`scipy.ndimage._fourier:fourier_gaussian`

source: build-install/usr/lib/python3.14/site-packages/scipy/ndimage/_fourier.py:71

Signature

def fourier_gaussian(input, sigma, n = -1, axis = -1, output = None)

Summary

Multidimensional Gaussian fourier filter.

Extended Summary

The array is multiplied with the fourier transform of a Gaussian kernel.

Parameters

input : array_like: The input array.
sigma : float or sequence: The sigma of the Gaussian kernel. If a float, sigma is the same for all axes. If a sequence, sigma 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_gaussian : 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_gaussian(input_, sigma=4)
result = numpy.fft.ifft2(result)

✓

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

✗

<matplotlib.image.AxesImage object at 0x7f3f68551810>

plt.show()

✓

Aliases

scipy.ndimage.fourier_gaussian