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ENH: enable fast indexed loops for complex add, subtract, multiply
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Continuation of the ufunc.at optimizations:
add indexed loops for maximum, minimum, fmax, fmin ufuncs and a benchmark for maximum.at (performance increased by ~13x)
* BENCH: add np.maximum.at benchmark
* remove 'explain_chain'
* add a seed to `default_rng() (from review)
* MAINT: formatting and change comments, from review
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Matti was wondering where it came from, so lets comment it out.
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ENH: create and use indexed inner loops
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Correct floating point types on several npyrandom functions exposed for Cython in c_distributions.pyx, add missing float functions
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ENH: Allow trivial pickling of user DType (classes)
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This also adds a `_legac` attribute, I am happy to rename it, but
I suspect having something like it is useful.
Arguably, the best solution would be to give our DTypes a working
module+name, but given that we are not there, this seems easy.
We could probably check for `__reduce__`, but I am not certain that
wouldn't pre-empt successfully already, so this just restores the
default for now.
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TYP,MAINT: Remove typing-related Python <3.9 leftovers
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library
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definition
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BLD: musllinux wheel build
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ENH: re-implement SIMD kernels of complex operations
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no performance gain with AVX512 enabled except for absolute
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access for complex load/store
summarized as follows:
64-bit contiguous partial load/store over 32-bit lane
npyv_load2_till_u32, npyv_load2_till_s32, npyv_load2_till_f32
npyv_load2_tillz_u32, npyv_load2_tillz_s32, npyv_load2_tillz_f32
npyv_store2_till_u32, npyv_store2_till_s32, npyv_store2_till_f32
128-bit contiguous partial load/store over 64-bit lane
npyv_load2_till_u64, npyv_load2_till_s64, npyv_load2_till_f64
npyv_load2_tillz_u64, npyv_load2_tillz_s64, npyv_load2_tillz_f64
npyv_store2_till_u64, npyv_store2_till_s64, npyv_store2_till_f64
64-bit non-contiguous load/store over 32-bit stride
npyv_loadn2_u32, npyv_loadn2_s32, npyv_loadn2_f32
npyv_storen2_u32, npyv_storen2_s32, npyv_storen2_f32
128-bit non-contiguous load/store over 64-bit stride
npyv_loadn2_u64, npyv_loadn2_s64, npyv_loadn2_f64
npyv_storen2_u64, npyv_storen2_s64, npyv_storen2_f64
64-bit non-contiguous partial load/store over 32-bit stride
npyv_loadn2_till_u32, npyv_loadn2_till_s32, npyv_loadn2_till_f32
npyv_loadn2_tillz_u32, npyv_loadn2_tillz_s32, npyv_loadn2_tillz_f32
npyv_storen2_till_u32, npyv_storen2_till_s32, npyv_storen2_till_f32
128-bit non-contiguous partial load/store over 64-bit stride
npyv_loadn2_till_u64, npyv_loadn2_till_s64, npyv_loadn2_till_f64
npyv_loadn2_tillz_u64, npyv_loadn2_tillz_s64, npyv_loadn2_tillz_f64
npyv_storen2_till_u64, npyv_storen2_till_s64, npyv_storen2_till_f64
2 channels de-interlave/interleave contiguous load/store for all data types
npyv_load_##sfx##x2, npyv_store_##sfx##x2
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New kernels provides better performance for non-contiguous
memory access and don't require 128-bit/64-bit aligment
for complex128/complex64 just 64-bit/32-bit, and implmented
via universal intrinics.
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shuffle intrinsics support 32-bit/64-bit vector data types,
unzip(deinterleave) intrinsics supports all data types.
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MAINT: Allow export/import of bools in dlpack
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Updates the header file and accept as well as export boolean now that
the header includes a definition for it.
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CI: Rebase NumPy compiled extension test modules on Cygwin
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This assumes NumPy is rebased before tests run,
but does not assume the locations are in the database.
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Also adjust CI so they don't immediately collide with NumPy.
I forgot to do that last time, which caused problems.
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