snake.core.engine.nufft

Acquisition engine using nufft.

Module Contents

Classes

NufftAcquisitionEngine

Acquisition engine using nufft.

API

class snake.core.engine.nufft.NufftAcquisitionEngine

Bases: snake.core.engine.base.BaseAcquisitionEngine

Acquisition engine using nufft.

__engine_name__ = 'NUFFT'

__mp_mode__ = 'spawn'

model: str = 'simple'

snr: float = None

slice_2d: bool = False

_job_trajectories(dataset: ismrmrd.Dataset, hdr: ismrmrd.xsd.ismrmrdHeader, sim_conf: snake.core.simulation.SimConfig, shot_idx: collections.abc.Sequence[int] | int) → numpy.typing.NDArray

Get Non Cartesian trajectories from the dataset.

Returns:

The trajectories.

Return type:

NDArray

static _init_model_nufft(samples: numpy.typing.NDArray, sim_conf: snake.core.simulation.SimConfig, backend: str, slice_2d: bool = False) → mrinufft.operators.FourierOperatorBase

Initialize the nufft operator.

static _job_model_T2s(phantom: snake.core.phantom.Phantom, dyn_datas: list[snake.core.phantom.DynamicData], sim_conf: snake.core.simulation.SimConfig, trajectories: numpy.typing.NDArray, nufft_backend: str, slice_2d: bool = False) → numpy.ndarray

Acquire k-space data with T2s relaxation effect.

static _job_model_simple(phantom: snake.core.phantom.Phantom, dyn_datas: list[snake.core.phantom.DynamicData], sim_conf: snake.core.simulation.SimConfig, trajectories: numpy.typing.NDArray, nufft_backend: str, slice_2d: bool = False) → numpy.ndarray

Acquire k-space data. No T2s decay.

_write_chunk_data(dataset: ismrmrd.Dataset, chunk: collections.abc.Sequence[int], chunk_data: numpy.typing.NDArray) → None