summaryrefslogtreecommitdiffstats
path: root/samples
diff options
context:
space:
mode:
Diffstat (limited to 'samples')
-rw-r--r--samples/python/s018_experimental_multires.py84
-rw-r--r--samples/python/s018_plugin.py132
2 files changed, 216 insertions, 0 deletions
diff --git a/samples/python/s018_experimental_multires.py b/samples/python/s018_experimental_multires.py
new file mode 100644
index 0000000..cf38e53
--- /dev/null
+++ b/samples/python/s018_experimental_multires.py
@@ -0,0 +1,84 @@
+#-----------------------------------------------------------------------
+#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
+from astra.experimental import do_composite_FP
+
+astra.log.setOutputScreen(astra.log.STDERR, astra.log.DEBUG)
+
+# low res part (voxels of 4x4x4)
+vol_geom1 = astra.create_vol_geom(32, 16, 32, -64, 0, -64, 64, -64, 64)
+
+# high res part (voxels of 1x1x1)
+vol_geom2 = astra.create_vol_geom(128, 64, 128, 0, 64, -64, 64, -64, 64)
+
+
+# Split the output in two parts as well, for demonstration purposes
+angles1 = np.linspace(0, np.pi/2, 90, False)
+angles2 = np.linspace(np.pi/2, np.pi, 90, False)
+proj_geom1 = astra.create_proj_geom('parallel3d', 1.0, 1.0, 128, 192, angles1)
+proj_geom2 = astra.create_proj_geom('parallel3d', 1.0, 1.0, 128, 192, angles2)
+
+# Create a simple hollow cube phantom
+cube1 = np.zeros((32,32,16))
+cube1[4:28,4:28,4:16] = 1
+
+cube2 = np.zeros((128,128,64))
+cube2[16:112,16:112,0:112] = 1
+cube2[33:97,33:97,4:28] = 0
+
+vol1 = astra.data3d.create('-vol', vol_geom1, cube1)
+vol2 = astra.data3d.create('-vol', vol_geom2, cube2)
+
+proj1 = astra.data3d.create('-proj3d', proj_geom1, 0)
+proj2 = astra.data3d.create('-proj3d', proj_geom2, 0)
+
+# The actual geometries don't matter for this composite FP/BP case
+projector = astra.create_projector('cuda3d', proj_geom1, vol_geom1)
+
+do_composite_FP(projector, [vol1, vol2], [proj1, proj2])
+
+proj_data1 = astra.data3d.get(proj1)
+proj_data2 = astra.data3d.get(proj2)
+
+# Display a single projection image
+import pylab
+pylab.gray()
+pylab.figure(1)
+pylab.imshow(proj_data1[:,0,:])
+pylab.figure(2)
+pylab.imshow(proj_data2[:,0,:])
+pylab.show()
+
+
+# Clean up. Note that GPU memory is tied up in the algorithm object,
+# and main RAM in the data objects.
+astra.data3d.delete(vol1)
+astra.data3d.delete(vol2)
+astra.data3d.delete(proj1)
+astra.data3d.delete(proj2)
+astra.projector3d.delete(projector)
diff --git a/samples/python/s018_plugin.py b/samples/python/s018_plugin.py
new file mode 100644
index 0000000..31cca95
--- /dev/null
+++ b/samples/python/s018_plugin.py
@@ -0,0 +1,132 @@
+#-----------------------------------------------------------------------
+#Copyright 2015 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 six
+
+# Define the plugin class (has to subclass astra.plugin.base)
+# Note that usually, these will be defined in a separate package/module
+class SIRTPlugin(astra.plugin.base):
+ """Example of an ASTRA plugin class, implementing a simple 2D SIRT algorithm.
+
+ Options:
+
+ 'rel_factor': relaxation factor (optional)
+ """
+
+ # The astra_name variable defines the name to use to
+ # call the plugin from ASTRA
+ astra_name = "SIRT-PLUGIN"
+
+ def initialize(self,cfg, rel_factor = 1):
+ self.W = astra.OpTomo(cfg['ProjectorId'])
+ self.vid = cfg['ReconstructionDataId']
+ self.sid = cfg['ProjectionDataId']
+ self.rel = rel_factor
+
+ def run(self, its):
+ v = astra.data2d.get_shared(self.vid)
+ s = astra.data2d.get_shared(self.sid)
+ W = self.W
+ for i in range(its):
+ v[:] += self.rel*(W.T*(s - (W*v).reshape(s.shape))).reshape(v.shape)/s.size
+
+if __name__=='__main__':
+
+ 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])
+
+ # Register the plugin with ASTRA
+ # First we import the package that contains the plugin
+ import s018_plugin
+ # Then, we register the plugin class with ASTRA
+ astra.plugin.register(s018_plugin.SIRTPlugin)
+
+ # Get a list of registered plugins
+ six.print_(astra.plugin.get_registered())
+
+ # To get help on a registered plugin, use get_help
+ six.print_(astra.plugin.get_help('SIRT-PLUGIN'))
+
+ # Create data structures
+ sid = astra.data2d.create('-sino', proj_geom, sinogram)
+ vid = astra.data2d.create('-vol', vol_geom)
+
+ # Create config using plugin name
+ cfg = astra.astra_dict('SIRT-PLUGIN')
+ cfg['ProjectorId'] = proj_id
+ cfg['ProjectionDataId'] = sid
+ cfg['ReconstructionDataId'] = vid
+
+ # Create algorithm object
+ alg_id = astra.algorithm.create(cfg)
+
+ # Run algorithm for 100 iterations
+ astra.algorithm.run(alg_id, 100)
+
+ # Get reconstruction
+ rec = astra.data2d.get(vid)
+
+ # Options for the plugin go in cfg['option']
+ cfg = astra.astra_dict('SIRT-PLUGIN')
+ cfg['ProjectorId'] = proj_id
+ cfg['ProjectionDataId'] = sid
+ cfg['ReconstructionDataId'] = vid
+ cfg['option'] = {}
+ cfg['option']['rel_factor'] = 1.5
+ alg_id_rel = astra.algorithm.create(cfg)
+ astra.algorithm.run(alg_id_rel, 100)
+ rec_rel = astra.data2d.get(vid)
+
+ # We can also use OpTomo to call the plugin
+ rec_op = W.reconstruct('SIRT-PLUGIN', sinogram, 100, extraOptions={'rel_factor':1.5})
+
+ import pylab as pl
+ pl.gray()
+ pl.figure(1)
+ pl.imshow(rec,vmin=0,vmax=1)
+ pl.figure(2)
+ pl.imshow(rec_rel,vmin=0,vmax=1)
+ pl.figure(3)
+ pl.imshow(rec_op,vmin=0,vmax=1)
+ pl.show()
+
+ # Clean up.
+ astra.projector.delete(proj_id)
+ astra.algorithm.delete([alg_id, alg_id_rel])
+ astra.data2d.delete([vid, sid])