Added Python interface

17 files changed, 1242 insertions, 0 deletions

diff --git a/samples/python/phantom.mat b/samples/python/phantom.mat
new file mode 100644
index 0000000..c465bbe
--- /dev/null
+++ b/samples/python/phantom.mat
diff --git a/samples/python/s001_sinogram_par2d.py b/samples/python/s001_sinogram_par2d.py
new file mode 100644
index 0000000..009d9b3
--- /dev/null
+++ b/samples/python/s001_sinogram_par2d.py
@@ -0,0 +1,60 @@
+#-----------------------------------------------------------------------
+#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 astra
+import numpy as np
+
+# Create a basic 256x256 square volume geometry
+vol_geom = astra.create_vol_geom(256, 256)
+
+# Create a parallel beam geometry with 180 angles between 0 and pi, and
+# 384 detector pixels of width 1.
+# For more details on available geometries, see the online help of the
+# function astra_create_proj_geom .
+proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,180,False))
+
+# Load a 256x256 phantom image
+import scipy.io
+P = scipy.io.loadmat('phantom.mat')['phantom256']
+
+# Create a sinogram using the GPU.
+# Note that the first time the GPU is accessed, there may be a delay
+# of up to 10 seconds for initialization.
+proj_id = astra.create_projector('line',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id,useCUDA=True)
+
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(P)
+pylab.figure(2)
+pylab.imshow(sinogram)
+pylab.show()
+
+
+# Free memory
+astra.data2d.delete(sinogram_id)
+astra.projector.delete(proj_id)
diff --git a/samples/python/s002_data2d.py b/samples/python/s002_data2d.py
new file mode 100644
index 0000000..35fb91f
--- /dev/null
+++ b/samples/python/s002_data2d.py
@@ -0,0 +1,77 @@
+#-----------------------------------------------------------------------
+#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 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))
+
+
+# Create volumes
+
+# initialized to zero
+v0 = astra.data2d.create('-vol', vol_geom)
+
+# initialized to 3.0
+v1 = astra.data2d.create('-vol', vol_geom, 3.0)
+
+# initialized to a matrix. A may be a single, double or logical (0/1) array.
+import scipy.io
+A = scipy.io.loadmat('phantom.mat')['phantom256']
+v2 = astra.data2d.create('-vol', vol_geom, A)
+
+
+# Projection data
+s0 = astra.data2d.create('-sino', proj_geom)
+# Initialization to a scalar or a matrix also works, exactly as with a volume.
+
+
+# Update data
+
+# set to zero
+astra.data2d.store(v0, 0)
+
+# set to a matrix
+astra.data2d.store(v2, A)
+
+
+
+# Retrieve data
+
+R = astra.data2d.get(v2)
+import pylab
+pylab.gray()
+pylab.imshow(R)
+pylab.show()
+
+
+# Free memory
+astra.data2d.delete(v0)
+astra.data2d.delete(v1)
+astra.data2d.delete(v2)
+astra.data2d.delete(s0)
diff --git a/samples/python/s003_gpu_reconstruction.py b/samples/python/s003_gpu_reconstruction.py
new file mode 100644
index 0000000..4f6ec1f
--- /dev/null
+++ b/samples/python/s003_gpu_reconstruction.py
@@ -0,0 +1,75 @@
+#-----------------------------------------------------------------------
+#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 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))
+
+# As before, create a sinogram from a phantom
+import scipy.io
+P = scipy.io.loadmat('phantom.mat')['phantom256']
+proj_id = astra.create_projector('line',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id,useCUDA=True)
+
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(P)
+pylab.figure(2)
+pylab.imshow(sinogram)
+
+# Create a data object for the reconstruction
+rec_id = astra.data2d.create('-vol', vol_geom)
+
+# Set up the parameters for a reconstruction algorithm using the GPU
+cfg = astra.astra_dict('SIRT_CUDA')
+cfg['ReconstructionDataId'] = rec_id
+cfg['ProjectionDataId'] = sinogram_id
+
+# Available algorithms:
+# SIRT_CUDA, SART_CUDA, EM_CUDA, FBP_CUDA (see the FBP sample)
+
+
+# Create the algorithm object from the configuration structure
+alg_id = astra.algorithm.create(cfg)
+
+# Run 150 iterations of the algorithm
+astra.algorithm.run(alg_id, 150)
+
+# Get the result
+rec = astra.data2d.get(rec_id)
+pylab.figure(3)
+pylab.imshow(rec)
+pylab.show()
+
+# Clean up. Note that GPU memory is tied up in the algorithm object,
+# and main RAM in the data objects.
+astra.algorithm.delete(alg_id)
+astra.data2d.delete(rec_id)
+astra.data2d.delete(sinogram_id)
+astra.projector.delete(proj_id)
diff --git a/samples/python/s004_cpu_reconstruction.py b/samples/python/s004_cpu_reconstruction.py
new file mode 100644
index 0000000..8385cf8
--- /dev/null
+++ b/samples/python/s004_cpu_reconstruction.py
@@ -0,0 +1,81 @@
+#-----------------------------------------------------------------------
+#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 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 "strip" model.
+proj_id = astra.create_projector('strip', proj_geom, vol_geom)
+
+# Create a sinogram from a phantom
+import scipy.io
+P = scipy.io.loadmat('phantom.mat')['phantom256']
+sinogram_id, sinogram = astra.create_sino(P, proj_id)
+
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(P)
+pylab.figure(2)
+pylab.imshow(sinogram)
+
+# Create a data object for the reconstruction
+rec_id = astra.data2d.create('-vol', vol_geom)
+
+# Set up the parameters for a reconstruction algorithm using the CPU
+# The main difference with the configuration of a GPU algorithm is the
+# extra ProjectorId setting.
+cfg = astra.astra_dict('SIRT')
+cfg['ReconstructionDataId'] = rec_id
+cfg['ProjectionDataId'] = sinogram_id
+cfg['ProjectorId'] = proj_id
+
+# Available algorithms:
+# ART, SART, SIRT, CGLS, FBP
+
+
+# Create the algorithm object from the configuration structure
+alg_id = astra.algorithm.create(cfg)
+
+# Run 20 iterations of the algorithm
+# This will have a runtime in the order of 10 seconds.
+astra.algorithm.run(alg_id, 20)
+
+# Get the result
+rec = astra.data2d.get(rec_id)
+pylab.figure(3)
+pylab.imshow(rec)
+pylab.show()
+
+# Clean up.
+astra.algorithm.delete(alg_id)
+astra.data2d.delete(rec_id)
+astra.data2d.delete(sinogram_id)
+astra.projector.delete(proj_id)
diff --git a/samples/python/s005_3d_geometry.py b/samples/python/s005_3d_geometry.py
new file mode 100644
index 0000000..f43fc7e
--- /dev/null
+++ b/samples/python/s005_3d_geometry.py
@@ -0,0 +1,114 @@
+#-----------------------------------------------------------------------
+#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/>.
+#
+#-----------------------------------------------------------------------
+
+from six.moves import range
+import astra
+import numpy as np
+
+vol_geom = astra.create_vol_geom(64, 64, 64)
+
+
+# There are two main 3d projection geometry types: cone beam and parallel beam.
+# Each has a regular variant, and a 'vec' variant.
+# The 'vec' variants are completely free in the placement of source/detector,
+# while the regular variants assume circular trajectories around the z-axis.
+
+
+# -------------
+# Parallel beam
+# -------------
+
+
+# Circular
+
+# Parameters: width of detector column, height of detector row, #rows, #columns
+angles = np.linspace(0, 2*np.pi, 48, False)
+proj_geom = astra.create_proj_geom('parallel3d', 1.0, 1.0, 32, 64, angles)
+
+
+# Free
+
+# We generate the same geometry as the circular one above. 
+vectors = np.zeros((len(angles), 12))
+for i in range(len(angles)):
+  # ray direction
+  vectors[i,0] = np.sin(angles[i])
+  vectors[i,1] = -np.cos(angles[i])
+  vectors[i,2] = 0
+
+  # center of detector
+  vectors[i,3:6] = 0
+
+  # vector from detector pixel (0,0) to (0,1)
+  vectors[i,6] = np.cos(angles[i])
+  vectors[i,7] = np.sin(angles[i])
+  vectors[i,8] = 0;
+
+  # vector from detector pixel (0,0) to (1,0)
+  vectors[i,9] = 0
+  vectors[i,10] = 0
+  vectors[i,11] = 1
+
+# Parameters: #rows, #columns, vectors
+proj_geom = astra.create_proj_geom('parallel3d_vec', 32, 64, vectors)
+
+# ----------
+# Cone beam
+# ----------
+
+
+# Circular
+
+# Parameters: width of detector column, height of detector row, #rows, #columns,
+#             angles, distance source-origin, distance origin-detector
+angles = np.linspace(0, 2*np.pi, 48, False)
+proj_geom = astra.create_proj_geom('cone', 1.0, 1.0, 32, 64, angles, 1000, 0)
+
+# Free
+
+vectors = np.zeros((len(angles), 12))
+for i in range(len(angles)):
+	# source
+	vectors[i,0] = np.sin(angles[i]) * 1000
+	vectors[i,1] = -np.cos(angles[i]) * 1000
+	vectors[i,2] = 0
+
+	# center of detector
+	vectors[i,3:6] = 0
+
+	# vector from detector pixel (0,0) to (0,1)
+	vectors[i,6] = np.cos(angles[i])
+	vectors[i,7] = np.sin(angles[i])
+	vectors[i,8] = 0
+
+	# vector from detector pixel (0,0) to (1,0)
+	vectors[i,9] = 0
+	vectors[i,10] = 0
+	vectors[i,11] = 1		
+
+# Parameters: #rows, #columns, vectors
+proj_geom = astra.create_proj_geom('cone_vec', 32, 64, vectors)
+
diff --git a/samples/python/s006_3d_data.py b/samples/python/s006_3d_data.py
new file mode 100644
index 0000000..5178179
--- /dev/null
+++ b/samples/python/s006_3d_data.py
@@ -0,0 +1,76 @@
+#-----------------------------------------------------------------------
+#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 astra
+import numpy as np
+
+# Create a 3D volume geometry.
+# Parameter order: rows, colums, slices (y, x, z)
+vol_geom = astra.create_vol_geom(64, 48, 32)
+
+
+# Create volumes
+
+# initialized to zero
+v0 = astra.data3d.create('-vol', vol_geom)
+
+# initialized to 3.0
+v1 = astra.data3d.create('-vol', vol_geom, 3.0)
+
+# initialized to a matrix. A may be a single or double array.
+# Coordinate order: slice, row, column (z, y, x)
+A = np.zeros((32, 64, 48))
+v2 = astra.data3d.create('-vol', vol_geom, A)
+
+
+# Projection data
+
+# 2 projection directions, along x and y axis resp.
+V = np.array([[ 1,0,0, 0,0,0,  0,1,0, 0,0,1],
+      [0,1,0, 0,0,0, -1,0,0, 0,0,1]],dtype=np.float)
+# 32 rows (v), 64 columns (u)
+proj_geom = astra.create_proj_geom('parallel3d_vec', 32, 64, V)
+
+s0 = astra.data3d.create('-proj3d', proj_geom)
+
+# Initialization to a scalar or zero works exactly as with a volume.
+
+# Initialized to a matrix:
+# Coordinate order: row (v), angle, column (u)
+A = np.zeros((32, 2, 64))
+s1 = astra.data3d.create('-proj3d', proj_geom, A)
+
+
+# Retrieve data:
+R = astra.data3d.get(v1)
+
+
+# Delete all created data objects
+astra.data3d.delete(v0)
+astra.data3d.delete(v1)
+astra.data3d.delete(v2)
+astra.data3d.delete(s0)
+astra.data3d.delete(s1)
diff --git a/samples/python/s007_3d_reconstruction.py b/samples/python/s007_3d_reconstruction.py
new file mode 100644
index 0000000..40e9556
--- /dev/null
+++ b/samples/python/s007_3d_reconstruction.py
@@ -0,0 +1,77 @@
+#-----------------------------------------------------------------------
+#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 astra
+import numpy as np
+
+vol_geom = astra.create_vol_geom(128, 128, 128)
+
+angles = np.linspace(0, np.pi, 180,False)
+proj_geom = astra.create_proj_geom('parallel3d', 1.0, 1.0, 128, 192, angles)
+
+# Create a simple hollow cube phantom
+cube = np.zeros((128,128,128))
+cube[17:113,17:113,17:113] = 1
+cube[33:97,33:97,33:97] = 0
+
+# Create projection data from this
+proj_id, proj_data = astra.create_sino3d_gpu(cube, proj_geom, vol_geom)
+
+# Display a single projection image
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(proj_data[:,20,:])
+
+# Create a data object for the reconstruction
+rec_id = astra.data3d.create('-vol', vol_geom)
+
+# Set up the parameters for a reconstruction algorithm using the GPU
+cfg = astra.astra_dict('SIRT3D_CUDA')
+cfg['ReconstructionDataId'] = rec_id
+cfg['ProjectionDataId'] = proj_id
+
+
+# Create the algorithm object from the configuration structure
+alg_id = astra.algorithm.create(cfg)
+
+# Run 150 iterations of the algorithm
+# Note that this requires about 750MB of GPU memory, and has a runtime
+# in the order of 10 seconds.
+astra.algorithm.run(alg_id, 150)
+
+# Get the result
+rec = astra.data3d.get(rec_id)
+pylab.figure(2)
+pylab.imshow(rec[:,:,65])
+pylab.show()
+
+
+# Clean up. Note that GPU memory is tied up in the algorithm object,
+# and main RAM in the data objects.
+astra.algorithm.delete(alg_id)
+astra.data3d.delete(rec_id)
+astra.data3d.delete(proj_id)
diff --git a/samples/python/s008_gpu_selection.py b/samples/python/s008_gpu_selection.py
new file mode 100644
index 0000000..c42e53b
--- /dev/null
+++ b/samples/python/s008_gpu_selection.py
@@ -0,0 +1,61 @@
+#-----------------------------------------------------------------------
+#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 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('line',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, useCUDA=True, 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)
diff --git a/samples/python/s009_projection_matrix.py b/samples/python/s009_projection_matrix.py
new file mode 100644
index 0000000..c4c4557
--- /dev/null
+++ b/samples/python/s009_projection_matrix.py
@@ -0,0 +1,65 @@
+#-----------------------------------------------------------------------
+#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 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.flatten())
+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)
diff --git a/samples/python/s010_supersampling.py b/samples/python/s010_supersampling.py
new file mode 100644
index 0000000..1a337bc
--- /dev/null
+++ b/samples/python/s010_supersampling.py
@@ -0,0 +1,85 @@
+#-----------------------------------------------------------------------
+#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 astra
+import numpy as np
+
+vol_geom = astra.create_vol_geom(256, 256)
+proj_geom = astra.create_proj_geom('parallel', 3.0, 128, np.linspace(0,np.pi,180,False))
+import scipy.io
+P = scipy.io.loadmat('phantom.mat')['phantom256']
+
+# Because the astra.create_sino method does not have support for
+# all possible algorithm options, we manually create a sinogram
+phantom_id = astra.data2d.create('-vol', vol_geom, P)
+sinogram_id = astra.data2d.create('-sino', proj_geom)
+cfg = astra.astra_dict('FP_CUDA')
+cfg['VolumeDataId'] = phantom_id
+cfg['ProjectionDataId'] = sinogram_id
+
+# Set up 3 rays per detector element
+cfg['option'] = {}
+cfg['option']['DetectorSuperSampling'] = 3
+
+alg_id = astra.algorithm.create(cfg)
+astra.algorithm.run(alg_id)
+astra.algorithm.delete(alg_id)
+astra.data2d.delete(phantom_id)
+
+sinogram3 = astra.data2d.get(sinogram_id)
+
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(P)
+pylab.figure(2)
+pylab.imshow(sinogram3)
+
+# Create a reconstruction, also using supersampling
+rec_id = astra.data2d.create('-vol', vol_geom)
+cfg = astra.astra_dict('SIRT_CUDA')
+cfg['ReconstructionDataId'] = rec_id
+cfg['ProjectionDataId'] = sinogram_id
+# Set up 3 rays per detector element
+cfg['option'] = {}
+cfg['option']['DetectorSuperSampling'] = 3
+
+# There is also an option for supersampling during the backprojection step.
+# This should be used if your detector pixels are smaller than the voxels.
+
+# Set up 2 rays per image pixel dimension, for 4 rays total per image pixel.
+# cfg['option']['PixelSuperSampling'] = 2
+
+
+alg_id = astra.algorithm.create(cfg)
+astra.algorithm.run(alg_id, 150)
+astra.algorithm.delete(alg_id)
+
+rec = astra.data2d.get(rec_id)
+pylab.figure(3)
+pylab.imshow(rec)
+pylab.show()
+
diff --git a/samples/python/s011_object_info.py b/samples/python/s011_object_info.py
new file mode 100644
index 0000000..02f387a
--- /dev/null
+++ b/samples/python/s011_object_info.py
@@ -0,0 +1,54 @@
+#-----------------------------------------------------------------------
+#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 astra
+
+# Create two volume geometries
+vol_geom1 = astra.create_vol_geom(256, 256)
+vol_geom2 = astra.create_vol_geom(512, 256)
+
+# Create volumes
+v0 = astra.data2d.create('-vol', vol_geom1)
+v1 = astra.data2d.create('-vol', vol_geom2)
+v2 = astra.data2d.create('-vol', vol_geom2)
+
+# Show the currently allocated volumes
+astra.data2d.info()
+
+
+astra.data2d.delete(v2)
+astra.data2d.info()
+
+astra.data2d.clear()
+astra.data2d.info()
+
+
+
+# The same clear and info command also work for other object types:
+astra.algorithm.info()  
+astra.data3d.info()
+astra.projector.info()
+astra.matrix.info()
diff --git a/samples/python/s012_masks.py b/samples/python/s012_masks.py
new file mode 100644
index 0000000..441d11b
--- /dev/null
+++ b/samples/python/s012_masks.py
@@ -0,0 +1,92 @@
+#-----------------------------------------------------------------------
+#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 astra
+import numpy as np
+
+# In this example we will create a reconstruction in a circular region,
+# instead of the usual rectangle.
+
+# This is done by placing a circular mask on the square reconstruction volume:
+
+c = np.linspace(-127.5,127.5,256)
+x, y = np.meshgrid(c,c)
+mask = np.array((x**2 + y**2 < 127.5**2),dtype=np.float)
+
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(mask)
+
+vol_geom = astra.create_vol_geom(256, 256)
+proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,50,False))
+
+# As before, create a sinogram from a phantom
+import scipy.io
+P = scipy.io.loadmat('phantom.mat')['phantom256']
+proj_id = astra.create_projector('line',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id,useCUDA=True)
+
+pylab.figure(2)
+pylab.imshow(P)
+pylab.figure(3)
+pylab.imshow(sinogram)
+
+# Create a data object for the reconstruction
+rec_id = astra.data2d.create('-vol', vol_geom)
+
+# Create a data object for the mask
+mask_id = astra.data2d.create('-vol', vol_geom, mask)
+
+# Set up the parameters for a reconstruction algorithm using the GPU
+cfg = astra.astra_dict('SIRT_CUDA')
+cfg['ReconstructionDataId'] = rec_id
+cfg['ProjectionDataId'] = sinogram_id
+cfg['option'] = {}
+cfg['option']['ReconstructionMaskId'] = mask_id
+
+# Create the algorithm object from the configuration structure
+alg_id = astra.algorithm.create(cfg)
+
+# Run 150 iterations of the algorithm
+astra.algorithm.run(alg_id, 150)
+
+# Get the result
+rec = astra.data2d.get(rec_id)
+
+pylab.figure(4)
+pylab.imshow(rec)
+
+pylab.show()
+
+# Clean up. Note that GPU memory is tied up in the algorithm object,
+# and main RAM in the data objects.
+astra.algorithm.delete(alg_id)
+astra.data2d.delete(mask_id)
+astra.data2d.delete(rec_id)
+astra.data2d.delete(sinogram_id)
+astra.projector.delete(proj_id)
diff --git a/samples/python/s013_constraints.py b/samples/python/s013_constraints.py
new file mode 100644
index 0000000..009360e
--- /dev/null
+++ b/samples/python/s013_constraints.py
@@ -0,0 +1,77 @@
+#-----------------------------------------------------------------------
+#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 astra
+import numpy as np
+
+# In this example we will create a reconstruction constrained to
+# greyvalues between 0 and 1
+
+vol_geom = astra.create_vol_geom(256, 256)
+proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,50,False))
+
+# As before, create a sinogram from a phantom
+import scipy.io
+P = scipy.io.loadmat('phantom.mat')['phantom256']
+proj_id = astra.create_projector('line',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id,useCUDA=True)
+
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(P)
+pylab.figure(2)
+pylab.imshow(sinogram)
+
+# Create a data object for the reconstruction
+rec_id = astra.data2d.create('-vol', vol_geom)
+
+# Set up the parameters for a reconstruction algorithm using the GPU
+cfg = astra.astra_dict('SIRT_CUDA')
+cfg['ReconstructionDataId'] = rec_id
+cfg['ProjectionDataId'] = sinogram_id
+cfg['option']={}
+cfg['option']['MinConstraint'] = 0
+cfg['option']['MaxConstraint'] = 1
+
+# Create the algorithm object from the configuration structure
+alg_id = astra.algorithm.create(cfg)
+
+# Run 150 iterations of the algorithm
+astra.algorithm.run(alg_id, 150)
+
+# Get the result
+rec = astra.data2d.get(rec_id)
+pylab.figure(3)
+pylab.imshow(rec)
+pylab.show()
+
+# Clean up. Note that GPU memory is tied up in the algorithm object,
+# and main RAM in the data objects.
+astra.algorithm.delete(alg_id)
+astra.data2d.delete(rec_id)
+astra.data2d.delete(sinogram_id)
+astra.projector.delete(proj_id)
diff --git a/samples/python/s014_FBP.py b/samples/python/s014_FBP.py
new file mode 100644
index 0000000..ef4afc2
--- /dev/null
+++ b/samples/python/s014_FBP.py
@@ -0,0 +1,76 @@
+#-----------------------------------------------------------------------
+#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 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))
+
+# As before, create a sinogram from a phantom
+import scipy.io
+P = scipy.io.loadmat('phantom.mat')['phantom256']
+proj_id = astra.create_projector('line',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id,useCUDA=True)
+
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(P)
+pylab.figure(2)
+pylab.imshow(sinogram)
+
+# Create a data object for the reconstruction
+rec_id = astra.data2d.create('-vol', vol_geom)
+
+# create configuration 
+cfg = astra.astra_dict('FBP_CUDA')
+cfg['ReconstructionDataId'] = rec_id
+cfg['ProjectionDataId'] = sinogram_id
+cfg['FilterType'] = 'Ram-Lak'
+
+# possible values for FilterType:
+# none, ram-lak, shepp-logan, cosine, hamming, hann, tukey, lanczos,
+# triangular, gaussian, barlett-hann, blackman, nuttall, blackman-harris,
+# blackman-nuttall, flat-top, kaiser, parzen
+
+
+# Create and run the algorithm object from the configuration structure
+alg_id = astra.algorithm.create(cfg)
+astra.algorithm.run(alg_id)
+
+# Get the result
+rec = astra.data2d.get(rec_id)
+pylab.figure(3)
+pylab.imshow(rec)
+pylab.show()
+
+# Clean up. Note that GPU memory is tied up in the algorithm object,
+# and main RAM in the data objects.
+astra.algorithm.delete(alg_id)
+astra.data2d.delete(rec_id)
+astra.data2d.delete(sinogram_id)
+astra.projector.delete(proj_id)
diff --git a/samples/python/s015_fp_bp.py b/samples/python/s015_fp_bp.py
new file mode 100644
index 0000000..10c238d
--- /dev/null
+++ b/samples/python/s015_fp_bp.py
@@ -0,0 +1,86 @@
+#-----------------------------------------------------------------------
+#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/>.
+#
+#-----------------------------------------------------------------------
+
+
+# This example demonstrates using the FP and BP primitives with Matlab's lsqr
+# solver. Calls to FP (astra_create_sino_cuda) and
+# BP (astra_create_backprojection_cuda) are wrapped in a function astra_wrap,
+# and a handle to this function is passed to lsqr.
+
+# Because in this case the inputs/outputs of FP and BP have to be vectors
+# instead of images (matrices), the calls require reshaping to and from vectors.
+
+import astra
+import numpy as np
+
+# FP/BP wrapper class
+class astra_wrap(object):
+    def __init__(self,proj_geom,vol_geom):
+        self.proj_id = astra.create_projector('line',proj_geom,vol_geom)
+        self.shape = (proj_geom['DetectorCount']*len(proj_geom['ProjectionAngles']),vol_geom['GridColCount']*vol_geom['GridRowCount'])
+        self.dtype = np.float
+    
+    def matvec(self,v):
+        sid, s = astra.create_sino(np.reshape(v,(vol_geom['GridRowCount'],vol_geom['GridColCount'])),self.proj_id,useCUDA=True)
+        astra.data2d.delete(sid)
+        return s.flatten()
+    
+    def rmatvec(self,v):
+        bid, b = astra.create_backprojection(np.reshape(v,(len(proj_geom['ProjectionAngles']),proj_geom['DetectorCount'],)),self.proj_id,useCUDA=True)
+        astra.data2d.delete(bid)
+        return b.flatten()
+
+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))
+
+# Create a 256x256 phantom image
+import scipy.io
+P = scipy.io.loadmat('phantom.mat')['phantom256']
+
+# Create a sinogram using the GPU.
+proj_id = astra.create_projector('line',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id,useCUDA=True)
+
+# Reshape the sinogram into a vector
+b = sinogram.flatten()
+
+# Call lsqr with ASTRA FP and BP
+import scipy.sparse.linalg
+wrapper = astra_wrap(proj_geom,vol_geom)
+result = scipy.sparse.linalg.lsqr(wrapper,b,atol=1e-4,btol=1e-4,iter_lim=25)
+
+# Reshape the result into an image
+Y = np.reshape(result[0],(vol_geom['GridRowCount'], vol_geom['GridColCount']));
+
+import pylab
+pylab.gray()
+pylab.imshow(Y)
+pylab.show()
+
+astra.data2d.delete(sinogram_id)
+astra.projector.delete(proj_id)
+astra.projector.delete(wrapper.proj_id)
+
diff --git a/samples/python/s016_plots.py b/samples/python/s016_plots.py
new file mode 100644
index 0000000..cd4d98c
--- /dev/null
+++ b/samples/python/s016_plots.py
@@ -0,0 +1,86 @@
+#-----------------------------------------------------------------------
+#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/>.
+#
+#-----------------------------------------------------------------------
+
+from six.moves import range
+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))
+
+# As before, create a sinogram from a phantom
+import scipy.io
+P = scipy.io.loadmat('phantom.mat')['phantom256']
+proj_id = astra.create_projector('line',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id,useCUDA=True)
+
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(P)
+pylab.figure(2)
+pylab.imshow(sinogram)
+
+# Create a data object for the reconstruction
+rec_id = astra.data2d.create('-vol', vol_geom)
+
+# Set up the parameters for a reconstruction algorithm using the GPU
+cfg = astra.astra_dict('SIRT_CUDA')
+cfg['ReconstructionDataId'] = rec_id
+cfg['ProjectionDataId'] = sinogram_id
+
+# Create the algorithm object from the configuration structure
+alg_id = astra.algorithm.create(cfg)
+
+# Run 1500 iterations of the algorithm one at a time, keeping track of errors
+nIters = 1500
+phantom_error = np.zeros(nIters)
+residual_error = np.zeros(nIters)
+for i in range(nIters):
+  # Run a single iteration
+  astra.algorithm.run(alg_id, 1)
+  residual_error[i] = astra.algorithm.get_res_norm(alg_id)
+  rec = astra.data2d.get(rec_id)
+  phantom_error[i] = np.sqrt(((rec - P)**2).sum())
+
+# Get the result
+rec = astra.data2d.get(rec_id)
+pylab.figure(3)
+pylab.imshow(rec)
+
+pylab.figure(4)
+pylab.plot(residual_error)
+pylab.figure(5)
+pylab.plot(phantom_error)
+
+pylab.show()
+
+# Clean up.
+astra.algorithm.delete(alg_id)
+astra.data2d.delete(rec_id)
+astra.data2d.delete(sinogram_id)
+astra.projector.delete(proj_id)