def process(self, cmd):
if cmd == 401:
astraMPI.create(None,None)
elif cmd == 402:
astraMPI._runInternal(None, None)
else:
print("Not implemented astraMPI command")
proj_geom['Vectors'][:, 3:5] = proj_geom[
'Vectors'][:, 3:5] + postAlignment * proj_geom['Vectors'][:, 6:8]
print proj_geom
vx = detectorColCount
vy = detectorColCount
vz = detectorRowCount
print('Object has size %d x %d x %d\n' % (vx, vy, vz))
vol_geom = astra.create_vol_geom(vx, vy, vz)
#Setup the MPI domain distribution
proj_geom, vol_geom = mpi.create(proj_geom,
vol_geom,
nGhostcellsVolume=0,
nGhostcellsProjection=19)
print proj_geom
proj_id = astra.data3d.create('-proj3d', proj_geom, P)
# 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 = astra.astra_dict('CGLS3D_CUDA')
cfg['ReconstructionDataId'] = rec_id
cfg['ProjectionDataId'] = proj_id
# Create the algorithm object from the configuration structure
#astra.log.setOutputFile("sirt3d.txt", astra.log.DEBUG)
X = 128
vol_geom = astra.create_vol_geom(X, X, X)
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((X, X, X))
cube[17:113, 17:113, 17:113] = 1
cube[33:97, 33:97, 33:97] = 0
# Modify the geometry to support distributed execution and then proceed as before
proj_geom, vol_geom = mpi.create(proj_geom, vol_geom)
# Create projection data from this volume
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, :])
rec_id = astra.data3d.create('-vol', vol_geom)
#Execute the plugin-based reconstruction
# Register the plugin with ASTRA
Y = 192
X = 160
vol_geom = astra.create_vol_geom(Y, X, Z)
angles = np.linspace(0, np.pi, 180, False)
#proj_geom = astra.create_proj_geom('parallel3d', 1.0, 1.0, 128, 192, angles)
proj_geom = astra.create_proj_geom('cone', 1.0, 1.0, X, Y + 64, angles, 1000,
0)
# Create a simple hollow cube phantom
cube = np.zeros((Z, Y, X))
cube[17:Z - 15, 17:Y - 15, 17:X - 15] = 1
cube[33:97, 33:Y - 31, 33:X - 31] = 0
#Setup the MPI domain distribution
mpi.create(proj_geom, vol_geom, nGhostcellsVolume=1, nGhostcellsProjection=0)
# Create projection data from this
proj_id, proj_data = astra.create_sino3d_gpu(cube, proj_geom, vol_geom)
# 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 = astra.astra_dict('CGLS3D_CUDA')
cfg['ReconstructionDataId'] = rec_id
cfg['ProjectionDataId'] = proj_id
# Create the algorithm object from the configuration structure
alg_id = astra.algorithm.create(cfg)
vol_geom = astra.create_vol_geom(Y, X, Z)
angles = np.linspace(0, np.pi, 180, False)
#proj_geom = astra.create_proj_geom('parallel3d', 1.0, 1.0, 128, 192, angles)
proj_geom = astra.create_proj_geom('cone', 1.0, 1.0, X, Y + 64, angles,
1000, 0)
# Create a simple hollow cube phantom
cube = np.zeros((Z, Y, X))
cube[17:Z - 15, 17:Y - 15, 17:X - 15] = 1
cube[33:97, 33:Y - 31, 33:X - 31] = 0
#Setup the MPI domain distribution
GPUList = [0, 1]
proj_geom, vol_geom = mpi.create(proj_geom,
vol_geom,
nGhostcellsVolume=1,
nGhostcellsProjection=0,
GPUList=GPUList)
# Create projection data from this
proj_id, proj_data = astra.create_sino3d_gpu(cube, proj_geom, vol_geom)
# Create a data object for the reconstruction
rec_id = astra.data3d.create('-vol', vol_geom)
# Register the plugin with ASTRA
astra.plugin.register(segment_plugin.SegmentationPlugin)
six.print_(astra.plugin.get_help('SIMPLE-SEGMENT-PLUGIN'))
# Set up the parameters for a reconstruction algorithm using the GPU
cfg = astra.astra_dict('SIMPLE-SEGMENT-PLUGIN')
cfg['ReconstructionDataId'] = rec_id