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saganattsaganatt
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Remove the multiopt parts from the dbs for now
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-210
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2 files changed

+8
-210
lines changed

‎machine_learning_hep/data/data_run3/database_ml_parameters_LcToPKPi_multiclass_fdd.yml‎

Lines changed: 4 additions & 105 deletions
Original file line numberDiff line numberDiff line change
@@ -341,119 +341,18 @@ LcpKpi:
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opt:
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isFONLLfromROOT: true
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filename_fonll: 'data/fonll/DmesonLcPredictions_13TeV_y05_FFptDepLHCb_BRpythia8_PDG2020.root' # file with FONLL predictions
344-
fonll_particle: ['hLcpkpipred_max', 'hLcpkpifromBpred_max_corr'] # prompt and optionally non-prompt FONLL file
344+
fonll_particle: 'hLcpkpipred'
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fonll_pred: 'max' # edge of the FONLL prediction
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FF: 0.204 # fragmentation fraction
347-
sigma_MB: 57.8e-3 # Minimum Bias cross section (pp) 50.87e-3 [b], 1 for Pb-Pb
347+
sigma_MB: 57.8e-3 # Minimum Bias cross section (pp) 50.87e-3 [b], 1 for Pb-Pb
348348
Taa: 1 # 23260 [b^-1] in 0-10% Pb-Pb, 3917 [b^-1] in 30-50% Pb-Pb, 1 for pp
349349
BR: 6.23e-2 # branching ratio of the decay Lc -> p K- pi+
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f_prompt: 0.9 # estimated fraction of prompt candidates
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bkg_data_fraction: 0.05 # fraction of real data used in the estimation
352-
num_steps: 100 # number of steps used in efficiency and signif. estimation
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signif_thresholds:
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
352+
num_steps: 111 # number of steps used in efficiency and signif. estimation
454353
bkg_function: pol2 # fit function for bkg (among TH1 predefined fit functions, e.g. expo, pol1, pol2, ...)
455354
save_fit: True # save bkg fits with the various cuts on ML output
456-
raahp: [1,1,1,1,1,1,1,1,1,1] # sel_skim_binmin bins
355+
raahp: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1] # sel_skim_binmin bins
457356
presel_gen_eff: "abs(fY) < 0.8"
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#presel_gen_eff: "abs(fY) < 0.8 and abs(fPosZ) < 10"
459358

‎machine_learning_hep/data/data_run3/database_ml_parameters_LcToPKPi_multiclass_ml.yml‎

Lines changed: 4 additions & 105 deletions
Original file line numberDiff line numberDiff line change
@@ -339,119 +339,18 @@ LcpKpi:
339339
opt:
340340
isFONLLfromROOT: true
341341
filename_fonll: 'data/fonll/DmesonLcPredictions_13TeV_y05_FFptDepLHCb_BRpythia8_PDG2020.root' # file with FONLL predictions
342-
fonll_particle: ['hLcpkpipred_max', 'hLcpkpifromBpred_max_corr'] # prompt and optionally non-prompt FONLL file
342+
fonll_particle: 'hLcpkpipred'
343343
fonll_pred: 'max' # edge of the FONLL prediction
344344
FF: 0.204 # fragmentation fraction
345-
sigma_MB: 57.8e-3 # Minimum Bias cross section (pp) 50.87e-3 [b], 1 for Pb-Pb
345+
sigma_MB: 57.8e-3 # Minimum Bias cross section (pp) 50.87e-3 [b], 1 for Pb-Pb
346346
Taa: 1 # 23260 [b^-1] in 0-10% Pb-Pb, 3917 [b^-1] in 30-50% Pb-Pb, 1 for pp
347347
BR: 6.23e-2 # branching ratio of the decay Lc -> p K- pi+
348348
f_prompt: 0.9 # estimated fraction of prompt candidates
349349
bkg_data_fraction: 0.05 # fraction of real data used in the estimation
350-
num_steps: 100 # number of steps used in efficiency and signif. estimation
351-
signif_thresholds:
352-
- prompt:
353-
y_min: 0.0
354-
y_max: 0.45
355-
x_min: 0.0
356-
x_max: 0.2
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non-prompt:
358-
y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
364-
y_max: 0.45
365-
x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
378-
y_min: 0.6
379-
y_max: 1.0
380-
x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
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y_max: 0.45
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x_min: 0.0
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x_max: 0.2
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non-prompt:
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y_min: 0.6
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y_max: 1.0
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x_min: 0.0
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x_max: 0.1
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- prompt:
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y_min: 0.0
394-
y_max: 0.45
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x_min: 0.0
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x_max: 0.2
397-
non-prompt:
398-
y_min: 0.6
399-
y_max: 1.0
400-
x_min: 0.0
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x_max: 0.1
402-
- prompt:
403-
y_min: 0.0
404-
y_max: 0.45
405-
x_min: 0.0
406-
x_max: 0.2
407-
non-prompt:
408-
y_min: 0.6
409-
y_max: 1.0
410-
x_min: 0.0
411-
x_max: 0.1
412-
- prompt:
413-
y_min: 0.0
414-
y_max: 0.45
415-
x_min: 0.0
416-
x_max: 0.2
417-
non-prompt:
418-
y_min: 0.6
419-
y_max: 1.0
420-
x_min: 0.0
421-
x_max: 0.1
422-
- prompt:
423-
y_min: 0.0
424-
y_max: 0.45
425-
x_min: 0.0
426-
x_max: 0.2
427-
non-prompt:
428-
y_min: 0.6
429-
y_max: 1.0
430-
x_min: 0.0
431-
x_max: 0.1
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- prompt:
433-
y_min: 0.0
434-
y_max: 0.45
435-
x_min: 0.0
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x_max: 0.2
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non-prompt:
438-
y_min: 0.6
439-
y_max: 1.0
440-
x_min: 0.0
441-
x_max: 0.1
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- prompt:
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y_min: 0.0
444-
y_max: 0.45
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x_min: 0.0
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x_max: 0.2
447-
non-prompt:
448-
y_min: 0.6
449-
y_max: 1.0
450-
x_min: 0.0
451-
x_max: 0.1
350+
num_steps: 111 # number of steps used in efficiency and signif. estimation
452351
bkg_function: pol2 # fit function for bkg (among TH1 predefined fit functions, e.g. expo, pol1, pol2, ...)
453352
save_fit: True # save bkg fits with the various cuts on ML output
454-
raahp: [1,1,1,1,1,1,1,1,1,1] # sel_skim_binmin bins
353+
raahp: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1] # sel_skim_binmin bins
455354
presel_gen_eff: "abs(fY) < 0.8"
456355
#presel_gen_eff: "abs(fY) < 0.8 and abs(fPosZ) < 10"
457356

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