Add cop mapping

src/ecotope_package_cs2306/__init__.py

@@ -1,8 +1,8 @@
 from .extract import get_noaa_data, json_to_df, extract_files, get_last_line, get_last_line, extract_new, csv_to_df, get_sub_dirs
-from .transform import rename_sensors, avg_duplicate_times, remove_outliers, ffill_missing, sensor_adjustment, get_energy_by_min, verify_power_energy, aggregate_values, calculate_cop_values, round_time, aggregate_df, join_to_hourly, concat_last_row, join_to_daily, get_temp_zones120, get_storage_gals120
+from .transform import rename_sensors, avg_duplicate_times, remove_outliers, ffill_missing, sensor_adjustment, get_energy_by_min, verify_power_energy, aggregate_values, estimate_cop_values, calculate_cop_values, round_time, aggregate_df, join_to_hourly, concat_last_row, join_to_daily, get_temp_zones120, get_storage_gals120
 from .load import get_login_info, connect_db, check_table_exists, create_new_table, load_database
 from .lbnl import aqsuite_filter_new, site_specific, condensate_calculations, gas_valve_diff, gather_outdoor_conditions, aqsuite_csv_to_df, add_date
 __all__ = ["get_last_line", "set_input", "set_output","get_noaa_data", "json_to_df", "extract_files", "avg_duplicate_times", "remove_outliers", "ffill_missing", "sensor_adjustment", "get_energy_by_min", "verify_power_energy",
-           "set_data", "aggregate_values", "calculate_cop_values", "get_login_info", "connect_db", "check_table_exists", "create_new_table", "createUnknownColumns", "load_database", "rename_sensors", "round_time", "aggregate_df", 
+           "set_data", "aggregate_values", "estimate_cop_values", "calculate_cop_values", "get_login_info", "connect_db", "check_table_exists", "create_new_table", "createUnknownColumns", "load_database", "rename_sensors", "round_time", "aggregate_df", 
            "extract_new", "csv_to_df", "set_config", "get_sub_dirs", "join_to_hourly", "concat_last_row", "join_to_daily", "get_temp_zones120", "get_storage_gals120",  "site_specific", "condensate_calculations", "gas_valve_diff",
            "aqsuite_filter_new", "gather_outdoor_conditions", "aqsuite_csv_to_df", "add_date"]

src/ecotope_package_cs2306/transform.py

@@ -6,8 +6,13 @@
 from dateutil.parser import parse
 from ecotope_package_cs2306.unit_convert import energy_to_power, energy_btu_to_kwh, energy_kwh_to_kbtu
 from ecotope_package_cs2306.config import _input_directory, _output_directory
+import pickle
 
 pd.set_option('display.max_columns', None)
+func_path = os.path.join(os.path.dirname(__file__), 'pickles', 'copFunctionPickle.pkl')
+copFunctionPickle = open(func_path, 'rb')
+copFunction = pickle.load(copFunctionPickle)
+copFunctionPickle.close()
 
 def concat_last_row(df : pd.DataFrame, last_row : pd.DataFrame):
     """
@@ -272,6 +277,11 @@ def aggregate_values(df: pd.DataFrame, thermo_slice: str) -> dict:
 
     return cop_inter
 
+def estimate_cop_values(df: pd.DataFrame) -> pd.DataFrame:
+    cop_mapped = copFunction(df[['Temp_HPWHInlet', 'Temp_HPWHOutlet', 'OAT_HPWH']].values)
+    df['cop_mapped'] = cop_mapped
+    return df
+
 
 def calculate_cop_values(df: pd.DataFrame, heatLoss_fixed: int, thermo_slice: str) -> dict:
     cop_inter = pd.DataFrame()

testing/Bayview/transform/transform_test.py

@@ -1,6 +1,7 @@
 import unittest
 import pandas as pd
-from ecotope_package_cs2306 import rename_sensors, avg_duplicate_times, remove_outliers, ffill_missing, sensor_adjustment, get_energy_by_min, verify_power_energy, calculate_cop_values, round_time, aggregate_df, join_to_hourly, join_to_daily, concat_last_row, get_temp_zones120, get_storage_gals120
+import numpy as np
+from ecotope_package_cs2306 import rename_sensors, avg_duplicate_times, remove_outliers, ffill_missing, sensor_adjustment, get_energy_by_min, verify_power_energy, estimate_cop_values, calculate_cop_values, round_time, aggregate_df, join_to_hourly, join_to_daily, concat_last_row, get_temp_zones120, get_storage_gals120
 
 class Test_Transform(unittest.TestCase):
 
@@ -204,6 +205,15 @@ def test_calculate_cop_values(self):
         self.assertEqual(list(cop_values.columns), list(cop_df.columns))
     """
 
+    #estimate_cop_values(df) - returns estimated cop_values as array
+    def test_estimate_cop_values(self):
+        pruned = pd.read_pickle("testing/Bayview/transform/pickles/pruned_outliers.pkl")
+        estimated_values = pd.read_pickle("testing/Bayview/transform/pickles/estimated_cop.pkl")
+
+        cop_df = estimate_cop_values(pruned)
+
+        np.testing.assert_array_equal(estimated_values['cop_mapped'], cop_df['cop_mapped'])
+
     #aggregate_df(df) - returns hourly_df and daily_df
     def test_aggregate_df_valid(self):
         #NOTE: This is potentially a candidate for extra testing