rollback last commit

app.py

@@ -2,8 +2,7 @@ import streamlit as st
 import pandas as pd
 import numpy as np
 import base64, pickle, textwrap
-import plotly.graph_objects as go
-from plotly.subplots import make_subplots
+import plotly.express as px
 
 # ---------------------------------------------------
 # Page configuration for wide layout
@@ -31,33 +30,45 @@ st.sidebar.title("Filters")
 
 def_opts = sorted(df['Dept Track'].dropna().astype(str).unique())
 def_stand = sorted(df['Standing'].dropna().astype(str).unique())
-# Clear filters
+
+# Clear filters button resets session state
 if st.sidebar.button("Clear All Filters"):
-    for key in ['standing', 'dept', 'names']:
-        st.session_state.pop(key, None)
+    st.session_state.pop('standing', None)
+    st.session_state.pop('dept', None)
+    st.session_state.pop('names', None)
 
-# Filter widgets
 standing_sel = st.sidebar.multiselect(
-    "Filter by Standing:", options=def_stand,
-    default=st.session_state.get('standing', def_stand), key='standing'
+    "Filter by Standing:",
+    options=def_stand,
+    default=st.session_state.get('standing', def_stand),
+    key='standing'
 )
+
 dept_sel = st.sidebar.multiselect(
-    "Filter by Dept Track:", options=def_opts,
-    default=st.session_state.get('dept', def_opts), key='dept'
+    "Filter by Dept Track:",
+    options=def_opts,
+    default=st.session_state.get('dept', def_opts),
+    key='dept'
 )
-# Names filter
+
+# Filter names based on selected Standing & Dept
 mask = (
-    df['Standing'].astype(str).isin(st.session_state.standing) &
-    df['Dept Track'].astype(str).isin(st.session_state.dept)
+    df['Standing'].astype(str).isin(standing_sel) &
+    df['Dept Track'].astype(str).isin(dept_sel)
 )
 name_opts = sorted(df.loc[mask, 'Name'].astype(str).unique())
+
+# Initialize or prune stored names
 if 'names' not in st.session_state or st.session_state.names is None:
     st.session_state.names = name_opts.copy()
 else:
     st.session_state.names = [n for n in st.session_state.names if n in name_opts]
+
 name_sel = st.sidebar.multiselect(
-    "Select Faculty:", options=name_opts,
-    default=st.session_state.names, key='names'
+    "Select Faculty:",
+    options=name_opts,
+    default=st.session_state.names,
+    key='names'
 )
 
 # ---------------------------------------------------
@@ -65,67 +76,42 @@ name_sel = st.sidebar.multiselect(
 # ---------------------------------------------------
 st.title("Faculty Heatmap Explorer")
 
+# Display heatmap (with optional row sums)
 if not name_sel:
     st.warning("No faculty selected — please choose at least one.")
+    fig = px.imshow(
+        [[0]],
+        labels={'x':'','y':'','color':'value'},
+        text_auto='.2f',
+        title="No faculty selected"
+    )
+    st.plotly_chart(fig, use_container_width=True)
 else:
-    # Combine and average matrices
+    # Combine matrices
     sum_df = None
     for name in name_sel:
         mat = filled_matrices[name]
         sum_df = mat if sum_df is None else sum_df.add(mat, fill_value=0)
     avg_df = sum_df.div(len(name_sel))
 
-    # Compute row sums
-    row_sums = avg_df.sum(axis=1)
-
-    # Wrap y labels
-    wrapped_y = wrap_labels(list(avg_df.index))
-    # x labels for main
-    wrapped_x_main = list(avg_df.columns)
-
-    # Determine color scale bounds
-    zmin = float(np.min(avg_df.values))
-    zmax = float(np.max(avg_df.values))
-
-    # Create subplots: main heatmap + sum column
-    fig = make_subplots(
-        rows=1, cols=2,
-        column_widths=[0.9, 0.1],
-        shared_yaxes=True,
-        horizontal_spacing=0.02,
-        subplot_titles=[f"Avg Heatmap for {len(name_sel)} Faculty", "Row Sum"]
-    )
-    # Main heatmap
-    fig.add_trace(
-        go.Heatmap(
-            z=avg_df.values,
-            x=wrapped_x_main,
-            y=wrapped_y,
-            text=np.round(avg_df.values, 2),
-            texttemplate="%{text}",
-            colorscale="Blues",
-            zmin=zmin, zmax=zmax,
-            colorbar=dict(title="Avg value", x=0.45)
-        ), row=1, col=1
-    )
-    # Sum column heatmap
-    fig.add_trace(
-        go.Heatmap(
-            z=row_sums.values.reshape(-1, 1),
-            x=["Sum"],
-            y=wrapped_y,
-            text=np.round(row_sums.values, 2),
-            texttemplate="%{text}",
-            colorscale="Blues",
-            zmin=zmin, zmax=zmax,
-            showscale=False
-        ), row=1, col=2
-    )
-    # Update layout
-    fig.update_yaxes(autorange='reversed', ticks='', tickfont=dict(size=10))
-    fig.update_xaxes(tickangle=45)
-    fig.update_layout(
-        height=800,
-        margin=dict(l=100, r=50, t=100, b=50)
+    # Add a sum column on the right
+    avg_df_ext = avg_df.copy()
+    avg_df_ext['Sum'] = avg_df_ext.sum(axis=1)
+
+    # Wrap y-axis labels for compact display
+    wrapped_y = wrap_labels(list(avg_df_ext.index))
+    wrapped_x = list(avg_df_ext.columns)
+
+    # Create heatmap
+    fig = px.imshow(
+        avg_df_ext.values,
+        x=wrapped_x,
+        y=wrapped_y,
+        labels={'color':'Avg value'},
+        text_auto='.2f',
+        title=f"Avg Heatmap for {len(name_sel)} Faculty"
     )
+    fig.update_yaxes(autorange='reversed')
+    # Set a taller figure height for wide layout
+    fig.update_layout(height=800, margin=dict(l=70, r=70, t=70, b=70))
     st.plotly_chart(fig, use_container_width=True)