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"input feature names -- content and order must match the Python training FEATURES list"};
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Configurable<std::vector<std::string>> mlInputFeatures{"mlInputFeatures", {"minv", "deltaEta", "deltaR", "phiv", "rConv", "totE", "e2", "e1", "deltaPhi", "harmonicEt", "m021", "m022", "time1", "time2", "ncell1", "ncell2"}, "input feature names -- content and order must match the Python training FEATURES list"};
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Configurable<std::string> mlModelPathLocal{"mlModelPathLocal", "/data/mhemmer/O2ML/code/conversion_tagging_bdt_conversion_splits_brems.onnx", "local ONNX model path"};
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Configurable<std::vector<std::string>> modelPathsCCDB{"modelPathsCCDB", std::vector<std::string>{"Users/m/mhemmer/EM/ML/"}, "Paths of models on CCDB"};
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Configurable<std::vector<std::string>> onnxFileNames{"onnxFileNames", std::vector<std::string>{"conversion_tagging_bdt_conversion_splits_brems.onnx"}, "ONNX file names for each pT bin (if not from CCDB full path)"};
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Configurable<float> mlThreshold{"mlThreshold", 0.5f, "positive-class score threshold for tagging"};
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Configurable<LabeledArray<double>> cutsMl{"cutsMl", {defaultCutsMl[0].data(), 1, 2, {"pT bin 0"}, {
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Configurable<LabeledArray<double>> cutsMl{"cutsMl", {DefaultCutsMl[0].data(), 1, 2, {"pT bin 0"}, {
} elseif (c1.leptonOrigin == LeptonOrigin::DirectMesonDecay && c2.leptonOrigin == LeptonOrigin::DirectMesonDecay && mcCluster1.mothersIds()[0] == mcCluster2.mothersIds()[0]) { // both cluster are leptons that come from the same meson decay
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mcMother.setCursor(mcCluster1.mothersIds()[0]);
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if (mcMother.daughtersIds().size() == 2) {
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if (mcMother.daughtersIds().size() == 2) {// o2-linter: disable=magic-number (number of daughters)
} elseif (c1.leptonOrigin == LeptonOrigin::Conversion && c2.leptonOrigin == LeptonOrigin::Conversion && mcCluster1.mothersIds()[0] != mcCluster2.mothersIds()[0] && areFromSamePi0) { // both cluster are leptons that come from different conversions that come from the same meson
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