/**
* Finds the median of values in single bin histograms rejecting spectra from
* masked
* detectors and the results of divide by zero (infinite and NaN).
* The median is an average that is less affected by small numbers of very large
* values.
* @param input :: A histogram workspace with one entry in each bin
* @param excludeZeroes :: If true then zeroes will not be included in the
* median calculation
* @param indexmap :: indexmap
* @return The median value of the histograms in the workspace that was passed
* to it
* @throw out_of_range if a value is negative
*/
std::vector<double> DetectorDiagnostic::calculateMedian(
const API::MatrixWorkspace &input, bool excludeZeroes,
const std::vector<std::vector<size_t>> &indexmap) {
std::vector<double> medianvec;
g_log.debug("Calculating the median count rate of the spectra");
bool checkForMask = false;
Geometry::Instrument_const_sptr instrument = input.getInstrument();
if (instrument != nullptr) {
checkForMask = ((instrument->getSource() != nullptr) &&
(instrument->getSample() != nullptr));
}
const auto &spectrumInfo = input.spectrumInfo();
for (const auto &hists : indexmap) {
std::vector<double> medianInput;
const int nhists = static_cast<int>(hists.size());
// The maximum possible length is that of workspace length
medianInput.reserve(nhists);
PARALLEL_FOR_IF(Kernel::threadSafe(input))
for (int i = 0; i < nhists; ++i) { // NOLINT
PARALLEL_START_INTERUPT_REGION
if (checkForMask && spectrumInfo.hasDetectors(hists[i])) {
if (spectrumInfo.isMasked(hists[i]) || spectrumInfo.isMonitor(hists[i]))
continue;
}
const double yValue = input.readY(hists[i])[0];
if (yValue < 0.0) {
throw std::out_of_range("Negative number of counts found, could be "
"corrupted raw counts or solid angle data");
}
if (!std::isfinite(yValue) ||
(excludeZeroes && yValue < DBL_EPSILON)) // NaNs/Infs
{
continue;
}
// Now we have a good value
PARALLEL_CRITICAL(DetectorDiagnostic_median_d) {
medianInput.push_back(yValue);
}
PARALLEL_END_INTERUPT_REGION
}
PARALLEL_CHECK_INTERUPT_REGION
if (medianInput.empty()) {
g_log.information(
"some group has no valid histograms. Will use 0 for median.");
medianInput.push_back(0.);
}
Kernel::Statistics stats =
Kernel::getStatistics(medianInput, StatOptions::Median);
double median = stats.median;
if (median < 0 || median > DBL_MAX / 10.0) {
throw std::out_of_range("The calculated value for the median was either "
"negative or unreliably large");
}
medianvec.push_back(median);
}
return medianvec;
}
