`scipy.ndimage._fourier:fourier_uniform`

source: build-install/usr/lib/python3.14/site-packages/scipy/ndimage/_fourier.py:129

Signature

def fourier_uniform(input, size, n = -1, axis = -1, output = None)

Summary

Multidimensional uniform fourier filter.

Extended Summary

The array is multiplied with the Fourier transform of a box of given size.

Parameters

input : array_like: The input array.
size : float or sequence: The size of the box used for filtering. If a float, size is the same for all axes. If a sequence, size has to contain one value for each axis.
n : int, optional: If n is negative (default), then the input is assumed to be the result of a complex fft. If n is larger than or equal to zero, the input is assumed to be the result of a real fft, and n gives the length of the array before transformation along the real transform direction.
axis : int, optional: The axis of the real transform.
output : ndarray, optional: If given, the result of filtering the input is placed in this array.

Returns

fourier_uniform : ndarray: The filtered input.

Examples

from scipy import ndimage, datasets
import numpy.fft
import matplotlib.pyplot as plt
fig, (ax1, ax2) = plt.subplots(1, 2)
plt.gray()  # show the filtered result in grayscale
ascent = datasets.ascent()
input_ = numpy.fft.fft2(ascent)
result = ndimage.fourier_uniform(input_, size=20)
result = numpy.fft.ifft2(result)

✓

ax1.imshow(ascent)
ax2.imshow(result.real)  # the imaginary part is an artifact

✗

<matplotlib.image.AxesImage object at 0x7f3f59d66210>

plt.show()

✓

Aliases

scipy.ndimage.fourier_uniform