ENH: vectorize cov
#507
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ENH: vectorize cov
#507
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mdhaber
commented
Oct 31, 2025
lucascolley
reviewed
Nov 1, 2025
| if xp.isdtype(m_transpose.dtype, "complex floating"): | ||
| m_transpose = xp.conj(m_transpose) | ||
| c = m @ m_transpose | ||
| c = xp.matmul(m, m_transpose) |
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what is the reason for this change?
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TBH I didn't know they were supposed to be equivalent until after looking it up. I wasn't sure what @ did for n-D arrays, and matmul is a lot easier to look up
If @ really does work like it should for all backends, it can be left alone. Do you know? If not, safer to use the function because it can be updated by array_api_compat.
| fact = 0 | ||
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| m -= avg[:, None] | ||
| m_transpose = m.T |
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That's not implemented in all backends yet (at least not CuPy and dask.array on colab) and it can't be added by array_api_compat.
mdhaber
commented
Nov 2, 2025
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Closes gh-502