Source code for cil.optimisation.operators.IdentityOperator

#  Copyright 2019 United Kingdom Research and Innovation
#  Copyright 2019 The University of Manchester
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#      http://www.apache.org/licenses/LICENSE-2.0
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from cil.optimisation.operators import LinearOperator
import scipy.sparse as sp
import numpy as np


[docs] class IdentityOperator(LinearOperator): '''IdentityOperator: Id: X -> Y, Id(x) = x\in Y X : gm_domain Y : gm_range ( Default: Y = X ) ''' def __init__(self, domain_geometry, range_geometry=None): if range_geometry is None: range_geometry = domain_geometry super(IdentityOperator, self).__init__(domain_geometry=domain_geometry, range_geometry=range_geometry)
[docs] def direct(self,x,out=None): '''Returns Id(x)''' if out is None: return x.copy() else: out.fill(x) return out
[docs] def adjoint(self,x, out=None): '''Returns Id(x)''' if out is None: return x.copy() else: out.fill(x) return out
[docs] def calculate_norm(self, **kwargs): '''Evaluates operator norm of IdentityOperator''' return 1.0
########################################################################### ############### For preconditioning ###################################### ########################################################################### def matrix(self): return sp.eye(np.prod(self.gm_domain.shape)) def sum_abs_row(self): return self.gm_range.allocate(1) def sum_abs_col(self): return self.gm_domain.allocate(1)
[docs] def is_orthogonal(self): '''Returns if the operator is orthogonal Returns ------- `Bool` ''' return True