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[RF] Fix codegen of RooMultiVarGaussian #20518

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[RF] Fix codegen of RooMultiVarGaussian #20518

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4 changes: 2 additions & 2 deletions roofit/roofitcore/inc/RooFit/Detail/MathFuncs.h
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Original file line number Diff line number Diff line change
Expand Up @@ -787,8 +787,8 @@ double bernsteinIntegral(double xlo, double xhi, double xmin, double xmax, Doubl
return norm * (xmax - xmin);
}

template <typename DoubleArray>
double multiVarGaussian(int n, DoubleArray x, DoubleArray mu, DoubleArray covI)
template <typename XArray, typename MuArray, typename CovArray>
double multiVarGaussian(int n, XArray x, MuArray mu, CovArray covI)
{
double result = 0.0;

Expand Down
50 changes: 38 additions & 12 deletions roofit/roofitcore/test/testRooFuncWrapper.cxx
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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@
#include <RooHistFunc.h>
#include <RooHistPdf.h>
#include <RooMinimizer.h>
#include <RooMultiVarGaussian.h>
#include <RooPoisson.h>
#include <RooPolynomial.h>
#include <RooRealSumPdf.h>
Expand Down Expand Up @@ -448,12 +449,8 @@ FactoryTestParams param11{"ClassFactory1D",
RooRealVar mu{"mu", "mu", 5, 0, 10};
RooRealVar sigma{"sigma", "sigma", 2.0, 0.1, 10};

// TODO: When Clad issue #635 is solved, we can
// actually use a complete Gaussian here, also
// with sigma.
std::unique_ptr<RooAbsPdf> pdf{RooClassFactory::makePdfInstance(
//"model", "std::exp(-0.5 * (x - mu)*(x - mu) / (sigma * sigma))", {x, mu, sigma})};
"model", "std::exp(-0.5 * (x - mu)*(x - mu))", {x, mu})};
"model", "std::exp(-0.5 * (x - mu)*(x - mu) / (sigma * sigma))", {x, mu, sigma})};
ws.import(*pdf);
ws.defineSet("observables", "x");
},
Expand All @@ -463,6 +460,34 @@ FactoryTestParams param11{"ClassFactory1D",
5e-3, // increase tolerance because the numeric integration algos are still different
/*randomizeParameters=*/true};

FactoryTestParams param12{"RooMultiVarGaussian",
[](RooWorkspace &ws) {
RooRealVar x("x", "x variable", -5, 5);
RooRealVar y("y", "y variable", -5, 5);

RooArgList vars(x, y);

RooRealVar mean_x("mean_x", "mean of x", 1.0, -5, 5);
RooRealVar mean_y("mean_y", "mean of y", -1.0, -5, 5);
RooArgList means(mean_x, mean_y);

TMatrixDSym cov(2);
cov(0, 0) = 1.0; // Var(x)
cov(1, 1) = 1.5; // Var(y)
cov(0, 1) = 0.3; // Cov(x,y)
cov(1, 0) = 0.3;

RooMultiVarGaussian mvgauss("model", "Multivariate Gaussian", vars, means, cov);

ws.import(mvgauss);
ws.defineSet("observables", vars);
},
[](RooAbsPdf &pdf, RooAbsData &data, RooWorkspace &, RooFit::EvalBackend backend) {
return std::unique_ptr<RooAbsReal>{pdf.createNLL(data, backend)};
},
5e-3, // increase tolerance because the numeric integration algos are still different
/*randomizeParameters=*/true};

FactoryTestParams makeTestParams(const char *name, std::vector<std::string> const &expressions,
double fitResultTolerance, bool randomizeParameters = true)
{
Expand Down Expand Up @@ -507,19 +532,19 @@ auto testValues = testing::Values(
5e-3, true),
makeTestParams("RooCBShape",
{"x[0., -200., 200.]", "x0[100., -200., 200.]",
"CBShape::model(x, x0, sigma[2., 1.E-6, 100.], alpha[1., 1.E-6, 100.], n[1., 1.E-6, 100.])"},
"CBShape::model(x, x0, sigma[2., 1.E-1, 100.], alpha[1., 1.E-1, 100.], n[1., 1.E-1, 100.])"},
6e-3, true),
makeTestParams("RooBernstein",
{"Bernstein::model(x[0., 100.], {c0[0.3, 0., 10.], c1[0.7, 0., 10.], c2[0.2, 0., 10.]})"}, 6e-3,
true),
// We're testing several Landau configurations, because the underlying
// ROOT::Math::landau_cdf is defined piecewise. Like this, we're covering
// all possible code paths in the pullback.
makeTestParams("RooLandau1", {"Landau::model(x[5., 0., 30.], ml[6., 1., 30.], sl[1., 0.01, 50.])"}, 6e-3, false),
makeTestParams("RooLandau2", {"Landau::model(x[5., 0., 30.], ml[6., 1., 30.], sl[2.1, 0.01, 50.])"}, 6e-3, false),
makeTestParams("RooLandau3", {"Landau::model(x[5., 0., 30.], ml[6., 1., 30.], sl[10., 0.01, 50.])"}, 6e-3, false),
makeTestParams("RooLandau4", {"Landau::model(x[5., 0., 30.], ml[6., 1., 30.], sl[0.3, 0.01, 50.])"}, 6e-3, false),
makeTestParams("RooLandau5", {"Landau::model(x[5., 0., 30.], ml[6., 1., 30.], sl[0.07, 0.01, 50.])"}, 6e-3, false),
makeTestParams("RooLandau1", {"Landau::model(x[5., 0., 30.], ml[6., 1., 30.], sl[1., 0.01, 50.])"}, 7e-3, false),
makeTestParams("RooLandau2", {"Landau::model(x[5., 0., 30.], ml[6., 1., 30.], sl[2.1, 0.01, 50.])"}, 7e-3, false),
makeTestParams("RooLandau3", {"Landau::model(x[5., 0., 30.], ml[6., 1., 30.], sl[10., 0.01, 50.])"}, 7e-3, false),
makeTestParams("RooLandau4", {"Landau::model(x[5., 0., 30.], ml[6., 1., 30.], sl[0.3, 0.01, 50.])"}, 7e-3, false),
makeTestParams("RooLandau5", {"Landau::model(x[5., 0., 30.], ml[6., 1., 30.], sl[0.07, 0.01, 50.])"}, 7e-3, false),
makeTestParams(
"RooRealSumPdf1",
{"Gaussian::gx(x[-10,10],m[0],1.0)", "Chebychev::ch(x,{0.1,0.2,-0.3})", "RealSumPdf::model({gx, ch}, {f[0,1]})"},
Expand All @@ -530,7 +555,8 @@ auto testValues = testing::Values(
{"x[-10., 10.]", "mean[1., -10., 10.]", "sigma[1., 0.1, 10.]",
"expr::gauss_func('std::exp(-0.5*(x - mean) * (x - mean) / (sigma * sigma))', {x, mean, sigma})",
"WrapperPdf::model(gauss_func)"},
6e-3, true));
6e-3, true),
param12);

INSTANTIATE_TEST_SUITE_P(RooFuncWrapper, FactoryTest, testValues,
[](testing::TestParamInfo<FactoryTest::ParamType> const &paramInfo) {
Expand Down
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