Refs #9782. Added Pearson-VII, changed AutoDiffTestAlg

Code/Mantid/Framework/CurveFitting/CMakeLists.txt

@@ -67,6 +67,7 @@ set ( SRC_FILES
 	src/NormaliseByPeakArea.cpp
 	src/PRConjugateGradientMinimizer.cpp
 	src/ParDomain.cpp
+	src/PearsonVIIFamily.cpp
 	src/PlotPeakByLogValue.cpp
 	src/Polynomial.cpp
 	src/ProcessBackground.cpp
@@ -177,6 +178,7 @@ set ( INC_FILES
 	inc/MantidCurveFitting/NormaliseByPeakArea.h
 	inc/MantidCurveFitting/PRConjugateGradientMinimizer.h
 	inc/MantidCurveFitting/ParDomain.h
+	inc/MantidCurveFitting/PearsonVIIFamily.h
 	inc/MantidCurveFitting/PlotPeakByLogValue.h
 	inc/MantidCurveFitting/Polynomial.h
 	inc/MantidCurveFitting/ProcessBackground.h
@@ -276,6 +278,7 @@ set ( TEST_FILES
 	NeutronBk2BkExpConvPVoigtTest.h
 	NormaliseByPeakAreaTest.h
 	PRConjugateGradientTest.h
+	PearsonVIIFamilyTest.h
 	PlotPeakByLogValueTest.h
 	PolynomialTest.h
 	ProcessBackgroundTest.h

Code/Mantid/Framework/CurveFitting/inc/MantidCurveFitting/PearsonVIIFamily.h

@@ -0,0 +1,85 @@
+#ifndef MANTID_CURVEFITTING_PEARSONVIIFAMILY_H_
+#define MANTID_CURVEFITTING_PEARSONVIIFAMILY_H_
+
+#include "MantidKernel/System.h"
+#include "MantidAPI/IFunction1D.h"
+#include "MantidAPI/ParamFunction.h"
+#include "MantidAPI/IFunction1DAutoDiff.h"
+
+
+namespace Mantid
+{
+namespace CurveFitting
+{
+
+  /** PearsonVIIFamily : TODO: DESCRIPTION
+
+    Copyright © 2014 ISIS Rutherford Appleton Laboratory & NScD Oak Ridge National Laboratory
+
+    This file is part of Mantid.
+
+    Mantid is free software; you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation; either version 3 of the License, or
+    (at your option) any later version.
+
+    Mantid is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+    File change history is stored at: <https://github.com/mantidproject/mantid>
+    Code Documentation is available at: <http://doxygen.mantidproject.org>
+  */
+
+namespace Pearsons {
+
+  class DLLExport PearsonVIIHandCoded : public API::IFunction1D, public API::ParamFunction
+  {
+  public:
+    virtual ~PearsonVIIHandCoded() {}
+
+    std::string name() const { return "PearsonVIIHandCoded"; }
+
+    void function1D(double *out, const double *xValues, const size_t nData) const;
+    void functionDeriv1D(API::Jacobian *out, const double *xValues, const size_t nData);
+
+  protected:
+    void init();
+  };
+
+  class DLLExport PearsonVIINumDiff : public API::IFunction1D, public API::ParamFunction
+  {
+  public:
+    virtual ~PearsonVIINumDiff() {}
+
+    std::string name() const { return "PearsonVIINumDiff"; }
+
+    void function1D(double *out, const double *xValues, const size_t nData) const;
+
+  protected:
+    void init();
+  };
+
+  class DLLExport PearsonVIIAutoDiff : virtual public API::IFunction1DAutoDiff, virtual public API::ParamFunction
+  {
+  public:
+      virtual ~PearsonVIIAutoDiff() {}
+
+      std::string name() const { return "PearsonVIIAutoDiff"; }
+
+      void function1DAutoDiff(const API::FunctionDomain1D &domain, std::vector<adept::adouble> &y, const API::AutoDiffParameterAdapter &parameters) const;
+
+  protected:
+      void init();
+
+  };
+
+} // namespace PearsonVIIFamily
+} // namespace CurveFitting
+} // namespace Mantid
+
+#endif  /* MANTID_CURVEFITTING_PEARSONVIIFAMILY_H_ */

Code/Mantid/Framework/CurveFitting/src/AutoDiffTestAlg.cpp

@@ -3,6 +3,7 @@
 #include "MantidCurveFitting/GaussianAutoDiff.h"
 #include "MantidCurveFitting/GaussianHandCoded.h"
 #include "MantidCurveFitting/LorentzianFamily.h"
+#include "MantidCurveFitting/PearsonVIIFamily.h"
 #include "MantidAPI/FunctionDomain1D.h"
 #include "MantidAPI/FunctionValues.h"
 #include "MantidCurveFitting/Jacobian.h"
@@ -60,7 +61,7 @@ const std::string AutoDiffTestAlg::summary() const { return "Test"; }
 void AutoDiffTestAlg::init()
 {
     declareProperty(new WorkspaceProperty<MatrixWorkspace>("InputWorkspace","",Direction::Input), "Data with 20 gaussian peaks.");
-    declareProperty("GaussianParameters", "", "Gaussian parameters (h, x0, s)");
+    declareProperty("GaussianParameters", "", "Function parameters");
     declareProperty(new WorkspaceProperty<MatrixWorkspace>("OutputWorkspace","",Direction::Output), "Data with 20 gaussian peaks.");
     declareProperty("DerivativeType","adept","How to calculate derivatives.");
 
@@ -77,14 +78,17 @@ namespace
   {
     if ( type == "adept" )
     {
-      return IFunction_sptr(new Lorentzians::LorentzianAutoDiff);
-      //return IFunction_sptr(new GaussianAutoDiff);
+      //return IFunction_sptr(new Lorentzians::LorentzianAutoDiff);
+      return IFunction_sptr(new Pearsons::PearsonVIIAutoDiff);
+      return IFunction_sptr(new GaussianAutoDiff);
     } else if ( type == "num") {
-      return IFunction_sptr(new Lorentzians::LorentzianNumDiff);
-      //return IFunction_sptr(new GaussianNumDiff);
+      //return IFunction_sptr(new Lorentzians::LorentzianNumDiff);
+      return IFunction_sptr(new Pearsons::PearsonVIINumDiff);
+      return IFunction_sptr(new GaussianNumDiff);
     }
-    return IFunction_sptr(new Lorentzians::LorentzianHandCoded);
-    //return IFunction_sptr(new GaussianHandCoded);
+    //return IFunction_sptr(new Lorentzians::LorentzianHandCoded);
+    return IFunction_sptr(new Pearsons::PearsonVIIHandCoded);
+    return IFunction_sptr(new GaussianHandCoded);
   }
 }
 
@@ -101,10 +105,10 @@ void AutoDiffTestAlg::exec()
     std::string parameterString = getProperty("GaussianParameters");
     std::vector<double> paramValues = parameterValues(parameterString);
 
-    if(fitData->getNumberHistograms() > 4) {
-        IFunction_sptr f = getFunction(m_derType);
-        f->initialize();
+    IFunction_sptr f = getFunction(m_derType);
+    f->initialize();
 
+    if(fitData->getNumberHistograms() > (f->nParams() + 1)) {
         for(size_t i = 0; i < paramValues.size(); ++i) {
             f->setParameter(i, paramValues[i] - 0.001 * paramValues[i]);
         }
@@ -115,7 +119,7 @@ void AutoDiffTestAlg::exec()
         fitAlgorithm->setProperty("CalcErrors", true);
         fitAlgorithm->setProperty("Function", f);
         fitAlgorithm->setProperty("InputWorkspace", fitData);
-        fitAlgorithm->setProperty("WorkspaceIndex", 4);
+        fitAlgorithm->setProperty("WorkspaceIndex", static_cast<int>(f->nParams() + 1));
 
         fitAlgorithm->execute();
 
@@ -134,7 +138,7 @@ void AutoDiffTestAlg::exec()
 
     FunctionDomain1DVector x(fitData->readX(0));
     FunctionValues y(x);
-    CurveFitting::Jacobian J(x.size(), 3);
+    CurveFitting::Jacobian J(x.size(), g->nParams());
 
     Kernel::Timer timerF;
 
@@ -166,33 +170,15 @@ void AutoDiffTestAlg::exec()
         }
     }
 
-    MantidVec &dfdx0 = t->dataY(1);
-    const MantidVec &dfdx0r = fitData->readY(1);
-    for(size_t i = 0; i < x.size(); ++i) {
-        dfdx0[i] = 1.0 - J.get(i, 1) / dfdx0r[i];
-
-        if(std::isinf(dfdx0[i])) {
-            dfdx0[i] = 0.0;
-        }
-    }
-
-    MantidVec &dfdh = t->dataY(2);
-    const MantidVec &dfdhr = fitData->readY(2);
-    for(size_t i = 0; i < x.size(); ++i) {
-        dfdh[i] = 1.0 - J.get(i, 0) / dfdhr[i];
-
-        if(std::isinf(dfdh[i])) {
-            dfdh[i] = 0.0;
-        }
-    }
-
-    MantidVec &dfds = t->dataY(3);
-    const MantidVec &dfdsr = fitData->readY(3);
-    for(size_t i = 0; i < x.size(); ++i) {
-        dfds[i] = 1.0 - J.get(i, 2) / dfdsr[i];
+    for(size_t j = 1; (j < f->nParams() + 1); ++j) {
+        MantidVec &partialDeriv = t->dataY(j);
+        const MantidVec &reference = fitData->readY(j);
+        for(size_t i = 0; i < partialDeriv.size(); ++i) {
+            partialDeriv[i] = 1.0 - J.get(i, j - 1) / reference[i];
 
-        if(std::isinf(dfds[i])) {
-            dfds[i] = 0.0;
+            if(std::isinf(partialDeriv[i])) {
+                partialDeriv[i] = 0.0;
+            }
         }
     }
 

Code/Mantid/Framework/CurveFitting/src/GaussianAutoDiff.cpp

@@ -30,8 +30,8 @@ void GaussianAutoDiff::function1DAutoDiff(const FunctionDomain1D &domain, std::v
 }
 
 void GaussianAutoDiff::init() {
-    declareParameter("Height");
     declareParameter("PeakCentre");
+    declareParameter("Height");    
     declareParameter("Sigma");
 }
 

Code/Mantid/Framework/CurveFitting/src/GaussianHandCoded.cpp

@@ -43,15 +43,15 @@ using namespace API;
           double term = (xDiff)/sigma;
           double expTerm = exp(-0.5 * term * term);
 
-          out->set(i, 0, expTerm);
-          out->set(i, 1, (height*expTerm*(xDiff))/(sigma * sigma));
+          out->set(i, 0, (height*expTerm*(xDiff))/(sigma * sigma));
+          out->set(i, 1, expTerm);
           out->set(i, 2, (height*expTerm*term * term)/(sigma));
       }
   }
 
   void GaussianHandCoded::init() {
-      declareParameter("Height");
       declareParameter("PeakCentre");
+      declareParameter("Height");      
       declareParameter("Sigma");
   }
 

Code/Mantid/Framework/CurveFitting/src/GaussianNumDiff.cpp

@@ -33,8 +33,8 @@ namespace CurveFitting
   }
 
   void GaussianNumDiff::init() {
-      declareParameter("Height");
       declareParameter("PeakCentre");
+      declareParameter("Height");      
       declareParameter("Sigma");
   }
 

Code/Mantid/Framework/CurveFitting/src/LorentzianFamily.cpp

@@ -32,16 +32,16 @@ void LorentzianHandCoded::functionDeriv1D(Jacobian *out, const double *xValues,
         double num = diff*diff + s * s;
         double ssquared = s * s;
 
-        out->set(i, 0, ssquared / (num));
-        out->set(i, 1, 2 * h * ssquared * diff / (num * num));
+        out->set(i, 0, 2 * h * ssquared * diff / (num * num));
+        out->set(i, 1, ssquared / (num));
         out->set(i, 2, 2 * h * s / num * (1 - ssquared / num));
     }
 }
 
 void LorentzianHandCoded::init()
 {
-    declareParameter("Height");
     declareParameter("Centre");
+    declareParameter("Height");    
     declareParameter("Gamma");
 }
 
@@ -60,8 +60,8 @@ void LorentzianNumDiff::function1D(double *out, const double *xValues, const siz
 
 void LorentzianNumDiff::init()
 {
-    declareParameter("Height");
     declareParameter("Centre");
+    declareParameter("Height");    
     declareParameter("Gamma");
 }
 
@@ -71,7 +71,7 @@ void LorentzianAutoDiff::function1DAutoDiff(const FunctionDomain1D &domain, std:
     adept::adouble x0 = parameters.getParameter("Centre");
     adept::adouble s = parameters.getParameter("Gamma");
 
-    for(size_t i = 0; i < domain.size(); ++i) {
+    for(size_t i = 0; i < y.size(); ++i) {
         adept::adouble diff = domain[i] - x0;
         y[i] = h * s * s / (diff*diff + s * s);
     }
@@ -80,8 +80,8 @@ void LorentzianAutoDiff::function1DAutoDiff(const FunctionDomain1D &domain, std:
 
 void LorentzianAutoDiff::init()
 {
-    declareParameter("Height");
     declareParameter("Centre");
+    declareParameter("Height");    
     declareParameter("Gamma");
 }