mantidimaging.core.utility.data_containers module

Containers for data. They don’t do much apart from storing the data, and optionally provide helpful operations.

The biggest benefit is explicitly marking what the value represents (e.g. Degrees), and helps the type hints to tell you that you might be passing the wrong value (e.g. ScalarCoR to a VectorCoR), while they’re both Float underneath and the value can be used, it just will produce nonsense.

class mantidimaging.core.utility.data_containers.Counts(value: 'numpy.ndarray')

Bases: SingleValue

value: numpy.ndarray

class mantidimaging.core.utility.data_containers.Degrees(value: 'float')

Bases: SingleValue

value: float

class mantidimaging.core.utility.data_containers.FILE_TYPES(value)

Bases: Enum

An enumeration.

DARK_AFTER = ('Dark', 'After', 'images')

DARK_BEFORE = ('Dark', 'Before', 'images')

FLAT_AFTER = ('Flat', 'After', 'images')

FLAT_AFTER_LOG = ('Flat After Log', '', 'log')

FLAT_BEFORE = ('Flat', 'Before', 'images')

FLAT_BEFORE_LOG = ('Flat Before Log', '', 'log')

PROJ_180 = ('180 degree', '', '180')

SAMPLE = ('Sample', '', 'sample')

SAMPLE_LOG = ('Sample Log', '', 'log')

property fname: str

class mantidimaging.core.utility.data_containers.Indices(start, end, step)

Bases: tuple

end: int

Alias for field number 1

start: int

Alias for field number 0

step: int

Alias for field number 2

class mantidimaging.core.utility.data_containers.Micron(value: 'int')

Bases: SingleValue

value: int

class mantidimaging.core.utility.data_containers.ProjectionAngles(value: 'numpy.ndarray')

Bases: SingleValue

value: numpy.ndarray

class mantidimaging.core.utility.data_containers.ReconstructionParameters(algorithm: 'str', filter_name: 'str', num_iter: 'int' = 1, cor: 'ScalarCoR | None' = None, tilt: 'Degrees | None' = None, pixel_size: 'float' = 0.0, alpha: 'float' = 0.0, non_negative: 'bool' = False, max_projection_angle: 'float' = 360.0, beam_hardening_coefs: 'list[float] | None' = None, stochastic: 'bool' = False, projections_per_subset: 'int' = 50, regularisation_percent: 'int' = 30)

Bases: object

algorithm: str

alpha: float = 0.0

beam_hardening_coefs: list[float] | None = None

cor: ScalarCoR | None = None

filter_name: str

max_projection_angle: float = 360.0

non_negative: bool = False

num_iter: int = 1

pixel_size: float = 0.0

projections_per_subset: int = 50

regularisation_percent: int = 30

stochastic: bool = False

tilt: Degrees | None = None

to_dict() → dict

class mantidimaging.core.utility.data_containers.ScalarCoR(value: 'float')

Bases: SingleValue

to_vec(detector_width)

value: float

class mantidimaging.core.utility.data_containers.SingleValue(value: 'Any')

Bases: object

value: Any

class mantidimaging.core.utility.data_containers.Slope(value: 'float')

Bases: SingleValue

value: float

class mantidimaging.core.utility.data_containers.VectorCoR(value: 'float')

Bases: SingleValue

to_scalar(detector_width)

value: float