Update app.py

app.py

@@ -63,7 +63,7 @@ def do_submit(n_points_per_cluster, min_samples, xi, min_cluster_size):
     reachability = clust.reachability_[clust.ordering_]
     labels = clust.labels_[clust.ordering_]
 
-    plt.figure(figsize=(10, 7))
+    plt.figure(figsize=(10, 6))
     G = gridspec.GridSpec(2, 3)
     ax1 = plt.subplot(G[0, :])
     ax2 = plt.subplot(G[1, 0])
@@ -125,47 +125,71 @@ with gr.Blocks(title=title, theme=theme) as demo:
         the different clusters of OPTICS’s Xi method can be recovered with different choices of thresholds in DBSCAN."
     )
 
-    n_points_per_cluster = gr.Slider(
-        minimum=200,
-        maximum=500,
-        label="Number of points per cluster",
-        step=50,
-        value=250,
-    )
-    min_samples = gr.Slider(
-        minimum=10,
-        maximum=100,
-        label="OPTICS - Minimum number of samples",
-        step=5,
-        value=50,
-        info="The number of samples in a neighborhood for a point to be considered as a core point.",
-    )
-    xi = gr.Slider(
-        minimum=0,
-        maximum=0.2,
-        label="OPTICS - Xi",
-        step=0.05,
-        value=0.05,
-        info="Determines the minimum steepness on the reachability plot that constitutes a cluster boundary. ",
-    )
+    with gr.Row().style(equal_height=True):
+        with gr.Column(scale=0.75):
+            n_points_per_cluster = gr.Slider(
+                minimum=200,
+                maximum=500,
+                label="Number of points per cluster",
+                step=50,
+                value=250,
+            )
+            with gr.Row(visible=False):
+                gr.Markdown("##")
+
+            min_samples = gr.Slider(
+                minimum=10,
+                maximum=100,
+                label="OPTICS - Minimum number of samples",
+                step=5,
+                value=50,
+                info="The number of samples in a neighborhood for a point to be considered as a core point.",
+            )
+            with gr.Row(visible=False):
+                gr.Markdown("##")
+
+            xi = gr.Slider(
+                minimum=0,
+                maximum=0.2,
+                label="OPTICS - Xi",
+                step=0.01,
+                value=0.05,
+                info="Determines the minimum steepness on the reachability plot that constitutes a cluster boundary. ",
+            )
+            with gr.Row(visible=False):
+                gr.Markdown("##")
+            min_cluster_size = gr.Slider(
+                minimum=0.01,
+                maximum=0.1,
+                label="OPTICS - Minimum cluster size",
+                step=0.01,
+                value=0.05,
+                info="Minimum number of samples in an OPTICS cluster, expressed as an absolute number or a fraction of the number of samples (rounded to be at least 2).",
+            )
+
+        plt_out = gr.Plot()
+
+        n_points_per_cluster.change(
+            do_submit,
+            inputs=[n_points_per_cluster, min_samples, xi, min_cluster_size],
+            outputs=plt_out,
+        )
+        min_samples.change(
+            do_submit,
+            inputs=[n_points_per_cluster, min_samples, xi, min_cluster_size],
+            outputs=plt_out,
+        )
+        xi.change(
+            do_submit,
+            inputs=[n_points_per_cluster, min_samples, xi, min_cluster_size],
+            outputs=plt_out,
+        )
+        min_cluster_size.change(
+            do_submit,
+            inputs=[n_points_per_cluster, min_samples, xi, min_cluster_size],
+            outputs=plt_out,
+        )
 
-    min_cluster_size = gr.Slider(
-        minimum=0.01,
-        maximum=0.1,
-        label="OPTICS - Minimum cluster size",
-        step=0.01,
-        value=0.05,
-        info="Minimum number of samples in an OPTICS cluster, expressed as an absolute number or a fraction of the number of samples (rounded to be at least 2).",
-    )
-
-    plt_out = gr.Plot()
-
-    sub_btn = gr.Button("Submit")
-    sub_btn.click(
-        fn=do_submit,
-        inputs=[n_points_per_cluster, min_samples, xi, min_cluster_size],
-        outputs=[plt_out],
-    )
 
 
 if __name__ == "__main__":