Pyvkfft

Latest version: v2024.1.4

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2024.1.4

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* support numpy >=2.0

2024.1.3

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* Correct handling of arrays where some axes
have a length of 1 [https://github.com/vincefn/pyvkfft/issues/34],
with a number of corner cases for R2C where the
fast axis must be transformed.

2024.1.2.post0

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* Fix nvcc search in setup.py without a CUDA_HOME type
environment variable under linux.

2024.1.2

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* Fix conda installation with specified ``cuda-version``,
notably for cuda 12.x support
* add conda-forge build test for cuda and opencl libraries

2024.1.1

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* Fix pycuda initialisation during accuracy tests (pyvkff-test).

2024.1

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* Based on VkFFT 1.3.4
* Add support for direct sine transforms (DST)
* R2C, DST and DCT now support arbitrary sizes (up to ~2^32,
same as C2C)
* Odd lengths for the fast axis is now supported for all R2C
transforms. Inplace transforms require using
the r2c_odd=True parameter
* Custom transform axes (strided) are now allowed also for R2C,
as long as the fast axis is transformed.
* added functions to access the size of the temporary buffer
created by VkFFT (if any), the type of algorithm used along
each axis (radix, Rader, Bluestein), and the number of
uploads for each transformed axis.
* DCT and DST now support F-ordered arrays
* Longer default test including multi-upload using radix,
Rader and Bluestein algorithms.
* The full test suite (including c2c, r2c, dct, dst, radix
and non-radix transforms, single and double precision)
now includes about 1.5 million unit tests
* The pyvkff-benchmark script can also test R2C, DCT and DST
transforms, and will give more details about the algorithm
used for performance tuning.
* Added pyvkfft-info script

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