/usr/local/lib64/python3.6/site-packages/numpy/fft/__pycache__
Edit: /usr/local/lib64/python3.6/site-packages/numpy/fft/__pycache__/helper.cpython-36.pyc (6756B)
3
Eg= @ s d Z ddlmZ ddlmZmZmZmZmZ ddl m
Z
m Z ddddgZ eef Zdd
d Z
e
e
d d
dddZe
e
d d
dddZe d dddZe d dddZd S )z*
Discrete Fourier Transforms - helper.py
)
integer_types)integeremptyarangeasarrayroll)array_function_dispatch
set_modulefftshift ifftshiftfftfreqrfftfreqNc C s | fS )N )xaxesr r >> freqs = np.fft.fftfreq(10, 0.1)
>>> freqs
array([ 0., 1., 2., ..., -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.]])
Nc S s g | ] }|d qS ) r ).0dimr r r
D s z fftshift..r c s g | ]} j | d qS )r )shape)r ax)r r r r H s )r tuplerangendimr
isinstancer r )r r shiftr )r r r
s -
c sj t |dkr0tt j}dd jD }n.t|trL j| d }n fdd|D }t ||S )a/
The inverse of `fftshift`. Although identical for even-length `x`, the
functions differ by one sample for odd-length `x`.
Parameters
----------
x : array_like
Input array.
axes : int or shape tuple, optional
Axes over which to calculate. Defaults to None, which shifts all axes.
Returns
-------
y : ndarray
The shifted array.
See Also
--------
fftshift : Shift zero-frequency component to the center of the spectrum.
Examples
--------
>>> freqs = np.fft.fftfreq(9, d=1./9).reshape(3, 3)
>>> freqs
array([[ 0., 1., 2.],
[ 3., 4., -4.],
[-3., -2., -1.]])
>>> np.fft.ifftshift(np.fft.fftshift(freqs))
array([[ 0., 1., 2.],
[ 3., 4., -4.],
[-3., -2., -1.]])
Nc S s g | ]}|d qS )r r )r r r r r r s s z ifftshift..r c s g | ]} j | d qS )r )r )r r )r r r r w s )r r r r r r r r )r r r r )r r r M s #
?c C sz t | tstdd| | }t| t}| d d d }td|td}||d|< t| d dtd}|||d< || S )a-
Return the Discrete Fourier Transform sample frequencies.
The returned float array `f` contains the frequency bin centers in cycles
per unit of the sample spacing (with zero at the start). For instance, if
the sample spacing is in seconds, then the frequency unit is cycles/second.
Given a window length `n` and a sample spacing `d`::
f = [0, 1, ..., n/2-1, -n/2, ..., -1] / (d*n) if n is even
f = [0, 1, ..., (n-1)/2, -(n-1)/2, ..., -1] / (d*n) if n is odd
Parameters
----------
n : int
Window length.
d : scalar, optional
Sample spacing (inverse of the sampling rate). Defaults to 1.
Returns
-------
f : ndarray
Array of length `n` containing the sample frequencies.
Examples
--------
>>> signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5], dtype=float)
>>> fourier = np.fft.fft(signal)
>>> n = signal.size
>>> timestep = 0.1
>>> freq = np.fft.fftfreq(n, d=timestep)
>>> freq
array([ 0. , 1.25, 2.5 , ..., -3.75, -2.5 , -1.25])
zn should be an integerg ? r r )dtypeN)r r
ValueErrorr intr )ndvalresultsNp1p2r r r r | s %
c C s@ t | tstdd| | }| d d }td|td}|| S )a?
Return the Discrete Fourier Transform sample frequencies
(for usage with rfft, irfft).
The returned float array `f` contains the frequency bin centers in cycles
per unit of the sample spacing (with zero at the start). For instance, if
the sample spacing is in seconds, then the frequency unit is cycles/second.
Given a window length `n` and a sample spacing `d`::
f = [0, 1, ..., n/2-1, n/2] / (d*n) if n is even
f = [0, 1, ..., (n-1)/2-1, (n-1)/2] / (d*n) if n is odd
Unlike `fftfreq` (but like `scipy.fftpack.rfftfreq`)
the Nyquist frequency component is considered to be positive.
Parameters
----------
n : int
Window length.
d : scalar, optional
Sample spacing (inverse of the sampling rate). Defaults to 1.
Returns
-------
f : ndarray
Array of length ``n//2 + 1`` containing the sample frequencies.
Examples
--------
>>> signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5, -3, 4], dtype=float)
>>> fourier = np.fft.rfft(signal)
>>> n = signal.size
>>> sample_rate = 100
>>> freq = np.fft.fftfreq(n, d=1./sample_rate)
>>> freq
array([ 0., 10., 20., ..., -30., -20., -10.])
>>> freq = np.fft.rfftfreq(n, d=1./sample_rate)
>>> freq
array([ 0., 10., 20., 30., 40., 50.])
zn should be an integerg ?r r r )r! )r r r" r r# )r$ r% r& r( r' r r r r
s ,
)N)N)N)r )r )__doc__Z numpy.compatr Z
numpy.corer r r r r Znumpy.core.overridesr r __all__r r
r r r
r r r r s
8
. 0