EWP-BplusToKstMuMu-AngAna/Code/Selection/flavio/parse_sensitivities.py

import numpy as np
from math import sqrt

# angular parameters for each folding (appearing in this order in the input files)
pars = {
        0: ['S1s', 'S3', 'S6s', 'S9'],
        1: ['S1s', 'S3', 'S4'],
        2: ['S1s', 'S3', 'S5'],
        3: ['S1s', 'S3', 'S7'],
        4: ['S1s', 'S3', 'S8'],
        }

import glob
files = {}
# get input files for given folding (if more than 1 for same folding, take first)
for fold in pars.keys():
    files[fold] = glob.glob('./SensitivityFromToys/*folding{}.txt'.format(fold))[0]

u = {} #fill with all uncertainties from toys
for fold in pars.keys():
    d = np.genfromtxt(files[fold], comments='#') 
    i = 0
    for angpar in pars[fold]:
        i = i+1 #header
        for q2bin in range(8):
            assert d[i][0]==q2bin
            u[(fold, angpar, q2bin)] = d[i][1]
            i = i+1

# simple conversions of uncertainties for FL and AFB
def FLerr(S1serr):
    return S1serr*4/3
def AFBerr(S6serr):
    return S6serr*3/4

def get_ordvals(year, scale):
    # take various uncertainties from different foldings
    ordvals = []
    for q2 in [0, 1, 2, 3, 4, 6, 7]: # not including q2bin 5 cause too close to ccbar
        ordvals = ordvals + [
                year,
                FLerr(u[(1, 'S1s', q2)])*scale, 
                u[(3, 'S3', q2)]*scale, 
                u[(1, 'S4', q2)]*scale, 
                u[(2, 'S5', q2)]*scale, 
                AFBerr(u[(0, 'S6s', q2)])*scale,
                u[(3, 'S7', q2)]*scale,
                u[(4, 'S8', q2)]*scale,
                u[(0, 'S9', q2)]*scale,
                ]
    return ordvals


with open('./measurements/Bp2Kstmumu_skeleton.yml', 'r') as myfile:
    skeleton = myfile.read()

ordvals = get_ordvals(2016, 1) #no scaling for 2016
with open('measurements/Bp2Kstmumu_2016.yml', "w") as text_file:
    print(skeleton.format(*ordvals), file=text_file)

lumi2016 = 5.2
lumi2018 = 9.0
addKppi0 = 2 # factor 2 larger stat?
statfactor = lumi2018/lumi2016 * addKppi0
ordvals = get_ordvals(2018, 1/sqrt(statfactor)) #no scaling for 2016
with open('measurements/Bp2Kstmumu_2018andpi0.yml', "w") as text_file:
    print(skeleton.format(*ordvals), file=text_file)