xorbits.numpy.fft.ifftn#

xorbits.numpy.fft.ifftn(a, s=None, axes=None, norm=None)[源代码]#

Compute the N-dimensional inverse discrete Fourier Transform.

This function computes the inverse of the N-dimensional discrete Fourier Transform over any number of axes in an M-dimensional array by means of the Fast Fourier Transform (FFT). In other words, ifftn(fftn(a)) == a to within numerical accuracy. For a description of the definitions and conventions used, see numpy.fft.

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.

参数

  • a (array_like) – Input array, can be complex.

  • s (sequence of ints, optional) – Shape (length of each transformed axis) of the output (s[0] refers to axis 0, s[1] 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.

  • axes (sequence 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. Repeated indices in axes means that the inverse transform over that axis is performed multiple times.

  • norm ({"backward", "ortho", "forward"}, optional) –

    1.10.0(numpy.fft) 新版功能.

    Normalization mode (see numpy.fft). Default is “backward”. Indicates which direction of the forward/backward pair of transforms is scaled and with what normalization factor.

    1.20.0(numpy.fft) 新版功能: The “backward”, “forward” values were added.

返回

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

返回类型

complex ndarray

引发

  • ValueError – If s and axes have different length.

  • IndexError – If an element of axes is larger than than the number of axes of a.

参见

numpy.fft

Overall view of discrete Fourier transforms, with definitions and conventions used.

fftn

The forward n-dimensional FFT, of which ifftn is the inverse.

ifft

The one-dimensional inverse FFT.

ifft2

The two-dimensional inverse FFT.

ifftshift

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

提示

See numpy.fft for definitions and conventions used.

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.

实际案例

>>> a = np.eye(4)  
>>> np.fft.ifftn(np.fft.fftn(a, 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  
>>> n = np.zeros((200,200), dtype=complex)  
>>> n[60:80, 20:40] = np.exp(1j*np.random.uniform(0, 2*np.pi, (20, 20)))  
>>> im = np.fft.ifftn(n).real  
>>> plt.imshow(im)  
<matplotlib.image.AxesImage object at 0x...>
>>> plt.show()

This docstring was copied from numpy.fft.