Skip to content

Commit

Permalink
Re #10031. Corrections that use new fitting changes.
Browse files Browse the repository at this point in the history
  • Loading branch information
@mantid-roman
mantid-roman committed Aug 4, 2014
1 parent 620e3b3 commit 7e0fcea
Show file tree
Hide file tree
Showing 3 changed files with 73 additions and 64 deletions.
4 changes: 2 additions & 2 deletions Code/Mantid/Framework/CurveFitting/inc/MantidCurveFitting/FABADAMinimizer.h
View file
Expand Up @@ -48,9 +48,9 @@ class CostFuncLeastSquares;
/// Name of the minimizer.
std::string name() const {return "FABADA";}
/// Initialize minimizer, i.e. pass a function to minimize.
virtual void initialize(API::ICostFunction_sptr function);
virtual void initialize(API::ICostFunction_sptr function, size_t maxIterations);
/// Do one iteration.
virtual bool iterate();
virtual bool iterate(size_t iter);
/// Return current value of the cost function
virtual double costFunctionVal();

Expand Down
94 changes: 48 additions & 46 deletions Code/Mantid/Framework/CurveFitting/src/FABADAMinimizer.cpp
View file
Expand Up @@ -37,7 +37,7 @@ namespace CurveFitting

namespace
{
/// static logger object
// static logger object
Kernel::Logger g_log("FABADAMinimizer");
}

Expand All @@ -49,8 +49,7 @@ DECLARE_FUNCMINIMIZER(FABADAMinimizer, FABADA)
/// Constructor
FABADAMinimizer::FABADAMinimizer()
{
////static_cast<size_t>
declareProperty("Chain length",10000.0,"Length of the converged chain.");
declareProperty("Chain length",static_cast<size_t>(10000),"Length of the converged chain.");
declareProperty("Convergence criteria",0.0001,"Variance in Chi square for considering convergence reached.");
declareProperty(
new API::WorkspaceProperty<>("OutputWorkspacePDF","pdf",Kernel::Direction::Output),
Expand All @@ -59,15 +58,14 @@ FABADAMinimizer::FABADAMinimizer()
new API::WorkspaceProperty<>("OutputWorkspaceChain","chain",Kernel::Direction::Output),
"The name to give the output workspace");
declareProperty(
new API::WorkspaceProperty<>("OutputWorkspaceConverged","conv",Kernel::Direction::Output),
new API::WorkspaceProperty<>("OutputWorkspaceConverged","",Kernel::Direction::Output,API::PropertyMode::Optional),
"The name to give the output workspace");
declareProperty(
new API::WorkspaceProperty<API::ITableWorkspace>("ChiSquareTable","chi2",Kernel::Direction::Output),
"The name to give the output workspace");
declareProperty(
new API::WorkspaceProperty<API::ITableWorkspace>("PdfError","pdfE",Kernel::Direction::Output),
"The name to give the output workspace");
declareProperty("ConvergedChain", true, "Show the coverged part of the chain separately");


}
Expand All @@ -79,7 +77,7 @@ FABADAMinimizer::~FABADAMinimizer()
}

/// Initialize minimizer. Set initial values for all private members.
void FABADAMinimizer::initialize(API::ICostFunction_sptr function)
void FABADAMinimizer::initialize(API::ICostFunction_sptr function, size_t maxIterations)
{

m_leastSquares = boost::dynamic_pointer_cast<CostFuncLeastSquares>(function);
Expand All @@ -91,6 +89,15 @@ FABADAMinimizer::~FABADAMinimizer()
m_counter = 0;
m_leastSquares->getParameters(m_parameters);
API::IFunction_sptr fun = m_leastSquares->getFittingFunction();

if ( fun->nParams() == 0 )
{
throw std::invalid_argument("Function has 0 fitting parameters.");
}

size_t n = getProperty("Chain length");
m_numberIterations = n / fun->nParams();

for (size_t i=0 ; i<m_leastSquares->nParams(); ++i)
{
double p = m_parameters.get(i);
Expand Down Expand Up @@ -143,29 +150,26 @@ FABADAMinimizer::~FABADAMinimizer()
std::vector<double> v;
v.push_back(m_chi2);
m_chain.push_back(v);
double n = getProperty("Chain length");
m_numberIterations = int(n)/(fun->nParams());
m_converged = false;
}



/// Do one iteration. Returns true if iterations to be continued, false if they must stop.
bool FABADAMinimizer::iterate()
bool FABADAMinimizer::iterate(size_t iter)
{
if ( !m_leastSquares )
{
throw std::runtime_error("Cost function isn't set up.");
}


size_t n = m_leastSquares->nParams();
size_t m = n;

// Just for the last iteration. For doing exactly the indicated number of iterations.
if(m_converged && m_counter == (m_numberIterations)){
double t = getProperty("Chain length");
m = int(t)%n;
size_t t = getProperty("Chain length");
m = t % n;
}

// Do one iteration of FABADA's algorithm for each parameter.
Expand All @@ -181,9 +185,7 @@ FABADAMinimizer::~FABADAMinimizer()
mt.seed(123*(int(m_counter)+45*int(i)));
boost::random::normal_distribution<> distr(0,std::abs(m_jump[i]));
step = distr(mt);
if (step == 0) {
step = 0.00000001;
}

}
else {
step = m_jump[i];
Expand Down Expand Up @@ -264,8 +266,13 @@ FABADAMinimizer::~FABADAMinimizer()

///std::cout << std::endl << std::endl << std::endl;// DELETE AT THE END

// Update the jump once each 200 iterations
if (m_counter%200 == 150)
//
const size_t jumpCheckingRate = 200;
//
const double lowJumpLimit = 1e-15;

// Update the jump once each jumpCheckingRate iterations
if (m_counter % jumpCheckingRate == 150)
{
double jnew;
// All this is just a temporal test...
Expand All @@ -280,7 +287,6 @@ FABADAMinimizer::~FABADAMinimizer()
}
if (c>38) {
jnew = m_jump[i]/100;
std::cout << std::endl<< std::endl<< std::endl<< "A;UOSKDV BPA<CNK"<< std::endl<<"ASDBUIVNPA;SJKLASD"<< std::endl<< std::endl;
} // ...untill here.

else {
Expand All @@ -296,10 +302,9 @@ FABADAMinimizer::~FABADAMinimizer()
m_jump[i] = jnew;

// Check if the new jump is too small. It means that it has been a wrong convergence.
if (std::abs(m_jump[i])<0.000000000000000001) {
if (std::abs(m_jump[i])<lowJumpLimit) {
API::IFunction_sptr fun = m_leastSquares->getFittingFunction();
throw std::runtime_error("Wrong convergence for parameter " + fun -> parameterName(i) +". Try to set a proper initial value this parameter" );
return false;
}
}

Expand Down Expand Up @@ -380,7 +385,8 @@ FABADAMinimizer::~FABADAMinimizer()
wsPdfE -> addColumn("double","Left's error");
wsPdfE -> addColumn("double","Rigth's error");

std::vector<double>::iterator pos_min = std::min_element(m_chain[n].begin(),m_chain[n].end()); // Calculate the position of the minimum Chi aquare value
std::vector<double>::iterator pos_min = std::min_element(m_chain[n].begin()+m_conv_point,m_chain[n].end()); // Calculate the position of the minimum Chi aquare value
m_chi2 = *pos_min;


std::vector<double> par_def(n);
Expand Down Expand Up @@ -431,9 +437,7 @@ FABADAMinimizer::~FABADAMinimizer()

// Set and name the two workspaces already calculated.
setProperty("OutputWorkspacePDF",ws);
API::AnalysisDataService::Instance().addOrReplace("Parameters PDF",ws);
setProperty("PdfError",wsPdfE);
API::AnalysisDataService::Instance().addOrReplace("PDF Errors",wsPdfE);

// Create the workspace for the complete parameters' chain (the last histogram is for the Chi square).
size_t chain_length = m_chain[0].size();
Expand All @@ -452,34 +456,32 @@ FABADAMinimizer::~FABADAMinimizer()

// Set and name the workspace for the complete chain
setProperty("OutputWorkspaceChain",wsC);
API::AnalysisDataService::Instance().addOrReplace("Parameters Chain",wsC);

// Read if necessary to show the workspace for the converged part of the chain.
const bool con = getProperty("ConvergedChain");
const bool con = !getPropertyValue("OutputWorkspaceConverged").empty();

if (con)
{
// Create the workspace for the converged part of the chain.
size_t conv_length = (m_counter-1)*n + m;
API::MatrixWorkspace_sptr wsConv = API::WorkspaceFactory::Instance().create("Workspace2D",n+1, conv_length, conv_length);
// Create the workspace for the converged part of the chain.
size_t conv_length = (m_counter-1)*n + m;
API::MatrixWorkspace_sptr wsConv = API::WorkspaceFactory::Instance().create("Workspace2D",n+1, conv_length, conv_length);

// Do one iteration for each parameter plus one for Chi square.
for (size_t j =0; j < n+1; ++j)
{
std::vector<double>::const_iterator first = m_chain[j].begin()+m_conv_point;
std::vector<double>::const_iterator last = m_chain[j].end();
std::vector<double> conv_chain(first, last);
MantidVec & X = wsConv->dataX(j);
MantidVec & Y = wsConv->dataY(j);
for(size_t k=0; k < conv_length; ++k) {
X[k] = double(k);
Y[k] = conv_chain[k];
}
}
// Do one iteration for each parameter plus one for Chi square.
for (size_t j =0; j < n+1; ++j)
{
std::vector<double>::const_iterator first = m_chain[j].begin()+m_conv_point;
std::vector<double>::const_iterator last = m_chain[j].end();
std::vector<double> conv_chain(first, last);
MantidVec & X = wsConv->dataX(j);
MantidVec & Y = wsConv->dataY(j);
for(size_t k=0; k < conv_length; ++k) {
X[k] = double(k);
Y[k] = conv_chain[k];
}
}

// Set and name the workspace for the converged part of the chain.
setProperty("OutputWorkspaceConverged",wsConv);
API::AnalysisDataService::Instance().addOrReplace("Converged Chain",wsConv);
// Set and name the workspace for the converged part of the chain.
setProperty("OutputWorkspaceConverged",wsConv);
}

// Create the workspace for the Chi square values.
Expand Down Expand Up @@ -509,13 +511,13 @@ FABADAMinimizer::~FABADAMinimizer()
API::TableRow row = wsChi2 -> appendRow();
row << *pos_min << Chi2MP << Chi2min_red << Chi2MP_red;
setProperty("ChiSquareTable",wsChi2);
API::AnalysisDataService::Instance().addOrReplace("Chi Square Values",wsChi2);


return false;
}
}
double FABADAMinimizer::costFunctionVal() {
return 0.0;
return m_chi2;
}


Expand Down
39 changes: 23 additions & 16 deletions Code/Mantid/MantidQt/MantidWidgets/src/FitPropertyBrowser.cpp
View file
Expand Up @@ -1101,26 +1101,33 @@ std::string FitPropertyBrowser::minimizer(bool withProperties)const
{
foreach(QtProperty* prop,m_minimizerProperties)
{
minimStr += "," + prop->propertyName() + "=";
if ( prop->propertyManager() == m_intManager )
if ( prop->propertyManager() == m_stringManager )
{
minimStr += QString::number( m_intManager->value(prop) );
}
else if ( prop->propertyManager() == m_doubleManager )
{
minimStr += QString::number( m_doubleManager->value(prop) );
}
else if ( prop->propertyManager() == m_boolManager )
{
minimStr += QString::number( m_boolManager->value(prop) );
}
else if ( prop->propertyManager() == m_stringManager )
{
minimStr += m_stringManager->value(prop);
QString value = m_stringManager->value(prop);
if ( !value.isEmpty() )
{
minimStr += "," + prop->propertyName() + "=" + value;
}
}
else
{
throw std::runtime_error("The fit browser doesn't support the type of minimizer's property " + prop->propertyName().toStdString() );
minimStr += "," + prop->propertyName() + "=";
if ( prop->propertyManager() == m_intManager )
{
minimStr += QString::number( m_intManager->value(prop) );
}
else if ( prop->propertyManager() == m_doubleManager )
{
minimStr += QString::number( m_doubleManager->value(prop) );
}
else if ( prop->propertyManager() == m_boolManager )
{
minimStr += QString::number( m_boolManager->value(prop) );
}
else
{
throw std::runtime_error("The fit browser doesn't support the type of minimizer's property " + prop->propertyName().toStdString() );
}
}
}
}
Expand Down

0 comments on commit 7e0fcea

Please sign in to comment.