Greedy taset after project

python/simod/demand_sample.py

@@ -16,7 +16,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 #
-from amodsim.init import config
+from simod.init import config
 import math
 import pandas as pd
 import numpy as np

python/simod/resources/config.cfg

@@ -1,9 +1,9 @@
 
 # common data for all experiments
-data_dir: 'C:/AIC Experiment data/VGA/'
+data_dir: '/Users/adela/Documents/bakalarka/randomdemand/'
 map_dir: $data_dir + 'maps/'
 
-experiments_dir: 'HERE FILL THE PROJECT EXPERIMENT DIR PATH/'
+experiments_dir: '/Users/adela/Documents/bakalarka/randomdemand/experiments/test/'
 rci_experiments_dir: 'HERE FILL THE PROJECT RCI EXPERIMENT DIR PATH/'
 
 # change this for each experiment!

python/simod/station_positions_map.py

@@ -16,7 +16,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 #
-from amodsim.init import config
+from simod.init import config
 
 import numpy as np
 import matplotlib
@@ -26,7 +26,7 @@
 import roadmaptools.utm
 import matplotlib
 import matplotlib.font_manager as fm
-import amodsim.demand
+import simod.demand
 
 from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar
 from matplotlib.colors import LogNorm
@@ -69,7 +69,7 @@
 # map = np.random.rand(len(lon_range), len(lat_range))
 
 # - fill heatmap
-demand_data = amodsim.demand.load(config.trips_path)
+demand_data = simod.demand.load(config.trips_path)
 xlist, ylist = roadmaptools.plotting.export_nodes_for_matplotlib(demand_data[["from_lat", "from_lon"]].to_numpy())
 for i, x in enumerate(xlist):
 	y = ylist[i]

python/simod/statistics/comparisons/comparison_table.py

@@ -16,7 +16,7 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 #
-from amodsim.init import config
+from simod.init import config
 
 import numpy as np
 import roadmaptools.inout
@@ -25,7 +25,7 @@
 from typing import List
 # from scripts.printer import print_table
 # from statistics.model.traffic_load import VehiclePhase
-from amodsim.statistics.traffic_density_histogram import TrafficDensityHistogram
+from simod.statistics.traffic_density_histogram import TrafficDensityHistogram
 
 
 def compute_stats(result: List, histogram: TrafficDensityHistogram, load) -> List:

python/simod/statistics/comparisons/density_histogram_scenario_comparion.py

@@ -17,14 +17,14 @@
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 #
 
-from amodsim.init import config
+from simod.init import config
 
 import matplotlib.pyplot as plt
 import numpy as np
 import statistics.model.traffic_load as traffic_load
 
 from matplotlib.axes import Axes
-from amodsim.statistics.traffic_density_histogram import TrafficDensityHistogram, HIGH_THRESHOLD, HISTOGRAM_SAMPLES
+from simod.statistics.traffic_density_histogram import TrafficDensityHistogram, HIGH_THRESHOLD, HISTOGRAM_SAMPLES
 from statistics.model.traffic_load import VehiclePhase
 
 

python/simod/statistics/comparisons/occupancy_histogram_comparison.py

@@ -16,16 +16,16 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 #
-from amodsim.init import config
+from simod.init import config
 
 import numpy as np
 import pandas as pd
 import matplotlib
 import matplotlib.pyplot as plt
 import datetime
 import roadmaptools.inout
-import amodsim.statistics.model.occupancy as occupancy
-import amodsim.statistics.comparisons.common as common
+import simod.statistics.model.occupancy as occupancy
+import simod.statistics.comparisons.common as common
 
 from matplotlib.ticker import FuncFormatter
 

python/simod/statistics/comparisons/performance_comparison.py

@@ -16,10 +16,10 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 #
-from init import config
+from simod.init import config
 
 import matplotlib.pyplot as plt
-import amodsim.statistics.model.ridesharing as ridesharing
+import simod.statistics.model.ridesharing as ridesharing
 
 
 ih_capacity1_stats = ridesharing.load(config.comparison.experiment_1_dir)

python/simod/statistics/comparisons/sensitivity_analysis.py

@@ -16,14 +16,14 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 #
-from amodsim.init import config
+from simod.init import config
 
 from typing import List, Tuple
 import roadmaptools.inout
-import amodsim.statistics.model.edges as edges
-import amodsim.statistics.model.transit as transit
-import amodsim.statistics.model.ridesharing as ridesharing
-import amodsim.statistics.model.service as service
+import simod.statistics.model.edges as edges
+import simod.statistics.model.transit as transit
+import simod.statistics.model.ridesharing as ridesharing
+import simod.statistics.model.service as service
 import matplotlib.pyplot as plt
 
 delay_experiments = ["sw-vga-max_delay_3_min", "sw-vga", "sw-vga-max_delay_5_min", "sw-vga-max_delay_6_min"]

python/simod/statistics/comparisons/transfer_ridesharing_comparison_table.py

@@ -0,0 +1,100 @@
+from simod.init import config
+
+import numpy as np
+import pandas.errors
+import roadmaptools.inout
+import simod.statistics.model.traffic_load as traffic_load
+import simod.statistics.model.transit as transit
+import simod.statistics.model.edges as edges
+import simod.statistics.model.ridesharing as ridesharing
+import simod.statistics.model.service as service
+import simod.statistics.model.occupancy as occupancy
+
+from typing import List, Dict, Iterable
+from pandas import DataFrame
+from roadmaptools.printer import print_table, print_info
+from simod.statistics.traffic_density_histogram import TrafficDensityHistogram
+from simod.statistics.model.vehicle_state import VehicleState
+
+
+def compute_stats(result: Dict, histogram: TrafficDensityHistogram, load, experiment_dir: str,
+                  edge_data: DataFrame) -> List:
+	# km total
+	transit_data = transit.load(experiment_dir)
+	km_total_window = int(round(transit.get_total_distance(transit_data, edge_data, True) / 1000 / 100))
+	km_per_served_demand = round(km_total_window / (result["demandsCount"] - result["numberOfDemandsDropped"]), 3)
+
+	dropped_demand_count = result["numberOfDemandsDropped"]
+	demand_count_served = result["demandsCount"] - result["numberOfDemandsDropped"]
+
+	occupancies = occupancy.load(experiment_dir)
+	occupancies_in_window = occupancy.filter_window(occupancies)
+	used_cars_count = len(occupancies_in_window.vehicle_id.unique())
+
+	# delay
+	service_stat = service.load_dataframe(experiment_dir)
+	delays_window = service.get_delays(service_stat, True, False)
+	mean_delay = int(round(delays_window.mean() / 1000))
+
+	transfers_count = result['transfersDone']
+
+	return [km_total_window, dropped_demand_count, used_cars_count, mean_delay, demand_count_served,
+	        km_per_served_demand, transfers_count]
+
+exp_dir_1 = '/Users/adela/Documents/bakalarka/vysledky2/InsertionHeuristic/Archiv/experiments/test/'
+# exp_dir_2 = '/Users/adela/Documents/bakalarka/vysledky2/transferInsertionHeuristic/Archiv/experiments/test/'
+exp_dir_2 = '/Users/adela/Documents/bakalarka/randomdemand/experiments/test/'
+
+exp_dir_3 = '/Users/adela/Documents/bakalarka/vysledky2/taset/Archiv/experiments/test/'
+
+edges_path = '/Users/adela/Documents/bakalarka/randomdemand/maps/edges.geojson'
+loaded_edges = roadmaptools.inout.load_geojson(edges_path)
+edge_data = edges.make_data_frame(loaded_edges)
+edge_object_data = edges.load_edges_mapped_by_id(loaded_edges)
+
+results_insertion_heuristic \
+	= roadmaptools.inout.load_json(exp_dir_1 + config.statistics.result_file_name)
+results_insertion_heuristic_transfer \
+	= roadmaptools.inout.load_json(exp_dir_2 + config.statistics.result_file_name)
+results_taset \
+	= roadmaptools.inout.load_json(exp_dir_3 + config.statistics.result_file_name)
+
+loads_insertion_heuristic = traffic_load.load_all_edges_load_history(
+	exp_dir_1 + config.statistics.all_edges_load_history_file_name)
+loads_insertion_heuristic_transfer = traffic_load.load_all_edges_load_history(
+	exp_dir_2 + config.statistics.all_edges_load_history_file_name)
+loads_taset = traffic_load.load_all_edges_load_history(
+	exp_dir_3 + config.statistics.all_edges_load_history_file_name)
+
+histogram = TrafficDensityHistogram(edge_object_data)
+
+insertion_heuristic_data = compute_stats(results_insertion_heuristic, histogram, loads_insertion_heuristic["ALL"],
+                                         exp_dir_1, edge_data)
+insertion_heuristic_transfer_data = compute_stats(results_insertion_heuristic_transfer, histogram,
+                                                  loads_insertion_heuristic_transfer["ALL"], exp_dir_2,
+                                                  edge_data)
+taset_data = compute_stats(results_taset, histogram, loads_taset["ALL"],
+                           exp_dir_3, edge_data)
+
+output_table = np.array([[" ", "INSERTION HEURISTIC", "INSERTION HEURISTIC TRANSFER", "GREEDY HEURISTIC TRANSFER"],
+                         ["Dropped demands", insertion_heuristic_data[1], insertion_heuristic_transfer_data[1],
+                          taset_data[1]],
+                         ["Demands served", insertion_heuristic_data[4], insertion_heuristic_transfer_data[4],
+                          taset_data[4]],
+                         ["Total transfers", insertion_heuristic_data[6], insertion_heuristic_transfer_data[6],
+                          taset_data[6]],
+                         ["Total veh. dist. traveled (km)", insertion_heuristic_data[0],
+                          insertion_heuristic_transfer_data[0], taset_data[0]],
+                         ["Total veh. dist. traveled per demand served (km)", insertion_heuristic_data[5],
+                          insertion_heuristic_transfer_data[5], taset_data[5]],
+                         ["Used car count", insertion_heuristic_data[2], insertion_heuristic_transfer_data[2],
+                          taset_data[2]],
+                         ["Average delay (s)", insertion_heuristic_data[3], insertion_heuristic_transfer_data[3],
+                          taset_data[3]],
+
+                         ])
+
+# console results
+print("COMPARISON:")
+print()
+print_table(output_table)

python/simod/statistics/delay_percentage.py

@@ -0,0 +1,65 @@
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+import pandas.errors
+import roadmaptools.inout
+import simod.statistics.model.traffic_load as traffic_load
+import simod.statistics.model.transit as transit
+import simod.statistics.model.edges as edges
+import simod.statistics.model.ridesharing as ridesharing
+import simod.statistics.model.service as service
+import simod.statistics.model.occupancy as occupancy
+
+
+exp_dir_1 = '/Users/adela/Documents/bakalarka/vysledky2/InsertionHeuristic/Archiv/experiments/test/'
+exp_dir_2 = '/Users/adela/Documents/bakalarka/vysledky2/transferInsertionHeuristic/Archiv/experiments/test/'
+exp_dir_3 = '/Users/adela/Documents/bakalarka/vysledky2/taset/Archiv/experiments/test/'
+
+save_dir_1 = '/Users/adela/Documents/bakalarka/vysledky2/InsertionHeuristic/Archiv/img/'
+save_dir_2 = '/Users/adela/Documents/bakalarka/vysledky2/transferInsertionHeuristic/Archiv/img/'
+save_dir_3 = '/Users/adela/Documents/bakalarka/vysledky2/taset/Archiv/img/'
+
+
+# delays dataframe
+# TODO change dir
+service_stat = service.load_dataframe(exp_dir_3)
+# TODO change dir
+save_results_to = save_dir_3
+
+delays = service.get_delays(service_stat, True, False).to_frame()
+service_stat['percentage_delay'] = (service_stat['dropoff_time'] - service_stat['demand_time']) / service_stat['min_possible_delay'] - 1
+maximum = service_stat['percentage_delay'].max()
+service_stat['percentage_delay_norm'] = service_stat['percentage_delay'] / maximum
+
+new_df = service_stat.where(service_stat['percentage_delay'] > 0.0)
+new_df = new_df.dropna()
+
+bins = [0.0, 0.1, 0.2, 0.3, 0.4, 0.6, 0.8, 1 * maximum]
+
+
+bins_df = pd.cut(new_df['percentage_delay'], bins)
+print(bins_df.value_counts())
+
+t = bins_df.value_counts(sort=False)
+labels = ['< 10 %', '< 20 %', '< 30 %', '< 40 %', '< 60 %', '< 80 %', '81 % +']
+
+
+counts = t
+plt.axis('equal')
+explode = bins
+colors = ['#191970','#0038E2','#0071C6','#329A82', '#46C3A6', '#93DCCB', '#E0F5F0']
+colors2 = ['#E6F7FF', '#BAE7FF', '#91D5FF', '#69C0FF', '#1890FF', '#096DD9', '#0050B3', '#002766']
+cc = list(reversed(colors))
+counts.plot(kind='pie', fontsize=15, colors=cc, labels=t,
+            wedgeprops={"edgecolor": "black",
+                        'linewidth': 0.2,
+                        'antialiased': True}
+            )
+plt.legend(labels=labels, loc="best")
+plt.ylabel('')
+
+
+plt.savefig(save_results_to + 'delay_percentages', bbox_inches='tight', transparent=True)
+
+
+plt.show()

python/simod/statistics/demand_service.py

@@ -17,7 +17,8 @@
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 #
 
-from simod.init import config, roadmaptools_config
+from simod.init import config
+from roadmaptools.config import roadmaptools_config
 
 from tqdm import tqdm
 import numpy as np

python/simod/statistics/demand_trip_duration_histogram.py

@@ -16,12 +16,12 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program. If not, see <http://www.gnu.org/licenses/>.
 #
-from amodsim.init import config
+from simod.init import config
 
 import numpy as np
 import matplotlib.pyplot as plt
 from matplotlib.ticker import FuncFormatter
-from amodsim.statistics.model import demand_trips
+from simod.statistics.model import demand_trips
 
 trips_data = demand_trips.load()