queso-0.53.0
GaussianLikelihoodScalarCovariance.C
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1 //-----------------------------------------------------------------------bl-
2 //--------------------------------------------------------------------------
3 //
4 // QUESO - a library to support the Quantification of Uncertainty
5 // for Estimation, Simulation and Optimization
6 //
7 // Copyright (C) 2008-2015 The PECOS Development Team
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23 //-----------------------------------------------------------------------el-
24 
25 #include <cmath>
26 
27 #include <queso/GslVector.h>
28 #include <queso/GslMatrix.h>
29 #include <queso/VectorSet.h>
30 #include <queso/GaussianLikelihoodScalarCovariance.h>
31 
32 namespace QUESO {
33 
34 template<class V, class M>
36  const char * prefix, const VectorSet<V, M> & domainSet,
37  const V & observations, double covariance)
38  : BaseGaussianLikelihood<V, M>(prefix, domainSet, observations),
39  m_covariance(covariance)
40 {
41 }
42 
43 template<class V, class M>
45 {
46 }
47 
48 template<class V, class M>
49 double
51  const V * domainDirection, V * gradVector, M * hessianMatrix,
52  V * hessianEffect) const
53 {
54  return std::exp(this->lnValue(domainVector, domainDirection, gradVector,
55  hessianMatrix, hessianEffect));
56 }
57 
58 template<class V, class M>
59 double
61  const V * domainDirection, V * gradVector, M * hessianMatrix,
62  V * hessianEffect) const
63 {
64  V modelOutput(this->m_observations, 0, 0); // At least it's not a copy
65 
66  this->evaluateModel(domainVector, domainDirection, modelOutput, gradVector,
67  hessianMatrix, hessianEffect);
68 
69  modelOutput -= this->m_observations; // Compute misfit
70  double norm2_squared = modelOutput.norm2Sq(); // Compute square of 2-norm
71 
72  return -0.5 * norm2_squared / m_covariance;
73 }
74 
75 } // End namespace QUESO
76 
GaussianLikelihoodScalarCovariance(const char *prefix, const VectorSet< V, M > &domainSet, const V &observations, double covariance)
Default constructor.
A templated class for handling sets.
Definition: VectorSet.h:52
virtual double lnValue(const V &domainVector, const V *domainDirection, V *gradVector, M *hessianMatrix, V *hessianEffect) const
Logarithm of the value of the scalar function.
A class that represents a Gaussian likelihood with scalar covariance.
virtual double actualValue(const V &domainVector, const V *domainDirection, V *gradVector, M *hessianMatrix, V *hessianEffect) const
Actual value of the scalar function.
Base class for canned Gaussian likelihoods.

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