https://github.com/enthought/mkl_fft

Default Repo description from terraform module
https://github.com/enthought/mkl_fft

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Default Repo description from terraform module

• Host: GitHub
• URL: https://github.com/enthought/mkl_fft
• Owner: enthought
• License: bsd-3-clause
• Created: 2018-06-07T11:55:47.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2018-04-20T16:27:36.000Z (about 8 years ago)
• Last Synced: 2024-12-27T02:42:42.459Z (over 1 year ago)
• Language: Python
• Homepage:
• Size: 40 KB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

          
## ``mkl_fft`` --  a NumPy-based Python interface to Intel (R) MKL FFT functionality

`mkl_fft` started as a part of Intel (R) Distribution for Python* optimizations to NumPy, and is now being released 

as a stand-alone package. It can be installed into conda environment using 

```

   conda install -c intel mkl_fft

```

---

Since MKL FFT supports performing discrete Fourier transforms over non-contiguously laid out arrays, MKL can be directly

used on any well-behaved floating point array with no internal overlaps for both in-place and not in-place transforms of 

arrays in single and double floating point precision.

This eliminates the need to copy input arrayy contiguously into an intermediate buffer.

`mkl_fft` directly supports N-dimensional Fourier transforms.

More details can be found in SciPy 2017 conference proceedings:

     https://github.com/scipy-conference/scipy_proceedings/tree/2017/papers/oleksandr_pavlyk

---

It implements the following functions:

### Complex transforms, similar to those in `scipy.fftpack`:

`fft(x, n=None, axis=-1, overwrite_x=False)`

`ifft(x, n=None, axis=-1, overwrite_x=False)`

`fft2(x, shape=None, axes=(-2,-1), overwrite_x=False)`

`ifft2(x, shape=None, axes=(-2,-1), overwrite_x=False)`

`fftn(x, n=None, axes=None, overwrite_x=False)`

`ifftn(x, n=None, axes=None, overwrite_x=False)`

### Real transforms

`rfft(x, n=None, axis=-1, overwrite_x=False)` - real 1D Fourier transform, like `scipy.fftpack.rfft`

`rfft_numpy(x, n=None, axis=-1)` - real 1D Fourier transform, like `numpy.fft.rfft`

`rfft2_numpy(x, s=None, axes=(-2,-1))` - real 2D Fourier transform, like `numpy.fft.rfft2`

`rfftn_numpy(x, s=None, axes=None)` - real 2D Fourier transform, like `numpy.fft.rfftn`

... and similar `irfft*` functions.

The package also provides `mkl_fft._numpy_fft` and `mkl_fft._scipy_fft` interfaces which provide drop-in replacements for equivalent functions in NumPy and SciPy respectively.

--- 

To build ``mkl_fft`` from sources on Linux:

  - install a recent version of MKL, if necessary;

  - execute ``source /path/to/mklroot/bin/mklvars.sh intel64`` ; 

  - execute ``pip install .``