jax.numpy.fft.irfftn#

jax.numpy.fft.irfftn(a,s=None,axes=None,norm=None)[source]#

Compute a real-valued multidimensional inverse discrete Fourier transform.

JAX implementation ofnumpy.fft.irfftn().

Parameters:

• a (ArrayLike) – input array.

• s (Shape |None) – optional sequence of integers. Specifies the size of the output in eachspecified axis. If not specified, the dimension of output along axisaxes[-1] is2*(m-1),m is the size of input along axisaxes[-1]and the dimension along other axes will be the same as that of input.

• axes (Sequence[int]|None) – optional sequence of integers, default=None. Specifies the axes alongwhich the transform is computed. If not specified, the transform is computedalong the lastlen(s) axes. If neitheraxes nors is specified,the transform is computed along all the axes.

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

Returns:

A real-valued array containing the multidimensional inverse discrete Fouriertransform ofa with sizes along specifiedaxes, and the same asthe input along other axes.

Return type:

Array

See also

• jax.numpy.fft.rfftn(): Computes a multidimensional discrete Fouriertransform of a real-valued array.

• jax.numpy.fft.irfft(): Computes a real-valued one-dimensional inversediscrete Fourier transform.

• jax.numpy.fft.irfft2(): Computes a real-valued two-dimensional inversediscrete Fourier transform.

Examples

jnp.fft.irfftn computes the transform along all the axes by default.

>>>x=jnp.array([[[1,3,5],...[2,4,6]],...[[7,9,11],...[8,10,12]]])>>>jnp.fft.irfftn(x)Array([[[ 6.5, -1. ,  0. , -1. ],        [-0.5,  0. ,  0. ,  0. ]],       [[-3. ,  0. ,  0. ,  0. ],        [ 0. ,  0. ,  0. ,  0. ]]], dtype=float32)

Whens=[3,4], size of the transform alongaxes(-2,-1) will be(3,4) and size along other axes will be the same as that of input.

>>>withjnp.printoptions(precision=2,suppress=True):...jnp.fft.irfftn(x,s=[3,4])Array([[[ 2.33, -0.67,  0.  , -0.67],        [ 0.33, -0.74,  0.  ,  0.41],        [ 0.33,  0.41,  0.  , -0.74]],       [[ 6.33, -0.67,  0.  , -0.67],        [ 1.33, -1.61,  0.  ,  1.28],        [ 1.33,  1.28,  0.  , -1.61]]], dtype=float32)

Whens=[3] andaxes=[0], size of the transform alongaxes0 willbe3 and dimension along other axes will be same as that of input.

>>>withjnp.printoptions(precision=2,suppress=True):...jnp.fft.irfftn(x,s=[3],axes=[0])Array([[[ 5.,  7.,  9.],        [ 6.,  8., 10.]],       [[-2., -2., -2.],        [-2., -2., -2.]],       [[-2., -2., -2.],        [-2., -2., -2.]]], dtype=float32)