}
void correlationType::update(const int frameNum, const std::vector< RVec > &curFrame) {
- std::cout << "\t ola001" << std::endl;
trajectory.push_back(curFrame);
- std::cout << "\t ola002" << std::endl;
int temp = window + tau;
- std::cout << "\t ola003" << std::endl;
if (trajectory.size() == temp + 1) {
- std::cout << "\t ola003.1" << std::endl;
trajectory.erase(trajectory.begin());
- std::cout << "\t ola003.2" << std::endl;
}
- std::cout << "\t ola004" << std::endl;
if (mode == 1) {
- std::cout << "\t ola005" << std::endl;
if ( ((frameNum - temp + 1) >= 0) && ((frameNum - temp + 1) % tauStep == 0)) {
- std::cout << "\t ola006" << std::endl;
+ std::cout << "\t ola001" << std::endl;
correlationEval();
- std::cout << "\t ola007" << std::endl;
+ std::cout << "\t ola002" << std::endl;
selections.erase(selections.begin());
- std::cout << "\t ola008" << std::endl;
std::cout << "\n\t\tcorrEval successful\n" << std::endl;
}
- std::cout << "\t ola009" << std::endl;
}
+ std::cout << "upd - end\n" << std::endl;
}
void correlationType::readEval() {
}
void correlationType::correlationEval() {
+ std::cout << "\t ola001.1" << std::endl;
trajectoryFitting();
+ std::cout << "\t ola001.2" << std::endl;
matrixNullFitting();
- std::vector< std::vector< double > > a, b, c;
- std::vector< double > d;
- d.resize(index.size(), 0.);
+ std::cout << "\t ola001.3" << std::endl;
#pragma omp parallel for ordered schedule(dynamic) shared(matrixes) firstprivate(trajectory, reference)
for (size_t i = 0; i <= static_cast< size_t >(tau); i++) {
- a.resize(0); b.resize(0); c.resize(0);
- a.resize(index.size(), d); b.resize(index.size(), d); c.resize(index.size(), d);
+ std::vector< std::vector< double > > a, b, c;
+ std::vector< double > d;
+ d.resize(index.size(), 0.);
+ a.resize(0);
+ b.resize(0);
+ c.resize(0);
+ a.resize(index.size(), d);
+ b.resize(index.size(), d);
+ c.resize(index.size(), d);
+ std::cout << "\tola001.4";
for (size_t j {0}; j < static_cast< size_t >(window); j++) {
for (size_t k1 {0}; k1 < index.size(); k1++) {
for (size_t k2 {0}; k2 < index.size(); k2++) {
matrixes[i][j][k] = a[j][k] / (std::sqrt(b[j][k] * c[j][k]));
}
}
+ std::cout << "\tola001.5";
}
#pragma omp barrier
+ std::cout << "\t ola001.6" << std::endl;
for (size_t i {0}; i < matrixes.size(); i++) {
for (size_t j {0}; j < matrixes[i].size(); j++) {
for (size_t k {0}; k < matrixes[i][j].size(); k++) {
}
}
}
+ std::cout << "\t ola001.7" << std::endl;
readWriteCorrelations(1);
count++;
+ std::cout << "\t ola001.8" << std::endl;
}
void correlationType::graphCalculations(size_t tauStart, size_t tauEnd) {