Added Python interface

1 files changed, 563 insertions, 0 deletions

diff --git a/python/astra/creators.py b/python/astra/creators.py
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+#-----------------------------------------------------------------------
+#Copyright 2013 Centrum Wiskunde & Informatica, Amsterdam
+#
+#Author: Daniel M. Pelt
+#Contact: D.M.Pelt@cwi.nl
+#Website: http://dmpelt.github.io/pyastratoolbox/
+#
+#
+#This file is part of the Python interface to the
+#All Scale Tomographic Reconstruction Antwerp Toolbox ("ASTRA Toolbox").
+#
+#The Python interface to the ASTRA Toolbox is free software: you can redistribute it and/or modify
+#it under the terms of the GNU General Public License as published by
+#the Free Software Foundation, either version 3 of the License, or
+#(at your option) any later version.
+#
+#The Python interface to the ASTRA Toolbox is distributed in the hope that it will be useful,
+#but WITHOUT ANY WARRANTY; without even the implied warranty of
+#MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+#GNU General Public License for more details.
+#
+#You should have received a copy of the GNU General Public License
+#along with the Python interface to the ASTRA Toolbox. If not, see <http://www.gnu.org/licenses/>.
+#
+#-----------------------------------------------------------------------
+
+import six
+import numpy as np
+import math
+from . import data2d
+from . import data3d
+from . import projector
+from . import algorithm
+
+def astra_dict(intype):
+    """Creates a dict to use with the ASTRA Toolbox.
+    
+    :param intype: Type of the ASTRA object.
+    :type intype: :class:`string`
+    :returns: :class:`dict` -- An ASTRA dict of type ``intype``.
+    
+    """
+    if intype == 'SIRT_CUDA2':
+        intype = 'SIRT_CUDA'
+        six.print_('SIRT_CUDA2 has been deprecated. Use SIRT_CUDA instead.')
+    elif intype == 'FP_CUDA2':
+        intype = 'FP_CUDA'
+        six.print_('FP_CUDA2 has been deprecated. Use FP_CUDA instead.')
+    return {'type': intype}
+
+def create_vol_geom(*varargin):
+    """Create a volume geometry structure.
+
+This method can be called in a number of ways:
+
+``create_vol_geom(N)``:
+    :returns: A 2D volume geometry of size :math:`N \\times N`.
+
+``create_vol_geom((M, N))``:
+    :returns: A 2D volume geometry of size :math:`M \\times N`.
+
+``create_vol_geom(M, N)``:
+    :returns: A 2D volume geometry of size :math:`M \\times N`.
+
+``create_vol_geom(M, N, minx, maxx, miny, maxy)``:
+    :returns: A 2D volume geometry of size :math:`M \\times N`, windowed as :math:`minx \\leq x \\leq maxx` and :math:`miny \\leq y \\leq maxy`.
+
+``create_vol_geom((M, N, Z))``:
+    :returns: A 3D volume geometry of size :math:`M \\times N \\times Z`.
+
+``create_vol_geom(M, N, Z)``:
+    :returns: A 3D volume geometry of size :math:`M \\times N \\times Z`.
+
+"""
+    vol_geom = {'option': {}}
+    # astra_create_vol_geom(row_count)
+    if len(varargin) == 1 and isinstance(varargin[0], int) == 1:
+        vol_geom['GridRowCount'] = varargin[0]
+        vol_geom['GridColCount'] = varargin[0]
+        vol_geom['option']['WindowMinX'] = -varargin[0] / 2.
+        vol_geom['option']['WindowMaxX'] = varargin[0] / 2.
+        vol_geom['option']['WindowMinY'] = -varargin[0] / 2.
+        vol_geom['option']['WindowMaxY'] = varargin[0] / 2.
+    # astra_create_vol_geom([row_count col_count])
+    elif len(varargin) == 1 and len(varargin[0]) == 2:
+        vol_geom['GridRowCount'] = varargin[0][0]
+        vol_geom['GridColCount'] = varargin[0][1]
+        vol_geom['option']['WindowMinX'] = -varargin[0][1] / 2.
+        vol_geom['option']['WindowMaxX'] = varargin[0][1] / 2.
+        vol_geom['option']['WindowMinY'] = -varargin[0][0] / 2.
+        vol_geom['option']['WindowMaxY'] = varargin[0][0] / 2.
+    # astra_create_vol_geom([row_count col_count slice_count])
+    elif len(varargin) == 1 and len(varargin[0]) == 3:
+        vol_geom['GridRowCount'] = varargin[0][0]
+        vol_geom['GridColCount'] = varargin[0][1]
+        vol_geom['GridSliceCount'] = varargin[0][2]
+        vol_geom['option']['WindowMinX'] = -varargin[0][1] / 2.
+        vol_geom['option']['WindowMaxX'] = varargin[0][1] / 2.
+        vol_geom['option']['WindowMinY'] = -varargin[0][0] / 2.
+        vol_geom['option']['WindowMaxY'] = varargin[0][0] / 2.
+        vol_geom['option']['WindowMinZ'] = -varargin[0][2] / 2.
+        vol_geom['option']['WindowMaxZ'] = varargin[0][2] / 2.
+    # astra_create_vol_geom(row_count, col_count)
+    elif len(varargin) == 2:
+        vol_geom['GridRowCount'] = varargin[0]
+        vol_geom['GridColCount'] = varargin[1]
+        vol_geom['option']['WindowMinX'] = -varargin[1] / 2.
+        vol_geom['option']['WindowMaxX'] = varargin[1] / 2.
+        vol_geom['option']['WindowMinY'] = -varargin[0] / 2.
+        vol_geom['option']['WindowMaxY'] = varargin[0] / 2.
+    # astra_create_vol_geom(row_count, col_count, min_x, max_x, min_y, max_y)
+    elif len(varargin) == 6:
+        vol_geom['GridRowCount'] = varargin[0]
+        vol_geom['GridColCount'] = varargin[1]
+        vol_geom['option']['WindowMinX'] = varargin[2]
+        vol_geom['option']['WindowMaxX'] = varargin[3]
+        vol_geom['option']['WindowMinY'] = varargin[4]
+        vol_geom['option']['WindowMaxY'] = varargin[5]
+    # astra_create_vol_geom(row_count, col_count, slice_count)
+    elif len(varargin) == 3:
+        vol_geom['GridRowCount'] = varargin[0]
+        vol_geom['GridColCount'] = varargin[1]
+        vol_geom['GridSliceCount'] = varargin[2]
+    return vol_geom
+
+
+def create_proj_geom(intype, *args):
+    """Create a projection geometry.
+
+This method can be called in a number of ways:
+
+``create_proj_geom('parallel', detector_spacing, det_count, angles)``:
+
+:param detector_spacing: Distance between two adjacent detector pixels.
+:type detector_spacing: :class:`float`
+:param det_count: Number of detector pixels.
+:type det_count: :class:`int`
+:param angles: Array of angles in radians.
+:type angles: :class:`numpy.ndarray`
+:returns: A parallel projection geometry.
+
+
+``create_proj_geom('fanflat', det_width, det_count, angles, source_origin, source_det)``:
+
+:param det_width: Size of a detector pixel.
+:type det_width: :class:`float`
+:param det_count: Number of detector pixels.
+:type det_count: :class:`int`
+:param angles: Array of angles in radians.
+:type angles: :class:`numpy.ndarray`
+:param source_origin: Position of the source.
+:param source_det: Position of the detector
+:returns: A fan-beam projection geometry.
+
+``create_proj_geom('fanflat_vec', det_count, V)``:
+
+:param det_count: Number of detector pixels.
+:type det_count: :class:`int`
+:param V: Vector array.
+:type V: :class:`numpy.ndarray`
+:returns: A fan-beam projection geometry.
+
+``create_proj_geom('parallel3d', detector_spacing_x, detector_spacing_y, det_row_count, det_col_count, angles)``:
+
+:param detector_spacing_*: Distance between two adjacent detector pixels.
+:type detector_spacing_*: :class:`float`
+:param det_row_count: Number of detector pixel rows.
+:type det_row_count: :class:`int`
+:param det_col_count: Number of detector pixel columns.
+:type det_col_count: :class:`int`
+:param angles: Array of angles in radians.
+:type angles: :class:`numpy.ndarray`
+:returns: A parallel projection geometry.
+
+``create_proj_geom('cone', detector_spacing_x, detector_spacing_y, det_row_count, det_col_count, angles, source_origin, source_det)``:
+
+:param detector_spacing_*: Distance between two adjacent detector pixels.
+:type detector_spacing_*: :class:`float`
+:param det_row_count: Number of detector pixel rows.
+:type det_row_count: :class:`int`
+:param det_col_count: Number of detector pixel columns.
+:type det_col_count: :class:`int`
+:param angles: Array of angles in radians.
+:type angles: :class:`numpy.ndarray`
+:param source_origin: Distance between point source and origin.
+:type source_origin: :class:`float`
+:param source_det: Distance between the detector and origin.
+:type source_det: :class:`float`
+:returns: A cone-beam projection geometry.
+
+``create_proj_geom('cone_vec', det_row_count, det_col_count, V)``:
+
+:param det_row_count: Number of detector pixel rows.
+:type det_row_count: :class:`int`
+:param det_col_count: Number of detector pixel columns.
+:type det_col_count: :class:`int`
+:param V: Vector array.
+:type V: :class:`numpy.ndarray`
+:returns: A cone-beam projection geometry.
+
+``create_proj_geom('parallel3d_vec', det_row_count, det_col_count, V)``:
+
+:param det_row_count: Number of detector pixel rows.
+:type det_row_count: :class:`int`
+:param det_col_count: Number of detector pixel columns.
+:type det_col_count: :class:`int`
+:param V: Vector array.
+:type V: :class:`numpy.ndarray`
+:returns: A parallel projection geometry.
+
+``create_proj_geom('sparse_matrix', det_width, det_count, angles, matrix_id)``:
+
+:param det_width: Size of a detector pixel.
+:type det_width: :class:`float`
+:param det_count: Number of detector pixels.
+:type det_count: :class:`int`
+:param angles: Array of angles in radians.
+:type angles: :class:`numpy.ndarray`
+:param matrix_id: ID of the sparse matrix.
+:type matrix_id: :class:`int`
+:returns: A projection geometry based on a sparse matrix.
+
+"""
+    if intype == 'parallel':
+        if len(args) < 3:
+            raise Exception(
+                'not enough variables: astra_create_proj_geom(parallel, detector_spacing, det_count, angles)')
+        return {'type': 'parallel', 'DetectorWidth': args[0], 'DetectorCount': args[1], 'ProjectionAngles': args[2]}
+    elif intype == 'fanflat':
+        if len(args) < 5:
+            raise Exception('not enough variables: astra_create_proj_geom(fanflat, det_width, det_count, angles, source_origin, source_det)')
+        return {'type': 'fanflat', 'DetectorWidth': args[0], 'DetectorCount': args[1], 'ProjectionAngles': args[2], 'DistanceOriginSource': args[3], 'DistanceOriginDetector': args[4]}
+    elif intype == 'fanflat_vec':
+        if len(args) < 2:
+            raise Exception('not enough variables: astra_create_proj_geom(fanflat_vec, det_count, V)')
+        if not args[1].shape[1] == 6:
+            raise Exception('V should be a Nx6 matrix, with N the number of projections')
+        return {'type':'fanflat_vec', 'DetectorCount':args[0], 'Vectors':args[1]}
+    elif intype == 'parallel3d':
+        if len(args) < 5:
+            raise Exception('not enough variables: astra_create_proj_geom(parallel3d, detector_spacing_x, detector_spacing_y, det_row_count, det_col_count, angles)')
+        return {'type':'parallel3d', 'DetectorSpacingX':args[0], 'DetectorSpacingY':args[1], 'DetectorRowCount':args[2], 'DetectorColCount':args[3],'ProjectionAngles':args[4]}
+    elif intype == 'cone':
+        if len(args) < 7:
+            raise Exception('not enough variables: astra_create_proj_geom(cone, detector_spacing_x, detector_spacing_y, det_row_count, det_col_count, angles, source_origin, source_det)')
+        return {'type':	'cone','DetectorSpacingX':args[0], 'DetectorSpacingY':args[1], 'DetectorRowCount':args[2],'DetectorColCount':args[3],'ProjectionAngles':args[4],'DistanceOriginSource':	args[5],'DistanceOriginDetector':args[6]}
+    elif intype == 'cone_vec':
+        if len(args) < 3:
+            raise Exception('not enough variables: astra_create_proj_geom(cone_vec, det_row_count, det_col_count, V)')
+        if not args[2].shape[1] == 12:
+            raise Exception('V should be a Nx12 matrix, with N the number of projections')
+        return {'type': 'cone_vec','DetectorRowCount':args[0],'DetectorColCount':args[1],'Vectors':args[2]}
+    elif intype == 'parallel3d_vec':
+        if len(args) < 3:
+            raise Exception('not enough variables: astra_create_proj_geom(parallel3d_vec, det_row_count, det_col_count, V)')
+        if not args[2].shape[1] == 12:
+            raise Exception('V should be a Nx12 matrix, with N the number of projections')
+        return {'type': 'parallel3d_vec','DetectorRowCount':args[0],'DetectorColCount':args[1],'Vectors':args[2]}    
+    elif intype == 'sparse_matrix':
+        if len(args) < 4:
+            raise Exception(
+                'not enough variables: astra_create_proj_geom(sparse_matrix, det_width, det_count, angles, matrix_id)')
+        return {'type': 'sparse_matrix', 'DetectorWidth': args[0], 'DetectorCount': args[1], 'ProjectionAngles': args[2], 'MatrixID': args[3]}
+    else:
+        raise Exception('Error: unknown type ' + intype) 
+
+
+def create_backprojection(data, proj_id, useCUDA=False, returnData=True):
+    """Create a backprojection of a sinogram (2D).
+
+:param data: Sinogram data or ID.
+:type data: :class:`numpy.ndarray` or :class:`int`
+:param proj_id: ID of the projector to use.
+:type proj_id: :class:`int`
+:param useCUDA: If ``True``, use CUDA for the calculation.
+:type useCUDA: :class:`bool`
+:param returnData: If False, only return the ID of the backprojection.
+:type returnData: :class:`bool`
+:returns: :class:`int` or (:class:`int`, :class:`numpy.ndarray`) -- If ``returnData=False``, returns the ID of the backprojection. Otherwise, returns a tuple containing the ID of the backprojection and the backprojection itself, in that order.
+
+"""
+    proj_geom = projector.projection_geometry(proj_id)
+    vol_geom = projector.volume_geometry(proj_id)
+    if isinstance(data, np.ndarray):
+        sino_id = data2d.create('-sino', proj_geom, data)
+    else:
+        sino_id = data
+    vol_id = data2d.create('-vol', vol_geom, 0)
+
+    algString = 'BP'
+    if useCUDA:
+        algString = algString + '_CUDA'
+
+    cfg = astra_dict(algString)
+    if not useCUDA:
+        cfg['ProjectorId'] = proj_id
+    cfg['ProjectionDataId'] = sino_id
+    cfg['ReconstructionDataId'] = vol_id
+    alg_id = algorithm.create(cfg)
+    algorithm.run(alg_id)
+    algorithm.delete(alg_id)
+
+    if isinstance(data, np.ndarray):
+        data2d.delete(sino_id)
+
+    if returnData:
+        return vol_id, data2d.get(vol_id)
+    else:
+        return vol_id
+
+def create_backprojection3d_gpu(data, proj_geom, vol_geom, returnData=True):
+    """Create a backprojection of a sinogram (3D) using CUDA.
+
+:param data: Sinogram data or ID.
+:type data: :class:`numpy.ndarray` or :class:`int`
+:param proj_geom: Projection geometry.
+:type proj_geom: :class:`dict`
+:param vol_geom: Volume geometry.
+:type vol_geom: :class:`dict`
+:param returnData: If False, only return the ID of the backprojection.
+:type returnData: :class:`bool`
+:returns: :class:`int` or (:class:`int`, :class:`numpy.ndarray`) -- If ``returnData=False``, returns the ID of the backprojection. Otherwise, returns a tuple containing the ID of the backprojection and the backprojection itself, in that order.
+
+"""
+    if isinstance(data, np.ndarray):
+        sino_id = data3d.create('-sino', proj_geom, data)
+    else:
+        sino_id = data
+
+    vol_id = data3d.create('-vol', vol_geom, 0)
+
+    cfg = astra_dict('BP3D_CUDA')
+    cfg['ProjectionDataId'] = sino_id
+    cfg['ReconstructionDataId'] = vol_id
+    alg_id = algorithm.create(cfg)
+    algorithm.run(alg_id)
+    algorithm.delete(alg_id)
+
+    if isinstance(data, np.ndarray):
+        data3d.delete(sino_id)
+
+    if returnData:
+        return vol_id, data3d.get(vol_id)
+    else:
+        return vol_id
+
+
+def create_sino(data, proj_id=None, proj_geom=None, vol_geom=None,
+                useCUDA=False, returnData=True, gpuIndex=None):
+    """Create a forward projection of an image (2D).
+
+    :param data: Image data or ID.
+    :type data: :class:`numpy.ndarray` or :class:`int`
+    :param proj_id: ID of the projector to use.
+    :type proj_id: :class:`int`
+    :param proj_geom: Projection geometry.
+    :type proj_geom: :class:`dict`
+    :param vol_geom: Volume geometry.
+    :type vol_geom: :class:`dict`
+    :param useCUDA: If ``True``, use CUDA for the calculation.
+    :type useCUDA: :class:`bool`
+    :param returnData: If False, only return the ID of the forward projection.
+    :type returnData: :class:`bool`
+    :param gpuIndex: Optional GPU index.
+    :type gpuIndex: :class:`int`
+    :returns: :class:`int` or (:class:`int`, :class:`numpy.ndarray`)
+
+    If ``returnData=False``, returns the ID of the forward
+    projection. Otherwise, returns a tuple containing the ID of the
+    forward projection and the forward projection itself, in that
+    order.
+
+    The geometry of setup is defined by ``proj_id`` or with
+    ``proj_geom`` and ``vol_geom``. If ``proj_id`` is given, then
+    ``proj_geom`` and ``vol_geom`` must be None and vice versa.
+"""
+    if proj_id is not None:
+        proj_geom = projector.projection_geometry(proj_id)
+        vol_geom = projector.volume_geometry(proj_id)
+    elif proj_geom is not None and vol_geom is not None:
+        if not useCUDA:
+            # We need more parameters to create projector.
+            raise ValueError(
+                """A ``proj_id`` is needed when CUDA is not used.""")
+    else:
+        raise Exception("""The geometry setup is not defined.
+        The geometry of setup is defined by ``proj_id`` or with
+        ``proj_geom`` and ``vol_geom``. If ``proj_id`` is given, then
+        ``proj_geom`` and ``vol_geom`` must be None and vice versa.""")
+
+    if isinstance(data, np.ndarray):
+        volume_id = data2d.create('-vol', vol_geom, data)
+    else:
+        volume_id = data
+    sino_id = data2d.create('-sino', proj_geom, 0)
+    algString = 'FP'
+    if useCUDA:
+        algString = algString + '_CUDA'
+    cfg = astra_dict(algString)
+    if not useCUDA:
+        cfg['ProjectorId'] = proj_id
+    if gpuIndex is not None:
+        cfg['option'] = {'GPUindex': gpuIndex}
+    cfg['ProjectionDataId'] = sino_id
+    cfg['VolumeDataId'] = volume_id
+    alg_id = algorithm.create(cfg)
+    algorithm.run(alg_id)
+    algorithm.delete(alg_id)
+
+    if isinstance(data, np.ndarray):
+        data2d.delete(volume_id)
+    if returnData:
+        return sino_id, data2d.get(sino_id)
+    else:
+        return sino_id
+
+
+
+def create_sino3d_gpu(data, proj_geom, vol_geom, returnData=True, gpuIndex=None):
+    """Create a forward projection of an image (3D).
+
+:param data: Image data or ID.
+:type data: :class:`numpy.ndarray` or :class:`int`
+:param proj_geom: Projection geometry.
+:type proj_geom: :class:`dict`
+:param vol_geom: Volume geometry.
+:type vol_geom: :class:`dict`
+:param returnData: If False, only return the ID of the forward projection.
+:type returnData: :class:`bool`
+:param gpuIndex: Optional GPU index.
+:type gpuIndex: :class:`int`
+:returns: :class:`int` or (:class:`int`, :class:`numpy.ndarray`) -- If ``returnData=False``, returns the ID of the forward projection. Otherwise, returns a tuple containing the ID of the forward projection and the forward projection itself, in that order.
+
+"""
+
+    if isinstance(data, np.ndarray):
+        volume_id = data3d.create('-vol', vol_geom, data)
+    else:
+        volume_id = data
+    sino_id = data3d.create('-sino', proj_geom, 0)
+    algString = 'FP3D_CUDA'
+    cfg = astra_dict(algString)
+    if not gpuIndex==None:
+        cfg['option']={'GPUindex':gpuIndex}
+    cfg['ProjectionDataId'] = sino_id
+    cfg['VolumeDataId'] = volume_id
+    alg_id = algorithm.create(cfg)
+    algorithm.run(alg_id)
+    algorithm.delete(alg_id)
+
+    if isinstance(data, np.ndarray):
+        data3d.delete(volume_id)
+    if returnData:
+        return sino_id, data3d.get(sino_id)
+    else:
+        return sino_id
+
+
+def create_reconstruction(rec_type, proj_id, sinogram, iterations=1, use_mask='no', mask=np.array([]), use_minc='no', minc=0, use_maxc='no', maxc=255, returnData=True, filterType=None, filterData=None):
+    """Create a reconstruction of a sinogram (2D).
+
+:param rec_type: Name of the reconstruction algorithm.
+:type rec_type: :class:`string`
+:param proj_id: ID of the projector to use.
+:type proj_id: :class:`int`
+:param sinogram: Sinogram data or ID.
+:type sinogram: :class:`numpy.ndarray` or :class:`int`
+:param iterations: Number of iterations to run.
+:type iterations: :class:`int`
+:param use_mask: Whether to use a mask.
+:type use_mask: ``'yes'`` or ``'no'``
+:param mask: Mask data or ID
+:type mask: :class:`numpy.ndarray` or :class:`int`
+:param use_minc: Whether to force a minimum value on the reconstruction pixels.
+:type use_minc: ``'yes'`` or ``'no'``
+:param minc: Minimum value to use.
+:type minc: :class:`float`
+:param use_maxc: Whether to force a maximum value on the reconstruction pixels.
+:type use_maxc: ``'yes'`` or ``'no'``
+:param maxc: Maximum value to use.
+:type maxc: :class:`float`
+:param returnData: If False, only return the ID of the reconstruction.
+:type returnData: :class:`bool`
+:param filterType: Which type of filter to use for filter-based methods.
+:type filterType: :class:`string`
+:param filterData: Optional filter data for filter-based methods.
+:type filterData: :class:`numpy.ndarray`
+:returns: :class:`int` or (:class:`int`, :class:`numpy.ndarray`) -- If ``returnData=False``, returns the ID of the reconstruction. Otherwise, returns a tuple containing the ID of the reconstruction and reconstruction itself, in that order.
+
+"""
+    proj_geom = projector.projection_geometry(proj_id)
+    if isinstance(sinogram, np.ndarray):
+        sino_id = data2d.create('-sino', proj_geom, sinogram)
+    else:
+        sino_id = sinogram
+    vol_geom = projector.volume_geometry(proj_id)
+    recon_id = data2d.create('-vol', vol_geom, 0)
+    cfg = astra_dict(rec_type)
+    if not 'CUDA' in rec_type:
+        cfg['ProjectorId'] = proj_id
+    cfg['ProjectionDataId'] = sino_id
+    cfg['ReconstructionDataId'] = recon_id
+    cfg['options'] = {}
+    if use_mask == 'yes':
+        if isinstance(mask, np.ndarray):
+            mask_id = data2d.create('-vol', vol_geom, mask)
+        else:
+            mask_id = mask
+        cfg['options']['ReconstructionMaskId'] = mask_id
+    if not filterType == None:
+        cfg['FilterType'] = filterType
+    if not filterData == None:
+        if isinstance(filterData, np.ndarray):
+            nexpow = int(
+                pow(2, math.ceil(math.log(2 * proj_geom['DetectorCount'], 2))))
+            filtSize = nexpow / 2 + 1
+            filt_proj_geom = create_proj_geom(
+                'parallel', 1.0, filtSize, proj_geom['ProjectionAngles'])
+            filt_id = data2d.create('-sino', filt_proj_geom, filterData)
+        else:
+            filt_id = filterData
+        cfg['FilterSinogramId'] = filt_id
+    cfg['options']['UseMinConstraint'] = use_minc
+    cfg['options']['MinConstraintValue'] = minc
+    cfg['options']['UseMaxConstraint'] = use_maxc
+    cfg['options']['MaxConstraintValue'] = maxc
+    cfg['options']['ProjectionOrder'] = 'random'
+    alg_id = algorithm.create(cfg)
+    algorithm.run(alg_id, iterations)
+
+    algorithm.delete(alg_id)
+
+    if isinstance(sinogram, np.ndarray):
+        data2d.delete(sino_id)
+    if use_mask == 'yes' and isinstance(mask, np.ndarray):
+        data2d.delete(mask_id)
+    if not filterData == None:
+        if isinstance(filterData, np.ndarray):
+            data2d.delete(filt_id)
+    if returnData:
+        return recon_id, data2d.get(recon_id)
+    else:
+        return recon_id
+
+
+def create_projector(proj_type, proj_geom, vol_geom):
+    """Create a 2D projector.
+
+:param proj_type: Projector type, such as ``'line'``, ``'linear'``, ...
+:type proj_type: :class:`string`
+:param proj_geom: Projection geometry.
+:type proj_geom: :class:`dict`
+:param vol_geom: Volume geometry.
+:type vol_geom: :class:`dict`
+:returns: :class:`int` -- The ID of the projector.
+
+"""
+    if proj_type == 'blob':
+        raise Exception('Blob type not yet implemented')
+    cfg = astra_dict(proj_type)
+    cfg['ProjectionGeometry'] = proj_geom
+    cfg['VolumeGeometry'] = vol_geom
+    return projector.create(cfg)