snake.core.phantom.static

`snake.core.phantom.static`#

Module to create phantom for simulation.

Module Contents#

Classes#

`PropTissueEnum`	Enum for the tissue properties.
`TissueFile`	Enum for the tissue properties file.
`Phantom`	A Phantom consist of a list of tissue mask and parameters for those tissues.

Functions#

`serialize_array`	Serialize the array for mrd compatible format.
`unserialize_array`	Unserialize the array for mrd compatible format.

Data#

`log`
`T`

API#

snake.core.phantom.static.log = 'getLogger(...)'[source]#

class snake.core.phantom.static.PropTissueEnum[source]#

Bases: enum.IntEnum

Enum for the tissue properties.

Initialization

Initialize self. See help(type(self)) for accurate signature.

T1 = 0#

T2 = 1#

T2s = 2#

rho = 3#

chi = 4#

class snake.core.phantom.static.TissueFile[source]#

Bases: str, snake._meta.NoCaseEnum

Enum for the tissue properties file.

Initialization

Initialize self. See help(type(self)) for accurate signature.

tissue_1T5 = 'str(...)'#

tissue_7T = 'str(...)'#

class snake.core.phantom.static.Phantom[source]#

A Phantom consist of a list of tissue mask and parameters for those tissues.

name: str = None#

masks: numpy.typing.NDArray[numpy.float32] = None#

labels: numpy.typing.NDArray[numpy.string_] = None#

props: numpy.typing.NDArray[numpy.float32] = None#

smaps: numpy.typing.NDArray[numpy.complex64] | None = None#

add_tissue(tissue_name: str, mask: numpy.typing.NDArray[numpy.float32], props: numpy.typing.NDArray[numpy.float32], phantom_name: str | None = None) → snake.core.phantom.static.Phantom[source]#: Add a tissue to the phantom. Creates a new Phantom object.

property labels_idx: dict[str, int]#: Get the index of the labels.

make_smaps(n_coils: int = None, sim_conf: snake.core.simulation.SimConfig = None, antenna: str = 'birdcage') → None[source]#: Get coil sensitivity maps for the phantom.

classmethod from_brainweb(sub_id: int, sim_conf: snake.core.simulation.SimConfig, tissue_file: str | snake.core.phantom.static.TissueFile = TissueFile.tissue_1T5, tissue_select: list[str] | None = None, tissue_ignore: list[str] | None = None) → snake.core.phantom.static.Phantom[source]#: Get the Brainweb Phantom.

abstract classmethod from_shepp_logan(resolution: tuple[int]) → snake.core.phantom.static.Phantom[source]#: Get the Shepp-Logan Phantom.

abstract classmethod from_guerin_kern(resolution: tuple[int]) → snake.core.phantom.static.Phantom[source]#: Get the Guerin-Kern Phantom.

classmethod from_mrd_dataset(dataset: ismrmrd.Dataset | os.PathLike, imnum: int = 0) → snake.core.phantom.static.Phantom[source]#: Load the phantom from a mrd dataset.

to_mrd_dataset(dataset: ismrmrd.Dataset, sim_conf: snake.core.simulation.SimConfig, imnum: int = 0) → ismrmrd.Dataset[source]#: Add the phantom as an image to the dataset.

classmethod from_shared_memory(name: str, mask_prop: snake.core.parallel.ArrayProps, properties_prop: snake.core.parallel.ArrayProps, label_prop: snake.core.parallel.ArrayProps, smaps_prop: snake.core.parallel.ArrayProps) → collections.abc.Generator[snake.core.phantom.static.Phantom, None, None][source]#: Give access the tissue masks and properties in shared memory.

in_shared_memory(manager: multiprocessing.managers.SharedMemoryManager) → tuple[tuple[str, snake.core.parallel.ArrayProps, snake.core.parallel.ArrayProps, snake.core.parallel.ArrayProps, snake.core.parallel.ArrayProps | None], tuple[multiprocessing.shared_memory.SharedMemory, multiprocessing.shared_memory.SharedMemory, multiprocessing.shared_memory.SharedMemory, multiprocessing.shared_memory.SharedMemory | None]][source]#: Add a copy of the phantom in shared memory.

property anat_shape: tuple[int, ...]#: Get the shape of the base volume.

property n_tissues: int#: Get the number of tissues.

__repr__()[source]#

__deepcopy__(memo: Any) → snake.core.phantom.static.Phantom[source]#: Create a copy of the phantom.

copy() → snake.core.phantom.static.Phantom[source]#: Return deep copy of the Phantom.

snake.core.phantom.static.T = 'TypeVar(...)'#

snake.core.phantom.static.serialize_array(arr: numpy.typing.NDArray) → str[source]#: Serialize the array for mrd compatible format.

snake.core.phantom.static.unserialize_array(s: str) → numpy.typing.NDArray[source]#: Unserialize the array for mrd compatible format.