GetEi.cpp 19.2 KB
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#include "MantidAlgorithms/GetEi.h"
#include "MantidKernel/ArrayProperty.h"
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#include "MantidAPI/FileProperty.h"
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#include "MantidKernel/PhysicalConstants.h"
#include "MantidAPI/WorkspaceValidators.h"
#include "MantidAPI/SpectraDetectorMap.h"
#include <boost/lexical_cast.hpp>
#include "MantidKernel/Exception.h" 
#include <cmath>

namespace Mantid
{
namespace Algorithms
{

// Register the algorithm into the algorithm factory
DECLARE_ALGORITHM(GetEi)

using namespace Kernel;
using namespace API;
using namespace Geometry;

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// adjustable fit criteria, increase the first number or reduce any of the last three for more promiscuous peak fitting
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// from the estimated location of the peak search forward by the following fraction and backward by the same fraction
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const double GetEi::HALF_WINDOW = 8.0/100;
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const double GetEi::PEAK_THRESH_H = 3.0;
const double GetEi::PEAK_THRESH_A = 5.0;
const int GetEi::PEAK_THRESH_W = 3;

// progress estimates
const double GetEi::CROP = 0.15;
const double GetEi::GET_COUNT_RATE = 0.15;
const double GetEi::FIT_PEAK = 0.2;
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/// Empty default constructor algorith() calls the constructor in the base class
GetEi::GetEi() : Algorithm(),
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  m_tempWS(), m_fracCompl(0.0)
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{
}

void GetEi::init()
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{// Declare required input parameters for algorithm and do some validation here
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  CompositeValidator<> *val = new CompositeValidator<>;
  val->add(new WorkspaceUnitValidator<>("TOF"));
  val->add(new HistogramValidator<>);
  declareProperty(new WorkspaceProperty<>(
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    "InputWorkspace","",Direction::Input,val),
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    "The X units of this workspace must be time of flight with times in\n"
    "micro-seconds");
  BoundedValidator<int> *mustBePositive = new BoundedValidator<int>();
  mustBePositive->setLower(0);
  declareProperty("Monitor1Spec", -1, mustBePositive,
    "The spectrum number of the output of the first monitor, e.g. MAPS\n"
    "41474, MARI 2, MERLIN 69634");
  declareProperty("Monitor2Spec", -1, mustBePositive->clone(),
    "The spectrum number of the output of the second monitor e.g. MAPS\n"
    "41475, MARI 3, MERLIN 69638");
  BoundedValidator<double> *positiveDouble = new BoundedValidator<double>();
  positiveDouble->setLower(0);
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  declareProperty("EnergyEstimate", -1.0, positiveDouble,
    "An approximate value for the typical incident energy, energy of\n"
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    "neutrons leaving the source (meV)");
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  declareProperty("IncidentEnergy", -1.0, Direction::Output);
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  declareProperty("FirstMonitorPeak", -1.0, Direction::Output);
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  m_fracCompl = 0.0;
}

/** Executes the algorithm
*  @throw out_of_range if the peak runs off the edge of the histogram
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*  @throw NotFoundError if one of the requested spectrum numbers was not found in the workspace
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*  @throw IndexError if there is a problem converting spectra indexes to spectra numbers, which would imply there is a problem with the workspace
*  @throw invalid_argument if a good peak fit wasn't made or the input workspace does not have common binning
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*  @throw runtime_error if there is a problem with the SpectraDetectorMap or a sub-algorithm falls over
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*/
void GetEi::exec()
{
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  MatrixWorkspace_const_sptr inWS = getProperty("InputWorkspace");
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  const int mon1Spec = getProperty("Monitor1Spec");
  const int mon2Spec = getProperty("Monitor2Spec");
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  double dist2moni0 = -1, dist2moni1 = -1;
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  getGeometry(inWS, mon1Spec, mon2Spec, dist2moni0, dist2moni1);
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  // the E_i estimate is used to find (identify) the monitor peaks, checking prior to fitting will throw an exception if this estimate is too big or small
  const double E_est = getProperty("EnergyEstimate");
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  // we're assuming that the time units for the X-values in the workspace are micro-seconds
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  const double peakLoc0 = 1e6*timeToFly(dist2moni0, E_est);
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  // write a lot of stuff to the log at user level as it is very possible for fit routines not to the expected thing
  g_log.information() << "Based on the user selected energy the first peak will be searched for at TOF " << peakLoc0 << " micro seconds +/-" << boost::lexical_cast<std::string>(100.0*HALF_WINDOW) << "%\n";
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  const double peakLoc1 = 1e6*timeToFly(dist2moni1, E_est);
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  g_log.information() << "Based on the user selected energy the second peak will be searched for at TOF " << peakLoc1 << " micro seconds +/-" << boost::lexical_cast<std::string>(100.0*HALF_WINDOW) << "%\n";
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    // get the histograms created by the monitors
  std::vector<int> indexes = getMonitorSpecIndexs(inWS, mon1Spec, mon2Spec);

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  g_log.information() << "Looking for a peak in the first monitor spectrum, spectra index " << indexes[0] << std::endl;
  double t_monitor0 = getPeakCentre(inWS, indexes[0], peakLoc0);
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  g_log.notice() << "The first peak has been found at TOF = " << t_monitor0 << " microseconds\n";
  setProperty("FirstMonitorPeak", t_monitor0);

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  g_log.information() << "Looking for a peak in the second monitor spectrum, spectra index " << indexes[1] << std::endl;
  double t_monitor1 = getPeakCentre(inWS, indexes[1], peakLoc1);
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  g_log.information() << "The second peak has been found at TOF = " << t_monitor1 << " microseconds\n";
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  // assumes that the source and the both mintors lie on one straight line, the 1e-6 converts microseconds to seconds as the mean speed needs to be in m/s
  double meanSpeed = (dist2moni1 - dist2moni0)/(1e-6*(t_monitor1 - t_monitor0));

  // uses 0.5mv^2 to get the kinetic energy in joules which we then convert to meV
  double E_i = neutron_E_At(meanSpeed)/PhysicalConstants::meV;
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  g_log.notice() << "The incident energy has been calculated to be " << E_i << " meV" << " (your estimate was " << E_est << " meV)\n";
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  setProperty("IncidentEnergy", E_i);
}
/** Gets the distances between the source and detectors whose IDs you pass to it
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*  @param WS the input workspace
*  @param mon0Spec Spectrum number of the output from the first monitor
*  @param mon1Spec Spectrum number of the output from the second monitor
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*  @param monitor0Dist the calculated distance to the detector whose ID was passed to this function first
*  @param monitor1Dist calculated distance to the detector whose ID was passed to this function second
*  @throw NotFoundError if no detector is found for the detector ID given
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*  @throw runtime_error if there is a problem with the SpectraDetectorMap
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*/
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void GetEi::getGeometry(API::MatrixWorkspace_const_sptr WS, int mon0Spec, int mon1Spec, double &monitor0Dist, double &monitor1Dist) const
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{
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  const IObjComponent_sptr source = WS->getInstrument()->getSource();
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  // retrieve a pointer to the first detector and get its distance
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  std::vector<int> dets = WS->spectraMap().getDetectors(mon0Spec);
  if ( dets.size() != 1 )
  {
    g_log.error() << "The detector for spectrum number " << mon0Spec << " was either not found or is a group, grouped monitors are not supported by this algorithm\n";
    g_log.error() << "Error retrieving data for the first monitor" << std::endl;
    throw std::bad_cast();
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  }
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  IDetector_sptr det = WS->getInstrument()->getDetector(dets[0]);
  monitor0Dist = det->getDistance(*(source.get()));

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  // repeat for the second detector
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  dets = WS->spectraMap().getDetectors(mon1Spec);
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  if ( dets.size() != 1 )
  {
    g_log.error() << "The detector for spectrum number " << mon1Spec << " was either not found or is a group, grouped monitors are not supported by this algorithm\n";
    g_log.error() << "Error retrieving data for the second monitor\n";
    throw std::bad_cast();
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  }
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  det = WS->getInstrument()->getDetector(dets[0]);
  monitor1Dist = det->getDistance(*(source.get()));
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}
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/** Converts detector IDs to spectra indexes
*  @param WS the workspace on which the calculations are being performed
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*  @param specNum1 spectrum number of the output of the first monitor
*  @param specNum2 spectrum number of the output of the second monitor
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*  @return the indexes of the histograms created by the detector whose ID were passed
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*  @throw NotFoundError if one of the requested spectrum numbers was not found in the workspace
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*/
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std::vector<int> GetEi::getMonitorSpecIndexs(API::MatrixWorkspace_const_sptr WS, int specNum1, int specNum2) const
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{// getting spectra numbers from detector IDs is hard because the map works the other way, getting index numbers from spectra numbers has the same problem and we are about to do both
  std::vector<int> specInds;
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  // get the index number of the histogram for the first monitor
  std::vector<int> specNumTemp(&specNum1, &specNum1+1);
  WorkspaceHelpers::getIndicesFromSpectra(WS, specNumTemp, specInds);
  if ( specInds.size() != 1 )
  {// the monitor spectrum isn't present in the workspace, we can't continue from here
    g_log.error() << "Couldn't find the first monitor spectrum, number " << specNum1 << std::endl;
    throw Exception::NotFoundError("GetEi::getMonitorSpecIndexs()", specNum1);
  }

  // nowe the second monitor
  std::vector<int> specIndexTemp;
  specNumTemp[0] = specNum2;
  WorkspaceHelpers::getIndicesFromSpectra(WS, specNumTemp, specIndexTemp);
  if ( specIndexTemp.size() != 1 )
  {// the monitor spectrum isn't present in the workspace, we can't continue from here
    g_log.error() << "Couldn't find the second monitor spectrum, number " << specNum2 << std::endl;
    throw Exception::NotFoundError("GetEi::getMonitorSpecIndexs()", specNum2);
  }
  
  specInds.push_back(specIndexTemp[0]);
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  return specInds;
}
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/** Uses E_KE = mv^2/2 and s = vt to calculate the time required for a neutron
*  to travel a distance, s
* @param s ditance travelled in meters
* @param E_KE kinetic energy in meV
* @return the time to taken to travel that uninterrupted distance in seconds
*/
double GetEi::timeToFly(double s, double E_KE) const
{
  // E_KE = mv^2/2, s = vt
  // t = s/v, v = sqrt(2*E_KE/m)
  // t = s/sqrt(2*E_KE/m)

  // convert E_KE to joules kg m^2 s^-2
  E_KE *= PhysicalConstants::meV;

  return s/sqrt(2*E_KE/PhysicalConstants::NeutronMass);
}
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/** Looks for and examines a peak close to that specified by the input parameters and
*  examines it to find a representative time for when the neutrons hit the detector
*  @param WS the workspace containing the monitor spectrum
*  @param monitIn the index of the histogram that contains the monitor spectrum
*  @param peakTime the estimated TOF of the monitor peak in the time units of the workspace
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*  @return a time of flight value in the peak in microseconds
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*  @throw invalid_argument if a good peak fit wasn't made or the input workspace does not have common binning
*  @throw out_of_range if the peak runs off the edge of the histogram
*  @throw runtime_error a sub-algorithm just falls over
*/
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double GetEi::getPeakCentre(API::MatrixWorkspace_const_sptr WS, const int monitIn, const double peakTime)
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{
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  const MantidVec& timesArray = WS->readX(monitIn);
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  // we search for the peak only inside some window because there are often more peaks in the monitor histogram
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  double halfWin = ( timesArray.back() - timesArray.front() )*HALF_WINDOW;
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  // runs CropWorkspace as a sub-algorithm to and puts the result in a new temporary workspace that will be deleted when this algorithm has finished
  extractSpec(monitIn, peakTime-halfWin, peakTime+halfWin);
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  // converting the workspace to count rate is required by the fitting algorithm if the bin widths are not all the same
  WorkspaceHelpers::makeDistribution(m_tempWS);
  // look out for user cancel messgages as the above command can take a bit of time
  advanceProgress(GET_COUNT_RATE);

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  // to store fit results
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  int centreGausInd;
  double height, backGroundlev;
  getPeakEstimates(height, centreGausInd, backGroundlev);
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  // look out for user cancel messgages
  advanceProgress(FIT_PEAK);
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  // the peak centre is defined as the centre of the two half maximum points as this is better for asymmetric peaks
  // first loop backwards along the histogram to get the first half height point
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  const double lHalf = findHalfLoc(centreGausInd, height, backGroundlev, GO_LEFT);
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  // go forewards to get the half height on the otherside of the peak
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  const double rHalf = findHalfLoc(centreGausInd, height, backGroundlev, GO_RIGHT);
  // the peak centre is defined as the mean of the two half height times 
  return (lHalf + rHalf)/2;
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}
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/** Calls CropWorkspace as a sub-algorithm and passes to it the InputWorkspace property
*  @param specInd the index number of the histogram to extract
*  @param start the number of the first bin to include (starts counting bins at 0)
*  @param end the number of the last bin to include (starts counting bins at 0)
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*  @throw out_of_range if start, end or specInd are set outside of the vaild range for the workspace
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*  @throw runtime_error if the algorithm just falls over
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*  @throw invalid_argument if the input workspace does not have common binning
*/
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void GetEi::extractSpec(int specInd, double start, double end)
{
  IAlgorithm_sptr childAlg =
    createSubAlgorithm("CropWorkspace", 100*m_fracCompl, 100*(m_fracCompl+CROP) );
  m_fracCompl += CROP;
  
  childAlg->setPropertyValue( "InputWorkspace",
                              getPropertyValue("InputWorkspace") );
  childAlg->setProperty( "XMin", start);
  childAlg->setProperty( "XMax", end);
  childAlg->setProperty( "StartWorkspaceIndex", specInd);
  childAlg->setProperty( "EndWorkspaceIndex", specInd);

  try
  {
    childAlg->execute();
  }
  catch (std::exception&)
  {
    g_log.error("Exception thrown while running CropWorkspace as a sub-algorithm");
    throw;
  }

  if ( ! childAlg->isExecuted() )
  {
    g_log.error("The CropWorkspace algorithm failed unexpectedly, aborting.");
    throw std::runtime_error(name() + " failed trying to run CropWorkspace");
  }
  m_tempWS = childAlg->getProperty("OutputWorkspace");

//DEBUGGING CODE uncomment out the line below if you want to see the TOF window that was analysed
//AnalysisDataService::Instance().addOrReplace("croped_dist_del", m_tempWS);
  progress(m_fracCompl);
  interruption_point();
}

/** Finds the largest peak by looping through the histogram and finding the maximum
*  value 
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* @param height its passed value ignored it is set to the peak height
* @param centreInd passed value is ignored it will be set to the bin index of the peak center
* @param background passed value ignored set mean number of counts per bin in the spectrum
* @throw invalid_argument if the peak is not clearly above the background
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*/
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void GetEi::getPeakEstimates(double &height, int &centreInd, double &background) const
{
  // take note of the number of background counts as error checking, do we have a peak or just a bump in the background
  background = 0;
  // start at the first Y value
  height = m_tempWS->readY(0)[0];
  centreInd = 0;
  // then loop through all the Y values and find the tallest peak
  for ( MantidVec::size_type i = 1; i < m_tempWS->readY(0).size()-1; ++i )
  {
    background += m_tempWS->readY(0)[i];
    if ( m_tempWS->readY(0)[i] > height )
    {
      centreInd = i;
      height = m_tempWS->readY(0)[centreInd];
    }
  }
  
  background = background/m_tempWS->readY(0).size();
  if ( height < PEAK_THRESH_H*background )
  {
    throw std::invalid_argument("No peak was found or its height is less than the threshold of " + boost::lexical_cast<std::string>(PEAK_THRESH_H) + " times the mean background, was the energy estimate (" + getPropertyValue("EnergyEstimate") + " meV) close enough?");
  }

  g_log.debug() << "Peak position is the bin that has the maximum Y value in the monitor spectrum, which is at TOF " << (m_tempWS->readX(0)[centreInd]+m_tempWS->readX(0)[centreInd+1])/2 << " (peak height " << height << " counts/microsecond)\n";

}
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/** Estimates the closest time, looking either or back, when the number of counts is
*  half that in the bin whose index that passed
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*  @param startInd index of the bin to search around, e.g. the index of the peak centre
*  @param height the number of counts (or count rate) to compare against e.g. a peak height
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*  @param noise mean number of counts in each bin in the workspace
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*  @param go either GetEi::GO_LEFT or GetEi::GO_RIGHT
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*  @return estimated TOF of the half maximum point
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*  @throw out_of_range if the end of the histogram is reached before the point is found
*  @throw invalid_argument if the peak is too thin
*/
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double GetEi::findHalfLoc(MantidVec::size_type startInd, const double height, const double noise, const direction go) const
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{
  MantidVec::size_type endInd = startInd;
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  while ( m_tempWS->readY(0)[endInd] >  (height+noise)/2.0 )
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  {
    endInd += go;
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    if ( endInd < 1 )
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    {
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      throw std::out_of_range("Can't analyse peak, some of the peak is outside the " + boost::lexical_cast<std::string>(HALF_WINDOW*100) + "% window, at TOF values that are too low. Was the energy estimate close enough?");
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    }
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    if ( endInd > m_tempWS->readY(0).size()-2)
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    {
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      throw std::out_of_range("Can't analyse peak, some of the peak is outside the " + boost::lexical_cast<std::string>(HALF_WINDOW*100) + "% window, at TOF values that are too high. Was the energy estimate close enough?");
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    }
  }
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  if ( std::abs(static_cast<int>(endInd - startInd)) < PEAK_THRESH_W )
  {// we didn't find a significant peak
    g_log.error() << "Likely precision problem or error, one half height distance is less than the threshold number of bins from the central peak: " << std::abs(static_cast<int>(endInd - startInd)) << "<" << PEAK_THRESH_W << ". Check the monitor peak\n";
  }
  // we have a peak in range, do an area check to see if the peak has any significance
  double hOverN = (height-noise)/noise;
  if ( hOverN < PEAK_THRESH_A && std::abs(hOverN*(endInd - startInd)) < PEAK_THRESH_A )
  {// the peak could just be noise on the background, ignore it
    throw std::invalid_argument("No good peak was found. The ratio of the height to the background multiplied either half widths must be above the threshold (>" + boost::lexical_cast<std::string>(PEAK_THRESH_A) + " bins). Was the energy estimate close enough?");
  }
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  // get the TOF value in the middle of the bin with the first value below the half height
  double halfTime = (m_tempWS->readX(0)[endInd]+m_tempWS->readX(0)[endInd+1])/2;
  // interpolate back between the first bin with less than half the counts to the bin before it
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  if ( endInd != startInd )
  {// let the bin that we found have coordinates (x_1, y_1) the distance of the half point (x_2, y_2) from this is (y_1-y_2)/gradient. Gradient = (y_3-y_1)/(x_3-x_1) where (x_3, y_3) are the coordinates of the other bin we are using
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    double gradient = ( m_tempWS->readY(0)[endInd] - m_tempWS->readY(0)[endInd-go] )/
      ( m_tempWS->readX(0)[endInd] - m_tempWS->readX(0)[endInd-go] );
    // we don't need to check for a zero or negative gradient if we assume the endInd bin was found when the Y-value dropped below the threshold
    double deltaY = m_tempWS->readY(0)[endInd]-(height+noise)/2.0;
    // correct for the interpolation back in the direction towards the peak centre
    halfTime -= deltaY/gradient;
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  }

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  g_log.debug() << "One half height point found at TOF = " << halfTime << " microseconds\n";
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  return halfTime;
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}
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/** Get the kinetic energy of a neuton in joules given it speed using E=mv^2/2
*  @param speed the instantanious speed of a neutron in metres per second
*  @return the energy in joules
*/
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double GetEi::neutron_E_At(double speed) const
{
  // E_KE = mv^2/2
  return PhysicalConstants::NeutronMass*speed*speed/(2);
}

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/// Update the percentage complete estimate assuming that the algorithm has completed a task with estimated RunTime toAdd
void GetEi::advanceProgress(double toAdd)
{
  m_fracCompl += toAdd;
  progress(m_fracCompl);
  // look out for user cancel messgages
  interruption_point();
}
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} // namespace Algorithms
} // namespace Mantid