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67 lines
2.1 KiB
67 lines
2.1 KiB
import numpy as np
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from math import sqrt
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# angular parameters for each folding (appearing in this order in the input files)
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pars = {
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0: ['S1s', 'S3', 'S6s', 'S9'],
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1: ['S1s', 'S3', 'S4'],
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2: ['S1s', 'S3', 'S5'],
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3: ['S1s', 'S3', 'S7'],
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4: ['S1s', 'S3', 'S8'],
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}
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import glob
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files = {}
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# get input files for given folding (if more than 1 for same folding, take first)
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for fold in pars.keys():
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files[fold] = glob.glob('./SensitivityFromToys/*folding{}.txt'.format(fold))[0]
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u = {} #fill with all uncertainties from toys
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for fold in pars.keys():
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d = np.genfromtxt(files[fold], comments='#')
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i = 0
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for angpar in pars[fold]:
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i = i+1 #header
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for q2bin in range(8):
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assert d[i][0]==q2bin
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u[(fold, angpar, q2bin)] = d[i][1]
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i = i+1
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# simple conversions of uncertainties for FL and AFB
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def FLerr(S1serr):
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return S1serr*4/3
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def AFBerr(S6serr):
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return S6serr*3/4
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def get_ordvals(year, scale):
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# take various uncertainties from different foldings
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ordvals = []
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for q2 in [0, 1, 2, 3, 4, 6, 7]: # not including q2bin 5 cause too close to ccbar
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ordvals = ordvals + [
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year,
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FLerr(u[(1, 'S1s', q2)])*scale,
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u[(3, 'S3', q2)]*scale,
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u[(1, 'S4', q2)]*scale,
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u[(2, 'S5', q2)]*scale,
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AFBerr(u[(0, 'S6s', q2)])*scale,
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u[(3, 'S7', q2)]*scale,
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u[(4, 'S8', q2)]*scale,
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u[(0, 'S9', q2)]*scale,
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]
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return ordvals
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with open('./measurements/Bp2Kstmumu_skeleton.yml', 'r') as myfile:
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skeleton = myfile.read()
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ordvals = get_ordvals(2016, 1) #no scaling for 2016
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with open('measurements/Bp2Kstmumu_2016.yml', "w") as text_file:
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print(skeleton.format(*ordvals), file=text_file)
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lumi2016 = 5.2
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lumi2018 = 9.0
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addKppi0 = 2 # factor 2 larger stat?
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statfactor = lumi2018/lumi2016 * addKppi0
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ordvals = get_ordvals(2018, 1/sqrt(statfactor)) #no scaling for 2016
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with open('measurements/Bp2Kstmumu_2018andpi0.yml', "w") as text_file:
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print(skeleton.format(*ordvals), file=text_file)
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