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