mantidimaging.core.reconstruct.base_recon module

class mantidimaging.core.reconstruct.base_recon.BaseRecon

Bases: object

static allowed_filters() → list[str]

static find_cor(images: ImageStack, slice_idx: int, start_cor: float, recon_params: ReconstructionParameters) → float

static full(images: ImageStack, cors: list[ScalarCoR], recon_params: ReconstructionParameters, progress: Progress | None = None) → ImageStack

Performs a volume reconstruction using sample data provided as sinograms.

Parameters:

• images – Array of sinogram images

• cors – Array of centre of rotation values

• proj_angles – Array of projection angles

• recon_params – Reconstruction Parameters

• progress – Optional progress reporter

Returns:

3D image data for reconstructed volume

static negative_log(data: ndarray) → ndarray

static prepare_sinogram(data: np.ndarray, recon_params: ReconstructionParameters)

static single_sino(sino: np.ndarray, cor: ScalarCoR, proj_angles: ProjectionAngles, recon_params: ReconstructionParameters, progress: Progress | None = None) → np.ndarray

Reconstruct a single sinogram

Parameters:

• sino – The 2D sinogram as a numpy array

• cor – Center of rotation for parallel geometry. It will be converted to vector geometry before reconstructing

• proj_angles – Projection angles

• recon_params – Reconstruction parameters to configure which algorithm/filter/etc is used

Returns:

2D image data for reconstructed slice