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Editing: _arraytools.cpython-311.pyc
� d�cA � �B � d Z ddlZd d�Zd d�Zd d�Zd d�Zd d�Zd d �ZdS ) z- Functions for acting on a axis of an array. � N���c � � t d� � g| j z }t |||� � ||< | t |� � }|S )a� Take a slice along axis 'axis' from 'a'. Parameters ---------- a : numpy.ndarray The array to be sliced. start, stop, step : int or None The slice parameters. axis : int, optional The axis of `a` to be sliced. Examples -------- >>> a = array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) >>> axis_slice(a, start=0, stop=1, axis=1) array([[1], [4], [7]]) >>> axis_slice(a, start=1, axis=0) array([[4, 5, 6], [7, 8, 9]]) Notes ----- The keyword arguments start, stop and step are used by calling slice(start, stop, step). This implies axis_slice() does not handle its arguments the exactly the same as indexing. To select a single index k, for example, use axis_slice(a, start=k, stop=k+1) In this case, the length of the axis 'axis' in the result will be 1; the trivial dimension is not removed. (Use numpy.squeeze() to remove trivial axes.) N)�slice�ndim�tuple)�a�start�stop�step�axis�a_slice�bs �:/usr/lib/python3/dist-packages/scipy/signal/_arraytools.py� axis_slicer sC � �D �T�{�{�m�a�f�$�G��%��t�,�,�G�D�M� �%��.�.��A� �H� c �& � t | d|�� � S )zeReverse the 1-D slices of `a` along axis `axis`. Returns axis_slice(a, step=-1, axis=axis). r )r r )r )r r s r � axis_reverser / s � � �a�b�t� ,� ,� ,�,r c �n � |dk r| S || j | dz k r"t d|| j | dz fz � � �t | dd|�� � }t | |dd|�� � }t | d|�� � }t | d|d z d|�� � }t j d |z |z | d |z |z f|� � � }|S ) a+ Odd extension at the boundaries of an array Generate a new ndarray by making an odd extension of `x` along an axis. Parameters ---------- x : ndarray The array to be extended. n : int The number of elements by which to extend `x` at each end of the axis. axis : int, optional The axis along which to extend `x`. Default is -1. Examples -------- >>> from scipy.signal._arraytools import odd_ext >>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]]) >>> odd_ext(a, 2) array([[-1, 0, 1, 2, 3, 4, 5, 6, 7], [-4, -1, 0, 1, 4, 9, 16, 23, 28]]) Odd extension is a "180 degree rotation" at the endpoints of the original array: >>> t = np.linspace(0, 1.5, 100) >>> a = 0.9 * np.sin(2 * np.pi * t**2) >>> b = odd_ext(a, 40) >>> import matplotlib.pyplot as plt >>> plt.plot(arange(-40, 140), b, 'b', lw=1, label='odd extension') >>> plt.plot(arange(100), a, 'r', lw=2, label='original') >>> plt.legend(loc='best') >>> plt.show() � �XThe extension length n (%d) is too big. It must not exceed x.shape[axis]-1, which is %d.r �r r r r �r r r r �r r ���� �r ��shape� ValueErrorr �np� concatenate)�x�nr �left_end�left_ext� right_end� right_ext�exts r �odd_extr) 7 s� � �F �1�u�u����1�7�4�=�1� � � �� L� �q�w�t�}�q� 0�1�2� 3� 3� 3� �!�1�1�4�8�8�8�H��!�1�1�2�D�A�A�A�H��1�B�T�2�2�2�I��1�B�q�1�u�X�B�T�J�J�J�I� �.�!�h�,��1���i�-�)�3�5� #� $� $� $�C� �Jr c � � |dk r| S || j | dz k r"t d|| j | dz fz � � �t | |dd|�� � }t | d|dz d|�� � }t j || |f|�� � }|S ) a( Even extension at the boundaries of an array Generate a new ndarray by making an even extension of `x` along an axis. Parameters ---------- x : ndarray The array to be extended. n : int The number of elements by which to extend `x` at each end of the axis. axis : int, optional The axis along which to extend `x`. Default is -1. Examples -------- >>> from scipy.signal._arraytools import even_ext >>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]]) >>> even_ext(a, 2) array([[ 3, 2, 1, 2, 3, 4, 5, 4, 3], [ 4, 1, 0, 1, 4, 9, 16, 9, 4]]) Even extension is a "mirror image" at the boundaries of the original array: >>> t = np.linspace(0, 1.5, 100) >>> a = 0.9 * np.sin(2 * np.pi * t**2) >>> b = even_ext(a, 40) >>> import matplotlib.pyplot as plt >>> plt.plot(arange(-40, 140), b, 'b', lw=1, label='even extension') >>> plt.plot(arange(100), a, 'r', lw=2, label='original') >>> plt.legend(loc='best') >>> plt.show() r r r r r r r r r )r" r# r r% r' r( s r �even_extr+ k s� � �D �1�u�u����1�7�4�=�1� � � �� L� �q�w�t�}�q� 0�1�2� 3� 3� 3� �!�1�1�2�D�A�A�A�H��1�B�q�1�u�X�B�T�J�J�J�I� �.�(��#�%� #� $� $� $�C� �Jr c � � |dk r| S t | dd|�� � }dg| j z }|||< t j || j �� � }||z }t | d|�� � }||z }t j || |f|�� � } | S )a� Constant extension at the boundaries of an array Generate a new ndarray that is a constant extension of `x` along an axis. The extension repeats the values at the first and last element of the axis. Parameters ---------- x : ndarray The array to be extended. n : int The number of elements by which to extend `x` at each end of the axis. axis : int, optional The axis along which to extend `x`. Default is -1. Examples -------- >>> from scipy.signal._arraytools import const_ext >>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]]) >>> const_ext(a, 2) array([[ 1, 1, 1, 2, 3, 4, 5, 5, 5], [ 0, 0, 0, 1, 4, 9, 16, 16, 16]]) Constant extension continues with the same values as the endpoints of the array: >>> t = np.linspace(0, 1.5, 100) >>> a = 0.9 * np.sin(2 * np.pi * t**2) >>> b = const_ext(a, 40) >>> import matplotlib.pyplot as plt >>> plt.plot(arange(-40, 140), b, 'b', lw=1, label='constant extension') >>> plt.plot(arange(100), a, 'r', lw=2, label='original') >>> plt.legend(loc='best') >>> plt.show() r r r ��dtyper r r )r r r �onesr. r! ) r" r# r r$ � ones_shaper/ r% r& r' r( s r � const_extr1 � s� � �L �1�u�u����!�1�1�4�8�8�8�H���q�v� �J��J�t�� �7�:�Q�W� -� -� -�D��h��H��1�B�T�2�2�2�I��y� �I� �.�(��#�%� #� $� $� $�C� �Jr c � � |dk r| S t | j � � }|||< t j || j �� � }t j || |f|�� � }|S )a� Zero padding at the boundaries of an array Generate a new ndarray that is a zero-padded extension of `x` along an axis. Parameters ---------- x : ndarray The array to be extended. n : int The number of elements by which to extend `x` at each end of the axis. axis : int, optional The axis along which to extend `x`. Default is -1. Examples -------- >>> from scipy.signal._arraytools import zero_ext >>> a = np.array([[1, 2, 3, 4, 5], [0, 1, 4, 9, 16]]) >>> zero_ext(a, 2) array([[ 0, 0, 1, 2, 3, 4, 5, 0, 0], [ 0, 0, 0, 1, 4, 9, 16, 0, 0]]) r r- r )�listr r �zerosr. r! )r" r# r � zeros_shaper4 r( s r �zero_extr6 � s_ � �2 �1�u�u����q�w�-�-�K��K��� �H�[��� 0� 0� 0�E� �.�%��E�*�� 6� 6� 6�C� �Jr )NNNr )r ) �__doc__�numpyr r r r) r+ r1 r6 � r r �<module>r: s� ��� � � � � �% � % � % � % �P-� -� -� -�1� 1� 1� 1�h.� .� .� .�b3� 3� 3� 3�l � � � � � r
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