# ----------------------------------------------------------------------- # Copyright: 2010-2016, iMinds-Vision Lab, University of Antwerp # 2013-2016, CWI, Amsterdam # # Contact: astra@uantwerpen.be # Website: http://www.astra-toolbox.com/ # # This file is part of the ASTRA Toolbox. # # # 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 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 ASTRA Toolbox. If not, see . # # ----------------------------------------------------------------------- import astra import numpy as np vol_geom = astra.create_vol_geom(256, 256) proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,180,False)) # For CPU-based algorithms, a "projector" object specifies the projection # model used. In this case, we use the "line" model. proj_id = astra.create_projector('line', proj_geom, vol_geom) # Generate the projection matrix for this projection model. # This creates a matrix W where entry w_{i,j} corresponds to the # contribution of volume element j to detector element i. matrix_id = astra.projector.matrix(proj_id) # Get the projection matrix as a Scipy sparse matrix. W = astra.matrix.get(matrix_id) # Manually use this projection matrix to do a projection: import scipy.io P = scipy.io.loadmat('phantom.mat')['phantom256'] s = W.dot(P.ravel()) s = np.reshape(s, (len(proj_geom['ProjectionAngles']),proj_geom['DetectorCount'])) import pylab pylab.gray() pylab.figure(1) pylab.imshow(s) pylab.show() # Each row of the projection matrix corresponds to a detector element. # Detector t for angle p is for row 1 + t + p*proj_geom.DetectorCount. # Each column corresponds to a volume pixel. # Pixel (x,y) corresponds to column 1 + x + y*vol_geom.GridColCount. astra.projector.delete(proj_id) astra.matrix.delete(matrix_id)