Python Sparse data Analysis Package external MRI plugin.
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class
mri.operators.proximity.ordered_weighted_l1_norm.OWL(alpha, beta, bands_shape, n_coils, mode='band_based', n_jobs=1)[source]¶ This class handles reshaping coefficients based on mode and feeding in right format the OWL operation to OrderedWeightedL1Norm
- Parameters
alpha: float
value of alpha for parameterizing weights
beta: float
value of beta for parameterizing weights
band_shape: list of tuples
the shape of all bands, this corresponds to linear_op.coeffs_shape
n_coils: int
number of channels
mode: string ‘all’ | ‘band_based’ | ‘coeff_based’, default ‘band_based’
Mode of operation of proximity: all -> on all coefficients in all channels band_based -> on all coefficients in each band coeff_based -> on all coefficients but across each channel
n_jobs: int, default 1
number of cores to be used for operation
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Samuel Farrens
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Inspired by AZMIND template.
Inspired by AZMIND template.