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AlphaCalc.cpp
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AlphaCalc.cpp
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// Mantid Repository : https://github.com/mantidproject/mantid
//
// Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
// NScD Oak Ridge National Laboratory, European Spallation Source,
// Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
// SPDX - License - Identifier: GPL - 3.0 +
//----------------------------------------------------------------------
// Includes
//----------------------------------------------------------------------
#include "MantidMuon/AlphaCalc.h"
#include "MantidAPI/MatrixWorkspace.h"
#include "MantidKernel/ArrayProperty.h"
#include <cmath>
#include <vector>
namespace Mantid::Algorithms {
using namespace Kernel;
// Register the class into the algorithm factory
DECLARE_ALGORITHM(AlphaCalc)
/** Initialisation method. Declares properties to be used in algorithm.
*
*/
void AlphaCalc::init() {
declareProperty(std::make_unique<API::WorkspaceProperty<>>("InputWorkspace", "", Direction::Input),
"Name of the input workspace");
std::vector<int> forwardDefault{1};
declareProperty(std::make_unique<ArrayProperty<int>>("ForwardSpectra", std::move(forwardDefault)),
"The spectra numbers of the forward group (default to 1)");
std::vector<int> backwardDefault{2};
declareProperty(std::make_unique<ArrayProperty<int>>("BackwardSpectra", std::move(backwardDefault)),
"The spectra numbers of the backward group (default to 2)");
declareProperty("FirstGoodValue", EMPTY_DBL(), "First good value (default lowest value of x)", Direction::Input);
declareProperty("LastGoodValue", EMPTY_DBL(), "Last good value (default highest value of x)", Direction::Input);
declareProperty("Alpha", 1.0, "The alpha efficiency (default to 1.0)", Direction::Output);
}
/** Executes the algorithm
*
*/
void AlphaCalc::exec() {
std::vector<int> forwardSpectraList = getProperty("ForwardSpectra");
std::vector<int> backwardSpectraList = getProperty("BackwardSpectra");
double alpha = getProperty("Alpha");
// no point in attempting to calculate alpha if input workspace on contains
// one spectra
API::MatrixWorkspace_sptr inputWS = getProperty("InputWorkspace");
if (inputWS->getNumberHistograms() < 2) {
g_log.error() << "Can't calculate alpha value for workspace which"
<< " contains one spectrum. A default value of alpha = 1.0 is returned";
setProperty("Alpha", alpha);
return;
}
// if for some reason the size of forward and backward lists are zero
// default these to their defaults
if (forwardSpectraList.empty())
forwardSpectraList.emplace_back(1);
if (backwardSpectraList.empty())
backwardSpectraList.emplace_back(2);
// first step is to create two workspaces which groups all forward and
// backward spectra
auto groupForward = createChildAlgorithm("GroupDetectors");
groupForward->setProperty("InputWorkspace", inputWS);
groupForward->setProperty("OutputWorkspace", "tmp");
groupForward->setProperty("SpectraList", forwardSpectraList);
groupForward->setProperty("KeepUngroupedSpectra", false);
groupForward->execute();
API::MatrixWorkspace_sptr forwardWS = groupForward->getProperty("OutputWorkspace");
auto groupBackward = createChildAlgorithm("GroupDetectors");
groupBackward->setProperty("InputWorkspace", inputWS);
groupBackward->setProperty("OutputWorkspace", "tmp");
groupBackward->setProperty("SpectraList", backwardSpectraList);
groupBackward->setProperty("KeepUngroupedSpectra", false);
groupBackward->execute();
API::MatrixWorkspace_sptr backwardWS = groupBackward->getProperty("OutputWorkspace");
// calculate sum of forward counts
double firstGoodvalue = getProperty("FirstGoodValue");
double lastGoodvalue = getProperty("LastGoodValue");
auto integr = createChildAlgorithm("Integration");
integr->setProperty("InputWorkspace", forwardWS);
integr->setPropertyValue("OutputWorkspace", "tmp");
if (firstGoodvalue != EMPTY_DBL())
integr->setProperty("RangeLower", firstGoodvalue);
if (lastGoodvalue != EMPTY_DBL())
integr->setProperty("RangeUpper", lastGoodvalue);
integr->execute();
API::MatrixWorkspace_sptr out = integr->getProperty("OutputWorkspace");
double sumForward = out->readY(0)[0];
if (sumForward < 0) {
g_log.error() << "Sum of forward detector counts is negative."
<< "Therefore can't calculate alpha. Return alpha = 1.0.";
setProperty("Alpha", alpha);
return;
}
// calculate sum of backward counts
auto integrB = createChildAlgorithm("Integration");
integrB->setProperty("InputWorkspace", backwardWS);
integrB->setPropertyValue("OutputWorkspace", "tmp");
if (firstGoodvalue != EMPTY_DBL())
integrB->setProperty("RangeLower", firstGoodvalue);
if (lastGoodvalue != EMPTY_DBL())
integrB->setProperty("RangeUpper", lastGoodvalue);
integrB->execute();
out = integrB->getProperty("OutputWorkspace");
double sumBackward = out->readY(0)[0];
if (sumBackward <= 0) {
g_log.error() << "Sum of backward detector counts is negative or zero."
<< "Therefore can't calculate alpha. Return alpha = 1.0.";
setProperty("Alpha", alpha);
return;
}
// finally calculate alpha
setProperty("Alpha", sumForward / sumBackward);
}
} // namespace Mantid::Algorithms