summaryrefslogtreecommitdiffstats
path: root/Wrappers/Python
diff options
context:
space:
mode:
Diffstat (limited to 'Wrappers/Python')
-rw-r--r--Wrappers/Python/ccpi/framework.py25
-rw-r--r--[-rwxr-xr-x]Wrappers/Python/ccpi/optimisation/algorithms/FBPD.py172
-rw-r--r--[-rwxr-xr-x]Wrappers/Python/ccpi/optimisation/algorithms/__init__.py58
-rwxr-xr-xWrappers/Python/test/test_DataContainer.py43
4 files changed, 176 insertions, 122 deletions
diff --git a/Wrappers/Python/ccpi/framework.py b/Wrappers/Python/ccpi/framework.py
index 0c23628..71a9f3f 100644
--- a/Wrappers/Python/ccpi/framework.py
+++ b/Wrappers/Python/ccpi/framework.py
@@ -111,8 +111,12 @@ class ImageGeometry(object):
repres += "voxel_size : x{0},y{1},z{2}\n".format(self.voxel_size_x, self.voxel_size_y, self.voxel_size_z)
repres += "center : x{0},y{1},z{2}\n".format(self.center_x, self.center_y, self.center_z)
return repres
-
-
+ def allocate(self, value=0, dimension_labels=None):
+ '''allocates an ImageData according to the size expressed in the instance'''
+ out = ImageData(geometry=self, dimension_labels=dimension_labels)
+ if value != 0:
+ out += value
+ return out
class AcquisitionGeometry(object):
def __init__(self,
@@ -192,9 +196,12 @@ class AcquisitionGeometry(object):
repres += "distance center-detector: {0}\n".format(self.dist_source_center)
repres += "number of channels: {0}\n".format(self.channels)
return repres
-
-
-
+ def allocate(self, value=0, dimension_labels=None):
+ '''allocates an AcquisitionData according to the size expressed in the instance'''
+ out = AcquisitionData(geometry=self, dimension_labels=dimension_labels)
+ if value != 0:
+ out += value
+ return out
class DataContainer(object):
'''Generic class to hold data
@@ -741,6 +748,7 @@ class DataContainer(object):
return numpy.sqrt(self.squared_norm())
+
class ImageData(DataContainer):
'''DataContainer for holding 2D or 3D DataContainer'''
def __init__(self,
@@ -903,8 +911,11 @@ class AcquisitionData(DataContainer):
elif dim == 'horizontal':
shape.append(horiz)
if len(shape) != len(dimension_labels):
- raise ValueError('Missing {0} axes'.format(
- len(dimension_labels) - len(shape)))
+ raise ValueError('Missing {0} axes.\nExpected{1} got {2}}'\
+ .format(
+ len(dimension_labels) - len(shape),
+ dimension_labels, shape)
+ )
shape = tuple(shape)
array = numpy.zeros( shape , dtype=numpy.float32)
diff --git a/Wrappers/Python/ccpi/optimisation/algorithms/FBPD.py b/Wrappers/Python/ccpi/optimisation/algorithms/FBPD.py
index 322e9eb..798fb61 100755..100644
--- a/Wrappers/Python/ccpi/optimisation/algorithms/FBPD.py
+++ b/Wrappers/Python/ccpi/optimisation/algorithms/FBPD.py
@@ -1,86 +1,86 @@
-# -*- coding: utf-8 -*-
-# This work is part of the Core Imaging Library developed by
-# Visual Analytics and Imaging System Group of the Science Technology
-# Facilities Council, STFC
-
-# Copyright 2019 Edoardo Pasca
-
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-# http://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""
-Created on Thu Feb 21 11:09:03 2019
-
-@author: ofn77899
-"""
-
-from ccpi.optimisation.algorithms import Algorithm
-from ccpi.optimisation.funcs import ZeroFun
-
-class FBPD(Algorithm):
- '''FBPD Algorithm
-
- Parameters:
- x_init: initial guess
- f: constraint
- g: data fidelity
- h: regularizer
- opt: additional algorithm
- '''
- constraint = None
- data_fidelity = None
- regulariser = None
- def __init__(self, **kwargs):
- pass
- def set_up(self, x_init, operator=None, constraint=None, data_fidelity=None,\
- regulariser=None, opt=None):
-
- # default inputs
- if constraint is None:
- self.constraint = ZeroFun()
- else:
- self.constraint = constraint
- if data_fidelity is None:
- data_fidelity = ZeroFun()
- else:
- self.data_fidelity = data_fidelity
- if regulariser is None:
- self.regulariser = ZeroFun()
- else:
- self.regulariser = regulariser
-
- # algorithmic parameters
-
-
- # step-sizes
- self.tau = 2 / (self.data_fidelity.L + 2)
- self.sigma = (1/self.tau - self.data_fidelity.L/2) / self.regulariser.L
-
- self.inv_sigma = 1/self.sigma
-
- # initialization
- self.x = x_init
- self.y = operator.direct(self.x)
-
-
- def update(self):
-
- # primal forward-backward step
- x_old = self.x
- self.x = self.x - self.tau * ( self.data_fidelity.grad(self.x) + self.operator.adjoint(self.y) )
- self.x = self.constraint.prox(self.x, self.tau);
-
- # dual forward-backward step
- self.y = self.y + self.sigma * self.operator.direct(2*self.x - x_old);
- self.y = self.y - self.sigma * self.regulariser.prox(self.inv_sigma*self.y, self.inv_sigma);
-
- # time and criterion
- self.loss = self.constraint(self.x) + self.data_fidelity(self.x) + self.regulariser(self.operator.direct(self.x))
+# -*- coding: utf-8 -*-
+# This work is part of the Core Imaging Library developed by
+# Visual Analytics and Imaging System Group of the Science Technology
+# Facilities Council, STFC
+
+# Copyright 2019 Edoardo Pasca
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+# http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Created on Thu Feb 21 11:09:03 2019
+
+@author: ofn77899
+"""
+
+from ccpi.optimisation.algorithms import Algorithm
+from ccpi.optimisation.funcs import ZeroFun
+
+class FBPD(Algorithm):
+ '''FBPD Algorithm
+
+ Parameters:
+ x_init: initial guess
+ f: constraint
+ g: data fidelity
+ h: regularizer
+ opt: additional algorithm
+ '''
+ constraint = None
+ data_fidelity = None
+ regulariser = None
+ def __init__(self, **kwargs):
+ pass
+ def set_up(self, x_init, operator=None, constraint=None, data_fidelity=None,\
+ regulariser=None, opt=None):
+
+ # default inputs
+ if constraint is None:
+ self.constraint = ZeroFun()
+ else:
+ self.constraint = constraint
+ if data_fidelity is None:
+ data_fidelity = ZeroFun()
+ else:
+ self.data_fidelity = data_fidelity
+ if regulariser is None:
+ self.regulariser = ZeroFun()
+ else:
+ self.regulariser = regulariser
+
+ # algorithmic parameters
+
+
+ # step-sizes
+ self.tau = 2 / (self.data_fidelity.L + 2)
+ self.sigma = (1/self.tau - self.data_fidelity.L/2) / self.regulariser.L
+
+ self.inv_sigma = 1/self.sigma
+
+ # initialization
+ self.x = x_init
+ self.y = operator.direct(self.x)
+
+
+ def update(self):
+
+ # primal forward-backward step
+ x_old = self.x
+ self.x = self.x - self.tau * ( self.data_fidelity.grad(self.x) + self.operator.adjoint(self.y) )
+ self.x = self.constraint.prox(self.x, self.tau);
+
+ # dual forward-backward step
+ self.y = self.y + self.sigma * self.operator.direct(2*self.x - x_old);
+ self.y = self.y - self.sigma * self.regulariser.prox(self.inv_sigma*self.y, self.inv_sigma);
+
+ # time and criterion
+ self.loss = self.constraint(self.x) + self.data_fidelity(self.x) + self.regulariser(self.operator.direct(self.x))
diff --git a/Wrappers/Python/ccpi/optimisation/algorithms/__init__.py b/Wrappers/Python/ccpi/optimisation/algorithms/__init__.py
index 52fe6d7..903bc30 100755..100644
--- a/Wrappers/Python/ccpi/optimisation/algorithms/__init__.py
+++ b/Wrappers/Python/ccpi/optimisation/algorithms/__init__.py
@@ -1,29 +1,29 @@
-# -*- coding: utf-8 -*-
-# This work is part of the Core Imaging Library developed by
-# Visual Analytics and Imaging System Group of the Science Technology
-# Facilities Council, STFC
-
-# Copyright 2019 Edoardo Pasca
-
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-# http://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""
-Created on Thu Feb 21 11:03:13 2019
-
-@author: ofn77899
-"""
-
-from .Algorithm import Algorithm
-from .CGLS import CGLS
-from .GradientDescent import GradientDescent
-from .FISTA import FISTA
-from .FBPD import FBPD \ No newline at end of file
+# -*- coding: utf-8 -*-
+# This work is part of the Core Imaging Library developed by
+# Visual Analytics and Imaging System Group of the Science Technology
+# Facilities Council, STFC
+
+# Copyright 2019 Edoardo Pasca
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+# http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Created on Thu Feb 21 11:03:13 2019
+
+@author: ofn77899
+"""
+
+from .Algorithm import Algorithm
+from .CGLS import CGLS
+from .GradientDescent import GradientDescent
+from .FISTA import FISTA
+from .FBPD import FBPD
diff --git a/Wrappers/Python/test/test_DataContainer.py b/Wrappers/Python/test/test_DataContainer.py
index 05f3fe8..3def054 100755
--- a/Wrappers/Python/test/test_DataContainer.py
+++ b/Wrappers/Python/test/test_DataContainer.py
@@ -457,6 +457,49 @@ class TestDataContainer(unittest.TestCase):
pixel_num_h=5, channels=2)
sino = AcquisitionData(geometry=sgeometry)
self.assertEqual(sino.shape, (2, 10, 3, 5))
+ def test_ImageGeometry_allocate(self):
+ vgeometry = ImageGeometry(voxel_num_x=4, voxel_num_y=3, channels=2)
+ image = vgeometry.allocate()
+ self.assertEqual(0,image.as_array()[0][0][0])
+ image = vgeometry.allocate(1)
+ self.assertEqual(1,image.as_array()[0][0][0])
+ default_order = ['channel' , 'horizontal_y' , 'horizontal_x']
+ self.assertEqual(default_order[0], image.dimension_labels[0])
+ self.assertEqual(default_order[1], image.dimension_labels[1])
+ self.assertEqual(default_order[2], image.dimension_labels[2])
+ order = [ 'horizontal_x' , 'horizontal_y', 'channel' ]
+ image = vgeometry.allocate(0,dimension_labels=order)
+ self.assertEqual(order[0], image.dimension_labels[0])
+ self.assertEqual(order[1], image.dimension_labels[1])
+ self.assertEqual(order[2], image.dimension_labels[2])
+ def test_AcquisitionGeometry_allocate(self):
+ ageometry = AcquisitionGeometry(dimension=2, angles=numpy.linspace(0, 180, num=10),
+ geom_type='parallel', pixel_num_v=3,
+ pixel_num_h=5, channels=2)
+ sino = ageometry.allocate()
+ shape = sino.shape
+ print ("shape", shape)
+ self.assertEqual(0,sino.as_array()[0][0][0][0])
+ self.assertEqual(0,sino.as_array()[shape[0]-1][shape[1]-1][shape[2]-1][shape[3]-1])
+
+ sino = ageometry.allocate(1)
+ self.assertEqual(1,sino.as_array()[0][0][0][0])
+ self.assertEqual(1,sino.as_array()[shape[0]-1][shape[1]-1][shape[2]-1][shape[3]-1])
+ print (sino.dimension_labels, sino.shape, ageometry)
+
+ default_order = ['channel' , ' angle' ,
+ 'vertical' , 'horizontal']
+ self.assertEqual(default_order[0], sino.dimension_labels[0])
+ self.assertEqual(default_order[1], sino.dimension_labels[1])
+ self.assertEqual(default_order[2], sino.dimension_labels[2])
+ self.assertEqual(default_order[3], sino.dimension_labels[3])
+ order = ['vertical' , 'horizontal', 'channel' , 'angle' ]
+ sino = ageometry.allocate(0,dimension_labels=order)
+ print (sino.dimension_labels, sino.shape, ageometry)
+ self.assertEqual(order[0], sino.dimension_labels[0])
+ self.assertEqual(order[1], sino.dimension_labels[1])
+ self.assertEqual(order[2], sino.dimension_labels[2])
+ self.assertEqual(order[2], sino.dimension_labels[2])
def assertNumpyArrayEqual(self, first, second):
res = True