mantidimaging.core.reconstruct.base_recon module

class mantidimaging.core.reconstruct.base_recon.BaseRecon

Bases: object

static allowed_filters() → List[str]

static find_cor(images: mantidimaging.core.data.images.Images, slice_idx: int, start_cor: float, recon_params: mantidimaging.core.utility.data_containers.ReconstructionParameters) → float

static full(images: mantidimaging.core.data.images.Images, cors: List[mantidimaging.core.utility.data_containers.ScalarCoR], recon_params: mantidimaging.core.utility.data_containers.ReconstructionParameters, progress: Optional[mantidimaging.core.utility.progress_reporting.progress.Progress] = None) → mantidimaging.core.data.images.Images

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: numpy.ndarray) → numpy.ndarray

static prepare_sinogram(data: numpy.ndarray, recon_params: mantidimaging.core.utility.data_containers.ReconstructionParameters)

static single_sino(sino: numpy.ndarray, cor: mantidimaging.core.utility.data_containers.ScalarCoR, proj_angles: mantidimaging.core.utility.data_containers.ProjectionAngles, recon_params: mantidimaging.core.utility.data_containers.ReconstructionParameters, progress: Optional[mantidimaging.core.utility.progress_reporting.progress.Progress] = None) → numpy.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