jax.numpy.fft.ifft2#

jax.numpy.fft.ifft2(a,s=None,axes=(-2,-1),norm=None)[source]#

Compute a two-dimensional inverse discrete Fourier transform.

JAX implementation ofnumpy.fft.ifft2().

Parameters:

• a (ArrayLike) – input array. Must havea.ndim>=2.

• s (Shape |None) – optional length-2 sequence of integers. Specifies the size of the outputin each specified axis. If not specified, it will default to the size ofa along the specifiedaxes.

• axes (Sequence[int]) – optional length-2 sequence of integers, default=(-2,-1). Specifies theaxes along which the transform is computed.

• norm (str |None) – string, default=”backward”. The normalization mode. “backward”, “ortho”and “forward” are supported.

Returns:

An array containing the two-dimensional inverse discrete Fourier transformofa along givenaxes.

Return type:

Array

See also

• jax.numpy.fft.ifft(): Computes a one-dimensional inverse discreteFourier transform.

• jax.numpy.fft.ifftn(): Computes a multidimensional inverse discreteFourier transform.

• jax.numpy.fft.fft2(): Computes a two-dimensional discrete Fouriertransform.

Examples

jnp.fft.ifft2 computes the transform along the last two axes by default.

>>>x=jnp.array([[[1,3],...[2,4]],...[[5,7],...[6,8]]])>>>withjnp.printoptions(precision=2,suppress=True):...jnp.fft.ifft2(x)Array([[[ 2.5+0.j, -1. +0.j],        [-0.5+0.j,  0. +0.j]],       [[ 6.5+0.j, -1. +0.j],        [-0.5+0.j,  0. +0.j]]], dtype=complex64)

Whens=[2,3], dimension of the transform alongaxes(-2,-1) will be(2,3) and dimension along other axes will be the same as that of input.

>>>withjnp.printoptions(precision=2,suppress=True):...jnp.fft.ifft2(x,s=[2,3])Array([[[ 1.67+0.j  , -0.08+1.01j, -0.08-1.01j],        [-0.33+0.j  , -0.08-0.14j, -0.08+0.14j]],       [[ 4.33+0.j  ,  0.58+2.17j,  0.58-2.17j],        [-0.33+0.j  , -0.08-0.14j, -0.08+0.14j]]], dtype=complex64)

Whens=[2,3] andaxes=(0,1), shape of the transform alongaxes(0,1) will be(2,3) and dimension along other axes will besame as that of input.

>>>withjnp.printoptions(precision=2,suppress=True):...jnp.fft.ifft2(x,s=[2,3],axes=(0,1))Array([[[ 2.33+0.j  ,  3.67+0.j  ],        [ 0.33+1.15j,  0.67+1.73j],        [ 0.33-1.15j,  0.67-1.73j]],       [[-1.33+0.j  , -1.33+0.j  ],        [-0.33-0.58j, -0.33-0.58j],        [-0.33+0.58j, -0.33+0.58j]]], dtype=complex64)