Source code for cil.optimisation.operators.ZeroOperator

#  Copyright 2019 United Kingdom Research and Innovation
#  Copyright 2019 The University of Manchester
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import numpy as np
from cil.framework import ImageData
from cil.optimisation.operators import LinearOperator

[docs] 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)
[docs] def direct(self,x,out=None): '''Returns O(x)''' if out is None: return self.range_geometry().allocate(value=0) else: out.fill(self.range_geometry().allocate(value=0)) return out
[docs] def adjoint(self,x, out=None): '''Returns O^{*}(y)''' if out is None: return self.domain_geometry().allocate(value=0) else: out.fill(self.domain_geometry().allocate(value=0)) return out
[docs] def calculate_norm(self, **kwargs): '''Evaluates operator norm of ZeroOperator''' return 0