Add lots of tests

postreise/plot/multi/constants.py

@@ -16,4 +16,74 @@
     'coal': sns.xkcd_rgb["light brown"],
     'other inc. biomass': 'rebeccapurple',
     'other': 'royalblue'
-}
+}
+BASELINES = {
+    'Arizona': 4.567094, 
+    '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, 
+    'Wyoming': 5.9288989999999995, 
+    'El Paso': 0.021684000000000002, 
+    'Western': 223.369046}
+CA_BASELINES = {
+    'Arizona': 4.567094, 
+    'California': 48.954528, 
+    '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, 
+    'Wyoming': 5.9288989999999995, 
+    'El Paso': 0.021684000000000002, 
+    'Western': 191.34526}
+TARGETS = {
+    'Arizona': 14.556582999999998, 
+    'California': 203.49599999999998, 
+    'Colorado': 18.892801000000002, 
+    'Idaho': 0.0, 
+    'Montana Western': 2.248663, 
+    'Nevada': 20.942648000000002, 
+    'New Mexico Western': 9.613257, 
+    'Oregon': 13.704619000000001, 
+    'Utah': 6.94292, 
+    'Washington': 95.334513, 
+    'Wyoming': 0.0, 
+    'El Paso': 0.0, 
+    'Western': 385.732004}
+CA_TARGETS = {
+    'Arizona': 58.22633199999999, 
+    'California': 203.49599999999998, 
+    'Colorado': 37.785602000000004, 
+    'Idaho': 23.28269, 
+    'Montana Western': 8.994652, 
+    'Nevada': 25.131178, 
+    'New Mexico Western': 11.535909, 
+    'Oregon': 32.891086, 
+    'Utah': 20.828761, 
+    'Washington': 71.500885, 
+    'Wyoming': 11.379466, 
+    'El Paso': 0.0, 
+    'Western': 505.052561}
+DEMAND = {
+    'Arizona': 97.04388686, 
+    'California': 339.16, 
+    'Colorado': 62.97600378, 
+    'Idaho': 38.80448402, 
+    'Montana Western': 14.991087099999998, 
+    'Nevada': 41.88529659, 
+    'New Mexico Western': 19.22651448, 
+    'Oregon': 54.81847715, 
+    'Utah': 34.71460116, 
+    'Washington': 119.16814099999999, 
+    'Wyoming': 18.96577653, 
+    'El Paso': 0.0, 
+    'Western': 841.7542689999999}

postreise/plot/multi/plot_bar.py

@@ -2,8 +2,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
-from collections import OrderedDict
-
 from postreise.plot.multi.constants import ALL_RESOURCE_TYPES, RESOURCE_LABELS
 from postreise.plot.multi.plot_helpers import handle_plot_inputs
 

postreise/plot/multi/plot_helpers.py

@@ -1,11 +1,10 @@
 import pandas as pd
 import matplotlib.pyplot as plt
 
-from collections import OrderedDict
 from postreise.plot.analyze_pg import AnalyzePG as apg
 from powersimdata.scenario.scenario import Scenario
 
-from postreise.plot.multi.constants import ZONES, SCENARIO_RESOURCE_TYPES
+from postreise.plot.multi.constants import ZONES, SCENARIO_RESOURCE_TYPES, BASELINES, CA_BASELINES, TARGETS, CA_TARGETS, DEMAND
 
 # Checks input validity for plotting code, fetches data if necessary
 # param: interconnect: either 'Western' or 'Texas'
@@ -26,7 +25,7 @@ def handle_plot_inputs(interconnect, scenario_ids, custom_data):
     if custom_data == None:
         custom_data = {}
 
-    graph_data = OrderedDict(scenario_data, **custom_data)
+    graph_data = dict(scenario_data, **custom_data)
     return (zone_list, graph_data)
 
 # Checks input validity for shortfall plotting code, fetches data if necessary
@@ -42,9 +41,12 @@ def handle_plot_inputs(interconnect, scenario_ids, custom_data):
 def handle_shortfall_inputs(interconnect, scenario_ids, custom_data, is_match_CA, baselines, targets, demand):
     zone_list, graph_data = handle_plot_inputs(interconnect, scenario_ids, custom_data)
 
-    baselines = _fetch_baselines() if baselines == None else baselines
-    targets = _fetch_targets(is_match_CA) if targets == None else targets
-    demand = _fetch_demand() if demand == None else demand
+    if baselines == None:
+        baselines = CA_BASELINES if is_match_CA else BASELINES
+    if targets == None:
+        targets = CA_TARGETS if is_match_CA else TARGETS
+    if demand == None:
+        demand = DEMAND
 
     return zone_list, graph_data, baselines, targets, demand
 
@@ -59,7 +61,7 @@ def unit_conversion(val, change): return round(val/1000**change, 2)
 # param zone_list: list(string) of zone names 
 # returns: formatted scenario data
 def _get_scenario_data(scenario_ids, zone_list):
-    scenario_data = OrderedDict()
+    scenario_data = dict()
     for id in scenario_ids:
         data_chart, scenario_name = _get_data_chart_from_scenario(id, zone_list)
         scenario_data[id] = _format_scenario_data(data_chart, scenario_name)
@@ -134,22 +136,5 @@ def _get_data_chart_from_csv(file_loc_1, file_loc_2, region, index='(in MW)'):
         data.append(df.to_dict())
 
     return data
-
-# Imports baseline data from a locally stored csv
-def _fetch_baselines():
-    baselines = {} # TODO import from csv
-    return baselines
-
-# Imports target data from a locally stored csv
-def _fetch_targets(is_match_CA):
-    if is_match_CA:
-        targets = {} # TODO import from csv
-    else:
-        targets = {} # TODO import from csv
-    return targets
-
-# Imports demand data from a locally stored csv
-def _fetch_demand():
-    demand = {} # TODO import from csv
-    return demand
+
 

postreise/plot/multi/plot_pie.py

@@ -2,8 +2,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
-from collections import OrderedDict
-
 from postreise.plot.multi.constants import ALL_RESOURCE_TYPES, RESOURCE_LABELS, RESOURCE_COLORS
 from postreise.plot.multi.plot_helpers import handle_plot_inputs
 

postreise/plot/multi/plot_shortfall.py

@@ -2,8 +2,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
-from collections import OrderedDict
-
 from postreise.plot.multi.plot_helpers import handle_shortfall_inputs
 
 # plot_shortfall: Plots any number of scenarios with two columns per scenario
@@ -33,6 +31,8 @@ def plot_shortfall(interconnect, scenario_ids=None, custom_data=None, is_match_C
         _construct_shortfall_visuals(zone, ax_data, shortfall_pct_list, targets[zone], is_match_CA)
     print(f'\nDone\n')
 
+# returns: dictionary of data to visualize { '2016 NREL': {'2016 Renewables': 100, 'Simulated increase in renewables': 30, 'Missed target': 10 }, ...}
+#          and a list of shortfall percentages to show on the graph
 def _construct_shortfall_ax_data(zone, scenarios, is_match_CA, baseline, target, demand):
     ax_data = {}
     shortfall_pct_list = []
@@ -54,36 +54,28 @@ def _construct_shortfall_ax_data(zone, scenarios, is_match_CA, baseline, target,
 
     return ax_data, shortfall_pct_list
 
-def _get_total_generated_renewables(zone, resource_data, is_match_CA):
-    CA_extras = 32045472
-
-    resource_types = ['wind', 'solar', 'geothermal']
-    total_renewables = [resource_data[resource] if resource in resource_data.keys() else 0 for resource in resource_types].sum()
-
-    # Scenario data does not include Extras for California so we add them back in
-    if zone == 'California':
-        total_renewables += CA_extras
-    # Washington's goals also include "clean energy", i.e. nuclear and hydro
-    if zone == 'Washington' and not is_match_CA:
-        total_renewables += resource_data['hydro'] + resource_data['nuclear']
-
-    return total_renewables
-
+# Western has unique needs for data construction
+# there are special rules around calculating shortfall when a scenario is collaborative vs. when it's independent. 
+# returns: dictionary of data to visualize { '2016 NREL': {'2016 Renewables': 100, 'Simulated increase in renewables': 30, 'Missed target': 10 }, ...}
+#          and a list of shortfall percentages to show on the graph
 def _construct_shortfall_data_for_western(scenarios, is_match_CA, has_collaborative_scenarios, baseline, targets, demand):
     ax_data = {}
     shortfall_pct_list = []
 
     for s_id, scenario in scenarios.items():
-        zone_list = scenario['gen']['data'].keys()
-        zone_list.remove('Western')
+        zone_list = list(scenario['gen']['data'].keys())
+        if 'Western' in zone_list:
+            zone_list.remove('Western')
         renewables_by_zone = {zone: _get_total_generated_renewables(zone, scenario['gen']['data'][zone], is_match_CA) for zone in zone_list}
 
-        if s_id in has_collaborative_scenarios:
+        # When states can collaborate they make up for each other's shortfall
+        if has_collaborative_scenarios != None and s_id in has_collaborative_scenarios:
             total_renewables = sum(renewables_by_zone.values())
             shortfall = shortfall = max(0, round(targets['Western'] - total_renewables, 2))
         else: 
             # When the zones do not collaborate, zones with extra renewables can't help zones with shortfall
-            shortfall = sum([max(0, round(targets['Western'] - renewables_by_zone[zone], 2)) for zone in zone_list])
+            # thus the shortfall is the sum of the shortfall from every state
+            shortfall = sum([max(0, round(targets[zone] - renewables_by_zone[zone], 2)) for zone in zone_list])
             # total_renewables here is meaningless in terms of the shortfall so we fudge it to match the target line
             total_renewables = targets['Western'] - shortfall
 
@@ -97,6 +89,23 @@ def _construct_shortfall_data_for_western(scenarios, is_match_CA, has_collaborat
 
     return ax_data, shortfall_pct_list
 
+# returns the sum of all the renewable energy generated in a zone
+def _get_total_generated_renewables(zone, resource_data, is_match_CA):
+    CA_extras = 32.045472
+
+    resource_types = ['wind', 'solar', 'geothermal']
+    total_renewables = sum([resource_data[resource] if resource in resource_data.keys() else 0 for resource in resource_types])
+
+    # Scenario data does not include Extras for California so we add them back in
+    if zone == 'California':
+        total_renewables += CA_extras
+    # Washington's goals also include "clean energy", i.e. nuclear and hydro
+    if zone == 'Washington' and not is_match_CA:
+        resource_types = ['hydro', 'nuclear']
+        total_renewables += sum([resource_data[resource] if resource in resource_data.keys() else 0 for resource in resource_types])
+
+    return total_renewables
+
 def _construct_shortfall_visuals(zone, ax_data, shortfall_pct_list, target, is_match_CA):
         df = pd.DataFrame(ax_data).T
         ax = df.plot.bar(stacked=True, color=['darkgreen', 'yellowgreen', 'salmon'], figsize=(10, 8), fontsize=16)

postreise/plot/multi/test/mock_graph_data.py

@@ -27,7 +27,31 @@
     }
 }
 
+_MORE_MOCK_DATA = {
+    '87': {
+        'Arizona': {'solar': 17.0},
+        'Colorado': {'ng': 12.0, 'solar': 3.0, 'hydro': 10.0},
+        'Oregon': {'wind': 7.0, 'hydro': 5.0},
+        'Western': {'solar': 20.0, 'wind': 7.0, 'ng': 12.0, 'hydro': 15}
+    },
+    '2016_nrel': {
+        'Arizona': {'solar': 15.0},
+        'Colorado': {'ng': 14.0, 'solar': 5.0, 'hydro': 10.0},
+        'Oregon': {'wind': 11.0, 'hydro': 5.0},
+        'Western': {'solar': 20.0, 'wind': 11.0, 'ng': 14.0, 'hydro': 15}
+    }
+}
+
 # Factory for creating mock graph data
-# will eventually have parameters to customize the data returned
-def create_mock_graph_data():
-    return _MOCK_GRAPH_DATA
+# param: more_gen - adds more robust data to mock data generation
+# will eventually have more parameters to customize the data returned
+def create_mock_graph_data(more_gen=False):
+    if more_gen == False: 
+        return _MOCK_GRAPH_DATA
+    else:
+        copy_graph_data = _MOCK_GRAPH_DATA.copy()
+        for scenario, data in _MORE_MOCK_DATA.items():
+            copy_graph_data[scenario]['gen']['data'] = data
+        return copy_graph_data
+
+

postreise/plot/multi/test/test_plot_helpers.py

@@ -1,6 +1,7 @@
 import pytest
+from pprint import pprint
 
-from postreise.plot.multi.constants import ZONES
+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.plot_helpers import handle_plot_inputs, handle_shortfall_inputs, _format_scenario_data, unit_conversion
@@ -14,7 +15,25 @@ def test_handle_plot_inputs():
     assert zone_list == ZONES['Western']
     assert graph_data == mock_graph_data
 
-def test_handle_shortfall_inputs():
+def test_handle_shortfall_inputs_where_is_match_CA_is_false():
+    mock_graph_data = create_mock_graph_data()
+    zone_list, graph_data, baselines, targets, demand = handle_shortfall_inputs('Western', None, mock_graph_data, False, None, None, None)
+    assert zone_list == ZONES['Western']
+    assert graph_data == mock_graph_data
+    assert baselines == BASELINES
+    assert targets == TARGETS
+    assert demand == DEMAND
+
+def test_handle_shortfall_inputs_where_is_match_CA_is_true():
+    mock_graph_data = create_mock_graph_data()
+    zone_list, graph_data, baselines, targets, demand = handle_shortfall_inputs('Western', None, mock_graph_data, True, None, None, None)
+    assert zone_list == ZONES['Western']
+    assert graph_data == mock_graph_data
+    assert baselines == CA_BASELINES
+    assert targets == CA_TARGETS
+    assert demand == DEMAND
+
+def test_handle_shortfall_inputs_with_baseline_target_and_demand_params():
     mock_graph_data = create_mock_graph_data()
     dummy_baselines = {'b': 1}
     dummy_targets = {'t': 2}
@@ -44,3 +63,4 @@ def test_unit_conversion_increase_by_2():
 
 def test_unit_conversion_decrease_by_1():
     assert unit_conversion(0.32, -1) == 320.00
+