ihfft2

paddle.fft. ihfft2 ( x: Tensor, s: list[int] | tuple[int, int] | None = None, axes: list[int] | tuple[int, int] = (- 2, - 1), norm: _NormalizeMode = 'backward', name: str | None = None ) → Tensor [source]

Compute the two dimensional inverse FFT of a real spectrum.

This is really ihfftn with different defaults. For more details see ihfftn.

Parameters

  • x (Tensor) – Input tensor.

  • s (sequence[int]|None, optional) – Shape (length of each transformed axis) of the output. It should be a sequence of 2 integers. This corresponds to n for ihfft(x, n). Along each 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. Default is None.

  • axes (sequence[int], optional) – Axes over which to compute the inverse FFT. It should be a sequence of 2 integers. If not specified, the last two axes are used by default.

  • norm (str, optional) – {“backward”, “ortho”, “forward”}. Default is “backward”.

  • name (str, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name .

Returns

The result of the inverse hermitian 2-D FFT.

Return type

out(Tensor)

Examples

>>> import paddle

>>> arr = paddle.arange(5, dtype="float64")
>>> x = paddle.meshgrid(arr, arr)[0]
>>> print(x)
Tensor(shape=[5, 5], dtype=float64, place=Place(cpu), stop_gradient=True,
[[0., 0., 0., 0., 0.],
 [1., 1., 1., 1., 1.],
 [2., 2., 2., 2., 2.],
 [3., 3., 3., 3., 3.],
 [4., 4., 4., 4., 4.]])

>>> ihfft2_xp = paddle.fft.ihfft2(x)
>>> print(ihfft2_xp.numpy())
[[2. +0.j 0. -0.j 0. -0.j]
 [-0.5-0.68819096j 0. +0.j 0. +0.j]
 [-0.5-0.16245985j 0. +0.j 0. +0.j]
 [-0.5+0.16245985j 0. +0.j 0. +0.j]
 [-0.5+0.68819096j 0. +0.j 0. +0.j]]