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-rw-r--r--Wrappers/Python/ccpi/astra/astra_processors.py273
-rw-r--r--Wrappers/Python/ccpi/astra/astra_utils.py61
-rw-r--r--Wrappers/Python/ccpi/framework.py30
-rw-r--r--Wrappers/Python/ccpi/reconstruction/astra_ops.py161
-rw-r--r--Wrappers/Python/ccpi/reconstruction/geoms.py45
-rw-r--r--Wrappers/Python/test/simple_mc_demo.py134
6 files changed, 582 insertions, 122 deletions
diff --git a/Wrappers/Python/ccpi/astra/astra_processors.py b/Wrappers/Python/ccpi/astra/astra_processors.py
new file mode 100644
index 0000000..650e11b
--- /dev/null
+++ b/Wrappers/Python/ccpi/astra/astra_processors.py
@@ -0,0 +1,273 @@
+from ccpi.framework import DataSetProcessor, DataSet, VolumeData, SinogramData
+from ccpi.astra.astra_utils import convert_geometry_to_astra
+import astra
+import numpy
+
+
+class AstraForwardProjector(DataSetProcessor):
+ '''AstraForwardProjector
+
+ Forward project VolumeDataSet to SinogramDataSet using ASTRA proj_id.
+
+ Input: VolumeDataSet
+ Parameter: proj_id
+ Output: SinogramDataSet
+ '''
+
+ def __init__(self,
+ volume_geometry=None,
+ sinogram_geometry=None,
+ proj_id=None,
+ device='cpu'):
+ kwargs = {
+ 'volume_geometry' : volume_geometry,
+ 'sinogram_geometry' : sinogram_geometry,
+ 'proj_id' : proj_id,
+ 'device' : device
+ }
+
+ #DataSetProcessor.__init__(self, **kwargs)
+ super(AstraForwardProjector, self).__init__(**kwargs)
+
+ self.setVolumeGeometry(volume_geometry)
+ self.setSinogramGeometry(sinogram_geometry)
+
+ # Set up ASTRA Volume and projection geometry, not to be stored in self
+ vol_geom, proj_geom = convert_geometry_to_astra(self.volume_geometry,
+ self.sinogram_geometry)
+
+ # ASTRA projector, to be stored
+ if device == 'cpu':
+ # Note that 'line' is only for parallel (2D) and only one option
+ self.setProjector(astra.create_projector('line', proj_geom, vol_geom) )
+ elif device == 'gpu':
+ self.setProjector(astra.create_projector('cuda', proj_geom, vol_geom) )
+ else:
+ NotImplemented
+
+ def checkInput(self, dataset):
+ if dataset.number_of_dimensions == 3 or dataset.number_of_dimensions == 2:
+ return True
+ else:
+ raise ValueError("Expected input dimensions is 2 or 3, got {0}"\
+ .format(dataset.number_of_dimensions))
+
+ def setProjector(self, proj_id):
+ self.proj_id = proj_id
+
+ def setVolumeGeometry(self, volume_geometry):
+ self.volume_geometry = volume_geometry
+
+ def setSinogramGeometry(self, sinogram_geometry):
+ self.sinogram_geometry = sinogram_geometry
+
+ def process(self):
+ IM = self.getInput()
+ sinogram_id, DATA = astra.create_sino(IM.as_array(), self.proj_id)
+ astra.data2d.delete(sinogram_id)
+ return SinogramData(DATA,geometry=self.sinogram_geometry)
+
+class AstraBackProjector(DataSetProcessor):
+ '''AstraBackProjector
+
+ Back project SinogramDataSet to VolumeDataSet using ASTRA proj_id.
+
+ Input: SinogramDataSet
+ Parameter: proj_id
+ Output: VolumeDataSet
+ '''
+
+ def __init__(self,
+ volume_geometry=None,
+ sinogram_geometry=None,
+ proj_id=None,
+ device='cpu'):
+ kwargs = {
+ 'volume_geometry' : volume_geometry,
+ 'sinogram_geometry' : sinogram_geometry,
+ 'proj_id' : proj_id,
+ 'device' : device
+ }
+
+ #DataSetProcessor.__init__(self, **kwargs)
+ super(AstraBackProjector, self).__init__(**kwargs)
+
+ self.setVolumeGeometry(volume_geometry)
+ self.setSinogramGeometry(sinogram_geometry)
+
+ # Set up ASTRA Volume and projection geometry, not to be stored in self
+ vol_geom, proj_geom = convert_geometry_to_astra(self.volume_geometry,
+ self.sinogram_geometry)
+
+ # ASTRA projector, to be stored
+ if device == 'cpu':
+ # Note that 'line' is only for parallel (2D) and only one option
+ self.setProjector(astra.create_projector('line', proj_geom, vol_geom) )
+ elif device == 'gpu':
+ self.setProjector(astra.create_projector('cuda', proj_geom, vol_geom) )
+ else:
+ NotImplemented
+
+ def checkInput(self, dataset):
+ if dataset.number_of_dimensions == 3 or dataset.number_of_dimensions == 2:
+ return True
+ else:
+ raise ValueError("Expected input dimensions is 2 or 3, got {0}"\
+ .format(dataset.number_of_dimensions))
+
+ def setProjector(self, proj_id):
+ self.proj_id = proj_id
+
+ def setVolumeGeometry(self, volume_geometry):
+ self.volume_geometry = volume_geometry
+
+ def setSinogramGeometry(self, sinogram_geometry):
+ self.sinogram_geometry = sinogram_geometry
+
+ def process(self):
+ DATA = self.getInput()
+ rec_id, IM = astra.create_backprojection(DATA.as_array(), self.proj_id)
+ astra.data2d.delete(rec_id)
+ return VolumeData(IM,geometry=self.volume_geometry)
+
+class AstraForwardProjectorMC(DataSetProcessor):
+ '''AstraForwardProjector
+
+ Forward project VolumeDataSet to SinogramDataSet using ASTRA proj_id.
+
+ Input: VolumeDataSet
+ Parameter: proj_id
+ Output: SinogramDataSet
+ '''
+
+ def __init__(self,
+ volume_geometry=None,
+ sinogram_geometry=None,
+ proj_id=None,
+ device='cpu'):
+ kwargs = {
+ 'volume_geometry' : volume_geometry,
+ 'sinogram_geometry' : sinogram_geometry,
+ 'proj_id' : proj_id,
+ 'device' : device
+ }
+
+ #DataSetProcessor.__init__(self, **kwargs)
+ super(AstraForwardProjectorMC, self).__init__(**kwargs)
+
+ self.setVolumeGeometry(volume_geometry)
+ self.setSinogramGeometry(sinogram_geometry)
+
+ # Set up ASTRA Volume and projection geometry, not to be stored in self
+ vol_geom, proj_geom = convert_geometry_to_astra(self.volume_geometry,
+ self.sinogram_geometry)
+
+ # ASTRA projector, to be stored
+ if device == 'cpu':
+ # Note that 'line' is only for parallel (2D) and only one option
+ self.setProjector(astra.create_projector('line', proj_geom, vol_geom) )
+ elif device == 'gpu':
+ self.setProjector(astra.create_projector('cuda', proj_geom, vol_geom) )
+ else:
+ NotImplemented
+
+ def checkInput(self, dataset):
+ if dataset.number_of_dimensions == 3 or dataset.number_of_dimensions == 2:
+ return True
+ else:
+ return True
+ #raise ValueError("Expected input dimensions is 2 or 3, got {0}"\
+ # .format(dataset.number_of_dimensions))
+
+ def setProjector(self, proj_id):
+ self.proj_id = proj_id
+
+ def setVolumeGeometry(self, volume_geometry):
+ self.volume_geometry = volume_geometry
+
+ def setSinogramGeometry(self, sinogram_geometry):
+ self.sinogram_geometry = sinogram_geometry
+
+ def process(self):
+ IM = self.getInput()
+ DATA = numpy.zeros((self.sinogram_geometry.angles.size,
+ self.sinogram_geometry.pixel_num_h,
+ 1,
+ self.sinogram_geometry.channels),
+ 'float32')
+ for k in range(self.sinogram_geometry.channels):
+ sinogram_id, DATA[:,:,0,k] = astra.create_sino(IM.as_array()[:,:,0,k],
+ self.proj_id)
+ astra.data2d.delete(sinogram_id)
+ return SinogramData(DATA,geometry=self.sinogram_geometry)
+
+class AstraBackProjectorMC(DataSetProcessor):
+ '''AstraBackProjector
+
+ Back project SinogramDataSet to VolumeDataSet using ASTRA proj_id.
+
+ Input: SinogramDataSet
+ Parameter: proj_id
+ Output: VolumeDataSet
+ '''
+
+ def __init__(self,
+ volume_geometry=None,
+ sinogram_geometry=None,
+ proj_id=None,
+ device='cpu'):
+ kwargs = {
+ 'volume_geometry' : volume_geometry,
+ 'sinogram_geometry' : sinogram_geometry,
+ 'proj_id' : proj_id,
+ 'device' : device
+ }
+
+ #DataSetProcessor.__init__(self, **kwargs)
+ super(AstraBackProjectorMC, self).__init__(**kwargs)
+
+ self.setVolumeGeometry(volume_geometry)
+ self.setSinogramGeometry(sinogram_geometry)
+
+ # Set up ASTRA Volume and projection geometry, not to be stored in self
+ vol_geom, proj_geom = convert_geometry_to_astra(self.volume_geometry,
+ self.sinogram_geometry)
+
+ # ASTRA projector, to be stored
+ if device == 'cpu':
+ # Note that 'line' is only for parallel (2D) and only one option
+ self.setProjector(astra.create_projector('line', proj_geom, vol_geom) )
+ elif device == 'gpu':
+ self.setProjector(astra.create_projector('cuda', proj_geom, vol_geom) )
+ else:
+ NotImplemented
+
+ def checkInput(self, dataset):
+ if dataset.number_of_dimensions == 3 or dataset.number_of_dimensions == 2:
+ return True
+ else:
+ return True
+ #raise ValueError("Expected input dimensions is 2 or 3, got {0}"\
+ # .format(dataset.number_of_dimensions))
+
+ def setProjector(self, proj_id):
+ self.proj_id = proj_id
+
+ def setVolumeGeometry(self, volume_geometry):
+ self.volume_geometry = volume_geometry
+
+ def setSinogramGeometry(self, sinogram_geometry):
+ self.sinogram_geometry = sinogram_geometry
+
+ def process(self):
+ DATA = self.getInput()
+ IM = numpy.zeros((self.volume_geometry.voxel_num_x,
+ self.volume_geometry.voxel_num_y,
+ 1,
+ self.volume_geometry.channels),
+ 'float32')
+ for k in range(self.volume_geometry.channels):
+ rec_id, IM[:,:,0,k] = astra.create_backprojection(DATA.as_array()[:,:,0,k],
+ self.proj_id)
+ astra.data2d.delete(rec_id)
+ return VolumeData(IM,geometry=self.volume_geometry) \ No newline at end of file
diff --git a/Wrappers/Python/ccpi/astra/astra_utils.py b/Wrappers/Python/ccpi/astra/astra_utils.py
new file mode 100644
index 0000000..8b5043a
--- /dev/null
+++ b/Wrappers/Python/ccpi/astra/astra_utils.py
@@ -0,0 +1,61 @@
+import astra
+
+def convert_geometry_to_astra(volume_geometry, sinogram_geometry):
+ # Set up ASTRA Volume and projection geometry, not stored
+ if sinogram_geometry.dimension == '2D':
+ vol_geom = astra.create_vol_geom(volume_geometry.voxel_num_x,
+ volume_geometry.voxel_num_y,
+ volume_geometry.getMinX(),
+ volume_geometry.getMaxX(),
+ volume_geometry.getMinY(),
+ volume_geometry.getMaxY())
+
+ if sinogram_geometry.geom_type == 'parallel':
+ proj_geom = astra.create_proj_geom('parallel',
+ sinogram_geometry.pixel_size_h,
+ sinogram_geometry.pixel_num_h,
+ sinogram_geometry.angles)
+ elif sinogram_geometry.geom_type == 'cone':
+ proj_geom = astra.create_proj_geom('fanflat',
+ sinogram_geometry.pixel_size_h,
+ sinogram_geometry.pixel_num_h,
+ sinogram_geometry.angles,
+ sinogram_geometry.dist_source_center,
+ sinogram_geometry.dist_center_detector)
+ else:
+ NotImplemented
+
+ elif sinogram_geometry.dimension == '3D':
+ vol_geom = astra.create_vol_geom(volume_geometry.voxel_num_x,
+ volume_geometry.voxel_num_y,
+ volume_geometry.voxel_num_z,
+ volume_geometry.getMinX(),
+ volume_geometry.getMaxX(),
+ volume_geometry.getMinY(),
+ volume_geometry.getMaxY(),
+ volume_geometry.getMinZ(),
+ volume_geometry.getMaxZ())
+
+ if sinogram_geometry.proj_geom == 'parallel':
+ proj_geom = astra.create_proj_geom('parallel3d',
+ sinogram_geometry.pixel_size_h,
+ sinogram_geometry.pixel_size_v,
+ sinogram_geometry.pixel_num_v,
+ sinogram_geometry.pixel_num_h,
+ sinogram_geometry.angles)
+ elif sinogram_geometry.geom_type == 'cone':
+ proj_geom = astra.create_proj_geom('cone',
+ sinogram_geometry.pixel_size_h,
+ sinogram_geometry.pixel_size_v,
+ sinogram_geometry.pixel_num_v,
+ sinogram_geometry.pixel_num_h,
+ sinogram_geometry.angles,
+ sinogram_geometry.dist_source_center,
+ sinogram_geometry.dist_center_detector)
+ else:
+ NotImplemented
+
+ else:
+ NotImplemented
+
+ return vol_geom, proj_geom \ No newline at end of file
diff --git a/Wrappers/Python/ccpi/framework.py b/Wrappers/Python/ccpi/framework.py
index 754e0ee..82ad65c 100644
--- a/Wrappers/Python/ccpi/framework.py
+++ b/Wrappers/Python/ccpi/framework.py
@@ -437,20 +437,20 @@ class VolumeData(DataSet):
if type(array) == DataSet:
# if the array is a DataSet get the info from there
- if not ( array.number_of_dimensions == 2 or \
- array.number_of_dimensions == 3 ):
- raise ValueError('Number of dimensions are not 2 or 3: {0}'\
- .format(array.number_of_dimensions))
+ #if not ( array.number_of_dimensions == 2 or \
+ # array.number_of_dimensions == 3 ):
+ # raise ValueError('Number of dimensions are not 2 or 3: {0}'\
+ # .format(array.number_of_dimensions))
#DataSet.__init__(self, array.as_array(), deep_copy,
# array.dimension_labels, **kwargs)
super(VolumeData, self).__init__(array.as_array(), deep_copy,
array.dimension_labels, **kwargs)
elif type(array) == numpy.ndarray:
- if not ( array.ndim == 3 or array.ndim == 2 ):
- raise ValueError(
- 'Number of dimensions are not 3 or 2 : {0}'\
- .format(array.ndim))
+ #if not ( array.ndim == 3 or array.ndim == 2 ):
+ # raise ValueError(
+ # 'Number of dimensions are not 3 or 2 : {0}'\
+ # .format(array.ndim))
if dimension_labels is None:
if array.ndim == 3:
@@ -485,17 +485,17 @@ class SinogramData(DataSet):
if type(array) == DataSet:
# if the array is a DataSet get the info from there
- if not ( array.number_of_dimensions == 2 or \
- array.number_of_dimensions == 3 ):
- raise ValueError('Number of dimensions are not 2 or 3: {0}'\
- .format(array.number_of_dimensions))
+ #if not ( array.number_of_dimensions == 2 or \
+ # array.number_of_dimensions == 3 ):
+ # raise ValueError('Number of dimensions are not 2 or 3: {0}'\
+ # .format(array.number_of_dimensions))
DataSet.__init__(self, array.as_array(), deep_copy,
array.dimension_labels, **kwargs)
elif type(array) == numpy.ndarray:
- if not ( array.ndim == 3 or array.ndim == 2 ):
- raise ValueError('Number of dimensions are != 3: {0}'\
- .format(array.ndim))
+ #if not ( array.ndim == 3 or array.ndim == 2 ):
+ # raise ValueError('Number of dimensions are != 3: {0}'\
+ # .format(array.ndim))
if dimension_labels is None:
if array.ndim == 3:
dimension_labels = ['angle' ,
diff --git a/Wrappers/Python/ccpi/reconstruction/astra_ops.py b/Wrappers/Python/ccpi/reconstruction/astra_ops.py
index 452c86a..1346f22 100644
--- a/Wrappers/Python/ccpi/reconstruction/astra_ops.py
+++ b/Wrappers/Python/ccpi/reconstruction/astra_ops.py
@@ -16,118 +16,105 @@
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from ccpi.reconstruction.ops import Operator
-import astra
import numpy
from ccpi.framework import SinogramData, VolumeData
from ccpi.reconstruction.ops import PowerMethodNonsquare
+from ccpi.astra.astra_processors import *
class AstraProjectorSimple(Operator):
"""ASTRA projector modified to use DataSet and geometry."""
def __init__(self, geomv, geomp, device):
super(AstraProjectorSimple, self).__init__()
- # Store our volume and sinogram geometries. Redundant with also
- # storing in ASTRA format below but needed to assign to
- # SinogramData in "direct" method and VolumeData in "adjoint" method
+ # Store volume and sinogram geometries.
self.sinogram_geometry = geomp
self.volume_geometry = geomv
- # ASTRA Volume geometry
- if geomp.dimension == '2D':
- self.vol_geom = astra.create_vol_geom(geomv.voxel_num_x,
- geomv.voxel_num_y,
- geomv.getMinX(),
- geomv.getMaxX(),
- geomv.getMinY(),
- geomv.getMaxY())
- elif geomp.dimension == '3D':
- self.vol_geom = astra.create_vol_geom(geomv.voxel_num_x,
- geomv.voxel_num_y,
- geomv.voxel_num_z,
- geomv.getMinX(),
- geomv.getMaxX(),
- geomv.getMinY(),
- geomv.getMaxY(),
- geomv.getMinZ(),
- geomv.getMaxZ())
- else:
- NotImplemented
-
-
- # ASTRA Projections geometry
- if geomp.dimension == '2D':
- if geomp.geom_type == 'parallel':
- self.proj_geom = astra.create_proj_geom('parallel',
- geomp.pixel_size_h,
- geomp.pixel_num_h,
- geomp.angles)
- elif geomp.geom_type == 'cone':
- self.proj_geom = astra.create_proj_geom('fanflat',
- geomp.pixel_size_h,
- geomp.pixel_num_h,
- geomp.angles,
- geomp.dist_source_center,
- geomp.dist_center_detector)
- else:
- NotImplemented
- elif geomp.dimension == '3D':
- if geomp.proj_geom == 'parallel':
- self.proj_geom = astra.create_proj_geom('parallel3d',
- geomp.pixel_size_h,
- geomp.pixel_size_v,
- geomp.pixel_num_v,
- geomp.pixel_num_h,
- geomp.angles)
- elif geomp.geom_type == 'cone':
- self.proj_geom = astra.create_proj_geom('cone',
- geomp.pixel_size_h,
- geomp.pixel_size_v,
- geomp.pixel_num_v,
- geomp.pixel_num_h,
- geomp.angles,
- geomp.dist_source_center,
- geomp.dist_center_detector)
- else:
- NotImplemented
- else:
- NotImplemented
-
- # ASTRA projector
- if device == 'cpu':
- # Note that 'line' is only for parallel (2D) and only one option
- self.proj_id = astra.create_projector('line', self.proj_geom,
- self.vol_geom) # for CPU
- elif device == 'gpu':
- self.proj_id = astra.create_projector('cuda', self.proj_geom,
- self.vol_geom) # for GPU
- else:
- NotImplemented
+ self.fp = AstraForwardProjector(volume_geometry=geomv,
+ sinogram_geometry=geomp,
+ proj_id=None,
+ device=device)
+ self.bp = AstraBackProjector(volume_geometry=geomv,
+ sinogram_geometry=geomp,
+ proj_id=None,
+ device=device)
+
+ # Initialise empty for singular value.
self.s1 = None
def direct(self, IM):
-
- sinogram_id, DATA = astra.create_sino(IM.as_array(), self.proj_id)
- astra.data2d.delete(sinogram_id)
- return SinogramData(DATA,geometry=self.sinogram_geometry)
+ self.fp.setInput(IM)
+ out = self.fp.getOutput()
+ return out
def adjoint(self, DATA):
- rec_id, IM = astra.create_backprojection(DATA.as_array(), self.proj_id)
- astra.data2d.delete(rec_id)
- return VolumeData(IM,geometry=self.volume_geometry)
+ self.bp.setInput(DATA)
+ out = self.bp.getOutput()
+ return out
- def delete(self):
- astra.data2d.delete(self.proj_id)
+ #def delete(self):
+ # astra.data2d.delete(self.proj_id)
def get_max_sing_val(self):
self.s1, sall, svec = PowerMethodNonsquare(self,10)
return self.s1
def size(self):
- return ( (self.proj_geom['ProjectionAngles'].size, \
- self.proj_geom['DetectorCount']), \
- (self.vol_geom['GridColCount'], \
- self.vol_geom['GridRowCount']) )
+ # Only implemented for 2D
+ return ( (self.sinogram_geometry.angles.size, \
+ self.sinogram_geometry.pixel_num_h), \
+ (self.volume_geometry.voxel_num_x, \
+ self.volume_geometry.voxel_num_y) )
+
+class AstraProjectorMC(Operator):
+ """ASTRA Multichannel projector"""
+ def __init__(self, geomv, geomp, device):
+ super(AstraProjectorMC, self).__init__()
+
+ # Store volume and sinogram geometries.
+ self.sinogram_geometry = geomp
+ self.volume_geometry = geomv
+
+ self.fp = AstraForwardProjectorMC(volume_geometry=geomv,
+ sinogram_geometry=geomp,
+ proj_id=None,
+ device=device)
+
+ self.bp = AstraBackProjectorMC(volume_geometry=geomv,
+ sinogram_geometry=geomp,
+ proj_id=None,
+ device=device)
+
+ # Initialise empty for singular value.
+ self.s1 = 50
+
+ def direct(self, IM):
+ self.fp.setInput(IM)
+ out = self.fp.getOutput()
+ return out
+
+ def adjoint(self, DATA):
+ self.bp.setInput(DATA)
+ out = self.bp.getOutput()
+ return out
+
+ #def delete(self):
+ # astra.data2d.delete(self.proj_id)
+
+ def get_max_sing_val(self):
+ if self.s1 is None:
+ self.s1, sall, svec = PowerMethodNonsquare(self,10)
+ return self.s1
+ else:
+ return self.s1
+
+ def size(self):
+ # Only implemented for 2D
+ return ( (self.sinogram_geometry.angles.size, \
+ self.sinogram_geometry.pixel_num_h), \
+ (self.volume_geometry.voxel_num_x, \
+ self.volume_geometry.voxel_num_y) )
class AstraProjector(Operator):
diff --git a/Wrappers/Python/ccpi/reconstruction/geoms.py b/Wrappers/Python/ccpi/reconstruction/geoms.py
index edce3b3..9f81fa0 100644
--- a/Wrappers/Python/ccpi/reconstruction/geoms.py
+++ b/Wrappers/Python/ccpi/reconstruction/geoms.py
@@ -1,16 +1,17 @@
class VolumeGeometry:
- def __init__(self, \
- voxel_num_x=None, \
- voxel_num_y=None, \
- voxel_num_z=None, \
- voxel_size_x=None, \
- voxel_size_y=None, \
- voxel_size_z=None, \
- center_x=0, \
- center_y=0, \
- center_z=0):
+ def __init__(self,
+ voxel_num_x=None,
+ voxel_num_y=None,
+ voxel_num_z=None,
+ voxel_size_x=None,
+ voxel_size_y=None,
+ voxel_size_z=None,
+ center_x=0,
+ center_y=0,
+ center_z=0,
+ channels=1):
self.voxel_num_x = voxel_num_x
self.voxel_num_y = voxel_num_y
@@ -21,6 +22,7 @@ class VolumeGeometry:
self.center_x = center_x
self.center_y = center_y
self.center_z = center_z
+ self.channels = channels
def getMinX(self):
return self.center_x - 0.5*self.voxel_num_x*self.voxel_size_x
@@ -43,16 +45,17 @@ class VolumeGeometry:
class SinogramGeometry:
- def __init__(self, \
- geom_type, \
- dimension, \
- angles, \
- pixel_num_h=None, \
- pixel_size_h=1, \
- pixel_num_v=None, \
- pixel_size_v=1, \
- dist_source_center=None, \
- dist_center_detector=None, \
+ def __init__(self,
+ geom_type,
+ dimension,
+ angles,
+ pixel_num_h=None,
+ pixel_size_h=1,
+ pixel_num_v=None,
+ pixel_size_v=1,
+ dist_source_center=None,
+ dist_center_detector=None,
+ channels=1
):
"""
General inputs for standard type projection geometries
@@ -91,6 +94,8 @@ class SinogramGeometry:
self.pixel_size_h = pixel_size_h
self.pixel_num_v = pixel_num_v
self.pixel_size_v = pixel_size_v
+
+ self.channels = channels
diff --git a/Wrappers/Python/test/simple_mc_demo.py b/Wrappers/Python/test/simple_mc_demo.py
new file mode 100644
index 0000000..a6959f9
--- /dev/null
+++ b/Wrappers/Python/test/simple_mc_demo.py
@@ -0,0 +1,134 @@
+
+
+import sys
+
+sys.path.append("..")
+
+from ccpi.framework import *
+from ccpi.reconstruction.algs import *
+from ccpi.reconstruction.funcs import *
+from ccpi.reconstruction.ops import *
+from ccpi.reconstruction.astra_ops import *
+from ccpi.reconstruction.geoms import *
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+test_case = 2 # 1=parallel2D, 2=cone2D
+
+# Set up phantom
+N = 128
+
+numchannels = 3
+
+x = np.zeros((N,N,1,numchannels))
+
+x[round(N/4):round(3*N/4),round(N/4):round(3*N/4),:,0] = 1.0
+x[round(N/8):round(7*N/8),round(3*N/8):round(5*N/8),:,0] = 2.0
+
+x[round(N/4):round(3*N/4),round(N/4):round(3*N/4),:,1] = 0.7
+x[round(N/8):round(7*N/8),round(3*N/8):round(5*N/8),:,1] = 1.2
+
+x[round(N/4):round(3*N/4),round(N/4):round(3*N/4),:,2] = 1.5
+x[round(N/8):round(7*N/8),round(3*N/8):round(5*N/8),:,2] = 2.2
+
+f, axarr = plt.subplots(1,numchannels)
+for k in numpy.arange(3):
+ axarr[k].imshow(x[:,:,0,k],vmin=0,vmax=2.5)
+plt.show()
+
+vg = VolumeGeometry(N,N,None, 1,1,None,channels=numchannels)
+
+
+Phantom = VolumeData(x,geometry=vg)
+
+# Set up measurement geometry
+angles_num = 20; # angles number
+
+if test_case==1:
+ angles = np.linspace(0,np.pi,angles_num,endpoint=False)
+elif test_case==2:
+ angles = np.linspace(0,2*np.pi,angles_num,endpoint=False)
+else:
+ NotImplemented
+
+det_w = 1.0
+det_num = N
+SourceOrig = 200
+OrigDetec = 0
+
+# Parallelbeam geometry test
+if test_case==1:
+ pg = SinogramGeometry('parallel',
+ '2D',
+ angles,
+ det_num,
+ det_w,
+ channels=numchannels)
+elif test_case==2:
+ pg = SinogramGeometry('cone',
+ '2D',
+ angles,
+ det_num,
+ det_w,
+ dist_source_center=SourceOrig,
+ dist_center_detector=OrigDetec,
+ channels=numchannels)
+
+# ASTRA operator using volume and sinogram geometries
+Aop = AstraProjectorMC(vg, pg, 'gpu')
+
+
+# Try forward and backprojection
+b = Aop.direct(Phantom)
+
+fb, axarrb = plt.subplots(1,numchannels)
+for k in numpy.arange(3):
+ axarrb[k].imshow(b.as_array()[:,:,0,k],vmin=0,vmax=250)
+plt.show()
+
+out2 = Aop.adjoint(b)
+
+fo, axarro = plt.subplots(1,numchannels)
+for k in range(3):
+ axarro[k].imshow(out2.as_array()[:,:,0,k],vmin=0,vmax=3500)
+plt.show()
+
+# Create least squares object instance with projector and data.
+f = Norm2sq(Aop,b,c=0.5)
+
+# Initial guess
+x_init = VolumeData(np.zeros(x.shape),geometry=vg)
+
+# FISTA options
+opt = {'tol': 1e-4, 'iter': 200}
+
+# Run FISTA for least squares without regularization
+x_fista0, it0, timing0, criter0 = FISTA(x_init, f, None, opt)
+
+
+ff0, axarrf0 = plt.subplots(1,numchannels)
+for k in numpy.arange(3):
+ axarrf0[k].imshow(x_fista0.as_array()[:,:,0,k],vmin=0,vmax=2.5)
+plt.show()
+
+plt.semilogy(criter0)
+plt.title('Criterion vs iterations, least squares')
+plt.show()
+
+# Now least squares plus 1-norm regularization
+lam = 0.1
+g0 = Norm1(lam)
+
+
+# Run FISTA for least squares plus 1-norm function.
+x_fista1, it1, timing1, criter1 = FISTA(x_init, f, g0, opt)
+
+ff1, axarrf1 = plt.subplots(1,numchannels)
+for k in numpy.arange(3):
+ axarrf1[k].imshow(x_fista1.as_array()[:,:,0,k],vmin=0,vmax=2.5)
+plt.show()
+
+plt.semilogy(criter1)
+plt.title('Criterion vs iterations, least squares plus 1-norm regu')
+plt.show() \ No newline at end of file