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: mantidimaging.core.utility.data_containers.Degrees
clear_points()[source]
clear_results()[source]
property cor: mantidimaging.core.utility.data_containers.ScalarCoR
property cors
property empty
get_all_cors_from_regression(image_height) List[mantidimaging.core.utility.data_containers.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: mantidimaging.core.utility.data_containers.Slope
property has_results
iter_points() Iterator[mantidimaging.core.rotation.data_model.Point][source]
linear_regression()[source]
property num_points
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: Optional[int] = None, cor: Optional[float] = None, reset_results=True)[source]
set_precalculated(cor: mantidimaging.core.utility.data_containers.ScalarCoR, tilt: mantidimaging.core.utility.data_containers.Degrees)[source]
property slices
sort_points()[source]
property stack_properties
class mantidimaging.core.rotation.data_model.Point(slice_index, cor)

Bases: tuple

cor: float

Alias for field number 1

slice_index: int

Alias for field number 0