/** Calculates the overall normalization factor.
* This multiplies result by (bin width * sum of monitor counts) / total
* frame
* width.
* @param X The BinEdges of the workspace
* @param Y The Counts of the workspace
* @param E The CountStandardDeviations of the workspace
*/
void NormaliseToMonitor::normalisationFactor(const BinEdges &X, Counts &Y,
CountStandardDeviations &E) {
const double monitorSum = std::accumulate(Y.begin(), Y.end(), 0.0);
const double range = X.back() - X.front();
auto specLength = Y.size();
auto &yNew = Y.mutableRawData();
auto &eNew = E.mutableRawData();
for (size_t j = 0; j < specLength; ++j) {
const double factor = range / ((X[j + 1] - X[j]) * monitorSum);
yNew[j] *= factor;
eNew[j] *= factor;
}
}
/// Constructs Points from BinEdges, where each point is a bin center.
Points::Points(const BinEdges &edges) {
if (!edges)
return;
if (edges.size() == 1)
throw std::logic_error("Points: Cannot construct from BinEdges of size 1");
if (edges.empty()) {
m_data = Kernel::make_cow<HistogramX>(0);
return;
}
std::vector<double> data(edges.size() - 1);
for (size_t i = 0; i < data.size(); ++i) {
data[i] = (0.5 * (edges[i] + edges[i + 1]));
}
m_data = Kernel::make_cow<HistogramX>(std::move(data));
}
/// Move-constructs FrequencyStandardDeviations from CountStandardDeviations and
/// bin width based on BinEdges.
FrequencyStandardDeviations::FrequencyStandardDeviations(
CountStandardDeviations &&counts, const BinEdges &edges) {
if (!counts)
return;
if (!edges)
throw std::logic_error("FrequencyStandardDeviations: Cannot construct from "
"CountStandardDeviations -- BinEdges are NULL.");
if ((counts.size() + 1) != edges.size())
if (!counts.empty() || !edges.empty())
throw std::logic_error("FrequencyStandardDeviations: Cannot construct "
"from CountStandardDeviations -- BinEdges size "
"does not match.");
// Cannot move counts private data since it is of different type.
m_data = counts.cowData();
counts = Kernel::cow_ptr<HistogramE>(nullptr);
auto &data = m_data.access();
for (size_t i = 0; i < data.size(); ++i) {
data[i] /= edges[i + 1] - edges[i];
}
}
/** Finds the indices of the bins at the limits of the range given.
* @param X :: The X vector to search
* @param startBin :: Returns the bin index including the starting value
* @param endBin :: Returns the bin index after the end value
*/
void MaskBins::findIndices(const BinEdges &X,
MantidVec::difference_type &startBin,
MantidVec::difference_type &endBin) {
startBin = std::distance(X.begin(),
std::upper_bound(X.cbegin(), X.cend(), m_startX));
if (startBin != 0)
--startBin;
auto last = std::lower_bound(X.cbegin(), X.cend(), m_endX);
if (last == X.cend())
--last;
endBin = std::distance(X.cbegin(), last);
}
