Change test dir to tests. Make small changes to scenario import and t…

…weaks to visuals

postreise/plot/multi/constants.py

@@ -7,13 +7,16 @@
 SCENARIO_RESOURCE_TYPES = ['wind', 'solar', 'ng', 'coal', 'nuclear', 'geothermal', 'hydro']
 ALL_RESOURCE_TYPES = SCENARIO_RESOURCE_TYPES + ['other inc. biomass']
 RESOURCE_LABELS = {'wind': 'Wind', 'solar': 'Solar', 'ng': 'Natural Gas', 'coal': 'Coal', 'nuclear': 'Nuclear', 'geothermal': 'Geothermal', 'hydro': 'Hydro', 'other inc. biomass': 'Other inc. Biomass'}
-RESOURCE_COLORS = type2color = {
+RESOURCE_COLORS = {
     'wind': sns.xkcd_rgb["green"],
     'solar': sns.xkcd_rgb["amber"],
     'hydro': sns.xkcd_rgb["light blue"],
     'ng': sns.xkcd_rgb["orchid"],
     'nuclear': sns.xkcd_rgb["silver"],
     'coal': sns.xkcd_rgb["light brown"],
+    'geothermal': sns.xkcd_rgb["hot pink"],
+    'dfo': sns.xkcd_rgb["royal blue"],
+    'storage': sns.xkcd_rgb["orange"],
     'other inc. biomass': 'rebeccapurple',
     'other': 'royalblue'
 }
@@ -33,15 +36,15 @@
     'Western': 223.369046}
 CA_BASELINES = {
     'Arizona': 4.567094, 
-    'California': 48.954528, 
+    'California': 81.0, 
     'Colorado': 11.039050999999999, 
     'Idaho': 2.5057110000000002, 
     'Montana Western': 2.28368, 
     'Nevada': 7.047959, 
     'New Mexico Western': 2.5586450000000003, 
     'Oregon': 7.509413, 
     'Utah': 2.798768, 
-    'Washington': 96.129826, 
+    'Washington': 7.24, 
     'Wyoming': 5.9288989999999995, 
     'El Paso': 0.021684000000000002, 
     'Western': 191.34526}

postreise/plot/multi/plot_bar.py

@@ -103,7 +103,7 @@ def _construct_bar_visuals(zone, ax_data_list):
         ax.set_yticks([])
         ax.set_ylim(top=1.3*ax.get_ylim()[1])
 
-        ax.legend(bbox_to_anchor=(-.03, -.67), loc='lower left', fontsize=16)
+        ax.legend(bbox_to_anchor=(-.03, -.67), loc='upper left', fontsize=16)
 
         for p in ax.patches:
             b = p.get_bbox()
@@ -115,7 +115,7 @@ def _construct_hbar_visuals(zone, ax_data_list):
 
     fig, axes = plt.subplots(1, 2, figsize=(20, 0.7*num_scenarios*num_resource_types))
     plt.suptitle(zone, fontsize=30, verticalalignment="bottom")
-    #plt.subplots_adjust(wspace=1)
+    plt.subplots_adjust(wspace=1)
 
     for ax_data, ax in zip(ax_data_list, axes):
         df = pd.DataFrame(ax_data['values'], index=ax_data['labels']) 
@@ -131,7 +131,7 @@ def _construct_hbar_visuals(zone, ax_data_list):
         ax.set_xticks([])
 
         handles, labels = ax.get_legend_handles_labels()
-        ax.legend(reversed(handles), reversed(labels), bbox_to_anchor=(-.03, -0.5), loc='lower left', fontsize=16)
+        ax.legend(reversed(handles), reversed(labels), bbox_to_anchor=(-.03, 0), loc='upper left', fontsize=16)
 
         for p in ax.patches:
             b = p.get_bbox()

postreise/plot/multi/plot_helpers.py

@@ -108,8 +108,8 @@ def _format_scenario_data(data_chart, scenario_name):
         gen_data[zone] = {}
         cap_data[zone] = {}
 
-        for resource in data_chart[zone]['Generation'].keys():
-            gen_data[zone][resource] = unit_conversion(sum(data_chart[zone]['Generation'][resource].values()), 2) #MWh to TWh
+        for resource in data_chart[zone]['Generation'].to_dict().keys():
+            gen_data[zone][resource] = unit_conversion(sum(data_chart[zone]['Generation'][resource].to_dict().values()), 2) #MWh to TWh
             cap_data[zone][resource] = unit_conversion(data_chart[zone]['Capacity'][resource], 1) #MW to GW
 
     formatted_data['gen']['data'] = gen_data

postreise/plot/multi/plot_pie.py

@@ -33,7 +33,7 @@ def _construct_pie_ax_data(zone, scenarios, min_percentage):
             ax_data, labels = _roll_up_small_pie_wedges(scenario[side]['data'][zone], min_percentage) 
 
             ax_data_list.append({
-                'title': scenario[side]['label'], 
+                'title': '{0}\n{1}'.format(scenario['label'], scenario[side]['label']), 
                 'labels': labels,
                 'values': list(ax_data.values()),
                 'colors': [RESOURCE_COLORS[resource] for resource in ax_data.keys()],

postreise/plot/multi/plot_shortfall.py

@@ -28,7 +28,7 @@ def plot_shortfall(interconnect, scenario_ids=None, custom_data=None, is_match_C
             ax_data, shortfall_pct_list = _construct_shortfall_data_for_western(graph_data, is_match_CA, has_collaborative_scenarios, baselines[zone], targets, demand[zone])
         else:
             ax_data, shortfall_pct_list = _construct_shortfall_ax_data(zone, graph_data, is_match_CA, baselines[zone], targets[zone], demand[zone])
-        _construct_shortfall_visuals(zone, ax_data, shortfall_pct_list, targets[zone], is_match_CA)
+        _construct_shortfall_visuals(zone, ax_data, shortfall_pct_list, is_match_CA, targets[zone], demand[zone])
     print(f'\nDone\n')
 
 # returns: dictionary of data to visualize { '2016 NREL': {'2016 Renewables': 100, 'Simulated increase in renewables': 30, 'Missed target': 10 }, ...}
@@ -45,8 +45,8 @@ def _construct_shortfall_ax_data(zone, scenarios, is_match_CA, baseline, target,
         shortfall_pct_list.append(shortfall_pct)
 
         #TODO this breaks the visuals if renewables decrease - decide with team on how to show
-
-        #print(baseline, '|', total_renewables, '|', target, '|', shortfall)
+        print(f'\n\n{zone}\n')
+        print(baseline, '|', total_renewables, '|', target, '|', shortfall)
         ax_data.update({scenario['label']: {
             '2016 Renewables': baseline, 
             'Simulated increase in renewables': max(0, round(total_renewables - baseline, 2)), 
@@ -81,7 +81,10 @@ def _construct_shortfall_data_for_western(scenarios, is_match_CA, has_collaborat
 
         shortfall_pct_list.append(round(shortfall/demand*100, 1))
 
-        #print(baseline, '|', total_renewables, '|', target, '|', shortfall)
+        # If increase in renewables is 0 we have a base case scenario and thus the baseline is used as the source of truth
+        shortfall = max(0, targets['Western'] - baseline) if total_renewables <= baseline else shortfall
+        print(f'\n\nWestern\n')
+        print(baseline, '|', total_renewables, '|', targets['Western'], '|', shortfall)
         ax_data.update({scenario['label']: {
             '2016 Renewables': baseline, 
             'Simulated increase in renewables': max(0, round(total_renewables - baseline, 2)), 
@@ -106,20 +109,20 @@ def _get_total_generated_renewables(zone, resource_data, is_match_CA):
 
     return total_renewables
 
-def _construct_shortfall_visuals(zone, ax_data, shortfall_pct_list, target, is_match_CA):
+def _construct_shortfall_visuals(zone, ax_data, shortfall_pct_list, is_match_CA, target, demand):
         df = pd.DataFrame(ax_data).T
         ax = df.plot.bar(stacked=True, color=['darkgreen', 'yellowgreen', 'salmon'], figsize=(10, 8), fontsize=16)
         ax.set_title(zone, fontsize=26)
         ax.set_ylim(top=1.33*ax.get_ylim()[1])
-        ax.xticks(rotation=45, horizontalalignment='right')
+        ax.set_xticklabels(ax.get_xticklabels(), rotation=45, horizontalalignment='right')
 
         #Legend
         handles, labels = ax.get_legend_handles_labels()
         ax.legend(reversed(handles), reversed(labels), bbox_to_anchor=(1.556, 1.015), fontsize=14)
 
         # Add target line
         if target > 0:
-            ax_text = f'Target {target} of\n2030 demand'
+            ax_text = f'Target {int(round(target/demand*100, 0))}% of\n2030 demand'
             if is_match_CA and zone != 'California':
                 ax_text = 'CA ' + ax_text
 

postreise/plot/multi/test/mock_data_chart.py → postreise/plot/multi/tests/mock_data_chart.py

@@ -1,11 +1,13 @@
+import pandas as pd
+
 # data_chart: zone -> gen/cap -> resource_type -> vals for each date
 _MOCK_DATA_CHART = {
     'Washington': {
-        'Generation': {
+        'Generation': pd.DataFrame({
             'coal': {'12252016': 2000000, '12262016': 2000000},
             'solar': {'12252016': 0000000, '12262016': 1000000},
             'hydro': {'12252016': 3000000, '12262016': 2000000}
-        },
+        }),
         'Capacity': {
             'coal': 5000,
             'solar': 1000,

postreise/plot/multi/test/test_plot_bar.py → postreise/plot/multi/tests/test_plot_bar.py

@@ -1,4 +1,4 @@
-from postreise.plot.multi.test.mock_graph_data import create_mock_graph_data
+from postreise.plot.multi.tests.mock_graph_data import create_mock_graph_data
 from postreise.plot.multi.plot_bar import _construct_bar_ax_data, _get_bar_display_val, _get_bar_resource_types
 
 # Since these are unit tests we're intentionally not testing methods that only have visualization code

postreise/plot/multi/test/test_plot_helpers.py → postreise/plot/multi/tests/test_plot_helpers.py

@@ -2,8 +2,8 @@
 from pprint import pprint
 
 from postreise.plot.multi.constants import ZONES, BASELINES, CA_BASELINES, TARGETS, CA_TARGETS, DEMAND
-from postreise.plot.multi.test.mock_graph_data import create_mock_graph_data
-from postreise.plot.multi.test.mock_data_chart import create_mock_data_chart
+from postreise.plot.multi.tests.mock_graph_data import create_mock_graph_data
+from postreise.plot.multi.tests.mock_data_chart import create_mock_data_chart
 from postreise.plot.multi.plot_helpers import handle_plot_inputs, handle_shortfall_inputs, _format_scenario_data, unit_conversion
 
 # Since these are unit tests we're intentionally not testing methods that pull in data

postreise/plot/multi/test/test_plot_pie.py → postreise/plot/multi/tests/test_plot_pie.py

@@ -1,31 +1,31 @@
 from postreise.plot.multi.constants import RESOURCE_COLORS
-from postreise.plot.multi.test.mock_graph_data import create_mock_graph_data
+from postreise.plot.multi.tests.mock_graph_data import create_mock_graph_data
 from postreise.plot.multi.plot_pie import _construct_pie_ax_data, _roll_up_small_pie_wedges
 
 # Since these are unit tests we're intentionally not testing methods that only have visualization code
 
 def test_construct_pie_ax_data():
     ax_data_list = _construct_pie_ax_data('Washington', create_mock_graph_data(), min_percentage=0)
     expected_output = [{
-        'title': 'Generation', 
+        'title': '2016 Simulated Base Case\nGeneration', 
         'labels': ['Coal', 'Solar', 'Hydro'],
         'values': [4,1,5],
         'colors': [RESOURCE_COLORS['coal'], RESOURCE_COLORS['solar'], RESOURCE_COLORS['hydro']],
         'unit': 'TWh'
     },{
-        'title': 'Capacity', 
+        'title': '2016 Simulated Base Case\nCapacity', 
         'labels': ['Coal', 'Solar', 'Hydro'],
         'values': [5,1,4],
         'colors': [RESOURCE_COLORS['coal'], RESOURCE_COLORS['solar'], RESOURCE_COLORS['hydro']],
         'unit': 'GW'
     },{
-        'title': 'Generation', 
+        'title': '2016 NREL Data\nGeneration', 
         'labels': ['Coal', 'Solar', 'Hydro'],
         'values': [4,1,5],
         'colors': [RESOURCE_COLORS['coal'], RESOURCE_COLORS['solar'], RESOURCE_COLORS['hydro']],
         'unit': 'TWh'
     },{
-        'title': 'Capacity', 
+        'title': '2016 NREL Data\nCapacity', 
         'labels': ['Coal', 'Solar', 'Hydro', 'Wind'],
         'values': [3,1,4,2],
         'colors': [RESOURCE_COLORS['coal'], RESOURCE_COLORS['solar'], RESOURCE_COLORS['hydro'], RESOURCE_COLORS['wind']],

postreise/plot/multi/test/test_plot_shortfall.py → postreise/plot/multi/tests/test_plot_shortfall.py

@@ -1,5 +1,5 @@
 from postreise.plot.multi.constants import ZONES
-from postreise.plot.multi.test.mock_graph_data import create_mock_graph_data
+from postreise.plot.multi.tests.mock_graph_data import create_mock_graph_data
 from postreise.plot.multi.plot_shortfall import _construct_shortfall_ax_data, _construct_shortfall_data_for_western, _get_total_generated_renewables
 
 # Since these are unit tests we're intentionally not testing methods that only have visualization code