updated changes from PR review comments

alternative_solar_profiles.py

@@ -48,7 +48,7 @@ class AlternativeSolarProfiles:
 
         num_trials: Number of solar profiles to create
 
-        length_trials: Length of solar profiles in days
+        length_trials: Length of solar profiles in hours
 
         start_year: Start year for solar data download
 
@@ -608,7 +608,7 @@ def create_trial_data(self, start_datetimes=None, validate=True):
             self.state_prob_daily: dataframe holding the probabilities of transition to a
                 given daily state, given the from-state.
             self.num_trials: number of solar profiles to generate
-            self.length_trials: length of profiles in days
+            self.length_trials: length of profiles in hours
 
         outputs:
             self.solar_trials: dict containing a dataframe for each trial
@@ -717,7 +717,7 @@ def generate_trial_date_ranges(self, start_datetimes=None):
             start_datetimes: list of datetime objects. If set as None (default), these are
                 generated randomly.
             self.nrel_data_df: historical solar data
-            self.length_trials: number of days in each trial
+            self.length_trials: number of hours in each trial
             self.num_trials: number of trials to generate
 
         outputs
@@ -727,12 +727,12 @@ def generate_trial_date_ranges(self, start_datetimes=None):
 
         # Randomly generate start times for each trial
         if start_datetimes is None:
-            start_datetimes = self.nrel_data_df.iloc[:-self.length_trials * 24].sample(
+            start_datetimes = self.nrel_data_df.iloc[:-self.length_trials].sample(
                 self.num_trials)['datetime'].values
 
         # Create a date range object for each start datetime
         date_ranges = [pd.date_range(start=start_date,
-                                     periods=self.length_trials * 24,
+                                     periods=self.length_trials,
                                      freq='H')
                        for start_date in start_datetimes]
 
@@ -805,7 +805,7 @@ def generate_random_state_daily(self, date_range):
 
         inputs:
             date_range: datetimeindex object for the trial
-            self.length_trials: length of profiles in days
+            self.length_trials: length of profiles in hours
             self.state_prob_daily_grouped: dataframe holding the probabilities of transition
                 to a given daily state, given the from-state, grouped by month and from-state.
             self.simple_prob_daily_grouped: dataframe holding the probabilities of
@@ -979,7 +979,7 @@ def generate_random_state_hourly(self, hourly_date_range, night_states,
             night_states: list containing a Boolean indicating if it is night-time for each
                 hour in the day
             current_state: array with hourly state from previous hour
-            self.length_trials: length of profiles in days
+            self.length_trials: length of profiles in hours
             self.nrel_data_df: historical solar data
             self.state_prob_hourly_grouped: dataframe holding the probabilities of transition
                 to a given daily state, given the from-state, grouped by month, hour,

generate_solar_profile.py

@@ -90,7 +90,7 @@ class SolarProfileGenerator:
     
         num_trials: Number of solar profiles to create
     
-        length_trials: Length of solar profiles in days
+        length_trials: Length of solar profiles in hours
 
         pv_racking: Type of pv racking (options: [roof, ground, carport])
             Default = ground
@@ -545,7 +545,7 @@ def get_power_profiles_from_upload(self, annual_production, temperature=None,
 
         # Create a date range object for each start datetime
         date_ranges = [pd.date_range(start=start_date,
-                                     periods=self.length_trials * 24,
+                                     periods=self.length_trials,
                                      freq='H')
                        for start_date in start_datetimes]
 

main_files/main.py

@@ -117,6 +117,8 @@ def run_mcor(input_dict):
     # Go back to main working directory
     os.chdir('..')
 
+    days_to_hours = 24
+
     # Define parameters and populate dict for run_mcor()
     input_dict = {}
 
@@ -127,7 +129,7 @@ def run_mcor(input_dict):
     input_dict["system_inputs"]["timezone"] = 'US/Pacific'
     input_dict["system_inputs"]["altitude"] = 0
     input_dict["system_inputs"]["num_trials"] = 200
-    input_dict["system_inputs"]["length_trials"] = 14
+    input_dict["system_inputs"]["length_trials"] = 14 * days_to_hours
 
     # PV dictionary
     input_dict["pv_inputs"] = {}

tests/system_tests/parameter_test.py

@@ -556,6 +556,7 @@ def test_lat_long_changes(self):
         # Check that for different latitude and longitude, pv and battery sizes are different
         self.latitude = self.latitude + 5
         self.longitude = self.longitude - 3
+        self.length_trials = self.length_trials * 24
         optim = self.run_main(generate_solar_data=True, generate_solar_profiles=True)
         self.compare_series('pv_capacity', 'not_equal', optim)
         self.compare_series('battery_capacity', 'not_equal', optim)
@@ -565,6 +566,7 @@ def test_solar_source(self):
         #   error
         self.latitude = -18.04
         self.longitude = 178.04
+        self.length_trials = self.length_trials * 24
         self.timezone = 'Pacific/Fiji'
         self.solar_source = 'himawari'
         self.solar_data_start_year = 2016

tests/unit_tests/test_asp.py

@@ -92,7 +92,7 @@ def setUp(self) -> None:
         self.asp = AlternativeSolarProfiles(latitude=46.34,
                                             longitude=-119.28,
                                             num_trials=10,
-                                            length_trials=3)
+                                            length_trials=3 * 24)
 
     def tearDown(self) -> None:
         """Runs after each test"""
@@ -375,7 +375,7 @@ def test_generate_trial_date_ranges(self):
 
         # for each date range assert they have the appropriate number of
         #   datetime objects and that they are that many hours apart
-        range_length = self.asp.length_trials * 24
+        range_length = self.asp.length_trials
         for date_range in test_ranges:
             self.assertEqual(len(date_range), range_length)
             first_hour = date_range[0]
@@ -466,7 +466,7 @@ def test_generate_random_state_daily(self):
             self.load_daily_grouped_probabilities()
 
         # create date_range to generate random states for
-        range_length = self.asp.length_trials * 24
+        range_length = self.asp.length_trials
         date_range = pd.date_range(start='2009-02-09 15:00:00', periods=range_length,
                                    freq='H')
 
@@ -605,7 +605,7 @@ def test_compare_hourly_daily_states(self):
         daily_state.index = daily_state.index.date
 
         # create date_range to generate random states for
-        range_length = self.asp.length_trials * 24
+        range_length = self.asp.length_trials
         date_range = pd.date_range(start='2009-02-09 15:00:00', periods=range_length,
                                    freq='H')
 
@@ -676,4 +676,4 @@ def test_create_trial_data(self, fake_preprocess):
     asp = AlternativeSolarProfiles(latitude=46.34,
                                    longitude=-119.28,
                                    num_trials=10,
-                                   length_trials=3)
+                                   length_trials=3)