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Petr Jacka
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[RDF] Adding tests
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‎bindings/distrdf/test/test_operation.py‎

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@@ -112,3 +112,14 @@ def test_histond_without_model(self):
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"""Creating a histogram without model raises ValueError."""
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with self.assertRaises(ValueError):
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_ = Operation.create_op("HistoND", ["a", "b", "c", "d"])
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def test_histonsparsed_with_thnsparsedmodel(self):
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"""THnDModel"""
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op = Operation.create_op("HistoNSparseD", ROOT.RDF.THnSparseDModel(), ["a", "b", "c", "d"])
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self.assertIsInstance(op, Operation.Histo)
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self.assertEqual(op.name, "HistoNSparseD")
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def test_histonsparsed_without_model(self):
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"""Creating a histogram without model raises ValueError."""
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with self.assertRaises(ValueError):
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_ = Operation.create_op("HistoNSparseD", ["a", "b", "c", "d"])

‎roottest/python/distrdf/backends/check_reducer_merge.py‎

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@@ -125,6 +125,28 @@ def test_histond_merge(self, payload):
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assert histond_distrdf.GetEntries() == histond_rdf.GetEntries()
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assert histond_distrdf.GetNbins() == histond_rdf.GetNbins()
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def test_histonsparsed_merge(self, payload):
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"""Check the working of HistoND merge operation in the reducer."""
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nbins = (10, 10, 10, 10)
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xmin = (0., 0., 0., 0.)
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xmax = (100., 100., 100., 100.)
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modelTHNSparseD = ("name", "title", 4, nbins, xmin, xmax)
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colnames = ("x0", "x1", "x2", "x3")
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connection, _ = payload
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distrdf = ROOT.RDataFrame(100, executor=connection)
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rdf = ROOT.RDataFrame(100)
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distrdf_withcols = self.define_four_columns(distrdf, colnames)
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rdf_withcols = self.define_four_columns(rdf, colnames)
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histond_distrdf = distrdf_withcols.HistoNSparseD(modelTHNSparseD, colnames)
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histond_rdf = rdf_withcols.HistoNSparseD(modelTHNSparseD, colnames)
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assert histond_distrdf.GetEntries() == histond_rdf.GetEntries()
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assert histond_distrdf.GetNbins() == histond_rdf.GetNbins()
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def test_profile1d_merge(self, payload):
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"""Check the working of Profile1D merge operation in the reducer."""
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# Operations with DistRDF

‎tree/dataframe/test/dataframe_cloning.cxx‎

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@@ -188,6 +188,26 @@ TEST(RDataFrameCloning, HistoND)
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EXPECT_EQ(df.GetNRuns(), 1);
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}
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TEST(RDataFrameCloning, HistoNSparseD)
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{
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ROOT::RDataFrame df{100};
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auto col1 = df.Define("x0", [](ULong64_t e) { return double(e); }, {"rdfentry_"});
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auto col2 = col1.Define("x1", [](ULong64_t e) { return double(e); }, {"rdfentry_"});
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auto col3 = col2.Define("x2", [](ULong64_t e) { return double(e); }, {"rdfentry_"});
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auto col4 = col3.Define("x3", [](ULong64_t e) { return double(e); }, {"rdfentry_"});
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int nbins[4] = {10, 10, 10, 10};
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double xmin[4] = {0., 0., 0., 0.};
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double xmax[4] = {100., 100., 100., 100.};
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auto histo =
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col4.HistoNSparseD<double, double, double, double>({"name", "title", 4, nbins, xmin, xmax}, {"x0", "x1", "x2", "x3"});
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auto clone = CloneResultAndAction(histo);
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EXPECT_EQ((*histo).GetEntries(), 100);
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EXPECT_EQ((*clone).GetEntries(), 100);
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EXPECT_EQ(df.GetNRuns(), 1);
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}
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TEST(RDataFrameCloning, Profile1D)
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{
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ROOT::RDataFrame df{100};

‎tree/dataframe/test/dataframe_histomodels.cxx‎

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@@ -336,6 +336,70 @@ TEST(RDataFrameHistoModels, HistoND)
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}
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}
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TEST(RDataFrameHistoModels, HistoNSparseD)
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{
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ROOT::RDataFrame tdf(10);
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auto x = 0.;
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auto d = tdf.Define("x0", [&x]() { return x++; })
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.Define("x1", [&x]() { return x + .1; })
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.Define("x2", [&x]() { return x + .1; })
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.Define("x3", [&x]() { return x + .1; });
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int nbins[4] = {10, 5, 2, 2};
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double xmin[4] = {0., 0., 0., 0.};
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double xmax[4] = {10., 10., 10., 10.};
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auto h1 = d.HistoNSparseD(::THnSparseD("h1", "h1", 4, nbins, xmin, xmax), {"x0", "x1", "x2", "x3"});
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auto h2 = d.HistoNSparseD({"h2", "h2", 4, nbins, xmin, xmax}, {"x0", "x1", "x2", "x3"});
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std::vector<double> edges0{1, 2, 3, 4, 5, 6, 10};
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std::vector<double> edges1{1.1, 2.1, 3.1, 4.1, 5.1, 6.1, 10.1};
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std::vector<double> edges2{1.2, 2.2, 3.2, 4.2, 5.2, 6.2, 10.2};
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std::vector<double> edges3{1.3, 2.3, 3.3, 4.3, 5.3, 6.3, 10.3};
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std::vector<std::vector<double>> edges = {edges0, edges1, edges2, edges3};
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int nbinse[4];
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for (unsigned int idim = 0; idim < edges.size(); ++idim) {
361+
nbinse[idim] = edges[idim].size() - 1;
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}
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auto h1e = d.HistoNSparseD(::THnSparseD("h1e", "h1e", 4, nbinse, edges), {"x0", "x1", "x2", "x3"});
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auto h2e = d.HistoNSparseD({"h2e", "h2e", 4, nbinse, edges}, {"x0", "x1", "x2", "x3"});
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THnSparseDModel m0("m0", "m0", 4, nbins, xmin, xmax);
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THnSparseDModel m1(::THnSparseD("m1", "m1", 4, nbins, xmin, xmax));
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auto hm0 = d.HistoNSparseD(m0, {"x0", "x1", "x2", "x3"});
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auto hm1 = d.HistoNSparseD(m1, {"x0", "x1", "x2", "x3"});
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auto hm0w = d.HistoNSparseD(m0, {"x0", "x1", "x2", "x3", "x3"});
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auto hm1w = d.HistoNSparseD(m1, {"x0", "x1", "x2", "x3", "x3"});
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std::vector<double> ref0({0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.});
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std::vector<double> ref1({0., 2., 4., 6., 8., 10.});
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std::vector<double> ref2({0., 5., 10.});
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std::vector<double> ref3({0., 5., 10.});
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std::vector<std::vector<double>> ref = {ref0, ref1, ref2, ref3};
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for (unsigned int idim = 0; idim < edges.size(); ++idim) {
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CheckBins(h1e->GetAxis(idim), edges[idim]);
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}
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for (unsigned int idim = 0; idim < edges.size(); ++idim) {
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CheckBins(h2e->GetAxis(idim), edges[idim]);
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}
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for (unsigned int idim = 0; idim < ref.size(); ++idim) {
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CheckBins(h1->GetAxis(idim), ref[idim]);
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}
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for (unsigned int idim = 0; idim < ref.size(); ++idim) {
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CheckBins(h2->GetAxis(idim), ref[idim]);
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}
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for (unsigned int idim = 0; idim < ref.size(); ++idim) {
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CheckBins(hm0->GetAxis(idim), ref[idim]);
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}
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for (unsigned int idim = 0; idim < ref.size(); ++idim) {
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CheckBins(hm0w->GetAxis(idim), ref[idim]);
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}
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}
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TEST(RDataFrameHisto, FillVecBool)
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{
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const auto n = 10u;

‎tree/dataframe/test/dataframe_merge_results.cxx‎

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@@ -161,6 +161,34 @@ TEST(RDataFrameMergeResults, MergeHistoND)
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EXPECT_EQ(mh.GetEntries(), 200);
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}
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TEST(RDataFrameMergeResults, MergeHistoNSparseD)
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{
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ROOT::RDataFrame df{100};
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auto col1 = df.Define("x0", [](ULong64_t e) { return double(e); }, {"rdfentry_"});
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auto col2 = col1.Define("x1", [](ULong64_t e) { return double(e); }, {"rdfentry_"});
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auto col3 = col2.Define("x2", [](ULong64_t e) { return double(e); }, {"rdfentry_"});
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auto col4 = col3.Define("x3", [](ULong64_t e) { return double(e); }, {"rdfentry_"});
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int nbins[4] = {10, 10, 10, 10};
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double xmin[4] = {0., 0., 0., 0.};
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double xmax[4] = {100., 100., 100., 100.};
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auto hist1 =
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col4.HistoNSparseD<double, double, double, double>({"name", "title", 4, nbins, xmin, xmax}, {"x0", "x1", "x2", "x3"});
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auto hist2 =
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col4.HistoNSparseD<double, double, double, double>({"name", "title", 4, nbins, xmin, xmax}, {"x0", "x1", "x2", "x3"});
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auto mh1 = GetMergeableValue(hist1);
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auto mh2 = GetMergeableValue(hist2);
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auto mergedptr = MergeValues(std::move(mh1), std::move(mh2));
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const auto &mh = mergedptr->GetValue();
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EXPECT_EQ(mh.GetEntries(), 200);
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}
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TEST(RDataFrameMergeResults, MergeProfile1D)
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{
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ROOT::RDataFrame df{100};

‎tree/dataframe/test/dataframe_vary.cxx‎

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@@ -1348,6 +1348,25 @@ TEST_P(RDFVary, VaryHistos)
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res = hNs["x:1"].Projection(3);
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EXPECT_DOUBLE_EQ(res->GetMean(), 5.);
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delete res;
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auto hNSparse = df.HistoNSparseD<ROOT::RVecI, ROOT::RVecI, ROOT::RVecI, ROOT::RVecI>({"", "", 4, nbins, xmin, xmax},
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{"x", "x", "x", "x"});
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auto hNSparses = VariationsFor(hNSparse);
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auto res = hNSparse->Projection(3);
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EXPECT_DOUBLE_EQ(res->GetMean(), 5.);
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delete res;
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res = hNSparses["nominal"].Projection(3);
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EXPECT_DOUBLE_EQ(res->GetMean(), 5.);
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delete res;
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res = hNSparses["x:0"].Projection(3);
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EXPECT_DOUBLE_EQ(res->GetMean(), 0.);
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delete res;
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res = hNSparses["x:1"].Projection(3);
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EXPECT_DOUBLE_EQ(res->GetMean(), 5.);
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delete res;
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}
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TEST_P(RDFVary, VaryMax)

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