Add quantile as parameter in the UI

app.py

@@ -5,12 +5,12 @@ from sklearn.cluster import MeanShift, estimate_bandwidth
 from sklearn.datasets import make_blobs
 
 
-def get_clusters_plot(n_blobs, cluster_std):
+def get_clusters_plot(n_blobs, quantile, cluster_std):
     X, _, centers = make_blobs(
         n_samples=10000, cluster_std=cluster_std, centers=n_blobs, return_centers=True
     )
 
-    bandwidth = estimate_bandwidth(X, quantile=0.2, n_samples=500)
+    bandwidth = estimate_bandwidth(X, quantile=quantile, n_samples=500)
 
     ms = MeanShift(bandwidth=bandwidth, bin_seeding=True)
     ms.fit(X)
@@ -20,25 +20,22 @@ def get_clusters_plot(n_blobs, cluster_std):
     labels_unique = np.unique(labels)
     n_clusters_ = len(labels_unique)
 
-    colors = ["#dede00", "#377eb8", "#f781bf"]
-    markers = ["x", "o", "^"]
-
     fig = plt.figure()
 
-    for k, col in zip(range(n_clusters_), colors):
+    for k in range(n_clusters_):
         my_members = labels == k
         cluster_center = cluster_centers[k]
-        plt.plot(X[my_members, 0], X[my_members, 1], markers[k], color=col)
+        plt.scatter(X[my_members, 0], X[my_members, 1])
         plt.plot(
             cluster_center[0],
             cluster_center[1],
-            markers[k],
-            markerfacecolor=col,
+            "x",
             markeredgecolor="k",
             markersize=14,
         )
 
-    return fig
+    message = f"## True Clusters: {len(centers)} | Detected Clusters: {n_clusters_}"
+    return fig, message
 
 
 demo = gr.Interface(
@@ -47,6 +44,14 @@ demo = gr.Interface(
         gr.Slider(
             minimum=2, maximum=10, label="Number of clusters in data", step=1, value=3
         ),
+        gr.Slider(
+            minimum=0,
+            maximum=1,
+            step=0.05,
+            value=0.2,
+            label="Quantile",
+            info="Used to determine clustering's bandwidth.",
+        ),
         gr.Slider(
             minimum=0.1,
             maximum=1,
@@ -55,7 +60,7 @@ demo = gr.Interface(
             value=0.6,
         ),
     ],
-    gr.Plot(),
+    [gr.Plot(), gr.Markdown()],
     allow_flagging="never",
 )