import hepdata_lib
from hepdata_lib import Submission
import numpy as np
submission = Submission()
lumi_sf = 1.0 / 35800.0
submission.read_abstract("hepdata_lib/examples/example_inputs/abstract.txt")
submission.add_link(
"Webpage with all figures and tables",
"https://cms-results.web.cern.ch/cms-results/public-results/publications/B2G-16-029/"
)
submission.add_link("arXiv", "http://arxiv.org/abs/arXiv:1802.09407")
submission.add_record_id(1657397, "inspire")
### Table
from hepdata_lib import Table
from hepdata_lib import Variable
from hepdata_lib import RootFileReader
### Begin covariance mumu dressed
# Create a reader for the input file
reader_covariance_mm_Pt = RootFileReader(
"HEPData/inputs/smp17010/folders_dressedleptons/output_root/matrix03__XSRatioSystPt.root"
)
# Read the histogram
data_covariance_mm_Pt = reader_covariance_mm_Pt.read_hist_2d(
"covariance_totsum_0")
# Create variable objects
from __future__ import print_function
import os
import numpy as np
from hepdata_lib import Submission, Table, Variable, Uncertainty
#INITIALIZE
submission = Submission()
#ABSTRACT
submission.read_abstract("input/abstract.txt")
submission.add_link(
"Webpage with all figures and tables",
"https://cms-results.web.cern.ch/cms-results/public-results/publications/SMP-19-013/"
)
submission.add_link("arXiv", "http://arxiv.org/abs/arXiv:2105.12780")
submission.add_record_id(1865855, "inspire")
#FIGURE 2 UPPER LEFT
fig2_ul = Table("Figure 2 (upper left)")
fig2_ul.description = "Distribution of the transverse momentum of the diphoton system for the $\mathrm{W}\gamma\gamma$ electron channel. The predicted yields are shown with their pre-fit normalisations. The observed data, the expected signal contribution and the background estimates are presented with error bars showing the corresponding statistical uncertainties."
fig2_ul.location = "Data from Figure 2 on Page 6 of the preprint"
fig2_ul.keywords["observables"] = ["Diphoton pT"]
fig2_ul.keywords["reactions"] = [
"P P --> W GAMMA GAMMA --> ELECTRON NU GAMMA GAMMA"
]
fig2_ul_in = np.loadtxt("input/fig2_ul.txt", skiprows=1)
#diphoton pT
fig2_ul_pt = Variable("$p_T^{\gamma\gamma}$",
is_independent=True,
from hepdata_lib import RootFileReader
import hepdata_lib
from hepdata_lib import Submission
from hepdata_lib import Table
from hepdata_lib import Variable
import numpy as np
submission = Submission()
submission.read_abstract("HEPData/inputs/smp20006/abstract.txt")
submission.add_link("Webpage with all figures and tables", "http://cms-results.web.cern.ch/cms-results/public-results/publications/SMP-20-006/index.html")
submission.add_link("arXiv", "http://arxiv.org/abs/arXiv:2009.09429")
submission.add_record_id(1818160, "inspire")
### Begin Table 4
table4 = Table("Table 4")
table4.description = "Systematic uncertainties of the $\mathrm{W}^\pm_{\mathrm{L}}\mathrm{W}^\pm_{\mathrm{L}}$ and $\mathrm{W}^\pm_{\mathrm{X}}\mathrm{W}^\pm_{\mathrm{T}}$, and $\mathrm{W}^\pm_{\mathrm{L}}\mathrm{W}^\pm_{\mathrm{X}}$ and $\mathrm{W}^\pm_{\mathrm{T}}\mathrm{W}^\pm_{\mathrm{T}}$ cross section measurements in units of percent."
table4.location = "Data from Table 4"
table4.keywords["observables"] = ["Uncertainty"]
table4.keywords["reactions"] = ["P P --> W W j j"]
table4.keywords["phrases"] = ["VBS", "Polarized", "Same-sign WW"]
data4 = np.loadtxt("HEPData/inputs/smp20006/systematics.txt", dtype='string', skiprows=2)
print(data4)
import hepdata_lib
from hepdata_lib import Submission
from hepdata_lib import Table
from hepdata_lib import Variable
import numpy as np
submission = Submission()
submission.read_abstract("HEPData/inputs/smp18003/abstract.txt")
submission.add_link(
"Webpage with all figures and tables",
"https://cms-results.web.cern.ch/cms-results/public-results/publications/SMP-18-003/"
)
submission.add_link("arXiv", "https://arxiv.org/abs/2012.09254")
submission.add_record_id(999999999, "inspire")
### Begin Figure 2
figure2 = Table("Figure 2")
figure2.description = "The measured and predicted inclusive fiducial cross sections in fb. The experimental measurement includes both statistical and systematics uncertainties. The theoretical prediction includes both the QCD scale and PDF uncertainties."
figure2.location = "Data from Figure 2"
figure2.keywords["observables"] = ["SIG"]
figure2.keywords["phrases"] = [
"Electroweak", "Cross Section", "Proton-Proton", "Z boson production"
]
figure2.keywords["reactions"] = ["PP -> Z"]
figure2_load = np.loadtxt("HEPData/inputs/smp18003/cross_section_results.txt",
dtype='string',
skiprows=2)
from hepdata_lib import Table
from hepdata_lib import Variable
import numpy as np
submission = Submission()
sig_digits = 3
sig_digits2 = 2
submission.read_abstract("HEPData/inputs/smp18006/abstract.txt")
submission.add_link(
"Webpage with all figures and tables",
"http://cms-results.web.cern.ch/cms-results/public-results/publications/SMP-18-006/index.html"
)
submission.add_link("arXiv", "http://arxiv.org/abs/arXiv:1905.07445")
submission.add_record_id(1735737, "inspire")
### Begin Table 2
table2 = Table("Table 2")
table2.description = "Expected yields from various background processes in $\mathrm{WV}$ and $\mathrm{ZV}$ final states. The combination of the statistical and systematic uncertainties are shown. The predicted yields are shown with their best-fit normalizations from the background-only fit. The aQGC signal yields are shown for two aQGC scenarios with $f_{T2}/ \Lambda^{4} = -0.5$ TeV$^{-4}$ and $f_{T2}/ \Lambda^{4} = -2.5$ TeV$^{-4}$ for the $\mathrm{WV}$ and $\mathrm{ZV}$ channels, respectively. The charged Higgs boson signal yields are also shown for values of $s_{\mathrm{H}}=0.5$ and $m_{\mathrm{H}_{5}}=500$ GeV in the GM model. The statistical uncertainties are shown for the expected signal yields."
table2.location = "Data from Table 2"
table2.keywords["observables"] = ["Events"]
table2.keywords["reactions"] = ["P P --> W V j j", "P P --> Z V j j"]
table2.keywords["phrases"] = [
"aQGC", "Charged Higgs", "Georgi-Machacek", "VBS"
]
data2 = np.loadtxt("HEPData/inputs/smp18006/total_yields.txt",
dtype='string',
skiprows=2)