Add mean bottle size, mathematical model

scripts/calculate_mean_bottle_size.py

@@ -0,0 +1,45 @@
+import numpy as np
+import pandas as pd
+
+
+filename_participants = "res/full_participant_measurement.csv"
+
+filename_left = "res/flowrate_left.csv"
+filename_right = "res/flowrate_right.csv"
+filename_both = "res/flowrate_both.csv"
+
+
+def main():
+    # Get bottle fillup times
+
+    df_part = pd.read_csv(filename_participants)
+
+    times_left = np.array(df_part[df_part["button"] == "left"]["time"])
+    times_right = np.array(df_part[df_part["button"] == "right"]["time"])
+    times_both = np.array(df_part[df_part["button"] == "both"]["time"])
+
+    # Get mean flowrates
+
+    df_left = pd.read_csv(filename_left)
+    df_right = pd.read_csv(filename_right)
+    df_both = pd.read_csv(filename_both)
+
+    flowrate_left = np.mean(np.array(df_left["flowrate"]))
+    flowrate_right = np.mean(np.array(df_right["flowrate"]))
+    flowrate_both = np.mean(np.array(df_both["flowrate"]))
+
+    # Calculate mean bottle size
+
+    sizes_left = times_left * flowrate_left
+    sizes_right = times_right * flowrate_right
+    sizes_both = times_both * flowrate_both
+
+    sizes = np.concatenate([sizes_left, sizes_right, sizes_both])
+
+    mean_size = np.mean(sizes)
+
+    print(f"Mean bottle size: {mean_size}")
+
+
+if __name__ == "__main__":
+    main()

scripts/perform_hypothesis_tests.py

@@ -16,7 +16,7 @@ def main():
     flowrate_right = np.array(df_right["flowrate"])
 
     df_both = pd.read_csv(filename_both)
-    flowrate_both = np.array(df_right["flowrate"])
+    flowrate_both = np.array(df_both["flowrate"])
     
     U_lr, p_lr = mannwhitneyu(flowrate_left, flowrate_both, method="exact")
     U_rb, p_rb = mannwhitneyu(flowrate_right, flowrate_both, method="exact")