/**
* Executes the algorithm
*/
void PlotAsymmetryByLogValue::exec()
{
m_forward_list = getProperty("ForwardSpectra");
m_backward_list = getProperty("BackwardSpectra");
m_autogroup = ( m_forward_list.size() == 0 && m_backward_list.size() == 0);
//double alpha = getProperty("Alpha");
std::string logName = getProperty("LogValue");
int red = getProperty("Red");
int green = getProperty("Green");
std::string stype = getProperty("Type");
m_int = stype == "Integral";
std::string firstFN = getProperty("FirstRun");
std::string lastFN = getProperty("LastRun");
std::string ext = firstFN.substr(firstFN.find_last_of("."));
firstFN.erase(firstFN.size()-4);
lastFN.erase(lastFN.size()-4);
std::string fnBase = firstFN;
size_t i = fnBase.size()-1;
while(isdigit(fnBase[i])) i--;
if (i == fnBase.size()-1)
{
g_log.error("File name must end with a number.");
throw Exception::FileError("File name must end with a number.",firstFN);
}
fnBase.erase(i+1);
firstFN.erase(0,fnBase.size());
lastFN.erase(0,fnBase.size());
size_t is = atoi(firstFN.c_str()); // starting run number
size_t ie = atoi(lastFN.c_str()); // last run number
int w = static_cast<int>(firstFN.size());
// The number of runs
size_t npoints = ie - is + 1;
// Create the 2D workspace for the output
int nplots = green != EMPTY_INT() ? 4 : 1;
MatrixWorkspace_sptr outWS = WorkspaceFactory::Instance().create("Workspace2D",
nplots, // the number of plots
npoints, // the number of data points on a plot
npoints // it's not a histogram
);
TextAxis* tAxis = new TextAxis(nplots);
if (nplots == 1)
{
tAxis->setLabel(0,"Asymmetry");
}
else
{
tAxis->setLabel(0,"Red-Green");
tAxis->setLabel(1,"Red");
tAxis->setLabel(2,"Green");
tAxis->setLabel(3,"Red+Green");
}
outWS->replaceAxis(1,tAxis);
Progress progress(this,0,1,ie-is+2);
for(size_t i=is; i<=ie; i++)
{
std::ostringstream fn,fnn;
fnn << std::setw(w) << std::setfill('0') << i ;
fn << fnBase << fnn.str() << ext;
// Load a muon nexus file with auto_group set to true
IAlgorithm_sptr loadNexus = createChildAlgorithm("LoadMuonNexus");
loadNexus->setPropertyValue("Filename", fn.str());
loadNexus->setPropertyValue("OutputWorkspace","tmp"+fnn.str());
if (m_autogroup)
loadNexus->setPropertyValue("AutoGroup","1");
loadNexus->execute();
std::string wsProp = "OutputWorkspace";
DataObjects::Workspace2D_sptr ws_red;
DataObjects::Workspace2D_sptr ws_green;
// Run through the periods of the loaded file and do calculations on the selected ones
Workspace_sptr tmp = loadNexus->getProperty(wsProp);
WorkspaceGroup_sptr wsGroup = boost::dynamic_pointer_cast<WorkspaceGroup>(tmp);
if (!wsGroup)
{
ws_red = boost::dynamic_pointer_cast<DataObjects::Workspace2D>(tmp);
TimeSeriesProperty<double>* logp =
dynamic_cast<TimeSeriesProperty<double>*>(ws_red->run().getLogData(logName));
if (!logp)
{
throw std::invalid_argument("Log "+logName+" does not exist or not a double type");
}
double Y,E;
calcIntAsymmetry(ws_red,Y,E);
outWS->dataY(0)[i-is] = Y;
outWS->dataX(0)[i-is] = logp->lastValue();
outWS->dataE(0)[i-is] = E;
}
else
{
for( int period = 1; period <= wsGroup->getNumberOfEntries(); ++period )
{
std::stringstream suffix;
suffix << period;
wsProp = "OutputWorkspace_" + suffix.str();// form the property name for higher periods
// Do only one period
if (green == EMPTY_INT() && period == red)
{
Workspace_sptr tmpff = loadNexus->getProperty(wsProp);
ws_red = boost::dynamic_pointer_cast<DataObjects::Workspace2D>(tmpff);
TimeSeriesProperty<double>* logp =
dynamic_cast<TimeSeriesProperty<double>*>(ws_red->run().getLogData(logName));
if (!logp)
{
throw std::invalid_argument("Log "+logName+" does not exist or not a double type");
}
double Y,E;
calcIntAsymmetry(ws_red,Y,E);
outWS->dataY(0)[i-is] = Y;
outWS->dataX(0)[i-is] = logp->lastValue();
outWS->dataE(0)[i-is] = E;
}
else // red & green
{
if (period == red)
{
Workspace_sptr temp = loadNexus->getProperty(wsProp);
ws_red = boost::dynamic_pointer_cast<Workspace2D>(temp);
}
if (period == green)
{
Workspace_sptr temp = loadNexus->getProperty(wsProp);
ws_green = boost::dynamic_pointer_cast<Workspace2D>(temp);
}
}
}
// red & green claculation
if (green != EMPTY_INT())
{
if (!ws_red || !ws_green)
throw std::invalid_argument("Red or green period is out of range");
TimeSeriesProperty<double>* logp =
dynamic_cast<TimeSeriesProperty<double>*>(ws_red->run().getLogData(logName));
if (!logp)
{
throw std::invalid_argument("Log "+logName+" does not exist or not a double type");
}
double Y,E;
double Y1,E1;
calcIntAsymmetry(ws_red,Y,E);
calcIntAsymmetry(ws_green,Y1,E1);
outWS->dataY(1)[i-is] = Y;
outWS->dataX(1)[i-is] = logp->lastValue();
outWS->dataE(1)[i-is] = E;
outWS->dataY(2)[i-is] = Y1;
outWS->dataX(2)[i-is] = logp->lastValue();
outWS->dataE(2)[i-is] = E1;
outWS->dataY(3)[i-is] = Y + Y1;
outWS->dataX(3)[i-is] = logp->lastValue();
outWS->dataE(3)[i-is] = sqrt(E*E+E1*E1);
// move to last for safety since some grouping takes place in the
// calcIntAsymmetry call below
calcIntAsymmetry(ws_red,ws_green,Y,E);
outWS->dataY(0)[i-is] = Y;
outWS->dataX(0)[i-is] = logp->lastValue();
outWS->dataE(0)[i-is] = E;
}
else if (!ws_red)
throw std::invalid_argument("Red period is out of range");
}
progress.report();
}
outWS->getAxis(0)->title() = logName;
outWS->setYUnitLabel("Asymmetry");
// Assign the result to the output workspace property
setProperty("OutputWorkspace", outWS);
}
/**
* Executes the algorithm
*/
void PlotPeakByLogValue::exec()
{
// Create a list of the input workspace
const std::vector<InputData> wsNames = makeNames();
std::string fun = getPropertyValue("Function");
//int wi = getProperty("WorkspaceIndex");
std::string logName = getProperty("LogValue");
bool sequential = getPropertyValue("FitType") == "Sequential";
bool isDataName = false; // if true first output column is of type string and is the data source name
ITableWorkspace_sptr result = WorkspaceFactory::Instance().createTable("TableWorkspace");
if (logName == "SourceName")
{
result->addColumn("str","Source name");
isDataName = true;
}
else if (logName.empty())
{
result->addColumn("double","axis-1");
}
else
{
result->addColumn("double",logName);
}
// Create an instance of the fitting function to obtain the names of fitting parameters
IFitFunction* ifun = FunctionFactory::Instance().createInitialized(fun);
if (!ifun)
{
throw std::invalid_argument("Fitting function failed to initialize");
}
for(size_t iPar=0;iPar<ifun->nParams();++iPar)
{
result->addColumn("double",ifun->parameterName(iPar));
result->addColumn("double",ifun->parameterName(iPar)+"_Err");
}
result->addColumn("double","Chi_squared");
delete ifun;
setProperty("OutputWorkspace",result);
double dProg = 1./static_cast<double>(wsNames.size());
double Prog = 0.;
for(int i=0;i<static_cast<int>(wsNames.size());++i)
{
InputData data = getWorkspace(wsNames[i]);
if (!data.ws)
{
g_log.warning() << "Cannot access workspace " << wsNames[i].name << '\n';
continue;
}
if (data.i < 0 && data.indx.empty())
{
g_log.warning() << "Zero spectra selected for fitting in workspace " << wsNames[i].name << '\n';
continue;
}
int j,jend;
if (data.i >= 0)
{
j = data.i;
jend = j + 1;
}
else
{// no need to check data.indx.empty()
j = data.indx.front();
jend = data.indx.back() + 1;
}
dProg /= abs(jend - j);
for(;j < jend;++j)
{
// Find the log value: it is either a log-file value or simply the workspace number
double logValue;
if (logName.empty())
{
API::Axis* axis = data.ws->getAxis(1);
logValue = (*axis)(j);
}
else if (logName != "SourceName")
{
Kernel::Property* prop = data.ws->run().getLogData(logName);
if (!prop)
{
throw std::invalid_argument("Log value "+logName+" does not exist");
}
TimeSeriesProperty<double>* logp =
dynamic_cast<TimeSeriesProperty<double>*>(prop);
logValue = logp->lastValue();
}
std::string resFun = fun;
std::vector<double> errors;
double chi2;
try
{
// Fit the function
API::IAlgorithm_sptr fit = createSubAlgorithm("Fit");
fit->initialize();
fit->setProperty("InputWorkspace",data.ws);
//fit->setPropertyValue("InputWorkspace",data.ws->getName());
fit->setProperty("WorkspaceIndex",j);
fit->setPropertyValue("Function",fun);
fit->setPropertyValue("StartX",getPropertyValue("StartX"));
fit->setPropertyValue("EndX",getPropertyValue("EndX"));
fit->setPropertyValue("Minimizer",getPropertyValue("Minimizer"));
fit->setPropertyValue("CostFunction",getPropertyValue("CostFunction"));
fit->execute();
resFun = fit->getPropertyValue("Function");
errors = fit->getProperty("Errors");
chi2 = fit->getProperty("OutputChi2overDoF");
}
catch(...)
{
g_log.error("Error in Fit subalgorithm");
throw;
}
if (sequential)
{
fun = resFun;
}
// Extract the fitted parameters and put them into the result table
TableRow row = result->appendRow();
if (isDataName)
{
row << wsNames[i].name;
}
else
{
row << logValue;
}
ifun = FunctionFactory::Instance().createInitialized(resFun);
for(size_t iPar=0;iPar<ifun->nParams();++iPar)
{
row << ifun->getParameter(iPar) << errors[iPar];
}
row << chi2;
delete ifun;
Prog += dProg;
progress(Prog);
interruption_point();
} // for(;j < jend;++j)
}
}
