state of generation of modelling results

docs/documentation.md

@@ -553,13 +553,14 @@ Data preparation of the raw input files was necessary:
 ### 4.4 Temperature data
 To calculate regional daily hourly load heating profiles, hourly temperature data are used from the [UK Met Office (2015)](http://catalogue.ceda.ac.uk/uuid/220a65615218d5c9cc9e4785a3234bd0) and loaded for weather stations across the UK.
 
+- The station ID can be retreived [here](http://badc.nerc.ac.uk/cgi-bin/midas_stations/search_by_name.cgi.py?name=&minyear=&maxyear=)
+- Metadatda of raw data can be found [here](http://artefacts.ceda.ac.uk/badc_datadocs/ukmo-midas/WH_Table.html)
+
 ### 4.5 Census data
 Employment statistics from the census (Office for National Statistics 2011)
 are used to disaggregate industry related energy demands for different end uses and sectors.
 
 - The data download link can be found [here](http://catalogue.ceda.ac.uk/uuid/916ac4bbc46f7685ae9a5e10451bae7c)
-- The station ID can be retreived [here](http://badc.nerc.ac.uk/cgi-bin/midas_stations/search_by_name.cgi.py?name=&minyear=&maxyear=)
-- Metadatda of raw data can be found [here](http://artefacts.ceda.ac.uk/badc_datadocs/ukmo-midas/WH_Table.html)
 
 ## Literature
 

energy_demand/geography/weather_region.py

@@ -253,7 +253,7 @@ def __init__(
             tech_stock=rs_tech_stock,
             rs_hdd_cy=self.rs_hdd_cy,
             model_yeardays=assumptions.model_yeardays)
-        
+
         # ------------
         # Set criteria wheter to use float load profile for heat pumps or not
         # ------------
@@ -307,7 +307,7 @@ def __init__(
                 unique_identifier=uuid.uuid4(),
                 technologies=assumptions.tech_list['heating_non_const'],
                 enduses=['rs_space_heating', 'rs_water_heating'],
-                shape_y_dh=tech_lp['rs_profile_hp_y_dh'],
+                shape_y_dh=rs_profile_hp_y_dh, #tech_lp['rs_profile_hp_y_dh'],
                 shape_yd=rs_hp_shape_yd,
                 shape_yh=rs_fuel_shape_hp_yh,
                 sectors=[dummy_sector],

energy_demand/plotting/result_mapping.py

@@ -866,19 +866,19 @@ def spatial_maps(
     unique_merge_id = 'name' #'geo_code'
 
     fueltype_str_to_create_maps = [
-        tech_related.get_fueltype_str(fueltypes, 'electricity'),
-        tech_related.get_fueltype_str(fueltypes, 'gas')]
+        'electricity'] #,
+        #'gas']
 
     # ======================================
     # Peak max h all enduses (abs)
     # ======================================
     if plot_crit_dict['plot_abs_peak_h']:
         for year in results_container['ed_fueltype_regs_yh'].keys():
-            for fueltype in range(fueltypes_nr):
-            #for fueltype_str in fueltype_str_to_create_maps:
+            #for fueltype in range(fueltypes_nr):
+            for fueltype_str in fueltype_str_to_create_maps:
 
-                fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
-                #fueltype = tech_related.get_fueltype_int(fueltype_str)
+                #fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
+                fueltype = tech_related.get_fueltype_int(fueltype_str)
 
                 # Calculate peak h across all regions
                 field_name = 'peak_abs_h_{}_{}'.format(year, fueltype_str)
@@ -931,11 +931,11 @@ def spatial_maps(
             if year == base_yr:
                 pass
             else:
-                for fueltype in range(fueltypes_nr):
-                #for fueltype_str in fueltype_str_to_create_maps:
+                #for fueltype in range(fueltypes_nr):
+                for fueltype_str in fueltype_str_to_create_maps:
 
-                    fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
-                    #fueltype = tech_related.get_fueltype_int(fueltype_str)
+                    #fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
+                    fueltype = tech_related.get_fueltype_int(fueltype_str)
 
                     # If total sum is zero, skip
                     if np.sum(results_container['ed_fueltype_regs_yh'][base_yr][fueltype]) == 0:
@@ -972,10 +972,12 @@ def spatial_maps(
                         merge_data,
                         unique_merge_id)
 
-                    bins_increments = 50 #10
+                    '''bins_increments = 25 #10 KAMEL
                     bins = get_reasonable_bin_values(
                         data_to_plot=list(data_to_plot.values()),
-                        increments=bins_increments)
+                        increments=bins_increments)'''
+                    #bins = [10, 20, 40, 80, 160, 320, 640]
+                    bins = [-160, -320, -640, -80, -40, -20, -10 ,0, 10, 20, 40, 80, 160, 320, 640]
 
                     color_list, color_prop, user_classification, color_zero = colors_plus_minus_map(
                         bins=bins,
@@ -1002,10 +1004,10 @@ def spatial_maps(
     # ======================================
     if plot_crit_dict['plot_load_factors']:
         for year in results_container['reg_load_factor_y'].keys():
-            for fueltype in range(fueltypes_nr):
-            #for fueltype_str in fueltype_str_to_create_maps:
-                fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
-                #fueltype = tech_related.get_fueltype_int(fueltype_str)
+            #for fueltype in range(fueltypes_nr):
+            for fueltype_str in fueltype_str_to_create_maps:
+                #fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
+                fueltype = tech_related.get_fueltype_int(fueltype_str)
 
                 field_name = 'lf_{}_{}'.format(year, fueltype_str)
 
@@ -1056,10 +1058,10 @@ def spatial_maps(
         final_yr = simulated_yrs[-1]
         base_yr = simulated_yrs[0]
 
-        for fueltype in range(fueltypes_nr):
-            #for fueltype_str in fueltype_str_to_create_maps:
-            #fueltype = tech_related.get_fueltype_int(fueltype_str)
-            fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
+        #for fueltype in range(fueltypes_nr):
+        for fueltype_str in fueltype_str_to_create_maps:
+            fueltype = tech_related.get_fueltype_int(fueltype_str)
+            #fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
 
             field_name = 'lf_diff_{}-{}_{}'.format(base_yr, final_yr, fueltype_str)
 
@@ -1151,10 +1153,10 @@ def spatial_maps(
     # Total fuel (y) all enduses
     # ======================================
     for year in results_container['ed_fueltype_regs_yh'].keys():
-        for fueltype in range(fueltypes_nr):
-        #for fueltype_str in fueltype_str_to_create_maps:
-            #fueltype = tech_related.get_fueltype_int(fueltype_str)
-            fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
+        #for fueltype in range(fueltypes_nr):
+        for fueltype_str in fueltype_str_to_create_maps:
+            fueltype = tech_related.get_fueltype_int(fueltype_str)
+            #fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
 
             if plot_crit_dict['plot_total_demand_fueltype']:
 
@@ -1237,14 +1239,12 @@ def spatial_maps(
                 # ----
                 # CAlculate classes for manual classification
                 # ----                
-                #logging.info("Min {}  Max {}".format(
-                #    min(list(data_to_plot.values())),
-                #     max(list(data_to_plot.values()))))
-                bins_increments = 10 #MAYBE NEEDS TO BE ADOPTED #TODO KAMEL
-
+                '''bins_increments = 25 #MAYBE NEEDS TO BE ADOPTED #TODO KAMEL
                 bins = get_reasonable_bin_values(
                     data_to_plot=list(data_to_plot.values()),
-                    increments=bins_increments)
+                    increments=bins_increments)'''
+                #bins = [10, 20, 40, 80, 160, 320, 640]
+                bins = [-160, -320, -640, -80, -40, -20, -10 ,0, 10, 20, 40, 80, 160, 320, 640]
 
                 color_list, color_prop, user_classification, color_zero = colors_plus_minus_map(
                     bins=bins,

energy_demand/result_processing/multiple_scenarios.py

@@ -8,7 +8,7 @@
 def process_result_multi_scen(
         #path_to_folder_with_scenarios="C:/Users/cenv0553/ed/results/_multiple_TEST",
         path_to_folder_with_scenarios="C:/Users/cenv0553/ed/results/Fig_11",
-        #path_to_folder_with_scenarios="C:/Users/cenv0553/ed/results/scen_A",
+        #path_to_folder_with_scenarios="C:/Users/cenv0553/ed/results/scenario_A", #scenario a charts
         #path_shapefile_input="C:/Users/cenv0553/ED/data/region_definitions/msoa_uk/msoa_lad_2015_uk.shp",
         path_shapefile_input="C:/Users/cenv0553/ED/data/region_definitions/lad_2016_uk_simplified.shp",
         base_yr=2015,
@@ -56,6 +56,7 @@ def process_result_multi_scen(
         '_results_PDF_figs']
 
     for scenario in scenarios:
+        print("... scenario: " + str(scenario))
         if scenario in scenario_names_ignored:
             pass
         else:

energy_demand/result_processing/scenario_charts.py

@@ -194,12 +194,12 @@ def process_scenarios(path_to_scenarios, year_to_model=2015):
 # Generate plots across all scenarios
 
 #process_scenarios(os.path.abspath("C:/Users/cenv0553/ed/results/scen_A"))
-process_scenarios(os.path.abspath("C:/Users/cenv0553/ed/results/scen_B"))
+#process_scenarios(os.path.abspath("C:/Users/cenv0553/ed/results/scen_B"))
 #process_scenarios(os.path.abspath("C:/Users/cenv0553/ed/results/scen_C"))
 #process_scenarios(os.path.abspath("C:/Users/cenv0553/ed/results/scen_D"))
 
-process_scenarios(os.path.abspath("C:/Users/cenv0553/ed/results/Fig_11"))
-
+#process_scenarios(os.path.abspath("C:/Users/cenv0553/ed/results/Fig_11"))
+process_scenarios(os.path.abspath("C:/Users/cenv0553/ed/results/scen_C_Fig12"))
 
 ##process_scenarios(os.path.abspath("C:/Users/cenv0553/ed/results/Fig_08_09"))
 #process_scenarios(os.path.abspath("C:/Users/cenv0553/ed/results/Fig_13"))  # Color scheme Fig 13

energy_demand/technologies/tech_related.py

@@ -225,8 +225,8 @@ def get_fueltype_int(fueltype_str):
     fueltype_in_string : str
         Fueltype string
     """
-    fueltype_lu = lookup_tables.basic_lookups()['fueltypes']
-
+    lookups = lookup_tables.basic_lookups()
+    fueltype_lu = lookups['fueltypes']
     if not fueltype_str:
         return None
     else:

tests/assumptions/test_assumptions_fuel_share.py

@@ -9,7 +9,7 @@
 from pkg_resources import resource_filename
 from pkg_resources import Requirement
 
-def test_assign_by_fuel_tech_p():
+'''def test_assign_by_fuel_tech_p():
     """
     """
     path_main = resource_filename(
@@ -46,3 +46,4 @@ def test_assign_by_fuel_tech_p():
         data['sectors'],
         data['lookups']['fueltypes'],
         data['lookups']['fueltypes_nr'])
+'''