sigpy.linop.ConvolveData

class sigpy.linop.ConvolveData(data_shape, filt, mode='full', strides=None, multi_channel=False)

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.

__init__(data_shape, filt, mode='full', strides=None, multi_channel=False)

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.