void SaveDiffFittingAscii::writeData(const API::ITableWorkspace_sptr workspace,
std::ofstream &file,
const size_t columnSize) {
for (size_t rowIndex = 0; rowIndex < workspace->rowCount(); ++rowIndex) {
TableRow row = workspace->getRow(rowIndex);
for (size_t columnIndex = 0; columnIndex < columnSize; columnIndex++) {
const auto row_str =
boost::lexical_cast<std::string>(row.Double(columnIndex));
g_log.debug() << row_str << std::endl;
if (columnIndex == columnSize - 1)
writeVal(row_str, file, true);
else
writeVal(row_str, file, false);
}
}
}
int PoldiFitPeaks1D2::getBestChebyshevPolynomialDegree(
const Workspace2D_sptr &dataWorkspace, const RefinedRange_sptr &range) {
double chiSquareMin = 1e10;
int nMin = -1;
try {
int n = 0;
while ((n < 3)) {
IAlgorithm_sptr fit = getFitAlgorithm(dataWorkspace, range, n);
bool fitSuccess = fit->execute();
if (fitSuccess) {
ITableWorkspace_sptr fitCharacteristics =
fit->getProperty("OutputParameters");
TableRow row =
fitCharacteristics->getRow(fitCharacteristics->rowCount() - 1);
double chiSquare = row.Double(1);
if (fabs(chiSquare - 1) < fabs(chiSquareMin - 1)) {
chiSquareMin = chiSquare;
nMin = n;
}
}
++n;
}
} catch (std::runtime_error) {
nMin = -1;
}
if (nMin == -1) {
g_log.information() << "Range [" << range->getXStart() << " - "
<< range->getXEnd() << "] is excluded.";
} else {
g_log.information() << "Chi^2 for range [" << range->getXStart() << " - "
<< range->getXEnd() << "] is minimal at n = " << nMin
<< " with Chi^2 = " << chiSquareMin << std::endl;
}
return nMin;
}