updated main.py file for new config

energy_demand/main.py

@@ -7,6 +7,7 @@
     Examples
     python energy_demand/energy_demand/main.py C:/Users/cenv0553/ed/energy_demand/local_run_config_file.ini test_run
     python energy_demand/energy_demand/main.py C:/Users/cenv0553/ed/energy_demand/local_run_config_file.ini h_max NF1 h_max
+
 """
 import os
 import sys
@@ -167,10 +168,10 @@ def energy_demand_model(
     data['enduses'], data['sectors'], data['fuels'], lookup_enduses, lookup_sector_enduses = data_loader.load_fuels(data['paths'])
     data['regions'] = read_data.get_region_names(name_region_set)
     data['reg_coord'] = basic_functions.get_long_lat_decimal_degrees(read_data.get_region_centroids(name_region_set))
-
-    data['scenario_data']['population'] = data_loader.read_scenario_data(name_population_dataset)
-    data['scenario_data']['gva_industry'] = data_loader.read_scenario_data_gva(name_gva_dataset, all_dummy_data=False)
-    data['scenario_data']['gva_per_head'] = data_loader.read_scenario_data(name_gva_dataset_per_head)
+    print("AA " + str(name_gva_dataset))
+    data['scenario_data']['population'] = data_loader.read_scenario_data(name_population_dataset, region_name='lad_uk_2016', value_name='population')
+    data['scenario_data']['gva_industry'] = data_loader.read_scenario_data_gva(name_gva_dataset, region_name='lad_uk_2016', value_name='gva_per_head', all_dummy_data=False)
+    data['scenario_data']['gva_per_head'] = data_loader.read_scenario_data(name_gva_dataset_per_head, region_name='lad_uk_2016', value_name='gva_per_head')
 
     # -----------------------------
     # Assumptions

energy_demand/read_write/data_loader.py

@@ -1262,7 +1262,7 @@ def ss_read_shapes_enduse_techs(ss_shapes_dh, ss_shapes_yd):
 
     return ss_all_tech_shapes_dh, ss_all_tech_shapes_yd
 
-def read_scenario_data(path_to_csv):
+def read_scenario_data(path_to_csv, value_name='value', region_name='region'):
     """
     """
     data = {}
@@ -1275,9 +1275,9 @@ def read_scenario_data(path_to_csv):
         headings = next(rows)  # Skip first row
         for row in rows:
 
-            region = str(row[read_data.get_position(headings, 'region')])
+            region = str(row[read_data.get_position(headings, region_name)])
             year = int(float(row[read_data.get_position(headings, 'timestep')]))
-            value = float(row[read_data.get_position(headings, 'value')])
+            value = float(row[read_data.get_position(headings, value_name)])
 
             try:
                 data[year][region] = value
@@ -1287,7 +1287,7 @@ def read_scenario_data(path_to_csv):
 
     return data
 
-def read_scenario_data_gva(path_to_csv, all_dummy_data=False):
+def read_scenario_data_gva(path_to_csv, region_name='region', value_name='value', all_dummy_data=False):
     """Function to read in GVA locally
 
     IF no value, provide with dummy value "1"
@@ -1306,9 +1306,8 @@ def read_scenario_data_gva(path_to_csv, all_dummy_data=False):
             # All dummy data
             # --------------
             if all_dummy_data:
-                region = str(row[read_data.get_position(headings, 'region')])
+                region = str(row[read_data.get_position(headings, region_name)])
                 for year_dummy in range(2015, 2051):
-
                     for sector_dummy in range(1, 47):
                         dummy_sector_value = 1
 
@@ -1320,15 +1319,15 @@ def read_scenario_data_gva(path_to_csv, all_dummy_data=False):
 
             else:
                 if row[read_data.get_position(headings, 'timestep')] == '': #No data provided
-                    region = str(row[read_data.get_position(headings, 'region')])
+                    region = str(row[read_data.get_position(headings, region_name)])
                     for year_dummy in range(2015, 2051):
                         for sector_dummy in range(1, 47):
                             dummy_sector_value = 1
                             out_dict[year_dummy][region][sector_dummy] = dummy_sector_value
                 else:
-                    region = str(row[read_data.get_position(headings, 'region')])
+                    region = str(row[read_data.get_position(headings, region_name)])
                     year = int(float(row[read_data.get_position(headings, 'timestep')]))
-                    value = float(row[read_data.get_position(headings, 'value')])
+                    value = float(row[read_data.get_position(headings, value_name)])
                     economic_sector__gor = float(row[read_data.get_position(headings, 'economic_sector__gor')])
                 try:
                     out_dict[year][region][economic_sector__gor] = value

energy_demand/scripts/s_post_installation.py

@@ -71,7 +71,7 @@ def post_install_setup(args):
         basic_functions.create_folder(folder)
 
     print("... Read in residential submodel load profiles", flush=True)
-    s_rs_raw_shapes.run(
+    '''s_rs_raw_shapes.run(
         data['paths'],
         data['local_paths'],
         base_yr)
@@ -83,7 +83,7 @@ def post_install_setup(args):
         data['lookups'])
 
     # Input data preparation
-    print("Generate additional data", flush=True)
+    print("Generate additional data", flush=True)'''
 
     # Extract NISMOD population data
     path_to_zip_file = os.path.join(local_data_path,"population-economic-smif-csv-from-nismod-db.zip")
@@ -98,9 +98,8 @@ def post_install_setup(args):
     geography_name = "lad_uk_2016"
 
     # All MISTRAL scenarios to prepare with correct config
-    scenarios_to_generate = [
-        'pop-baseline16_econ-c16_fuel-c16'
-    ]
+    scenarios_to_generate = ['pop-baseline16_econ-c16_fuel-c16']
+    #scenarios_to_generate = []
 
     script_data_preparation_MISTRAL_pop_gva.run(
         path_to_folder=data_pop,

energy_demand/scripts/smif_data_related/script_data_preparation_MISTRAL_pop_gva.py

@@ -211,9 +211,8 @@ def run(
         break
 
     for folder_name in all_csv_folders:
-
         all_files = os.listdir(os.path.join(path_to_folder, folder_name))
-        if folder_name in scenarios_to_generate:
+        if (scenarios_to_generate == []) or (folder_name in scenarios_to_generate):
             print("folder name: " + str(folder_name), flush=True)
             for file_name in all_files:
                 filename_split = file_name.split("__")

energy_demand/wrapper_model.py

@@ -137,7 +137,10 @@ def load_data_before_simulation(
         name_population_dataset = config['DATA_PATHS']['path_population_data_for_disaggregation_msoa']
     else:
         name_population_dataset = config['DATA_PATHS']['path_population_data_for_disaggregation_lad']
-    data['pop_for_disag'] = data_loader.read_scenario_data(name_population_dataset)
+    data['pop_for_disag'] = data_loader.read_scenario_data(
+        name_population_dataset,
+        region_name='lad_uk_2016', 
+        value_name='population')
 
     # ------------------------------------------------
     # Load building related data