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-rw-r--r--samples/matlab/s017_opTomo.m62
-rw-r--r--samples/python/s001_sinogram_par2d.py4
-rw-r--r--samples/python/s003_gpu_reconstruction.py4
-rw-r--r--samples/python/s005_3d_geometry.py6
-rw-r--r--samples/python/s008_gpu_selection.py4
-rw-r--r--samples/python/s012_masks.py4
-rw-r--r--samples/python/s013_constraints.py4
-rw-r--r--samples/python/s014_FBP.py4
-rw-r--r--samples/python/s015_fp_bp.py14
-rw-r--r--samples/python/s016_plots.py10
-rw-r--r--samples/python/s017_OpTomo.py61
11 files changed, 154 insertions, 23 deletions
diff --git a/samples/matlab/s017_opTomo.m b/samples/matlab/s017_opTomo.m
new file mode 100644
index 0000000..891a93d
--- /dev/null
+++ b/samples/matlab/s017_opTomo.m
@@ -0,0 +1,62 @@
+% -----------------------------------------------------------------------
+% This file is part of the ASTRA Toolbox
+%
+% Copyright: 2010-2015, iMinds-Vision Lab, University of Antwerp
+% 2014-2015, CWI, Amsterdam
+% License: Open Source under GPLv3
+% Contact: astra@uantwerpen.be
+% Website: http://sf.net/projects/astra-toolbox
+% -----------------------------------------------------------------------
+
+% This sample illustrates the use of opTomo.
+%
+% opTomo is a wrapper around the FP and BP operations of the ASTRA Toolbox,
+% to allow you to use them as you would a matrix.
+%
+% This class requires the Spot Linear-Operator Toolbox to be installed.
+% You can download this at http://www.cs.ubc.ca/labs/scl/spot/
+
+% load a phantom image
+im = phantom(256);
+% and flatten it to a vector
+x = im(:);
+
+%% Setting up the geometry
+% projection geometry
+proj_geom = astra_create_proj_geom('parallel', 1, 256, linspace2(0,pi,180));
+% object dimensions
+vol_geom = astra_create_vol_geom(256,256);
+
+%% Generate projection data
+% Create the Spot operator for ASTRA using the GPU.
+W = opTomo('cuda', proj_geom, vol_geom);
+
+p = W*x;
+
+% reshape the vector into a sinogram
+sinogram = reshape(p, W.proj_size);
+imshow(sinogram, []);
+
+
+%% Reconstruction
+% We use a least squares solver lsqr from Matlab to solve the
+% equation W*x = p.
+% Max number of iterations is 100, convergence tolerance of 1e-6.
+y = lsqr(W, p, 1e-6, 100);
+
+% the output is a vector, so we reshape it into an image
+reconstruction = reshape(y, W.vol_size);
+
+subplot(1,3,1);
+imshow(reconstruction, []);
+title('Reconstruction');
+
+subplot(1,3,2);
+imshow(im, []);
+title('Ground truth');
+
+% The transpose of the operator corresponds to the backprojection.
+backProjection = W'*p;
+subplot(1,3,3);
+imshow(reshape(backProjection, W.vol_size), []);
+title('Backprojection');
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)
generated by cgit v1.2.3 (git 2.25.1) at 2024-11-14 05:19:50 +0000