mantidimaging.core.rotation.data_model module#

class mantidimaging.core.rotation.data_model.CorTiltDataModel[source]#

Bases: object

Model for finding COR/Tilt from (slice index, centre of rotation) data points

add_point(idx=None, slice_idx=0, cor=0.0)[source]#

property angle_in_degrees: Degrees#

clear_points()[source]#

clear_results()[source]#

property cor: ScalarCoR#

property cors#

property empty: bool#

get_all_cors_from_regression(image_height) → list[ScalarCoR][source]#

Parameters:: image_height – How many cors will be generated, this should be equal to the image height (i.e. number of sinograms that will be reconstructed)
Returns:: List of cors for every slice of the image height

get_cor_from_regression(slice_idx) → float[source]#

property gradient: Slope#

property has_results: bool#

iter_points() → Iterator[Point][source]#

linear_regression()[source]#

property num_points: int#

point(idx)[source]#

populate_slice_indices(begin, end, count, cor=0.0)[source]#

remove_point(idx)[source]#

set_cor_at_slice(slice_idx: int, cor: float)[source]#

set_point(idx, slice_idx: int | None = None, cor: float | None = None, reset_results=True)[source]#

set_precalculated(cor: ScalarCoR, tilt: Degrees)[source]#

property slices#

sort_points()[source]#

property stack_properties: dict#

class mantidimaging.core.rotation.data_model.Point(slice_index, cor)#

Bases: NamedTuple

cor: float#: Alias for field number 1

slice_index: int#: Alias for field number 0