Add files via upload

2024-06-18 13:18:37 -07:00
parent 9e69cc24ea
commit 6af40bc6cf
74 changed files with 8332 additions and 0 deletions
@@ -0,0 +1,50 @@
+import matplotlib
+import matplotlib.pyplot as plt
+import numpy as np
+import umap
+
+matplotlib.use("Agg")
+
+
+colormap = (
+    np.array(
+        [
+            [76, 255, 0],
+            [0, 127, 70],
+            [255, 0, 0],
+            [255, 217, 38],
+            [0, 135, 255],
+            [165, 0, 165],
+            [255, 167, 255],
+            [0, 255, 255],
+            [255, 96, 38],
+            [142, 76, 0],
+            [33, 0, 127],
+            [0, 0, 0],
+            [183, 183, 183],
+        ],
+        dtype=float,
+    )
+    / 255
+)
+
+
+def plot_embeddings(embeddings, num_classes_in_batch):
+    num_utter_per_class = embeddings.shape[0] // num_classes_in_batch
+
+    # if necessary get just the first 10 classes
+    if num_classes_in_batch > 10:
+        num_classes_in_batch = 10
+        embeddings = embeddings[: num_classes_in_batch * num_utter_per_class]
+
+    model = umap.UMAP()
+    projection = model.fit_transform(embeddings)
+    ground_truth = np.repeat(np.arange(num_classes_in_batch), num_utter_per_class)
+    colors = [colormap[i] for i in ground_truth]
+    fig, ax = plt.subplots(figsize=(16, 10))
+    _ = ax.scatter(projection[:, 0], projection[:, 1], c=colors)
+    plt.gca().set_aspect("equal", "datalim")
+    plt.title("UMAP projection")
+    plt.tight_layout()
+    plt.savefig("umap")
+    return fig