from numpy.core import asarray, concatenate,swapaxes
import numpy.core.numerictypes as nt


def fftshift(x,axes=None):
    """
Shift the zero-frequency component to the center of the spectrum.

This function swaps half-spaces for all axes listed (defaults to all).
Note that ``y[0]`` is the Nyquist component only if ``len(x)`` is even.

Parameters
----------
x : array_like
Input array.
axes : int or shape tuple, optional
Axes over which to shift. Default is None, which shifts all axes.

Returns
-------
y : ndarray
The shifted array.

See Also
--------
ifftshift : The inverse of `fftshift`.

Examples
--------
>>> freqs = np.fft.fftfreq(10, 0.1)
>>> freqs
array([ 0., 1., 2., 3., 4., -5., -4., -3., -2., -1.])
>>> np.fft.fftshift(freqs)
array([-5., -4., -3., -2., -1., 0., 1., 2., 3., 4.])

Shift the zero-frequency component only along the second axis:

>>> freqs = np.fft.fftfreq(9, d=1./9).reshape(3, 3)
>>> freqs
array([[ 0., 1., 2.],
[ 3., 4., -4.],
[-3., -2., -1.]])
>>> np.fft.fftshift(freqs, axes=(1,))
array([[ 2., 0., 1.],
[-4., 3., 4.],
[-1., -3., -2.]])

"""
    tmp = asarray(x)
    if axes is None:
	axes = range(tmp.ndim)
    elif isinstance(axes, (int, nt.integer)):
	axes = (axes,)
    y = tmp
    for k in axes:
	n = tmp.shape[k]
	p2 = (n+1)//2
	y = swapaxes(y,0,k)
	
	y = concatenate((y[p2:,...], y[:p2,...]))
	y = swapaxes(y,0,k)
	
    return y