Basic iterative reconstruction#

We start by defining a 3D projection data Numpy array of unsigned integer 16-bit data type (optional) and with axes labels given as ["detY", "angles", "detX"]. We also provide the corresponding flats and darks fields (also 3D arrays of the same axes order).

The first step is to normalise dataRaw using the normaliser function from tomobar.supp.suppTools.normaliser.

from tomobar.supp.suppTools import normaliser

data_norm = normaliser(dataRaw, flats, darks, log=True, method='mean', axis=1)

Instantiate the iterative reconstructor tomobar.methodsIR:

from tomobar.methodsIR import RecToolsIR

detectorVert, angles_number, detectorHoriz = np.shape(data_norm)

Rectools = RecToolsIR(
    DetectorsDimH=detectorHoriz,  # Horizontal detector dimension
    DetectorsDimV=detectorVert,  # Vertical detector dimension
    CenterRotOffset=0.0,  # Center of Rotation (needs to be found)
    AnglesVec=angles_rad,  # A vector of projection angles in radians
    ObjSize=detectorHoriz,  # The reconstructed object dimensions
    datafidelity="LS",  # Least-Squares data fidelity for basic methods
    device_projector="gpu", # Device to perform reconstruction on
    )

Now we have an access to all methods of this particular reconstructor.
The basic iterative algorithms are wrapped directly from ASTRA-Toolbox, with an exception of CuPy-enabled ones. Let us use SIRT and CGLS reconstruction algorithms.

Please note that the dictionaries needed for all iterative methods with exact keyword arguments defined in tomobar.supp.dicts.

_data_ = {"projection_norm_data": data_norm,
          "data_axes_labels_order": ["detY", "angles", "detX"],
}  # data dictionary

_algorithm_ = {"iterations": 300, "nonnegativity": True} # algorithm dict

SIRT_Rec = Rectools.SIRT(_data_, _algorithm_)
CGLS_Rec = Rectools.CGLS(_data_, _algorithm_)

One can also operate purely on CuPy arrays if Dependencies are satisfied for the CuPy package. For that one needs to use tomobar.methodsIR_CuPy class instead of tomobar.methodsIR. Note that the array of angles for the CuPy modules should be provided as a Numpy array.