From 9595c91a1117c29659c82cab5870ca4aafd5debd Mon Sep 17 00:00:00 2001
From: Federico Montesino Pouzols <federico.montesino-pouzols@stfc.ac.uk>
Date: Sat, 29 Aug 2015 09:58:01 +0100
Subject: [PATCH] add new perf test cases, 2x8, but some disabled, re #13349
---
.../Framework/CurveFitting/test/FitTest.h | 169 +++++++++---------
.../CurveFitting/test/FitTestHelpers.h | 2 +
2 files changed, 83 insertions(+), 88 deletions(-)
diff --git a/Code/Mantid/Framework/CurveFitting/test/FitTest.h b/Code/Mantid/Framework/CurveFitting/test/FitTest.h
index 171ec7861ab..d4ce164b490 100644
--- a/Code/Mantid/Framework/CurveFitting/test/FitTest.h
+++ b/Code/Mantid/Framework/CurveFitting/test/FitTest.h
@@ -4,13 +4,11 @@
#include <cxxtest/TestSuite.h>
#include "MantidTestHelpers/FakeObjects.h"
-#include "MantidAPI/AlgorithmManager.h"
#include "MantidAPI/FrameworkManager.h"
-#include "MantidAPI/WorkspaceProperty.h"
-#include "MantidAPI/AnalysisDataService.h"
#include "MantidAPI/IFuncMinimizer.h"
#include "MantidAPI/FuncMinimizerFactory.h"
#include "MantidCurveFitting/Fit.h"
+#include "FitTestHelpers.h"
using namespace Mantid;
using namespace Mantid::CurveFitting;
@@ -137,103 +135,98 @@ public:
static void destroySuite(FitTestPerformance *suite) { delete suite; }
FitTestPerformance() {
- m_smoothWS = generateSmoothCurveWorkspace();
- m_onePeakWS = generatePeaksCurveWorkspace();
+ m_smoothWS = FitTestHelpers::generateCurveDataForFit(
+ FitTestHelpers::SmoothishGaussians);
+
+ m_onePeakWS =
+ FitTestHelpers::generateCurveDataForFit(FitTestHelpers::SingleB2BPeak);
}
- // Equivalent Python script. Fit a back-to-back exponential:
- // Fit(InputWorkspace=pws, Function='name=BackToBackExponential')
- void test_peaks_fit() {
- Fit fit;
- fit.setChild(true);
- fit.initialize();
+ // tests for a single peak (BackToBackExponential)
- // example X0, S values after a good fit are 10079.0, 404.5
- fit.setProperty("Function", "name=BackToBackExponential, X0=8500, S=800");
- fit.setProperty("InputWorkspace", m_onePeakWS);
- // fit.setProperty("MaxIterations", 99);
- fit.setProperty("CreateOutput", true);
+ // LM for Levenberg-Marquardt hereafter
+ void test_fit_peaks_LM() {
+ runFitAlgorithm(m_onePeakWS, FitTestHelpers::SingleB2BPeak,
+ "Levenberg-MarquardtMD");
+ }
- fit.execute();
+ void test_fit_peaks_Simplex() {
+ runFitAlgorithm(m_onePeakWS, FitTestHelpers::SingleB2BPeak, "Simplex");
}
- // Equivalent Python script. Fit with a BSpline function:
- // Fit(InputWorkspace=ws, Function='name=BSpline, Order=40')
- void test_smooth_curve_fit() {
- Fit fit;
- fit.setChild(true);
- fit.initialize();
+ void test_fit_peaks_ConjG_FR() {
+ runFitAlgorithm(m_onePeakWS, FitTestHelpers::SingleB2BPeak,
+ "Conjugate gradient (Fletcher-Reeves imp.)");
+ }
- // From a quick test, order 30 => ~2.5s; order 40 => ~6s; order 50 =>
- // ~14s
- fit.setProperty("Function", "name=BSpline, Order=20, StartX=0, EndX=10");
- fit.setProperty("InputWorkspace", m_smoothWS);
- fit.setProperty("CreateOutput", true);
+ void test_fit_peaks_ConjG_PR() {
+ runFitAlgorithm(m_onePeakWS, FitTestHelpers::SingleB2BPeak,
+ "Conjugate gradient (Polak-Ribiere imp.)");
+ }
- fit.execute();
+ void test_fit_peaks_BFGS() {
+ runFitAlgorithm(m_onePeakWS, FitTestHelpers::SingleB2BPeak, "BFGS");
}
-private:
- // Equivalent python script. Create data with a peak and a bit of noise:
- // pws = CreateSampleWorkspace(Function="User Defined",
- // UserDefinedFunction="name=BackToBackExponential, I=15000, A=1, B=1.2,
- // X0=10000, S=400", NumBanks=1, BankPixelWidth=1, Random=True)
- API::MatrixWorkspace_sptr generatePeaksCurveWorkspace() {
- Mantid::API::IAlgorithm_sptr sampleAlg =
- Mantid::API::AlgorithmManager::Instance().create(
- "CreateSampleWorkspace");
- sampleAlg->initialize();
- sampleAlg->setChild(true);
- sampleAlg->setProperty("Function", "User Defined");
- sampleAlg->setProperty(
- "UserDefinedFunction",
- "name=BackToBackExponential, I=15000, A=1, B=1.2, X0=10000, S=400");
- sampleAlg->setProperty("NumBanks", 1);
- sampleAlg->setProperty("BankPixelWidth", 1);
- sampleAlg->setProperty("XMin", 0.0);
- sampleAlg->setProperty("XMax", 100.0);
- sampleAlg->setProperty("BinWidth", 0.1);
- sampleAlg->setProperty("Random", true);
- sampleAlg->setPropertyValue("OutputWorkspace", "sample_peak_curve_ws");
-
- sampleAlg->execute();
- API::MatrixWorkspace_sptr ws = sampleAlg->getProperty("OutputWorkspace");
-
- return ws;
- }
-
- // Equivalent python script. Create smooth-ish data curve:
- // ws = CreateSampleWorkspace(Function="User Defined",
- // UserDefinedFunction="name=LinearBackground, A0=0.4, A1=0.4; name=Gaussian,
- // PeakCentre=1.3, Height=7, Sigma=1.7; name=Gaussian, PeakCentre=5,
- // Height=10, Sigma=0.7; name=Gaussian, PeakCentre=8, Height=9, Sigma=1.8",
- // NumBanks=1, BankPixelWidth=1, XMin=0, XMax=10, BinWidth=0.01, Random=True)
- API::MatrixWorkspace_sptr generateSmoothCurveWorkspace() {
- Mantid::API::IAlgorithm_sptr sampleAlg =
- Mantid::API::AlgorithmManager::Instance().create(
- "CreateSampleWorkspace");
- sampleAlg->initialize();
- sampleAlg->setChild(true);
- sampleAlg->setProperty("Function", "User Defined");
- sampleAlg->setProperty(
- "UserDefinedFunction",
- "name=LinearBackground, A0=0.4, A1=0.4; name=Gaussian, PeakCentre=1.3, "
- "Height=7, Sigma=1.7; name=Gaussian, PeakCentre=5, Height=10, "
- "Sigma=0.7; name=Gaussian, PeakCentre=8, Height=9, Sigma=1.8");
- sampleAlg->setProperty("NumBanks", 1);
- sampleAlg->setProperty("BankPixelWidth", 1);
- sampleAlg->setProperty("XMin", 0.0);
- sampleAlg->setProperty("XMax", 10.0);
- sampleAlg->setProperty("BinWidth", 0.01);
- sampleAlg->setProperty("Random", true);
- sampleAlg->setPropertyValue("OutputWorkspace", "sample_smooth_curve_ws");
-
- sampleAlg->execute();
- API::MatrixWorkspace_sptr ws = sampleAlg->getProperty("OutputWorkspace");
-
- return ws;
+ void test_fit_peaks_Damping() {
+ runFitAlgorithm(m_onePeakWS, FitTestHelpers::SingleB2BPeak, "Damping");
}
+ void test_fit_peaks_SteepestDescent() {
+ runFitAlgorithm(m_onePeakWS, FitTestHelpers::SingleB2BPeak,
+ "SteepestDescent");
+ }
+
+ // Note: does not converge unless you give a better initial guess of
+ // parameters. So this is testing 500 iterations but not convergence.
+ void test_fit_peaks_FABADA() {
+ runFitAlgorithm(m_onePeakWS, FitTestHelpers::SingleB2BPeak, "FABADA");
+ }
+
+ // tests for a smooth function (2 Gaussians + linear background)
+
+ void test_fit_smooth_LM() {
+ runFitAlgorithm(m_smoothWS, FitTestHelpers::SmoothishGaussians,
+ "Levenberg-MarquardtMD");
+ }
+
+ void test_fit_smooth_Simplex() {
+ runFitAlgorithm(m_smoothWS, FitTestHelpers::SmoothishGaussians, "Simplex");
+ }
+
+ // disabled because it is awfully slow: ~20s while others take <1s
+ void disabled_test_fit_smooth_ConjG_FR() {
+ runFitAlgorithm(m_smoothWS, FitTestHelpers::SmoothishGaussians,
+ "Conjugate gradient (Fletcher-Reeves imp.)");
+ }
+
+ // disabled: awfully slow: ~20s
+ void disabled_test_fit_smooth_ConjG_PR() {
+ runFitAlgorithm(m_smoothWS, FitTestHelpers::SmoothishGaussians,
+ "Conjugate gradient (Polak-Ribiere imp.)");
+ }
+
+ // disabled: slow: ~5s
+ void disabled_test_fit_smooth_BFGS() {
+ runFitAlgorithm(m_smoothWS, FitTestHelpers::SmoothishGaussians, "BFGS");
+ }
+
+ void test_fit_smooth_Damping() {
+ runFitAlgorithm(m_smoothWS, FitTestHelpers::SmoothishGaussians, "Damping");
+ }
+
+ // disabled: too slow: ~17s
+ void disabled_test_fit_smooth_SteepestDescent() {
+ runFitAlgorithm(m_smoothWS, FitTestHelpers::SmoothishGaussians,
+ "SteepestDescent");
+ }
+
+ // disabled: too slow: ~10s (and it doesn't converge)
+ void disabled_test_fit_smooth_FABADA() {
+ runFitAlgorithm(m_smoothWS, FitTestHelpers::SmoothishGaussians, "FABADA");
+ }
+
+private:
API::MatrixWorkspace_sptr m_smoothWS;
API::MatrixWorkspace_sptr m_onePeakWS;
};
diff --git a/Code/Mantid/Framework/CurveFitting/test/FitTestHelpers.h b/Code/Mantid/Framework/CurveFitting/test/FitTestHelpers.h
index 53a2cb0aa7a..e0472d97b39 100644
--- a/Code/Mantid/Framework/CurveFitting/test/FitTestHelpers.h
+++ b/Code/Mantid/Framework/CurveFitting/test/FitTestHelpers.h
@@ -16,6 +16,8 @@ static API::MatrixWorkspace_sptr generatePeaksCurveWorkspace();
static API::MatrixWorkspace_sptr generateSmoothCurveWorkspace();
+/// Run fit on a (single spectrum) matrix workspace, using the given type
+/// of function and minimizer option
static Mantid::API::IAlgorithm_sptr
runFitAlgorithm(MatrixWorkspace_sptr dataToFit, CurveBenchmarks ctype,
const std::string minimizer = "Levenberg-MarquardtMD") {
--
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