Update my_pages/rashomon_effect.py

my_pages/rashomon_effect.py

@@ -18,13 +18,6 @@ def render():
 
     st.markdown("---")
 
-    # Generate synthetic data
-    # np.random.seed(42)
-    # n_points = 100
-    # income = np.random.normal(50, 15, n_points)
-    # credit = np.random.normal(50, 15, n_points)
-    # labels = (income + credit > 100).astype(int)  # 1 = paid back, 0 = default
-
     income = np.array([80, 85, 97, 91, 78, 102, 84, 88, 45, 51, 34, 47, 38, 39, 97, 91, 38, 32])
     credit = np.array([970, 880, 1020, 910, 805, 800, 804, 708, 470, 309, 450, 304, 380, 501, 370, 301, 1080, 902])
     labels = np.array([1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1])
@@ -63,7 +56,7 @@ def render():
 
         # Highlight specific point
         if highlight_point is not None:
-            ax.scatter(*highlight_point, c='yellow', edgecolors='black', s=200, zorder=5)
+            ax.scatter(*highlight_point, c='yellow', edgecolors='black', s=200, zorder=5, alpha=0)
 
         ax.spines['right'].set_visible(False)
         ax.spines['top'].set_visible(False)
@@ -72,37 +65,37 @@ def render():
         
         return fig
 
-    # Top scatter plot (centered to match smaller width)
+
+    # Store highlight point based on selection
+    highlight_point = None
+    if vertical_selected:
+        highlight_point = (32, 902)
+    elif horizontal_selected:
+        highlight_point = (97, 370)  # Low credit score, high income
+    elif slant_selected:
+        highlight_point = (32, 902)  # Example point for slant model
+
+# Top scatter plot (centered to match smaller width)
     col1, col2, col3 = st.columns([1.5, 1, 1.5])
     with col2:
         st.pyplot(plot_scatter(income, credit, colors, title="Original Data"))
 
     col1, col2, col3, col4, col5 = st.columns([0.5, 1, 1, 1, 0.5])
     with col2:
-        st.pyplot(plot_scatter(income, credit, colors, boundary_type="vertical"))
+        st.pyplot(plot_scatter(income, credit, colors, boundary_type="vertical", highlight_point=highlight_point))
         vertical_selected = st.button("Choose Model 1")
     with col3:
-        st.pyplot(plot_scatter(income, credit, colors, boundary_type="slant"))
+        st.pyplot(plot_scatter(income, credit, colors, boundary_type="slant", highlight_point=highlight_point))
         slant_selected = st.button("Choose Model 2")
     with col4:
-        st.pyplot(plot_scatter(income, credit, colors, boundary_type="horizontal"))
+        st.pyplot(plot_scatter(income, credit, colors, boundary_type="horizontal", highlight_point=highlight_point))
         horizontal_selected = st.button("Choose Model 3")
 
-    # col1, col2, col3 = st.columns([1.5, 1, 1.5])
-    # Show new individual based on selection
-    # if left_selected:
-    #     new_point = (40, 80)  # High credit score, low income
-    #     with col2:
-    #         st.pyplot(plot_scatter(income, credit, colors,
-    #                                title="Vertical Boundary + New Individual",
-    #                                boundary_type="vertical",
-    #                                highlight_point=new_point))
-    #     st.warning("This individual was rejected by your chosen model. Why not choose a model that helps them?")
-    # elif right_selected:
-    #     new_point = (80, 40)  # Low credit score, high income
-    #     with col2:
-    #         st.pyplot(plot_scatter(income, credit, colors,
-    #                                title="Horizontal Boundary + New Individual",
-    #                                boundary_type="horizontal",
-    #                                highlight_point=new_point))
-    #     st.warning("This individual was rejected by your chosen model. Why not choose a model that helps them?")
+    st.markdown("---")
+    col1, col2, col3, col4 = st.columns([2, 1, 1, 1])
+    with col3:
+        if st.button("Go Home"):
+            go_to("home")
+    with col4:
+        if st.button("Next"):
+            go_to("developer_decisions")