Update app.py

app.py

@@ -77,6 +77,11 @@ ALL_DRIVER_LABELS = [
     "Workload",
 ]
 
+# =========================
+# UPDATED: Goal Average per driver = Cluster 3 mean per driver
+# =========================
+GOAL_AVG = {v: CLUSTER_3[v] for v in ALL_DRIVER_VARS}
+
 
 # =========================
 # Helpers
@@ -101,30 +106,30 @@ def risk_label(p: float) -> str:
     return "At Risk" if p >= 0.5 else "Not At Risk"
 
 
-def not_at_risk_threshold_from_cluster3():
-    """
-    threshold line = MIN of Cluster 3 across the driver vars in the averages chart,
-    labeled "Not at-risk threshold".
-    """
-    return min(CLUSTER_3[v] for v in ALL_DRIVER_VARS)
-
-
 # =========================
-# Plot: Average of key drivers + threshold
+# Plot: Average of key drivers + Goal Average (Cluster 3 means)
 # =========================
 def make_driver_plot(driver_vals: dict):
     values = [driver_vals[v] for v in ALL_DRIVER_VARS]
-    th = not_at_risk_threshold_from_cluster3()
+    goals = [GOAL_AVG[v] for v in ALL_DRIVER_VARS]
 
     fig, ax = plt.subplots(figsize=(8.6, 3.1))
-    ax.bar(ALL_DRIVER_LABELS, values)
 
-    # threshold line
-    ax.axhline(th, linestyle="--", linewidth=2)
+    # Bars (current values)
+    bars = ax.bar(range(len(ALL_DRIVER_LABELS)), values, tick_label=ALL_DRIVER_LABELS)
+
+    # UPDATED: draw a dashed goal line for each bar at that driver’s Cluster 3 mean
+    for i, b in enumerate(bars):
+        y = goals[i]
+        left = b.get_x()
+        right = b.get_x() + b.get_width()
+        ax.plot([left, right], [y, y], linestyle="--", linewidth=2)
+
+    # UPDATED: label it once as "Goal Average"
     ax.text(
-        len(ALL_DRIVER_LABELS) - 0.1,
-        th,
-        "Not at-risk threshold",
+        len(ALL_DRIVER_LABELS) - 0.02,
+        goals[-1],
+        "Goal Average",
         va="center",
         ha="right",
     )
@@ -256,6 +261,7 @@ def load_at_risk_group():
         shap_fig,
     )
 
+
 def apply_recommendation():
     # Recommendation = move toward high performers
     # average of Cluster 1 and Cluster 2
@@ -290,12 +296,10 @@ def apply_recommendation():
 # =========================
 CSS = """
 #app-wrap { max-width: 1200px; margin: 0 auto; }
-
 /* Remove extra padding/margins from blocks */
 .gr-block { padding: 10px 12px !important; }
 .gr-form { gap: 8px !important; }
 .gr-row { gap: 10px !important; }
-
 /* Make markdown tighter */
 .compact h2 { margin: 0 0 6px 0; }
 .compact p { margin: 0 0 8px 0; }
@@ -335,7 +339,7 @@ with gr.Blocks(css=CSS) as demo:
             shap_plot = gr.Plot(label="Feature Importance (Shap)")
 
     # =========================
-    # WIRE UP EVENTS (this was missing)
+    # WIRE UP EVENTS
     # =========================
     slider_inputs = [Engagement, SupportiveGM, WellBeing, WorkEnvironment, Voice, DecisionAutonomy, Workload]