# ----------------------------------------------------------------------- # 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)) import scipy.io P = scipy.io.loadmat('phantom.mat')['phantom256'] proj_id = astra.create_projector('cuda',proj_geom,vol_geom) # Create a sinogram from a phantom, using GPU #1. (The default is #0) sinogram_id, sinogram = astra.create_sino(P, proj_id, gpuIndex=1) # Set up the parameters for a reconstruction algorithm using the GPU rec_id = astra.data2d.create('-vol', vol_geom) cfg = astra.astra_dict('SIRT_CUDA') cfg['ReconstructionDataId'] = rec_id cfg['ProjectionDataId'] = sinogram_id # Use GPU #1 for the reconstruction. (The default is #0.) cfg['option'] = {} cfg['option']['GPUindex'] = 1 # Run 150 iterations of the algorithm alg_id = astra.algorithm.create(cfg) astra.algorithm.run(alg_id, 150) rec = astra.data2d.get(rec_id) # Clean up. astra.algorithm.delete(alg_id) astra.data2d.delete(rec_id) astra.data2d.delete(sinogram_id) astra.projector.delete(proj_id)