distributed_representation_of_APF/fig_simulation.py at main · songfei-psy/distributed_representation_of_APF · GitHub

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import os
import argparse
from config import *
from Simulation.Env import *
from Tools.statistic import *
from Tools.utils import write_results_to_text
from Tools.plotting import *


args = argparse.ArgumentParser()
args.add_argument('--env', type=str, default='grid',
                  choices=['grid', 'polygon', 'maze', 'dynamics'], help='environment to simulate')


if __name__ == '__main__':
    args = args.parse_args()
    # folder
    ratios = SimulationConfig()
    project_folder = os.path.dirname(os.path.abspath(__file__))
    figure_folder = os.path.join(project_folder, 'data', 'simulation', 'figure')
    if not os.path.exists(figure_folder):
        os.makedirs(figure_folder)
    figure_appendix = os.path.join(figure_folder, f'{args.env}_')

    path_to_show = []
    stat_group_value = []
    for ratio in ratios:
        data_folder = os.path.join(project_folder, 'data', 'simulation', f'ratio={ratio}', args.env)
        if not os.path.exists(data_folder):
            raise FileNotFoundError('Data folder not found, please run simulation first!')
        # configuration functions
        config_map = {'grid': GridConfig, 'polygon': PolygonConfig, 'maze': MazeConfig, 'dynamics': DynamicConfig}
        algoConfig = config_map[args.env]()

        # trajectory
        paths = {}
        for algo_name, _ in algoConfig.items():
            file_name = os.path.join(data_folder, f'{algo_name}.npy')
            if not os.path.exists(file_name):
                raise FileNotFoundError(f'Data file not found: {file_name}')
            data = np.load(file_name, allow_pickle=True).item()
            paths[algo_name] = data['path_to_show']
        path_to_show.append(paths)

        # statistic
        file_name = os.path.join(data_folder, 'statistic_results.npy')
        results = np.load(file_name, allow_pickle=True)
        statistic_values = {}
        for result in results:  # algo_name, mean_path_len, mean_turn_angle, unnorm_turn, mean_duration
            statistic_values[str(result[0])] = result[1].astype(float)/ratio
        stat_group_value.append(statistic_values)

    # plotting
    env_map = {'grid': GridEnv, 'polygon': PolygonEnv, 'maze': MazeEnv, 'dynamics': DynamicsEnv}
    env_func = env_map[args.env]
    plotting_map = {'grid': Plotting_Grid_Map, 'polygon': Plotting_Polygon_Map,
                    'maze': Plotting_Maze_Map, 'dynamics': Plotting_Dynamic_Map}
    plotting = plotting_map[args.env](env_func, path_to_show, stat_group_value, ratios, figure_appendix)
    plotting.showing()