jax.numpy.fft.rfft#

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

Compute the one-dimensional discrete Fourier Transform for real input.

LAX-backend implementation of numpy.fft.rfft().

Original docstring below.

This function computes the one-dimensional n-point discrete Fourier Transform (DFT) of a real-valued array by means of an efficient algorithm called the Fast Fourier Transform (FFT).

Parameters:

  • a (array_like) – Input array

  • n (int, optional) – Number of points along transformation axis in the input to use. If n is smaller than the length of the input, the input is cropped. If it is larger, the input is padded with zeros. If n is not given, the length of the input along the axis specified by axis is used.

  • axis (int, optional) – Axis over which to compute the FFT. If not given, the last axis is used.

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

Returns:

out – The truncated or zero-padded input, transformed along the axis indicated by axis, or the last one if axis is not specified. If n is even, the length of the transformed axis is (n/2)+1. If n is odd, the length is (n+1)/2.

Return type:

complex ndarray