summaryrefslogtreecommitdiffstats
path: root/Wrappers
diff options
context:
space:
mode:
Diffstat (limited to 'Wrappers')
-rw-r--r--Wrappers/Python/ccpi/astra/astra_processors.py60
-rw-r--r--Wrappers/Python/ccpi/framework.py186
-rw-r--r--Wrappers/Python/ccpi/reconstruction/algs.py1
-rw-r--r--Wrappers/Python/ccpi/reconstruction/ops.py10
-rw-r--r--Wrappers/Python/wip/simple_demo.py12
-rwxr-xr-xWrappers/Python/wip/simple_mc_demo.py10
6 files changed, 139 insertions, 140 deletions
diff --git a/Wrappers/Python/ccpi/astra/astra_processors.py b/Wrappers/Python/ccpi/astra/astra_processors.py
index f51aec9..bf6048b 100644
--- a/Wrappers/Python/ccpi/astra/astra_processors.py
+++ b/Wrappers/Python/ccpi/astra/astra_processors.py
@@ -1,17 +1,16 @@
-from ccpi.framework import DataSetProcessor, DataSet, VolumeData, SinogramData
+from ccpi.framework import DataSetProcessor, ImageData, AcquisitionData
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.
+ Forward project ImageData to AcquisitionData using ASTRA proj_id.
- Input: VolumeDataSet
+ Input: ImageData
Parameter: proj_id
- Output: SinogramDataSet
+ Output: AcquisitionData
'''
def __init__(self,
@@ -50,7 +49,7 @@ class AstraForwardProjector(DataSetProcessor):
else:
NotImplemented
- def checkInput(self, dataset):
+ def check_input(self, dataset):
if dataset.number_of_dimensions == 3 or\
dataset.number_of_dimensions == 2:
return True
@@ -68,24 +67,24 @@ class AstraForwardProjector(DataSetProcessor):
self.sinogram_geometry = sinogram_geometry
def process(self):
- IM = self.getInput()
- DATA = SinogramData(geometry=self.sinogram_geometry)
+ IM = self.get_input()
+ DATA = AcquisitionData(geometry=self.sinogram_geometry)
#sinogram_id, DATA = astra.create_sino( IM.as_array(),
# self.proj_id)
sinogram_id, DATA.array = astra.create_sino(IM.as_array(),
self.proj_id)
astra.data2d.delete(sinogram_id)
- #return SinogramData(array=DATA, geometry=self.sinogram_geometry)
+ #return AcquisitionData(array=DATA, geometry=self.sinogram_geometry)
return DATA
class AstraBackProjector(DataSetProcessor):
'''AstraBackProjector
- Back project SinogramDataSet to VolumeDataSet using ASTRA proj_id.
+ Back project AcquisitionData to ImageData using ASTRA proj_id.
- Input: SinogramDataSet
+ Input: AcquisitionData
Parameter: proj_id
- Output: VolumeDataSet
+ Output: ImageData
'''
def __init__(self,
@@ -124,7 +123,7 @@ class AstraBackProjector(DataSetProcessor):
else:
NotImplemented
- def checkInput(self, dataset):
+ def check_input(self, dataset):
if dataset.number_of_dimensions == 3 or dataset.number_of_dimensions == 2:
return True
else:
@@ -141,8 +140,8 @@ class AstraBackProjector(DataSetProcessor):
self.sinogram_geometry = sinogram_geometry
def process(self):
- DATA = self.getInput()
- IM = VolumeData(geometry=self.volume_geometry)
+ DATA = self.get_input()
+ IM = ImageData(geometry=self.volume_geometry)
rec_id, IM.array = astra.create_backprojection(DATA.as_array(),
self.proj_id)
astra.data2d.delete(rec_id)
@@ -151,13 +150,13 @@ class AstraBackProjector(DataSetProcessor):
class AstraForwardProjectorMC(AstraForwardProjector):
'''AstraForwardProjector Multi channel
- Forward project VolumeDataSet to SinogramDataSet using ASTRA proj_id.
+ Forward project ImageData to AcquisitionDataSet using ASTRA proj_id.
- Input: VolumeDataSet
+ Input: ImageDataSet
Parameter: proj_id
- Output: SinogramDataSet
+ Output: AcquisitionData
'''
- def checkInput(self, dataset):
+ def check_input(self, dataset):
if dataset.number_of_dimensions == 2 or \
dataset.number_of_dimensions == 3 or \
dataset.number_of_dimensions == 4:
@@ -166,9 +165,9 @@ class AstraForwardProjectorMC(AstraForwardProjector):
raise ValueError("Expected input dimensions is 2 or 3, got {0}"\
.format(dataset.number_of_dimensions))
def process(self):
- IM = self.getInput()
- #create the output Sinogram
- DATA = SinogramData(geometry=self.sinogram_geometry)
+ IM = self.get_input()
+ #create the output AcquisitionData
+ DATA = AcquisitionData(geometry=self.sinogram_geometry)
for k in range(DATA.geometry.channels):
sinogram_id, DATA.as_array()[k] = astra.create_sino(IM.as_array()[k],
@@ -179,13 +178,13 @@ class AstraForwardProjectorMC(AstraForwardProjector):
class AstraBackProjectorMC(AstraBackProjector):
'''AstraBackProjector Multi channel
- Back project SinogramDataSet to VolumeDataSet using ASTRA proj_id.
+ Back project AcquisitionData to ImageData using ASTRA proj_id.
- Input: SinogramDataSet
+ Input: AcquisitionData
Parameter: proj_id
- Output: VolumeDataSet
+ Output: ImageData
'''
- def checkInput(self, dataset):
+ def check_input(self, dataset):
if dataset.number_of_dimensions == 2 or \
dataset.number_of_dimensions == 3 or \
dataset.number_of_dimensions == 4:
@@ -194,12 +193,13 @@ class AstraBackProjectorMC(AstraBackProjector):
raise ValueError("Expected input dimensions is 2 or 3, got {0}"\
.format(dataset.number_of_dimensions))
def process(self):
- DATA = self.getInput()
+ DATA = self.get_input()
- IM = VolumeData(geometry=self.volume_geometry)
+ IM = ImageData(geometry=self.volume_geometry)
for k in range(IM.geometry.channels):
- rec_id, IM.as_array()[k] = astra.create_backprojection(DATA.as_array()[k],
- self.proj_id)
+ rec_id, IM.as_array()[k] = astra.create_backprojection(
+ DATA.as_array()[k],
+ self.proj_id)
astra.data2d.delete(rec_id)
return IM \ No newline at end of file
diff --git a/Wrappers/Python/ccpi/framework.py b/Wrappers/Python/ccpi/framework.py
index b2f8a7e..3409611 100644
--- a/Wrappers/Python/ccpi/framework.py
+++ b/Wrappers/Python/ccpi/framework.py
@@ -94,7 +94,7 @@ class CCPiBaseClass(ABC):
if self.debug:
print ("{0}: {1}".format(self.__class__.__name__, msg))
-class DataSet(object):
+class DataContainer(object):
'''Generic class to hold data
Data is currently held in a numpy arrays'''
@@ -106,7 +106,7 @@ class DataSet(object):
self.shape = numpy.shape(array)
self.number_of_dimensions = len (self.shape)
self.dimension_labels = {}
- self.geometry = None # Only relevant for SinogramData and VolumeData
+ self.geometry = None # Only relevant for AcquisitionData and ImageData
if dimension_labels is not None and \
len (dimension_labels) == self.number_of_dimensions:
@@ -134,10 +134,10 @@ class DataSet(object):
def as_array(self, dimensions=None):
- '''Returns the DataSet as Numpy Array
+ '''Returns the DataContainer as Numpy Array
Returns the pointer to the array if dimensions is not set.
- If dimensions is set, it first creates a new DataSet with the subset
+ If dimensions is set, it first creates a new DataContainer with the subset
and then it returns the pointer to the array'''
if dimensions is not None:
return self.subset(dimensions).as_array()
@@ -145,7 +145,7 @@ class DataSet(object):
def subset(self, dimensions=None, **kw):
- '''Creates a DataSet containing a subset of self according to the
+ '''Creates a DataContainer containing a subset of self according to the
labels in dimensions'''
if dimensions is None:
return self.array.copy()
@@ -155,7 +155,7 @@ class DataSet(object):
proceed = True
unknown_key = ''
# axis_order contains the order of the axis that the user wants
- # in the output DataSet
+ # in the output DataContainer
axis_order = []
if type(dimensions) == list:
for dl in dimensions:
@@ -221,12 +221,12 @@ class DataSet(object):
numpy.shape(array)))
self.array = array[:]
- def checkDimensions(self, other):
+ def check_dimensions(self, other):
return self.shape == other.shape
def __add__(self, other):
- if issubclass(type(other), DataSet):
- if self.checkDimensions(other):
+ if issubclass(type(other), DataContainer):
+ if self.check_dimensions(other):
out = self.as_array() + other.as_array()
return type(self)(out,
deep_copy=True,
@@ -242,13 +242,13 @@ class DataSet(object):
dimension_labels=self.dimension_labels,
geometry=self.geometry)
else:
- raise TypeError('Cannot {0} DataSet with {1}'.format("add" ,
+ raise TypeError('Cannot {0} DataContainer with {1}'.format("add" ,
type(other)))
# __add__
def __sub__(self, other):
- if issubclass(type(other), DataSet):
- if self.checkDimensions(other):
+ if issubclass(type(other), DataContainer):
+ if self.check_dimensions(other):
out = self.as_array() - other.as_array()
return type(self)(out,
deep_copy=True,
@@ -263,7 +263,7 @@ class DataSet(object):
dimension_labels=self.dimension_labels,
geometry=self.geometry)
else:
- raise TypeError('Cannot {0} DataSet with {1}'.format("subtract" ,
+ raise TypeError('Cannot {0} DataContainer with {1}'.format("subtract" ,
type(other)))
# __sub__
def __truediv__(self,other):
@@ -271,8 +271,8 @@ class DataSet(object):
def __div__(self, other):
print ("calling __div__")
- if issubclass(type(other), DataSet):
- if self.checkDimensions(other):
+ if issubclass(type(other), DataContainer):
+ if self.check_dimensions(other):
out = self.as_array() / other.as_array()
return type(self)(out,
deep_copy=True,
@@ -287,13 +287,13 @@ class DataSet(object):
dimension_labels=self.dimension_labels,
geometry=self.geometry)
else:
- raise TypeError('Cannot {0} DataSet with {1}'.format("divide" ,
+ raise TypeError('Cannot {0} DataContainer with {1}'.format("divide" ,
type(other)))
# __div__
def __pow__(self, other):
- if issubclass(type(other), DataSet):
- if self.checkDimensions(other):
+ if issubclass(type(other), DataContainer):
+ if self.check_dimensions(other):
out = self.as_array() ** other.as_array()
return type(self)(out,
deep_copy=True,
@@ -308,13 +308,13 @@ class DataSet(object):
dimension_labels=self.dimension_labels,
geometry=self.geometry)
else:
- raise TypeError('Cannot {0} DataSet with {1}'.format("power" ,
+ raise TypeError('Cannot {0} DataContainer with {1}'.format("power" ,
type(other)))
# __pow__
def __mul__(self, other):
- if issubclass(type(other), DataSet):
- if self.checkDimensions(other):
+ if issubclass(type(other), DataContainer):
+ if self.check_dimensions(other):
out = self.as_array() * other.as_array()
return type(self)(out,
deep_copy=True,
@@ -329,7 +329,7 @@ class DataSet(object):
dimension_labels=self.dimension_labels,
geometry=self.geometry)
else:
- raise TypeError('Cannot {0} DataSet with {1}'.format("multiply" ,
+ raise TypeError('Cannot {0} DataContainer with {1}'.format("multiply" ,
type(other)))
# __mul__
@@ -386,8 +386,8 @@ class DataSet(object):
return type(self)(fother ** self.array ,
dimension_labels=self.dimension_labels,
geometry=self.geometry)
- elif issubclass(other, DataSet):
- if self.checkDimensions(other):
+ elif issubclass(other, DataContainer):
+ if self.check_dimensions(other):
return type(self)(other.as_array() ** self.array ,
dimension_labels=self.dimension_labels,
geometry=self.geometry)
@@ -437,8 +437,8 @@ class DataSet(object):
-class VolumeData(DataSet):
- '''DataSet for holding 2D or 3D dataset'''
+class ImageData(DataContainer):
+ '''DataContainer for holding 2D or 3D DataContainer'''
def __init__(self,
array = None,
deep_copy=True,
@@ -476,24 +476,24 @@ class VolumeData(DataSet):
'horizontal_x']
array = numpy.zeros( shape , dtype=numpy.float32)
- super(VolumeData, self).__init__(array, deep_copy,
+ super(ImageData, self).__init__(array, deep_copy,
dim_labels, **kwargs)
else:
- raise ValueError('Please pass either a DataSet, ' +\
+ raise ValueError('Please pass either a DataContainer, ' +\
'a numpy array or a geometry')
else:
- if type(array) == DataSet:
- # if the array is a DataSet get the info from there
+ if type(array) == DataContainer:
+ # if the array is a DataContainer get the info from there
if not ( array.number_of_dimensions == 2 or \
array.number_of_dimensions == 3 or \
array.number_of_dimensions == 4):
raise ValueError('Number of dimensions are not 2 or 3 or 4: {0}'\
.format(array.number_of_dimensions))
- #DataSet.__init__(self, array.as_array(), deep_copy,
+ #DataContainer.__init__(self, array.as_array(), deep_copy,
# array.dimension_labels, **kwargs)
- super(VolumeData, self).__init__(array.as_array(), deep_copy,
+ super(ImageData, self).__init__(array.as_array(), deep_copy,
array.dimension_labels, **kwargs)
elif type(array) == numpy.ndarray:
if not ( array.ndim == 2 or array.ndim == 3 or array.ndim == 4 ):
@@ -512,8 +512,8 @@ class VolumeData(DataSet):
dimension_labels = ['horizontal_y' ,
'horizontal_x']
- #DataSet.__init__(self, array, deep_copy, dimension_labels, **kwargs)
- super(VolumeData, self).__init__(array, deep_copy,
+ #DataContainer.__init__(self, array, deep_copy, dimension_labels, **kwargs)
+ super(ImageData, self).__init__(array, deep_copy,
dimension_labels, **kwargs)
# load metadata from kwargs if present
@@ -526,8 +526,8 @@ class VolumeData(DataSet):
self.spacing = value
-class SinogramData(DataSet):
- '''DataSet for holding 2D or 3D sinogram'''
+class AcquisitionData(DataContainer):
+ '''DataContainer for holding 2D or 3D sinogram'''
def __init__(self,
array = None,
deep_copy=True,
@@ -565,21 +565,21 @@ class SinogramData(DataSet):
'horizontal']
array = numpy.zeros( shape , dtype=numpy.float32)
- super(SinogramData, self).__init__(array, deep_copy,
+ super(AcquisitionData, self).__init__(array, deep_copy,
dim_labels, **kwargs)
else:
- if type(array) == DataSet:
- # if the array is a DataSet get the info from there
+ if type(array) == DataContainer:
+ # if the array is a DataContainer get the info from there
if not ( array.number_of_dimensions == 2 or \
array.number_of_dimensions == 3 or \
array.number_of_dimensions == 4):
raise ValueError('Number of dimensions are not 2 or 3 or 4: {0}'\
.format(array.number_of_dimensions))
- #DataSet.__init__(self, array.as_array(), deep_copy,
+ #DataContainer.__init__(self, array.as_array(), deep_copy,
# array.dimension_labels, **kwargs)
- super(SinogramData, self).__init__(array.as_array(), deep_copy,
+ super(AcquisitionData, self).__init__(array.as_array(), deep_copy,
array.dimension_labels, **kwargs)
elif type(array) == numpy.ndarray:
if not ( array.ndim == 2 or array.ndim == 3 or array.ndim == 4 ):
@@ -598,16 +598,16 @@ class SinogramData(DataSet):
dimension_labels = ['angle' ,
'horizontal']
- #DataSet.__init__(self, array, deep_copy, dimension_labels, **kwargs)
- super(SinogramData, self).__init__(array, deep_copy,
+ #DataContainer.__init__(self, array, deep_copy, dimension_labels, **kwargs)
+ super(AcquisitionData, self).__init__(array, deep_copy,
dimension_labels, **kwargs)
class DataSetProcessor(object):
- '''Defines a generic DataSet processor
+ '''Defines a generic DataContainer processor
- accepts DataSet as inputs and
- outputs DataSet
+ accepts DataContainer as inputs and
+ outputs DataContainer
additional attributes can be defined with __setattr__
'''
@@ -624,7 +624,7 @@ class DataSetProcessor(object):
def __setattr__(self, name, value):
if name == 'input':
- self.setInput(value)
+ self.set_input(value)
elif name in self.__dict__.keys():
self.__dict__[name] = value
self.__dict__['mTime'] = datetime.now()
@@ -632,23 +632,23 @@ class DataSetProcessor(object):
raise KeyError('Attribute {0} not found'.format(name))
#pass
- def setInput(self, dataset):
- if issubclass(type(dataset), DataSet):
- if self.checkInput(dataset):
+ def set_input(self, dataset):
+ if issubclass(type(dataset), DataContainer):
+ if self.check_input(dataset):
self.__dict__['input'] = dataset
else:
raise TypeError("Input type mismatch: got {0} expecting {1}"\
- .format(type(dataset), DataSet))
+ .format(type(dataset), DataContainer))
- def checkInput(self, dataset):
- '''Checks parameters of the input DataSet
+ def check_input(self, dataset):
+ '''Checks parameters of the input DataContainer
- Should raise an Error if the DataSet does not match expectation, e.g.
- if the expected input DataSet is 3D and the Processor expects 2D.
+ Should raise an Error if the DataContainer does not match expectation, e.g.
+ if the expected input DataContainer is 3D and the Processor expects 2D.
'''
- raise NotImplementedError('Implement basic checks for input DataSet')
+ raise NotImplementedError('Implement basic checks for input DataContainer')
- def getOutput(self):
+ def get_output(self):
if None in self.__dict__.values():
raise ValueError('Not all parameters have been passed')
shouldRun = False
@@ -665,21 +665,21 @@ class DataSetProcessor(object):
self.runTime = datetime.now()
return self.process()
- def setInputProcessor(self, processor):
+ def set_input_processor(self, processor):
if issubclass(type(processor), DataSetProcessor):
self.__dict__['input'] = processor
else:
raise TypeError("Input type mismatch: got {0} expecting {1}"\
.format(type(processor), DataSetProcessor))
- def getInput(self):
- '''returns the input DataSet
+ def get_input(self):
+ '''returns the input DataContainer
It is useful in the case the user has provided a DataSetProcessor as
input
'''
if issubclass(type(self.input), DataSetProcessor):
- dsi = self.input.getOutput()
+ dsi = self.input.get_output()
else:
dsi = self.input
return dsi
@@ -691,8 +691,8 @@ class DataSetProcessor23D(DataSetProcessor):
'''Regularizers DataSetProcessor
'''
- def checkInput(self, dataset):
- '''Checks number of dimensions input DataSet
+ def check_input(self, dataset):
+ '''Checks number of dimensions input DataContainer
Expected input is 2D or 3D
'''
@@ -714,7 +714,7 @@ class AX(DataSetProcessor):
a is a scalar
- x a DataSet.
+ x a DataContainer.
'''
def __init__(self):
@@ -725,15 +725,15 @@ class AX(DataSetProcessor):
#DataSetProcessor.__init__(self, **kwargs)
super(AX, self).__init__(**kwargs)
- def checkInput(self, dataset):
+ def check_input(self, dataset):
return True
def process(self):
- dsi = self.getInput()
+ dsi = self.get_input()
a = self.scalar
- y = DataSet( a * dsi.as_array() , True,
+ y = DataContainer( a * dsi.as_array() , True,
dimension_labels=dsi.dimension_labels )
#self.setParameter(output_dataset=y)
return y
@@ -744,7 +744,7 @@ class AX(DataSetProcessor):
class PixelByPixelDataSetProcessor(DataSetProcessor):
'''Example DataSetProcessor
- This processor applies a python function to each pixel of the DataSet
+ This processor applies a python function to each pixel of the DataContainer
f is a python function
@@ -758,18 +758,18 @@ class PixelByPixelDataSetProcessor(DataSetProcessor):
#DataSetProcessor.__init__(self, **kwargs)
super(PixelByPixelDataSetProcessor, self).__init__(**kwargs)
- def checkInput(self, dataset):
+ def check_input(self, dataset):
return True
def process(self):
pyfunc = self.pyfunc
- dsi = self.getInput()
+ dsi = self.get_input()
eval_func = numpy.frompyfunc(pyfunc,1,1)
- y = DataSet( eval_func( dsi.as_array() ) , True,
+ y = DataContainer( eval_func( dsi.as_array() ) , True,
dimension_labels=dsi.dimension_labels )
return y
@@ -786,7 +786,7 @@ if __name__ == '__main__':
print("a refcount " , sys.getrefcount(a))
a = numpy.reshape(a, shape)
print("a refcount " , sys.getrefcount(a))
- ds = DataSet(a, False, ['X', 'Y','Z' ,'W'])
+ ds = DataContainer(a, False, ['X', 'Y','Z' ,'W'])
print("a refcount " , sys.getrefcount(a))
print ("ds label {0}".format(ds.dimension_labels))
subset = ['W' ,'X']
@@ -797,34 +797,34 @@ if __name__ == '__main__':
c = ds.subset(['Z','W','X'])
print("a refcount " , sys.getrefcount(a))
- # Create a VolumeData sharing the array with c
- volume0 = VolumeData(c.as_array(), False, dimensions = c.dimension_labels)
- volume1 = VolumeData(c, False)
+ # Create a ImageData sharing the array with c
+ volume0 = ImageData(c.as_array(), False, dimensions = c.dimension_labels)
+ volume1 = ImageData(c, False)
print ("volume0 {0} volume1 {1}".format(id(volume0.array),
id(volume1.array)))
- # Create a VolumeData copying the array from c
- volume2 = VolumeData(c.as_array(), dimensions = c.dimension_labels)
- volume3 = VolumeData(c)
+ # Create a ImageData copying the array from c
+ volume2 = ImageData(c.as_array(), dimensions = c.dimension_labels)
+ volume3 = ImageData(c)
print ("volume2 {0} volume3 {1}".format(id(volume2.array),
id(volume3.array)))
# single number DataSet
- sn = DataSet(numpy.asarray([1]))
+ sn = DataContainer(numpy.asarray([1]))
ax = AX()
ax.scalar = 2
- ax.setInput(c)
+ ax.set_input(c)
#ax.apply()
print ("ax in {0} out {1}".format(c.as_array().flatten(),
- ax.getOutput().as_array().flatten()))
+ ax.get_output().as_array().flatten()))
axm = AX()
axm.scalar = 0.5
- axm.setInput(c)
+ axm.set_input(c)
#axm.apply()
- print ("axm in {0} out {1}".format(c.as_array(), axm.getOutput().as_array()))
+ print ("axm in {0} out {1}".format(c.as_array(), axm.get_output().as_array()))
# create a PixelByPixelDataSetProcessor
@@ -832,20 +832,20 @@ if __name__ == '__main__':
pyfunc = lambda x: -x if x > 20 else x
clip = PixelByPixelDataSetProcessor()
clip.pyfunc = pyfunc
- clip.setInput(c)
+ clip.set_input(c)
#clip.apply()
- print ("clip in {0} out {1}".format(c.as_array(), clip.getOutput().as_array()))
+ print ("clip in {0} out {1}".format(c.as_array(), clip.get_output().as_array()))
#dsp = DataSetProcessor()
- #dsp.setInput(ds)
+ #dsp.set_input(ds)
#dsp.input = a
# pipeline
chain = AX()
chain.scalar = 0.5
- chain.setInputProcessor(ax)
- print ("chain in {0} out {1}".format(ax.getOutput().as_array(), chain.getOutput().as_array()))
+ chain.set_input_processor(ax)
+ print ("chain in {0} out {1}".format(ax.get_output().as_array(), chain.get_output().as_array()))
# testing arithmetic operations
@@ -875,14 +875,14 @@ if __name__ == '__main__':
s = [i for i in range(3 * 4 * 4)]
s = numpy.reshape(numpy.asarray(s), (3,4,4))
- sino = SinogramData( s )
+ sino = AcquisitionData( s )
shape = (4,3,2)
a = [i for i in range(2*3*4)]
a = numpy.asarray(a)
a = numpy.reshape(a, shape)
print (numpy.shape(a))
- ds = DataSet(a, True, ['X', 'Y','Z'])
+ ds = DataContainer(a, True, ['X', 'Y','Z'])
# this means that I expect the X to be of length 2 ,
# y of length 3 and z of length 4
subset = ['Y' ,'Z']
@@ -896,13 +896,13 @@ if __name__ == '__main__':
print ("shape b 2,3? {0}".format(numpy.shape(b1.as_array())))
- # create VolumeData from geometry
+ # create ImageData from geometry
vgeometry = geoms.VolumeGeometry(voxel_num_x=2, voxel_num_y=3, channels=2)
- vol = VolumeData(geometry=vgeometry)
+ vol = ImageData(geometry=vgeometry)
sgeometry = geoms.SinogramGeometry(dimension=2, angles=numpy.linspace(0, 180, num=20),
geom_type='parallel', pixel_num_v=3,
pixel_num_h=5 , channels=2)
- sino = SinogramData(geometry=sgeometry)
+ sino = AcquisitionData(geometry=sgeometry)
sino2 = sino.clone()
\ No newline at end of file
diff --git a/Wrappers/Python/ccpi/reconstruction/algs.py b/Wrappers/Python/ccpi/reconstruction/algs.py
index 088b36e..ec52fee 100644
--- a/Wrappers/Python/ccpi/reconstruction/algs.py
+++ b/Wrappers/Python/ccpi/reconstruction/algs.py
@@ -21,7 +21,6 @@ import numpy
import time
from ccpi.reconstruction.funcs import BaseFunction
-from ccpi.framework import SinogramData, VolumeData
def FISTA(x_init, f=None, g=None, opt=None):
diff --git a/Wrappers/Python/ccpi/reconstruction/ops.py b/Wrappers/Python/ccpi/reconstruction/ops.py
index c21ff06..d6f31eb 100644
--- a/Wrappers/Python/ccpi/reconstruction/ops.py
+++ b/Wrappers/Python/ccpi/reconstruction/ops.py
@@ -19,10 +19,10 @@
import numpy
from scipy.sparse.linalg import svds
-from ccpi.framework import DataSet, VolumeData, SinogramData, DataSetProcessor
+from ccpi.framework import DataContainer
# Maybe operators need to know what types they take as inputs/outputs
-# to not just use generic DataSet
+# to not just use generic DataContainer
class Operator(object):
@@ -60,10 +60,10 @@ class LinearOperatorMatrix(Operator):
super(LinearOperatorMatrix, self).__init__()
def direct(self,x):
- return DataSet(numpy.dot(self.A,x.as_array()))
+ return DataContainer(numpy.dot(self.A,x.as_array()))
def adjoint(self,x):
- return DataSet(numpy.dot(self.A.transpose(),x.as_array()))
+ return DataContainer(numpy.dot(self.A.transpose(),x.as_array()))
def size(self):
return self.A.shape
@@ -130,7 +130,7 @@ class FiniteDiff2D(Operator):
def PowerMethodNonsquare(op,numiters):
# Initialise random
inputsize = op.size()[1]
- x0 = DataSet(numpy.random.randn(inputsize[0],inputsize[1]))
+ x0 = DataContainer(numpy.random.randn(inputsize[0],inputsize[1]))
s = numpy.zeros(numiters)
# Loop
for it in numpy.arange(numiters):
diff --git a/Wrappers/Python/wip/simple_demo.py b/Wrappers/Python/wip/simple_demo.py
index 766e448..99109a6 100644
--- a/Wrappers/Python/wip/simple_demo.py
+++ b/Wrappers/Python/wip/simple_demo.py
@@ -1,10 +1,10 @@
#import sys
#sys.path.append("..")
-from ccpi.framework import VolumeData
-from ccpi.reconstruction.algs import *
+from ccpi.framework import ImageData
+from ccpi.reconstruction.algs import FISTA, FBPD, CGLS
from ccpi.reconstruction.funcs import Norm2sq, Norm1
-from ccpi.reconstruction.astra_ops import AstraProjectorSimple
+from ccpi.astra.astra_ops import AstraProjectorSimple
from ccpi.reconstruction.geoms import VolumeGeometry, SinogramGeometry
import numpy as np
@@ -16,7 +16,7 @@ test_case = 1 # 1=parallel2D, 2=cone2D
N = 128
vg = VolumeGeometry(voxel_num_x=N,voxel_num_y=N)
-Phantom = VolumeData(geometry=vg)
+Phantom = ImageData(geometry=vg)
x = Phantom.as_array()
x[round(N/4):round(3*N/4),round(N/4):round(3*N/4)] = 1.0
@@ -77,7 +77,7 @@ plt.show()
f = Norm2sq(Aop,b,c=0.5)
# Initial guess
-x_init = VolumeData(np.zeros(x.shape),geometry=vg)
+x_init = ImageData(np.zeros(x.shape),geometry=vg)
# Run FISTA for least squares without regularization
x_fista0, it0, timing0, criter0 = FISTA(x_init, f, None)
@@ -131,7 +131,7 @@ current = 1
fig = plt.figure()
# projections row
a=fig.add_subplot(rows,cols,current)
-a.set_title('phantom {0}'.format(numpy.shape(Phantom.as_array())))
+a.set_title('phantom {0}'.format(np.shape(Phantom.as_array())))
imgplot = plt.imshow(Phantom.as_array())
current = current + 1
diff --git a/Wrappers/Python/wip/simple_mc_demo.py b/Wrappers/Python/wip/simple_mc_demo.py
index 0d976d7..0bd48dd 100755
--- a/Wrappers/Python/wip/simple_mc_demo.py
+++ b/Wrappers/Python/wip/simple_mc_demo.py
@@ -1,10 +1,10 @@
#import sys
#sys.path.append("..")
-from ccpi.framework import VolumeData, SinogramData
+from ccpi.framework import ImageData, AcquisitionData
from ccpi.reconstruction.algs import FISTA
from ccpi.reconstruction.funcs import Norm2sq, Norm1
-from ccpi.reconstruction.astra_ops import AstraProjectorMC
+from ccpi.astra.astra_ops import AstraProjectorMC
from ccpi.reconstruction.geoms import VolumeGeometry, SinogramGeometry
import numpy
@@ -18,7 +18,7 @@ M = 100
numchannels = 3
vg = VolumeGeometry(voxel_num_x=N,voxel_num_y=N,channels=numchannels)
-Phantom = VolumeData(geometry=vg)
+Phantom = ImageData(geometry=vg)
x = Phantom.as_array()
x[0 , round(N/4):round(3*N/4) , round(N/4):round(3*N/4) ] = 1.0
@@ -49,7 +49,7 @@ plt.show()
#vg = VolumeGeometry(N,N,None, 1,1,None,channels=numchannels)
-#Phantom = VolumeData(x,geometry=vg)
+#Phantom = ImageData(x,geometry=vg)
# Set up measurement geometry
angles_num = 20; # angles number
@@ -107,7 +107,7 @@ plt.show()
f = Norm2sq(Aop,b,c=0.5)
# Initial guess
-x_init = VolumeData(numpy.zeros(x.shape),geometry=vg)
+x_init = ImageData(numpy.zeros(x.shape),geometry=vg)
# FISTA options
opt = {'tol': 1e-4, 'iter': 200}
generated by cgit v1.2.3 (git 2.25.1) at 2024-12-02 18:52:04 +0000