Fix fftconvolve axis handling

src/pyrecest/_backend/pytorch/signal.py

@@ -5,6 +5,8 @@
 
 
 def _coerce_axis(axis):
+    if isinstance(axis, bool):
+        return int(axis)
     try:
         axis_array = _np.asarray(axis)
     except (TypeError, ValueError) as exc:

tests/backend/test_pytorch_signal_bool_axes.py

@@ -0,0 +1,39 @@
+from __future__ import annotations
+
+import numpy as np
+import pytest
+
+pytorch_backend = pytest.importorskip("pyrecest._backend.pytorch")
+
+
+@pytest.mark.parametrize(
+    ("axes", "expected"),
+    [
+        (
+            False,
+            [[0.5, 2.0, 1.5], [3.5, 9.0, 7.5], [6.0, 10.0, 9.0]],
+        ),
+        (
+            True,
+            [[0.5, 2.0, 4.0, 4.0, 1.5], [6.0, 15.5, 25.0, 19.5, 9.0]],
+        ),
+    ],
+)
+def test_fftconvolve_accepts_python_bool_axes_like_scalar_axes(
+    axes: bool,
+    expected: list[list[float]],
+) -> None:
+    in1 = pytorch_backend.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
+    in2 = pytorch_backend.array([[0.5, 1.0, 0.5], [1.5, 2.0, 1.5]])
+
+    result = pytorch_backend.signal.fftconvolve(in1, in2, axes=axes)
+
+    assert pytorch_backend.allclose(result, pytorch_backend.array(expected))
+
+
+def test_fftconvolve_rejects_numpy_bool_axis() -> None:
+    in1 = pytorch_backend.ones((2, 3))
+    in2 = pytorch_backend.ones((2, 3))
+
+    with pytest.raises((TypeError, ValueError)):
+        pytorch_backend.signal.fftconvolve(in1, in2, axes=np.bool_(True))