NufftAcquisitionEngine

class snake.core.engine.nufft.NufftAcquisitionEngine(*, model='simple', snr=inf)

Bases: BaseAcquisitionEngine

Acquisition engine using nufft.

Methods

__init__

Attributes

log	Get a logger.
model
snr

Parameters:

• model (str)

• snr (float)

_job_trajectories(dataset, hdr, sim_conf, shot_idx)

Get Non Cartesian trajectories from the dataset.

Returns:

The trajectories.

Return type:

NDArray

Parameters:

• dataset (Dataset)

• hdr (ismrmrdHeader)

• sim_conf (SimConfig)

• shot_idx (Sequence[int])

static _init_model_nufft(samples, sim_conf, smaps, backend)

Initialize the nufft operator.

Parameters:

• samples (ndarray[Any, dtype[_ScalarType_co]])

• sim_conf (SimConfig)

• smaps (ndarray[Any, dtype[_ScalarType_co]])

• backend (str)

Return type:

FourierOperatorBase

static _job_model_T2s(phantom, dyn_datas, sim_conf, trajectories, smaps, nufft_backend)

Acquire k-space data with T2s relaxation effect.

Parameters:

• phantom (Phantom)

• dyn_datas (list[DynamicData])

• sim_conf (SimConfig)

• trajectories (ndarray[Any, dtype[_ScalarType_co]])

• smaps (ndarray[Any, dtype[_ScalarType_co]])

• nufft_backend (str)

Return type:

ndarray

static _job_model_simple(phantom, dyn_datas, sim_conf, trajectories, smaps, nufft_backend)

Acquire k-space data. No T2s decay.

Parameters:

• phantom (Phantom)

• dyn_datas (list[DynamicData])

• sim_conf (SimConfig)

• trajectories (ndarray[Any, dtype[_ScalarType_co]])

• smaps (ndarray[Any, dtype[_ScalarType_co]])

• nufft_backend (str)

Return type:

ndarray

property log: Logger

Get a logger.