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# -*- coding: utf-8 -*-
# CCP in Tomographic Imaging (CCPi) Core Imaging Library (CIL).
# Copyright 2017 UKRI-STFC
# Copyright 2017 University of Manchester
# 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.
from ccpi.optimisation.functions import Function
from ccpi.optimisation.functions import ScaledFunction
class FunctionOperatorComposition(Function):
''' Function composition with Operator, i.e., f(Ax)
A: operator
f: function
'''
def __init__(self, function, operator):
super(FunctionOperatorComposition, self).__init__()
self.function = function
self.operator = operator
self.L = function.L * operator.norm()**2
def __call__(self, x):
''' Evaluate FunctionOperatorComposition at x
returns f(Ax)
'''
return self.function(self.operator.direct(x))
def gradient(self, x, out=None):
#
''' Gradient takes into account the Operator'''
if out is None:
return self.operator.adjoint(self.function.gradient(self.operator.direct(x)))
else:
tmp = self.operator.range_geometry().allocate()
self.operator.direct(x, out=tmp)
self.function.gradient(tmp, out=tmp)
self.operator.adjoint(tmp, out=out)
if __name__ == '__main__':
from ccpi.framework import ImageGeometry, AcquisitionGeometry
from ccpi.optimisation.operators import Gradient
from ccpi.optimisation.functions import L2NormSquared
from ccpi.astra.ops import AstraProjectorSimple
import numpy as np
M, N= 50, 50
ig = ImageGeometry(voxel_num_x=M, voxel_num_y = N)
detectors = N
angles_num = N
det_w = 1.0
angles = np.linspace(0, np.pi, angles_num, endpoint=False)
ag = AcquisitionGeometry('parallel',
'2D',
angles,
detectors,det_w)
Aop = AstraProjectorSimple(ig, ag, 'cpu')
u = ig.allocate('random_int', seed=15)
u1 = ig.allocate('random_int', seed=10)
b = Aop.direct(u1)
# G = Gradient(ig)
alpha = 0.5
f1 = alpha * L2NormSquared(b=b)
f_comp = FunctionOperatorComposition(f1, Aop)
print(f_comp(u))
z1 = Aop.direct(u)
tmp = 0.5 * ((z1 - b)**2).sum()
print(tmp)
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