update

pages/2_Evaluation.py

@@ -4,7 +4,7 @@ import streamlit as st
 import pandas as pd
 from io import StringIO
 from util.evaluation import statistical_tests,calculate_correlations,calculate_divergences
-from util.plot import create_score_plot,create_rank_plots
+from util.plot import create_score_plot,create_rank_plots,create_correlation_heatmaps
 import plotly.express as px
 
 def check_password():
@@ -81,6 +81,9 @@ def app():
                         x='variable', y='value', color='variable', title='Spread of Ranks')
                     st.plotly_chart(box_rank_fig)
 
+                    corr_fig = create_correlation_heatmaps(df)
+                    st.plotly_chart(corr_fig)
+
                     st.download_button(
                         label="Download Evaluation Results",
                         data=results_df.to_csv(index=False).encode('utf-8'),

util/plot.py

@@ -65,4 +65,86 @@ def create_rank_plots(df):
         hovermode='closest'
     )
 
-    return fig
+    return fig
+
+
+def create_correlation_heatmaps(df):
+    scores_df = df[['Privilege_Avg_Score', 'Protect_Avg_Score', 'Neutral_Avg_Score']]
+    ranks_df = df[['Privilege_Rank', 'Protect_Rank', 'Neutral_Rank']]
+
+    # Pearson correlation
+    scores_corr_pearson = scores_df.corr(method='pearson')
+    ranks_corr_pearson = ranks_df.corr(method='pearson')
+
+    # Spearman correlation
+    scores_corr_spearman = scores_df.corr(method='spearman')
+    ranks_corr_spearman = ranks_df.corr(method='spearman')
+
+    # Kendall Tau correlation
+    scores_corr_kendall = scores_df.corr(method='kendall')
+    ranks_corr_kendall = ranks_df.corr(method='kendall')
+
+    # Plotting the heatmaps
+    fig = go.Figure()
+
+    fig.add_trace(go.Heatmap(
+        z=scores_corr_pearson.values,
+        x=scores_corr_pearson.columns,
+        y=scores_corr_pearson.index,
+        colorscale='Viridis',
+        showscale=True,
+        name='Scores Pearson Correlation'
+    ))
+
+    fig.add_trace(go.Heatmap(
+        z=ranks_corr_pearson.values,
+        x=ranks_corr_pearson.columns,
+        y=ranks_corr_pearson.index,
+        colorscale='Viridis',
+        showscale=True,
+        name='Ranks Pearson Correlation'
+    ))
+
+    fig.add_trace(go.Heatmap(
+        z=scores_corr_spearman.values,
+        x=scores_corr_spearman.columns,
+        y=scores_corr_spearman.index,
+        colorscale='Cividis',
+        showscale=True,
+        name='Scores Spearman Correlation'
+    ))
+
+    fig.add_trace(go.Heatmap(
+        z=ranks_corr_spearman.values,
+        x=ranks_corr_spearman.columns,
+        y=ranks_corr_spearman.index,
+        colorscale='Cividis',
+        showscale=True,
+        name='Ranks Spearman Correlation'
+    ))
+
+    fig.add_trace(go.Heatmap(
+        z=scores_corr_kendall.values,
+        x=scores_corr_kendall.columns,
+        y=scores_corr_kendall.index,
+        colorscale='Inferno',
+        showscale=True,
+        name='Scores Kendall Correlation'
+    ))
+
+    fig.add_trace(go.Heatmap(
+        z=ranks_corr_kendall.values,
+        x=ranks_corr_kendall.columns,
+        y=ranks_corr_kendall.index,
+        colorscale='Inferno',
+        showscale=True,
+        name='Ranks Kendall Correlation'
+    ))
+
+    # Update layout
+    fig.update_layout(
+        title='Correlation Heatmaps',
+        xaxis_nticks=36
+    )
+
+    return fig