improved spider plot

energy_demand/plotting/plotting_multiple_scenarios.py

@@ -1,13 +1,16 @@
 """
 This file containes functions to plot multiple scenarios in a folder
 """
+import os
 import operator
 import numpy as np
 import matplotlib.pyplot as plt
 from energy_demand.plotting import plotting_styles
 from energy_demand.plotting import plotting_program
 from energy_demand.basic import conversions
 from energy_demand.plotting import plotting_results
+from energy_demand.basic import lookup_tables
+from energy_demand.technologies import tech_related
 
 def plot_reg_y_over_time(
         scenario_data,
@@ -211,69 +214,73 @@ def plot_radar_plots_average_peak_day(
         scenario_data,
         year_to_plot,
         fig_name,
-        plotshow):
-        """Compare averaged dh profile overall regions for peak day
-        """
-
-        # Scenarios
-        all_scenarios = list(scenario_data.keys())
-        first_scenario = str(all_scenarios[:1][0])
-
-        # ----------------
-        # Create base year peak load profile
-        # -----------------
-        all_regs_fueltypes_yh_by = {}
-        for fueltype, fuels_regs in enumerate(scenario_data[first_scenario]['results_every_year'][2015]):
-            for region_array_nr, fuel_reg in enumerate(fuels_regs):
-                try:
-                    all_regs_fueltypes_yh_by[fueltype] += fuel_reg
-                except KeyError:
-                    all_regs_fueltypes_yh_by[fueltype] = fuel_reg
-
-                try:
-                    all_fuels += fuel_reg
-                except:
-                    all_fuels = fuel_reg
-
-        # Future year
-        all_regs_fueltypes_yh_ey = {}
-        for fueltype, fuels_regs in enumerate(scenario_data[first_scenario]['results_every_year'][year_to_plot]):
-            for region_array_nr, fuel_reg in enumerate(fuels_regs):
-                try:
-                    all_regs_fueltypes_yh_ey[fueltype] += fuel_reg
-                except KeyError:
-                    all_regs_fueltypes_yh_ey[fueltype] = fuel_reg
-
-        # -----------
-        # get peak day across all fueltypes
-        # -----------
-        for fueltype in all_regs_fueltypes_yh_by.keys():
-            all_regs_fueltypes_yh_by[fueltype].reshape((365, 24))
-        for fueltype in all_regs_fueltypes_yh_ey.keys():
-            all_regs_fueltypes_yh_ey[fueltype].reshape((365, 24))
-
-        all_fuels_d = all_fuels.np.reshape((365, 24))
-
-        peak_day_nr = np.argmax(all_fuels_d, axis=0)
-
-        print("peak_day_nr" + str(peak_day_nr))
-
-        #fueltype_to_plot = 'electricity']
-        for fueltype, fuels_regs in all_regs_fueltypes_yh_by.items():
-
-            name_spider_plot = "spider_{}".format(fueltype)
-            # ----------------------------------
-            # Plot dh for peak day for base year
-            # ----------------------------------
-            individ_radars_to_plot_dh = [
-                list(all_regs_fueltypes_yh_by[fueltype][peak_day_nr]),
-                list(all_regs_fueltypes_yh_ey[peak_day_nr])]
-
-            plotting_results.plot_radar_plot_multiple_lines(
-                individ_radars_to_plot_dh,
-                name_spider_plot,
-                plot_steps=20,
-                plotshow=False)
+        plotshow
+    ):
+    """Compare averaged dh profile overall regions for peak day
+    for future year and base year
+    """
+    lookups = lookup_tables.basic_lookups()
+
+    # Scenarios
+    all_scenarios = list(scenario_data.keys())
+    first_scenario = str(all_scenarios[:1][0])
+
+    # ----------------
+    # Create base year peak load profile
+    # -----------------
+    all_regs_fueltypes_yh_by = {}
+    for fueltype, fuels_regs in enumerate(scenario_data[first_scenario]['results_every_year'][2015]):
+        for region_array_nr, fuel_reg in enumerate(fuels_regs):
+            try:
+                all_regs_fueltypes_yh_by[fueltype] += fuel_reg
+            except KeyError:
+                all_regs_fueltypes_yh_by[fueltype] = fuel_reg
+
+            try:
+                all_fuels_by += fuel_reg
+            except:
+                all_fuels_by = fuel_reg
+
+    # ------------------------
+    # Future year load profile
+    # ------------------------
+    all_regs_fueltypes_yh_ey = {}
+    for fueltype, fuels_regs in enumerate(scenario_data[first_scenario]['results_every_year'][year_to_plot]):
+        for region_array_nr, fuel_reg in enumerate(fuels_regs):
+            try:
+                all_regs_fueltypes_yh_ey[fueltype] += fuel_reg
+            except KeyError:
+                all_regs_fueltypes_yh_ey[fueltype] = fuel_reg
+
+    # -----------
+    # get peak day across all fueltypes
+    # -----------
+    for fueltype in all_regs_fueltypes_yh_by.keys():
+        all_regs_fueltypes_yh_by[fueltype] = all_regs_fueltypes_yh_by[fueltype].reshape((365, 24))
+    for fueltype in all_regs_fueltypes_yh_ey.keys():
+        all_regs_fueltypes_yh_ey[fueltype] = all_regs_fueltypes_yh_ey[fueltype].reshape((365, 24))
+
+    all_fuels_by_d = all_fuels_by.reshape((365, 24))
+
+    peak_day_nr = np.argmax(np.sum(all_fuels_by_d, axis=1))
+
+    for fueltype in all_regs_fueltypes_yh_by.keys():
+
+        fueltype_str = tech_related.get_fueltype_str(lookups['fueltypes'], fueltype)
+        name_spider_plot = os.path.join(fig_name, "spider_{}_.pdf".format(fueltype_str))
+
+        # ----------------------------------
+        # Plot dh for peak day for base year
+        # ----------------------------------
+        individ_radars_to_plot_dh = [
+            list(all_regs_fueltypes_yh_by[fueltype][peak_day_nr]),
+            list(all_regs_fueltypes_yh_ey[fueltype][peak_day_nr])]
+
+        plotting_results.plot_radar_plot_multiple_lines(
+            individ_radars_to_plot_dh,
+            name_spider_plot,
+            plot_steps=20,
+            plotshow=False)
 
 def plot_LAD_comparison_scenarios(
         scenario_data,

energy_demand/plotting/plotting_results.py

@@ -1717,7 +1717,12 @@ def plot_radar_plot(dh_profile, fig_name, plot_steps=30, plotshow=False):
     else:
         plt.close()
 
-def plot_radar_plot_multiple_lines(dh_profiles, fig_name, plot_steps=30, plotshow=False):
+def plot_radar_plot_multiple_lines(
+        dh_profiles,
+        fig_name,
+        plot_steps=30,
+        plotshow=False
+    ):
     """Plot daily load profile on a radar plot
 
     Arguments
@@ -1730,12 +1735,14 @@ def plot_radar_plot_multiple_lines(dh_profiles, fig_name, plot_steps=30, plotsho
     SOURCE: https://python-graph-gallery.com/390-basic-radar-chart/
     """
 
-    # Get maximum demand of first array
-    max_entry = np.array(dh_profiles[0]).max()
-    max_demand = round(max_entry, -1) + 10 # Round to nearest 10 plus add 10
-    max_demand = 120 #SCRAP
+    # Get maximum demand of all lines
+    max_entry = 0
+    for line_entries in dh_profiles:
+        max_in_line = max(line_entries)
+        if max_in_line > max_entry:
+            max_entry = max_in_line
 
-    #
+    max_demand = round(max_entry, -1) + 10 # Round to nearest 10 plus add 10
 
     nr_of_plot_steps = int(max_demand / plot_steps) + 1
 
@@ -1747,8 +1754,14 @@ def plot_radar_plot_multiple_lines(dh_profiles, fig_name, plot_steps=30, plotsho
         axis_plots_inner.append(plot_steps*i)
         axis_plots_outer.append(str(plot_steps*i))
 
+    color_lines = ['grey', 'blue']
+    years = ['2015', '2050']
+
     # Iterate lines
-    for dh_profile in dh_profiles:
+    for cnt, dh_profile in enumerate(dh_profiles):
+
+        color_line = color_lines[cnt]
+        year_line = years[cnt]
 
         data = {'dh_profile': ['testname']}
 
@@ -1811,14 +1824,27 @@ def plot_radar_plot_multiple_lines(dh_profiles, fig_name, plot_steps=30, plotsho
             angles,
             values,
             linestyle='--',
-            linewidth=0.5)
+            linewidth=0.5,
+            label="{}".format(year_line))
 
         ax.fill(
             angles,
             values,
-            'blue', #b
+            color_line, #b
             alpha=0.1)
 
+    # ------------
+    # Plot legend
+    # ------------
+    plt.legend(
+        ncol=2,
+        loc='best',
+        prop={
+            'family': 'arial',
+            'size': 10},
+        frameon=False)
+
+
     plt.savefig(fig_name)
 
     if plotshow:

energy_demand/processing_multiple_scenarios.py

@@ -5,6 +5,7 @@
 from energy_demand.basic import date_prop
 from energy_demand.plotting import plotting_multiple_scenarios
 from energy_demand import processing
+from energy_demand.basic import basic_functions
 
 def process_result_multi_scen(path_to_scenarios, path_shapefile_input):
     """Iterate the folders with scenario
@@ -33,6 +34,10 @@ def process_scenarios(path_to_scenarios, year_to_model=2015):
     path_to_scenarios : str
         Path to folders with stored results
     """
+    # Delete folder results if existing
+    path_result_folder = os.path.join(path_to_scenarios, "results_multiple_scenarios")
+    basic_functions.delete_folder(path_result_folder)
+
     seasons = date_prop.get_season(
         year_to_model=year_to_model)
 
@@ -62,46 +67,51 @@ def process_scenarios(path_to_scenarios, year_to_model=2015):
             seasons=seasons,
             model_yeardays_daytype=model_yeardays_daytype)
 
+    # -----------------------
+    # Generate result folder
+    # -----------------------
+    basic_functions.create_folder(path_result_folder)
+
     # ------------
     # Create plots
     # ------------
     # Plot total demand for every year in line plot
     plotting_multiple_scenarios.plot_tot_y_over_time(
         scenario_data,
-        fig_name=os.path.join(path_to_scenarios, "tot_y_multiple.pdf"),
+        fig_name=os.path.join(path_result_folder, "tot_y_multiple.pdf"),
         plotshow=True)
 
     # Plot for all regions demand for every year in line plot
     plotting_multiple_scenarios.plot_reg_y_over_time(
         scenario_data,
-        fig_name=os.path.join(path_to_scenarios, "reg_y_multiple.pdf"),
+        fig_name=os.path.join(path_result_folder, "reg_y_multiple.pdf"),
         plotshow=True)
 
     # Plot comparison of total demand for a year for all LADs (scatter plot)
     plotting_multiple_scenarios.plot_LAD_comparison_scenarios(
         scenario_data,
         year_to_plot=2050,
-        fig_name=os.path.join(path_to_scenarios, "LAD_multiple.pdf"),
+        fig_name=os.path.join(path_result_folder, "LAD_multiple.pdf"),
         plotshow=False)
 
     # Plot different profiels in radar plot
     plotting_multiple_scenarios.plot_radar_plots_average_peak_day(
         scenario_data,
         year_to_plot=2050,
-        fig_name=os.path.join(path_to_scenarios, "radar_average.pdf"),
+        fig_name=os.path.join(path_result_folder),
         plotshow=False)
     return
 
 # ------------------------------------
 # Execute rusult processing for every scenario
 # ------------------------------------^
-#'''
+'''
 process_result_multi_scen(
     os.path.abspath("C:/Users/cenv0553/nismod/data_energy_demand/_MULT2"),
     os.path.abspath('C:/Users/cenv0553/nismod/data_energy_demand/_raw_data/C_LAD_geography/same_as_pop_scenario/lad_2016_uk_simplified.shp'))
-#'''
+'''
 
 # ------------------------------------
 # Generate plots across all scenarios
 # ------------------------------------
-#process_scenarios(os.path.abspath("C:/Users/cenv0553/nismod/data_energy_demand/_MULT2"))
+process_scenarios(os.path.abspath("C:/Users/cenv0553/nismod/data_energy_demand/_MULT2"))