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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 __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from ccpi.framework import ImageData
from ccpi.optimisation.operators import LinearOperator
class ZeroOperator(LinearOperator):
r'''ZeroOperator: O: X -> Y, maps any element of :math:`x\in X` into the zero element :math:`\in Y, O(x) = O_{Y}`
:param gm_domain: domain of the operator
:param gm_range: range of the operator, default: same as domain
Note:
.. math::
O^{*}: Y^{*} -> X^{*} \text{(Adjoint)}
< O(x), y > = < x, O^{*}(y) >
'''
def __init__(self, domain_geometry, range_geometry=None):
if range_geometry is None:
range_geometry = domain_geometry.clone()
super(ZeroOperator, self).__init__(domain_geometry=domain_geometry,
range_geometry=range_geometry)
def direct(self,x,out=None):
'''Returns O(x)'''
if out is None:
return self.range_geometry().allocate()
else:
out.fill(self.range_geometry.allocate())
def adjoint(self,x, out=None):
'''Returns O^{*}(y)'''
if out is None:
return self.domain_geometry().allocate()
else:
out.fill(self.domain_geometry().allocate())
def calculate_norm(self, **kwargs):
'''Evaluates operator norm of ZeroOperator'''
return 0
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