Update app.py

app.py

@@ -39,8 +39,11 @@ def _matrix_payload(np_mat: np.ndarray, labels: Optional[List[str]] = None):
     Return a safe gr.update payload for a Dataframe (headers must match col_count).
     """
     df = pd.DataFrame(np_mat)
-    # Round to 3 decimal places
+    # Format values to always show 3 decimal places
     df = df.round(3)
+    # Format each value to show exactly 3 decimal places
+    for col in df.columns:
+        df[col] = df[col].apply(lambda x: f"{x:.3f}")
     if labels is not None and len(labels) == df.shape[0]:
         df.index = labels
     if labels is not None and len(labels) == df.shape[1]:
@@ -58,7 +61,7 @@ def _plot_heatmap(D: np.ndarray, labels: Optional[List[str]] = None) -> np.ndarr
     # Set dark mode style
     plt.style.use('dark_background')
     
-    fig, ax = plt.subplots(figsize=(6, 5), dpi=160, facecolor='#1e1e1e')
+    fig, ax = plt.subplots(figsize=(6, 5), dpi=200, facecolor='#1e1e1e')
     ax.set_facecolor('#1e1e1e')
     
     im = ax.imshow(D, cmap="magma")
@@ -299,6 +302,14 @@ def run_compute(
         label_max_per_class=int(label_max_per_class),
     )
     D_np = D.detach().cpu().numpy()
+    
+    # Normalize distance matrix to [0, 1] range (min-max normalization)
+    d_min = D_np.min()
+    d_max = D_np.max()
+    if d_max > d_min:  # Avoid division by zero
+        D_np = (D_np - d_min) / (d_max - d_min)
+    else:
+        D_np = np.zeros_like(D_np)  # All values are the same, set to 0
 
     img = _plot_heatmap(D_np, labels=names)
     return (