void compute(const QUESO::FullEnvironment& env, unsigned int numModes) {
////////////////////////////////////////////////////////
// Step 1 of 5: Instantiate the parameter space
////////////////////////////////////////////////////////
#ifdef APPLS_MODAL_USES_CONCATENATION
QUESO::VectorSpace<QUESO::GslVector, QUESO::GslMatrix>
paramSpaceA(env, "paramA_", 2, NULL);
QUESO::VectorSpace<QUESO::GslVector, QUESO::GslMatrix>
paramSpaceB(env, "paramB_", 1, NULL);
#endif
QUESO::VectorSpace<QUESO::GslVector, QUESO::GslMatrix>
paramSpace(env, "param_", 3, NULL);
////////////////////////////////////////////////////////
// Step 2 of 5: Instantiate the parameter domain
////////////////////////////////////////////////////////
#ifdef APPLS_MODAL_USES_CONCATENATION
QUESO::GslVector paramMinsA(paramSpaceA.zeroVector());
paramMinsA[0] = 0.;
paramMinsA[1] = 0.;
QUESO::GslVector paramMaxsA(paramSpaceA.zeroVector());
paramMaxsA[0] = 3.;
paramMaxsA[1] = 3.;
QUESO::BoxSubset<QUESO::GslVector,QUESO::GslMatrix>
paramDomainA("paramA_",paramSpaceA,paramMinsA,paramMaxsA);
QUESO::GslVector paramMinsB(paramSpaceB.zeroVector());
paramMinsB[0] = 0.;
QUESO::GslVector paramMaxsB(paramSpaceB.zeroVector());
paramMaxsB[0] = INFINITY;
QUESO::BoxSubset<QUESO::GslVector,QUESO::GslMatrix>
paramDomainB("paramB_",paramSpaceB,paramMinsB,paramMaxsB);
QUESO::ConcatenationSubset<QUESO::GslVector,QUESO::GslMatrix>
paramDomain("",paramSpace,paramDomainA,paramDomainB);
#else
QUESO::GslVector paramMins(paramSpace.zeroVector());
paramMins[0] = 0.;
paramMins[1] = 0.;
paramMins[2] = 0.;
QUESO::GslVector paramMaxs(paramSpace.zeroVector());
paramMaxs[0] = 3.;
paramMaxs[1] = 3.;
paramMaxs[2] = .3;
QUESO::BoxSubset<QUESO::GslVector,QUESO::GslMatrix>
paramDomain("param_",paramSpace,paramMins,paramMaxs);
#endif
////////////////////////////////////////////////////////
// Step 3 of 5: Instantiate the likelihood function object
////////////////////////////////////////////////////////
likelihoodRoutine_DataType likelihoodRoutine_Data;
likelihoodRoutine_Data.numModes = numModes;
QUESO::GenericScalarFunction<QUESO::GslVector,QUESO::GslMatrix>
likelihoodFunctionObj("like_",
paramDomain,
likelihoodRoutine,
(void *) &likelihoodRoutine_Data,
true); // routine computes [-2.*ln(function)]
////////////////////////////////////////////////////////
// Step 4 of 5: Instantiate the inverse problem
////////////////////////////////////////////////////////
#ifdef APPLS_MODAL_USES_CONCATENATION
QUESO::UniformVectorRV<QUESO::GslVector,QUESO::GslMatrix>
priorRvA("priorA_", paramDomainA);
QUESO::GslVector alpha(paramSpaceB.zeroVector());
alpha[0] = 3.;
QUESO::GslVector beta(paramSpaceB.zeroVector());
if (numModes == 1) {
beta[0] = 0.09709133373799;
}
else {
beta[0] = 0.08335837191688;
}
QUESO::InverseGammaVectorRV<QUESO::GslVector,QUESO::GslMatrix>
priorRvB("priorB_", paramDomainB,alpha,beta);
QUESO::ConcatenatedVectorRV<QUESO::GslVector,QUESO::GslMatrix>
priorRv("prior_", priorRvA, priorRvB, paramDomain);
#else
QUESO::UniformVectorRV<QUESO::GslVector,QUESO::GslMatrix>
priorRv("prior_", paramDomain);
#endif
QUESO::GenericVectorRV<QUESO::GslVector,QUESO::GslMatrix>
postRv("post_", paramSpace);
QUESO::StatisticalInverseProblem<QUESO::GslVector,QUESO::GslMatrix>
ip("", NULL, priorRv, likelihoodFunctionObj, postRv);
////////////////////////////////////////////////////////
// Step 5 of 5: Solve the inverse problem
////////////////////////////////////////////////////////
ip.solveWithBayesMLSampling();
////////////////////////////////////////////////////////
// Print some statistics
////////////////////////////////////////////////////////
unsigned int numPosTotal = postRv.realizer().subPeriod();
if (env.subDisplayFile()) {
*env.subDisplayFile() << "numPosTotal = " << numPosTotal
<< std::endl;
}
QUESO::GslVector auxVec(paramSpace.zeroVector());
unsigned int numPosTheta1SmallerThan1dot5 = 0;
for (unsigned int i = 0; i < numPosTotal; ++i) {
postRv.realizer().realization(auxVec);
if (auxVec[0] < 1.5) numPosTheta1SmallerThan1dot5++;
}
if (env.subDisplayFile()) {
*env.subDisplayFile() << "numPosTheta1SmallerThan1dot5 = " << numPosTheta1SmallerThan1dot5
<< ", ratio = " << ((double) numPosTheta1SmallerThan1dot5)/((double) numPosTotal)
<< std::endl;
}
return;
}
void compute(const QUESO::FullEnvironment& env) {
struct timeval timevalNow;
gettimeofday(&timevalNow, NULL);
std::cout << std::endl << "Beginning run of 'Hysteretic' example at "
<< ctime(&timevalNow.tv_sec);
//------------------------------------------------------
// Step 1 of 5: Instantiate the parameter space
//------------------------------------------------------
QUESO::VectorSpace<> paramSpaceA(env, "paramA_", 1, NULL);
QUESO::VectorSpace<> paramSpaceB(env, "paramB_", 14, NULL);
QUESO::VectorSpace<> paramSpace (env, "param_", 15, NULL);
//------------------------------------------------------
// Step 2 of 5: Instantiate the parameter domain
//------------------------------------------------------
QUESO::GslVector paramMinsA(paramSpaceA.zeroVector());
paramMinsA.cwSet(0);
QUESO::GslVector paramMaxsA(paramSpaceA.zeroVector());
paramMaxsA.cwSet(5);
QUESO::BoxSubset<> paramDomainA("paramA_",paramSpaceA,paramMinsA,paramMaxsA);
QUESO::GslVector paramMinsB(paramSpaceB.zeroVector());
paramMinsB.cwSet(-INFINITY);
QUESO::GslVector paramMaxsB(paramSpaceB.zeroVector());
paramMaxsB.cwSet( INFINITY);
QUESO::BoxSubset<> paramDomainB("paramB_",paramSpaceB,paramMinsB,paramMaxsB);
QUESO::ConcatenationSubset<> paramDomain("",paramSpace,paramDomainA,paramDomainB);
//------------------------------------------------------
// Step 3 of 5: Instantiate the likelihood function object
//------------------------------------------------------
std::cout << "\tInstantiating the Likelihood; calling internally the hysteretic model"
<< std::endl;
Likelihood<> likelihood("like_", paramDomain);
likelihood.floor.resize(4,NULL);
unsigned int numTimeSteps = 401;
for (unsigned int i = 0; i < 4; ++i) {
likelihood.floor[i] = new std::vector<double>(numTimeSteps,0.);
}
likelihood.accel.resize(numTimeSteps,0.);
FILE *inp;
inp = fopen("an.txt","r");
unsigned int numObservations = 0;
double tmpA;
while (fscanf(inp,"%lf",&tmpA) != EOF) {
likelihood.accel[numObservations] = tmpA;
numObservations++;
}
numObservations=1;
FILE *inp1_1;
inp1_1=fopen("measured_data1_1.txt","r");
while (fscanf(inp1_1,"%lf",&tmpA) != EOF) {
(*likelihood.floor[0])[numObservations]=tmpA;
numObservations++;
}
numObservations=0;
FILE *inp1_2;
inp1_2=fopen("measured_data1_2.txt","r");
while (fscanf(inp1_2,"%lf",&tmpA) != EOF) {
(*likelihood.floor[1])[numObservations]=tmpA;
numObservations++;
}
numObservations=0;
FILE *inp1_3;
inp1_3=fopen("measured_data1_3.txt","r");
while (fscanf(inp1_3,"%lf",&tmpA) != EOF) {
(*likelihood.floor[2])[numObservations]=tmpA;
numObservations++;
}
numObservations=0;
FILE *inp1_4;
inp1_4=fopen("measured_data1_4.txt","r");
while (fscanf(inp1_4,"%lf",&tmpA) != EOF) {
(*likelihood.floor[3])[numObservations]=tmpA;
numObservations++;
}
//------------------------------------------------------
// Step 4 of 5: Instantiate the inverse problem
//------------------------------------------------------
std::cout << "\tInstantiating the SIP" << std::endl;
QUESO::UniformVectorRV<> priorRvA("priorA_", paramDomainA);
QUESO::GslVector meanVec(paramSpaceB.zeroVector());
QUESO::GslVector diagVec(paramSpaceB.zeroVector());
diagVec.cwSet(0.6*0.6);
QUESO::GslMatrix covMatrix(diagVec);
QUESO::GaussianVectorRV<> priorRvB("priorB_", paramDomainB,meanVec,covMatrix);
QUESO::ConcatenatedVectorRV<> priorRv("prior_", priorRvA, priorRvB, paramDomain);
QUESO::GenericVectorRV<> postRv("post_", paramSpace);
QUESO::StatisticalInverseProblem<> ip("", NULL, priorRv, likelihood, postRv);
//------------------------------------------------------
// Step 5 of 5: Solve the inverse problem
//------------------------------------------------------
std::cout << "\tSolving the SIP with Multilevel method" << std::endl;
ip.solveWithBayesMLSampling();
gettimeofday(&timevalNow, NULL);
std::cout << "Ending run of 'Hysteretic' example at "
<< ctime(&timevalNow.tv_sec) << std::endl;
return;
}
