Terciles

ccsr/config-defaults.yaml

@@ -14,11 +14,20 @@ maprooms:
     flex_fcst:
 
         # App set up
-        - title: flex_cst_precip
+        - title: flex_fcst_precip
           core_path: flex_fcst_precip
           forecast_path: /Data/data21/iri/FD.3
           variable: Precipitation
           y_transform: False
           method: elr # or pycpt
           var: precip
-          issue_format: "%b %Y"
+          issue_format: "%b %Y"
+
+    terc_fcst:
+        - title: terc_fcst_precip
+          core_path: terc_fcst_precip
+          forecast_path: /Data/data21/iri/FD/NMME_Seasonal_Forecast/Precipitation_ELR
+          variable: Precipitation
+          var: precip
+          issue_format: "%b %Y"
+

ccsr/config-iri.yaml

@@ -35,3 +35,11 @@ maprooms:
           method: elr # or pycpt
           var: precip
           issue_format: "%b %Y"
+
+    terc_fcst:
+        - title: terc_fcst_precip
+          core_path: terc_fcst_precip
+          forecast_path: /Data/data21/iri/FD/NMME_Seasonal_Forecast/Precipitation_ELR
+          variable: Precipitation
+          var: precip
+          issue_format: "%b %Y"

ccsr/flex_fcst/layout.py

@@ -1,8 +1,5 @@
-from dash import dcc
 from dash import html
-import dash_bootstrap_components as dbc
-import dash_leaflet as dlf
-from fieldsets import Block, Select, PickPoint, Month, Number
+from fieldsets import Block, Select, PickPoint, Number
 import layout_utilities as lou
 
 from globals_ import GLOBAL_CONFIG

ccsr/flex_fcst_calc.py

@@ -4,14 +4,15 @@
 import pingrid
 import numpy as np
 import datetime
+import predictions
 
 
 def get_targets_dict(fcst_conf, fcst_ds, start_date):
     if fcst_conf["method"] == "pycpt":
         return pycpt.pycptv2_targets_dict(fcst_ds, start_date=start_date)
     else:
         S = datetime.datetime(
-            int(start_date[4:8]), ife.strftimeb2int(start_date[0:3]), 1
+            int(start_date[4:8]), predictions.strftimeb2int(start_date[0:3]), 1
         )
         return ife.targets_dict(fcst_ds, S)
 

ccsr/iri_fd_elr.py

@@ -1,47 +1,10 @@
-from pathlib import Path
 import xarray as xr
 import datetime
 import predictions
 from dateutil.relativedelta import relativedelta
 import numpy as np
 
 
-def strftimeb2int(strftimeb):
-    """Convert month values to integers (1-12) from strings.
-
-    Parameters
-    ----------
-    strftimeb : str
-        String value representing months of year.               
-    Returns
-    -------
-    strftimebint : int
-        Integer value corresponding to month.
-    See Also
-    --------
-    Notes
-    -----
-    Examples
-    --------
-    """
-    strftimeb_all = {
-        "Jan": 1,
-        "Feb": 2,
-        "Mar": 3,
-        "Apr": 4,
-        "May": 5,
-        "Jun": 6,
-        "Jul": 7,
-        "Aug": 8,
-        "Sep": 9,
-        "Oct": 10,
-        "Nov": 11,
-        "Dec": 12,
-    }
-    strftimebint = strftimeb_all[strftimeb]
-    return strftimebint
-
-
 def get_elr_S(data_path, var):
     """Returns list of dates of forecast issues.
 
@@ -58,7 +21,7 @@ def get_elr_S(data_path, var):
     files_list = data_path.glob(f"forecast_mean_{var}_*.nc")
     return sorted([datetime.datetime(
         int(f.name[-7:-3]),
-        strftimeb2int(f.name[-10:-7]),
+        predictions.strftimeb2int(f.name[-10:-7]),
         1,
     ) for f in files_list], reverse=True)
 

ccsr/layout_utilities.py

@@ -103,8 +103,10 @@ def description(title, subtitle, *elems):
 def map(
     default_zoom,
     layers_control_position="topleft", scale_control_position="bottomright",
-    cb_nTicks=9, cb_opacity=1, cb_tooltip=True,
-    cb_position="topright", cb_width=10, cb_height=300,
+    colorbars={"colorbar" : {
+        "nTicks": 9, "opacity": 1, "tooltip": True, "position": "topright",
+        "width": 10, "height": 300
+    }},
 ):
     """
     A dlf map topped with and H5 title,
@@ -134,21 +136,18 @@ def map(
                     dlf.ScaleControl(
                         imperial=False, position=scale_control_position
                     ),
+                ] + [
                     dlf.Colorbar(
-                        id="colorbar",
-                        nTicks=cb_nTicks,
-                        opacity=cb_opacity,
-                        tooltip=cb_tooltip,
-                        position=cb_position,
-                        width=cb_width,
-                        height=cb_height,
+                        id=cb,
                         className="p-1",
                         style={
                             "background": "white", "border-style": "inset",
                             "-moz-border-radius": "4px", "border-radius": "4px",
                             "border-color": "LightGrey",
                         },
-                    ),
+                        **cbd,
+                    )
+                    for cb, cbd in colorbars.items()
                 ],
                 id="map",
                 center=None,

ccsr/predictions.py

@@ -52,3 +52,38 @@ def target_range_formatting(target_start, target_end, time_units):
     date_range = f"{target_start_str}-{target_end_str}"
     return date_range
 
+
+def strftimeb2int(strftimeb):
+    """Convert month values to integers (1-12) from strings.
+
+    Parameters
+    ----------
+    strftimeb : str
+        String value representing months of year.               
+    Returns
+    -------
+    strftimebint : int
+        Integer value corresponding to month.
+    See Also
+    --------
+    Notes
+    -----
+    Examples
+    --------
+    """
+    strftimeb_all = {
+        "Jan": 1,
+        "Feb": 2,
+        "Mar": 3,
+        "Apr": 4,
+        "May": 5,
+        "Jun": 6,
+        "Jul": 7,
+        "Aug": 8,
+        "Sep": 9,
+        "Oct": 10,
+        "Nov": 11,
+        "Dec": 12,
+    }
+    strftimebint = strftimeb_all[strftimeb]
+    return strftimebint

ccsr/terc_fcst/__init__.py

@@ -0,0 +1 @@
+from .maproom import register

ccsr/terc_fcst/layout.py

@@ -0,0 +1,56 @@
+from dash import html
+from fieldsets import Block, PickPoint
+import layout_utilities as lou
+
+from globals_ import GLOBAL_CONFIG
+
+IRI_BLUE = "rgb(25,57,138)"
+IRI_GRAY = "rgb(113,112,116)"
+LIGHT_GRAY = "#eeeeee"
+
+def app_layout():
+
+    return lou.app_1(
+
+        lou.navbar("Forecast",
+            Block("issue_block", "Issue", html.Div(id="start_div")),
+            Block("target_block", "Target Period", html.Div(id="lead_div")),
+            PickPoint(width="8em"),
+        ),
+
+        lou.description(
+            "Precipitation Terciles Seasonal Forecast",
+            """
+            The seasonal forecast for above-, below- and near-normal precipitation 
+            from the IRI.
+            """,
+            html.P(
+                """
+                The default map shows globally the seasonal precipitation forecast 
+                tercile probability. The historical climatology used is 1982-2010 up 
+                to the forecast issued in August 2021, and is 1991-2020 from the 
+                forecast issued in September 2021. The forecast shown is the latest 
+                forecast made (e.g. Dec 2017) for the next season to come 
+                (e.g. Jan-Mar 2018). Four different seasons are forecasted and it is 
+                also possible to consult forecasts made previously. The forecasts 
+                are directly computed from the extended logistic regression model as 
+                tercile probabilities. 
+                """
+            ),
+        ),
+
+        lou.map(GLOBAL_CONFIG["zoom"], scale_control_position="bottomleft", colorbars={
+            "below_cb" : {
+                "nTicks": 6, "min": 37.5, "max": 100, "tickDecimals": 1, "unit": "%",
+                "opacity": 1, "tooltip": True, "position": "bottomright",
+                "width": 10, "height": 140,
+            },
+            "above_cb" : {
+                "nTicks": 6, "min": 37.5, "max": 100, "tickDecimals": 1, "unit": "%",
+                "opacity": 1, "tooltip": True, "position": "topright",
+                "width": 10, "height": 140,
+            },
+        }),
+
+        lou.local_single_tabbed("Tercile Probabilities"),
+    )