AS merged

rdas/AS.py

@@ -0,0 +1,26 @@
+from typing import Callable
+import numpy as np
+
+def check_input(X):
+    # X : ndarray of input samples
+
+    assert len(X.shape) == 2 and type(X) == np.ndarray, 'X should be a 2d numpy array'
+    N, d = X.shape
+    return X, N, d
+
+def get_n(S):
+    ediff = np.fabs(np.diff(S.reshape((S.size,))))
+    n = np.argmax(ediff)+1
+
+    return n
+
+def compute_AS(X: np.ndarray, kde_pdf) -> np.ndarray:
+    # X : ndarray - input samples
+    # f_deriv : Callable - function derivative
+
+    X, N, d = check_input(X)
+
+    G = 1/np.sqrt(N) * np.column_stack([kde_pdf.grad(x) for x in X])
+    U, S, Vh = np.linalg.svd(G)
+
+    return get_n(S)