Thesis-NoiseDetection-attributes/display_simulation_curves.py

import numpy as np
import pandas as pd

import matplotlib.pyplot as plt
import os, sys, getopt

from modules.utils.data_type import get_svd_data

label_freq = 6
folder_path = "Curve_simulations"


def display_curves(folder_path):

    data_files = os.listdir(folder_path)

    scene_names = [f.split('_')[3] for f in data_files]

    for id, f in enumerate(data_files):

        print(scene_names[id])
        path_file = os.path.join(folder_path, f)

        df = pd.read_csv(path_file, header=None, sep=";")


        fig=plt.figure(figsize=(8, 8))
        fig.suptitle("Detection simulation for " + scene_names[id] + " scene", fontsize=20)

        for index, row in df.iterrows():

            row = np.asarray(row)

            threshold = row[2]
            start_index = row[3]
            step_value = row[4]

            counter_index = 0

            current_value = start_index

            while(current_value < threshold):
                counter_index += 1
                current_value += step_value

            fig.add_subplot(4, 4, (index + 1))
            plt.plot(row[5:])

            # draw vertical line from (70,100) to (70, 250)
            plt.plot([counter_index, counter_index], [-2, 2], 'k-', lw=2, color='red')
            plt.ylabel('Not noisy / Noisy', fontsize=18)
            plt.xlabel('Time in minutes / Samples per pixel', fontsize=16)

            x_labels = [id * step_value + start_index for id, val in enumerate(row[5:]) if id % label_freq == 0]

            x = [v for v in np.arange(0, len(row[5:])+1) if v % label_freq == 0]

            plt.xticks(x, x_labels, rotation=45)
            plt.ylim(-1, 2)

        plt.show()

def main():

    if len(sys.argv) <= 1:
        print('Run with default parameters...')
        print('python display_simulation_curves.py --folder "path"')
        sys.exit(2)
    try:
        opts, args = getopt.getopt(sys.argv[1:], "hm:s:k", ["help=", "folder="])
    except getopt.GetoptError:
        # print help information and exit:
        print('python display_simulation_curves.py --folder "path"')
        sys.exit(2)
    for o, a in opts:
        if o == "-h":
            print('python display_simulation_curves.py --folder "path"')
            sys.exit()
        elif o in ("-f", "--folder"):
            p_folder = a

        else:
            assert False, "unhandled option"


    display_curves(p_folder)

if __name__== "__main__":
    main()