--- a
+++ b/run_exp_1.py
@@ -0,0 +1,121 @@
+import run
+import sys
+import os
+import numpy as np
+import matplotlib.pyplot as plt
+
+def run_experiment1(data_path):
+    os.makedirs('exp1_results', exist_ok=True)
+
+    accuracies1 = []
+    accuracies2 = []
+    accuracies3 = []
+    accuracies4 = []
+    accuracies5 = []
+
+    for num_subjects in range(20, 150, 20):
+        print(f"Training for {num_subjects} subjects with III+V3+V5")
+        accuracy, total_train_time, total_eval_time  = run.run(NUM_SEGMENTS=500, 
+                                                              NUM_SECONDS=2, 
+                                                              NUM_BATCH=16, 
+                                                              LEADS=[0,1,2], 
+                                                              NUM_EPOCHS=200, 
+                                                              DATA_PATH = data_path, 
+                                                              FS=128,
+                                                              NUM_PATIENTS=num_subjects)
+        accuracies1.append(accuracy)
+        with open('exp1_results/result-III-V3-V5.txt', 'a') as f:
+            f.write(f"With number subjects: {num_subjects}:\n")
+            f.write(f"Accuracy: {accuracy}, Time train: {total_train_time}, Time eval: {total_eval_time}\n\n")
+    
+
+    for num_subjects in range(20, 150, 20):
+        print(f"Training for {num_subjects} subjects with III+V3")
+        accuracy, total_train_time, total_eval_time  = run.run(NUM_SEGMENTS=500, 
+                                                              NUM_SECONDS=2, 
+                                                              NUM_BATCH=16, 
+                                                              LEADS=[0,1], 
+                                                              NUM_EPOCHS=200, 
+                                                              DATA_PATH = data_path, 
+                                                              FS=128,
+                                                              NUM_PATIENTS=num_subjects)
+        accuracies2.append(accuracy)
+        with open('exp1_results/result-III-V3.txt', 'a') as f:
+            f.write(f"With number subjects: {num_subjects}:\n")
+            f.write(f"Accuracy: {accuracy}, Time train: {total_train_time}, Time eval: {total_eval_time}\n\n")
+
+    for num_subjects in range(20, 150, 20):
+        print(f"Training for {num_subjects} subjects with V5")
+        accuracy, total_train_time, total_eval_time  = run.run(NUM_SEGMENTS=500, 
+                                                              NUM_SECONDS=2, 
+                                                              NUM_BATCH=16, 
+                                                              LEADS=[2], 
+                                                              NUM_EPOCHS=200, 
+                                                              DATA_PATH = data_path, 
+                                                              FS=128,
+                                                              NUM_PATIENTS=num_subjects)
+        accuracies3.append(accuracy)
+        with open('exp1_results/result-V5.txt', 'a') as f:
+            f.write(f"With number subjects: {num_subjects}:\n")
+            f.write(f"Accuracy: {accuracy}, Time train: {total_train_time}, Time eval: {total_eval_time}\n\n")
+
+    for num_subjects in range(20, 150, 20):
+        print(f"Training for {num_subjects} subjects with V3")
+        accuracy, total_train_time, total_eval_time  = run.run(NUM_SEGMENTS=500, 
+                                                              NUM_SECONDS=2, 
+                                                              NUM_BATCH=16, 
+                                                              LEADS=[1], 
+                                                              NUM_EPOCHS=200, 
+                                                              DATA_PATH = data_path, 
+                                                              FS=128,
+                                                              NUM_PATIENTS=num_subjects)
+        accuracies4.append(accuracy)
+        with open('exp1_results/result-V3.txt', 'a') as f:
+            f.write(f"With number subjects: {num_subjects}:\n")
+            f.write(f"Accuracy: {accuracy}, Time train: {total_train_time}, Time eval: {total_eval_time}\n\n")
+
+    for num_subjects in range(20, 150, 20):
+        print(f"Training for {num_subjects} subjects with III")
+        accuracy, total_train_time, total_eval_time  = run.run(NUM_SEGMENTS=500, 
+                                                              NUM_SECONDS=2, 
+                                                              NUM_BATCH=16, 
+                                                              LEADS=[0], 
+                                                              NUM_EPOCHS=200, 
+                                                              DATA_PATH = data_path, 
+                                                              FS=128,
+                                                              NUM_PATIENTS=num_subjects)
+        accuracies5.append(accuracy)
+        with open('exp1_results/result-III.txt', 'a') as f:
+            f.write(f"With number subjects: {num_subjects}:\n")
+            f.write(f"Accuracy: {accuracy}, Time train: {total_train_time}, Time eval: {total_eval_time}\n\n")
+
+
+    #plotting             
+    num_subjects = list(range(20, 150, 20))
+    plt.figure(figsize=(10, 8), dpi=100)
+    plt.plot(num_subjects, accuracies1, '#8C2155',marker='.', label='III+V3+V5')
+    plt.plot(num_subjects, accuracies2, '#F99083',marker='.', label='III+V3')
+    plt.plot(num_subjects, accuracies3, '#8AA29E',marker='.', label='V5')
+    plt.plot(num_subjects, accuracies4, '#98CE00',marker='.', label='V3')
+    plt.plot(num_subjects, accuracies5, '#FFC857',marker='.', label='III')
+
+    plt.xlabel('Number of subjects', fontsize=16)
+    plt.ylabel('Accuracy (%)', fontsize=16)
+    plt.tick_params(axis='both', which='major', labelsize=12)
+    plt.legend()
+    plt.xlim((np.min(num_subjects),np.max(num_subjects)))
+    plt.grid(True, 'both')
+    plt.savefig('exp1_results/fig_exp1.png')
+    plt.show()
+    plt.close()
+
+
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print("Usage: python run_exp_1.py <data_path>")
+        sys.exit(1)
+    data_path = sys.argv[1]
+
+    run_experiment1(data_path)
+
+    
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