mantidimaging.gui.windows.recon.model module#

class mantidimaging.gui.windows.recon.model.ReconstructWindowModel(data_model: CorTiltPointQtModel)[source]#

Bases: object

auto_find_correlation(progress: Progress) → tuple[ScalarCoR, Degrees][source]#

auto_find_minimisation_sqsum(slices: list[int], recon_params: ReconstructionParameters, initial_cor: list[float], progress: Progress) → list[float][source]#

Parameters:

slices – Slice indices to be reconstructed
recon_params – Reconstruction parameters
initial_cor – Initial COR for the slices. Will be used as the start for the minimisation. If a float is passed it will be used for all slices. If a list is passed, the COR will be retrieved for each slice.
progress – Progress reporter

property cors: ndarray#

do_fit() → bool[source]#

find_initial_cor() → tuple[int, ScalarCoR][source]#

static get_allowed_filters(alg_name: str) → list[source]#

get_cor_for_slice_from_regression() → ScalarCoR[source]#

get_me_a_cor(cor: ScalarCoR | None = None) → ScalarCoR[source]#

get_results() → tuple[ScalarCoR, Degrees, Slope][source]#

get_slice_indices(num_cors: int) → tuple[int, ndarray | tuple[ndarray, float | None]][source]#

property has_results: bool#

property images#

initial_select_data(images: ImageStack | None) → None[source]#

is_current_stack(uuid: uuid.UUID) → bool[source]#

property last_cor: ScalarCoR#

static load_allowed_recon_kwargs() → dict[str, Any][source]#

property num_points: int#

property preview_projection_idx: int#

property preview_slice_idx: int#

static proj_180_degree_shape_matches_images(images) → bool[source]#

reset_cor_model() → None[source]#

reset_selected_row() → None[source]#

run_full_recon(recon_params: ReconstructionParameters, progress: Progress) → ImageStack | None[source]#

run_preview_recon(slice_idx: int, cor: ScalarCoR, recon_params: ReconstructionParameters, progress: Progress | None = None) → ImageStack | None[source]#

property selected_row: int#

set_precalculated(cor: ScalarCoR, tilt: Degrees) → None[source]#

property slices: ndarray#

stack_contains_nans() → bool[source]#

stack_contains_negative_values() → bool[source]#

stack_contains_zeroes() → bool[source]#

property stack_id: uuid.UUID | None#

property tilt_angle: Degrees | None#