f for nn_keras in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test176 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 152 test type: prediction, description: tests the huber loss function Huber and sample weights -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test152 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss huber -sw_coef 8 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +specs_path ../specs +Running test 181 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test181 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 153 test type: prediction, description: tests the logcosh loss function LogCosh and sample weights -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test153 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss logcosh -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mse -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +specs_path ../specs +Running test 182 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test182 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" -spec_fn smlp_toy_num_resp_mult_y2_verify.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 154 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner for functional model training -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test154 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 +Running test 186 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test186 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_y2_verify.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 155 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test155 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae +Running test 192 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test192 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_verify.spec +spec_fn smlp_toy_system_stable_constant_synth_feasible.spec specs_path ../specs -Running test 156 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner for functional model training; adapts test 154 by consdering multiple responses -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test156 -mode verify -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse +Running test 125 test type: optsyn, description: optimized synthesis test with constant knob and no inputs where synthesis is feasible and optimization is performed +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test125 -mode optsyn -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_verify.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 157 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training; adapts test 155 by consdering multiple responses -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test157 -mode verify -resp y1,y2 -feat x,p1,p2 --model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse,logcosh +Running test 144 test type: verify, description: basic test for compress_rules for dt_sklearn in mode verify and re-using saved model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test144 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -save_model f -use_model f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 158 test type: prediction, description: tests the mape loss function and sample weights with model_per_response t -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test158 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -model_per_response t -sw_coef 8 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 150 test type: prediction, description: tests the mape loss function MeanAbsolutePercentageError and sample weights +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test150 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" Running test 159 test type: prediction, description: tests the msle loss function and sample weights with model_per_response t -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test159 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -model_per_response t -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae,cosine -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 160 test type: prediction, description: tests nn keras tuner bayesian -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test160 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -nn_keras_metrics msle -nn_keras_tuner bayesian -nn_keras_layers_grid "2,3" -nn_keras_losses_grid "mse,mae,huber" -model_per_response f -sw_coef 8 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 161 test type: prediction, description: tests nn keras tuner bayesian -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test161 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -nn_keras_metrics mape,logcosh -nn_keras_tuner random -nn_keras_lrates_grid "0.01,0.001" -nn_keras_batches_grid "32,64" -model_per_response f -sw_coef 4 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test159 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -model_per_response t -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae,cosine -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs Running test 164 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test164 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test164 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 165 test type: optsyn, description: basic flat tree encoding test for dt_caretin model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test165 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding flat -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 166 test type: optsyn, description: basic flat tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test166 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 166 test type: optsyn, description: basic flat tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test166 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 170 test type: optimize, description: basic test for et_sklearn with flat tree_encoding and model_per_response f in model exploration mode optimize +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test170 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 167 test type: optsyn, description: basic flat tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test167 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 175 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test175 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 168 test type: optimize, description: basic test for rf_caret with flat tree_encoding and modelper_response in model exploration mode optimize -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test168 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding flat -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 180 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features and responses are not scaled adapts test 175 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test180 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_feat f -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs -Running test 169 test type: optimize, description: basic test for et_sklearn with flat tree_encoding and model_per_response t in model exploration mode optimize -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test169 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 183 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test183 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs -Running test 170 test type: optimize, description: basic test for et_sklearn with flat tree_encoding and model_per_response f in model exploration mode optimize -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test170 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 187 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization adapts test 164 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test187 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 171 test type: optimize, description: basic test for et_caret with flat tree_encoding in model exploration mode optimize -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test171 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 193 test type: optimize, description: basic test for et_caret with branched tree_encoding in model exploration mode optimize adapts test 171 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test193 -mode optimize -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_y2_verify.spec +Running test 216 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test216 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f + +Running test 222 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test222 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +spec_fn smlp_toy_missing_radii.spec specs_path ../specs -Running test 172 test type: verify, description: basic test for nn_keras flat encoding for functional api -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test172 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" +Running test 229 test type: certify, description: basic test for checking that each knob must have either absolute or relative radius specified in the spec file (even if radii are specified in the command line) +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test229 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_missing_radii.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_y2_verify.spec + +Running test 153 test type: prediction, description: tests the logcosh loss function LogCosh and sample weights +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test153 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss logcosh -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mse -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +Running test 161 test type: prediction, description: tests nn keras tuner bayesian +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test161 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -nn_keras_metrics mape,logcosh -nn_keras_tuner random -nn_keras_lrates_grid "0.01,0.001" -nn_keras_batches_grid "32,64" -model_per_response f -sw_coef 4 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 173 test type: verify, description: basic test for nn_keras flat encoding for sequential api -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test173 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" +Running test 168 test type: optimize, description: basic test for rf_caret with flat tree_encoding and modelper_response in model exploration mode optimize +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test168 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding flat -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs Running test 174 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test174 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test174 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 175 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test175 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 190 test type: optimize, description: basic test for rf_caret with branched tree_encoding and modelper_response in model exploration mode optimize adapts test 168 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test190 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding branched -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_mult_no_input.spec specs_path ../specs -Running test 176 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api f for nn_keras in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test176 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 202 test type: optimize, description: basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and no beta constraints +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test202 -mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_no_input.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +Running test 215 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test215 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +Running test 221 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test221 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +spec_fn smlp_toy_system_radii_update_certify.spec specs_path ../specs -Running test 177 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test177 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 228 test type: certify, description: test that radii specified in command line properly override the radii specified in the spec file. Here we override both ansolute and relative radii and one can observe that the certification results also change compared to test 116 +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test228 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system_radii_update_certify.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec + +spec_fn smlp_toy_system_stable_constant_synth_feasible.spec specs_path ../specs -Running test 178 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features are not scaled adapts test 177 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test178 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 205 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 145 +smlp -out_dir ./ -pref Test205 -mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +Running test 219 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test219 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type integer -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +Running test 225 test type: correlate, description: basic test for correlate mode and tests the adjusted mutual information +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test225 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f + +Running test 233 test type: subgroups, description: tests subgroup discovery mode when the response has string values +smlp -data "../data/smlp_toy_string_response.csv" -out_dir ./ -pref Test233 -mode subgroups -resp str_resp1 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f + + +specs_path ../specs +Running test 145 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed +smlp -out_dir ./ -pref Test145 -mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +Running test 152 test type: prediction, description: tests the huber loss function Huber and sample weights +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test152 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss huber -sw_coef 8 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +Running test 160 test type: prediction, description: tests nn keras tuner bayesian +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test160 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -nn_keras_metrics msle -nn_keras_tuner bayesian -nn_keras_layers_grid "2,3" -nn_keras_losses_grid "mse,mae,huber" -model_per_response f -sw_coef 8 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 179 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn when resposes are not scaled adapts test 174 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test179 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 177 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test177 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 180 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features and responses are not scaled adapts test 175 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test180 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_feat f -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 191 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response t in model exploration mode optimize adapts test 169 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test191 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap t -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs -Running test 181 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test181 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 196 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 and test 181 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test196 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +spec_fn smlp_toy_system_stable_constant_synth_fail.spec specs_path ../specs -Running test 182 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test182 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" +Running test 203 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed adapts test 122 +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test203 -mode optimize -pareto f -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +Running test 217 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test217 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +Running test 223 test type: correlate, description: basic test for correlate mode and tests the normalized mutual information +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test223 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f + +spec_fn smlp_toy_system_monotone_knob.05_verify.spec specs_path ../specs -Running test 183 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test183 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 230 test type: verify, description: tests that outputs in system specificaation might depend on different inuts (knobs and free inputs) +smlp -data "../data/smlp_toy_monotone_basic.csv" -out_dir ./ -pref Test230 -mode verify -spec ../specs/smlp_toy_system_monotone_knob.05_verify.spec -model system -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec + +spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 187 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization adapts test 164 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test187 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 154 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner for functional model training +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test154 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 188 test type: optsyn, description: basic branched tree encoding test for dt_caretin model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test188 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding branched -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 178 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features are not scaled adapts test 177 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test178 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 185 test type: verify, description: tests model term construction with branched_encoding of tress and model per reponse when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test185 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs Running test 189 test type: optsyn, description: basic branched tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn adapts test 166 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test189 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test189 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 190 test type: optimize, description: basic test for rf_caret with branched tree_encoding and modelper_response in model exploration mode optimize adapts test 168 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test190 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding branched -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 194 test type: optsyn, description: basic branched tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test194 -mode optsyn -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs -Running test 191 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response t in model exploration mode optimize adapts test 169 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test191 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap t -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 198 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 and test 183 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test198 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_system_stable_constant_synth_feasible.spec specs_path ../specs -Running test 192 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test192 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 204 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 123 +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test204 -mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +Running test 218 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test218 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +Running test 226 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test226 -mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f + +spec_fn smlp_toy_system_running_example_certify.spec specs_path ../specs -Running test 193 test type: optimize, description: basic test for et_caret with branched tree_encoding in model exploration mode optimize adapts test 171 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test193 -mode optimize -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 232 test type: certify, description: running example from smlp manual +smlp -data "../data/smlp_toy_system_running_example_certify.csv" -out_dir ./ -pref Test232 -mode certify -spec ../specs/smlp_toy_system_running_example_certify.spec -model system -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec + +spec_fn smlp_toy_num_resp_mult_query.spec specs_path ../specs -Running test 194 test type: optsyn, description: basic branched tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test194 -mode optsyn -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 143 test type: query, description: basic test for compress_rules for et_sklearn in mode query +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test143 -mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_mult_verify.spec specs_path ../specs -Running test 195 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 192 by setting n_estimators 3 and then discrepancy between z3 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test195 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 157 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training; adapts test 155 by consdering multiple responses +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test157 -mode verify -resp y1,y2 -feat x,p1,p2 --model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse,logcosh -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 196 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 and test 181 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test196 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 163 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test163 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 197 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 and test 182 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test197 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" +Running test 169 test type: optimize, description: basic test for et_sklearn with flat tree_encoding and model_per_response t in model exploration mode optimize +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test169 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 198 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 and test 183 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test198 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 173 test type: verify, description: basic test for nn_keras flat encoding for sequential api +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test173 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs Running test 199 test type: optimize, description: test to demonstrate that in pareto optimization and optsyn modes with multiple objectives when beta constraints are not present SMLP results are not consistent when different solvers are used; this is due to fact that when a subset of objectoves are exemined in pareto algo -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test199 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test199 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +Running test 224 test type: correlate, description: basic test for correlate mode and tests the Shannon mutual information +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test224 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f + +spec_fn smlp_toy_system_decreasing_knob.05_certify.spec specs_path ../specs -Running test 200 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test200 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 231 test type: certify, description: certification test with monotonicity query with a knob with a grid point +smlp -data "../data/smlp_toy_monotone_basic.csv" -out_dir ./ -pref Test231 -mode certify -spec ../specs/smlp_toy_system_decreasing_knob.05_certify.spec -model system -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_no_input_beta.spec + +spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 201 test type: optimize, description: basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and there are beta constraints -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test201 -mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_no_input_beta.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 155 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test155 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae -spec_fn smlp_toy_num_resp_mult_no_input.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 202 test type: optimize, description: basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and no beta constraints -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test202 -mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_no_input.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 179 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn when resposes are not scaled adapts test 174 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test179 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_fail.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 203 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed adapts test 122 -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test203 -mode optimize -pareto f -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 184 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model adapts test 139 +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test184 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 204 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 123 -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test204 -mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 188 test type: optsyn, description: basic branched tree encoding test for dt_caretin model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test188 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding branched -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs -Running test 205 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 145 -../../src/run_smlp.py -out_dir ./ -pref Test205 -mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 197 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 and test 182 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test197 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" + +spec_fn smlp_toy_num_resp_mult_no_input_beta.spec +specs_path ../specs +Running test 201 test type: optimize, description: basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and there are beta constraints +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test201 -mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_no_input_beta.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_system_stable_constant_synth_feasible.spec specs_path ../specs Running test 206 test type: optsyn, description: optimized synthesis test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 125 -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test206 -mode optsyn -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -Running test 215 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test215 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass - -Running test 216 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test216 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f - -Running test 217 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test217 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass - -Running test 218 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test218 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass - -Running test 219 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test219 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type integer -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test206 -mode optsyn -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f Running test 220 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test220 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test220 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -Running test 221 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test221 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 227 test type: correlate, description: basic test for correlate mode and tests the normalized mutual information +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test227 -mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f -Running test 222 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test222 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 234 test type: subgroups, description: tests subgroup discovery mode when there are two responses with string values +smlp -data "../data/smlp_toy_string_response.csv" -out_dir ./ -pref Test234 -mode subgroups -resp str_resp1,str_resp2 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f -Running test 223 test type: correlate, description: basic test for correlate mode and tests the normalized mutual information -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test223 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f -Running test 224 test type: correlate, description: basic test for correlate mode and tests the Shannon mutual information -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test224 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f +spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +specs_path ../specs +Running test 121 test type: synthesize, description: synthesis test with constant knob and no inputs where synthesis is feasible +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test121 -mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 225 test type: correlate, description: basic test for correlate mode and tests the adjusted mutual information -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test225 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f +spec_fn smlp_toy_configuration_verify.spec +specs_path ../specs +Running test 129 test type: verify, description: verification example with demonstrating all basic result scenarious for assertions +smlp -data "../data/smlp_toy_ctg_num_resp.csv" -out_dir ./ -pref Test129 -mode verify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model f -model_per_response f -spec ../specs/smlp_toy_configuration_verify.spec -asrt_names assert_stable_config,assert_grid_conflict,assert_unstable_config,assert_infeasible -asrt_exprs "y2<=90;y1>=9;y1>=(-10);y1>20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 226 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test226 -mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f +spec_fn smlp_toy_system.spec +specs_path ../specs +Running test 146 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed +smlp -out_dir ./ -pref Test146 -mode optimize -pareto t -opt_strategy lazy -model poly_sklearn -resp y1,y2 -feat p1,p2,x1,x2 -save_model t -use_model f -mrmr_pred 0 -model_per_response t -split 1 -spec ../specs/smlp_toy_system.spec -doe_spec ../grids/explore_doe_two_levels.csv -doe_algo latin_hypercube -epsilon 0.99999999 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 227 test type: correlate, description: basic test for correlate mode and tests the normalized mutual information -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test227 -mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f +Running test 151 test type: prediction, description: tests msle loss function MeanSquaredLogarithmicError and and sample weoghts +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test151 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss msle -sw_coef 3 -sw_exp 10 -sw_int 0 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_system_radii_update_certify.spec -specs_path ../specs -Running test 228 test type: certify, description: test that radii specified in command line properly override the radii specified in the spec file. Here we override both ansolute and relative radii and one can observe that the certification results also change compared to test 116 -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test228 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system_radii_update_certify.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 158 test type: prediction, description: tests the mape loss function and sample weights with model_per_response t +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test158 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -model_per_response t -sw_coef 8 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_missing_radii.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 229 test type: certify, description: basic test for checking that each knob must have either absolute or relative radius specified in the spec file (even if radii are specified in the command line) -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test229 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_missing_radii.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 165 test type: optsyn, description: basic flat tree encoding test for dt_caretin model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test165 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding flat -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_monotone_knob.05_verify.spec +spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 230 test type: verify, description: tests that outputs in system specificaation might depend on different inuts (knobs and free inputs) -../../src/run_smlp.py -data "../data/smlp_toy_monotone_basic.csv" -out_dir ./ -pref Test230 -mode verify -spec ../specs/smlp_toy_system_monotone_knob.05_verify.spec -model system -seed 10 -log_time f +Running test 172 test type: verify, description: basic test for nn_keras flat encoding for functional api +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test172 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" -spec_fn smlp_toy_system_decreasing_knob.05_certify.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 231 test type: certify, description: certification test with monotonicity query with a knob with a grid point -../../src/run_smlp.py -data "../data/smlp_toy_monotone_basic.csv" -out_dir ./ -pref Test231 -mode certify -spec ../specs/smlp_toy_system_decreasing_knob.05_certify.spec -model system -seed 10 -log_time f +Running test 195 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 192 by setting n_estimators 3 and then discrepancy between z3 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test195 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_running_example_certify.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 232 test type: certify, description: running example from smlp manual -../../src/run_smlp.py -data "../data/smlp_toy_system_running_example_certify.csv" -out_dir ./ -pref Test232 -mode certify -spec ../specs/smlp_toy_system_running_example_certify.spec -model system -seed 10 -log_time f - -Running test 233 test type: subgroups, description: tests subgroup discovery mode when the response has string values -../../src/run_smlp.py -data "../data/smlp_toy_string_response.csv" -out_dir ./ -pref Test233 -mode subgroups -resp str_resp1 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f - -Running test 234 test type: subgroups, description: tests subgroup discovery mode when there are two responses with string values -../../src/run_smlp.py -data "../data/smlp_toy_string_response.csv" -out_dir ./ -pref Test234 -mode subgroups -resp str_resp1,str_resp2 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f +Running test 200 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test200 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Initiating 7 worker... comparing Test1_smlp_toy_num_resp_mult_y1_dt_caret_tree_rules.txt to master Passed! comparing Test1_smlp_toy_num_resp_mult.txt to master @@ -1611,9 +1704,34 @@ comparing Test56_smlp_toy_mult_discr.txt to master Passed! comparing Test56_smlp_toy_mult_discr_missing_values_dict.json to master Passed! -Test 57 Failed: -Error in Build stage: -Data file does not exist +comparing Test57_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! comparing Test58_smlp_toy_num_resp_mult.txt to master Passed! comparing Test58_smlp_toy_num_resp_mult_data_bounds.json to master @@ -1664,158 +1782,415 @@ comparing Test59_smlp_toy_num_resp_mult_model_levels_dict.json to master Passed! comparing Test59_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master Passed! -comparing Test59_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +comparing Test59_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +Passed! +File master Test59_smlp_toy_num_resp_mult_trace.csv does not exist +File master Test59_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist +comparing Test59_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +Passed! +comparing Test59_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +Passed! +comparing Test59_smlp_toy_num_resp_mult_verify_results.json to master +Passed! +File master Test59_smlp_toy_num_resp_mult_y2_smlp_full_model_term.json does not exist +File master Test59_smlp_toy_num_resp_mult_y2_smlp_model_term.json does not exist +comparing Test60_smlp_toy_num_resp_mult.txt to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_data_bounds.json to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_missing_values_dict.json to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_model_features_dict.json to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_model_gen.json to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_model_levels_dict.json to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +Passed! +File master Test60_smlp_toy_num_resp_mult_trace.csv does not exist +File master Test60_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist +comparing Test60_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_verify_results.json to master +Passed! +File master Test60_smlp_toy_num_resp_mult_y2_smlp_full_model_term.json does not exist +File master Test60_smlp_toy_num_resp_mult_y2_smlp_model_term.json does not exist +comparing Test61_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_model_gen.json to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +File master Test61_smlp_toy_num_resp_noknobs_train-reg_y1_mse.png does not exist +File master Test61_smlp_toy_num_resp_noknobs_train-reg_y2_mse.png does not exist +comparing Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_model_gen.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +File master Test62_smlp_toy_num_resp_noknobs_train-reg_all_responses_mse.png does not exist +comparing Test62_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! +File master test63_model_dt_sklearn_y1_tree_rules.txt does not exist +comparing Test63_smlp_toy_num_resp_mult.txt to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_missing_values_dict.json to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +Passed! +File master Test63_smlp_toy_num_resp_mult_trace.csv does not exist +comparing Test63_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_verify_results.json to master +Passed! +comparing test63_model_data_bounds.json to master +Passed! +comparing test63_model_model_features_dict.json to master +Passed! +comparing test63_model_model_levels_dict.json to master +Passed! +comparing test63_model_rerun_model_config.json to master +Passed! +File master test63_model_y1_smlp_full_model_term.json does not exist +File master test63_model_y1_smlp_model_term.json does not exist +comparing Test64_test63_model.txt to master +File master Test64_test63_model_trace.csv does not exist +comparing Test64_test63_model_verify_results.json to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! +comparing test65_model_data_bounds.json to master +Passed! +comparing test65_model_dt_sklearn_tree_rules.txt to master +Passed! +comparing test65_model_model_features_dict.json to master +Passed! +comparing test65_model_model_levels_dict.json to master +Passed! +comparing test65_model_rerun_model_config.json to master +Passed! +comparing Test66_test65_model.txt to master +Passed! +comparing Test66_test65_model_trace.csv to master +Passed! +comparing Test66_test65_model_verify_results.json to master +Passed! +comparing test67_model_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! +comparing test67_model_data_bounds.json to master +Passed! +comparing test67_model_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing test67_model_model_features_dict.json to master +Passed! +comparing test67_model_model_levels_dict.json to master +Passed! +comparing test67_model_rerun_model_config.json to master +Passed! +comparing Test68_test67_model.txt to master +Passed! +comparing Test68_test67_model_trace.csv to master +Passed! +comparing Test68_test67_model_verify_results.json to master +Passed! +comparing Test69_smlp_toy_num_resp_mult.txt to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_missing_values_dict.json to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +Passed! +File master Test69_smlp_toy_num_resp_mult_trace.csv does not exist +File master Test69_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist +comparing Test69_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_verify_results.json to master +Passed! +comparing test69_model_data_bounds.json to master +Passed! +comparing test69_model_model_features_dict.json to master +Passed! +comparing test69_model_model_gen.json to master +Passed! +comparing test69_model_model_levels_dict.json to master +Passed! +comparing test69_model_rerun_model_config.json to master +Passed! +File master test69_model_y2_smlp_full_model_term.json does not exist +File master test69_model_y2_smlp_model_term.json does not exist +comparing Test70_test69_model.txt to master +File master Test70_test69_model_trace.csv does not exist +comparing Test70_test69_model_verify_results.json to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +File master Test71_smlp_toy_num_resp_noknobs_train-reg_y1_mse.png does not exist +File master Test71_smlp_toy_num_resp_noknobs_train-reg_y2_mse.png does not exist +comparing Test71_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! +comparing test71_model_data_bounds.json to master +Passed! +comparing test71_model_model_features_dict.json to master +Passed! +comparing test71_model_model_gen.json to master +Passed! +comparing test71_model_model_levels_dict.json to master +Passed! +comparing test71_model_rerun_model_config.json to master +Passed! +comparing Test72_test71_model.txt to master +Passed! +comparing Test72_test71_model_trace.csv to master +Passed! +comparing Test72_test71_model_verify_results.json to master +Passed! +comparing test73_model_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! +comparing test73_model_data_bounds.json to master +Passed! +comparing test73_model_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing test73_model_model_features_dict.json to master +Passed! +comparing test73_model_model_levels_dict.json to master +Passed! +comparing test73_model_rerun_model_config.json to master Passed! -File master Test59_smlp_toy_num_resp_mult_trace.csv does not exist -File master Test59_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist -comparing Test59_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt to master Passed! -comparing Test59_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master Passed! -comparing Test59_smlp_toy_num_resp_mult_verify_results.json to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master Passed! -File master Test59_smlp_toy_num_resp_mult_y2_smlp_full_model_term.json does not exist -File master Test59_smlp_toy_num_resp_mult_y2_smlp_model_term.json does not exist -comparing Test60_smlp_toy_num_resp_mult.txt to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_data_bounds.json to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master Passed! -comparing Test60_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt to master Passed! -comparing Test60_smlp_toy_num_resp_mult_missing_values_dict.json to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master Passed! -comparing Test60_smlp_toy_num_resp_mult_model_features_dict.json to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_model_gen.json to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_model_levels_dict.json to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master Passed! -comparing Test60_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +comparing Test76_smlp_toy_num_resp_noknobs.txt to master Passed! -File master Test60_smlp_toy_num_resp_mult_trace.csv does not exist -File master Test60_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist -comparing Test60_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_verify_results.json to master +comparing Test76_smlp_toy_num_resp_noknobs_missing_values_dict.json to master Passed! -File master Test60_smlp_toy_num_resp_mult_y2_smlp_full_model_term.json does not exist -File master Test60_smlp_toy_num_resp_mult_y2_smlp_model_term.json does not exist -Test 61 Failed: -Error in Build stage: -Data file does not exist -Test 62 Failed: -Error in Build stage: -Data file does not exist -File master test63_model_dt_sklearn_y1_tree_rules.txt does not exist -comparing Test63_smlp_toy_num_resp_mult.txt to master +comparing Test76_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master Passed! -comparing Test63_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master Passed! -comparing Test63_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_trace.csv to master Passed! -comparing Test63_smlp_toy_num_resp_mult_missing_values_dict.json to master +comparing Test76_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master Passed! -comparing Test63_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master Passed! -comparing Test63_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_verify_results.json to master Passed! -File master Test63_smlp_toy_num_resp_mult_trace.csv does not exist -comparing Test63_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +comparing test76_model_data_bounds.json to master Passed! -comparing Test63_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +comparing test76_model_dt_sklearn_tree_rules.txt to master Passed! -comparing Test63_smlp_toy_num_resp_mult_verify_results.json to master +comparing test76_model_model_features_dict.json to master Passed! -comparing test63_model_data_bounds.json to master +comparing test76_model_model_levels_dict.json to master Passed! -comparing test63_model_model_features_dict.json to master +comparing test76_model_rerun_model_config.json to master Passed! -comparing test63_model_model_levels_dict.json to master +comparing Test77_test76_model.txt to master Passed! -comparing test63_model_rerun_model_config.json to master +comparing Test77_test76_model_trace.csv to master Passed! -File master test63_model_y1_smlp_full_model_term.json does not exist -File master test63_model_y1_smlp_model_term.json does not exist -comparing Test64_test63_model.txt to master -File master Test64_test63_model_trace.csv does not exist -comparing Test64_test63_model_verify_results.json to master +comparing Test77_test76_model_verify_results.json to master Passed! -Test 65 Failed: -Error in Build stage: -Data file does not exist -comparing Test66_test65_model.txt to master -File new Test66_test65_model_verify_results.json does not exist -Test 67 Failed: -Error in Build stage: -Data file does not exist -comparing Test68_test67_model.txt to master -File new Test68_test67_model_verify_results.json does not exist -comparing Test69_smlp_toy_num_resp_mult.txt to master +comparing test78_model_dt_sklearn_tree_rules.txt to master Passed! -comparing Test69_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +comparing Test78_smlp_toy_num_resp_noknobs.txt to master Passed! -comparing Test69_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +comparing Test78_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master Passed! -comparing Test69_smlp_toy_num_resp_mult_missing_values_dict.json to master +comparing Test78_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master Passed! -comparing Test69_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +comparing Test78_smlp_toy_num_resp_noknobs_missing_values_dict.json to master Passed! -comparing Test69_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +comparing Test78_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master Passed! -File master Test69_smlp_toy_num_resp_mult_trace.csv does not exist -File master Test69_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist -comparing Test69_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +comparing Test78_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master Passed! -comparing Test69_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +comparing Test78_smlp_toy_num_resp_noknobs_trace.csv to master Passed! -comparing Test69_smlp_toy_num_resp_mult_verify_results.json to master +comparing Test78_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master Passed! -comparing test69_model_data_bounds.json to master +comparing Test78_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master Passed! -comparing test69_model_model_features_dict.json to master +comparing Test78_smlp_toy_num_resp_noknobs_verify_results.json to master Passed! -comparing test69_model_model_gen.json to master +comparing test78_model_data_bounds.json to master Passed! -comparing test69_model_model_levels_dict.json to master +comparing test78_model_model_features_dict.json to master Passed! -comparing test69_model_rerun_model_config.json to master +comparing test78_model_model_levels_dict.json to master Passed! -File master test69_model_y2_smlp_full_model_term.json does not exist -File master test69_model_y2_smlp_model_term.json does not exist -comparing Test70_test69_model.txt to master -File master Test70_test69_model_trace.csv does not exist -comparing Test70_test69_model_verify_results.json to master +comparing test78_model_rerun_model_config.json to master Passed! -Test 71 Failed: -Error in Build stage: -Data file does not exist -comparing Test72_test71_model.txt to master -File new Test72_test71_model_verify_results.json does not exist -Test 73 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist -Test 74 Failed: -Error in Build stage: -New data file does not exist -Test 75 Failed: -Error in Build stage: -New data file does not exist -Test 76 Failed: -Error in Build stage: -Data file does not exist -comparing Test77_test76_model.txt to master -File new Test77_test76_model_verify_results.json does not exist -Test 78 Failed: -Error in Build stage: -Data file does not exist comparing Test79_smlp_toy_num_resp_mult.txt to master Passed! comparing Test79_smlp_toy_num_resp_mult_data_bounds.json to master @@ -1979,9 +2354,36 @@ comparing Test83_smlp_toy_num_resp_mult_training_prediction_precisions.csv to ma Passed! comparing Test83_smlp_toy_num_resp_mult_training_predictions_summary.csv to master Passed! -Test 84 Failed: -Error in Build stage: -Data file does not exist +comparing Test84_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! comparing Test85_smlp_toy_num_resp_mult_dt_sklearn_tree_rules.txt to master Passed! comparing Test85_smlp_toy_num_resp_mult.txt to master @@ -3110,11 +3512,42 @@ New data file does not exist Test 138 Failed: Error in Build stage: Data file does not exist -Test 139 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! File master Test140_smlp_toy_basic.txt does not exist File master Test140_smlp_toy_basic_data_bounds.json does not exist File master Test140_smlp_toy_basic_features_scaler.pkl does not exist @@ -3189,9 +3622,34 @@ File master Test143_smlp_toy_num_resp_mult_y1_smlp_full_model_term.json does not File master Test143_smlp_toy_num_resp_mult_y1_smlp_model_term.json does not exist File master Test143_smlp_toy_num_resp_mult_y2_smlp_full_model_term.json does not exist File master Test143_smlp_toy_num_resp_mult_y2_smlp_model_term.json does not exist -Test 144 Failed: -Error in Build stage: -Data file does not exist +comparing Test144_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! File master Test145_doe_two_levels_opt.txt does not exist File master Test145_doe_two_levels_opt_trace.csv does not exist File master Test146_explore_doe_two_levels.txt does not exist @@ -3489,16 +3947,76 @@ File master Test161_smlp_toy_num_resp_mult_smlp_toy_num_resp_mult_pred_labeled_t File master Test161_smlp_toy_num_resp_mult_smlp_toy_num_resp_mult_pred_labeled_train-reg_all_responses_mape.png does not exist File master Test161_smlp_toy_num_resp_mult_smlp_toy_num_resp_mult_pred_labeled_training_prediction_precisions.csv does not exist File master Test161_smlp_toy_num_resp_mult_smlp_toy_num_resp_mult_pred_labeled_training_predictions_summary.csv does not exist -Test 162 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist -Test 163 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist +comparing Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! File master Test164_smlp_toy_num_resp_mult.txt does not exist File master Test164_smlp_toy_num_resp_mult_data_bounds.json does not exist File master Test164_smlp_toy_num_resp_mult_dt_sklearn_model_complete.pkl does not exist @@ -3945,21 +4463,112 @@ File master Test183_smlp_toy_num_resp_mult_test_predictions_summary.csv does not File master Test183_smlp_toy_num_resp_mult_trace.csv does not exist File master Test183_smlp_toy_num_resp_mult_training_prediction_precisions.csv does not exist File master Test183_smlp_toy_num_resp_mult_training_predictions_summary.csv does not exist -Test 184 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist -Test 185 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist -Test 186 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! File master Test187_smlp_toy_num_resp_mult.txt does not exist File master Test187_smlp_toy_num_resp_mult_data_bounds.json does not exist File master Test187_smlp_toy_num_resp_mult_dt_sklearn_model_complete.pkl does not exist @@ -4429,5 +5038,5 @@ Passed! master log file does not exist! Do you wish to copy the new log file to master? (yes/no|y/n): No new tests crashed (not in the masters) -Time: 35.39404908021291 minutes +Time: 28.481274580955507 minutes End of regression diff --git a/tests/smlp_regression/run_smlp_regression_expected_diff_report.log b/tests/smlp_regression/run_smlp_regression_expected_diff_report.log index 952a5d6a..125c558f 100644 --- a/tests/smlp_regression/run_smlp_regression_expected_diff_report.log +++ b/tests/smlp_regression/run_smlp_regression_expected_diff_report.log @@ -386,424 +386,12 @@ --- > smlp_logger - INFO - Seving model rerun configuration in file ./../models/test63_model_rerun_model_config.json =================== End of Test64_test63_model.txt diff report ================================ -=================== Diff report for: Test66_test65_model.txt ================================== -0a1,97 -> -> smlp_logger - INFO - Model exploration specification: -> {'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} -> -> smlp_logger - INFO - Executing run_smlp.py script: Start -> -> smlp_logger - INFO - Running SMLP in mode "verify": Start -> -> smlp_logger - INFO - Computed spec global constraint expressions: -> -> smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 -> -> smlp_logger - INFO - Global beta : None -> -> smlp_logger - INFO - Radii theta : {} -> -> smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} -> -> smlp_logger - INFO - Assertion asrt1: x0**2+y1>4.3 -> -> smlp_logger - INFO - Assertion asrt2: (y1+x2)/2<6 -> -> smlp_logger - INFO - PREPARE DATA FOR MODELING -> -> smlp_logger - INFO - LOAD TRAINED MODEL -> -> smlp_logger - INFO - Seving model rerun configuration in file ./../models/test65_model_rerun_model_config.json -> -> smlp_logger - INFO - Creating model exploration base components: Start -> -> smlp_logger - INFO - Parsing the SPEC: Start -> -> smlp_logger - INFO - Parsing the SPEC: End -> -> smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} -> -> smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} -> -> smlp_logger - INFO - Knob bounds (eta): {} -> -> smlp_logger - INFO - Knob grids (eta): {} -> -> smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) -> -> smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) -> -> smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) -> -> smlp_logger - INFO - Beta global constraints: true -> -> smlp_logger - INFO - Eta ranges constraints: true -> -> smlp_logger - INFO - Eta grid constraints: true -> -> smlp_logger - INFO - Eta global constraints: true -> -> smlp_logger - INFO - Eta combined constraints: true -> -> smlp_logger - INFO - Creating model exploration base components: End -> -> smlp_logger - INFO - Input and knob interface constraints are consistent -> -> smlp_logger - INFO - Building model terms: Start -> -> smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} -> -> smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} -> -> smlp_logger - INFO - Building model terms: End -> -> smlp_logger - INFO - Model interface constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying assertion asrt1 <-> x0**2+y1>4.3 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt1 -> -> smlp_logger - INFO - Completed with result: PASS -> -> smlp_logger - INFO - Verifying assertion asrt2 <-> (y1+x2)/2<6 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt2 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Running SMLP in mode "verify": End -> -> smlp_logger - INFO - Executing run_smlp.py script: End -=================== End of Test66_test65_model.txt diff report ================================ -=================== Diff report for: Test66_test65_model_verify_results.json ================================== -diff: /app/smlp/regr_smlp/code/Test66_test65_model_verify_results.json: No such file or directory -=================== End of Test66_test65_model_verify_results.json diff report ================================ -=================== Diff report for: Test68_test67_model.txt ================================== -0a1,97 -> -> smlp_logger - INFO - Model exploration specification: -> {'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} -> -> smlp_logger - INFO - Executing run_smlp.py script: Start -> -> smlp_logger - INFO - Running SMLP in mode "verify": Start -> -> smlp_logger - INFO - Computed spec global constraint expressions: -> -> smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 -> -> smlp_logger - INFO - Global beta : None -> -> smlp_logger - INFO - Radii theta : {} -> -> smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} -> -> smlp_logger - INFO - Assertion asrt1: x0**2+y1>4.3 -> -> smlp_logger - INFO - Assertion asrt2: (y1+x2)/2<6 -> -> smlp_logger - INFO - PREPARE DATA FOR MODELING -> -> smlp_logger - INFO - LOAD TRAINED MODEL -> -> smlp_logger - INFO - Seving model rerun configuration in file ./../models/test67_model_rerun_model_config.json -> -> smlp_logger - INFO - Creating model exploration base components: Start -> -> smlp_logger - INFO - Parsing the SPEC: Start -> -> smlp_logger - INFO - Parsing the SPEC: End -> -> smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} -> -> smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} -> -> smlp_logger - INFO - Knob bounds (eta): {} -> -> smlp_logger - INFO - Knob grids (eta): {} -> -> smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) -> -> smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) -> -> smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) -> -> smlp_logger - INFO - Beta global constraints: true -> -> smlp_logger - INFO - Eta ranges constraints: true -> -> smlp_logger - INFO - Eta grid constraints: true -> -> smlp_logger - INFO - Eta global constraints: true -> -> smlp_logger - INFO - Eta combined constraints: true -> -> smlp_logger - INFO - Creating model exploration base components: End -> -> smlp_logger - INFO - Input and knob interface constraints are consistent -> -> smlp_logger - INFO - Building model terms: Start -> -> smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 7, 'ite': 3, 'and': 3, 'prop': 6, 'const': 24, 'sub': 6, 'var': 6} -> -> smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 4, 'ite': 2, 'and': 1, 'prop': 3, 'const': 14, 'sub': 3, 'var': 3} -> -> smlp_logger - INFO - Building model terms: End -> -> smlp_logger - INFO - Model interface constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying assertion asrt1 <-> x0**2+y1>4.3 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt1 -> -> smlp_logger - INFO - Completed with result: PASS -> -> smlp_logger - INFO - Verifying assertion asrt2 <-> (y1+x2)/2<6 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt2 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Running SMLP in mode "verify": End -> -> smlp_logger - INFO - Executing run_smlp.py script: End -=================== End of Test68_test67_model.txt diff report ================================ -=================== Diff report for: Test68_test67_model_verify_results.json ================================== -diff: /app/smlp/regr_smlp/code/Test68_test67_model_verify_results.json: No such file or directory -=================== End of Test68_test67_model_verify_results.json diff report ================================ =================== Diff report for: Test70_test69_model.txt ================================== 25c25 < smlp_logger - INFO - Seving model rerun configuration in file ../models/test69_model_rerun_model_config.json --- > smlp_logger - INFO - Seving model rerun configuration in file ./../models/test69_model_rerun_model_config.json =================== End of Test70_test69_model.txt diff report ================================ -=================== Diff report for: Test72_test71_model.txt ================================== -0a1,84 -> -> smlp_logger - INFO - Model exploration specification: -> {'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} -> -> smlp_logger - INFO - Executing run_smlp.py script: Start -> -> smlp_logger - INFO - Running SMLP in mode "verify": Start -> -> smlp_logger - INFO - Computed spec global constraint expressions: -> -> smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 -> -> smlp_logger - INFO - Global beta : None -> -> smlp_logger - INFO - Radii theta : {} -> -> smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} -> -> smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 -> -> smlp_logger - INFO - PREPARE DATA FOR MODELING -> -> smlp_logger - INFO - LOAD TRAINED MODEL -> -> smlp_logger - INFO - Seving model rerun configuration in file ./../models/test71_model_rerun_model_config.json -> -> smlp_logger - INFO - Creating model exploration base components: Start -> -> smlp_logger - INFO - Parsing the SPEC: Start -> -> smlp_logger - INFO - Parsing the SPEC: End -> -> smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} -> -> smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} -> -> smlp_logger - INFO - Knob bounds (eta): {} -> -> smlp_logger - INFO - Knob grids (eta): {} -> -> smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) -> -> smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) -> -> smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) -> -> smlp_logger - INFO - Beta global constraints: true -> -> smlp_logger - INFO - Eta ranges constraints: true -> -> smlp_logger - INFO - Eta grid constraints: true -> -> smlp_logger - INFO - Eta global constraints: true -> -> smlp_logger - INFO - Eta combined constraints: true -> -> smlp_logger - INFO - Creating model exploration base components: End -> -> smlp_logger - INFO - Input and knob interface constraints are consistent -> -> smlp_logger - INFO - Building model terms: Start -> -> smlp_logger - INFO - Model operator counts for y1: {'add': 256, 'mul': 472, 'ite': 39, 'prop': 39, 'const': 846, 'sub': 216, 'var': 216} -> -> smlp_logger - INFO - Model operator counts for y2: {'add': 256, 'mul': 472, 'ite': 39, 'prop': 39, 'const': 846, 'sub': 216, 'var': 216} -> -> smlp_logger - INFO - Building model terms: End -> -> smlp_logger - INFO - Model interface constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt1 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Running SMLP in mode "verify": End -> -> smlp_logger - INFO - Executing run_smlp.py script: End -=================== End of Test72_test71_model.txt diff report ================================ -=================== Diff report for: Test72_test71_model_verify_results.json ================================== -diff: /app/smlp/regr_smlp/code/Test72_test71_model_verify_results.json: No such file or directory -=================== End of Test72_test71_model_verify_results.json diff report ================================ -=================== Diff report for: Test77_test76_model.txt ================================== -0a1,110 -> -> smlp_logger - INFO - Model exploration specification: -> {'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} -> -> smlp_logger - INFO - Executing run_smlp.py script: Start -> -> smlp_logger - INFO - Running SMLP in mode "verify": Start -> -> smlp_logger - INFO - Computed spec global constraint expressions: -> -> smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 -> -> smlp_logger - INFO - Global beta : None -> -> smlp_logger - INFO - Radii theta : {} -> -> smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} -> -> smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 -> -> smlp_logger - INFO - Assertion asrt2: y1>=9 -> -> smlp_logger - INFO - Assertion asrt3: y2<0 -> -> smlp_logger - INFO - PREPARE DATA FOR MODELING -> -> smlp_logger - INFO - LOAD TRAINED MODEL -> -> smlp_logger - INFO - Seving model rerun configuration in file ./../models/test76_model_rerun_model_config.json -> -> smlp_logger - INFO - Creating model exploration base components: Start -> -> smlp_logger - INFO - Parsing the SPEC: Start -> -> smlp_logger - INFO - Parsing the SPEC: End -> -> smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} -> -> smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} -> -> smlp_logger - INFO - Knob bounds (eta): {} -> -> smlp_logger - INFO - Knob grids (eta): {} -> -> smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) -> -> smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) -> -> smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) -> -> smlp_logger - INFO - Beta global constraints: true -> -> smlp_logger - INFO - Eta ranges constraints: true -> -> smlp_logger - INFO - Eta grid constraints: true -> -> smlp_logger - INFO - Eta global constraints: true -> -> smlp_logger - INFO - Eta combined constraints: true -> -> smlp_logger - INFO - Creating model exploration base components: End -> -> smlp_logger - INFO - Input and knob interface constraints are consistent -> -> smlp_logger - INFO - Building model terms: Start -> -> smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 21, 'ite': 6, 'and': 14, 'prop': 20, 'const': 69, 'sub': 20, 'var': 20} -> -> smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 21, 'ite': 6, 'and': 14, 'prop': 20, 'const': 69, 'sub': 20, 'var': 20} -> -> smlp_logger - INFO - Building model terms: End -> -> smlp_logger - INFO - Model interface constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 -> -> smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt2 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 -> -> smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Running SMLP in mode "verify": End -> -> smlp_logger - INFO - Executing run_smlp.py script: End -=================== End of Test77_test76_model.txt diff report ================================ -=================== Diff report for: Test77_test76_model_verify_results.json ================================== -diff: /app/smlp/regr_smlp/code/Test77_test76_model_verify_results.json: No such file or directory -=================== End of Test77_test76_model_verify_results.json diff report ================================ =================== Diff report for: Test97_smlp_toy_num_resp_mult.txt ================================== 252c252 < smlp_logger - INFO - Model operator counts for y2: {'add': 100, 'mul': 715, 'const': 2547, 'ite': 305, 'and': 408, 'prop': 713, 'sub': 713, 'var': 713} @@ -817,7 +405,7 @@ diff: /app/smlp/regr_smlp/code/Test77_test76_model_verify_results.json: No such > smlp_logger - INFO - Seving model rerun configuration in file ./../models/test101_model_rerun_model_config.json =================== End of Test102_test101_model.txt diff report ================================ =================== Diff report for: test110_model_poly_sklearn_formula.txt ================================== -diff: /app/smlp/regr_smlp/code/test110_model_poly_sklearn_formula.txt: No such file or directory +diff: /home/testuser/smlp/regr_smlp/code/test110_model_poly_sklearn_formula.txt: No such file or directory =================== End of test110_model_poly_sklearn_formula.txt diff report ================================ =================== Diff report for: Test111_test110_model_smlp_toy_basic_pred_unlabeled.txt ================================== 79c79 From 45ac152ad6852f97bd05e04a226a5e972a1666cf Mon Sep 17 00:00:00 2001 From: Dmitry Messerman Date: Tue, 2 Jun 2026 20:11:16 +0300 Subject: [PATCH 20/20] Updated expected results for virtual environment --- .../run_smlp_regression_venv_expected.log | 1823 +++++++++++------ ...p_regression_venv_expected_diff_report.log | 414 +--- 2 files changed, 1217 insertions(+), 1020 deletions(-) diff --git a/tests/smlp_regression/run_smlp_regression_venv_expected.log b/tests/smlp_regression/run_smlp_regression_venv_expected.log index ce736b01..0779c92b 100644 --- a/tests/smlp_regression/run_smlp_regression_venv_expected.log +++ b/tests/smlp_regression/run_smlp_regression_venv_expected.log @@ -7,822 +7,915 @@ Initiating 4 worker... Initiating 5 worker... Initiating 6 worker... Running test 7 test type: prediction, description: basic rf_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test7 -mode predict -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test7 -mode predict -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" Running test 11 test type: prediction, description: basic poly_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test11 -mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test11 -mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 16 test type: prediction, description: basic nn_keras prediction test from saved model on new data with numeric labels and two responses -../../src/run_smlp.py -model_name "../models/Test8_smlp_toy_num_resp_mult" -out_dir ./ -pref Test16 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 18 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test18 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test19_model -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 25 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test25 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test26_model -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 26 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels +smlp -model_name "../models/test26_model" -out_dir ./ -pref Test26 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 36 test type: doe, description: doe test with four levels with sukharev_grid -../../src/run_smlp.py -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test36 -mode doe -doe_algo sukharev_grid -doe_samples 125 -log_time f +Running test 32 test type: unknown, description: test reusing saved model by using configuration file +smlp -model_name "../models/test20_model" -out_dir ./ -pref Test32 -config ../models/test20_model_rerun_model_config.json -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 44 test type: doe, description: doe test with four levels with uniform_random_matrix -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test44 -mode doe -doe_algo uniform_random_matrix -doe_samples 20 -log_time f +Running test 37 test type: doe, description: doe test with four levels with box_behnken +smlp -doe_spec "../grids/doe_three_levels_real_nan.csv" -out_dir ./ -pref Test37 -mode doe -doe_algo box_behnken -log_time f -Running test 52 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test52 -mode discretize -resp "PF,PF1" -discr_algo jenks -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 48 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test48 -mode discretize -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +Running test 55 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test55 -mode discretize -resp "PF,PF1" -discr_algo ranks -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass spec_fn smlp_toy_num_resp_mult_y1_verify.spec specs_path ../specs Running test 63 test type: verify, description: basic dt_sklearn assertion verification test on data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test63 -mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test63_model -spec ../specs/smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x/2+y1>4.3;(y1+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test63 -mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test63_model -spec ../specs/smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x/2+y1>4.3;(y1+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 72 test type: verify, description: nn_keras verification test with re-using saved model_per_response trained model -../../src/run_smlp.py -model_name "../models/test71_model" -out_dir ./ -pref Test72 -mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 67 test type: verify, description: basic dt_sklearn assertion verification test on data with numeric labels +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test67 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -model_per_response t -save_model t -use_model f -model_name test67_model -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 73 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test73 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test73_model -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult_free_inps.spec specs_path ../specs -Running test 83 test type: optimize, description: basic dt_sklearn multi objective pareto optimization test with numeric labels and integer grid as domain and with scaling objectives -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test83 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -beta "y1>7 and y2>6" -objv_names obj1,objv2,objv3 -objv_exprs "(y1+y2)/2;y1/2-y2;y2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 82 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test82 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1,objv2,objv3 -objv_exprs "(y1+y2)/2;y1;y2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult_verify_vacuous.spec +spec_fn smlp_toy_num_resp_mult_query_vacuous.spec specs_path ../specs -Running test 92 test type: verify, description: test to detect contradictory constraints in verification mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test92 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_verify_vacuous.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 91 test type: query, description: test to detect contradictory constraints in optimization mode due to contradictory alpha global and alpha bounds constraints on FMAX_xyx +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test91 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs Running test 99 test type: optimize, description: testing that the response and feature names can be taken from spec file in model exploration modes when the responses and/or features are not specified in the command line -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test99 -mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test99 -mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_certify_witness.spec specs_path ../specs Running test 103 test type: certify, description: -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test103 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test103_model -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_certify_witness.spec -quer_names valid_candidate,grid_conflict,range_conflict -quer_exprs "True;True;True" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test103 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test103_model -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_certify_witness.spec -quer_names valid_candidate,grid_conflict,range_conflict -quer_exprs "True;True;True" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_cannot_synthesize.spec specs_path ../specs Running test 109 test type: synthesize, description: basic test for mode synthesize where synthesis fails -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test109 -mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_cannot_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -spec_fn smlp_toy_system_stable_constant_synth_fail.spec -specs_path ../specs -Running test 122 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test122 -mode optimize -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -spec_fn smlp_toy_system_stable_verify.spec -specs_path ../specs -Running test 140 test type: verify, description: verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stabilityRunning test 3 test type: prediction, description: basic poly_sklearn prediction test on labeled and new data with numeric response in training/test data only -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test3 -mode predict -resp y1 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_unlabeled.csv" +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test109 -mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_cannot_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 3 test type: prediction, description: basic poly_sklearn prediction test on labeled and new data with numeric response in training/test data only +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test3 -mode predict -resp y1 -feat x,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_unlabeled.csv" Running test 10 test type: prediction, description: basic et_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test10 -mode predict -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 15 -et_sklearn_bootstrap f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test10 -mode predict -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 15 -et_sklearn_bootstrap f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" Running test 17 test type: prediction, description: basic poly_sklearn prediction test from saved model on new data with numeric labels and two responses -../../src/run_smlp.py -model_name "../models/Test11_smlp_toy_num_resp_mult" -out_dir ./ -pref Test17 -mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +smlp -model_name "../models/Test11_smlp_toy_num_resp_mult" -out_dir ./ -pref Test17 -mode predict -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 24 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels -../../src/run_smlp.py -model_name "../models/test24_model" -out_dir ./ -pref Test24 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 23 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test23 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test24_model -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 30 test type: subgroups, description: basic test for subgroup discovery for numric responses -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test30 -mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -feat x,p1,p2 -plots t -seed 10 -log_time f +Running test 31 test type: subgroups, description: testing resp2b in subgroup discovery mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test31 -mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -resp2b "y1<6;y2>6" -feat x,p1,p2 -plots t -seed 10 -log_time f -save_config t -Running test 37 test type: doe, description: doe test with four levels with box_behnken -../../src/run_smlp.py -doe_spec "../grids/doe_three_levels_real_nan.csv" -out_dir ./ -pref Test37 -mode doe -doe_algo box_behnken -log_time f +Running test 40 test type: doe, description: doe test with four levels with latin_hypercube_space_filling +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test40 -mode doe -doe_algo latin_hypercube_sf -doe_samples 20 -log_time f -Running test 45 test type: doe, description: doe test with four levels with fractional_factorial -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels_real.csv" -out_dir ./ -pref Test45 -mode doe -doe_algo fractional_factorial -doe_resolution 5 -log_time f +Running test 44 test type: doe, description: doe test with four levels with uniform_random_matrix +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test44 -mode doe -doe_algo uniform_random_matrix -doe_samples 20 -log_time f -Running test 55 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test55 -mode discretize -resp "PF,PF1" -discr_algo ranks -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 51 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test51 -mode discretize -resp "PF,PF1" -discr_algo jenks -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 69 test type: verify, description: nn_keras verification test with model_per_response training -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test69 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model t -use_model f -model_name test69_model -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 59 test type: verify, description: basic nn_keras assertion verification test for functional nn_keras model +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test59 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat + +spec_fn smlp_toy_num_resp_mult_y2_verify.spec +specs_path ../specs +Running test 70 test type: verify, description: nn_keras verification test with re-using saved model_per_response trained model +smlp -model_name "../models/test69_model" -out_dir ./ -pref Test70 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat + +spec_fn smlp_toy_num_resp_mult_free_inps.spec +specs_path ../specs +Running test 81 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test81 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs Running test 88 test type: optimize, description: basic dt_sklearn multi objective pareto optimization test with beta and objectives specified in spec file -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test88 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test88 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs Running test 94 test type: optsyn, description: basic test for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test94 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test94 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_witness.spec specs_path ../specs Running test 102 test type: certify, description: basic test in certify mode to test stability (theta) and guard (eta) constraint generation -../../src/run_smlp.py -model_name "../models/test101_model" -out_dir ./ -pref Test102 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -model_name "../models/test101_model" -out_dir ./ -pref Test102 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_unsat_eta_verify.spec +spec_fn smlp_toy_num_resp_mult_stable_verify.spec specs_path ../specs -Running test 106 test type: verify, description: test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test106 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_unsat_eta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 105 test type: verify, description: basic dt_sklearn assertion verfication test with numeric labels and integer grid as domain +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test105 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_stable_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_basic.spec -specs_path ../specs -Running test 113 test type: optimize, description: smlp toy basic test for mode optimize from SMLP manual -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test113 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model t -model_name test113_model -save_model_config t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec ../specs/smlp_toy_basic.spec +Running test 111 test type: unknown, description: smlp toy basic test to rerun saved model using the model rerun config file saved during model training +smlp -model_name "../models/test110_model" -out_dir ./ -pref Test111 -config ../models/test110_model_rerun_model_config.json -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" spec_fn smlp_toy_system_stable_constant_verify.spec specs_path ../specs -Running test 118 test type: verify, description: verification test with knobs only where assertion is valid without stability and fails with stability -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test118 -mode verify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -spec_fn smlp_toy_system_stable_verify.spec -specs_path ../specs -Running test 126 test type: verify, description: verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test126 -mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 118 test type: verify, description: verification test with knobs only where assertion is valid without stability and fails with stabilityRunning test 6 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test6 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_optsyn.spec -specs_pathRunning test 5 test type: prediction, description: basic dt_caret prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test5 -mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model t -use_model f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 9 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test9 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -model_name test20_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -save_config t -save_model_config t -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 18 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test18 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test19_model -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 15 test type: prediction, description: basic dt_caret prediction test from saved model on new data with numeric labels +smlp -model_name "../models/Test5_smlp_toy_num_resp_mult" -out_dir ./ -pref Test15 -mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 26 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels -../../src/run_smlp.py -model_name "../models/test26_model" -out_dir ./ -pref Test26 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 22 test type: prediction, description: test for illegal symbols in column names +smlp -model_name "../models/test22_model" -out_dir ./ -pref Test22 -mode predict -resp "PF ,|PF |" -model poly_sklearn -save_model f -use_model t -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_metasymbol_mult_reg_pred_labeled.csv" Running test 33 test type: unknown, description: testing -config option with subgroups mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test33 -config ../models/Test31_smlp_toy_num_resp_mult_args_config.json +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test33 -config ../models/Test31_smlp_toy_num_resp_mult_args_config.json Running test 41 test type: doe, description: doe test with four levels with random_k_means -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test41 -mode doe -doe_algo random_k_means -doe_samples 20 -log_time f +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test41 -mode doe -doe_algo random_k_means -doe_samples 20 -log_time f Running test 49 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test49 -mode discretize -resp "PF,PF1" -discr_algo quantile -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test49 -mode discretize -resp "PF,PF1" -discr_algo quantile -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 58 test type: optimize, description: basic dt_sklearn optimization test with numeric labels and integer grid as domain and without scaling objectives -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test58 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs "y1;y2" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 57 test type: verify, description: basic dt_sklearn assertion verfication test with numeric labels and integer grid as domain +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test57 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x0<=5 and y1<=10;-2*y2-1<10-x2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_y2_verify.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 70 test type: verify, description: nn_keras verification test with re-using saved model_per_response trained model -../../src/run_smlp.py -model_name "../models/test69_model" -out_dir ./ -pref Test70 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 65 test type: verify, description: basic dt_sklearn assertion verification test on data with numeric labels +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test65 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test65_model -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 85 test type: optimize, description: tests alpha and eta constraints specified in command line in optimization mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test85 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs "(y1+y2)/2;y1" -alpha "p2<5 and x==10 and x<12" -eta "p1==4" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 69 test type: verify, description: nn_keras verification test with model_per_response training +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test69 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model t -use_model f -model_name test69_model -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_mult.spec specs_path ../specs -Running test 93 test type: optsyn, description: basic test for mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test93 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 80 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test80 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_witness.spec +spec_fn smlp_toy_num_resp_mult.spec specs_path ../specs -Running test 101 test type: certify, description: basic test in certify mode to test stability (theta) and guard (eta) constraint generation -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test101 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test101_model -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 86 test type: optimize, description: tests alpha +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test86 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs "(y1+y2)/2;y1" -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+p2)/2<6;y1>=9;y2<0" -alpha "p2<5 and x==10 and x<12" -eta "p1==4" -epsilon 0.05 -delta_rel 0.01 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_stable_verify.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 105 test type: verify, description: basic dt_sklearn assertion verfication test with numeric labels and integer grid as domain -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test105 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_stable_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -Running test 111 test type: unknown, description: smlp toy basic test to rerun saved model using the model rerun config file saved during model training -../../src/run_smlp.py -model_name "../models/test110_model" -out_dir ./ -pref Test111 -config ../models/test110_model_rerun_model_config.json -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" +Running test 95 test type: optsyn, description: basic test for dt_caret in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test95 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_certify.spec +spec_fn smlp_toy_num_resp_mult_beta_verify.spec specs_path ../specs -Running test 117 test type: certify, description: certification test with knobs only where assertion is valid without stability and fails with stability -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test117 -mode certify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 107 test type: verify, description: test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test107 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_beta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +spec_fn smlp_toy_basic.spec specs_path ../specs -Running test 123 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test123 -mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 113 test type: optimize, description: smlp toy basic test for mode optimize from SMLP manual +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test113 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model t -model_name test113_model -save_model_config t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec ../specs/smlp_toy_basic.spec -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +spec_fn smlp_toy_system_stable_constant_synth_fail.spec specs_path ../specs -Running test 145 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed -../../src/run_smlp.py -out_dir ./ -pref Test145 -mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 6 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test6 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 9 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test9 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -model_name test20_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -save_config t -save_model_config t -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 120 test type: synthesize, description: synthesis test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test120 -mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 4 test type: prediction, description: basic nn_keras prediction test on labeled and new data with numeric labels and one response +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test4 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nn_keras_weights_precision 2 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 15 test type: prediction, description: basic dt_caret prediction test from saved model on new data with numeric labels -../../src/run_smlp.py -model_name "../models/Test5_smlp_toy_num_resp_mult" -out_dir ./ -pref Test15 -mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 13 test type: train, description: EV-SI real life nn_keras prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test13 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 23 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test23 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test24_model -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 25 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels and saving model using name specified through model_name option - adapts Test6 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test25 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model t -use_model f -model_name test26_model -mrmr_pred 2 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 29 test type: subgroups, description: basic test for subgroup discovery for pass-fail responses -../../src/run_smlp.py -data "../data/smlp_toy_cls_metasymbol_colnames_mult.csv" -out_dir ./ -pref Test29 -mode subgroups -psg_dim 3 -psg_top 10 -resp "PF 1,PF#" -plots t -seed 10 -log_time f +Running test 34 test type: doe, description: doe test with four levels with full_factorial method +smlp -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test34 -mode doe -doe_algo full_factorial -log_time f -Running test 38 test type: doe, description: doe test with four levels with box_wilson -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test38 -mode doe -doe_algo box_wilson -doe_cc_face ccc -doe_cc_alpha r -doe_cc_center 2,3 -log_time f +Running test 42 test type: doe, description: doe test with four levels with maximin_reconstruction +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test42 -mode doe -doe_algo maximin_reconstruction -doe_samples 20 -log_time f -Running test 46 test type: prediction, description: tests options -pos_val and -neg_val -../../src/run_smlp.py -data "../data/smlp_toy_pf_mult.csv" -out_dir ./ -pref Test46 -mode predict -resp "PF,PF1" -model poly_sklearn -save_model t -save_model_config f -use_model f -model_name test47_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass -new_dat "../data/smlp_toy_pf_mult.csv" +Running test 50 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test50 -mode discretize -resp "PF,PF1" -discr_algo kmeans -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -Running test 56 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test56 -mode discretize -resp "PF,PF1" -discr_algo ranks -discr_bins 6 -discr_labels f -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +spec_fn smlp_toy_num_resp_mult.spec +specs_path ../specs +Running test 58 test type: optimize, description: basic dt_sklearn optimization test with numeric labels and integer grid as domain and without scaling objectives +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test58 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs "y1;y2" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 68 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response -../../src/run_smlp.py -model_name "../models/test67_model" -out_dir ./ -pref Test68 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -model_per_response t -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 66 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response +smlp -model_name "../models/test65_model" -out_dir ./ -pref Test66 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 80 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test80 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 72 test type: verify, description: nn_keras verification test with re-using saved model_per_response trained model +smlp -model_name "../models/test71_model" -out_dir ./ -pref Test72 -mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -save_model f -use_model t -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1 -asrt_exprs "(y2**3+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult_alpha_asrt_verify.spec +Running test 77 test type: unknown, description: verification test run using model_rerun config covering the case when mrmr selcts only a subset of features specified through the command line or config file +smlp -model_name "../models/test76_model" -out_dir ./ -pref Test77 -config ../models/test76_model_rerun_model_config.json + +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 87 test type: verify, description: tests global alpha constraints and assertions specified in spec file -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test87 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_alpha_asrt_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 84 test type: verify, description: tests global alpha constraints specified using option -alpha on inputs +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test84 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -alpha "x2==7.0 and x0==0 and x1==2.5" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 96 test type: optsyn, description: basic test for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test96 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 93 test type: optsyn, description: basic test for mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test93 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 112 test type: prediction, description: smlp toy basic test from SMLP manual -../../src/run_smlp.py -model_name "../models/test110_model" -out_dir ./ -pref Test112 -mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -use_model t -save_model f -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" +spec_fn smlp_toy_num_resp_mult_witness.spec +specs_path ../specs +Running test 101 test type: certify, description: basic test in certify mode to test stability (theta) and guard (eta) constraint generation +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test101 -mode certify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test101_model -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_witness.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_query.spec +spec_fn smlp_toy_num_resp_mult_unsat_eta_verify.spec specs_path ../specs -Running test 119 test type: query, description: query test with knobs only where query is satisfiable without stability and fails with stability -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test119 -mode query -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 106 test type: verify, description: test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test106 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_unsat_eta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +spec_fn smlp_toy_basic.spec specs_path ../specs -Running test 125 test type: optsyn, description: optimized synthesis test with constant knob and no inputs where synthesis is feasible and optimization is performed -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test125 -mode optsyn -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 114 test type: optimize, description: smlp toy basic test for mode optimize from SMLP manual without specifying resp and feat in command line +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test114 -mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model f -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec ../specs/smlp_toy_basic.spec -spec_fn smlp_toy_system.spec +spec_fn smlp_toy_system_stable_constant_synth_feasible.spec specs_path ../specs -Running test 146 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed -../../src/run_smlp.py -out_dir ./ -pref Test146 -mode optimize -pareto t -opt_strategy lazy -model poly_sklearn -resp y1,y2 -feat p1,p2,x1,x2 -save_model t -use_model f -mrmr_pred 0 -model_per_response t -split 1 -spec ../specs/smlp_toy_system.spec -doe_spec ../grids/explore_doe_two_levels.csv -doe_algo latin_hypercube -epsilon 0.99999999 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 121 test type: synthesize, description: synthesis test with constant knob and no inputs where synthesis is feasible +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test121 -mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 152 test type: prediction, description: tests the huber loss function Huber and sample weights -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test152 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss huber -sw_coef 8 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 4 test type: prediction, description: basic nn_keras prediction test on labeled and new data with numeric labels and one response -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test4 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nn_keras_weights_precision 2 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fnRunning test 2 test type: prediction, description: basic rf_sklearn prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test2 -mode predict -resp y1 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 13 test type: train, description: EV-SI real life nn_keras prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test13 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 12 test type: train, description: EV-SI real life dt_sklearn predict test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test12 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 22 test type: prediction, description: test for illegal symbols in column names -../../src/run_smlp.py -model_name "../models/test22_model" -out_dir ./ -pref Test22 -mode predict -resp "PF ,|PF |" -model poly_sklearn -save_model f -use_model t -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_metasymbol_mult_reg_pred_labeled.csv" +Running test 20 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels +smlp -model_name "../models/test20_model" -out_dir ./ -pref Test20 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 32 test type: unknown, description: test reusing saved model by using configuration file -../../src/run_smlp.py -model_name "../models/test20_model" -out_dir ./ -pref Test32 -config ../models/test20_model_rerun_model_config.json -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 28 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and functional API +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test28 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 39 test type: doe, description: doe test with four levels with latin_hypercube -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test39 -mode doe -doe_algo latin_hypercube -doe_prob_distr Exponential -doe_samples 30 -log_time f +Running test 38 test type: doe, description: doe test with four levels with box_wilson +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test38 -mode doe -doe_algo box_wilson -doe_cc_face ccc -doe_cc_alpha r -doe_cc_center 2,3 -log_time f -Running test 47 test type: prediction, description: tests options -pos_val and -neg_val when re-using saved model -../../src/run_smlp.py -model_name "../models/test47_model" -out_dir ./ -pref Test47 -mode predict -resp "PF,PF1" -model poly_sklearn -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass -new_dat "../data/smlp_toy_pf_mult.csv" +Running test 46 test type: prediction, description: tests options -pos_val and -neg_val +smlp -data "../data/smlp_toy_pf_mult.csv" -out_dir ./ -pref Test46 -mode predict -resp "PF,PF1" -model poly_sklearn -save_model t -save_model_config f -use_model f -model_name test47_model -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass -new_dat "../data/smlp_toy_pf_mult.csv" Running test 54 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test54 -mode discretize -resp "PF,PF1" -discr_algo ordinals -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test54 -mode discretize -resp "PF,PF1" -discr_algo ordinals -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass spec_fn smlp_toy_num_resp_mult_y1_verify.spec specs_path ../specs Running test 64 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response -../../src/run_smlp.py -model_name "../models/test63_model" -out_dir ./ -pref Test64 -mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x/2+y1>4.3;(y1+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -Running test 77 test type: unknown, description: verification test run using model_rerun config covering the case when mrmr selcts only a subset of features specified through the command line or config file -../../src/run_smlp.py -model_name "../models/test76_model" -out_dir ./ -pref Test77 -config ../models/test76_model_rerun_model_config.json +smlp -model_name "../models/test63_model" -out_dir ./ -pref Test64 -mode verify -resp y1 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_mult_y1_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x/2+y1>4.3;(y1+p2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 86 test type: optimize, description: tests alpha -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test86 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs "(y1+y2)/2;y1" -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+p2)/2<6;y1>=9;y2<0" -alpha "p2<5 and x==10 and x<12" -eta "p1==4" -epsilon 0.05 -delta_rel 0.01 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 68 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response +smlp -model_name "../models/test67_model" -out_dir ./ -pref Test68 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -model_per_response t -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 95 test type: optsyn, description: basic test for dt_caret in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test95 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 74 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model. with separate model for each response +smlp -model_name "../models/test73_model" -out_dir ./ -pref Test74 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_beta_verify.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 107 test type: verify, description: test for verification mode to check that eta contraints are not contradictory and as otherwise verification problem is not well defined -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test107 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_beta_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 78 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test78 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test78_model -mrmr_pred 1 -model_per_response f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "y1==9;y2>0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_basic.spec +spec_fn smlp_toy_num_resp_mult_alpha_asrt_verify.spec specs_path ../specs -Running test 114 test type: optimize, description: smlp toy basic test for mode optimize from SMLP manual without specifying resp and feat in command line -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test114 -mode optimize -pareto t -opt_strategy lazy -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 0 -epsilon 0.05 -delta_rel 0.01 -save_model f -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec ../specs/smlp_toy_basic.spec +Running test 87 test type: verify, description: tests global alpha constraints and assertions specified in spec file +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test87 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_alpha_asrt_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_fail.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 120 test type: synthesize, description: synthesis test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test120 -mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 96 test type: optsyn, description: basic test for rf_sklearn in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test96 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +Running test 112 test type: prediction, description: smlp toy basic test from SMLP manual +smlp -model_name "../models/test110_model" -out_dir ./ -pref Test112 -mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -use_model t -save_model f -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" -spec_fn smlp_toy_witness_certify.spec +spec_fn smlp_toy_system_stable_constant_query.spec specs_path ../specs -Running test 128 test type: certify, description: Basic regression test in certify mode covering all four possible outcomes when certifying a witness for a query: the witness is stable -../../src/run_smlp.py -data "../data/smlp_toy_ctg_num_resp.csv" -out_dir ./ -pref Test128 -mode certify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model f -model_per_response f -spec ../specs/smlp_toy_witness_certify.spec -quer_names query_stable_witness,query_grid_conflict,query_unstable_witness,query_infeasible_witness,query_poly_intercept_sensitive -quer_exprs "y2<=90;y1>=9;y1>=(-13);y1>9;y1>=(-10)" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 119 test type: query, description: query test with knobs only where query is satisfiable without stability and fails with stability +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test119 -mode query -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 149 test type: prediction, description: tests the mae loss function MeanAbsoluteError and sample weoghts -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test149 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mae -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_system_stable_verify.spec +specs_path ../specs +Running test 126 test type: verify, description: verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test126 -mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_y2_verify.specRunning test 8 test type: prediction, description: basic nn_keras prediction test on labeled and new data with numeric labels and two responses -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test8 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -nn_keras_epochs 20 -nn_keras_seq_api f -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_num_resp_mult.spec +specs_path ../specs +Running test 141 test type: optimize, description: basic test for compress_rules option for dt_sklearn in optimization mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test141 -mode optimize -opt_strategy lazy -pareto f -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -spec ../specs/smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs "y1;y2" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 8 test type: prediction, description: basic nn_keras prediction test on labeled and new data with numeric labels and two responses +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test8 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -nn_keras_epochs 20 -nn_keras_seq_api f -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" Running test 14 test type: train, description: EV-SI real life poly_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test14 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test14 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f Running test 21 test type: prediction, description: test for illegal symbols in column names -../../src/run_smlp.py -data "../data/smlp_toy_num_metasymbol_mult_reg.csv" -out_dir ./ -pref Test21 -mode predict -resp "PF ,|PF |" -model poly_sklearn -save_model t -use_model f -model_name test22_model -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_metasymbol_mult_reg_pred_labeled.csv" +smlp -data "../data/smlp_toy_num_metasymbol_mult_reg.csv" -out_dir ./ -pref Test21 -mode predict -resp "PF ,|PF |" -model poly_sklearn -save_model t -use_model f -model_name test22_model -pred_plots t -resp_plots t -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_metasymbol_mult_reg_pred_labeled.csv" -Running test 31 test type: subgroups, description: testing resp2b in subgroup discovery mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test31 -mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -resp2b "y1<6;y2>6" -feat x,p1,p2 -plots t -seed 10 -log_time f -save_config t +Running test 29 test type: subgroups, description: basic test for subgroup discovery for pass-fail responses +smlp -data "../data/smlp_toy_cls_metasymbol_colnames_mult.csv" -out_dir ./ -pref Test29 -mode subgroups -psg_dim 3 -psg_top 10 -resp "PF 1,PF#" -plots t -seed 10 -log_time f -Running test 40 test type: doe, description: doe test with four levels with latin_hypercube_space_filling -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test40 -mode doe -doe_algo latin_hypercube_sf -doe_samples 20 -log_time f +Running test 35 test type: doe, description: doe test with four levels with plackett_burman +smlp -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test35 -mode doe -doe_algo plackett_burman -log_time f -Running test 48 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test48 -mode discretize -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 43 test type: doe, description: doe test with four levels with halton_sequence +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test43 -mode doe -doe_algo halton_sequence -doe_samples 20 -log_time f Running test 53 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test53 -mode discretize -resp "PF,PF1" -discr_algo ordinals -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test53 -mode discretize -resp "PF,PF1" -discr_algo ordinals -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 66 test type: verify, description: basic dt_sklearn assertion verification test on data with one numeric response -../../src/run_smlp.py -model_name "../models/test65_model" -out_dir ./ -pref Test66 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 61 test type: verify, description: tests verificaion mode for NN with nn_keras_seq_api f +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test61 -mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -nn_keras_epochs 100 -save_model_config f --spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "not(x25 and y1<=10);-2*y2-1<10-x2 and x2>5 and x2<8" -vacuity f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 79 test type: query, description: basic test in query mode to test stability (theta) and guard (eta) constraint generation -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test79 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 76 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test76 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -use_model f -model_name test76_model -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn_vacuous.spec +spec_fn smlp_toy_num_resp_mult.spec specs_path ../specs -Running test 90 test type: optsyn, description: test to detect contradictory constraints in optsyn mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test90 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 85 test type: optimize, description: tests alpha and eta constraints specified in command line in optimization mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test85 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -data_scaler min_max -objv_names obj1,objv2 -objv_exprs "(y1+y2)/2;y1" -alpha "p2<5 and x==10 and x<12" -eta "p1==4" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_mult_verify_vacuous.spec specs_path ../specs -Running test 98 test type: optsyn, description: basic test for et_caret in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test98 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 92 test type: verify, description: test to detect contradictory constraints in verification mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test92 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_verify_vacuous.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system.spec +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs -Running test 115 test type: certify, description: basic test in certify mode -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test115 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system.spec -quer_names query1,query2 -quer_exprs "y1>0;y2<=0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 100 test type: optimize, description: basic test for sat_threshold option enabing usage of objectve values in SAT assignments that prove optimization thresholds +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test100 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_fail.spec +spec_fn smlp_toy_num_resp_mult.spec specs_path ../specs -Running test 124 test type: optsyn, description: optimized synthesis test with constant knob and no inputs where synthesis is not feasible because while beta constraint is feasible the assertion is not feasible therefore optimization is not performed -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test124 -mode optsyn -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 104 test type: verify, description: assertion verfication test with wrong spec that does not assign a single value using a singleton grid or range with equal max and min +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test104 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult.spec +Running test 110 test type: prediction, description: smlp toy basic example for predict mode from SMLP user manual +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test110 -mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model t -model_name test110_model -save_model_config t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" + +spec_fn smlp_toy_system.spec specs_path ../specs -Running test 141 test type: optimize, description: basic test for compress_rules option for dt_sklearn in optimization mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test141 -mode optimize -opt_strategy lazy -pareto f -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -spec ../specs/smlp_toy_num_resp_mult.spec -objv_names objv_y1,objv_y2 -objv_exprs "y1;y2" -epsilon 0.01 -delta_rel 0.01 -data_scaler none -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 116 test type: certify, description: basic test in certify mode when system is specified and is used as the model; p2 rel-rad needs to be 0 or very close to it the witness to first query to be stable +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test116 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system.spec -quer_names query1,query2 -quer_exprs "y1>0;y2<=0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 148 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and sequential API -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test148 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_system_stable_certify.spec +specs_path ../specs +Running test 127 test type: certify, description: certification example with knobs only and fictitious inputs with values fixed through their ranges +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test127 -mode certify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_verify.spec +spec_fn smlp_toy_num_resp_mult_query.spec specs_path ../specs -Running test 157 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training; adapts test 155 by consdering multiple responses -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test157 -mode verify -resp y1,y2 -feat x,p1,p2 --model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse,logcosh +Running test 143 test type: query, description: basic test for compress_rules for et_sklearn in mode query +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test143 -mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f Running test 1 test type: train, description: basic dt_caret training and test on labeled data with single numeric response -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test1 -mode train -resp y1 -feat x,p1,p2 -model dt_caret -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test1 -mode train -resp y1 -feat x,p1,p2 -model dt_caret -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f -Running test 20 test type: prediction, description: basic dt_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -model_name "../models/test20_model" -out_dir ./ -pref Test20 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 19 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels +smlp -model_name "../models/test19_model" -out_dir ./ -pref Test19 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 28 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and functional API -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test28 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 27 test type: prediction, description: checks nn_keras prediction with nn_keras_seq_api t +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test27 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 34 test type: doe, description: doe test with four levels with full_factorial method -../../src/run_smlp.py -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test34 -mode doe -doe_algo full_factorial -log_time f +Running test 36 test type: doe, description: doe test with four levels with sukharev_grid +smlp -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test36 -mode doe -doe_algo sukharev_grid -doe_samples 125 -log_time f -Running test 42 test type: doe, description: doe test with four levels with maximin_reconstruction -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test42 -mode doe -doe_algo maximin_reconstruction -doe_samples 20 -log_time f +Running test 45 test type: doe, description: doe test with four levels with fractional_factorial +smlp -doe_spec "../grids/doe_two_levels_real.csv" -out_dir ./ -pref Test45 -mode doe -doe_algo fractional_factorial -doe_resolution 5 -log_time f -Running test 50 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test50 -mode discretize -resp "PF,PF1" -discr_algo kmeans -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 52 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test52 -mode discretize -resp "PF,PF1" -discr_algo jenks -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs Running test 60 test type: verify, description: basic nn_keras assertion verification test for functional nn_keras model -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test60 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test60 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult_free_inps.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 82 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test82 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1,objv2,objv3 -objv_exprs "(y1+y2)/2;y1;y2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 71 test type: verify, description: nn_keras verification test with model_per_response training +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test71 -mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -save_model t -use_model f -model_name test71_model -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1 -asrt_exprs "(y1**3+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult_query_vacuous.spec +spec_fn smlp_toy_num_resp_mult_free_inps.spec specs_path ../specs -Running test 91 test type: query, description: test to detect contradictory constraints in optimization mode due to contradictory alpha global and alpha bounds constraints on FMAX_xyx -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test91 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 83 test type: optimize, description: basic dt_sklearn multi objective pareto optimization test with numeric labels and integer grid as domain and with scaling objectives +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test83 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -beta "y1>7 and y2>6" -objv_names obj1,objv2,objv3 -objv_exprs "(y1+y2)/2;y1/2-y2;y2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +spec_fn smlp_toy_num_resp_mult_query.spec specs_path ../specs -Running test 100 test type: optimize, description: basic test for sat_threshold option enabing usage of objectve values in SAT assignments that prove optimization thresholds -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test100 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 89 test type: query, description: basic test in query mode to test stability (theta) and guard (eta) constraint generation +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test89 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult.spec +spec_fn smlp_toy_num_resp_mult_query.spec specs_path ../specs -Running test 104 test type: verify, description: assertion verfication test with wrong spec that does not assign a single value using a singleton grid or range with equal max and min -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test104 -mode verify -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "y1*2+x<=5 and y1<=10;-2*y2-1<10-p2" -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 97 test type: query, description: basic test for rf_sklearn in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test97 -mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_synthesize.spec specs_path ../specs Running test 108 test type: synthesize, description: basic test for dt_sklearn in model exploration mode synthesize where synthesis succeeds -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test108 -mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test108 -mode synthesize -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_synthesize.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +spec_fn smlp_toy_system_stable_constant_certify.spec specs_path ../specs -Running test 121 test type: synthesize, description: synthesis test with constant knob and no inputs where synthesis is feasible -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test121 -mode synthesize -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 117 test type: certify, description: certification test with knobs only where assertion is valid without stability and fails with stability +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test117 -mode certify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_configuration_verify.spec +spec_fn smlp_toy_system_stable_constant_synth_fail.spec specs_path ../specs -Running test 129 test type: verify, description: verification example with demonstrating all basic result scenarious for assertions -../../src/run_smlp.py -data "../data/smlp_toy_ctg_num_resp.csv" -out_dir ./ -pref Test129 -mode verify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model f -model_per_response f -spec ../specs/smlp_toy_configuration_verify.spec -asrt_names assert_stable_config,assert_grid_conflict,assert_unstable_config,assert_infeasible -asrt_exprs "y2<=90;y1>=9;y1>=(-10);y1>20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 124 test type: optsyn, description: optimized synthesis test with constant knob and no inputs where synthesis is not feasible because while beta constraint is feasible the assertion is not feasible therefore optimization is not performed +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test124 -mode optsyn -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 150 test type: prediction, description: tests the mape loss function MeanAbsolutePercentageError and sample weights -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test150 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +spec_fn smlp_toy_system_stable_verify.spec +specs_path ../specs +Running test 140 test type: verify, description: verification example with knobs only and fictitious inputs that have no effect where proparty is valid without stability and fails with stability +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test140 -mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_verify.spec -trace_prec 1 -trace_anonym t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 158 test type: prediction, description: tests the mape loss function and sample weights with model_per_response t -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test158 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -model_per_response t -sw_coef 8 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 2 test type: prediction, description: basic rf_sklearn prediction test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test2 -mode predict -resp y1 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 147 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and sequential API +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test147 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 5 test type: prediction, description: basic dt_caret prediction test on labeled and new data with numeric labels +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test5 -mode predict -resp y1 -feat x,p1,p2 -model dt_caret -save_model t -use_model f -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 12 test type: train, description: EV-SI real life dt_sklearn predict test on labeled and new data with numeric labels -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test12 -mode train -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 16 test type: prediction, description: basic nn_keras prediction test from saved model on new data with numeric labels and two responses +smlp -model_name "../models/Test8_smlp_toy_num_resp_mult" -out_dir ./ -pref Test16 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 19 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels -../../src/run_smlp.py -model_name "../models/test19_model" -out_dir ./ -pref Test19 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 24 test type: prediction, description: basic dt_sklearn prediction test using a model saved under a name specified through model_name option on new data with numeric labels +smlp -model_name "../models/test24_model" -out_dir ./ -pref Test24 -mode predict -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model t -model_per_response t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 27 test type: prediction, description: checks nn_keras prediction with nn_keras_seq_api t -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test27 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 30 test type: subgroups, description: basic test for subgroup discovery for numric responses +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test30 -mode subgroups -psg_dim 3 -psg_top 10 -resp y1,y2 -feat x,p1,p2 -plots t -seed 10 -log_time f -Running test 35 test type: doe, description: doe test with four levels with plackett_burman -../../src/run_smlp.py -doe_spec "../grids/doe_four_levels_real.csv" -out_dir ./ -pref Test35 -mode doe -doe_algo plackett_burman -log_time f +Running test 39 test type: doe, description: doe test with four levels with latin_hypercube +smlp -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test39 -mode doe -doe_algo latin_hypercube -doe_prob_distr Exponential -doe_samples 30 -log_time f -Running test 43 test type: doe, description: doe test with four levels with halton_sequence -../../src/run_smlp.py -doe_spec "../grids/doe_two_levels.csv" -out_dir ./ -pref Test43 -mode doe -doe_algo halton_sequence -doe_samples 20 -log_time f +Running test 47 test type: prediction, description: tests options -pos_val and -neg_val when re-using saved model +smlp -model_name "../models/test47_model" -out_dir ./ -pref Test47 -mode predict -resp "PF,PF1" -model poly_sklearn -save_model f -use_model t -data_scaler none -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -pos_val fail -neg_val pass -new_dat "../data/smlp_toy_pf_mult.csv" -Running test 51 test type: discretization, description: tests discretization options -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test51 -mode discretize -resp "PF,PF1" -discr_algo jenks -discr_bins 6 -discr_labels f -discr_type integer -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 56 test type: discretization, description: tests discretization options +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test56 -mode discretize -resp "PF,PF1" -discr_algo ranks -discr_bins 6 -discr_labels f -discr_type object -data_scaler none -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -spec_fn smlp_toy_num_resp_mult_y2_verify.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 59 test type: verify, description: basic nn_keras assertion verification test for functional nn_keras model -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test59 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 62 test type: verify, description: tests verificaion mode for NN with nn_keras_seq_api t +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test62 -mode verify -resp y1,y2 -feat x0,x1,x2 -model nn_keras -nnet_encoding nested -nn_keras_epochs 100 -nn_keras_seq_api t -save_model_config f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt_y1,asrt_y2 -asrt_expr "not(x25 and y1<=10);-2*y2-1<10-x2 and x2>5 and x2<8" -vacuity f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -spec_fn smlp_toy_num_resp_mult_free_inps.spec -specs_path ../specs -Running test 81 test type: optimize, description: basic dt_sklearn single objective optimization test with numeric labels and integer grid as domain and with scaling objectives -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test81 -mode optimize -pareto f -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_free_inps.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 75 test type: unknown, description: verification test run using model_rerun config covering the case when mrmr selcts only a subset of features specified through the command line or config file +smlp -model_name "../models/test73_model" -out_dir ./ -pref Test75 -config ../models/test73_model_rerun_model_config.json -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_query.spec +spec_fn smlp_toy_num_resp_mult.spec specs_path ../specs -Running test 89 test type: query, description: basic test in query mode to test stability (theta) and guard (eta) constraint generation -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test89 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 79 test type: query, description: basic test in query mode to test stability (theta) and guard (eta) constraint generation +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test79 -mode query -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult.spec -quer_names query1,query2,query3 -quer_exprs "(y2**3+p2)/2<6;y1>=9;y2<0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_query.spec +spec_fn smlp_toy_num_resp_mult_optsyn_vacuous.spec specs_path ../specs -Running test 97 test type: query, description: basic test for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test97 -mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 90 test type: optsyn, description: test to detect contradictory constraints in optsyn mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test90 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn_vacuous.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 110 test type: prediction, description: smlp toy basic example for predict mode from SMLP user manual -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test110 -mode predict -resp y1,y2 -feat x1,x2,p1,p2 -model poly_sklearn -save_model t -model_name test110_model -save_model_config t -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_basic_pred_unlabeled.csv" +spec_fn smlp_toy_num_resp_mult_optsyn.spec +specs_path ../specs +Running test 98 test type: optsyn, description: basic test for et_caret in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test98 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -save_model f -use_model f -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_system.spec specs_path ../specs -Running test 116 test type: certify, description: basic test in certify mode when system is specified and is used as the model; p2 rel-rad needs to be 0 or very close to it the witness to first query to be stable -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test116 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system.spec -quer_names query1,query2 -quer_exprs "y1>0;y2<=0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 115 test type: certify, description: basic test in certify mode +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test115 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system.spec -quer_names query1,query2 -quer_exprs "y1>0;y2<=0" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_certify.spec +spec_fn smlp_toy_system_stable_constant_synth_feasible.spec specs_path ../specs -Running test 127 test type: certify, description: certification example with knobs only and fictitious inputs with values fixed through their ranges -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test127 -mode certify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_certify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 123 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test123 -mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_query.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 143 test type: query, description: basic test for compress_rules for et_sklearn in mode query -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test143 -mode query -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_bootstrap f -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_query.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 142 test type: optsyn, description: basic test for compress_rules option for rf_sklearn in optsin mode +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test142 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 160 test type: prediction, description: tests nn keras tuner bayesian -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test160 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -nn_keras_metrics msle -nn_keras_tuner bayesian -nn_keras_layers_grid "2,3" -nn_keras_losses_grid "mse,mae,huber" -model_per_response f -sw_coef 8 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 153 test type: prediction, description: tests the logcosh loss function LogCosh and sample weights +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test153 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss logcosh -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mse -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn -Running test 151 test type: prediction, description: tests msle loss function MeanSquaredLogarithmicError and and sample weoghts -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test151 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss msle -sw_coef 3 -sw_exp 10 -sw_int 0 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 161 test type: prediction, description: tests nn keras tuner bayesian +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test161 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -nn_keras_metrics mape,logcosh -nn_keras_tuner random -nn_keras_lrates_grid "0.01,0.001" -nn_keras_batches_grid "32,64" -model_per_response f -sw_coef 4 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test118 -mode verify -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_verify.spec -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +specs_path ../specs +Running test 125 test type: optsyn, description: optimized synthesis test with constant knob and no inputs where synthesis is feasible and optimization is performed +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test125 -mode optsyn -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 144 test type: verify, description: basic test for compress_rules for dt_sklearn in mode verify and re-using saved model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test144 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -save_model f -use_model f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2 -asrt_exprs "x0**2+y1>4.3;(y1+x2)/2<6" -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +Running test 150 test type: prediction, description: tests the mape loss function MeanAbsolutePercentageError and sample weights +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test150 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult_verify.spec specs_path ../specs -Running test 156 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner for functional model training; adapts test 154 by consdering multiple responses -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test156 -mode verify -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse +Running test 157 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training; adapts test 155 by consdering multiple responses +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test157 -mode verify -resp y1,y2 -feat x,p1,p2 --model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse,logcosh + +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 162 test type: verify, description: tests model term construction with flat_encoding of tress and model per reponse when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test162 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs Running test 167 test type: optsyn, description: basic flat tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test167 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test167 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs Running test 171 test type: optimize, description: basic test for et_caret with flat tree_encoding in model exploration mode optimize -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test171 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test171 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 175 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test175 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 176 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api f for nn_keras in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test176 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs -Running test 178 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features are not scaled adapts test 177 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test178 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 181 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test181 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs -Running test 188 test type: optsyn, description: basic branched tree encoding test for dt_caretin model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test188 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding branched -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 183 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test183 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 196 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 and test 181 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test196 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 185 test type: verify, description: tests model term construction with branched_encoding of tress and model per reponse when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test185 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_no_input_beta.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 201 test type: optimize, description: basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and there are beta constraints -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test201 -mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_no_input_beta.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 191 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response t in model exploration mode optimize adapts test 169 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test191 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap t -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_no_input.spec +spec_fn smlp_toy_system_stable_constant_synth_fail.spec specs_path ../specs -Running test 202 test type: optimize, description: basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and no beta constraints -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test202 -mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_no_input.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 122 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test122 -mode optimize -pareto f -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 206 test type: optsyn, description: optimized synthesis test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 125 -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test206 -mode optsyn -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 139 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test139 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -tree_encoding nested -compress_rules f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -Running test 219 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test219 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type integer -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 149 test type: prediction, description: tests the mae loss function MeanAbsoluteError and sample weoghts +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test149 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mae -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -Running test 224 test type: correlate, description: basic test for correlate mode and tests the Shannon mutual information -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test224 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f +spec_fn smlp_toy_num_resp_mult_verify.spec +specs_path ../specs +Running test 156 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner for functional model training; adapts test 154 by consdering multiple responses +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test156 -mode verify -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs Running test 164 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test164 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test164 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 168 test type: optimize, description: basic test for rf_caret with flat tree_encoding and modelper_response in model exploration mode optimize -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test168 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding flat -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 166 test type: optsyn, description: basic flat tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test166 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_y2_verify.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 173 test type: verify, description: basic test for nn_keras flat encoding for sequential api -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test173 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" +Running test 170 test type: optimize, description: basic test for et_sklearn with flat tree_encoding and model_per_response f in model exploration mode optimize +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test170 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 183 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test183 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 175 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test175 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 191 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response t in model exploration mode optimize adapts test 169 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test191 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap t -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 179 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn when resposes are not scaled adapts test 174 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test179 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +spec_fn smlp_toy_num_resp_noknobs_verify.spec +specs_path ../specs +Running test 184 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model adapts test 139 +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test184 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 195 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 192 by setting n_estimators 3 and then discrepancy between z3 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test195 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 189 test type: optsyn, description: basic branched tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn adapts test 166 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test189 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 199 test type: optimize, description: test to demonstrate that in pareto optimization and optsyn modes with multiple objectives when beta constraints are not present SMLP results are not consistent when different solvers are used; this is due to fact that when a subset of objectoves are exemined in pareto algo -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test199 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 193 test type: optimize, description: basic test for et_caret with branched tree_encoding in model exploration mode optimize adapts test 171 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test193 -mode optimize -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 218 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test218 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +spec_fn smlp_toy_system_stable_constant_synth_fail.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec +specs_path ../specs +Running test 168 test type: optimize, description: basic test for rf_caret with flat tree_encoding and modelper_response in model exploration mode optimize +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test168 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding flat -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +spec_fn smlp_toy_num_resp_mult_y2_verify.spec +specs_path ../specs +Running test 173 test type: verify, description: basic test for nn_keras flat encoding for sequential api +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test173 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" + +spec_fn smlp_toy_num_resp_mult_optsyn.spec +specs_path ../specs +Running test 199 test type: optimize, description: test to demonstrate that in pareto optimization and optsyn modes with multiple objectives when beta constraints are not present SMLP results are not consistent when different solvers are used; this is due to fact that when a subset of objectoves are exemined in pareto algo +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test199 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f Running test 223 test type: correlate, description: basic test for correlate mode and tests the normalized mutual information -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test223 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test223 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f -spec_fn smlp_toy_system_radii_update_certify.spec +spec_fn smlp_toy_missing_radii.spec specs_path ../specs -Running test 228 test type: certify, description: test that radii specified in command line properly override the radii specified in the spec file. Here we override both ansolute and relative radii and one can observe that the certification results also change compared to test 116 -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test228 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system_radii_update_certify.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 229 test type: certify, description: basic test for checking that each knob must have either absolute or relative radius specified in the spec file (even if radii are specified in the command line) +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test229 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_missing_radii.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 233 test type: subgroups, description: tests subgroup discovery mode when the response has string values -../../src/run_smlp.py -data "../data/smlp_toy_string_response.csv" -out_dir ./ -pref Test233 -mode subgroups -resp str_resp1 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f - smlp_toy_num_resp_mult_optsyn.spec +Running test 148 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and sequential API +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test148 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 177 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test177 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 155 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test155 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae + +spec_fn smlp_toy_num_resp_mult_optsyn.spec +specs_path ../specs +Running test 180 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features and responses are not scaled adapts test 175 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test180 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_feat f -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs Running test 182 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test182 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test182 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" + +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +specs_path ../specs +Running test 187 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization adapts test 164 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test187 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 192 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test192 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 194 test type: optsyn, description: basic branched tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test194 -mode optsyn -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +specs_path ../specs +Running test 198 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 and test 183 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test198 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat + +Running test 216 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test216 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f + +Running test 221 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test221 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +spec_fn smlp_toy_system_radii_update_certify.spec +specs_path ../specs +Running test 228 test type: certify, description: test that radii specified in command line properly override the radii specified in the spec file. Here we override both ansolute and relative radii and one can observe that the certification results also change compared to test 116 +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test228 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_system_radii_update_certify.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + + +spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +specs_path ../specs +Running test 196 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 and test 181 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test196 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +spec_fn smlp_toy_num_resp_mult_no_input.spec +specs_path ../specs +Running test 202 test type: optimize, description: basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and no beta constraints +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test202 -mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_no_input.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_system_stable_constant_synth_feasible.spec specs_path ../specs -Running test 204 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 123 -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test204 -mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 205 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 145 +smlp -out_dir ./ -pref Test205 -mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 217 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test217 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 218 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test218 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type ordered -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -Running test 222 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test222 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 226 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test226 -mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -Running test 227 test type: correlate, description: basic test for correlate mode and tests the normalized mutual information -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test227 -mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f +Running test 233 test type: subgroups, description: tests subgroup discovery mode when the response has string values +smlp -data "../data/smlp_toy_string_response.csv" -out_dir ./ -pref Test233 -mode subgroups -resp str_resp1 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f -Running test 234 test type: subgroups, description: tests subgroup discovery mode when there are two responses with string values -../../src/run_smlp.py -data "../data/smlp_toy_string_response.csv" -out_dir ./ -pref Test234 -mode subgroups -resp str_resp1,str_resp2 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f +Running test 158 test type: prediction, description: tests the mape loss function and sample weights with model_per_response t +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test158 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -model_per_response t -sw_coef 8 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics rmse -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 166 test type: optsyn, description: basic flat tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test166 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding flat -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 163 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test163 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs Running test 169 test type: optimize, description: basic test for et_sklearn with flat tree_encoding and model_per_response t in model exploration mode optimize -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test169 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test169 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 176 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api f for nn_keras in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test176 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 174 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test174 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 179 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn when resposes are not scaled adapts test 174 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test179 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 192 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test192 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +Running test 215 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test215 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +Running test 222 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test222 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +spec_fn smlp_toy_system_monotone_knob.05_verify.spec specs_path ../specs -Running test 181 test type: optimize, description: basic flat tree encoding test for dt_sklearn multi objective pareto optimization when features are not scaled modifies test 164 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test181 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding flat -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 230 test type: verify, description: tests that outputs in system specificaation might depend on different inuts (knobs and free inputs) +smlp -data "../data/smlp_toy_monotone_basic.csv" -out_dir ./ -pref Test230 -mode verify -spec ../specs/smlp_toy_system_monotone_knob.05_verify.spec -model system -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec + +spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 187 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization adapts test 164 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test187 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 154 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner for functional model training +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test154 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 194 test type: optsyn, description: basic branched tree encoding test with model_per_response t for rf_sklearn in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test194 -mode optsyn -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 178 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features are not scaled adapts test 177 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test178 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec +spec_fn smlp_toy_num_resp_noknobs_verify.spec specs_path ../specs -Running test 197 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 and test 182 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test197 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" +Running test 186 test type: verify, description: tests model term formation when mrmr_pred is activated and not all features are selected for training the model +smlp -data "../data/smlp_toy_num_resp_noknobs.csv" -out_dir ./ -pref Test186 -mode verify -resp y1,y2 -feat x0,x1,x2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_noknobs_verify.spec -asrt_names asrt1,asrt2,asrt3 -asrt_exprs "(y2**3+x2)/2<6;y1>=9;y2<0" -trace_anonym t -trace_prec 3 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -new_dat "../data/smlp_toy_num_resp_noknobs_pred_labeled.csv" -spec_fn smlp_toy_system_stable_constant_synth_fail.spec +spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 203 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed adapts test 122 -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test203 -mode optimize -pareto f -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 190 test type: optimize, description: basic test for rf_caret with branched tree_encoding and modelper_response in model exploration mode optimize adapts test 168 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test190 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding branched -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 216 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test216 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f +spec_fn smlp_toy_num_resp_mult_no_input_beta.spec +specs_path ../specs +Running test 201 test type: optimize, description: basic dt_sklearn single objective optimization with the eager algorithm when there are no inputs and there are beta constraints +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test201 -mode optimize -pareto t -opt_strategy eager -resp y1,y2 -feat p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -spec ../specs/smlp_toy_num_resp_mult_no_input_beta.spec -data_scaler min_max -objv_names obj1 -objv_exprs "(y1+y2)/2" -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 220 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test220 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +spec_fn smlp_toy_system_stable_constant_synth_feasible.spec +specs_path ../specs +Running test 204 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 123 +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test204 -mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +Running test 219 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test219 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type integer -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass Running test 225 test type: correlate, description: basic test for correlate mode and tests the adjusted mutual information -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test225 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test225 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method adjusted -mrmr_pred 0 -plots f -seed 10 -log_time f -spec_fn smlp_toy_system_monotone_knob.05_verify.spec +spec_fn smlp_toy_system_running_example_certify.spec specs_path ../specs -Running test 230 test type: verify, description: tests that outputs in system specificaation might depend on different inuts (knobs and free inputs) -../../src/run_smlp.py -data "../data/smlp_toy_monotone_basic.csv" -out_dir ./ -pref Test230 -mode verify -spec ../specs/smlp_toy_system_monotone_knob.05_verify.spec -model system -seed 10 -log_time f +Running test 232 test type: certify, description: running example from smlp manual +smlp -data "../data/smlp_toy_system_running_example_certify.csv" -out_dir ./ -pref Test232 -mode certify -spec ../specs/smlp_toy_system_running_example_certify.spec -model system -seed 10 -log_time f -Running test 159 test type: prediction, description: tests the msle loss function and sample weights with model_per_response t -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test159 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -model_per_response t -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae,cosine -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +specs_path ../specs +Running test 203 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is not feasible because the assertion is not feasible but beta constraint is feasible therefore optimization is performed adapts test 122 +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test203 -mode optimize -pareto f -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_fail.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +Running test 217 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test217 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type category -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass + +Running test 224 test type: correlate, description: basic test for correlate mode and tests the Shannon mutual information +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test224 -mode correlate -resp y1,y2 -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f + +spec_fn smlp_toy_system_decreasing_knob.05_certify.spec specs_path ../specs -Running test 165 test type: optsyn, description: basic flat tree encoding test for dt_caretin model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test165 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding flat -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 231 test type: certify, description: certification test with monotonicity query with a knob with a grid point +smlp -data "../data/smlp_toy_monotone_basic.csv" -out_dir ./ -pref Test231 -mode certify -spec ../specs/smlp_toy_system_decreasing_knob.05_certify.spec -model system -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_y2_verify.spec + smlp_toy_witness_certify.spec specs_path ../specs -Running test 172 test type: verify, description: basic test for nn_keras flat encoding for functional api -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test172 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" +Running test 128 test type: certify, description: Basic regression test in certify mode covering all four possible outcomes when certifying a witness for a query: the witness is stable +smlp -data "../data/smlp_toy_ctg_num_resp.csv" -out_dir ./ -pref Test128 -mode certify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -dt_sklearn_max_depth 15 -save_model f -use_model f -model_per_response f -spec ../specs/smlp_toy_witness_certify.spec -quer_names query_stable_witness,query_grid_conflict,query_unstable_witness,query_infeasible_witness,query_poly_intercept_sensitive -quer_exprs "y2<=90;y1>=9;y1>=(-13);y1>9;y1>=(-10)" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +spec_fn smlp_toy_system.spec +specs_path ../specs +Running test 146 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed +smlp -out_dir ./ -pref Test146 -mode optimize -pareto t -opt_strategy lazy -model poly_sklearn -resp y1,y2 -feat p1,p2,x1,x2 -save_model t -use_model f -mrmr_pred 0 -model_per_response t -split 1 -spec ../specs/smlp_toy_system.spec -doe_spec ../grids/explore_doe_two_levels.csv -doe_algo latin_hypercube -epsilon 0.99999999 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f + +Running test 152 test type: prediction, description: tests the huber loss function Huber and sample weights +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test152 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss huber -sw_coef 8 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" + +Running test 160 test type: prediction, description: tests nn keras tuner bayesian +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test160 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss mape -nn_keras_metrics msle -nn_keras_tuner bayesian -nn_keras_layers_grid "2,3" -nn_keras_losses_grid "mse,mae,huber" -model_per_response f -sw_coef 8 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 180 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api t for nn_keras in model exploration mode optsyn when features and responses are not scaled adapts test 175 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test180 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -scale_feat f -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 177 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response t nn_keras_seq_api t for nn_keras in model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test177 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api t -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 190 test type: optimize, description: basic test for rf_caret with branched tree_encoding and modelper_response in model exploration mode optimize adapts test 168 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test190 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_caret -model_per_response t -compress_rules t -tree_encoding branched -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 188 test type: optsyn, description: basic branched tree encoding test for dt_caretin model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test188 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding branched -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_free_inps_beta_objv.spec specs_path ../specs -Running test 198 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when features and responses are not scaled modifies test 164 and test 183 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test198 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -scale_feat f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat +Running test 197 test type: optimize, description: basic branched tree encoding test for dt_sklearn multi objective pareto optimization when responses are not scaled modifies test 164 and test 182 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test197 -mode optimize -pareto t -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_sklearn -dt_sklearn_max_depth 15 -compress_rules f -tree_encoding branched -scale_resp f -spec ../specs/smlp_toy_num_resp_mult_free_inps_beta_objv.spec -data_scaler min_max -epsilon 0.05 -delta_rel 0.01 -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" spec_fn smlp_toy_system_stable_constant_synth_feasible.spec specs_path ../specs -Running test 205 test type: optimize, description: optimization test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 145 -../../src/run_smlp.py -out_dir ./ -pref Test205 -mode optimize -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -Running test 215 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test215 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 206 test type: optsyn, description: optimized synthesis test with eager strategy and with constant knob and no inputs where synthesis is feasible and optimization is performed adapts test 125 +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test206 -mode optsyn -pareto t -opt_strategy eager -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 221 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test221 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method shannon -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass +Running test 220 test type: correlate, description: basic test for correlate mode +smlp -data "../data/smlp_toy_mult_discr.csv" -out_dir ./ -pref Test220 -mode correlate -resp "PF,PF1" -discr_algo uniform -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f -pos_val fail -neg_val pass -Running test 226 test type: correlate, description: basic test for correlate mode -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test226 -mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method correlation -mrmr_pred 0 -plots f -seed 10 -log_time f +Running test 227 test type: correlate, description: basic test for correlate mode and tests the normalized mutual information +smlp -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test227 -mode correlate -resp y1,y2 -discr_algo uniform -discret_num t -discr_bins 6 -discr_labels t -discr_type object -data_scaler none -cont_est pearson,spearman,kendall -mi_method normalized -mrmr_pred 0 -plots f -seed 10 -log_time f -spec_fn smlp_toy_system_running_example_certify.spec -specs_path ../specs -Running test 232 test type: certify, description: running example from smlp manual -../../src/run_smlp.py -data "../data/smlp_toy_system_running_example_certify.csv" -out_dir ./ -pref Test232 -mode certify -spec ../specs/smlp_toy_system_running_example_certify.spec -model system -seed 10 -log_time f +Running test 234 test type: subgroups, description: tests subgroup discovery mode when there are two responses with string values +smlp -data "../data/smlp_toy_string_response.csv" -out_dir ./ -pref Test234 -mode subgroups -resp str_resp1,str_resp2 -feat num,int,str -pos_val no -neg_val yes -seed 10 -log_time f -spec_fn smlp_toy_missing_radii.spec +spec_fn smlp_toy_configuration_verify.spec specs_path ../specs -Running test 229 test type: certify, description: basic test for checking that each knob must have either absolute or relative radius specified in the spec file (even if radii are specified in the command line) -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test229 -mode certify -resp y1,y2 -feat x1,x2,p1,p2 -model system -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_missing_radii.spec -rad_rel 0.005 -rad_abs 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 129 test type: verify, description: verification example with demonstrating all basic result scenarious for assertions +smlp -data "../data/smlp_toy_ctg_num_resp.csv" -out_dir ./ -pref Test129 -mode verify -resp y1,y2 -feat x,p1,p2 -model poly_sklearn -save_model f -use_model f -model_per_response f -spec ../specs/smlp_toy_configuration_verify.spec -asrt_names assert_stable_config,assert_grid_conflict,assert_unstable_config,assert_infeasible -asrt_exprs "y2<=90;y1>=9;y1>=(-10);y1>20" -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_system_decreasing_knob.05_certify.spec +spec_fn smlp_toy_system_stable_constant_synth_feasible.spec specs_path ../specs -Running test 231 test type: certify, description: certification test with monotonicity query with a knob with a grid point -../../src/run_smlp.py -data "../data/smlp_toy_monotone_basic.csv" -out_dir ./ -pref Test231 -mode certify -spec ../specs/smlp_toy_system_decreasing_knob.05_certify.spec -model system -seed 10 -log_time f - - -../../src/run_smlp.py -data "../data/smlp_toy_basic.csv" -out_dir ./ -pref Test140 -mode verify -model system -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_verify.spec -trace_prec 1 -trace_anonym t -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -Running test 147 test type: prediction, description: checks nn_keras prediction with sw_coef 0.8 and sequential API -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test147 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -sw_coef 0.8 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" - -Running test 153 test type: prediction, description: tests the logcosh loss function LogCosh and sample weights -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test153 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss logcosh -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mse -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 145 test type: optimize, description: optimization test with constant knob and no inputs where synthesis is feasible and optimization is performed +smlp -out_dir ./ -pref Test145 -mode optimize -pareto t -opt_strategy lazy -model system -resp y1,y2 -feat p1,p2 -save_model f -use_model f -mrmr_pred 0 -model_per_response t -spec ../specs/smlp_toy_system_stable_constant_synth_feasible.spec -doe_spec ../grids/doe_two_levels_opt.csv -doe_algo latin_hypercube -epsilon 0.00000001 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -Running test 161 test type: prediction, description: tests nn keras tuner bayesian -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test161 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -nn_keras_metrics mape,logcosh -nn_keras_tuner random -nn_keras_lrates_grid "0.01,0.001" -nn_keras_batches_grid "32,64" -model_per_response f -sw_coef 4 -sw_exp 5 -sw_int 0.5 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" +Running test 151 test type: prediction, description: tests msle loss function MeanSquaredLogarithmicError and and sample weoghts +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test151 -mode predict -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_loss msle -sw_coef 3 -sw_exp 10 -sw_int 0 -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" -spec_fn smlp_toy_num_resp_mult_optsyn.spec -specs_path ../specs -Running test 170 test type: optimize, description: basic test for et_sklearn with flat tree_encoding and model_per_response f in model exploration mode optimize -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test170 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -rf_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding flat -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 159 test type: prediction, description: tests the msle loss function and sample weights with model_per_response t +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test159 -mode predict -resp y1,y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -save_model_config f -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_loss msle -model_per_response t -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae,cosine -new_dat "../data/smlp_toy_num_resp_mult_pred_labeled.csv" spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 174 test type: optsyn, description: basic layered nn_keras encoding test with model_per_response f nn_keras_seq_api f for nn_keras in model exploration mode optsyn -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test174 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model nn_keras -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -save_model f -use_model f -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 165 test type: optsyn, description: basic flat tree encoding test for dt_caretin model exploration mode optsyn +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test165 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model dt_caret -tree_encoding flat -save_model f -use_model f -compress_rules f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -spec_fn smlp_toy_num_resp_mult_optsyn.spec +spec_fn smlp_toy_num_resp_mult_y2_verify.spec specs_path ../specs -Running test 189 test type: optsyn, description: basic branched tree encoding test with model_per_response f for rf_sklearn in model exploration mode optsyn adapts test 166 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test189 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 4 -rf_sklearn_n_estimators 3 -tree_encoding branched -compress_rules t -save_model f -use_model f -compress_rules t -mrmr_pred 2 -model_per_response f -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 172 test type: verify, description: basic test for nn_keras flat encoding for functional api +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test172 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nnet_encoding layered -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat"" spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs -Running test 193 test type: optimize, description: basic test for et_caret with branched tree_encoding in model exploration mode optimize adapts test 171 -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test193 -mode optimize -resp y1,y2 -feat x,p1,p2 -model et_caret -tree_encoding branched -model_per_response t -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f +Running test 195 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 192 by setting n_estimators 3 and then discrepancy between z3 +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test195 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 3 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f spec_fn smlp_toy_num_resp_mult_optsyn.spec specs_path ../specs Running test 200 test type: optimize, description: basic test for et_sklearn with branched tree_encoding and model_per_response f in model exploration mode optimize adapts test 170 !!!!!!!!! in this test z3 result differs from mathsat and yices results (the latter two give sma results -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test200 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - - ../specs -Running test 142 test type: optsyn, description: basic test for compress_rules option for rf_sklearn in optsin mode -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test142 -mode optsyn -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model rf_sklearn -rf_sklearn_max_depth 15 -tree_encoding nested -compress_rules t -save_model f -use_model f -mrmr_pred 2 -model_per_response t -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0.05 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f - -spec_fn smlp_toy_num_resp_mult_y2_verify.spec -specs_path ../specs -Running test 154 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner for functional model training -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test154 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api f -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 - - -specs_path ../specs -Running test 155 test type: verify, description: basic nn_keras assertion verification test that uses keras tuner with sequrntial models for model training -../../src/run_smlp.py -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test155 -mode verify -resp y2 -feat x,p1,p2 -model nn_keras -nnet_encoding nested -mrmr_pred 0 -plots f -pred_plots f -resp_plots f -seed 10 -log_time f -nn_keras_epochs 20 -nn_keras_seq_api t -nn_keras_tuner hyperband -nn_keras_layers_grid "2,2;3,3,3" -save_model_config f -spec ../specs/smlp_toy_num_resp_mult_y2_verify.spec -asrt_names asrt1 -asrt_exprs "2*y2>1" -sw_coef 4 -sw_exp 5 -sw_int 0.5 -nn_keras_metrics mae +smlp -data "../data/smlp_toy_num_resp_mult.csv" -out_dir ./ -pref Test200 -mode optimize -opt_strategy lazy -resp y1,y2 -feat x,p1,p2 -model et_sklearn -et_sklearn_max_depth 2 -et_sklearn_n_estimators 100 -et_sklearn_bootstrap f -tree_encoding branched -model_per_response f -compress_rules t -save_model f -use_model f -mrmr_pred 2 -spec ../specs/smlp_toy_num_resp_mult_optsyn.spec -epsilon 0.1 -delta_rel 0 -solver_path ../../../external/mathsat-5.6.8-linux-x86_64-reentrant/bin/mathsat -plots f -pred_plots f -resp_plots f -seed 10 -log_time f Initiating 7 worker... comparing Test1_smlp_toy_num_resp_mult_y1_dt_caret_tree_rules.txt to master @@ -1611,9 +1704,34 @@ comparing Test56_smlp_toy_mult_discr.txt to master Passed! comparing Test56_smlp_toy_mult_discr_missing_values_dict.json to master Passed! -Test 57 Failed: -Error in Build stage: -Data file does not exist +comparing Test57_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test57_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! comparing Test58_smlp_toy_num_resp_mult.txt to master Passed! comparing Test58_smlp_toy_num_resp_mult_data_bounds.json to master @@ -1664,158 +1782,415 @@ comparing Test59_smlp_toy_num_resp_mult_model_levels_dict.json to master Passed! comparing Test59_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master Passed! -comparing Test59_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +comparing Test59_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +Passed! +File master Test59_smlp_toy_num_resp_mult_trace.csv does not exist +File master Test59_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist +comparing Test59_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +Passed! +comparing Test59_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +Passed! +comparing Test59_smlp_toy_num_resp_mult_verify_results.json to master +Passed! +File master Test59_smlp_toy_num_resp_mult_y2_smlp_full_model_term.json does not exist +File master Test59_smlp_toy_num_resp_mult_y2_smlp_model_term.json does not exist +comparing Test60_smlp_toy_num_resp_mult.txt to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_data_bounds.json to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_missing_values_dict.json to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_model_features_dict.json to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_model_gen.json to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_model_levels_dict.json to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +Passed! +File master Test60_smlp_toy_num_resp_mult_trace.csv does not exist +File master Test60_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist +comparing Test60_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +Passed! +comparing Test60_smlp_toy_num_resp_mult_verify_results.json to master +Passed! +File master Test60_smlp_toy_num_resp_mult_y2_smlp_full_model_term.json does not exist +File master Test60_smlp_toy_num_resp_mult_y2_smlp_model_term.json does not exist +comparing Test61_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_model_gen.json to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +File master Test61_smlp_toy_num_resp_noknobs_train-reg_y1_mse.png does not exist +File master Test61_smlp_toy_num_resp_noknobs_train-reg_y2_mse.png does not exist +comparing Test61_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test61_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_model_gen.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +File master Test62_smlp_toy_num_resp_noknobs_train-reg_all_responses_mse.png does not exist +comparing Test62_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test62_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! +File master test63_model_dt_sklearn_y1_tree_rules.txt does not exist +comparing Test63_smlp_toy_num_resp_mult.txt to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_missing_values_dict.json to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +Passed! +File master Test63_smlp_toy_num_resp_mult_trace.csv does not exist +comparing Test63_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +Passed! +comparing Test63_smlp_toy_num_resp_mult_verify_results.json to master +Passed! +comparing test63_model_data_bounds.json to master +Passed! +comparing test63_model_model_features_dict.json to master +Passed! +comparing test63_model_model_levels_dict.json to master +Passed! +comparing test63_model_rerun_model_config.json to master +Passed! +File master test63_model_y1_smlp_full_model_term.json does not exist +File master test63_model_y1_smlp_model_term.json does not exist +comparing Test64_test63_model.txt to master +File master Test64_test63_model_trace.csv does not exist +comparing Test64_test63_model_verify_results.json to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test65_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! +comparing test65_model_data_bounds.json to master +Passed! +comparing test65_model_dt_sklearn_tree_rules.txt to master +Passed! +comparing test65_model_model_features_dict.json to master +Passed! +comparing test65_model_model_levels_dict.json to master +Passed! +comparing test65_model_rerun_model_config.json to master +Passed! +comparing Test66_test65_model.txt to master +Passed! +comparing Test66_test65_model_trace.csv to master +Passed! +comparing Test66_test65_model_verify_results.json to master +Passed! +comparing test67_model_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test67_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! +comparing test67_model_data_bounds.json to master +Passed! +comparing test67_model_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing test67_model_model_features_dict.json to master +Passed! +comparing test67_model_model_levels_dict.json to master +Passed! +comparing test67_model_rerun_model_config.json to master +Passed! +comparing Test68_test67_model.txt to master +Passed! +comparing Test68_test67_model_trace.csv to master +Passed! +comparing Test68_test67_model_verify_results.json to master +Passed! +comparing Test69_smlp_toy_num_resp_mult.txt to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_missing_values_dict.json to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +Passed! +File master Test69_smlp_toy_num_resp_mult_trace.csv does not exist +File master Test69_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist +comparing Test69_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +Passed! +comparing Test69_smlp_toy_num_resp_mult_verify_results.json to master +Passed! +comparing test69_model_data_bounds.json to master +Passed! +comparing test69_model_model_features_dict.json to master +Passed! +comparing test69_model_model_gen.json to master +Passed! +comparing test69_model_model_levels_dict.json to master +Passed! +comparing test69_model_rerun_model_config.json to master +Passed! +File master test69_model_y2_smlp_full_model_term.json does not exist +File master test69_model_y2_smlp_model_term.json does not exist +comparing Test70_test69_model.txt to master +File master Test70_test69_model_trace.csv does not exist +comparing Test70_test69_model_verify_results.json to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +File master Test71_smlp_toy_num_resp_noknobs_train-reg_y1_mse.png does not exist +File master Test71_smlp_toy_num_resp_noknobs_train-reg_y2_mse.png does not exist +comparing Test71_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test71_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! +comparing test71_model_data_bounds.json to master +Passed! +comparing test71_model_model_features_dict.json to master +Passed! +comparing test71_model_model_gen.json to master +Passed! +comparing test71_model_model_levels_dict.json to master +Passed! +comparing test71_model_rerun_model_config.json to master +Passed! +comparing Test72_test71_model.txt to master +Passed! +comparing Test72_test71_model_trace.csv to master +Passed! +comparing Test72_test71_model_verify_results.json to master +Passed! +comparing test73_model_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test73_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! +comparing test73_model_data_bounds.json to master +Passed! +comparing test73_model_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing test73_model_model_features_dict.json to master +Passed! +comparing test73_model_model_levels_dict.json to master +Passed! +comparing test73_model_rerun_model_config.json to master Passed! -File master Test59_smlp_toy_num_resp_mult_trace.csv does not exist -File master Test59_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist -comparing Test59_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt to master Passed! -comparing Test59_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master Passed! -comparing Test59_smlp_toy_num_resp_mult_verify_results.json to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master Passed! -File master Test59_smlp_toy_num_resp_mult_y2_smlp_full_model_term.json does not exist -File master Test59_smlp_toy_num_resp_mult_y2_smlp_model_term.json does not exist -comparing Test60_smlp_toy_num_resp_mult.txt to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_data_bounds.json to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +comparing Test74_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master Passed! -comparing Test60_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled.txt to master Passed! -comparing Test60_smlp_toy_num_resp_mult_missing_values_dict.json to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master Passed! -comparing Test60_smlp_toy_num_resp_mult_model_features_dict.json to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_model_gen.json to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_model_levels_dict.json to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +comparing Test75_test73_model_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master Passed! -comparing Test60_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +comparing Test76_smlp_toy_num_resp_noknobs.txt to master Passed! -File master Test60_smlp_toy_num_resp_mult_trace.csv does not exist -File master Test60_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist -comparing Test60_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master Passed! -comparing Test60_smlp_toy_num_resp_mult_verify_results.json to master +comparing Test76_smlp_toy_num_resp_noknobs_missing_values_dict.json to master Passed! -File master Test60_smlp_toy_num_resp_mult_y2_smlp_full_model_term.json does not exist -File master Test60_smlp_toy_num_resp_mult_y2_smlp_model_term.json does not exist -Test 61 Failed: -Error in Build stage: -Data file does not exist -Test 62 Failed: -Error in Build stage: -Data file does not exist -File master test63_model_dt_sklearn_y1_tree_rules.txt does not exist -comparing Test63_smlp_toy_num_resp_mult.txt to master +comparing Test76_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master Passed! -comparing Test63_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master Passed! -comparing Test63_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_trace.csv to master Passed! -comparing Test63_smlp_toy_num_resp_mult_missing_values_dict.json to master +comparing Test76_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master Passed! -comparing Test63_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master Passed! -comparing Test63_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +comparing Test76_smlp_toy_num_resp_noknobs_verify_results.json to master Passed! -File master Test63_smlp_toy_num_resp_mult_trace.csv does not exist -comparing Test63_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +comparing test76_model_data_bounds.json to master Passed! -comparing Test63_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +comparing test76_model_dt_sklearn_tree_rules.txt to master Passed! -comparing Test63_smlp_toy_num_resp_mult_verify_results.json to master +comparing test76_model_model_features_dict.json to master Passed! -comparing test63_model_data_bounds.json to master +comparing test76_model_model_levels_dict.json to master Passed! -comparing test63_model_model_features_dict.json to master +comparing test76_model_rerun_model_config.json to master Passed! -comparing test63_model_model_levels_dict.json to master +comparing Test77_test76_model.txt to master Passed! -comparing test63_model_rerun_model_config.json to master +comparing Test77_test76_model_trace.csv to master Passed! -File master test63_model_y1_smlp_full_model_term.json does not exist -File master test63_model_y1_smlp_model_term.json does not exist -comparing Test64_test63_model.txt to master -File master Test64_test63_model_trace.csv does not exist -comparing Test64_test63_model_verify_results.json to master +comparing Test77_test76_model_verify_results.json to master Passed! -Test 65 Failed: -Error in Build stage: -Data file does not exist -comparing Test66_test65_model.txt to master -File new Test66_test65_model_verify_results.json does not exist -Test 67 Failed: -Error in Build stage: -Data file does not exist -comparing Test68_test67_model.txt to master -File new Test68_test67_model_verify_results.json does not exist -comparing Test69_smlp_toy_num_resp_mult.txt to master +comparing test78_model_dt_sklearn_tree_rules.txt to master Passed! -comparing Test69_smlp_toy_num_resp_mult_labeled_prediction_precisions.csv to master +comparing Test78_smlp_toy_num_resp_noknobs.txt to master Passed! -comparing Test69_smlp_toy_num_resp_mult_labeled_predictions_summary.csv to master +comparing Test78_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master Passed! -comparing Test69_smlp_toy_num_resp_mult_missing_values_dict.json to master +comparing Test78_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master Passed! -comparing Test69_smlp_toy_num_resp_mult_test_prediction_precisions.csv to master +comparing Test78_smlp_toy_num_resp_noknobs_missing_values_dict.json to master Passed! -comparing Test69_smlp_toy_num_resp_mult_test_predictions_summary.csv to master +comparing Test78_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master Passed! -File master Test69_smlp_toy_num_resp_mult_trace.csv does not exist -File master Test69_smlp_toy_num_resp_mult_train-reg_y2_mse.png does not exist -comparing Test69_smlp_toy_num_resp_mult_training_prediction_precisions.csv to master +comparing Test78_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master Passed! -comparing Test69_smlp_toy_num_resp_mult_training_predictions_summary.csv to master +comparing Test78_smlp_toy_num_resp_noknobs_trace.csv to master Passed! -comparing Test69_smlp_toy_num_resp_mult_verify_results.json to master +comparing Test78_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master Passed! -comparing test69_model_data_bounds.json to master +comparing Test78_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master Passed! -comparing test69_model_model_features_dict.json to master +comparing Test78_smlp_toy_num_resp_noknobs_verify_results.json to master Passed! -comparing test69_model_model_gen.json to master +comparing test78_model_data_bounds.json to master Passed! -comparing test69_model_model_levels_dict.json to master +comparing test78_model_model_features_dict.json to master Passed! -comparing test69_model_rerun_model_config.json to master +comparing test78_model_model_levels_dict.json to master Passed! -File master test69_model_y2_smlp_full_model_term.json does not exist -File master test69_model_y2_smlp_model_term.json does not exist -comparing Test70_test69_model.txt to master -File master Test70_test69_model_trace.csv does not exist -comparing Test70_test69_model_verify_results.json to master +comparing test78_model_rerun_model_config.json to master Passed! -Test 71 Failed: -Error in Build stage: -Data file does not exist -comparing Test72_test71_model.txt to master -File new Test72_test71_model_verify_results.json does not exist -Test 73 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist -Test 74 Failed: -Error in Build stage: -New data file does not exist -Test 75 Failed: -Error in Build stage: -New data file does not exist -Test 76 Failed: -Error in Build stage: -Data file does not exist -comparing Test77_test76_model.txt to master -File new Test77_test76_model_verify_results.json does not exist -Test 78 Failed: -Error in Build stage: -Data file does not exist comparing Test79_smlp_toy_num_resp_mult.txt to master Passed! comparing Test79_smlp_toy_num_resp_mult_data_bounds.json to master @@ -1979,9 +2354,36 @@ comparing Test83_smlp_toy_num_resp_mult_training_prediction_precisions.csv to ma Passed! comparing Test83_smlp_toy_num_resp_mult_training_predictions_summary.csv to master Passed! -Test 84 Failed: -Error in Build stage: -Data file does not exist +comparing Test84_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test84_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! comparing Test85_smlp_toy_num_resp_mult_dt_sklearn_tree_rules.txt to master Passed! comparing Test85_smlp_toy_num_resp_mult.txt to master @@ -3110,11 +3512,42 @@ New data file does not exist Test 138 Failed: Error in Build stage: Data file does not exist -Test 139 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test139_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! File master Test140_smlp_toy_basic.txt does not exist File master Test140_smlp_toy_basic_data_bounds.json does not exist File master Test140_smlp_toy_basic_features_scaler.pkl does not exist @@ -3189,9 +3622,34 @@ File master Test143_smlp_toy_num_resp_mult_y1_smlp_full_model_term.json does not File master Test143_smlp_toy_num_resp_mult_y1_smlp_model_term.json does not exist File master Test143_smlp_toy_num_resp_mult_y2_smlp_full_model_term.json does not exist File master Test143_smlp_toy_num_resp_mult_y2_smlp_model_term.json does not exist -Test 144 Failed: -Error in Build stage: -Data file does not exist +comparing Test144_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs.txt to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_labeled_prediction_precisions.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_labeled_predictions_summary.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_missing_values_dict.json to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_test_prediction_precisions.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_test_predictions_summary.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_trace.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_training_prediction_precisions.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_training_predictions_summary.csv to master +Passed! +comparing Test144_smlp_toy_num_resp_noknobs_verify_results.json to master +Passed! File master Test145_doe_two_levels_opt.txt does not exist File master Test145_doe_two_levels_opt_trace.csv does not exist File master Test146_explore_doe_two_levels.txt does not exist @@ -3489,16 +3947,76 @@ File master Test161_smlp_toy_num_resp_mult_smlp_toy_num_resp_mult_pred_labeled_t File master Test161_smlp_toy_num_resp_mult_smlp_toy_num_resp_mult_pred_labeled_train-reg_all_responses_mape.png does not exist File master Test161_smlp_toy_num_resp_mult_smlp_toy_num_resp_mult_pred_labeled_training_prediction_precisions.csv does not exist File master Test161_smlp_toy_num_resp_mult_smlp_toy_num_resp_mult_pred_labeled_training_predictions_summary.csv does not exist -Test 162 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist -Test 163 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist +comparing Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test162_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test163_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! File master Test164_smlp_toy_num_resp_mult.txt does not exist File master Test164_smlp_toy_num_resp_mult_data_bounds.json does not exist File master Test164_smlp_toy_num_resp_mult_dt_sklearn_model_complete.pkl does not exist @@ -3945,21 +4463,112 @@ File master Test183_smlp_toy_num_resp_mult_test_predictions_summary.csv does not File master Test183_smlp_toy_num_resp_mult_trace.csv does not exist File master Test183_smlp_toy_num_resp_mult_training_prediction_precisions.csv does not exist File master Test183_smlp_toy_num_resp_mult_training_predictions_summary.csv does not exist -Test 184 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist -Test 185 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist -Test 186 Failed: -Error in Build stage: -Data file does not exist -Error in Build stage: -New data file does not exist +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test184_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_dt_sklearn_y1_tree_rules.txt to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_dt_sklearn_y2_tree_rules.txt to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test185_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_dt_sklearn_tree_rules.txt to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_data_bounds.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_model_features_dict.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_model_levels_dict.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_rerun_model_config.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled.txt to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_prediction_precisions.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_labeled_predictions_summary.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_missing_values_dict.json to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_prediction_precisions.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_new_predictions_summary.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_prediction_precisions.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_test_predictions_summary.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_trace.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_prediction_precisions.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_training_predictions_summary.csv to master +Passed! +comparing Test186_smlp_toy_num_resp_noknobs_smlp_toy_num_resp_noknobs_pred_labeled_verify_results.json to master +Passed! File master Test187_smlp_toy_num_resp_mult.txt does not exist File master Test187_smlp_toy_num_resp_mult_data_bounds.json does not exist File master Test187_smlp_toy_num_resp_mult_dt_sklearn_model_complete.pkl does not exist @@ -4429,5 +5038,5 @@ Passed! master log file does not exist! Do you wish to copy the new log file to master? (yes/no|y/n): No new tests crashed (not in the masters) -Time: 32.59507596492767 minutes +Time: 28.443782750765482 minutes End of regression diff --git a/tests/smlp_regression/run_smlp_regression_venv_expected_diff_report.log b/tests/smlp_regression/run_smlp_regression_venv_expected_diff_report.log index 5d8bc15b..8c813c01 100644 --- a/tests/smlp_regression/run_smlp_regression_venv_expected_diff_report.log +++ b/tests/smlp_regression/run_smlp_regression_venv_expected_diff_report.log @@ -386,424 +386,12 @@ --- > smlp_logger - INFO - Seving model rerun configuration in file ./../models/test63_model_rerun_model_config.json =================== End of Test64_test63_model.txt diff report ================================ -=================== Diff report for: Test66_test65_model.txt ================================== -0a1,97 -> -> smlp_logger - INFO - Model exploration specification: -> {'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} -> -> smlp_logger - INFO - Executing run_smlp.py script: Start -> -> smlp_logger - INFO - Running SMLP in mode "verify": Start -> -> smlp_logger - INFO - Computed spec global constraint expressions: -> -> smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 -> -> smlp_logger - INFO - Global beta : None -> -> smlp_logger - INFO - Radii theta : {} -> -> smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} -> -> smlp_logger - INFO - Assertion asrt1: x0**2+y1>4.3 -> -> smlp_logger - INFO - Assertion asrt2: (y1+x2)/2<6 -> -> smlp_logger - INFO - PREPARE DATA FOR MODELING -> -> smlp_logger - INFO - LOAD TRAINED MODEL -> -> smlp_logger - INFO - Seving model rerun configuration in file ./../models/test65_model_rerun_model_config.json -> -> smlp_logger - INFO - Creating model exploration base components: Start -> -> smlp_logger - INFO - Parsing the SPEC: Start -> -> smlp_logger - INFO - Parsing the SPEC: End -> -> smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} -> -> smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} -> -> smlp_logger - INFO - Knob bounds (eta): {} -> -> smlp_logger - INFO - Knob grids (eta): {} -> -> smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) -> -> smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) -> -> smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) -> -> smlp_logger - INFO - Beta global constraints: true -> -> smlp_logger - INFO - Eta ranges constraints: true -> -> smlp_logger - INFO - Eta grid constraints: true -> -> smlp_logger - INFO - Eta global constraints: true -> -> smlp_logger - INFO - Eta combined constraints: true -> -> smlp_logger - INFO - Creating model exploration base components: End -> -> smlp_logger - INFO - Input and knob interface constraints are consistent -> -> smlp_logger - INFO - Building model terms: Start -> -> smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} -> -> smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 15, 'ite': 5, 'and': 9, 'prop': 14, 'const': 50, 'sub': 14, 'var': 14} -> -> smlp_logger - INFO - Building model terms: End -> -> smlp_logger - INFO - Model interface constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying assertion asrt1 <-> x0**2+y1>4.3 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt1 -> -> smlp_logger - INFO - Completed with result: PASS -> -> smlp_logger - INFO - Verifying assertion asrt2 <-> (y1+x2)/2<6 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt2 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Running SMLP in mode "verify": End -> -> smlp_logger - INFO - Executing run_smlp.py script: End -=================== End of Test66_test65_model.txt diff report ================================ -=================== Diff report for: Test66_test65_model_verify_results.json ================================== -diff: /home/mdmitry/github/smlp_subgroups_assertion_fix/scripts/venv/smlp_regression_venv/smlp/regr_smlp/code/Test66_test65_model_verify_results.json: No such file or directory -=================== End of Test66_test65_model_verify_results.json diff report ================================ -=================== Diff report for: Test68_test67_model.txt ================================== -0a1,97 -> -> smlp_logger - INFO - Model exploration specification: -> {'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} -> -> smlp_logger - INFO - Executing run_smlp.py script: Start -> -> smlp_logger - INFO - Running SMLP in mode "verify": Start -> -> smlp_logger - INFO - Computed spec global constraint expressions: -> -> smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 -> -> smlp_logger - INFO - Global beta : None -> -> smlp_logger - INFO - Radii theta : {} -> -> smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} -> -> smlp_logger - INFO - Assertion asrt1: x0**2+y1>4.3 -> -> smlp_logger - INFO - Assertion asrt2: (y1+x2)/2<6 -> -> smlp_logger - INFO - PREPARE DATA FOR MODELING -> -> smlp_logger - INFO - LOAD TRAINED MODEL -> -> smlp_logger - INFO - Seving model rerun configuration in file ./../models/test67_model_rerun_model_config.json -> -> smlp_logger - INFO - Creating model exploration base components: Start -> -> smlp_logger - INFO - Parsing the SPEC: Start -> -> smlp_logger - INFO - Parsing the SPEC: End -> -> smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} -> -> smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} -> -> smlp_logger - INFO - Knob bounds (eta): {} -> -> smlp_logger - INFO - Knob grids (eta): {} -> -> smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) -> -> smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) -> -> smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) -> -> smlp_logger - INFO - Beta global constraints: true -> -> smlp_logger - INFO - Eta ranges constraints: true -> -> smlp_logger - INFO - Eta grid constraints: true -> -> smlp_logger - INFO - Eta global constraints: true -> -> smlp_logger - INFO - Eta combined constraints: true -> -> smlp_logger - INFO - Creating model exploration base components: End -> -> smlp_logger - INFO - Input and knob interface constraints are consistent -> -> smlp_logger - INFO - Building model terms: Start -> -> smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 7, 'ite': 3, 'and': 3, 'prop': 6, 'const': 24, 'sub': 6, 'var': 6} -> -> smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 4, 'ite': 2, 'and': 1, 'prop': 3, 'const': 14, 'sub': 3, 'var': 3} -> -> smlp_logger - INFO - Building model terms: End -> -> smlp_logger - INFO - Model interface constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying assertion asrt1 <-> x0**2+y1>4.3 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt1 -> -> smlp_logger - INFO - Completed with result: PASS -> -> smlp_logger - INFO - Verifying assertion asrt2 <-> (y1+x2)/2<6 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt2 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Running SMLP in mode "verify": End -> -> smlp_logger - INFO - Executing run_smlp.py script: End -=================== End of Test68_test67_model.txt diff report ================================ -=================== Diff report for: Test68_test67_model_verify_results.json ================================== -diff: /home/mdmitry/github/smlp_subgroups_assertion_fix/scripts/venv/smlp_regression_venv/smlp/regr_smlp/code/Test68_test67_model_verify_results.json: No such file or directory -=================== End of Test68_test67_model_verify_results.json diff report ================================ =================== Diff report for: Test70_test69_model.txt ================================== 25c25 < smlp_logger - INFO - Seving model rerun configuration in file ../models/test69_model_rerun_model_config.json --- > smlp_logger - INFO - Seving model rerun configuration in file ./../models/test69_model_rerun_model_config.json =================== End of Test70_test69_model.txt diff report ================================ -=================== Diff report for: Test72_test71_model.txt ================================== -0a1,84 -> -> smlp_logger - INFO - Model exploration specification: -> {'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} -> -> smlp_logger - INFO - Executing run_smlp.py script: Start -> -> smlp_logger - INFO - Running SMLP in mode "verify": Start -> -> smlp_logger - INFO - Computed spec global constraint expressions: -> -> smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 -> -> smlp_logger - INFO - Global beta : None -> -> smlp_logger - INFO - Radii theta : {} -> -> smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} -> -> smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 -> -> smlp_logger - INFO - PREPARE DATA FOR MODELING -> -> smlp_logger - INFO - LOAD TRAINED MODEL -> -> smlp_logger - INFO - Seving model rerun configuration in file ./../models/test71_model_rerun_model_config.json -> -> smlp_logger - INFO - Creating model exploration base components: Start -> -> smlp_logger - INFO - Parsing the SPEC: Start -> -> smlp_logger - INFO - Parsing the SPEC: End -> -> smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} -> -> smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} -> -> smlp_logger - INFO - Knob bounds (eta): {} -> -> smlp_logger - INFO - Knob grids (eta): {} -> -> smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) -> -> smlp_logger - INFO - Alpha ranges constraints: (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) -> -> smlp_logger - INFO - Alpha combined constraints: (and (and (and (and true (and (>= x0 0) (<= x0 10))) (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) -> -> smlp_logger - INFO - Beta global constraints: true -> -> smlp_logger - INFO - Eta ranges constraints: true -> -> smlp_logger - INFO - Eta grid constraints: true -> -> smlp_logger - INFO - Eta global constraints: true -> -> smlp_logger - INFO - Eta combined constraints: true -> -> smlp_logger - INFO - Creating model exploration base components: End -> -> smlp_logger - INFO - Input and knob interface constraints are consistent -> -> smlp_logger - INFO - Building model terms: Start -> -> smlp_logger - INFO - Model operator counts for y1: {'add': 256, 'mul': 472, 'ite': 39, 'prop': 39, 'const': 846, 'sub': 216, 'var': 216} -> -> smlp_logger - INFO - Model operator counts for y2: {'add': 256, 'mul': 472, 'ite': 39, 'prop': 39, 'const': 846, 'sub': 216, 'var': 216} -> -> smlp_logger - INFO - Building model terms: End -> -> smlp_logger - INFO - Model interface constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt1 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Running SMLP in mode "verify": End -> -> smlp_logger - INFO - Executing run_smlp.py script: End -=================== End of Test72_test71_model.txt diff report ================================ -=================== Diff report for: Test72_test71_model_verify_results.json ================================== -diff: /home/mdmitry/github/smlp_subgroups_assertion_fix/scripts/venv/smlp_regression_venv/smlp/regr_smlp/code/Test72_test71_model_verify_results.json: No such file or directory -=================== End of Test72_test71_model_verify_results.json diff report ================================ -=================== Diff report for: Test77_test76_model.txt ================================== -0a1,110 -> -> smlp_logger - INFO - Model exploration specification: -> {'version': '1.1', 'spec': [{'label': 'y1', 'type': 'response', 'range': 'float'}, {'label': 'y2', 'type': 'response', 'range': 'float'}, {'label': 'x0', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x1', 'type': 'input', 'range': 'float', 'bounds': [0, 10]}, {'label': 'x2', 'type': 'input', 'range': 'float', 'bounds': [3, 7]}], 'alpha': 'x1==1 or x1==4 or x1==7'} -> -> smlp_logger - INFO - Executing run_smlp.py script: Start -> -> smlp_logger - INFO - Running SMLP in mode "verify": Start -> -> smlp_logger - INFO - Computed spec global constraint expressions: -> -> smlp_logger - INFO - Global alpha : x1==1 or x1==4 or x1==7 -> -> smlp_logger - INFO - Global beta : None -> -> smlp_logger - INFO - Radii theta : {} -> -> smlp_logger - INFO - Delta const : {'delta_abs': 0.0, 'delta_rel': 0.01} -> -> smlp_logger - INFO - Assertion asrt1: (y2**3+x2)/2<6 -> -> smlp_logger - INFO - Assertion asrt2: y1>=9 -> -> smlp_logger - INFO - Assertion asrt3: y2<0 -> -> smlp_logger - INFO - PREPARE DATA FOR MODELING -> -> smlp_logger - INFO - LOAD TRAINED MODEL -> -> smlp_logger - INFO - Seving model rerun configuration in file ./../models/test76_model_rerun_model_config.json -> -> smlp_logger - INFO - Creating model exploration base components: Start -> -> smlp_logger - INFO - Parsing the SPEC: Start -> -> smlp_logger - INFO - Parsing the SPEC: End -> -> smlp_logger - INFO - Variable domains (alpha): {'y1': {'range': 'float', 'interval': None}, 'y2': {'range': 'float', 'interval': None}, 'x0': {'range': 'float', 'interval': [0, 10]}, 'x1': {'range': 'float', 'interval': [0, 10]}, 'x2': {'range': 'float', 'interval': [3, 7]}} -> -> smlp_logger - INFO - Input bounds (alpha): {'x0': {'min': 0, 'max': 10}, 'x1': {'min': 0, 'max': 10}, 'x2': {'min': 3, 'max': 7}} -> -> smlp_logger - INFO - Knob bounds (eta): {} -> -> smlp_logger - INFO - Knob grids (eta): {} -> -> smlp_logger - INFO - Alpha global constraints: (or (or (= x1 1) (= x1 4)) (= x1 7)) -> -> smlp_logger - INFO - Alpha ranges constraints: (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) -> -> smlp_logger - INFO - Alpha combined constraints: (and (and (and true (and (>= x1 0) (<= x1 10))) (and (>= x2 3) (<= x2 7))) (or (or (= x1 1) (= x1 4)) (= x1 7))) -> -> smlp_logger - INFO - Beta global constraints: true -> -> smlp_logger - INFO - Eta ranges constraints: true -> -> smlp_logger - INFO - Eta grid constraints: true -> -> smlp_logger - INFO - Eta global constraints: true -> -> smlp_logger - INFO - Eta combined constraints: true -> -> smlp_logger - INFO - Creating model exploration base components: End -> -> smlp_logger - INFO - Input and knob interface constraints are consistent -> -> smlp_logger - INFO - Building model terms: Start -> -> smlp_logger - INFO - Model operator counts for y1: {'add': 1, 'mul': 21, 'ite': 6, 'and': 14, 'prop': 20, 'const': 69, 'sub': 20, 'var': 20} -> -> smlp_logger - INFO - Model operator counts for y2: {'add': 1, 'mul': 21, 'ite': 6, 'and': 14, 'prop': 20, 'const': 69, 'sub': 20, 'var': 20} -> -> smlp_logger - INFO - Building model terms: End -> -> smlp_logger - INFO - Model interface constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt1: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt2: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying consistency of configuration for assertion asrt3: -> true -> -> smlp_logger - INFO - Input, knob and configuration constraints are consistent -> -> smlp_logger - INFO - Verifying assertion asrt1 <-> (y2**3+x2)/2<6 -> -> smlp_logger - INFO - The configuration is inconsistent with assertion asrt1 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Verifying assertion asrt2 <-> y1>=9 -> -> smlp_logger - INFO - The configuration is consistent with assertion asrt2 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Verifying assertion asrt3 <-> y2<0 -> -> smlp_logger - INFO - The configuration is inconsistent with assertion asrt3 -> -> smlp_logger - INFO - Completed with result: FAIL -> -> smlp_logger - INFO - Running SMLP in mode "verify": End -> -> smlp_logger - INFO - Executing run_smlp.py script: End -=================== End of Test77_test76_model.txt diff report ================================ -=================== Diff report for: Test77_test76_model_verify_results.json ================================== -diff: /home/mdmitry/github/smlp_subgroups_assertion_fix/scripts/venv/smlp_regression_venv/smlp/regr_smlp/code/Test77_test76_model_verify_results.json: No such file or directory -=================== End of Test77_test76_model_verify_results.json diff report ================================ =================== Diff report for: Test97_smlp_toy_num_resp_mult.txt ================================== 252c252 < smlp_logger - INFO - Model operator counts for y2: {'add': 100, 'mul': 715, 'const': 2547, 'ite': 305, 'and': 408, 'prop': 713, 'sub': 713, 'var': 713} @@ -817,7 +405,7 @@ diff: /home/mdmitry/github/smlp_subgroups_assertion_fix/scripts/venv/smlp_regres > smlp_logger - INFO - Seving model rerun configuration in file ./../models/test101_model_rerun_model_config.json =================== End of Test102_test101_model.txt diff report ================================ =================== Diff report for: test110_model_poly_sklearn_formula.txt ================================== -diff: /home/mdmitry/github/smlp_subgroups_assertion_fix/scripts/venv/smlp_regression_venv/smlp/regr_smlp/code/test110_model_poly_sklearn_formula.txt: No such file or directory +diff: /home/mdmitry/github/smlp_noknobs_tests_recovery/scripts/venv/smlp_package_venv/smlp/regr_smlp/code/test110_model_poly_sklearn_formula.txt: No such file or directory =================== End of test110_model_poly_sklearn_formula.txt diff report ================================ =================== Diff report for: Test111_test110_model_smlp_toy_basic_pred_unlabeled.txt ================================== 79c79