labelling: Added a script solemnly for manually labelling data

Author: Joas329

labelling.py

@@ -0,0 +1,55 @@
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy.signal import find_peaks
+
+# Load the dataset with comma as delimiter
+df = pd.read_csv("lab5_Philco-L05.txt", delimiter=",")
+
+
+time = df.iloc[:, 0]
+
+# Get the Channel data
+data = df.iloc[:, 1]
+
+time_subset = time[:10000]
+
+df_subset = data[:10000]
+
+
+p_indices = [110, 910, 1670, 2490, 3300, 4085]
+q_indices = [219, 1018, 1785, 2605, 3400, 4160]
+r_indices = [257, 1052, 1825, 2641, 3450, 4238]
+s_indices = [284, 1079, 1851, 2663, 3474, 4265]
+t_indices = [460, 1250, 2020, 2840, 3650, 4436]
+
+# Plot the ECG signal
+plt.figure(figsize=(10, 6))
+plt.plot(time_subset, df_subset, label='ECG Data')
+plt.xlabel('Time')
+plt.ylabel('Data')
+plt.title('ECG Data from Joaquin Philco')
+plt.grid(True)
+
+
+# Marking P Features
+plt.scatter(time_subset[p_indices], df_subset[p_indices], color='black', marker='x', label='P')
+
+# Marking Q Features
+plt.scatter(time_subset[q_indices], df_subset[q_indices], color='purple', marker='x', label='Q')
+
+# Marking R Features
+plt.scatter(time_subset[r_indices], df_subset[r_indices], color='green', marker='x', label='R')
+
+# Marking S Features
+plt.scatter(time_subset[s_indices], df_subset[s_indices], color='red', marker='x', label='S')
+
+# Marking T Features
+plt.scatter(time_subset[t_indices], df_subset[t_indices], color='black', marker='x', label='T')
+
+plt.xlabel('Time')
+plt.ylabel('Data')
+plt.title('ECG Data with QRS Features')
+plt.legend()
+plt.grid(True)
+plt.show()