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atlas 13tev ttb hadr implementation #1973

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Original file line number Diff line number Diff line change
@@ -0,0 +1,139 @@
import yaml
import numpy as np
from utils import covmat_to_artunc as cta
from utils import matlist_to_matrix as mtm
from utils import concat_matrices as cm


covmat_mtt = []
covmat_mtt_norm = []
covmat_ytt = []
covmat_ytt_norm = []
covmat_501 = []
covmat_502 = []
covmat_503 = []
covmat_504 = []
covmat_505 = []
covmat_506 = []
covmat_492 = []
covmat_493 = []
covmat_494 = []
covmat_495 = []
covmat_496 = []
covmat_497 = []

covariance_matrix_mtt="rawdata/Table464.yaml"
with open(covariance_matrix_mtt, 'r') as file1:
input1 = yaml.safe_load(file1)
for i in range(81):
covmat_mtt.append(input1['dependent_variables'][0]['values'][i]['value'])
artunc_mtt = cta(9, covmat_mtt)


covariance_matrix_mtt_norm="rawdata/Table462.yaml"
with open(covariance_matrix_mtt_norm, 'r') as file2:
input2 = yaml.safe_load(file2)
for i in range(81):
covmat_mtt_norm.append(input2['dependent_variables'][0]['values'][i]['value'])
artunc_mtt_norm = cta(9, covmat_mtt_norm, 1)


covariance_matrix_ytt="rawdata/Table476.yaml"
with open(covariance_matrix_ytt, 'r') as file3:
input3 = yaml.safe_load(file3)
for i in range(144):
covmat_ytt.append(input3['dependent_variables'][0]['values'][i]['value'])
artunc_ytt = cta(12, covmat_ytt)

covariance_matrix_ytt_norm="rawdata/Table474.yaml"
with open(covariance_matrix_ytt_norm, 'r') as file4:
input4 = yaml.safe_load(file4)
for i in range(144):
covmat_ytt_norm.append(input4['dependent_variables'][0]['values'][i]['value'])
artunc_ytt_norm = cta(12, covmat_ytt_norm, 1)

# abs mtt-ytt
# m1 | m2 | m3
# m1 | 501 502t 504t
# m2 | 502 503 505t
# m3 | 504 505 506

with open("rawdata/Table501.yaml", 'r') as file5:
input5 = yaml.safe_load(file5)
for i in range(16):
covmat_501.append(input5['dependent_variables'][0]['values'][i]['value'])
covmat_501 = mtm(4, 4, covmat_501)
with open("rawdata/Table502.yaml", 'r') as file6:
input6 = yaml.safe_load(file6)
for i in range(16):
covmat_502.append(input6['dependent_variables'][0]['values'][i]['value'])
covmat_502 = mtm(4, 4, covmat_502)
covmat_502t = np.transpose(covmat_502)
with open("rawdata/Table503.yaml", 'r') as file7:
input7 = yaml.safe_load(file7)
for i in range(16):
covmat_503.append(input7['dependent_variables'][0]['values'][i]['value'])
covmat_503 = mtm(4, 4, covmat_503)
with open("rawdata/Table504.yaml", 'r') as file8:
input8 = yaml.safe_load(file8)
for i in range(12):
covmat_504.append(input8['dependent_variables'][0]['values'][i]['value'])
covmat_504 = mtm(3, 4, covmat_504)
covmat_504t = np.transpose(covmat_504)
with open("rawdata/Table505.yaml", 'r') as file9:
input9 = yaml.safe_load(file9)
for i in range(12):
covmat_505.append(input9['dependent_variables'][0]['values'][i]['value'])
covmat_505 = mtm(3, 4, covmat_505)
covmat_505t = np.transpose(covmat_505)
with open("rawdata/Table506.yaml", 'r') as file10:
input10 = yaml.safe_load(file10)
for i in range(9):
covmat_506.append(input10['dependent_variables'][0]['values'][i]['value'])
covmat_506 = mtm(3, 3, covmat_506)

covmat_mtt_ytt = cm(3, 3, [covmat_501, covmat_502t, covmat_504t, covmat_502, covmat_503, covmat_505t, covmat_504, covmat_505, covmat_506])
artunc_mtt_ytt = cta(11, covmat_mtt_ytt)

# abs mtt-ytt-norm
# m1 | m2 | m3
# m1 | 492 493t 495t
# m2 | 493 494 496t
# m3 | 495 496 497

with open("rawdata/Table492.yaml", 'r') as file11:
input11 = yaml.safe_load(file11)
for i in range(16):
covmat_492.append(input11['dependent_variables'][0]['values'][i]['value'])
covmat_492 = mtm(4, 4, covmat_492)
with open("rawdata/Table493.yaml", 'r') as file12:
input12 = yaml.safe_load(file12)
for i in range(16):
covmat_493.append(input12['dependent_variables'][0]['values'][i]['value'])
covmat_493 = mtm(4, 4, covmat_493)
covmat_493t = np.transpose(covmat_493)
with open("rawdata/Table494.yaml", 'r') as file13:
input13 = yaml.safe_load(file13)
for i in range(16):
covmat_494.append(input13['dependent_variables'][0]['values'][i]['value'])
covmat_494 = mtm(4, 4, covmat_494)
with open("rawdata/Table495.yaml", 'r') as file14:
input14 = yaml.safe_load(file14)
for i in range(12):
covmat_495.append(input14['dependent_variables'][0]['values'][i]['value'])
covmat_495 = mtm(3, 4, covmat_495)
covmat_495t = np.transpose(covmat_495)
with open("rawdata/Table496.yaml", 'r') as file15:
input15 = yaml.safe_load(file15)
for i in range(12):
covmat_496.append(input15['dependent_variables'][0]['values'][i]['value'])
covmat_496 = mtm(3, 4, covmat_496)
covmat_496t = np.transpose(covmat_496)
with open("rawdata/Table497.yaml", 'r') as file16:
input16 = yaml.safe_load(file16)
for i in range(9):
covmat_497.append(input16['dependent_variables'][0]['values'][i]['value'])
covmat_497 = mtm(3, 3, covmat_497)

covmat_mtt_ytt_norm = cm(3, 3, [covmat_492, covmat_493t, covmat_495t, covmat_493, covmat_494, covmat_496t, covmat_495, covmat_496, covmat_497])
artunc_mtt_ytt_norm = cta(11, covmat_mtt_ytt_norm, 1)
Original file line number Diff line number Diff line change
@@ -0,0 +1,12 @@
data_central:
- 0.7569238
- 0.6696305
- 0.4818348
- 0.1334117
- 0.202234
- 0.1971964
- 0.1578857
- 0.04561878
- 0.01063745
- 0.007859592
- 0.001781781
Original file line number Diff line number Diff line change
@@ -0,0 +1,12 @@
data_central:
- 0.0008937502
- 0.0007906771
- 0.0005689343
- 0.000157528
- 0.0002387912
- 0.0002328429
- 0.0001864262
- 5.386512e-05
- 1.256034e-05
- 9.280342e-06
- 2.103867e-06
Original file line number Diff line number Diff line change
@@ -0,0 +1,10 @@
data_central:
- 3.755971
- 2.475661
- 1.095144
- 0.5433309
- 0.2582264
- 0.140046
- 0.07230107
- 0.03606311
- 0.003269028
Original file line number Diff line number Diff line change
@@ -0,0 +1,10 @@
data_central:
- 0.00384425
- 0.002533848
- 0.001120884
- 0.0005561011
- 0.0002642956
- 0.0001433376
- 7.400041e-05
- 3.691072e-05
- 3.345862e-06
Original file line number Diff line number Diff line change
@@ -0,0 +1,13 @@
data_central:
- 592.8617
- 620.3081
- 624.3119
- 587.1975
- 580.3204
- 535.3079
- 468.0838
- 431.4822
- 398.2482
- 343.5596
- 242.6841
- 109.6994
Original file line number Diff line number Diff line change
@@ -0,0 +1,13 @@
data_central:
- 0.7048442
- 0.7374748
- 0.7422349
- 0.6981101
- 0.689934
- 0.6364193
- 0.5564977
- 0.5129826
- 0.4734712
- 0.4084528
- 0.2885234
- 0.13042
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