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from __future__ import division, print_function, absolute_import
__all__ = ['fftshift', 'ifftshift', 'fftfreq', 'rfftfreq']
from numpy import arange
from numpy.fft.helper import fftshift, ifftshift, fftfreq
def rfftfreq(n, d=1.0):
"""DFT sample frequencies (for usage with rfft, irfft).
The returned float array contains the frequency bins in
cycles/unit (with zero at the start) given a window length `n` and a
sample spacing `d`::
f = [0,1,1,2,2,...,n/2-1,n/2-1,n/2]/(d*n) if n is even
f = [0,1,1,2,2,...,n/2-1,n/2-1,n/2,n/2]/(d*n) if n is odd
Parameters
----------
n : int
Window length.
d : scalar, optional
Sample spacing. Default is 1.
Returns
-------
out : ndarray
The array of length `n`, containing the sample frequencies.
Examples
--------
>>> from scipy import fftpack
>>> sig = np.array([-2, 8, 6, 4, 1, 0, 3, 5], dtype=float)
>>> sig_fft = fftpack.rfft(sig)
>>> n = sig_fft.size
>>> timestep = 0.1
>>> freq = fftpack.rfftfreq(n, d=timestep)
>>> freq
array([ 0. , 1.25, 1.25, 2.5 , 2.5 , 3.75, 3.75, 5. ])
"""
if not isinstance(n, int) or n < 0:
raise ValueError("n = %s is not valid. n must be a nonnegative integer." % n)
return (arange(1, n + 1, dtype=int) // 2) / float(n * d)
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