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-249
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‎PWGDQ/Core/DQMlResponse.h‎

Lines changed: 91 additions & 94 deletions
Original file line numberDiff line numberDiff line change
@@ -17,25 +17,24 @@
1717
#ifndef PWGDQ_CORE_DQMLRESPONSE_H_
1818
#define PWGDQ_CORE_DQMLRESPONSE_H_
1919

20+
#include "Tools/ML/MlResponse.h"
21+
2022
#include <map>
2123
#include <string>
2224
#include <vector>
2325

24-
#include "Tools/ML/MlResponse.h"
25-
2626
// Fill the map of available input features
2727
// the key is the feature's name (std::string)
2828
// the value is the corresponding value in EnumInputFeatures
29-
#define FILL_MAP(FEATURE) \
30-
{ \
29+
#define FILL_MAP(FEATURE) \
30+
{ \
3131
#FEATURE, static_cast<uint8_t>(InputFeatures::FEATURE) \
3232
}
3333

34-
3534
namespace o2::analysis
3635
{
3736

38-
enum class InputFeatures : uint8_t { //refer to DielectronsAll
37+
enum class InputFeatures : uint8_t { // refer to DielectronsAll
3938
fMass = 0,
4039
fPt,
4140
fEta,
@@ -69,37 +68,36 @@ enum class InputFeatures : uint8_t { //refer to DielectronsAll
6968
};
7069

7170
static const std::map<InputFeatures, std::string> gFeatureNameMap = {
72-
{InputFeatures::fMass, "fMass"},
73-
{InputFeatures::fPt, "fPt"},
74-
{InputFeatures::fEta, "fEta"},
75-
{InputFeatures::fPhi, "fPhi"},
76-
{InputFeatures::fPt1, "fPt1"},
77-
{InputFeatures::fITSChi2NCl1, "fITSChi2NCl1"},
78-
{InputFeatures::fTPCNClsCR1, "fTPCNClsCR1"},
79-
{InputFeatures::fTPCNClsFound1, "fTPCNClsFound1"},
80-
{InputFeatures::fTPCChi2NCl1, "fTPCChi2NCl1"},
81-
{InputFeatures::fDcaXY1, "fDcaXY1"},
82-
{InputFeatures::fDcaZ1, "fDcaZ1"},
83-
{InputFeatures::fTPCNSigmaEl1, "fTPCNSigmaEl1"},
84-
{InputFeatures::fTPCNSigmaPi1, "fTPCNSigmaPi1"},
85-
{InputFeatures::fTPCNSigmaPr1, "fTPCNSigmaPr1"},
86-
{InputFeatures::fTOFNSigmaEl1, "fTOFNSigmaEl1"},
87-
{InputFeatures::fTOFNSigmaPi1, "fTOFNSigmaPi1"},
88-
{InputFeatures::fTOFNSigmaPr1, "fTOFNSigmaPr1"},
89-
{InputFeatures::fPt2, "fPt2"},
90-
{InputFeatures::fITSChi2NCl2, "fITSChi2NCl2"},
91-
{InputFeatures::fTPCNClsCR2, "fTPCNClsCR2"},
92-
{InputFeatures::fTPCNClsFound2, "fTPCNClsFound2"},
93-
{InputFeatures::fTPCChi2NCl2, "fTPCChi2NCl2"},
94-
{InputFeatures::fDcaXY2, "fDcaXY2"},
95-
{InputFeatures::fDcaZ2, "fDcaZ2"},
96-
{InputFeatures::fTPCNSigmaEl2, "fTPCNSigmaEl2"},
97-
{InputFeatures::fTPCNSigmaPi2, "fTPCNSigmaPi2"},
98-
{InputFeatures::fTPCNSigmaPr2, "fTPCNSigmaPr2"},
99-
{InputFeatures::fTOFNSigmaEl2, "fTOFNSigmaEl2"},
100-
{InputFeatures::fTOFNSigmaPi2, "fTOFNSigmaPi2"},
101-
{InputFeatures::fTOFNSigmaPr2, "fTOFNSigmaPr2"}
102-
};
71+
{InputFeatures::fMass, "fMass"},
72+
{InputFeatures::fPt, "fPt"},
73+
{InputFeatures::fEta, "fEta"},
74+
{InputFeatures::fPhi, "fPhi"},
75+
{InputFeatures::fPt1, "fPt1"},
76+
{InputFeatures::fITSChi2NCl1, "fITSChi2NCl1"},
77+
{InputFeatures::fTPCNClsCR1, "fTPCNClsCR1"},
78+
{InputFeatures::fTPCNClsFound1, "fTPCNClsFound1"},
79+
{InputFeatures::fTPCChi2NCl1, "fTPCChi2NCl1"},
80+
{InputFeatures::fDcaXY1, "fDcaXY1"},
81+
{InputFeatures::fDcaZ1, "fDcaZ1"},
82+
{InputFeatures::fTPCNSigmaEl1, "fTPCNSigmaEl1"},
83+
{InputFeatures::fTPCNSigmaPi1, "fTPCNSigmaPi1"},
84+
{InputFeatures::fTPCNSigmaPr1, "fTPCNSigmaPr1"},
85+
{InputFeatures::fTOFNSigmaEl1, "fTOFNSigmaEl1"},
86+
{InputFeatures::fTOFNSigmaPi1, "fTOFNSigmaPi1"},
87+
{InputFeatures::fTOFNSigmaPr1, "fTOFNSigmaPr1"},
88+
{InputFeatures::fPt2, "fPt2"},
89+
{InputFeatures::fITSChi2NCl2, "fITSChi2NCl2"},
90+
{InputFeatures::fTPCNClsCR2, "fTPCNClsCR2"},
91+
{InputFeatures::fTPCNClsFound2, "fTPCNClsFound2"},
92+
{InputFeatures::fTPCChi2NCl2, "fTPCChi2NCl2"},
93+
{InputFeatures::fDcaXY2, "fDcaXY2"},
94+
{InputFeatures::fDcaZ2, "fDcaZ2"},
95+
{InputFeatures::fTPCNSigmaEl2, "fTPCNSigmaEl2"},
96+
{InputFeatures::fTPCNSigmaPi2, "fTPCNSigmaPi2"},
97+
{InputFeatures::fTPCNSigmaPr2, "fTPCNSigmaPr2"},
98+
{InputFeatures::fTOFNSigmaEl2, "fTOFNSigmaEl2"},
99+
{InputFeatures::fTOFNSigmaPi2, "fTOFNSigmaPi2"},
100+
{InputFeatures::fTOFNSigmaPr2, "fTOFNSigmaPr2"}};
103101

104102
template <typename TypeOutputScore = float>
105103
class DQMlResponse : public MlResponse<TypeOutputScore>
@@ -111,67 +109,66 @@ class DQMlResponse : public MlResponse<TypeOutputScore>
111109
virtual ~DQMlResponse() = default;
112110

113111
/// Method to get the input features vector needed for ML inference
114-
/// \return inputFeatures vector
115-
template <typename T1, typename T2, typename TValues>
116-
std::vector<float> getInputFeatures(const T1& t1,
117-
const T2& t2,
118-
const TValues& fg) const
119-
{
120-
using Accessor = std::function<float(const T1&, const T2&, const TValues&)>;
121-
static const std::unordered_map<std::string, Accessor> featureMap{
122-
{"fMass", [](auto const&, auto const&, auto const& v){ return v[VarManager::kMass]; }},
123-
{"fPt", [](auto const&, auto const&, auto const& v){ return v[VarManager::kPt]; }},
124-
{"fEta", [](auto const&, auto const&, auto const& v){ return v[VarManager::kEta]; }},
125-
{"fPhi", [](auto const&, auto const&, auto const& v){ return v[VarManager::kPhi]; }},
126-
127-
{"fPt1", [](auto const& t1, auto const&, auto const&) { return t1.pt(); }},
128-
{"fITSChi2NCl1", [](auto const& t1, auto const&, auto const&) { return t1.itsChi2NCl(); }},
129-
{"fTPCNClsCR1", [](auto const& t1, auto const&, auto const&) { return t1.tpcNClsCrossedRows(); }},
112+
/// \return inputFeatures vector
113+
template <typename T1, typename T2, typename TValues>
114+
std::vector<float> getInputFeatures(const T1& t1,
115+
const T2& t2,
116+
const TValues& fg) const
117+
{
118+
using Accessor = std::function<float(const T1&, const T2&, const TValues&)>;
119+
static const std::unordered_map<std::string, Accessor> featureMap{
120+
{"fMass", [](auto const&, auto const&, auto const& v) { return v[VarManager::kMass]; }},
121+
{"fPt", [](auto const&, auto const&, auto const& v) { return v[VarManager::kPt]; }},
122+
{"fEta", [](auto const&, auto const&, auto const& v) { return v[VarManager::kEta]; }},
123+
{"fPhi", [](auto const&, auto const&, auto const& v) { return v[VarManager::kPhi]; }},
124+
125+
{"fPt1", [](auto const& t1, auto const&, auto const&) { return t1.pt(); }},
126+
{"fITSChi2NCl1", [](auto const& t1, auto const&, auto const&) { return t1.itsChi2NCl(); }},
127+
{"fTPCNClsCR1", [](auto const& t1, auto const&, auto const&) { return t1.tpcNClsCrossedRows(); }},
130128
{"fTPCNClsFound1", [](auto const& t1, auto const&, auto const&) { return t1.tpcNClsFound(); }},
131-
{"fTPCChi2NCl1", [](auto const& t1, auto const&, auto const&) { return t1.tpcChi2NCl(); }},
132-
{"fDcaXY1", [](auto const& t1, auto const&, auto const&) { return t1.dcaXY(); }},
133-
{"fDcaZ1", [](auto const& t1, auto const&, auto const&) { return t1.dcaZ(); }},
134-
{"fTPCNSigmaEl1", [](auto const& t1, auto const&, auto const&) { return t1.tpcNSigmaEl(); }},
135-
{"fTPCNSigmaPi1", [](auto const& t1, auto const&, auto const&) { return t1.tpcNSigmaPi(); }},
136-
{"fTPCNSigmaPr1", [](auto const& t1, auto const&, auto const&) { return t1.tpcNSigmaPr(); }},
137-
{"fTOFNSigmaEl1", [](auto const& t1, auto const&, auto const&) { return t1.tofNSigmaEl(); }},
138-
{"fTOFNSigmaPi1", [](auto const& t1, auto const&, auto const&) { return t1.tofNSigmaPi(); }},
139-
{"fTOFNSigmaPr1", [](auto const& t1, auto const&, auto const&) { return t1.tofNSigmaPr(); }},
140-
141-
{"fPt2", [](auto const&, auto const& t2, auto const&) { return t2.pt(); }},
142-
{"fITSChi2NCl2", [](auto const&, auto const& t2, auto const&) { return t2.itsChi2NCl(); }},
143-
{"fTPCNClsCR2", [](auto const&, auto const& t2, auto const&) { return t2.tpcNClsCrossedRows(); }},
129+
{"fTPCChi2NCl1", [](auto const& t1, auto const&, auto const&) { return t1.tpcChi2NCl(); }},
130+
{"fDcaXY1", [](auto const& t1, auto const&, auto const&) { return t1.dcaXY(); }},
131+
{"fDcaZ1", [](auto const& t1, auto const&, auto const&) { return t1.dcaZ(); }},
132+
{"fTPCNSigmaEl1", [](auto const& t1, auto const&, auto const&) { return t1.tpcNSigmaEl(); }},
133+
{"fTPCNSigmaPi1", [](auto const& t1, auto const&, auto const&) { return t1.tpcNSigmaPi(); }},
134+
{"fTPCNSigmaPr1", [](auto const& t1, auto const&, auto const&) { return t1.tpcNSigmaPr(); }},
135+
{"fTOFNSigmaEl1", [](auto const& t1, auto const&, auto const&) { return t1.tofNSigmaEl(); }},
136+
{"fTOFNSigmaPi1", [](auto const& t1, auto const&, auto const&) { return t1.tofNSigmaPi(); }},
137+
{"fTOFNSigmaPr1", [](auto const& t1, auto const&, auto const&) { return t1.tofNSigmaPr(); }},
138+
139+
{"fPt2", [](auto const&, auto const& t2, auto const&) { return t2.pt(); }},
140+
{"fITSChi2NCl2", [](auto const&, auto const& t2, auto const&) { return t2.itsChi2NCl(); }},
141+
{"fTPCNClsCR2", [](auto const&, auto const& t2, auto const&) { return t2.tpcNClsCrossedRows(); }},
144142
{"fTPCNClsFound2", [](auto const&, auto const& t2, auto const&) { return t2.tpcNClsFound(); }},
145-
{"fTPCChi2NCl2", [](auto const&, auto const& t2, auto const&) { return t2.tpcChi2NCl(); }},
146-
{"fDcaXY2", [](auto const&, auto const& t2, auto const&) { return t2.dcaXY(); }},
147-
{"fDcaZ2", [](auto const&, auto const& t2, auto const&) { return t2.dcaZ(); }},
148-
{"fTPCNSigmaEl2", [](auto const&, auto const& t2, auto const&) { return t2.tpcNSigmaEl(); }},
149-
{"fTPCNSigmaPi2", [](auto const&, auto const& t2, auto const&) { return t2.tpcNSigmaPi(); }},
150-
{"fTPCNSigmaPr2", [](auto const&, auto const& t2, auto const&) { return t2.tpcNSigmaPr(); }},
151-
{"fTOFNSigmaEl2", [](auto const&, auto const& t2, auto const&) { return t2.tofNSigmaEl(); }},
152-
{"fTOFNSigmaPi2", [](auto const&, auto const& t2, auto const&) { return t2.tofNSigmaPi(); }},
153-
{"fTOFNSigmaPr2", [](auto const&, auto const& t2, auto const&) { return t2.tofNSigmaPr(); }}
154-
};
155-
156-
std::vector<float> dqInputFeatures;
157-
dqInputFeatures.reserve(MlResponse<TypeOutputScore>::mCachedIndices.size());
158-
159-
for (auto idx : MlResponse<TypeOutputScore>::mCachedIndices) {
160-
auto enumIdx = static_cast<InputFeatures>(idx);
161-
const auto& name = gFeatureNameMap.at(enumIdx);
162-
163-
auto acc = featureMap.find(name);
164-
if (acc == featureMap.end()) {
165-
LOG(error) << "Missing accessor for " << name;
166-
continue;
167-
} else {
168-
dqInputFeatures.push_back(acc->second(t1, t2, fg));
143+
{"fTPCChi2NCl2", [](auto const&, auto const& t2, auto const&) { return t2.tpcChi2NCl(); }},
144+
{"fDcaXY2", [](auto const&, auto const& t2, auto const&) { return t2.dcaXY(); }},
145+
{"fDcaZ2", [](auto const&, auto const& t2, auto const&) { return t2.dcaZ(); }},
146+
{"fTPCNSigmaEl2", [](auto const&, auto const& t2, auto const&) { return t2.tpcNSigmaEl(); }},
147+
{"fTPCNSigmaPi2", [](auto const&, auto const& t2, auto const&) { return t2.tpcNSigmaPi(); }},
148+
{"fTPCNSigmaPr2", [](auto const&, auto const& t2, auto const&) { return t2.tpcNSigmaPr(); }},
149+
{"fTOFNSigmaEl2", [](auto const&, auto const& t2, auto const&) { return t2.tofNSigmaEl(); }},
150+
{"fTOFNSigmaPi2", [](auto const&, auto const& t2, auto const&) { return t2.tofNSigmaPi(); }},
151+
{"fTOFNSigmaPr2", [](auto const&, auto const& t2, auto const&) { return t2.tofNSigmaPr(); }}};
152+
153+
std::vector<float> dqInputFeatures;
154+
dqInputFeatures.reserve(MlResponse<TypeOutputScore>::mCachedIndices.size());
155+
156+
for (auto idx : MlResponse<TypeOutputScore>::mCachedIndices) {
157+
auto enumIdx = static_cast<InputFeatures>(idx);
158+
const auto& name = gFeatureNameMap.at(enumIdx);
159+
160+
auto acc = featureMap.find(name);
161+
if (acc == featureMap.end()) {
162+
LOG(error) << "Missing accessor for " << name;
163+
continue;
164+
} else {
165+
dqInputFeatures.push_back(acc->second(t1, t2, fg));
166+
}
169167
}
168+
return dqInputFeatures;
170169
}
171-
return dqInputFeatures;
172-
}
173170

174-
protected:
171+
protected:
175172
void setAvailableInputFeatures()
176173
{
177174
MlResponse<TypeOutputScore>::mAvailableInputFeatures = {
@@ -212,4 +209,4 @@ std::vector<float> getInputFeatures(const T1& t1,
212209

213210
#undef FILL_MAP
214211

215-
#endif // PWGDQ_CORE_DQMLRESPONSE_H_
212+
#endif // PWGDQ_CORE_DQMLRESPONSE_H_

‎PWGDQ/Macros/bdtCut.json‎

Lines changed: 53 additions & 43 deletions
Original file line numberDiff line numberDiff line change
@@ -1,46 +1,56 @@
11
{
2-
"TestCut": {
3-
"type": "Binary",
4-
"title": "MyBDTModel",
5-
"inputFeatures": [ "fPt1",
6-
"fITSChi2NCl1",
7-
"fTPCNClsCR1",
8-
"fTPCNClsFound1",
9-
"fTPCChi2NCl1",
10-
"fDcaXY1",
11-
"fDcaZ1",
12-
"fTPCNSigmaEl1",
13-
"fTPCNSigmaPi1",
14-
"fTPCNSigmaPr1",
15-
"fTOFNSigmaEl1",
16-
"fTOFNSigmaPi1",
17-
"fTOFNSigmaPr1",
18-
"fPt2",
19-
"fITSChi2NCl2",
20-
"fTPCNClsCR2",
21-
"fTPCNClsFound2",
22-
"fTPCChi2NCl2",
23-
"fDcaXY2",
24-
"fDcaZ2",
25-
"fTPCNSigmaEl2",
26-
"fTPCNSigmaPi2",
27-
"fTPCNSigmaPr2",
28-
"fTOFNSigmaEl2",
29-
"fTOFNSigmaPi2",
30-
"fTOFNSigmaPr2"],
31-
"modelFiles": [
32-
"cent_30_50_pt0_2_onnx.onnx",
33-
"cent_30_50_pt2_20_onnx.onnx"
34-
],
35-
"AddMLCut-pTBin1": {
36-
"pTMin": 0,
37-
"pTMax": 2,
38-
"AddMLCut-background": { "var": "kBdtBackground", "cut": 0.5, "exclude": false }
39-
},
40-
"AddMLCut-pTBin2": {
41-
"pTMin": 2,
42-
"pTMax": 20,
43-
"AddMLCut-background": { "var": "kBdtBackground", "cut": 0.5, "exclude": false }
2+
"TestCut": {
3+
"type": "Binary",
4+
"title": "MyBDTModel",
5+
"inputFeatures": [
6+
"fPt1",
7+
"fITSChi2NCl1",
8+
"fTPCNClsCR1",
9+
"fTPCNClsFound1",
10+
"fTPCChi2NCl1",
11+
"fDcaXY1",
12+
"fDcaZ1",
13+
"fTPCNSigmaEl1",
14+
"fTPCNSigmaPi1",
15+
"fTPCNSigmaPr1",
16+
"fTOFNSigmaEl1",
17+
"fTOFNSigmaPi1",
18+
"fTOFNSigmaPr1",
19+
"fPt2",
20+
"fITSChi2NCl2",
21+
"fTPCNClsCR2",
22+
"fTPCNClsFound2",
23+
"fTPCChi2NCl2",
24+
"fDcaXY2",
25+
"fDcaZ2",
26+
"fTPCNSigmaEl2",
27+
"fTPCNSigmaPi2",
28+
"fTPCNSigmaPr2",
29+
"fTOFNSigmaEl2",
30+
"fTOFNSigmaPi2",
31+
"fTOFNSigmaPr2"
32+
],
33+
"modelFiles": [
34+
"cent_30_50_pt0_2_onnx.onnx",
35+
"cent_30_50_pt2_20_onnx.onnx"
36+
],
37+
"AddMLCut-pTBin1": {
38+
"pTMin": 0,
39+
"pTMax": 2,
40+
"AddMLCut-background": {
41+
"var": "kBdtBackground",
42+
"cut": 0.5,
43+
"exclude": false
44+
}
45+
},
46+
"AddMLCut-pTBin2": {
47+
"pTMin": 2,
48+
"pTMax": 20,
49+
"AddMLCut-background": {
50+
"var": "kBdtBackground",
51+
"cut": 0.5,
52+
"exclude": false
53+
}
54+
}
4455
}
45-
}
4656
}

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