sigpy.linop.ConvolveDataAdjoint¶
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class
sigpy.linop.
ConvolveDataAdjoint
(data_shape, filt, mode='full', strides=None, multi_channel=False)[source]¶ Adjoint convolution operator for data arrays.
Parameters: - data_shape (tuple of ints) – data array shape: \([\ldots, m_1, \ldots, m_D]\) if multi_channel is False, \([\ldots, c_i, m_1, \ldots, m_D]\) otherwise.
- filt (array) – filter array of shape: \([n_1, \ldots, n_D]\) if multi_channel is False \([c_o, c_i, n_1, \ldots, n_D]\) otherwise.
- mode (str) – {‘full’, ‘valid’}.
- strides (None or tuple of ints) – convolution strides of length D.
- multi_channel (bool) – specify if input/output has multiple channels.
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__init__
(data_shape, filt, mode='full', strides=None, multi_channel=False)[source]¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__
(data_shape, filt[, mode, strides, …])Initialize self. apply
(input)Apply linear operation on input. Attributes
H
Return adjoint linear operator. N
Return normal linear operator.