# scipy.fft.ifftn#

scipy.fft.ifftn(x, s=None, axes=None, norm=None, overwrite_x=False, workers=None, *, plan=None)[source]#

Compute the N-D inverse discrete Fourier Transform.

This function computes the inverse of the N-D discrete Fourier Transform over any number of axes in an M-D array by means of the Fast Fourier Transform (FFT). In other words, `ifftn(fftn(x)) == x` to within numerical accuracy.

The input, analogously to `ifft`, should be ordered in the same way as is returned by `fftn`, i.e., it should have the term for zero frequency in all axes in the low-order corner, the positive frequency terms in the first half of all axes, the term for the Nyquist frequency in the middle of all axes and the negative frequency terms in the second half of all axes, in order of decreasingly negative frequency.

Parameters:
xarray_like

Input array, can be complex.

ssequence of ints, optional

Shape (length of each transformed axis) of the output (`s` refers to axis 0, `s` to axis 1, etc.). This corresponds to `n` for `ifft(x, n)`. Along any axis, if the given shape is smaller than that of the input, the input is cropped. If it is larger, the input is padded with zeros. if s is not given, the shape of the input along the axes specified by axes is used. See notes for issue on `ifft` zero padding.

axessequence of ints, optional

Axes over which to compute the IFFT. If not given, the last `len(s)` axes are used, or all axes if s is also not specified.

norm{“backward”, “ortho”, “forward”}, optional

Normalization mode (see `fft`). Default is “backward”.

overwrite_xbool, optional

If True, the contents of x can be destroyed; the default is False. See `fft` for more details.

workersint, 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.

planobject, optional

This argument is reserved for passing in a precomputed plan provided by downstream FFT vendors. It is currently not used in SciPy.

New in version 1.5.0.

Returns:
outcomplex ndarray

The truncated or zero-padded input, transformed along the axes indicated by axes, or by a combination of s or x, as explained in the parameters section above.

Raises:
ValueError

If s and axes have different length.

IndexError

If an element of axes is larger than the number of axes of x.

`fftn`

The forward N-D FFT, of which `ifftn` is the inverse.

`ifft`

The 1-D inverse FFT.

`ifft2`

The 2-D inverse FFT.

`ifftshift`

Undoes `fftshift`, shifts zero-frequency terms to beginning of array.

Notes

Zero-padding, analogously with `ifft`, is performed by appending zeros to the input along the specified dimension. Although this is the common approach, it might lead to surprising results. If another form of zero padding is desired, it must be performed before `ifftn` is called.

Examples

```>>> import scipy.fft
>>> import numpy as np
>>> x = np.eye(4)
>>> scipy.fft.ifftn(scipy.fft.fftn(x, axes=(0,)), axes=(1,))
array([[1.+0.j,  0.+0.j,  0.+0.j,  0.+0.j], # may vary
[0.+0.j,  1.+0.j,  0.+0.j,  0.+0.j],
[0.+0.j,  0.+0.j,  1.+0.j,  0.+0.j],
[0.+0.j,  0.+0.j,  0.+0.j,  1.+0.j]])
```

Create and plot an image with band-limited frequency content:

```>>> import matplotlib.pyplot as plt
>>> rng = np.random.default_rng()
>>> n = np.zeros((200,200), dtype=complex)
>>> n[60:80, 20:40] = np.exp(1j*rng.uniform(0, 2*np.pi, (20, 20)))
>>> im = scipy.fft.ifftn(n).real
>>> plt.imshow(im)
<matplotlib.image.AxesImage object at 0x...>
>>> plt.show()
```