mega commit

visualize.py

@@ -3,7 +3,6 @@ import matplotlib.pyplot as plt
 import pandas as pd
 import numpy as np
 import seaborn as sns
-from math import pi
 
 # Load the JSON data
 with open('saved_results.json', 'r') as f:
@@ -14,7 +13,7 @@ results = []
 for test_hash, test_data in data.items():
     results.append({
         "hash": test_hash,
-        "model": test_data['model'],
+        "model": test_data['model_name'],
         "seed": test_data['seed'],
         "test_name": test_data['test_name'],
         "validation": test_data['validation']
@@ -61,52 +60,7 @@ plt.savefig('validation_results_by_test_name.png')
 
 
 ## 3rd Chart
-# Prepare data for the spider chart
-models = df['model'].unique()
-
-# Calculate the pass rate for each model on each test
 pass_rate = pd.pivot_table(df, values='validation', index='model', columns='test_name', aggfunc="mean", fill_value=0)
-tests = df['test_name'].unique().tolist()
-
-# Initialize the spider plot
-num_vars = len(pass_rate)-1
-angles = np.linspace(0, 2 * np.pi, num_vars, endpoint=False).tolist()
-angles += [ angles[0] ]
-
-fig, ax = plt.subplots(figsize=(8, 8), subplot_kw=dict(polar=True))
-
-# Plot each model's performance
-for model in models:
-    values = pass_rate.loc[model].tolist()
-    values += [ values[0] ]
-    ax.fill(angles, values, alpha=0.25)
-    ax.plot(angles, values, label=model)
-# 
-
-# Configure the spider chart
-ax.set_theta_offset(pi / 2)
-ax.set_theta_direction(-1)
-
-tests.append(tests[0])
-tests.pop(0)
-
-ax.set_xticks(angles[:-1])
-ax.set_xticklabels(tests)
-
-ax.set_yticks(np.linspace(0, 1, 5))
-ax.set_yticklabels([f'{int(i * 100)}%' for i in np.linspace(0, 1, 5)], color="grey", size=8)
-ax.set_ylim(0, 1)
-
-plt.title('Model Performance on Each Test')
-plt.legend(loc='upper right', bbox_to_anchor=(1.1, 1.1))
-plt.tight_layout()
-plt.savefig('model_performance_spider_chart.png')
-
-
-
-
-
-# 4th chart
 # Create a heatmap
 plt.figure(figsize=(8, 8))
 sns.heatmap(pass_rate*100, annot=True, fmt=".0f", cmap=sns.color_palette("blend:#100,#255,#4a3", as_cmap=True), cbar=True, annot_kws={"size": 10})