Handling all zero pairwise distances case

Signed-off-by: Nicholas Parente <[email protected]>

dodiscover/toporder/utils.py

@@ -19,8 +19,9 @@ def kernel_width(X: NDArray):
         Matrix of the data.
     """
     X_diff = np.expand_dims(X, axis=1) - X  # Gram matrix of the data
-    D = np.linalg.norm(X_diff, axis=2)
-    s = np.median(D.flatten()[D.flatten() > 0])  # removes zero elements
+    D = np.linalg.norm(X_diff, axis=2).flatten()
+    D_nonzeros = D[D > 0]  # Remove zeros
+    s = np.median(D_nonzeros) if np.any(D_nonzeros) else 1
     return s
 
 

tests/unit_tests/toporder/test_utils.py

@@ -7,3 +7,7 @@ def test_kernel_width_when_zero_median_pairwise_distances():
     arr = np.zeros((100, 1), dtype=np.int64)
     arr[1] = 1
     assert kernel_width(arr) == 1
+
+def test_kernel_width_when_constant_pairwise_distances():
+    arr = np.ones((100, 1), dtype=np.int64)
+    assert kernel_width(arr) == 1