before removing shape_peak_yd_factor

energy_demand/enduse_func.py

@@ -1609,7 +1609,6 @@ def industry_enduse_changes(
     Info
     ----
     OLD MODEL TODO
-
     """
     factor = 1
 

energy_demand/plotting/plotting_multiple_scenarios.py

@@ -312,7 +312,7 @@ def plot_heat_pump_chart(
     # -----
 
     # Criteria to plot maximum boundaries
-    plot_max_min_polygon = False #TODO
+    plot_max_min_polygon = False
     plot_all_regs = False
 
     # Set figure size

energy_demand/plotting/result_mapping.py

@@ -810,12 +810,11 @@ def create_geopanda_files(
                     if np.sum(results_container['results_every_year'][base_year][fueltype]) == 0:
                         continue
 
-                    # TODO Check if 'nan' entry or total sum is 0. (Remove as soon as nan error is removed)
-                    if np.isnan(np.sum(results_container['results_every_year'][base_year][fueltype])):
-                        logging.info("Error: Contains nan entry {} {}".format(year, fueltype))
-                        continue
-                    logging.info("============ {}  {}".format(fueltype, np.isnan(np.sum(results_container['results_every_year'][base_year][fueltype]))))
-                    logging.info(results_container['results_every_year'][base_year][fueltype])
+                    ##if np.isnan(np.sum(results_container['results_every_year'][base_year][fueltype])):
+                    #    logging.info("Error: Contains nan entry {} {}".format(year, fueltype))
+                    #    continue
+                    #logging.info("============ {}  {}".format(fueltype, np.isnan(np.sum(results_container['results_every_year'][base_year][fueltype]))))
+                    #logging.info(results_container['results_every_year'][base_year][fueltype])
                     fueltype_str = tech_related.get_fueltype_str(fueltypes, fueltype)
 
                     # Calculate peak h across all regions

energy_demand/processing/scenario_charts.py

@@ -79,7 +79,7 @@ def process_scenarios(path_to_scenarios, year_to_model=2015):
     # Generate plot with heat pump ranges
     # -------------------------------
     if heat_pump_range_plot:
-        #TODO WRITE THAT FROM SEVERAL FOLDERS CAN BE GENERATED (i.e. different scenario)
+
         plotting_multiple_scenarios.plot_heat_pump_chart(
             lookups,
             regions,

energy_demand/read_write/read_data.py

@@ -267,7 +267,7 @@ def read_in_results(path_runs, seasons, model_yeardays_daytype):
 
             fueltype_str = tech_related.get_fueltype_str(lookups['fueltypes'], fueltype_int)
 
-            # Calculate peak per fueltype for all regions (reg_ed_yh= np.array(fueltype, reg, yh)) TODO CHECK
+            # Calculate peak per fueltype for all regions (reg_ed_yh= np.array(fueltype, reg, yh))
             all_regs_yh = np.sum(reg_ed_yh, axis=0)    # sum regs
             peak_h = np.max(all_regs_yh)               # select max of 8760 h
             results_container['ed_peak_h'][year][fueltype_str] = peak_h

energy_demand/scripts/init_scripts.py

@@ -486,7 +486,17 @@ def global_to_reg_capacity_switch(
     """Conversion of global capacity switch installations
     to regional installation
 
-    TODO
+    Arguments
+    ---------
+    regions : list
+        Regions
+    global_capactiy_switch : float
+        Global switch
+    spatial_factors : dict
+        
+    Returns
+    -------
+
     """
     reg_capacity_switch = {}
     for reg in regions:

energy_demand/technologies/fuel_service_switch.py

@@ -319,7 +319,7 @@ def autocomplete_switches(
                         enduse_switches.append(switch_new)
                         switch_yr = switch.switch_yr
 
-                        # Create switch TODO TODO SHIFTED ONE TAB CHECK 03.05.2018
+                        # Create switch
                         switches_new = create_switches_from_s_shares(
                             enduse=enduse,
                             s_tech_by_p=s_tech_by_p,

energy_demand/validation/lad_validation.py

@@ -241,7 +241,7 @@ def spatial_validation_lad_level(
     logging.info("comparison real: {}  modelled: {}".format(100, (100 / tot_sum_real_gas) * tot_sum_modelled_gas))
     #'''
     # ----------------------------------------------
-    # TODO Correct REAL Values that sum is the same
+    # Correct REAL Values that sum is the same
     # ----------------------------------------------
     data_inputlist = [
         (fuel_elec_residential_regs_yh, subnational_elec_residential),          # domestic
@@ -323,7 +323,7 @@ def spatial_validation_lad_level(
         os.path.join(result_paths['data_results_validation'], 'validation_spatial_residential_gas.pdf'),
         label_points=True,
         plotshow=plot_crit)
-    
+
     logging.info("... ================= Validaiton of non residential gas")
     spatial_validation(
         reg_coord,
@@ -361,7 +361,7 @@ def temporal_validation_lad(
     logging.info("... temporal validation")
 
     # -------------------------------------------
-    # Spatial validation after calculations TODO REMOVE SPATIAL
+    # Spatial validation after calculations
     # -------------------------------------------
     subnational_elec = data_loader.read_national_real_elec_data(
         paths['path_val_subnational_elec'])
@@ -580,9 +580,7 @@ def spatial_validation(
         try:
             real = result_dict['real_demand'][reg_geocode]
             modelled = result_dict['modelled_demand'][reg_geocode]
-            #diff_real_modelled_p.append((100 / real) * modelled)
             diff_real_modelled_p.append(abs(100 - ((100 / real) * modelled)))
-            #logging.info("Absolute difference in percentage {}".format(abs(100 - ((100 / real) * modelled)))) #TODO
             diff_real_modelled_abs.append(real - modelled)
         except KeyError:
             pass

tests/scripts/test_s_disaggregation.py

@@ -3,7 +3,7 @@
 import numpy as np
 from energy_demand.scripts import s_disaggregation
 from energy_demand.assumptions import non_param_assumptions
-'''
+#'''
 def test_rs_disaggregate():
     """testing
     """
@@ -23,9 +23,9 @@ def test_rs_disaggregate():
             'sig_midpoint': 0,
             'sig_steepness': 1,
             'yr_until_changed': 2020},
-        'strategy_variables': {'rs_t_base_heating_future_yr': {'scenario_value': 0}}}
+        'strategy_variables': {'rs_t_base_heating_future_yr': {'scenario_value': 15}}}
     assumptions = non_param_assumptions.DummyClass(assumptions)
-    assumptions.__setattr__('t_bases', non_param_assumptions.DummyClass({'rs_t_heating_by': 0}))
+    assumptions.__setattr__('t_bases', non_param_assumptions.DummyClass({'rs_t_heating_by': 15}))
 
     reg_coord = {
         'regA': {'longitude': 0,'latitude': 0},
@@ -68,23 +68,20 @@ def test_rs_disaggregate():
 
     assert result['regA']['rs_space_heating'] == national_fuel / 2
 
-test_rs_disaggregate() #TODO FIX
-'''
-#TODO TODO FIX
-'''def test_ss_disaggregate():
+def test_ss_disaggregate():
     """testing
     """
     regions = ['regA', 'regB']
     national_fuel = 100
-    raw_fuel_sectors_enduses = {'ss_space_heating': {'sectorA': national_fuel}}
+    raw_fuel_sectors_enduses = {'ss_space_heating': {'offices': national_fuel}}
 
     scenario_data = {
         'population': {2015: {'regA': 10, 'regB': 10}},
         'floor_area': {
             'ss_floorarea_newcastle': {
                 2015: {'regA': 10, 'regB': 10}},
             'ss_floorarea' :{
-                 2015: {'regA': {'sectorA': 100}, 'regB': {'sectorA': 100}}}
+                 2015: {'regA': {'offices': 100}, 'regB': {'offices': 100}}}
             },
         }
 
@@ -95,25 +92,31 @@ def test_rs_disaggregate():
             'sig_midpoint': 0,
             'sig_steepness': 1,
             'yr_until_changed': 2020},
-        'strategy_variables': {'ss_t_base_heating_future_yr': {'scenario_value': 0}, 'ss_t_base_cooling_future_yr': {'scenario_value': 0}}}
+        'strategy_variables': {
+            'ss_t_base_heating_future_yr': {'scenario_value': 15},
+            'ss_t_base_cooling_future_yr': {'scenario_value': 20}}}
 
     assumptions = non_param_assumptions.DummyClass(assumptions)
-    assumptions.__setattr__('t_bases', non_param_assumptions.DummyClass({'ss_t_heating_by': 0, 'ss_t_cooling_by': 0}))
+    assumptions.__setattr__('t_bases', non_param_assumptions.DummyClass(
+        {'ss_t_heating_by': 15, 'ss_t_cooling_by': 20}))
 
     reg_coord = {
-        'regA': {'longitude': 0,'latitude': 0},
-        'regB': {'longitude': 0,'latitude': 0}}
+        'regA': {'longitude': 0, 'latitude': 0},
+        'regB': {'longitude': 0, 'latitude': 0}}
 
     weather_stations = {
         'stationID_1': {'station_longitude': 1,'station_latitude': 1}}
 
     temp_data = {'stationID_1': np.ones((365, 24)) + 10}
 
     enduses = ['ss_space_heating']
-    sectors = ['sectorA']
-    all_sectors = ['sectorA']
+    sectors = ['offices']
+    all_sectors = ['offices']
 
-    service_building_count = None
+    service_building_count = {}
+    service_building_count[9] = {}
+    service_building_count[9]['regA'] = 10
+    service_building_count[9]['regB'] = 10
 
     result = s_disaggregation.ss_disaggregate(
         raw_fuel_sectors_enduses,
@@ -131,8 +134,8 @@ def test_rs_disaggregate():
         crit_limited_disagg_pop=True,
         crit_full_disagg=False)
 
-    assert result['regA']['ss_space_heating']['sectorA'] == national_fuel / 2
-'''
+    assert result['regA']['ss_space_heating']['offices'] == national_fuel / 2
+test_ss_disaggregate()
 def test_is_disaggregate():
     """TESTING"""
     temp_data = {'stationID_1': np.ones((365, 24)) + 10}
@@ -209,5 +212,3 @@ def test_is_disaggregate():
     assert round(result['regA']['is_space_heating']['pharmaceuticals'], 3) == round(10.0/15.0 * 100,3) 
     assert result['regB']['is_space_heating']['mining'] == 100
     assert round(result['regB']['is_space_heating']['pharmaceuticals'], 3)  == round(5.0/15.0 * 100, 3)
-
-test_is_disaggregate()

tests/test_enduse_func.py

@@ -29,8 +29,7 @@ def test_enduse():
         criterias='test',
         strategy_variables='test',
         fueltypes_nr='test',
-        fueltypes='test',
-        model_yeardays_nrs='test')
+        fueltypes='test')
 
     assert out.flat_profile_crit == True
 
@@ -621,8 +620,7 @@ def test_calc_fuel_tech_yh():
         load_profiles=lp_stock_obj,
         fueltypes_nr=2,
         fueltypes=fueltypes,
-        mode_constrained=False,
-        model_yeardays_nrs=365)
+        mode_constrained=False)
 
     assert results[1][3][0] == 3.0 / float(np.sum(range(365)) * 24) * 200
 
@@ -635,7 +633,6 @@ def test_calc_fuel_tech_yh():
         load_profiles=lp_stock_obj,
         fueltypes_nr=2,
         fueltypes=fueltypes,
-        model_yeardays_nrs=365,
         mode_constrained=True)
 
     assert results['techA'][3][0] == 3.0 / float(np.sum(range(365)) * 24) * 200