diff --git a/Framework/Algorithms/inc/MantidAlgorithms/FindPeakBackground.h b/Framework/Algorithms/inc/MantidAlgorithms/FindPeakBackground.h
index 62ce8bda1e0f32d9677e690ff1b173b7a76bcb88..26f32d2c04d3bcd3cba0e3406d249e833cf16e95 100644
--- a/Framework/Algorithms/inc/MantidAlgorithms/FindPeakBackground.h
+++ b/Framework/Algorithms/inc/MantidAlgorithms/FindPeakBackground.h
@@ -74,7 +74,9 @@ private:
/// create output workspace
void createOutputWorkspaces();
- void findStartStopIndex(size_t &istart, size_t &istop);
+ /// main method to find peak background
+ int findBackground(std::vector<size_t> &peak_min_max_indexes,
+ std::vector<double> &bkgd3);
/// set histogram data to find background
void setHistogram(const HistogramData::Histogram &histogram);
@@ -88,12 +90,19 @@ private:
/// set fit window
void setFitWindow(const std::vector<double> &window);
+ /// add result to output workpsace
+ void addResultToOutput(const int &goodfit,
+ const std::vector<size_t> &peakindexes,
+ const std::vector<double> &bkgdparams);
+
/// histogram data to find peak background
boost::shared_ptr<const HistogramData::Histogram> m_histogram;
// HistogramData::Histogram& m_histogram;
/// fit window
std::vector<double> m_vecFitWindows;
+ size_t m_iStartX; /// l0 in original code
+ size_t m_iStopX; /// n in original code
/// background order: 0 for flat, 1 for linear, 2 for quadratic
size_t m_backgroundOrder;
/// constant sigma
diff --git a/Framework/Algorithms/src/FindPeakBackground.cpp b/Framework/Algorithms/src/FindPeakBackground.cpp
index ec60398fc8b0cfe996924c09fe254520b4c830bf..350ecb4e91e7e58aa4f29cb21484c47995282abd 100644
--- a/Framework/Algorithms/src/FindPeakBackground.cpp
+++ b/Framework/Algorithms/src/FindPeakBackground.cpp
@@ -71,30 +71,85 @@ void FindPeakBackground::exec() {
// Get input and validate
processInputProperties();
- auto &inpX = m_histogram->x();
- auto &inpY = m_histogram->y();
- size_t sizex = inpX.size(); // inpWS->x(inpwsindex).size();
- size_t sizey = inpY.size(); // inpWS->y(inpwsindex).size();
-
- // determine the fit window with their index in X (or Y)
- size_t n = sizey;
- size_t l0 = 0;
- if (m_vecFitWindows.size() > 1) {
- Mantid::Algorithms::FindPeaks fp;
- l0 = fp.getIndex(inpX, m_vecFitWindows[0]);
- n = fp.getIndex(inpX, m_vecFitWindows[1]);
- if (n < sizey)
- n++;
- }
- // m_vecFitWindows won't be used again form this point till end.
+ // auto &inpX = m_histogram->x();
+ // auto &inpY = m_histogram->y();
+ // size_t sizex = inpX.size(); // inpWS->x(inpwsindex).size();
+ // size_t sizey = inpY.size(); // inpWS->y(inpwsindex).size();
+
+ // // determine the fit window with their index in X (or Y)
+ // size_t n = sizey;
+ // size_t l0 = 0;
+ // if (m_vecFitWindows.size() > 1) {
+ // Mantid::Algorithms::FindPeaks fp;
+ // l0 = fp.getIndex(inpX, m_vecFitWindows[0]);
+ // n = fp.getIndex(inpX, m_vecFitWindows[1]);
+ // if (n < sizey)
+ // n++;
+ // }
+ // // m_vecFitWindows won't be used again form this point till end.
// Set up output table workspace
createOutputWorkspaces();
- // 3. Get Y values
+ // set progress 10%
Progress prog(this, 0.0, 1.0, 1);
// Find background
+ std::vector<size_t> peakindexes;
+ std::vector<double> bkgdparams;
+ int goodfit = findBackground(peakindexes, bkgdparams);
+
+ // add to output workspace
+ addResultToOutput(goodfit, peakindexes, bkgdparams);
+
+ prog.report();
+
+ // 4. Set the output
+ setProperty("OutputWorkspace", m_outPeakTableWS);
+}
+
+//----------------------------------------------------------------------------------------------
+/**
+ * @brief FindPeakBackground::addResultToOutput
+ * @param goodfit
+ * @param peakindexes
+ * @param bkgdparams
+ */
+void FindPeakBackground::addResultToOutput(
+ const int &goodfit, const std::vector<size_t> &peakindexes,
+ const std::vector<double> &bkgdparams) {
+ if (goodfit > 0) {
+ int min_peak = static_cast<int>(peakindexes[0]);
+ int max_peak = static_cast<int>(peakindexes[1]);
+ double a0 = bkgdparams[0];
+ double a1 = bkgdparams[1];
+ double a2 = bkgdparams[2];
+
+ API::TableRow t = m_outPeakTableWS->getRow(0);
+ t << static_cast<int>(m_inputWSIndex) << min_peak << max_peak << a0 << a1
+ << a2 << goodfit;
+ }
+
+ return;
+}
+
+//----------------------------------------------------------------------------------------------
+/** Main method to process find peak background
+ * Note: all inputs shall be set up by this method
+ * @brief FindPeakBackground::findBackground
+ * @param peak_min_max_indexes
+ * @param bkgd3
+ * @return integer as good fit or not!
+ */
+int FindPeakBackground::findBackground(
+ std::vector<size_t> &peak_min_max_indexes, std::vector<double> &bkgd3) {
+ // get something from previously set up class variable
+ auto &inpX = m_histogram->x();
+ auto &inpY = m_histogram->y();
+ size_t l0 = m_iStartX;
+ size_t n = m_iStopX;
+
+ int goodfit(0);
double Ymean, Yvariance, Ysigma;
MantidVec maskedY;
auto in = std::min_element(inpY.cbegin(), inpY.cend());
@@ -162,10 +217,10 @@ void FindPeakBackground::exec() {
if (inpY[l + l0] > peaks[ipeak].maxY)
peaks[ipeak].maxY = inpY[l + l0];
}
- }
+ } // END-FOR (l)
+
size_t min_peak, max_peak;
double a0 = 0., a1 = 0., a2 = 0.;
- int goodfit;
if (!peaks.empty()) {
g_log.debug() << "Peaks' size = " << peaks.size()
<< " -> esitmate background. \n";
@@ -186,20 +241,28 @@ void FindPeakBackground::exec() {
goodfit = 2;
}
-
estimateBackground(inpX, inpY, l0, n, min_peak, max_peak, (!peaks.empty()),
a0, a1, a2);
// Add a new row
- API::TableRow t = m_outPeakTableWS->getRow(0);
- t << static_cast<int>(m_inputWSIndex) << static_cast<int>(min_peak)
- << static_cast<int>(max_peak) << a0 << a1 << a2 << goodfit;
- }
- prog.report();
+ // API::TableRow t = m_outPeakTableWS->getRow(0);
+ // t << static_cast<int>(m_inputWSIndex) << static_cast<int>(min_peak)
+ // << static_cast<int>(max_peak) << a0 << a1 << a2 << goodfit;
- // 4. Set the output
- setProperty("OutputWorkspace", m_outPeakTableWS);
+ // set up good fit result
+ peak_min_max_indexes.resize(2);
+ peak_min_max_indexes[0] = min_peak;
+ peak_min_max_indexes[1] = max_peak;
+
+ bkgd3.resize(3);
+ bkgd3[0] = a0;
+ bkgd3[1] = a1;
+ bkgd3[2] = a2;
+
+ } // END-IF: if (n - l0 > 5)
+
+ return goodfit;
}
//----------------------------------------------------------------------------------------------
@@ -444,6 +507,10 @@ void FindPeakBackground::setBackgroundOrder(size_t order) {
* @param fitwindow
*/
void FindPeakBackground::setFitWindow(const std::vector<double> &fitwindow) {
+
+ size_t l0 = 0;
+ size_t n = m_histogram->y().size();
+
// validate input
if (m_vecFitWindows.size() == 0) {
m_vecFitWindows.resize(2);
@@ -453,11 +520,37 @@ void FindPeakBackground::setFitWindow(const std::vector<double> &fitwindow) {
m_vecFitWindows[0] >= m_vecFitWindows[1]) {
throw std::invalid_argument("Fit window has either wrong item number or "
"window value is not in ascending order.");
+ } else {
+ Mantid::Algorithms::FindPeaks fp;
+ l0 = fp.getIndex(m_histogram->x(), m_vecFitWindows[0]);
+ n = fp.getIndex(m_histogram->x(), m_vecFitWindows[1]);
+ if (n < m_histogram->y().size())
+ n++;
}
- // m_vecFitWindows.resize(2);
// copy the input to class variable
m_vecFitWindows = fitwindow;
+ m_iStartX = l0;
+ m_iStopX = n;
+
+ // ---- from here .. all from original code
+
+ // auto &inpX = m_histogram->x();
+ // auto &inpY = m_histogram->y();
+ // size_t sizex = inpX.size(); // inpWS->x(inpwsindex).size();
+ // size_t sizey = inpY.size(); // inpWS->y(inpwsindex).size();
+
+ // determine the fit window with their index in X (or Y)
+ // size_t n = sizey;
+ // size_t l0 = 0;
+ // if (m_vecFitWindows.size() > 1) {
+ // Mantid::Algorithms::FindPeaks fp;
+ // l0 = fp.getIndex(inpX, m_vecFitWindows[0]);
+ // n = fp.getIndex(inpX, m_vecFitWindows[1]);
+ // if (n < sizey)
+ // n++;
+ // }
+ // m_vecFitWindows won't be used again form this point till end.
return;
}