MRIStackedNUFFT#
- class mrinufft.operators.stacked.MRIStackedNUFFT(samples, shape, z_index, backend, smaps, n_coils=1, n_batchs=1, squeeze_dims=False, **kwargs)[source]#
Bases:
FourierOperatorBase
Stacked NUFFT Operator for MRI.
The dimension of stacking is always the last one.
- Parameters:
samples (array-like) – Sample locations in a 2D kspace
shape (tuple) – Shape of the image.
z_index (array-like) – Cartesian z index of masked plan.
backend (str or FourierOperatorBase) – Backend to use. If str, a NUFFT operator is initialized with str being a registered backend. If FourierOperatorBase, operator is checked for compatibility and used as is notably one should have:
n_coils = self.n_coils*len(z_index), squeeze_dims=True, smaps=None
smaps (array-like) – Sensitivity maps.
n_coils (int) – Number of coils.
n_batchs (int) – Number of batchs.
**kwargs (dict) – Additional arguments to pass to the backend.
Methods
__init__
Adjoint operator.
compute_density
Compute the density compensation weights and set it.
data_consistency
Compute the gradient data consistency.
get_lipschitz_cst
Return the Lipschitz constant of the operator.
Forward operator.
with_off_resonnance_correction
Return a new operator with Off Resonnance Correction.
Attributes
available
backend
cpx_dtype
Return complex floating precision of the operator.
density
Density compensation of the operator.
Return dtype.
interfaces
n_coils
Number of coils for the operator.
Return number of samples.
ndim
Number of dimensions in image space of the operator.
norm_factor
Normalization factor of the operator.
samples
Return the samples used by the operator.
shape
Shape of the image space of the operator.
smaps
Sensitivity maps of the operator.
uses_density
Return True if the operator uses density compensation.
uses_sense
Return True if the operator uses sensitivity maps.
- property dtype#
Return dtype.
- property n_samples#
Return number of samples.