Merge pull request #1 from PhysicsOfMobility/black

code formatting

Author: fxjung

examples/hh_algorithm.py

@@ -13,29 +13,29 @@ def run_city_static(city_params):
     place, save = city_params
 
     params["dynamic routes"] = False
-    run_simulation(place, f'{save}_static', params=params, paths=paths)
+    run_simulation(place, f"{save}_static", params=params, paths=paths)
 
     params["penalty weighting"] = False
-    run_simulation(place, f'{save}_static_npw', params=params, paths=paths)
+    run_simulation(place, f"{save}_static_npw", params=params, paths=paths)
 
 
-if __name__ == '__main__':
-    city = 'Hamburg'
-    base_save = 'hh'
+if __name__ == "__main__":
+    city = "Hamburg"
+    base_save = "hh"
     hom_sets = 10
 
     # If you only want to run the algorithm for the empirical data, use this
     # command and remove the lines below.
     # run_simulation(city, base_save, params=params, paths=paths)
 
-    city_p = [(city, f'{base_save}_hom_{i + 1}') for i in range(hom_sets)]
+    city_p = [(city, f"{base_save}_hom_{i + 1}") for i in range(hom_sets)]
     city_p.insert(0, (city, base_save))
 
-    p = Pool(processes=min(cpu_count()-1, len(city_p)))
+    p = Pool(processes=min(cpu_count() - 1, len(city_p)))
     data = p.map(run_city, city_p)
     p.close()
 
     # Small comparison with static approach
     # run_city_static((city, base_save))
 
-    print('Run complete!')
+    print("Run complete!")

examples/hh_plot.py

@@ -1,32 +1,36 @@
 import warnings
 from params import params
 from paths import paths
-from BikePathNet.main.plot import plot_city, plot_city_hom_demand,\
-    plot_dynamic_vs_static
+from BikePathNet.main.plot import (
+    plot_city,
+    plot_city_hom_demand,
+    plot_dynamic_vs_static,
+)
 
-warnings.simplefilter(action='ignore', category=FutureWarning)
+warnings.simplefilter(action="ignore", category=FutureWarning)
 
-base_save = 'hh'
-city = 'Hamburg'
+base_save = "hh"
+city = "Hamburg"
 
 params["legends"] = False
 params["titles"] = False
-params["plot_format"] = 'png'
+params["plot_format"] = "png"
 
 params["figs_station_usage"] = (2.7, 2.6)
-params["stat_usage_norm"] = 1246/365    # norm station usage to year average
+params["stat_usage_norm"] = 1246 / 365  # norm station usage to year average
 
 params["figs_bp_comp"] = (2.8, 2.6)
 
 plot_city(city, base_save, paths=paths, params=params)
 
 for i in range(1, 11):
-    hom_save = f'{base_save}_hom_{i}'
+    hom_save = f"{base_save}_hom_{i}"
     params["stat_usage_norm"] = 1
     plot_city(city, hom_save, paths=paths, params=params)
 
-plot_city_hom_demand(city, base_save, paths, params, hom_pattern='hom',
-                     nbr_of_hom_sets=10)
+plot_city_hom_demand(
+    city, base_save, paths, params, hom_pattern="hom", nbr_of_hom_sets=10
+)
 
 
 # Small comparison with static approach

examples/hh_prep.py

@@ -3,17 +3,23 @@
 from paths import paths
 from shutil import copyfile
 
-city_name = 'Hamburg'
-save_name = 'hh'
+city_name = "Hamburg"
+save_name = "hh"
 hom_sets = 10
 
-input_csv = f'{save_name}.csv'
+input_csv = f"{save_name}.csv"
 
-prep_city(city_name, save_name, input_csv, consolidate=False,
-              cached_graph=True,
-              cached_graph_folder=f'{paths["input_folder"]}{save_name}/',
-              cached_graph_name=save_name,
-              paths=paths, params=params)
+prep_city(
+    city_name,
+    save_name,
+    input_csv,
+    consolidate=False,
+    cached_graph=True,
+    cached_graph_folder=f'{paths["input_folder"]}{save_name}/',
+    cached_graph_name=save_name,
+    paths=paths,
+    params=params,
+)
 
 # If you want to use the newest version of the street network us the
 # following command and remove the one above. Be aware, the existing graph
@@ -22,15 +28,20 @@
           consolidate=True, tol=35, paths=paths, params=params)"""
 
 for i in range(hom_sets):
-    hom_save_name = f'{save_name}_hom_{i+1}'
-    hom_input_csv = f'{hom_save_name}.csv'
-    prep_city(city_name, hom_save_name, hom_input_csv,
-              consolidate=False,
-              cached_graph=True,    # use same graph as emp. demand
-              cached_graph_folder=f'{paths["input_folder"]}{save_name}/',
-              cached_graph_name=save_name,
-              paths=paths, params=params)
-              
+    hom_save_name = f"{save_name}_hom_{i+1}"
+    hom_input_csv = f"{hom_save_name}.csv"
+    prep_city(
+        city_name,
+        hom_save_name,
+        hom_input_csv,
+        consolidate=False,
+        cached_graph=True,  # use same graph as emp. demand
+        cached_graph_folder=f'{paths["input_folder"]}{save_name}/',
+        cached_graph_name=save_name,
+        paths=paths,
+        params=params,
+    )
+
 # Small comparison with static approach
 """static = f'{save_name}_static'
 prep_city(city_name, static, input_csv, consolidate=False,

examples/params.py

@@ -3,14 +3,17 @@
 """
 
 params = {}
-params["penalties"] = {'primary': 7, 'secondary': 2.4, 'tertiary': 1.4,
-                       'residential': 1.1}
-params["street_cost"] = {'primary': 1, 'secondary': 1, 'tertiary': 1,
-                         'residential': 1}
-                         
+params["penalties"] = {
+    "primary": 7,
+    "secondary": 2.4,
+    "tertiary": 1.4,
+    "residential": 1.1,
+}
+params["street_cost"] = {"primary": 1, "secondary": 1, "tertiary": 1, "residential": 1}
+
 params["penalty weighting"] = True  # Penalties for load weighting
 params["dynamic routes"] = True  # Route recalculation after each step
-                       
+
 params["cut"] = True  # If results should be normalised to first removal
 params["bike_paths"] = None  # Additional ike Paths for current state
 params["correct_area"] = True  # Correction of the area size
@@ -20,58 +23,62 @@
 params["dpi"] = 300  # dpi of plots
 params["titles"] = True  # If figure title should be plotted
 params["legends"] = True  # If legends should be plotted
-params["plot_format"] = 'png'  # Format of the saved plot
+params["plot_format"] = "png"  # Format of the saved plot
 
 params["fs_title"] = 12  # Fontsize for title
 params["fs_axl"] = 7  # Fontsize for axis labels
 params["fs_ticks"] = 6  # Fontsize for axis tick numbers
 params["fs_legend"] = 6  # Fontsize for legends
 
 params["figs_ba_cost"] = (2.8, 2.6)  # Figsize ba-cost plot
-params["c_ba"] = '#0080c0'  # Colour for ba in normal plot
+params["c_ba"] = "#0080c0"  # Colour for ba in normal plot
 params["lw_ba"] = 0.75
-params["m_ba"] = 'o'  # Marker for ba
+params["m_ba"] = "o"  # Marker for ba
 params["ms_ba"] = 2  # Marker size for ba
-params["c_cost"] = '#4d4d4d'  # Colour for cost in normal plot
+params["c_cost"] = "#4d4d4d"  # Colour for cost in normal plot
 params["lw_cost"] = 0.75
-params["m_cost"] = 's'
+params["m_cost"] = "s"
 params["ms_cost"] = 2  # Marker size for cost
 
-params["c_st"] = {'primary': '#4d4d4d', 'secondary': '#666666',
-                  'tertiary': '#808080', 'residential': '#999999',
-                  'bike paths': '#0080c0'}
+params["c_st"] = {
+    "primary": "#4d4d4d",
+    "secondary": "#666666",
+    "tertiary": "#808080",
+    "residential": "#999999",
+    "bike paths": "#0080c0",
+}
 params["figs_comp_st"] = (0.8, 1.6)  # Figsize for comp_st_driven plot
 
 params["figs_snetwork"] = (7, 5)
 params["ns_snetwork"] = 4
-params["nc_snetwork"] = '#333333'
+params["nc_snetwork"] = "#333333"
 params["ew_snetwork"] = 1
-params["ec_snetwork"] = '#b3b3b3'
+params["ec_snetwork"] = "#b3b3b3"
 
 params["figs_station_usage"] = (2.7, 2.6)
-params["figs_station_usage_hist"] = (2.9, 1)    # (2.4, 0.8)
+params["figs_station_usage_hist"] = (2.9, 1)  # (2.4, 0.8)
 params["stat_usage_norm"] = 1
-params["cmap_nodes"] = 'cool'  # Cmap for nodes usage
+params["cmap_nodes"] = "cool"  # Cmap for nodes usage
 params["ns_station_usage"] = 10
 params["edge_lw"] = 0.5
-params["ec_station_usage"] = '#b3b3b3'
+params["ec_station_usage"] = "#b3b3b3"
 
 params["figs_bp_evo"] = (2.2, 2.2)
 params["lw_legend_bp_evo"] = 4
 
 params["figs_bp_comp"] = (2.8, 2.6)
 params["ns_bp_comp"] = 5
-params["nc_pb_evo"] = '#d726ffff'
-params["color_algo"] = '#000075'
-params["color_cs"] = '#40e640'
-params["color_both"] = '#e6194B'
-params["color_unused"] = '#b3b3b3ff'
+params["nc_pb_evo"] = "#d726ffff"
+params["color_algo"] = "#000075"
+params["color_cs"] = "#40e640"
+params["color_both"] = "#e6194B"
+params["color_unused"] = "#b3b3b3ff"
 
 
 params["figs_hom_comp"] = (2.6, 2.4)
-params["c_ed"] = '#0080c0'
-params["c_hom"] = '#f58231'
+params["c_ed"] = "#0080c0"
+params["c_hom"] = "#f58231"
 params["lw_ed"] = 0.9
 params["lw_hom"] = 0.9
-params["c_hom_ed_area"] = '#999999'
+params["c_hom_ed_area"] = "#999999"
 params["a_hom_ed_area"] = 0.75

examples/paths.py

@@ -3,11 +3,11 @@
 """
 
 paths = {}
-paths["csv_folder"] = 'examples/data/csv/'
-paths["input_folder"] = 'examples/data/input/'
-paths["output_folder"] = 'examples/data/output/'
-paths["log_folder"] = 'examples/logs/'
-paths["polygon_folder"] = 'examples/data/polygons/'
+paths["csv_folder"] = "examples/data/csv/"
+paths["input_folder"] = "examples/data/input/"
+paths["output_folder"] = "examples/data/output/"
+paths["log_folder"] = "examples/logs/"
+paths["polygon_folder"] = "examples/data/polygons/"
 
-paths["plot_folder"] = 'examples/plots/'
-paths["comp_folder"] = 'examples/data/plot/'
+paths["plot_folder"] = "examples/plots/"
+paths["comp_folder"] = "examples/data/plot/"