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Edit: helper.cpython-311.pyc
� �|oi � � � d Z ddlmZmZmZmZmZ ddlmZm Z g d�Z eefZdd�Z ee d�� � dd �� � Z ee d�� � dd �� � Z e d� � dd�� � Z e d� � dd �� � ZdS )z* Discrete Fourier Transforms - helper.py � )�integer�empty�arange�asarray�roll)�array_function_dispatch� set_module)�fftshift� ifftshift�fftfreq�rfftfreqNc � � | fS �N� )�x�axess �G/opt/cloudlinux/venv/lib64/python3.11/site-packages/numpy/fft/helper.py�_fftshift_dispatcherr s � � �4�K� z numpy.fft)�modulec � � � t � � � � |�3t t � j � � � � }d� � j D � � }n4t |t � � r� j | dz }n� fd�|D � � }t � ||� � S )ad 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., -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 � � g | ]}|d z ��S �� r ��.0�dims r � <listcomp>zfftshift.<locals>.<listcomp>C s � �-�-�-�c����-�-�-r r c �0 �� g | ]}�j | d z ��S r ��shape�r �axr s �r r zfftshift.<locals>.<listcomp>G s$ �� �1�1�1�b������!�1�1�1r �r �tuple�range�ndimr! � isinstance� integer_typesr �r r �shifts ` r r r s� �� �Z �� � �A��|��U�1�6�]�]�#�#��-�-�Q�W�-�-�-��� �D�-� (� (� 2���� ��"���1�1�1�1�D�1�1�1����5�$���r c � � � t � � � � |�3t t � j � � � � }d� � j D � � }n5t |t � � r� j | dz }n� fd�|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 � � g | ]}|d z �� S r r r s r r zifftshift.<locals>.<listcomp>r s � �0�0�0��3�!�8��0�0�0r r c �2 �� g | ]}�j | d z ��S r r r"