🚧 Adds (non-working) boxplot

analyze.py

@@ -1,7 +1,14 @@
 from typing import List
+import argparse
 
 import numpy as np
 import scipy.stats as stats
+import matplotlib.pyplot as plt
+
+parser = argparse.ArgumentParser()
+parser.add_argument("-g", "--graph", action="store_true", default=False, help="Plot graph")
+args = parser.parse_args()
+graph = args.graph
 
 
 def analyze(name: str, data: List[np.ndarray]):
@@ -11,8 +18,37 @@ def analyze(name: str, data: List[np.ndarray]):
 
     if p > 0.05:
         print("statistically insignificant\n")
-        return
+        return F, p
 
     print("statistically significant")
     tukey_results = stats.tukey_hsd(*data)
     print(tukey_results)
+
+    return F, p
+
+
+def plot_box(data, labels, Fs, ps, title, titles):
+    if not graph:
+        return
+
+    fig, axs = plt.subplots(2, 2, sharex=True)
+    fig.suptitle(title)
+    fig.set_size_inches(12, 9)
+
+    for i in range(2):
+        for j in range(2):
+            print(f"{i}x{j} giving {i * 2 + j}")
+            axs[i, j].boxplot(data[i * 2 + j], labels=labels)
+            axs[i, j].set_title(titles[i * 2 + j])
+
+            F = round(Fs[i * 2 + j], 2)
+            p = round(ps[i * 2 + j], 4)
+            axs[i, j].text(0.01, 0.99, f"F-stat: {F}\np-val: {p}", ha="left", va="top", transform=axs[i, j].transAxes,
+                           fontweight="bold")
+
+            avgs = np.array([a.mean() for a in data[i * 2 + j]])
+            print(avgs)
+
+    fig.tight_layout()
+    fig.show()
+    plt.show()