Added documentation

Home.py

@@ -80,17 +80,19 @@ if st.session_state.authenticated:
     col1, col2 = st.columns(2)
     
     with col1:
+        if st.button("📚 Documentation", key="doc_button", use_container_width=True):
+            st.switch_page("pages/01_Documentation.py")
         st.markdown("""
-            <div class="nav-button" onclick="window.location.href='/Documentation'">
-                <h3>Documentation</h3>
+            <div style="text-align: center; padding: 10px; border: 1px solid #e0e0e0; border-radius: 5px; margin-top: -10px;">
                 <p>Learn how the analysis works, how to use the tool, and what features are available</p>
             </div>
         """, unsafe_allow_html=True)
     
     with col2:
+        if st.button("🔧 Analysis Tool", key="tool_button", use_container_width=True):
+            st.switch_page("pages/02_Tool.py")
         st.markdown("""
-            <div class="nav-button" onclick="window.location.href='/Tool'">
-                <h3>Analysis Tool</h3>
+            <div style="text-align: center; padding: 10px; border: 1px solid #e0e0e0; border-radius: 5px; margin-top: -10px;">
                 <p>Generate visualizations and analyze task similarity for various sensor configurations</p>
             </div>
         """, unsafe_allow_html=True)

dashboard.py

@@ -6,6 +6,7 @@ import sys
 import numpy as np
 import matplotlib.pyplot as plt
 import seaborn as sns
+from mpl_toolkits.axes_grid1 import make_axes_locatable
 from multivariate_gaussian_overlap import calculate_similarity_portrait_abstraction
 from plot_similarity import plot_similarity_measure
 from sensor_illustration import LegIllustration
@@ -632,6 +633,21 @@ if st.session_state.authenticated:
                     task_y_name=task1_name_backend[0]
                 )
                 axs[1,1].set_title("Input Similarity")
+                
+                # Add a bar plot showing input similarity value
+                # Calculate the average input similarity
+                avg_input_similarity = np.mean(input_similarity)
+                # Create a small subplot above the heatmap for the bar plot
+                divider = make_axes_locatable(axs[1,1])
+                ax_bar = divider.append_axes("top", size="15%", pad=0.2)
+                # Create the bar plot
+                ax_bar.barh(y=0, width=avg_input_similarity, height=0.5, color='red')
+                ax_bar.set_xlim(0, 1)
+                ax_bar.set_ylim(-0.5, 0.5)
+                ax_bar.set_yticks([])
+                ax_bar.set_xticks([0, 0.25, 0.5, 0.75, 1.0])
+                ax_bar.set_title(f"Avg. Input Similarity: {avg_input_similarity:.2f}", fontsize=9)
+                ax_bar.grid(axis='x', linestyle='--', alpha=0.7)
 
                 # Ax[1,2]: Conflict Heatmap
                 if show_conflict and conflict_main is not None:

pages/02_Tool.py

@@ -628,7 +628,7 @@ if st.session_state.authenticated:
                     task_y_name=task1_name_backend[0]
                 )
                 axs[1,1].set_title("Input Similarity")
-
+                
                 # Ax[1,2]: Conflict Heatmap
                 if show_conflict and conflict_main is not None:
                     plot_similarity_measure(