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)