10 files changed, 92 insertions, 23 deletions
diff --git a/samples/python/s001_sinogram_par2d.py b/samples/python/s001_sinogram_par2d.py
index 009d9b3..1d1b912 100644
--- a/samples/python/s001_sinogram_par2d.py
+++ b/samples/python/s001_sinogram_par2d.py
@@ -43,8 +43,8 @@ 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)
+proj_id = astra.create_projector('cuda',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id)
 
 import pylab
 pylab.gray()
diff --git a/samples/python/s003_gpu_reconstruction.py b/samples/python/s003_gpu_reconstruction.py
index 4f6ec1f..07b38ef 100644
--- a/samples/python/s003_gpu_reconstruction.py
+++ b/samples/python/s003_gpu_reconstruction.py
@@ -33,8 +33,8 @@ proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,180
 # 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)
+proj_id = astra.create_projector('cuda',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id)
 
 import pylab
 pylab.gray()
diff --git a/samples/python/s005_3d_geometry.py b/samples/python/s005_3d_geometry.py
index f43fc7e..a7f7a3d 100644
--- a/samples/python/s005_3d_geometry.py
+++ b/samples/python/s005_3d_geometry.py
@@ -24,7 +24,11 @@
 #
 #-----------------------------------------------------------------------
 
-from six.moves import range
+try:
+    from six.moves import range
+except ImportError:
+    # six 1.3.0
+    from six.moves import xrange as range
 import astra
 import numpy as np
 
diff --git a/samples/python/s008_gpu_selection.py b/samples/python/s008_gpu_selection.py
index c42e53b..a180802 100644
--- a/samples/python/s008_gpu_selection.py
+++ b/samples/python/s008_gpu_selection.py
@@ -32,10 +32,10 @@ proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,180
 import scipy.io
 P = scipy.io.loadmat('phantom.mat')['phantom256']
 
-proj_id = astra.create_projector('line',proj_geom,vol_geom)
+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, useCUDA=True, gpuIndex=1)
+sinogram_id, sinogram = astra.create_sino(P, proj_id, gpuIndex=1)
 
 
 # Set up the parameters for a reconstruction algorithm using the GPU
diff --git a/samples/python/s012_masks.py b/samples/python/s012_masks.py
index 441d11b..0f667b0 100644
--- a/samples/python/s012_masks.py
+++ b/samples/python/s012_masks.py
@@ -48,8 +48,8 @@ proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,50,
 # 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)
+proj_id = astra.create_projector('cuda',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id)
 
 pylab.figure(2)
 pylab.imshow(P)
diff --git a/samples/python/s013_constraints.py b/samples/python/s013_constraints.py
index 009360e..8b63d5e 100644
--- a/samples/python/s013_constraints.py
+++ b/samples/python/s013_constraints.py
@@ -36,8 +36,8 @@ proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,50,
 # 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)
+proj_id = astra.create_projector('cuda',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id)
 
 import pylab
 pylab.gray()
diff --git a/samples/python/s014_FBP.py b/samples/python/s014_FBP.py
index ef4afc2..2f8e388 100644
--- a/samples/python/s014_FBP.py
+++ b/samples/python/s014_FBP.py
@@ -33,8 +33,8 @@ proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,180
 # 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)
+proj_id = astra.create_projector('cuda',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id)
 
 import pylab
 pylab.gray()
diff --git a/samples/python/s015_fp_bp.py b/samples/python/s015_fp_bp.py
index 10c238d..fa0bf86 100644
--- a/samples/python/s015_fp_bp.py
+++ b/samples/python/s015_fp_bp.py
@@ -26,8 +26,8 @@
 
 
 # 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,
+# solver. Calls to FP (astra.create_sino) and
+# BP (astra.create_backprojection) 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
@@ -39,17 +39,17 @@ 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.proj_id = astra.create_projector('cuda',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)
+        sid, s = astra.create_sino(np.reshape(v,(vol_geom['GridRowCount'],vol_geom['GridColCount'])),self.proj_id)
         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)
+        bid, b = astra.create_backprojection(np.reshape(v,(len(proj_geom['ProjectionAngles']),proj_geom['DetectorCount'],)),self.proj_id)
         astra.data2d.delete(bid)
         return b.flatten()
 
@@ -61,8 +61,8 @@ 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)
+proj_id = astra.create_projector('cuda',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id)
 
 # Reshape the sinogram into a vector
 b = sinogram.flatten()
diff --git a/samples/python/s016_plots.py b/samples/python/s016_plots.py
index cd4d98c..8a8ba64 100644
--- a/samples/python/s016_plots.py
+++ b/samples/python/s016_plots.py
@@ -24,7 +24,11 @@
 #
 #-----------------------------------------------------------------------
 
-from six.moves import range
+try:
+    from six.moves import range
+except ImportError:
+    # six 1.3.0
+    from six.moves import xrange as range
 import astra
 import numpy as np
 
@@ -35,8 +39,8 @@ proj_geom = astra.create_proj_geom('parallel', 1.0, 384, np.linspace(0,np.pi,180
 # 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)
+proj_id = astra.create_projector('cuda',proj_geom,vol_geom)
+sinogram_id, sinogram = astra.create_sino(P, proj_id)
 
 import pylab
 pylab.gray()
diff --git a/samples/python/s017_OpTomo.py b/samples/python/s017_OpTomo.py
new file mode 100644
index 0000000..967fa64
--- /dev/null
+++ b/samples/python/s017_OpTomo.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
+import scipy.sparse.linalg
+
+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('cuda',proj_geom,vol_geom)
+
+# construct the OpTomo object
+W = astra.OpTomo(proj_id)
+
+sinogram = W * P
+sinogram = sinogram.reshape([180, 384])
+
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(P)
+pylab.figure(2)
+pylab.imshow(sinogram)
+
+# Run the lsqr linear solver
+output = scipy.sparse.linalg.lsqr(W, sinogram.flatten(), iter_lim=150)
+rec = output[0].reshape([256, 256])
+
+pylab.figure(3)
+pylab.imshow(rec)
+pylab.show()
+
+# Clean up.
+astra.projector.delete(proj_id)