42def PixelNNMonitorHistograms(helper, alg):
43 """Pixel-NN performance histograms.
44
45 NumberNet/ - number-of-particles (cluster-splitting) classification.
46 PositionNet/ - per-particle position residual / pull vs the Geant4 truth,
47 split by true multiplicity (1/2/3 particle). The position net
48 is run with the track estimate as input (as in on-track reco)
49 but the residual is always against truth, never the track.
50 """
51
52
53 num = helper.addGroup(alg, 'PixelNNNumber', '/PixelNNMonitor/NumberNet/')
54 num.defineHistogram('predN;h_predN', type='TH1I',
55 title='Predicted N particles;N_{pred};Clusters', xbins=3, xmin=0.5, xmax=3.5)
56 for p in (1, 2, 3):
57 num.defineHistogram(f'prob{p};h_prob{p}', type='TH1F',
58 title=f'P({p} particle);P({p});Clusters', xbins=100, xmin=0, xmax=1)
59 num.defineHistogram('nClusters;h_nClusters', type='TH1I',
60 title='Clusters per event;N_{clusters};Events', xbins=200, xmin=0, xmax=20000)
61
62 num.defineHistogram('trueN,predNconf;h_confusion', type='TH2I',
63 title='Number-net confusion;N_{true};N_{pred}',
64 xbins=3, xmin=0.5, xmax=3.5, ybins=3, ymin=0.5, ymax=3.5)
65 num.defineHistogram('isCorrect;h_correct', type='TH1I',
66 title='Correctly classified;correct;Clusters', xbins=2, xmin=-0.5, xmax=1.5)
67 num.defineHistogram('eta,isCorrect;h_acc_vs_eta', type='TProfile',
68 title='Classification accuracy vs #eta;#eta;accuracy', xbins=50, xmin=-3, xmax=3)
69 num.defineHistogram('nCell,isCorrect;h_acc_vs_nCell', type='TProfile',
70 title='Classification accuracy vs cluster size;N_{cells};accuracy',
71 xbins=15, xmin=0.5, xmax=15.5)
72 num.defineHistogram('trueN,probMulti;h_probMulti_vs_trueN', type='TH2F',
73 title='Split discriminant P(#geq2) vs N_{true};N_{true};P(#geq2)',
74 xbins=3, xmin=0.5, xmax=3.5, ybins=50, ymin=0, ymax=1)
75
76
77
78
79
80 sf = helper.addGroup(alg, 'PixelNNSplitFrac', '/PixelNNMonitor/SplitFraction/')
81 ptEdges = [0.5 * 100.0 ** (i / 20.0) for i in range(21)]
82 for var, edges, label in (
83 ('trackPt', ptEdges, 'p_{T}^{lead} [GeV]'),
84 ('trkPhi', {'nb': 24, 'lo': -0.6, 'hi': 0.6}, 'track incidence #phi [rad]'),
85 ('trkTheta', {'nb': 24, 'lo': -1.2, 'hi': 1.2}, 'track incidence #theta [rad]'),
86 ('clusEta', {'nb': 40, 'lo': -4.0, 'hi': 4.0}, 'cluster #eta')):
87 for curve, cname in (('truthSplit', 'Truth'), ('nnSplit', 'NN'),
88 ('recoSplit', 'Reco')):
89 binning = ({'xbins': edges} if isinstance(edges, list) else
90 {'xbins': edges['nb'], 'xmin': edges['lo'],
91 'xmax': edges['hi']})
92 sf.defineHistogram(f'{var},{curve};h_{curve}_vs_{var}',
93 type='TProfile',
94 title=f'{cname} split fraction;{label};split fraction',
95 **binning)
96
97
98
99
100 dq = helper.addGroup(alg, 'PixelNNPosDQ', '/PixelNNMonitor/PositionNet/DQ/')
101 dq.defineHistogram('posDeltaXWide;h_deltaX_wide', type='TH1F',
102 title='#DeltaX wide range;#DeltaX [mm];Entries', xbins=200, xmin=-1.0, xmax=1.0)
103 dq.defineHistogram('posDeltaYWide;h_deltaY_wide', type='TH1F',
104 title='#DeltaY wide range;#DeltaY [mm];Entries', xbins=200, xmin=-5.0, xmax=5.0)
105 dq.defineHistogram('posErrXWide;h_errX_wide', type='TH1F',
106 title='#sigma_{X} wide range;#sigma_{X} [mm];Entries', xbins=200, xmin=0, xmax=1.0)
107 dq.defineHistogram('posErrYWide;h_errY_wide', type='TH1F',
108 title='#sigma_{Y} wide range;#sigma_{Y} [mm];Entries', xbins=200, xmin=0, xmax=5.0)
109 dq.defineHistogram('posPrecX;h_precX', type='TH1F',
110 title='Precision X (1/#sigma^{2}_{X});Prec_{X} [mm^{-2}];Entries', xbins=200, xmin=0, xmax=1e6)
111 dq.defineHistogram('posPrecY;h_precY', type='TH1F',
112 title='Precision Y (1/#sigma^{2}_{Y});Prec_{Y} [mm^{-2}];Entries', xbins=200, xmin=0, xmax=1e5)
113
114
115 ex = helper.addGroup(alg, 'PixelNNExtremes', '/PixelNNMonitor/Extremes/')
116 ex.defineHistogram('evtMinErrX;h_evtMinErrX', type='TH1F',
117 title='Per-event min #sigma_{X};min #sigma_{X} [mm];Events', xbins=100, xmin=0, xmax=0.05)
118 ex.defineHistogram('evtMaxErrX;h_evtMaxErrX', type='TH1F',
119 title='Per-event max #sigma_{X};max #sigma_{X} [mm];Events', xbins=100, xmin=0, xmax=0.5)
120 ex.defineHistogram('evtMinErrY;h_evtMinErrY', type='TH1F',
121 title='Per-event min #sigma_{Y};min #sigma_{Y} [mm];Events', xbins=100, xmin=0, xmax=0.1)
122 ex.defineHistogram('evtMaxErrY;h_evtMaxErrY', type='TH1F',
123 title='Per-event max #sigma_{Y};max #sigma_{Y} [mm];Events', xbins=100, xmin=0, xmax=2.0)
124 ex.defineHistogram('evtMaxAbsDeltaX;h_evtMaxAbsDeltaX', type='TH1F',
125 title='Per-event max |#DeltaX|;max |#DeltaX| [mm];Events', xbins=100, xmin=0, xmax=0.5)
126 ex.defineHistogram('evtMaxAbsDeltaY;h_evtMaxAbsDeltaY', type='TH1F',
127 title='Per-event max |#DeltaY|;max |#DeltaY| [mm];Events', xbins=100, xmin=0, xmax=2.0)
128 ex.defineHistogram('evtMaxProb2;h_evtMaxProb2', type='TH1F',
129 title='Per-event max P(2);max P(2);Events', xbins=100, xmin=0, xmax=1)
130
131 for n in (1, 2, 3):
132 _bookPositionGroup(helper, alg, n)
133
134 summ = helper.addGroup(alg, 'PixelNNPosSummary',
135 '/PixelNNMonitor/PositionNet/Summary/')
136 summ.defineHistogram('posN,pullX;h_pullX_vs_N', type='TH2F',
137 title='Pull X vs multiplicity;N_{true};pull_{X}',
138 xbins=3, xmin=0.5, xmax=3.5, ybins=50, ymin=-5, ymax=5)
139 summ.defineHistogram('posN,pullY;h_pullY_vs_N', type='TH2F',
140 title='Pull Y vs multiplicity;N_{true};pull_{Y}',
141 xbins=3, xmin=0.5, xmax=3.5, ybins=50, ymin=-5, ymax=5)
142 summ.defineHistogram('posN,errX;h_errX_vs_N', type='TProfile',
143 title='Mean #sigma_{X} vs multiplicity;N_{true};#sigma_{X} [#mum]',
144 xbins=3, xmin=0.5, xmax=3.5)
145 summ.defineHistogram('posN,errY;h_errY_vs_N', type='TProfile',
146 title='Mean #sigma_{Y} vs multiplicity;N_{true};#sigma_{Y} [#mum]',
147 xbins=3, xmin=0.5, xmax=3.5)
148
149
1.16.1