98 lines
3.9 KiB
Python
98 lines
3.9 KiB
Python
from latencyPlots import plot_delay_histogram_with_ci, plot_horizontal_hist_with_ci, plot_point_cloud
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from latencyData import LatencyData
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from confidence import compare_confidence_intervals
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import argparse
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import glob, logging, yaml, os
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import numpy as np
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logging.basicConfig(level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s')
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def parse_args():
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parser = argparse.ArgumentParser()
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parser.add_argument('-f', '--file',
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type=str,
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help='Path to the csv or yml file, depends on the mode',
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required=True)
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parser.add_argument('-m', '--mode',
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type=int,
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default=0,
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help='Mode of the script; 0 - one file, 1 - dir')
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return parser.parse_args()
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def one_file_run():
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csv_file = parse_args().file
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path_splitted = csv_file.split(os.sep)
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title = path_splitted[len(path_splitted) - 1].split('.')[0]
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print("АНАЛИЗ ДОВЕРИТЕЛЬНЫХ ИНТЕРВАЛОВ ДЛЯ ЗАДЕРЖЕК")
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print("=" * 50)
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l = None
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try:
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l = LatencyData(csv_file, confidence_level=0.99)
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except FileNotFoundError:
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print(f"✗ Ошибка: Файл '{csv_file}' не найден")
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exit(1)
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results = plot_delay_histogram_with_ci(
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save_to_file=True,
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show_plot=False,
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title=title,
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l=l
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)
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print("\n" + "=" * 50)
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compare_results = compare_confidence_intervals(
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csv_file, [0.90, 0.95, 0.99])
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if results:
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print("\n--- ИНТЕРПРЕТАЦИЯ РЕЗУЛЬТАТОВ ---")
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print(f"С вероятностью 95% истинное среднее значение задержки ")
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print(
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f"находится в интервале от {results['ci_lower']:.2f} до {results['ci_upper']:.2f} мс.")
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print(f"Это означает, что если бы мы повторили эксперимент много раз,")
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print(f"95% вычисленных таким образом интервалов содержали бы истинное среднее значение.")
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def validate_csv_list(csv_arr: list, dirConfig: dict) -> bool:
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is_colors_valid = all(file in dirConfig['colors'].keys() for file in csv_arr)
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is_labels_valid = all(file in dirConfig['labels'].keys() for file in csv_arr)
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if not is_labels_valid:
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logging.error("Labels in yaml is not fully valid")
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if not is_colors_valid:
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logging.error("Colors in yaml is not fully valid")
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return is_colors_valid & is_labels_valid
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def dir_run():
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dirConfig = None
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with open(parse_args().file + os.sep + 'dir.yml', encoding='utf-8') as f:
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dirConfig = yaml.safe_load(f)
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if dirConfig is None:
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raise Exception("File not found or not loaded")
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path_separated = parse_args().file.split(os.sep)
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title = path_separated[len(path_separated) - 2]
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all_csv_in_dir = glob.glob(parse_args().file + os.sep +'*.csv')
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logging.info(f"Found {len(all_csv_in_dir)} csv files in directory {parse_args().file}")
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lDataArr = {os.path.basename(file): LatencyData(file) for file in all_csv_in_dir}
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validate_csv_list([os.path.basename(file) for file in all_csv_in_dir], dirConfig)
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plot_point_cloud(lDataArr,
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dirConfig['colors'],
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dirConfig['labels'],
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float(dirConfig['point_cloud']['dT']),
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title=title)
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plot_horizontal_hist_with_ci(lDataArr,
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dirConfig['colors'],
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dirConfig['labels'],
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title=title)
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if __name__ == "__main__":
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import matplotlib.pyplot as plt
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plt.rcParams['font.family'] = 'Arial'
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args = parse_args()
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mode = args.mode
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if mode == 0:
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one_file_run()
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elif mode == 1:
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dir_run() |