import numpy as np import pandas as pd import matplotlib.pyplot as plt import os, sys label_freq = 6 folder_path = "Curve_simulations" 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()