PSLmodels · andersonfrailey · Aug 21, 2020 · Jul 22, 2020 · Aug 3, 2020 · Aug 3, 2020
diff --git a/.gitignore b/.gitignore
@@ -22,5 +22,9 @@ cpsmar*.sas
 cpsmar*.csv
 *.dat
 
+
 # pickle
 cps*.pkl
+
+# .npz numpy files
+*.npz
diff --git a/Makefile b/Makefile
@@ -106,7 +106,8 @@ puf_stage1/growfactors.csv: puf_stage1/factors_finalprep.py \
 	cd puf_stage1 ; python factors_finalprep.py
 
 puf_stage2/puf_weights.csv.gz: puf_stage2/stage2.py \
-                               puf_stage2/solve_lp_for_year.py \
+                               puf_stage2/dataprep.py \
+                               puf_stage2/solver.jl \
                                puf_data/cps-matched-puf.csv \
                                puf_stage1/Stage_I_factors.csv \
                                puf_stage1/Stage_II_targets.csv

diff --git a/Manifest.toml b/Manifest.toml
diff --git a/Project.toml b/Project.toml
@@ -0,0 +1,4 @@
+[deps]
+Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
+JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
+NPZ = "15e1cf62-19b3-5cfa-8e77-841668bca605"
diff --git a/README.md b/README.md
@@ -51,6 +51,10 @@ conda env create -f environment.yml
 To run the scripts that produce `puf.csv` and `cps.csv.gz`, activate the
 `taxdata-dev` conda environment and follow the workflow laid out below.
 
+`Julia` must also be installed to solve for the PUF and CPS weights. You 
+can download `Julia` from their [website](https://julialang.org/downloads/)
+or by using `homebrew`.
+
 Data-Preparation Documentation and Workflow
 -------------------------------------------
 

diff --git a/cps_stage2/cps_weights.csv.gz b/cps_stage2/cps_weights.csv.gz