Update app.py

app.py

@@ -4,7 +4,7 @@ import numpy as np
 import pandas as pd
 import plotly.graph_objects as go
 from plotly.subplots import make_subplots
-from umap.umap_ import UMAP
+from umap import UMAP
 from sklearn.cluster import KMeans
 from scipy.stats import entropy as shannon_entropy
 from scipy import special as sp_special
@@ -118,8 +118,11 @@ else:
     n_dummy_items_per_category = 50 
     
     rng = np.random.default_rng(42)
-    dog_labels = ["bark", "growl", "whine", "pant"] * (n_dummy_items_per_category // 4)
-    human_labels = ["speech", "laugh", "cry", "shout"] * (n_dummy_items_per_category // 4)
+    # Ensure labels match the exact number of items
+    base_dog_labels = ["bark", "growl", "whine", "pant"]
+    base_human_labels = ["speech", "laugh", "cry", "shout"]
+    dog_labels = [base_dog_labels[i % len(base_dog_labels)] for i in range(n_dummy_items_per_category)]
+    human_labels = [base_human_labels[i % len(base_human_labels)] for i in range(n_dummy_items_per_category)]
     dog_rows = {
         "feature_1": rng.random(n_dummy_items_per_category), "feature_2": rng.random(n_dummy_items_per_category), "feature_3": rng.random(n_dummy_items_per_category),
         "label": dog_labels, "filepath": [f"dog_{i}.wav" for i in range(n_dummy_items_per_category)],