2024.1.4

Version 2024.1.4 (2024-07-23)

• support numpy >=2.0

Version 2024.1.3 (2024-03-19)

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

Version 2024.1.2.post0 (2024-05-01)

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

Version 2024.1.2 (2024-02-17)

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

Version 2024.1.1 (2024-02-12)

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

Version 2024.1 (2024-02-06)

• 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