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ConvolutionFit.cpp
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ConvolutionFit.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
// SPDX - License - Identifier: GPL - 3.0 +
#include "MantidAPI/AlgorithmManager.h"
#include "MantidAPI/CompositeFunction.h"
#include "MantidAPI/FunctionDomain1D.h"
#include "MantidAPI/FunctionFactory.h"
#include "MantidAPI/ITableWorkspace.h"
#include "MantidAPI/NumericAxis.h"
#include "MantidAPI/Progress.h"
#include "MantidAPI/Run.h"
#include "MantidAPI/TextAxis.h"
#include "MantidAPI/WorkspaceGroup.h"
#include "MantidCurveFitting/Algorithms/ConvolutionFit.h"
#include "MantidCurveFitting/Algorithms/QENSFitSequential.h"
#include "MantidCurveFitting/Algorithms/QENSFitSimultaneous.h"
#include "MantidKernel/BoundedValidator.h"
#include "MantidKernel/ListValidator.h"
#include "MantidKernel/MandatoryValidator.h"
#include "MantidKernel/StringContainsValidator.h"
#include "MantidKernel/VectorHelper.h"
#include <algorithm>
#include <cmath>
namespace {
using namespace Mantid::API;
using namespace Mantid::Kernel;
using Mantid::MantidVec;
std::size_t numberOfFunctions(IFunction_sptr function,
const std::string &functionName);
std::size_t numberOfFunctions(CompositeFunction_sptr composite,
const std::string &functionName) {
std::size_t count = 0;
for (auto i = 0u; i < composite->nFunctions(); ++i)
count += numberOfFunctions(composite->getFunction(i), functionName);
return count;
}
std::size_t numberOfFunctions(IFunction_sptr function,
const std::string &functionName) {
const auto composite =
boost::dynamic_pointer_cast<CompositeFunction>(function);
if (composite)
return numberOfFunctions(composite, functionName);
return function->name() == functionName ? 1 : 0;
}
bool containsFunction(IFunction_sptr function, const std::string &functionName);
bool containsFunction(CompositeFunction_sptr composite,
const std::string &functionName) {
for (auto i = 0u; i < composite->nFunctions(); ++i) {
if (containsFunction(composite->getFunction(i), functionName))
return true;
}
return false;
}
bool containsFunction(IFunction_sptr function,
const std::string &functionName) {
const auto composite =
boost::dynamic_pointer_cast<CompositeFunction>(function);
if (function->name() == functionName)
return true;
else if (composite)
return containsFunction(composite, functionName);
return false;
}
template <typename T, typename F, typename... Ts>
std::vector<T, Ts...> transformVector(const std::vector<T, Ts...> &vec,
F const &functor) {
auto target = std::vector<T, Ts...>();
target.reserve(vec.size());
std::transform(vec.begin(), vec.end(), std::back_inserter(target), functor);
return target;
}
template <typename T, typename F, typename... Ts>
std::vector<T, Ts...> combineVectors(const std::vector<T, Ts...> &vec,
const std::vector<T, Ts...> &vec2,
F const &combinator) {
auto combined = std::vector<T, Ts...>();
combined.reserve(vec.size());
std::transform(vec.begin(), vec.end(), vec2.begin(),
std::back_inserter(combined), combinator);
return combined;
}
template <typename T, typename... Ts>
std::vector<T, Ts...> divideVectors(const std::vector<T, Ts...> ÷nd,
const std::vector<T, Ts...> &divisor) {
return combineVectors(dividend, divisor, std::divides<T>());
}
template <typename T, typename... Ts>
std::vector<T, Ts...> addVectors(const std::vector<T, Ts...> &vec,
const std::vector<T, Ts...> &vec2) {
return combineVectors(vec, vec2, std::plus<T>());
}
template <typename T, typename... Ts>
std::vector<T, Ts...> multiplyVectors(const std::vector<T, Ts...> &vec,
const std::vector<T, Ts...> &vec2) {
return combineVectors(vec, vec2, std::multiplies<T>());
}
template <typename T, typename... Ts>
std::vector<T, Ts...> squareVector(const std::vector<T, Ts...> &vec) {
return transformVector(vec, VectorHelper::Squares<T>());
}
template <typename T, typename... Ts>
std::vector<T, Ts...> squareRootVector(const std::vector<T, Ts...> &vec) {
return transformVector(vec, static_cast<T (*)(T)>(sqrt));
}
IFunction_sptr extractFirstBackground(IFunction_sptr function);
IFunction_sptr extractFirstBackground(CompositeFunction_sptr composite) {
for (auto i = 0u; i < composite->nFunctions(); ++i) {
auto background = extractFirstBackground(composite->getFunction(i));
if (background)
return background;
}
return nullptr;
}
IFunction_sptr extractFirstBackground(IFunction_sptr function) {
auto composite = boost::dynamic_pointer_cast<CompositeFunction>(function);
if (composite)
return extractFirstBackground(composite);
else if (function->category() == "Background")
return function;
return nullptr;
}
std::string extractBackgroundType(IFunction_sptr function) {
auto background = extractFirstBackground(function);
if (!background)
return "None";
auto backgroundType = background->name();
auto position = backgroundType.rfind("Background");
if (position != std::string::npos)
backgroundType = backgroundType.substr(0, position);
if (background->isFixed(0))
backgroundType = "Fixed " + backgroundType;
else
backgroundType = "Fit " + backgroundType;
return backgroundType;
}
std::vector<std::size_t>
searchForFitParameters(const std::string &suffix,
ITableWorkspace_sptr tableWorkspace) {
auto indices = std::vector<std::size_t>();
for (auto i = 0u; i < tableWorkspace->columnCount(); ++i) {
auto name = tableWorkspace->getColumn(i)->name();
auto position = name.rfind(suffix);
if (position != std::string::npos &&
position + suffix.size() == name.size())
indices.emplace_back(i);
}
return indices;
}
std::pair<MantidVec, MantidVec>
calculateEISFAndError(const MantidVec &height, const MantidVec &heightError,
const MantidVec &litude,
const MantidVec &litudeError) {
auto total = addVectors(height, amplitude);
auto eisfY = divideVectors(height, total);
auto heightESq = squareVector(heightError);
auto ampErrSq = squareVector(amplitudeError);
auto totalErr = addVectors(heightESq, ampErrSq);
auto heightYSq = squareVector(height);
auto totalSq = squareVector(total);
auto errOverTotalSq = divideVectors(totalErr, totalSq);
auto heightESqOverYSq = divideVectors(heightESq, heightYSq);
auto sqrtESqOverYSq = squareRootVector(heightESqOverYSq);
auto eisfYSumRoot = multiplyVectors(eisfY, sqrtESqOverYSq);
return {eisfY, addVectors(eisfYSumRoot, errOverTotalSq)};
}
void addEISFToTable(ITableWorkspace_sptr &tableWs) {
// Get height data from parameter table
const auto height = searchForFitParameters("Height", tableWs).at(0);
const auto heightErr = searchForFitParameters("Height_Err", tableWs).at(0);
const auto heightY = tableWs->getColumn(height)->numeric_fill();
const auto heightE = tableWs->getColumn(heightErr)->numeric_fill();
// Get amplitude column names
const auto ampIndices = searchForFitParameters("Amplitude", tableWs);
const auto ampErrorIndices = searchForFitParameters("Amplitude_Err", tableWs);
// For each lorentzian, calculate EISF
auto maxSize = ampIndices.size();
if (ampErrorIndices.size() > maxSize)
maxSize = ampErrorIndices.size();
for (auto i = 0u; i < maxSize; ++i) {
// Get amplitude from column in table workspace
auto ampY = tableWs->getColumn(ampIndices[i])->numeric_fill();
auto ampErr = tableWs->getColumn(ampErrorIndices[i])->numeric_fill();
auto eisfAndError = calculateEISFAndError(heightY, heightE, ampY, ampErr);
// Append the calculated values to the table workspace
auto ampName = tableWs->getColumn(ampIndices[i])->name();
auto ampErrorName = tableWs->getColumn(ampErrorIndices[i])->name();
auto columnName =
ampName.substr(0, (ampName.size() - std::string("Amplitude").size()));
columnName += "EISF";
auto errorColumnName = ampErrorName.substr(
0, (ampErrorName.size() - std::string("Amplitude_Err").size()));
errorColumnName += "EISF_Err";
tableWs->addColumn("double", columnName);
tableWs->addColumn("double", errorColumnName);
auto maxEisf = eisfAndError.first.size();
if (eisfAndError.second.size() > maxEisf) {
maxEisf = eisfAndError.second.size();
}
auto col = tableWs->getColumn(columnName);
auto errCol = tableWs->getColumn(errorColumnName);
for (auto j = 0u; j < maxEisf; j++) {
col->cell<double>(j) = eisfAndError.first.at(j);
errCol->cell<double>(j) = eisfAndError.second.at(j);
}
}
}
} // namespace
namespace Mantid {
namespace CurveFitting {
namespace Algorithms {
using namespace API;
using namespace Kernel;
//----------------------------------------------------------------------------------------------
/// Algorithms name for identification. @see Algorithm::name
template <> const std::string ConvolutionFit<QENSFitSequential>::name() const {
return "ConvolutionFitSequential";
}
template <>
const std::string ConvolutionFit<QENSFitSimultaneous>::name() const {
return "ConvolutionFitSimultaneous";
}
template <typename Base> const std::string ConvolutionFit<Base>::name() const {
return "ConvolutionFit";
}
/// Algorithm's version for identification. @see Algorithm::version
template <typename Base> int ConvolutionFit<Base>::version() const { return 1; }
/// Algorithm's category for identification. @see Algorithm::category
template <typename Base>
const std::string ConvolutionFit<Base>::category() const {
return "Workflow\\MIDAS";
}
/// Algorithm's summary for use in the GUI and help. @see Algorithm::summary
template <>
const std::string ConvolutionFit<QENSFitSequential>::summary() const {
return "Performs a sequential fit for a convolution workspace";
}
template <>
const std::string ConvolutionFit<QENSFitSimultaneous>::summary() const {
return "Performs a simultaneous fit across convolution workspaces";
}
template <typename Base>
const std::string ConvolutionFit<Base>::summary() const {
return "Performs a convolution fit";
}
/// Algorithm's see also for related algorithms. @see Algorithm::seeAlso
template <>
const std::vector<std::string>
ConvolutionFit<QENSFitSequential>::seeAlso() const {
return {"QENSFitSequential"};
}
template <>
const std::vector<std::string>
ConvolutionFit<QENSFitSimultaneous>::seeAlso() const {
return {"QENSFitSimultaneous"};
}
template <typename Base>
const std::vector<std::string> ConvolutionFit<Base>::seeAlso() const {
return {};
}
template <typename Base>
std::map<std::string, std::string> ConvolutionFit<Base>::validateInputs() {
auto errors = Base::validateInputs();
IFunction_sptr function = Base::getProperty("Function");
if (!containsFunction(function, "Convolution") ||
!containsFunction(function, "Resolution"))
errors["Function"] = "Function provided does not contain convolution with "
"a resolution function.";
return errors;
}
template <typename Base>
bool ConvolutionFit<Base>::throwIfElasticQConversionFails() const {
return true;
}
template <typename Base>
bool ConvolutionFit<Base>::isFitParameter(const std::string &name) const {
bool isBackgroundParameter = name.rfind("A0") != std::string::npos ||
name.rfind("A1") != std::string::npos;
return name.rfind("Centre") == std::string::npos && !isBackgroundParameter;
}
template <typename Base>
ITableWorkspace_sptr ConvolutionFit<Base>::processParameterTable(
ITableWorkspace_sptr parameterTable) {
IFunction_sptr function = Base::getProperty("Function");
m_deltaUsed = containsFunction(function, "DeltaFunction");
if (m_deltaUsed)
addEISFToTable(parameterTable);
return parameterTable;
}
template <typename Base>
std::map<std::string, std::string>
ConvolutionFit<Base>::getAdditionalLogStrings() const {
IFunction_sptr function = Base::getProperty("Function");
auto logs = Base::getAdditionalLogStrings();
logs["delta_function"] = m_deltaUsed ? "true" : "false";
logs["background"] = extractBackgroundType(function);
return logs;
}
template <typename Base>
std::map<std::string, std::string>
ConvolutionFit<Base>::getAdditionalLogNumbers() const {
auto logs = Base::getAdditionalLogNumbers();
IFunction_sptr function = Base::getProperty("Function");
logs["lorentzians"] = boost::lexical_cast<std::string>(
numberOfFunctions(function, "Lorentzian"));
return logs;
}
template <typename Base>
std::vector<std::string> ConvolutionFit<Base>::getFitParameterNames() const {
auto names = Base::getFitParameterNames();
if (m_deltaUsed)
names.emplace_back("EISF");
return names;
}
// Register the algorithms into the AlgorithmFactory
template class ConvolutionFit<QENSFitSequential>;
template class ConvolutionFit<QENSFitSimultaneous>;
using ConvolutionFitSequential = ConvolutionFit<QENSFitSequential>;
using ConvolutionFitSimultaneous = ConvolutionFit<QENSFitSimultaneous>;
DECLARE_ALGORITHM(ConvolutionFitSequential)
DECLARE_ALGORITHM(ConvolutionFitSimultaneous)
} // namespace Algorithms
} // namespace CurveFitting
} // namespace Mantid