`scipy.fft._basic:rfft2`

source: /scipy/fft/_basic.py :1136

Signature

   def     rfft2 (    x    ,    s    =  None   ,    axes    =  (-2, -1)   ,    norm    =  None   ,    overwrite_x    =  False   ,    workers    =  None   ,  * ,     plan    =  None     )

Summary

Compute the 2-D FFT of a real array.

Parameters

x : array: Input array, taken to be real.
s : sequence of ints, optional: Shape of the FFT.
axes : sequence of ints, optional: Axes over which to compute the FFT.
norm : {"backward", "ortho", "forward"}, optional: Normalization mode (see fft). Default is "backward".
overwrite_x : bool, optional: If True, the contents of x can be destroyed; the default is False. See fft for more details.
workers : int, optional: Maximum number of workers to use for parallel computation. If negative, the value wraps around from os.cpu_count(). See fft for more details.
plan : object, optional: This argument is reserved for passing in a precomputed plan provided by downstream FFT vendors. It is currently not used in SciPy.
versionadded 1.5.0

Returns

out : ndarray: The result of the real 2-D FFT.

Notes

This is really just rfftn with different default behavior. For more details see rfftn.

Array API Standard Support

rfft2 has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

====================  ====================  ====================
Library               CPU                   GPU
====================  ====================  ====================
NumPy                 ✅                     n/a                 
CuPy                  n/a                   ✅                   
PyTorch               ✅                     ✅                   
JAX                   ✅                     ✅                   
Dask                  ⚠️ computes graph     n/a                 
====================  ====================  ====================

See dev-arrayapi for more information.

Examples

import scipy.fft
import numpy as np
x = np.broadcast_to([1, 0, -1, 0], (4, 4))
scipy.fft.rfft2(x)

✓

Aliases

scipy.fft.rfft2