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[BUG] Preserve input dtype in shift_scale_invariant zero-padding #3773

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[BUG] Preserve input dtype in shift_scale_invariant zero-padding #3773

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[BUG] Preserve input dtype in shift_scale_invariant zero-padding
Jorge-Polanco-Roque Aug 30, 2026
e4d80f4
Merge branch 'main' into fix/shift-scale-invariant-float32
TonyBagnall Sep 2, 2026
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4 changes: 2 additions & 2 deletions aeon/distances/_shift_scale_invariant.py
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Original file line number Diff line number Diff line change
Expand Up @@ -141,10 +141,10 @@ def _univariate_shift_scale_invariant_distance(
shifted_y = y
elif sh < 0:
# Shift left
shifted_y = np.append(y[-sh:], np.zeros(-sh))
shifted_y = np.append(y[-sh:], np.zeros(-sh, dtype=y.dtype))
else:
# Shift right
shifted_y = np.append(np.zeros(sh), y[:-sh])
shifted_y = np.append(np.zeros(sh, dtype=y.dtype), y[:-sh])

dist = _scale_d(x, shifted_y)

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15 changes: 15 additions & 0 deletions aeon/distances/tests/test_miscellaneous_distances.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,3 +35,18 @@ def test_shift_scale_invariant_distance():
assert univariate_shift[1].shape == (10,)
assert isinstance(multivariate_shift[1], np.ndarray)
assert multivariate_shift[1].shape == (3, 10)


def test_shift_scale_invariant_distance_float32():
"""Test that float32 input does not raise a numba TypingError (#3722).

The zero-padding in the shift branches used to default to float64, which could
not unify with the float32 input inside the numba-compiled distance.
"""
x = make_example_2d_numpy_series(n_channels=1, n_timepoints=10, random_state=1)
y = make_example_2d_numpy_series(n_channels=1, n_timepoints=10, random_state=2)

dist64 = shift_scale_invariant_distance(x.astype(np.float64), y.astype(np.float64))
dist32 = shift_scale_invariant_distance(x.astype(np.float32), y.astype(np.float32))

assert_almost_equal(dist32, dist64, decimal=4)
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