Accept strided inputs in Numba-backed features

src/antropy/entropy.py

@@ -859,7 +859,7 @@ def sample_entropy(x, order=2, tolerance=None, metric="chebyshev"):
         r = tolerance
     x = np.asarray(x, dtype=np.float64)
     if metric == "chebyshev" and x.size < 5000:
-        return _numba_sampen(x, order=order, r=r)
+        return _numba_sampen(np.ascontiguousarray(x), order=order, r=r)
     else:
         phi = _app_samp_entropy(x, order=order, r=r, metric=metric, approximate=False)
         return -np.log(np.divide(phi[1], phi[0]))

src/antropy/fractal.py

@@ -327,7 +327,7 @@ def higuchi_fd(x, kmax=10):
     """
     x = np.asarray(x, dtype=np.float64)
     kmax = int(kmax)
-    return _higuchi_fd(x, kmax)
+    return _higuchi_fd(np.ascontiguousarray(x), kmax)
 
 
 @jit((types.Array(types.float64, 1, "C", readonly=True),), nopython=True)
@@ -477,4 +477,4 @@ def detrended_fluctuation(x):
     2.0390
     """
     x = np.asarray(x, dtype=np.float64)
-    return _dfa(x)
+    return _dfa(np.ascontiguousarray(x))

tests/test_strided_inputs.py

@@ -0,0 +1,45 @@
+"""Public feature functions accept NumPy views as well as contiguous arrays."""
+
+import numpy as np
+import pytest
+
+import antropy as ant
+
+
+@pytest.mark.parametrize("name", ["sample_entropy", "higuchi_fd", "detrended_fluctuation"])
+@pytest.mark.parametrize("dtype", [np.float32, np.float64])
+@pytest.mark.parametrize("readonly", [False, True])
+@pytest.mark.parametrize("layout", ["step", "reverse", "column", "contiguous"])
+def test_numba_features_accept_array_views(name, dtype, readonly, layout):
+    """The same samples yield the same feature regardless of physical layout."""
+    source = np.random.default_rng(42).normal(size=(512, 3)).astype(dtype)
+    if layout == "step":
+        data = source[:, 0][::2]
+    elif layout == "reverse":
+        data = source[:, 0][::-1]
+    elif layout == "column":
+        data = source[:, 1]
+    else:
+        data = source[:, 1].copy()
+    if layout != "contiguous":
+        assert not data.flags.c_contiguous
+    data.flags.writeable = not readonly
+    original = data.copy()
+    feature = getattr(ant, name)
+    reference = feature(np.array(data, dtype=np.float64, copy=True, order="C"))
+
+    result = feature(data)
+
+    assert np.isfinite(reference)
+    assert result == reference
+    np.testing.assert_array_equal(data, original)
+    assert data.flags.writeable == (not readonly)
+
+
+@pytest.mark.parametrize("metric,size", [("chebyshev", 5000), ("euclidean", 512)])
+def test_sample_entropy_strided_kdtree_path(metric, size):
+    """The non-Numba routes retain their existing behavior."""
+    data = np.random.default_rng(52).normal(size=2 * size)[::2]
+    reference = ant.sample_entropy(data.copy(), metric=metric)
+
+    assert ant.sample_entropy(data, metric=metric) == reference