cleaning

energy_demand/cli/__init__.py

@@ -74,7 +74,9 @@ def run_model(args):
 
     data['weather_stations'], data['temp_data'] = data_loader.load_temp_data(data['local_paths'])
 
-    data['rs_floorarea'], data['ss_floorarea'] = data_loader.virtual_building_datasets(data['lu_reg'], data['sectors']['all_sectors'], data)
+    data['rs_floorarea'], data['ss_floorarea'] = data_loader.virtual_building_datasets(
+        data['lu_reg'], data['sectors']['all_sectors'], 
+        data['local_paths'])
 
     rs_floorarea = defaultdict(dict)
     for year in range(2015, 2101):

energy_demand/main.py

@@ -119,7 +119,8 @@ def energy_demand_model(data, fuel_in=0, fuel_in_elec=0):
     data['sim_param']['base_yr'] = 2015
     data['sim_param']['curr_yr'] = data['sim_param']['base_yr']
     data['sim_param']['simulated_yrs'] = [2015, 2050]
-    data['lu_reg'] = data_loader.load_LAC_geocodes_info(data['local_paths']['path_dummy_regions'])
+
+    data['lu_reg'] = data_loader.load_LAC_geocodes_info(os.path.join(local_data_path, '_raw_data', 'B-census_data', 'regions_local_area_districts', '_quick_and_dirty_spatial_disaggregation', 'infuse_dist_lyr_2011_saved.csv'))
 
     # GVA
     gva_data = {}
@@ -170,7 +171,7 @@ def energy_demand_model(data, fuel_in=0, fuel_in_elec=0):
         rs_floorarea, ss_floorarea = data_loader.virtual_building_datasets(
             data['lu_reg'],
             data['sectors']['all_sectors'],
-            data)
+            data['local_paths'])
     else:
         pass
 

energy_demand/profiles/hdd_cdd.py

@@ -339,6 +339,8 @@ def calc_reg_hdd(temperatures, t_base_heating, model_yeardays):
         Temperatures
     t_base_heating : float
         Base temperature for heating
+    model_yeardays : dict
+        Modelled yeardays
 
     Return
     ------

energy_demand/profiles/load_factors.py

@@ -152,9 +152,7 @@ def calc_lf_season(seasons, fuel_region_yh, average_fuel_yd):
     """
     seasons_lfs = {}
     for season, yeardays_modelled in seasons.items():
-        #max_load_yd_season = np.max(fuel_region_yh[:, yeardays_modelled])
 
-        #average_fuel_yd_season = np.average(average_fuel_yd[:, yeardays_modelled], axis=1)
         average_fuel_yd_full_year = np.average(average_fuel_yd[:, ], axis=1)
 
         # Calculate maximum hour in year
@@ -163,7 +161,6 @@ def calc_lf_season(seasons, fuel_region_yh, average_fuel_yd):
 
         # Unable local RuntimeWarning: divide by zero encountered
         with np.errstate(divide='ignore', invalid='ignore'):
-            #season_lf = (average_fuel_yd_season / max_load_h_season) * 100 #convert to percentage
             season_lf = (average_fuel_yd_full_year / max_load_h_season) * 100 #convert to percentage
 
         # Replace

energy_demand/profiles/load_profile.py

@@ -35,17 +35,19 @@ def add_lp(
         """Add load profile to stock
 
         Arguments
-        ----------
+        ---------
+        unique_identifier : str
+            Name (unique identifier)
         technologies : list
             Technologies for which the profile applies
         enduses : list
             Enduses for which the profile applies
-        sectors : list
-            Sectors for which the profile applies
         shape_yd : array
             Shape yd (from year to day)
         shape_yh : array
             Shape yh (from year to hour)
+        sectors : list, default=False
+            Sectors for which the profile applies
         enduse_peak_yd_factor : float
             Factor to calculate daily demand from yearly demand
             Standard value is average daily amount
@@ -97,7 +99,7 @@ def get_lp(self, enduse, sector, technology, shape):
 
         Return
         ------
-        Load profile
+        Load profile attribute
         """
         # Get key from lookup dict
         position_in_dict = self.dict_tuple_keys[(enduse, sector, technology)]
@@ -155,6 +157,11 @@ def generate_key_lu_dict(dict_tuple_keys, unique_identifier, enduses, sectors, t
         List with sectors
     technologies : list
         List with technologies
+
+    Returns
+    -------
+    dict_tuple_keys : str
+        Lookup position in dict
     """
     for enduse in enduses:
         for sector in sectors:
@@ -171,6 +178,11 @@ def get_stock_enduses(load_profile_dict):
     ---------
     load_profile_dict : dict
         All load profiles of load profile stock
+
+    Returns
+    ------
+    all_enduses : list
+        All enduses in stock
     """
     all_enduses = set([])
     for profile_obj in load_profile_dict.values():

energy_demand/read_and_plot_results.py

@@ -48,7 +48,7 @@ def main(path_data_energy_demand):
 
     # Read scenario data
     data['scenario_data'] = {}
-    data['scenario_data']['population'] = read_data.read_pop(
+    data['scenario_data']['population'] = read_data.read_scenaric_population_data(
         os.path.join(data['local_paths']['data_results'], 'model_run_pop'))
 
     # --------------------------------------------

energy_demand/read_write/data_loader.py

@@ -12,8 +12,56 @@
 from energy_demand.basic import conversions
 from energy_demand.basic import date_prop
 
+def load_basic_lookups():
+    """Definition of basic lookups or other related information
+
+    Return
+    ------
+    lookups : dict
+        Lookup information and other very basic properties
+    """
+    lookups = {}
+
+    lookups['dwtype'] = {
+        0: 'detached',
+        1: 'semi_detached',
+        2: 'terraced',
+        3: 'flat',
+        4: 'bungalow'}
+
+    lookups['fueltype'] = {
+        'solid_fuel': 0,
+        'gas': 1,
+        'electricity': 2,
+        'oil': 3,
+        'biomass': 4,
+        'hydrogen': 5,
+        'heat': 6}
+
+    lookups['fueltypes_nr'] = int(len(lookups['fueltype']))
+
+    return lookups
+
 def load_sim_param_ini(path):
     """Load simulation parameter run information
+
+    Arguments
+    ---------
+    path : str
+        Path to `ini` file
+
+    Returns
+    -------
+    sim_param : dict
+        Simulation parameters
+    enduses : dict
+        Enduses
+    assumptions : dict
+        Assumptions
+    reg_nrs : dict
+        Number of regions
+    lu_reg : dict
+        Regions
     """
     config = configparser.ConfigParser()
 
@@ -66,9 +114,7 @@ def read_national_real_elec_data(path_to_csv):
         for row in read_lines:
             geocode = str.strip(row[2])
             tot_consumption_unclean = row[7].strip()
-            total_consumption = float(tot_consumption_unclean.replace(",", ""))
-
-            national_fuel_data[geocode] = total_consumption
+            national_fuel_data[geocode] = float(tot_consumption_unclean.replace(",", ""))
 
     return national_fuel_data
 
@@ -111,51 +157,30 @@ def read_national_real_gas_data(path_to_csv):
 
     return national_fuel_data
 
-def load_basic_lookups():
-    """Definition of basic lookups or other related information
-
-    Return
-    ------
-    lookups : dict
-        Lookup information and other very basic properties
-    """
-    lookups = {}
-
-    lookups['dwtype'] = {
-        0: 'detached',
-        1: 'semi_detached',
-        2: 'terraced',
-        3: 'flat',
-        4: 'bungalow'}
-
-    lookups['fueltype'] = {
-        'solid_fuel': 0,
-        'gas': 1,
-        'electricity': 2,
-        'oil': 3,
-        'biomass': 4,
-        'hydrogen': 5,
-        'heat': 6
-        }
-
-    lookups['fueltypes_nr'] = int(len(lookups['fueltype']))
-
-    return lookups
-
-def virtual_building_datasets(lu_reg, all_sectors, data):
+def virtual_building_datasets(lu_reg, all_sectors, local_paths):
     """Load necessary data for virtual building stock
     in case the link to the building stock model in
     Newcastle is not used
 
     Arguments
     ---------
+    lu_reg : dict
+        Regions
+    all_sectors : dict
+        All sectors
 
+    Returns
+    -------
+    rs_floorarea : dict
+        Residential floor area
+    ss_floorarea : dict
+        Service sector floor area
     """
     # --------------------------------------------------
     # Floor area for residential buildings for base year
     # --------------------------------------------------
     resid_footprint, non_res_flootprint = read_data.read_floor_area_virtual_stock(
-        data['local_paths']['path_floor_area_virtual_stock_by'])
+        local_paths['path_floor_area_virtual_stock_by'])
 
     rs_floorarea = defaultdict(dict)
     for year in range(2015, 2101):
@@ -166,12 +191,6 @@ def virtual_building_datasets(lu_reg, all_sectors, data):
                 logging.warning("No virtual residential floor area for region %s %s", reg_geocode, year)
                 rs_floorarea[year][reg_geocode] = 1
 
-    '''
-    rs_floorarea = defaultdict(dict)
-    for year in range(2015, 2101):
-        for region_geocode in lu_reg:
-            rs_floorarea[year][region_geocode] = 10000
-    '''
     # --------------------------------------------------
     # Floor area for service sector buildings
     # --------------------------------------------------
@@ -229,10 +248,8 @@ def load_local_paths(path):
             path, '_raw_data', 'D-validation', '02_subnational_gas_demand', 'data_2015_gas.csv'),
         'path_employment_statistics': os.path.join(
             path, '_raw_data', 'b-census_data', 'employment_statistics_2011_LAD', 'LAD_prior_2015.csv'),
-        'path_floor_area_virtual_stock_by': os.path.join( #TODO
+        'path_floor_area_virtual_stock_by': os.path.join(
             path, '_raw_data', 'K-floor_area', 'floor_area_by.csv'),
-        'path_dummy_regions': os.path.join(
-            path, '_raw_data', 'B-census_data', 'regions_local_area_districts', '_quick_and_dirty_spatial_disaggregation', 'infuse_dist_lyr_2011_saved.csv'),
         'path_assumptions_db': os.path.join(
             path, '_processed_data', 'assumptions_from_db'),
         'data_processed': os.path.join(
@@ -261,7 +278,7 @@ def load_local_paths(path):
             path, '_processed_data', '_post_installation_data', 'load_profiles', 'rs_submodel'),
         'ss_load_profiles': os.path.join(
             path, '_processed_data', '_post_installation_data', 'load_profiles', 'ss_submodel'),
-        'dir_disattregated': os.path.join(
+        'dir_disaggregated': os.path.join(
             path, '_processed_data', '_post_installation_data', 'disaggregated'),
         'rs_load_profile_txt': os.path.join(
             path, '_processed_data', '_post_installation_data', 'load_profiles', 'rs_submodel'),
@@ -292,7 +309,6 @@ def load_paths(path):
         Data container containing dics
     """
     paths = {
-
         'path_main': path,
 
         # Path for dwelling stock assumptions
@@ -326,6 +342,7 @@ def load_paths(path):
             path, 'config_data', 'submodel_service', 'capacity_installations.csv'),
         'is_path_capacity_installation': os.path.join(
             path, 'config_data', 'submodel_industry', 'capacity_installations.csv'),
+
         # Paths to fuel raw data
         'rs_fuel_raw_data_enduses': os.path.join(
             path, 'config_data', 'submodel_residential', 'rs_fuel_data.csv'),
@@ -360,8 +377,9 @@ def load_data_tech_profiles(tech_lp, paths):
 
     Arguments
     ----------
-    data : dict
-        Data container
+    tech_lp : dict
+        Load profiles
+    paths : dict
 
     Returns
     ------

energy_demand/read_write/read_data.py

@@ -959,6 +959,18 @@ def read_disaggregated_fuel(path_to_csv, fueltypes_nr):
 
 def read_disaggregated_fuel_sector(path_to_csv, fueltypes_nr):
     """Read disaggregated fuel
+
+    Arguments
+    ----------
+    path_to_csv : str
+        Path to csv file
+    fueltypes_nr : int
+        Nr of fueltypes
+
+    Returns
+    -------
+    fuel_sector_enduse : dict
+        Disaggregated fuel
     """
     fuel_sector_enduse = {}
 
@@ -1045,8 +1057,19 @@ def read_lf_y(path_enduse_specific_results):
 
     return dict(results)
 
-def read_pop(path_enduse_specific_results):
-    """Read load factors from txt file
+def read_scenaric_population_data(path_enduse_specific_results):
+    """Read population data
+
+    Arguments
+    ---------
+    path_enduse_specific_results : str
+        Path
+
+    Returns
+    -------
+    results : dict
+        Population, {year: np.array(fueltype, regions)}
+
     """
     results = defaultdict(dict)
 

energy_demand/scripts/s_disaggregation.py

@@ -661,13 +661,13 @@ def run(data):
 
     #Write to csv file disaggregated demand
     write_disagg_fuel(
-        os.path.join(data['local_paths']['dir_disattregated'], 'rs_fuel_disagg.csv'),
+        os.path.join(data['local_paths']['dir_disaggregated'], 'rs_fuel_disagg.csv'),
         rs_fuel_disagg)
     write_disagg_fuel_sector(
-        os.path.join(data['local_paths']['dir_disattregated'], 'ss_fuel_disagg.csv'),
+        os.path.join(data['local_paths']['dir_disaggregated'], 'ss_fuel_disagg.csv'),
         ss_fuel_disagg)
     write_disagg_fuel_sector(
-        os.path.join(data['local_paths']['dir_disattregated'], 'is_fuel_disagg.csv'),
+        os.path.join(data['local_paths']['dir_disaggregated'], 'is_fuel_disagg.csv'),
         is_fuel_disagg)
 
     logging.debug("... finished script %s", os.path.basename(__file__))

energy_demand/scripts/s_post_installation.py

@@ -76,7 +76,7 @@ def post_install_setup(args):
     basic_functions.create_folder(data['local_paths']['load_profiles'])
     basic_functions.create_folder(data['local_paths']['rs_load_profiles'])
     basic_functions.create_folder(data['local_paths']['ss_load_profiles'])
-    basic_functions.create_folder(data['local_paths']['dir_disattregated'])
+    basic_functions.create_folder(data['local_paths']['dir_disaggregated'])
 
     # Read in temperature data from raw files
     s_raw_weather_data.run(data)

run.py

@@ -148,7 +148,7 @@ def before_model_run(self, data=None):
         # Get building related data
         if data['criterias']['virtual_building_stock_criteria']:
             rs_floorarea, ss_floorarea = data_loader.virtual_building_datasets(
-                data['lu_reg'], data['sectors']['all_sectors'], data)
+                data['lu_reg'], data['sectors']['all_sectors'], data['local_paths'])
         else:
             pass
             # Load floor area from newcastle