Set random seed for all datasets

app.py

@@ -68,6 +68,7 @@ def get_moons(n_clusters):
 
 
 def get_noise(n_clusters):
+    np.random.seed(SEED)
     X, labels = np.random.rand(N_SAMPLES, 2), np.random.randint(0, n_clusters, size=(N_SAMPLES,))
     return normalize(X), labels
 
@@ -90,6 +91,7 @@ def get_varied(n_clusters):
 
 def get_spiral(n_clusters):
     # from https://scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering.html
+    np.random.seed(SEED)
     t = 1.5 * np.pi * (1 + 3 * np.random.rand(1, N_SAMPLES))
     x = t * np.cos(t)
     y = t * np.sin(t)