jax.numpy.fft.irfft#

jax.numpy.fft.irfft(a,n=None,axis=-1,norm=None)[source]#

Compute a real-valued one-dimensional inverse discrete Fourier transform.

JAX implementation ofnumpy.fft.irfft().

Parameters:

• a (ArrayLike) – input array.

• n (int |None) – int. Specifies the dimension of the result alongaxis. If not specified,n=2*(m-1), wherem is the dimension ofa alongaxis.

• axis (int) – int, default=-1. Specifies the axis along which the transform is computed.If not specified, the transform is computed along axis -1.

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

Returns:

A real-valued array containing the one-dimensional inverse discrete Fouriertransform ofa, with a dimension ofn alongaxis.

Return type:

Array

See also

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

• jax.numpy.fft.irfft(): Computes a one-dimensional inverse discreteFourier transform for real input.

• jax.numpy.fft.rfftn(): Computes a multidimensional discrete Fouriertransform for real input.

• jax.numpy.fft.irfftn(): Computes a multidimensional inverse discreteFourier transform for real input.

Examples

jnp.fft.rfft computes the transform alongaxis-1 by default.

>>>x=jnp.array([[1,3,5],...[2,4,6]])>>>jnp.fft.irfft(x)Array([[ 3., -1.,  0., -1.],       [ 4., -1.,  0., -1.]], dtype=float32)

Whenn=3, dimension of the transform along axis -1 will be3 anddimension along other axes will be the same as that of input.

>>>withjnp.printoptions(precision=2,suppress=True):...jnp.fft.irfft(x,n=3)Array([[ 2.33, -0.67, -0.67],       [ 3.33, -0.67, -0.67]], dtype=float32)

Whenn=4 andaxis=0, dimension of the transform alongaxis0 willbe4 and dimension along other axes will be same as that of input.

>>>withjnp.printoptions(precision=2,suppress=True):...jnp.fft.irfft(x,n=4,axis=0)Array([[ 1.25,  2.75,  4.25],       [ 0.25,  0.75,  1.25],       [-0.75, -1.25, -1.75],       [ 0.25,  0.75,  1.25]], dtype=float32)