chore: add fisize

app.py

@@ -104,7 +104,14 @@ os.makedirs("plots", exist_ok=True)
 
 
 def plot_distances(
-    model, dataset, use_average, cluster_method, cluster_method_param, plot_fn
+    model,
+    dataset,
+    use_average,
+    cluster_method,
+    cluster_method_param,
+    plot_fn,
+    figsize_h,
+    figsize_w,
 ):
     """
     Plots all languages from the distances matrix using t-SNE.
@@ -143,6 +150,7 @@ def plot_distances(
         filtered_languages,
         clusters,
         legends,
+        fig_size=(figsize_w, figsize_h),
     )
     fig.tight_layout()
     fig.savefig(plot_path, format="pdf")
@@ -323,6 +331,14 @@ with gr.Blocks() as demo:
             plot_umap_button = gr.Button("Plot UMAP")
             plot_mst_button = gr.Button("Plot MST")
 
+        with gr.Row():
+            plot_figsize_dist_h_input = gr.Slider(
+                label="Figure Height", minimum=5, maximum=30, step=1, value=15
+            )
+            plot_figsize_dist_w_input = gr.Slider(
+                label="Figure Width", minimum=5, maximum=30, step=1, value=15
+            )
+
         with gr.Row():
             download_plot_button = gr.DownloadButton("Download Plot")
 
@@ -359,6 +375,8 @@ with gr.Blocks() as demo:
                 average_checkbox,
                 cluster_method_input,
                 clusters_input,
+                plot_figsize_dist_h_input,
+                plot_figsize_dist_w_input,
             ],
             outputs=[plot_output, download_plot_button],
         )

utils.py

@@ -212,7 +212,14 @@ def cluster_languages_hdbscan(dist_matrix, languages, min_cluster_size=2):
 
 
 def plot_distances_tsne(
-    model, dataset, use_average, matrix, languages, clusters, legend=None
+    model,
+    dataset,
+    use_average,
+    matrix,
+    languages,
+    clusters,
+    legend=None,
+    fig_size=(16, 12),
 ):
     """
     Plots all languages from the distances matrix using t-SNE and colors them by clusters.
@@ -225,7 +232,7 @@ def plot_distances_tsne(
     cmap = get_dynamic_color_map(len(unique_clusters))
     cluster_colors = {cluster: cmap[i] for i, cluster in enumerate(unique_clusters)}
 
-    fig, ax = plt.subplots(figsize=(16, 12))
+    fig, ax = plt.subplots(figsize=fig_size)
     scatter = ax.scatter(
         tsne_results[:, 0],
         tsne_results[:, 1],
@@ -272,7 +279,14 @@ def plot_distances_tsne(
 
 
 def plot_distances_umap(
-    model, dataset, use_average, matrix, languages, clusters, legend=None
+    model,
+    dataset,
+    use_average,
+    matrix,
+    languages,
+    clusters,
+    legend=None,
+    fig_size=(16, 12),
 ):
     """
     Plots all languages from the distances matrix using UMAP and colors them by clusters.
@@ -286,7 +300,7 @@ def plot_distances_umap(
     cmap = get_dynamic_color_map(len(unique_clusters))
     cluster_colors = {cluster: cmap[i] for i, cluster in enumerate(unique_clusters)}
 
-    fig, ax = plt.subplots(figsize=(16, 12))
+    fig, ax = plt.subplots(figsize=fig_size)
     scatter = ax.scatter(
         umap_results[:, 0],
         umap_results[:, 1],