finished refactoring

energy_demand/enduse_func.py

@@ -8,7 +8,6 @@
 """
 import logging
 import numpy as np
-
 from energy_demand.initalisations import helpers
 from energy_demand.profiles import load_profile as lp
 from energy_demand.profiles import load_factors as lf
@@ -56,12 +55,8 @@ class Enduse(object):
         Distribution of fuel within year to days (yd) (directly correlates with HDD)
     cooling_factor_y : array
         Distribution of fuel within year to days (yd) (directly correlates with CDD)
-    fuel_switches : list
-        Fuel switches
     service_switches : list
         Service switches
-    capacity_switches : list
-        Capacity switches
     fuel_tech_p_by : dict
         Fuel tech assumtions in base year
     tech_increased_service : dict
@@ -70,8 +65,6 @@ class Enduse(object):
         Technologies per enduse with decreased service due to scenarios
     tech_constant_share : dict
         Technologies per enduse with constat service
-    installed_tech : dict
-        Installed technologes for this enduse
     sig_param_tech : dict
         Sigmoid parameters
     enduse_overall_change : dict
@@ -417,6 +410,9 @@ def assign_lp_no_techs(enduse, sector, load_profiles, fuel_new_y):
 
     Returns
     -------
+    fuel_yh
+    fuel_peak_dh
+    fuel_peak_h
     """
     _fuel = fuel_new_y[:, np.newaxis, np.newaxis]
 

energy_demand/geography/spatial_diffusion.py

@@ -1,7 +1,7 @@
 """This file calculates spatial diffusion index
 """
-import numpy as np
 from collections import defaultdict
+import numpy as np
 
 def load_spatial_diff_values(regions, enduses):
     """Load or calculate spatial diffusion values

energy_demand/main.py

@@ -119,7 +119,7 @@ def energy_demand_model(data, fuel_in=0, fuel_in_elec=0):
     data['criterias']['mode_constrained'] = False
     data['criterias']['plot_HDD_chart'] = False
     data['criterias']['virtual_building_stock_criteria'] = virtual_building_stock_criteria
-    data['criterias']['spatial_exliclit_diffusion'] = False
+    data['criterias']['spatial_exliclit_diffusion'] = True
 
     data['paths'] = data_loader.load_paths(path_main)
     data['local_paths'] = data_loader.load_local_paths(local_data_path)

energy_demand/scripts/init_scripts.py

@@ -3,7 +3,6 @@
 """
 import os
 import logging
-from collections import defaultdict
 import numpy as np
 from energy_demand.read_write import data_loader
 from energy_demand.scripts import s_fuel_to_service
@@ -32,6 +31,7 @@ def scenario_initalisation(path_data_ed, data=False):
     sgs_cont = {}
     fts_cont = {}
     sd_cont = {}
+    switches_cont = {}
 
     logger_setup.set_up_logger(os.path.join(path_data_ed, "scenario_init.log"))
 
@@ -43,7 +43,6 @@ def scenario_initalisation(path_data_ed, data=False):
         data['local_paths']['data_processed'],
         data['local_paths']['path_post_installation_data'])
     basic_functions.del_previous_setup(data['local_paths']['data_results'])
-
     basic_functions.create_folder(data['local_paths']['data_results'])
     basic_functions.create_folder(data['local_paths']['dir_services'])
     basic_functions.create_folder(data['local_paths']['path_sigmoid_data'])
@@ -88,35 +87,34 @@ def scenario_initalisation(path_data_ed, data=False):
         data['assumptions']['technologies'])
 
     # Service
-    ss_fuels_aggregated_across_sectors = s_fuel_to_service.sum_fuel_enduse_sectors(
+    ss_aggr_sector_fuels = s_fuel_to_service.sum_fuel_enduse_sectors(
         data['fuels']['ss_fuel_raw_data_enduses'],
         data['enduses']['ss_all_enduses'],
         data['lookups']['fueltypes_nr'])
     fts_cont['ss_service_tech_by_p'], fts_cont['ss_service_fueltype_tech_by_p'], fts_cont['ss_service_fueltype_by_p'] = s_fuel_to_service.get_service_fueltype_tech(
         data['assumptions']['tech_list'],
         data['lookups']['fueltype'],
         data['assumptions']['ss_fuel_tech_p_by'],
-        ss_fuels_aggregated_across_sectors,
+        ss_aggr_sector_fuels,
         data['assumptions']['technologies'])
 
     # Industry
-    is_fuels_aggregated_across_sectors = s_fuel_to_service.sum_fuel_enduse_sectors(
+    is_aggr_sector_fuels = s_fuel_to_service.sum_fuel_enduse_sectors(
         data['fuels']['is_fuel_raw_data_enduses'],
         data['enduses']['is_all_enduses'],
         data['lookups']['fueltypes_nr'])
     fts_cont['is_service_tech_by_p'], fts_cont['is_service_fueltype_tech_by_p'], fts_cont['is_service_fueltype_by_p'] = s_fuel_to_service.get_service_fueltype_tech(
         data['assumptions']['tech_list'],
         data['lookups']['fueltype'],
         data['assumptions']['is_fuel_tech_p_by'],
-        is_fuels_aggregated_across_sectors,
+        is_aggr_sector_fuels,
         data['assumptions']['technologies'])
 
     # ------------------------------------
     # Autocomplement defined service switches
     # with technologies not explicityl specified in switch
     # on a national scale
     # ------------------------------------
-    switches_cont = {}
     switches_cont['rs_service_switches'] = fuel_service_switch.autocomplete_switches(
         data['assumptions']['rs_service_switches'],
         data['assumptions']['rs_specified_tech_enduse_by'],
@@ -149,7 +147,7 @@ def scenario_initalisation(path_data_ed, data=False):
         data['assumptions']['capacity_switches']['ss_capacity_switches'],
         data['assumptions']['technologies'],
         data['assumptions']['enduse_overall_change']['other_enduse_mode_info'],
-        ss_fuels_aggregated_across_sectors,
+        ss_aggr_sector_fuels,
         data['assumptions']['ss_fuel_tech_p_by'],
         data['sim_param']['base_yr'])
 
@@ -158,7 +156,7 @@ def scenario_initalisation(path_data_ed, data=False):
         data['assumptions']['capacity_switches']['is_capacity_switches'],
         data['assumptions']['technologies'],
         data['assumptions']['enduse_overall_change']['other_enduse_mode_info'],
-        is_fuels_aggregated_across_sectors,
+        is_aggr_sector_fuels,
         data['assumptions']['is_fuel_tech_p_by'],
         data['sim_param']['base_yr'])
 
@@ -180,23 +178,14 @@ def scenario_initalisation(path_data_ed, data=False):
     # Calculate sigmoid diffusion parameters
     # (either for every region or aggregated for all regions)
     # -------------------------------
-    sgs_cont['rs_sig_param_tech'] = {}
-    sgs_cont['rs_tech_increased_service'] = {}
-    sgs_cont['rs_tech_decreased_share'] = {}
-    sgs_cont['rs_tech_constant_share'] = {}
-    sgs_cont['rs_service_switch'] = {}
-
-    sgs_cont['ss_sig_param_tech'] = {}
-    sgs_cont['ss_tech_increased_service'] = {}
-    sgs_cont['ss_tech_decreased_share'] = {}
-    sgs_cont['ss_tech_constant_share'] = {}
-    sgs_cont['ss_service_switch'] = {}
-
-    sgs_cont['is_sig_param_tech'] = {}
-    sgs_cont['is_tech_increased_service'] = {}
-    sgs_cont['is_tech_decreased_share'] = {}
-    sgs_cont['is_tech_constant_share'] = {}
-    sgs_cont['is_service_switch'] = {}
+    key_to_init = [
+        'rs_sig_param_tech', 'rs_tech_increased_service', 'rs_tech_decreased_share', 'rs_tech_constant_share',
+        'rs_service_switch', 'ss_sig_param_tech', 'ss_tech_increased_service', 'ss_tech_decreased_share',
+        'ss_tech_constant_share', 'ss_service_switch', 'is_sig_param_tech', 'is_tech_increased_service',
+        'is_tech_decreased_share', 'is_tech_constant_share', 'is_service_switch']
+
+    for key_name in key_to_init:
+        sgs_cont[key_name] = {}
 
     if data['criterias']['spatial_exliclit_diffusion']:
 

energy_demand/scripts/s_fuel_to_service.py

@@ -72,16 +72,30 @@ def sum_2_level_dict(two_level_dict):
 
     return tot_sum
 
-def sum_fuel_enduse_sectors(ss_fuel_raw_data_enduses, ss_enduses, nr_fueltypes):
+def sum_fuel_enduse_sectors(data_enduses, enduses, nr_fueltypes):
     """Aggregated fuel for all sectors according to enduse
+
+    Arguments
+    --------
+    data_enduses : dict
+        Fuel per enduse
+    enduses : list
+        Enduses
+    nr_fueltypes : int
+        Number of fuetlypes
+
+    Returns
+    -------
+    aggregated_fuel_enduse : dict
+        Arregated fuel per enduse ({enduse: np.array(fueltype)})
     """
     aggregated_fuel_enduse = {}
 
-    for enduse in ss_enduses:
+    for enduse in enduses:
         aggregated_fuel_enduse[str(enduse)] = np.zeros((nr_fueltypes), dtype=float)
 
     # Iterate and sum fuel per enduse
-    for fuels_sector in ss_fuel_raw_data_enduses.values():
+    for fuels_sector in data_enduses.values():
         for enduse, fuels_enduse in fuels_sector.items():
             aggregated_fuel_enduse[enduse] += fuels_enduse
 

energy_demand/scripts/s_generate_sigmoid.py

@@ -279,6 +279,9 @@ def calc_service_fuel_switched(
     ):
     """Calculate energy service demand percentages after fuel switches
 
+
+    TODO CLEAN AN IMPROVE
+
     Arguments
     ----------
     enduse_fuel_switches : dict
@@ -330,8 +333,7 @@ def calc_service_fuel_switched(
 
         # Substract service demand for replaced technologies
         for tech in replaced_tech_fueltype:
-            fueltype_of_tech_replacing = technologies[tech].fuel_type_int
-            service_tech_switched_p[tech] = service_tech_by_p[tech] - (change_service_fueltype_by_p * fuel_tech_p_by[fueltype_of_tech_replacing][tech])
+            service_tech_switched_p[tech] = service_tech_by_p[tech] - (change_service_fueltype_by_p * fuel_tech_p_by[fueltype_tech_replace][tech])
 
     # -----------------------
     # Calculate service fraction of all technologies in enduse not affected
@@ -342,19 +344,19 @@ def calc_service_fuel_switched(
     remaining_service_to_distr_p = 1 - affected_service_p_ey
 
     # Calculate service fraction of remaining technologies
-    all_fractions_not_affected_by_switch = {}
+    all_fractions_unaffected_switch = {}
     for tech in service_tech_by_p:
         if tech not in service_tech_switched_p.keys():
-            all_fractions_not_affected_by_switch[tech] = service_tech_by_p[tech]
+            all_fractions_unaffected_switch[tech] = service_tech_by_p[tech]
 
     # Iterate all technologies of enduse_by
-    service_tot_remaining = sum(all_fractions_not_affected_by_switch.values())
+    service_tot_remaining = sum(all_fractions_unaffected_switch.values())
 
     # Get relative distribution of all not affected techs
-    for tech in all_fractions_not_affected_by_switch:
+    for tech in all_fractions_unaffected_switch:
 
         # Relative share
-        rel_service_fraction_p = all_fractions_not_affected_by_switch[tech] / service_tot_remaining
+        rel_service_fraction_p = all_fractions_unaffected_switch[tech] / service_tot_remaining
         service_tech_switched_p[tech] = rel_service_fraction_p * remaining_service_to_distr_p
 
     return dict(service_tech_switched_p)

energy_demand/technologies/fuel_service_switch.py

@@ -1,8 +1,8 @@
 """Function related to service or fuel switch
 """
+from collections import defaultdict
 from energy_demand.technologies import tech_related
 from energy_demand.read_write import read_data
-from collections import defaultdict
 
 def get_share_service_tech_ey(service_switches, specified_tech_enduse_by):
     """Get fraction of service for each technology
@@ -372,7 +372,6 @@ def capacity_assumption_to_service(
     # Add to switch of technology_install
     # -------------------------------------------
     service_switches_enduse = []
-
     for tech, service_tech_p in service_enduse_tech.items():
 
         # WARNING: MUST BE THE SAME YEAR FOR ALL CAPACITY SWITCHES