Update my_pages/ica.py

my_pages/ica.py

@@ -5,46 +5,50 @@ import numpy as np
 def render():
     st.title("Intentional / Conventional / Arbitrary Triangle")
 
-    # Initialize state for slider values
+    # Initialize session state for sliders
     if "intentional" not in st.session_state:
         st.session_state.intentional = 0.33
         st.session_state.conventional = 0.33
         st.session_state.arbitrary = 0.34
 
-    # Sliders for each dimension
-    new_intentional = st.slider("Intentional", 0.0, 1.0, st.session_state.intentional, 0.01)
-    new_conventional = st.slider("Conventional", 0.0, 1.0, st.session_state.conventional, 0.01)
-    new_arbitrary = st.slider("Arbitrary", 0.0, 1.0, st.session_state.arbitrary, 0.01)
+    # Sliders
+    intentional = st.slider("Intentional", 0.0, 1.0, st.session_state.intentional, 0.01)
+    conventional = st.slider("Conventional", 0.0, 1.0, st.session_state.conventional, 0.01)
+    arbitrary = st.slider("Arbitrary", 0.0, 1.0, st.session_state.arbitrary, 0.01)
 
-    # Update button
-    if st.button("Update Point"):
-        total = new_intentional + new_conventional + new_arbitrary
-        if total == 0:
-            total = 1  # avoid div by zero
-        st.session_state.intentional = new_intentional / total
-        st.session_state.conventional = new_conventional / total
-        st.session_state.arbitrary = new_arbitrary / total
+    # Normalize values so sum is always 1
+    total = intentional + conventional + arbitrary
+    if total == 0:
+        total = 1
+    intentional /= total
+    conventional /= total
+    arbitrary /= total
+
+    # Store back in session state
+    st.session_state.intentional = intentional
+    st.session_state.conventional = conventional
+    st.session_state.arbitrary = arbitrary
 
     # Plot triangle
     fig, ax = plt.subplots(figsize=(5, 5))
 
-    # Triangle vertices
-    vertices = np.array([[0.5, np.sqrt(3)/2], [0, 0], [1, 0]])  # Intentional, Conventional, Arbitrary
+    # Triangle vertices (Intentional, Conventional, Arbitrary)
+    vertices = np.array([[0.5, np.sqrt(3)/2], [0, 0], [1, 0]])
     labels = ["Intentional", "Conventional", "Arbitrary"]
 
-    # Draw triangle
+    # Draw triangle edges
     ax.plot([vertices[0][0], vertices[1][0]], [vertices[0][1], vertices[1][1]], 'k-')
     ax.plot([vertices[1][0], vertices[2][0]], [vertices[1][1], vertices[2][1]], 'k-')
     ax.plot([vertices[2][0], vertices[0][0]], [vertices[2][1], vertices[0][1]], 'k-')
 
-    # Add labels
+    # Add vertex labels
     for i, label in enumerate(labels):
         ax.text(vertices[i][0], vertices[i][1] + 0.05, label, ha='center', fontsize=12, fontweight='bold')
 
     # Convert (intentional, conventional, arbitrary) to XY coords
     point = (
-        st.session_state.conventional + 0.5 * st.session_state.intentional,
-        (np.sqrt(3)/2) * st.session_state.intentional
+        conventional + 0.5 * intentional,
+        (np.sqrt(3)/2) * intentional
     )
 
     # Plot point
@@ -54,11 +58,11 @@ def render():
     ax.axis('off')
     st.pyplot(fig)
 
-    # Display property based on dominant dimension
+    # Show dominant property description
     dominant = max(
-        ("Intentional", st.session_state.intentional),
-        ("Conventional", st.session_state.conventional),
-        ("Arbitrary", st.session_state.arbitrary),
+        ("Intentional", intentional),
+        ("Conventional", conventional),
+        ("Arbitrary", arbitrary),
         key=lambda x: x[1]
     )[0]