From b6d19f39658ad3aba44309d9898a850b8cb7df28 Mon Sep 17 00:00:00 2001
From: Samuel Jackson <samuel.jackson@stfc.ac.uk>
Date: Thu, 13 Mar 2014 12:01:25 +0000
Subject: [PATCH] Refs #9174 Add unit test for new options.
---
.../test/PlotPeakByLogValueTest.h | 78 +++++++++++++++++++
1 file changed, 78 insertions(+)
diff --git a/Code/Mantid/Framework/CurveFitting/test/PlotPeakByLogValueTest.h b/Code/Mantid/Framework/CurveFitting/test/PlotPeakByLogValueTest.h
index a4b8a125c48..b194f691b94 100644
--- a/Code/Mantid/Framework/CurveFitting/test/PlotPeakByLogValueTest.h
+++ b/Code/Mantid/Framework/CurveFitting/test/PlotPeakByLogValueTest.h
@@ -15,6 +15,7 @@
#include "MantidAPI/FunctionFactory.h"
#include "MantidAPI/WorkspaceGroup.h"
#include "MantidKernel/TimeSeriesProperty.h"
+#include "MantidKernel/UnitFactory.h"
#include "MantidTestHelpers/WorkspaceCreationHelper.h"
#include <sstream>
@@ -389,6 +390,53 @@ public:
TS_ASSERT( fits->getNames().size() == 3 );
}
+
+ void test_createOutputWithExtraOutputOptions()
+ {
+ auto ws = createTestWorkspace();
+ AnalysisDataService::Instance().add( "PLOTPEAKBYLOGVALUETEST_WS", ws );
+ PlotPeakByLogValue alg;
+ alg.initialize();
+ alg.setPropertyValue("Input","PLOTPEAKBYLOGVALUETEST_WS,v0:2");
+ alg.setPropertyValue("OutputWorkspace","PlotPeakResult");
+ alg.setProperty("PassWSIndexToFunction",true);
+ alg.setProperty("CreateOutput", true);
+ alg.setProperty("OutputCompositeMembers", true);
+ alg.setProperty("ConvolveMembers", true);
+ alg.setPropertyValue("Function","name=LinearBackground,A0=0,A1=0;"
+ "(composite=Convolution,FixResolution=true,NumDeriv=true;"
+ "name=Resolution,Workspace=PLOTPEAKBYLOGVALUETEST_WS,WorkspaceIndex=0;"
+ "name=Gaussian,Height=3000,PeakCentre=6493,Sigma=50;);");
+ alg.execute();
+
+ TS_ASSERT( alg.isExecuted() );
+
+ TWS_type result = WorkspaceCreationHelper::getWS<TableWorkspace>("PlotPeakResult");
+ TS_ASSERT( result );
+
+ auto matrices = AnalysisDataService::Instance().retrieveWS<const WorkspaceGroup>("PlotPeakResult_NormalisedCovarianceMatrices");
+ auto params = AnalysisDataService::Instance().retrieveWS<const WorkspaceGroup>("PlotPeakResult_Parameters");
+ auto fits = AnalysisDataService::Instance().retrieveWS<const WorkspaceGroup>("PlotPeakResult_Workspaces");
+
+ TS_ASSERT( matrices );
+ TS_ASSERT( params );
+ TS_ASSERT( fits );
+
+ TS_ASSERT( matrices->getNames().size() == 2 );
+ TS_ASSERT( params->getNames().size() == 2 );
+ TS_ASSERT( fits->getNames().size() == 2 );
+
+ auto wsNames = fits->getNames();
+ for (size_t i=0; i< wsNames.size(); ++i)
+ {
+ auto fit = AnalysisDataService::Instance().retrieveWS<const MatrixWorkspace>(wsNames[i]);
+ TS_ASSERT( fit );
+ TS_ASSERT( fit->getNumberHistograms() == 5);
+ }
+
+ AnalysisDataService::Instance().clear();
+ }
+
private:
WorkspaceGroup_sptr m_wsg;
@@ -415,6 +463,36 @@ private:
}
}
+ MatrixWorkspace_sptr createTestWorkspace()
+ {
+ const int numHists(2);
+ const int numBins(2000);
+ MatrixWorkspace_sptr testWS = WorkspaceCreationHelper::create2DWorkspaceWithFullInstrument(numHists, numBins, true);
+ testWS->getAxis(0)->unit() = Mantid::Kernel::UnitFactory::Instance().create("TOF");
+ MantidVecPtr xdata;
+ xdata.access().resize(numBins+1);
+ // Update X data to a sensible values. Looks roughly like the MARI binning
+ // Update the Y values. We don't care about errors here
+
+ // We'll simply use a gaussian as a test
+ const double peakOneCentre(6493.0), sigmaSqOne(250*250.), peakTwoCentre(10625.), sigmaSqTwo(50*50);
+ const double peakOneHeight(3000.), peakTwoHeight(1000.);
+ for( int i = 0; i <= numBins; ++i)
+ {
+ const double xValue = 5.0 + 5.5*i;
+ if( i < numBins )
+ {
+ testWS->dataY(0)[i] = peakOneHeight * exp(-0.5*pow(xValue - peakOneCentre, 2.)/sigmaSqOne);
+ testWS->dataY(1)[i] = peakTwoHeight * exp(-0.5*pow(xValue - peakTwoCentre, 2.)/sigmaSqTwo);
+
+ }
+ xdata.access()[i] = xValue;
+ }
+ testWS->setX(0, xdata);
+ testWS->setX(1, xdata);
+ return testWS;
+ }
+
void deleteData()
{
FrameworkManager::Instance().deleteWorkspace(m_wsg->getName());
--
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