BUG: integrate.trapezoid: fix broadcasting issue #21912
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lucascolley
reviewed
Nov 19, 2024
integrate.trapezoid fixCo-authored-by: Lucas Colley <[email protected]>
lucascolley
reviewed
Nov 19, 2024
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| assert_allclose(trapezoid(y, x=np.array([0, 10., 20.]), axis=0), out0) | ||
| # x needs to be broadcastable against y | ||
| assert_allclose( | ||
| trapezoid(y, x=np.array([0, 10., 20.])[:, None], axis=0), | ||
| out0 | ||
| ) | ||
| with pytest.raises(Exception): | ||
| # x is not broadcastable against y | ||
| trapezoid(y, x=np.array([0, 10., 20.])[None, :], axis=0) | ||
|
|
||
| out1 = np.array([ 40.5, 130.5, 220.5]) | ||
| assert_allclose(trapezoid(y, x=x, axis=1), out1) | ||
| assert_allclose( | ||
| trapezoid(y, x=np.array(np.linspace(0, 9, 10)), axis=1), | ||
| out1 | ||
| ) |
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in case I wasn't clear, the rest of the test needs changes too (np -> xp, assert_allclose -> xp_assert_close)
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Closes #21908.
Fixes the 1-D case, and fixes another problem with the n-D case that wasn't picked up by our tests. The latter problem was that it wasn't possible to integrate with an
xarray that had exactly the same shape asy.The only selection rule for
xis that it needs to be broadcastable toyalong the axis of integration.