Update choropleth maps

docs/source/plotting_scripts/maps.py

@@ -3,6 +3,7 @@
 #%% Imports
 import os
 import sys
+from adjustText import adjust_text
 import shapely
 import datetime
 import numpy as np
@@ -230,39 +231,47 @@
         dfcounty.plot(ax=ax, facecolor='none', edgecolor='C7', lw=0.02, zorder=1e6)
     if draw_lakes:
         greatlakes.plot(ax=ax, edgecolor='#2CA8E7', facecolor='#D3EFFA', lw=0.2, zorder=-1)
+    text_artists = []
     for r, row in dfregion.iterrows():
         dfregion.loc[[r]].plot(ax=ax, color=colors[r], alpha=alpha_region, lw=0, zorder=1)
         if label_regions.get(level, True):
             x, y = (
                 np.array([row.geometry.centroid.x, row.geometry.centroid.y])
                 + np.array(offset.get(level, {}).get(r, (0,0)))
             )
-            for i, (c, a) in enumerate([('k',1), (colors[r], 0.6)]):
+            ## Shade the r labels with the zone color
+            for i, (_color, _alpha) in enumerate([('k', 1), (colors[r], 0.6)]):
                 if i == 1 and level != 'r':
                     continue
-                ax.annotate(
+                text_artists.append(ax.annotate(
                     (r if level == 'r' else r.replace('_','\n')),
                     (x, y),
                     ha='center', va='center', weight='bold',
                     size={'r':7, 'hurdlereg':7, 'st':10}.get(level,11),
-                    color=c, zorder=1e11+i, alpha=a,
+                    color=_color, zorder=1e11+i, alpha=_alpha,
                     path_effects=(
                         [pe.withStroke(linewidth=1.5, foreground='w', alpha=(1 if i == 0 else 0))]
                     ),
-                )
+                ))
+    adjust_text(text_artists, ax=ax, avoid_self=False, ensure_inside_axes=True)
+
+    text_artists = []
     if label_zones.get(level, True):
         for r, row in dfmap['r'].iterrows():
             x, y = (
                 np.array([row.geometry.centroid.x, row.geometry.centroid.y])
                 + np.array(offset.get('r', {}).get(r, (0,0)))
             )
-            ax.annotate(
-                r,
-                (x, y),
-                ha='center', va='center', size=6, weight='normal',
-                color='C7', zorder=1e10,
-                path_effects=[pe.withStroke(linewidth=0.7, foreground='w', alpha=1)]
+            text_artists.append(
+                ax.annotate(
+                    r,
+                    (x, y),
+                    ha='center', va='center', size=6, weight='normal',
+                    color='C7', zorder=1e10,
+                    path_effects=[pe.withStroke(linewidth=0.7, foreground='w', alpha=1)]
+                )
             )
+        adjust_text(text_artists, ax=ax, avoid_self=False, ensure_inside_axes=True)
 
     ax.axis('off')
     savename = (

environment.yml

@@ -27,6 +27,7 @@ dependencies:
   - tqdm=4.68
   ## vvv The next packages are optional for default settings and may
   ## vvv be excluded if you're having trouble building the environment.
+  - adjustText=1.4 # for avoiding map label overlaps
   - fiona=1.10 # for interactive maps
   - folium=0.20 # for interactive maps
   - ipykernel=7.3 # for interactive python in VS Code

postprocessing/compare_cases.py

@@ -130,7 +130,7 @@
 
 
 #%%### Fixed inputs
-cmap = cmocean.cm.rain
+cmap = cmocean.cm.tempo
 cmap_diff = plt.cm.RdBu_r
 ## https://www.whitehouse.gov/wp-content/uploads/2023/11/CircularA-4.pdf
 discountrate_social = DEFAULT_DISCOUNT_RATE
@@ -2595,7 +2595,7 @@ def two_bars(dfplot, basecase, colors, ax, col=0, ypad=0.02):
                 year=lastyear, casebase=casebase, casecomp=casecomp,
                 level=level,
                 plot='base', f=f, ax=ax[0],
-                cmap=cmocean.cm.rain,
+                cmap=cmap,
             )
             ax[0].annotate(
                 casebase_name,
@@ -2606,7 +2606,7 @@ def two_bars(dfplot, basecase, colors, ax, col=0, ypad=0.02):
                 year=lastyear, casebase=casebase, casecomp=casecomp,
                 level=level,
                 plot='comp', f=f, ax=ax[1],
-                cmap=cmocean.cm.rain,
+                cmap=cmap,
             )
             ax[1].annotate(
                 casecomp_name,
@@ -2682,6 +2682,7 @@ def two_bars(dfplot, basecase, colors, ax, col=0, ypad=0.02):
                     ax=ax[coords[case]], column='GW', cmap=cmap, vmin=vmin, vmax=vmax,
                     legend=False,
                 )
+                reedsplots.label_region_value(dfplot, ax=ax[coords[case]], column="GW", fontsize=5)
                 ## Legend
                 if coords[case] == legendcoords:
                     plots.addcolorbarhist(
@@ -2753,6 +2754,7 @@ def two_bars(dfplot, basecase, colors, ax, col=0, ypad=0.02):
                     vmax=(absmax if case == basecase else diffmax),
                     legend=False,
                 )
+                reedsplots.label_region_value(dfplot, ax=ax[coords[case]], column="GW", fontsize=5)
                 ## Difference legend
                 if coords[case] == legendcoords:
                     plots.addcolorbarhist(

postprocessing/single_case_plots.py

@@ -29,7 +29,7 @@
 ## the position of the annotations
 crs = 'ESRI:102008'
 ### General purpose
-cmap = cmocean.cm.rain
+cmap = cmocean.cm.tempo
 ### For VRE siting & transmission maps
 transalpha = 0.25
 transcolor = 'k'
@@ -267,7 +267,7 @@
     plt.close()
     f,ax = reedsplots.plot_trans_vsc(
         case=case, year=year, wscale=wscale_straight*1e3,
-        alpha=1.0, miles=300,
+        alpha=1.0, miles=300, cmap=cmap,
     )
     savename = f'map_translines_vsc-{year}.png'
     if write and (f is not None):
@@ -288,7 +288,10 @@
 for vmax in ['each', 'shared']:
     try:
         f,ax = reedsplots.map_capacity_techs(
-            case, year=year, ncols=ncols, vmax=vmax,
+            case, year=year, ncols=ncols, vmax=vmax, cmap=cmap,
+            label_regions = (
+                True if len(reeds.inputs.parse_regions(case))<=100 else False
+                ),
         )
         savename = f'map_capacity-{year}-{vmax}.png'
         if write:
@@ -517,7 +520,11 @@
     if int(sw.GSw_H2):
         plt.close()
         f,ax = reedsplots.map_h2_capacity(
-            case=case, year=year, cmap=cmap, wscale_h2=wscale_h2)
+            case=case, year=year, cmap=cmap, wscale_h2=wscale_h2,
+            label_regions = (
+                True if len(reeds.inputs.parse_regions(case))<=100 else False
+                ),
+        )
         savename = f'map_h2_capacity-{sw.endyear}.png'
         if write:
             plt.savefig(os.path.join(savepath, savename))
@@ -646,7 +653,7 @@
 try:
     for y in [y for y in years if y >= 2025]:
         plt.close()
-        f, ax, neue, _iteration = reedsplots.map_neue(case=case, year=y)
+        f, ax, neue, _iteration = reedsplots.map_neue(case=case, year=y, cmap=cmap)
         savename = f"map_PRAS_neue-{y}i{_iteration}.png"
         if write:
             plt.savefig(os.path.join(savepath, savename))
@@ -860,7 +867,7 @@
 #%% PRM if iterating
 if int(sw.GSw_PRM_StressIterateMax) and int(sw.GSw_PRM_UpdateMethod):
     try:
-        f, ax, prm_final = reedsplots.map_prm(case)
+        f, ax, prm_final = reedsplots.map_prm(case, cmap=cmap)
         savename = 'map_prm.png'
         if write:
             plt.savefig(os.path.join(savepath, savename))
@@ -928,6 +935,7 @@
             years=[year],
             vscale=1e-3,
             vmin=0,
+            cmap=cmap,
             title='Sited demand [GW]',
         )
         savename = f'map_loadsite-{year}.png'

reeds/input_processing/hourly_plots.py

@@ -14,6 +14,7 @@
 from pathlib import Path
 sys.path.append(str(Path(__file__).parent.parent.parent))
 import reeds
+from reeds import reedsplots
 from reeds import plots
 plots.plotparams()
 
@@ -230,7 +231,7 @@ def plot_maps(sw, inputs_case, reeds_path, figpath, periodtype='rep', crs='EPSG:
     ### Settings
     cmaps = {
         'cf_actual':plt.cm.turbo, 'cf_rep':plt.cm.turbo, 'cf_diff':plt.cm.RdBu_r,
-        'GW_actual':cmocean.cm.rain, 'GW_rep':cmocean.cm.rain,
+        'GW_actual':cmocean.cm.tempo, 'GW_rep':cmocean.cm.tempo,
         'GW_diff':plt.cm.RdBu_r, 'GW_frac':plt.cm.RdBu_r, 'pct_diff':plt.cm.RdBu_r, 
     }
     vm = {
@@ -351,17 +352,16 @@ def plot_maps(sw, inputs_case, reeds_path, figpath, periodtype='rep', crs='EPSG:
             dfdiffs[level].plot(
                 ax=ax[coords[level]], column='cf_diff', cmap=cmaps['cf_diff'],
                 vmin=vm[tech]['cf_diff'][0], vmax=vm[tech]['cf_diff'][1], 
-                lw=0, legend=False,
+                lw=0, legend=False, missing_kwds={"color": "white"},
             )
             dfmap[level].plot(ax=ax[coords[level]], facecolor='none', edgecolor='k', lw=0.2)
-            ## Text differences
-            for r, row in (dfdiffs[level].assign(val=dfdiffs[level].cf_diff.abs()).sort_values('val')).iterrows():
-                decimals = 0 if abs(row.cf_diff) >= 1 else 1
-                ax[coords[level]].annotate(
-                    f"{row.cf_diff*100:+.{decimals}f}",
-                    [row.centroid_x, row.centroid_y],
-                    ha='center', va='center', c='k', fontsize={'r':5}.get(level,7),
-                    path_effects=[pe.withStroke(linewidth=1.5, foreground='w', alpha=0.5)],
+            dfmap[level]['cf_diff_pct'] = (dfdiffs[level].cf_diff * 100).values
+            reedsplots.label_region_value(
+                dfmap[level],
+                ax[coords[level]],
+                column='cf_diff_pct',
+                text_kwargs={'fontsize': {'r':5}.get(level,7)},
+                pe_kwargs={'linewidth': 1.5, 'foreground': 'w', 'alpha': 0.5},
                 )
             ## Colorbar
             plots.addcolorbarhist(
@@ -485,14 +485,12 @@ def plot_maps(sw, inputs_case, reeds_path, figpath, periodtype='rep', crs='EPSG:
                 lw=0, legend=False,
             )
             dfmap[level].plot(ax=ax[coords[level]], facecolor='none', edgecolor='k', lw=0.2)
-            ## Text differences
-            for r, row in (dfdiffs[level].assign(val=dfdiffs[level][val].abs()).sort_values('val')).iterrows():
-                decimals = 0 if abs(row[val]) >= 1 else 1
-                ax[coords[level]].annotate(
-                    f"{row[val]:+.{decimals}f}",
-                    [row.centroid_x, row.centroid_y],
-                    ha='center', va='center', c='k', fontsize={'r':5}.get(level,7),
-                    path_effects=[pe.withStroke(linewidth=1.5, foreground='w', alpha=0.5)],
+            reedsplots.label_region_value(
+                dfdiffs[level],
+                ax[coords[level]],
+                column=val,
+                text_kwargs={'fontsize': {'r':5}.get(level,7)},
+                pe_kwargs={'linewidth': 1.5, 'foreground': 'w', 'alpha': 0.5},
                 )
             ## Colorbar
             plots.addcolorbarhist(

reeds/input_processing/outage_rates.py

@@ -7,6 +7,7 @@
 import argparse
 import h5py
 from pathlib import Path
+import cmocean
 sys.path.append(str(Path(__file__).parent.parent.parent))
 import reeds
 reeds_path = reeds.io.reeds_path
@@ -19,6 +20,7 @@
 tz_out = 'Etc/GMT+6'
 temp_min = -50
 temp_max = 60
+cmap = cmocean.cm.tempo
 ## Only use during_quarters for techs without a monthly scheduled outage rate
 during_quarters = ['spring', 'fall']
 ## Cap the extrapolation of forced outage rates at high/low temperatures to 0.4 because
@@ -383,7 +385,7 @@ def plot_outage_forced(
 
         plt.close()
         f, ax = reeds.plots.map_years_months(
-            dfzones=dfzones, dfdata=dfdata, aggfunc=aggfunc,
+            dfzones=dfzones, dfdata=dfdata, cmap=cmap, aggfunc=aggfunc,
             title=f"Monthly {aggfunc}\nforced outage rate,\n{nicelabels.get(pm,pm)} [%]",
         )
         plt.savefig(os.path.join(figpath, f'FOR_monthly-{aggfunc}-{pm}.png'))