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HEP-PBSP / SIMUnet

The public code for SIMUnet, a NNPDF based tool to perform simultaneous determination of PDFs and EFT Wilson coefficients.
https://hep-pbsp.github.io/SIMUnet/
GNU General Public License v3.0
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Weird crash #28

Closed LucaMantani closed 10 months ago

LucaMantani commented 11 months ago

There is a weird crash due to segmentation fault when I run vp-setupfit with this runcard (in attachment) with these two datasets only: ATLASTTBARTOT7TEV LEP_ZDATA

The error message is:

[WARNING]: Output folder exists: /nfs/scratch/fynu/lmantani/SimuRelease/check/test Overwriting contents
[WARNING]: Using q2min from runcard
[WARNING]: Using w2min from runcard
Using Keras backend
[INFO]: All requirements processed and checked successfully. Executing actions.
[INFO]: Filtering real data.
[WARNING]: Dataset output folder exists: /nfs/scratch/fynu/lmantani/SimuRelease/check/test/filter/ATLASTTBARTOT7TEV Overwriting contents
[INFO]: 1/1 datapoints in ATLASTTBARTOT7TEV passed kinematic cuts.
[WARNING]: Dataset output folder exists: /nfs/scratch/fynu/lmantani/SimuRelease/check/test/filter/LEP_ZDATA Overwriting contents
[INFO]: 19/19 datapoints in LEP_ZDATA passed kinematic cuts.
Fatal Python error: Segmentation fault

Current thread 0x00007fe29ec8f740 (most recent call first):
  File "/home/ucl/cp3/lmantani/miniconda3/envs/simunet/lib/python3.9/site-packages/NNPDF/nnpdf.py", line 3457 in __init__
  File "/auto/home/users/l/m/lmantani/applications/SIMUnet/simunet_release/validphys2/src/validphys/core.py", line 555 in load
  File "/auto/home/users/l/m/lmantani/applications/SIMUnet/simunet_release/validphys2/src/validphys/filters.py", line 167 in _filter_real_data
  File "/auto/home/users/l/m/lmantani/applications/SIMUnet/simunet_release/validphys2/src/validphys/filters.py", line 132 in filter_real_data
  File "/home/ucl/cp3/lmantani/miniconda3/envs/simunet/lib/python3.9/site-packages/reportengine/resourcebuilder.py", line 175 in get_result
  File "/home/ucl/cp3/lmantani/miniconda3/envs/simunet/lib/python3.9/site-packages/reportengine/resourcebuilder.py", line 166 in execute_sequential
  File "/home/ucl/cp3/lmantani/miniconda3/envs/simunet/lib/python3.9/site-packages/reportengine/app.py", line 380 in run
  File "/auto/home/users/l/m/lmantani/applications/SIMUnet/simunet_release/validphys2/src/validphys/app.py", line 158 in run
  File "/auto/home/users/l/m/lmantani/applications/SIMUnet/simunet_release/n3fit/src/n3fit/scripts/vp_setupfit.py", line 197 in run
  File "/home/ucl/cp3/lmantani/miniconda3/envs/simunet/lib/python3.9/site-packages/reportengine/app.py", line 395 in main
  File "/auto/home/users/l/m/lmantani/applications/SIMUnet/simunet_release/n3fit/src/n3fit/scripts/vp_setupfit.py", line 214 in main
  File "/home/ucl/cp3/lmantani/miniconda3/envs/simunet/bin/vp-setupfit", line 33 in <module>
Segmentation fault

If I add other datasets it doesn't happen anymore, it's weird.

the runcard:

# Configuration file for NNPDF++
#
############################################################
description: "Runcard template. This one performs a simultaenous fit with some top operators. The fit was performed as a check to verify that the renaming to simu_fac and simu_parameters has been successfull. NNPDF4.0 methodology."

############################################################
# frac: training fraction
# ewk: apply ewk k-factors
# sys: systematics treatment (see systypes)

dataset_inputs:
# - {dataset: NMCPD_dw_ite, frac: 0.75}
# - {dataset: NMC, frac: 0.75}
# - {dataset: SLACP_dwsh, frac: 0.75}
# - {dataset: SLACD_dw_ite, frac: 0.75}
# - {dataset: BCDMSP_dwsh, frac: 0.75}
# - {dataset: BCDMSD_dw_ite, frac: 0.75}
# - {dataset: CHORUSNUPb_dw_ite, frac: 0.75}
# - {dataset: CHORUSNBPb_dw_ite, frac: 0.75}
# - {dataset: NTVNUDMNFe_dw_ite, frac: 0.75, cfac: [MAS]}
# - {dataset: NTVNBDMNFe_dw_ite, frac: 0.75, cfac: [MAS]}
# - {dataset: HERACOMBNCEM, frac: 0.75}
# - {dataset: HERACOMBNCEP460, frac: 0.75}
# - {dataset: HERACOMBNCEP575, frac: 0.75}
# - {dataset: HERACOMBNCEP820, frac: 0.75}
# - {dataset: HERACOMBNCEP920, frac: 0.75}
# - {dataset: HERACOMBCCEM, frac: 0.75}
# - {dataset: HERACOMBCCEP, frac: 0.75}
# - {dataset: HERACOMB_SIGMARED_C, frac: 0.75} 
# - {dataset: HERACOMB_SIGMARED_B, frac: 0.75}   
# - {dataset: DYE886R_dw_ite, frac: 0.75, cfac: [QCD]}
# - {dataset: DYE886P, frac: 0.75, cfac: [QCD]}
# - {dataset: DYE605_dw_ite, frac: 0.75, cfac: [QCD]}
# - {dataset: DYE906R_dw_ite, frac: 0.75, cfac: [ACC,QCD]}
# - {dataset: CDFZRAP_NEW, frac: 0.75, cfac: [QCD]}
# - {dataset: D0ZRAP_40, frac: 0.75, cfac: [QCD]}
# - {dataset: D0WMASY, frac: 0.75, cfac: [QCD]}
# - {dataset: ATLASWZRAP36PB, frac: 0.75, cfac: [QCD]}
# - {dataset: ATLASZHIGHMASS49FB, frac: 0.75, cfac: [QCD]}
# - {dataset: ATLASLOMASSDY11EXT, frac: 0.75, cfac: [QCD]}
# - {dataset: ATLASWZRAP11CC, frac: 0.75, cfac: [QCD]}               
# - {dataset: ATLASWZRAP11CF, frac: 0.75, cfac: [QCD]}
# - {dataset: ATLASDY2D8TEV, frac: 0.75, cfac: [QCDEWK]}
# - {dataset: ATLAS_DY_2D_8TEV_LOWMASS, frac: 0.75, cfac: [QCD]} 
# - {dataset: ATLAS_WZ_TOT_13TEV, frac: 0.75, cfac: [NRM, QCD]}       
# - {dataset: ATLAS_WP_JET_8TEV_PT, frac: 0.75, cfac: [QCD]}         
# - {dataset: ATLAS_WM_JET_8TEV_PT, frac: 0.75, cfac: [QCD]}         
# - {dataset: ATLASZPT8TEVMDIST, frac: 0.75, cfac: [QCD], sys: 10}
# - {dataset: ATLASZPT8TEVYDIST, frac: 0.75, cfac: [QCD], sys: 10}
# - {dataset: ATLAS_1JET_8TEV_R06_DEC, frac: 0.75, cfac: [QCD]}
# - {dataset: ATLAS_2JET_7TEV_R06, frac: 0.75, cfac: [QCD]}     
# - {dataset: ATLASPHT15_SF, frac: 0.75, cfac: [QCD, EWK]}         
# - {dataset: CMSWEASY840PB, frac: 0.75, cfac: [QCD]}
# - {dataset: CMSWMASY47FB, frac: 0.75, cfac: [QCD]}
# - {dataset: CMSDY2D11, frac: 0.75, cfac: [QCD]}
# - {dataset: CMSWMU8TEV, frac: 0.75, cfac: [QCD]}
# - {dataset: CMSZDIFF12, frac: 0.75, cfac: [QCD, NRM], sys: 10}
# - {dataset: CMS_2JET_7TEV, frac: 0.75, cfac: [QCD]}       
# - {dataset: CMS_1JET_8TEV, frac: 0.75, cfac: [QCD]}
# - {dataset: LHCBZ940PB, frac: 0.75, cfac: [QCD]}
# - {dataset: LHCBZEE2FB_40, frac: 0.75, cfac: [QCD]}
# - {dataset: LHCBWZMU7TEV, frac: 0.75, cfac: [NRM, QCD]}
# - {dataset: LHCBWZMU8TEV, frac: 0.75, cfac: [NRM, QCD]}
# - {dataset: LHCB_Z_13TEV_DIMUON, frac: 0.75, cfac: [QCD]}
# - {dataset: LHCB_Z_13TEV_DIELECTRON, frac: 0.75, cfac: [QCD]} # HERE STARTS THE TOP SECTOR
#  #ttbar
- {dataset: ATLASTTBARTOT7TEV, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLASTTBARTOT8TEV, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: ATLAS_TOPDIFF_DILEPT_8TEV_TTMNORM, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: ATLAS_TTBAR_8TEV_LJETS_TOTAL, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: ATLAS_TTB_DIFF_8TEV_LJ_TRAPNORM, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: ATLAS_TTB_DIFF_8TEV_LJ_TTRAPNORM, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: ATLAS_TTBAR_13TEV_DILEPTON_TOTAL, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: ATLAS_TTBAR_13TEV_HADRONIC_TOTAL, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: ATLAS_TTBAR_13TEV_HADRONIC_2D_TTM_ABSYTTNORM, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: ATLAS_TTBAR_13TEV_LJETS_TOTAL, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: ATLAS_TTBAR_13TEV_TTMNORM, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: CMSTTBARTOT5TEV, cfac: [QCD], simu_fac: "EFT_NLO"}  
# - {dataset: CMSTTBARTOT7TEV, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMSTTBARTOT8TEV, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: CMS_TTBAR_2D_DIFF_MTT_TTRAP_NORM, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: CMSTOPDIFF8TEVTTRAPNORM, cfac: [QCD], simu_fac: "EFT_NLO"} 
# - {dataset: CMSTTBARTOT13TEV, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_TTB_DIFF_13TEV_2016_2L_TTMNORM, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_TTBAR_13TEV_LJETS_TOTAL, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_TTBAR_13TEV_TTMNORM, cfac: [QCD], simu_fac: "EFT_NLO"} 
# # # ttbar AC
# - {dataset: ATLAS_TTBAR_8TEV_ASY, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_TTBAR_13TEV_ASY_2022, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_TTBAR_8TEV_ASY, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_TTBAR_13TEV_ASY, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_CMS_TTBAR_8TEV_ASY, cfac: [QCD], simu_fac: "EFT_NLO"}
# # # # TTZ
# - {dataset: ATLAS_TTBARZ_8TEV_TOTAL, simu_fac: "EFT_LO"}
# - {dataset: ATLAS_TTBARZ_13TEV_TOTAL, cfac: [QCD], simu_fac: "EFT_LO"}
# - {dataset: ATLAS_TTBARZ_13TEV_PTZNORM, simu_fac: "EFT_LO"}
# - {dataset: CMS_TTBARZ_8TEV_TOTAL, simu_fac: "EFT_LO"}
# - {dataset: CMS_TTBARZ_13TEV_TOTAL, cfac: [QCD], simu_fac: "EFT_LO"}
# - {dataset: CMS_TTBARZ_13TEV_PTZNORM, simu_fac: "EFT_LO"}
# # # # TTW
# - {dataset: ATLAS_TTBARW_8TEV_TOTAL, simu_fac: "EFT_LO"}
# - {dataset: ATLAS_TTBARW_13TEV_TOTAL, cfac: [QCD], simu_fac: "EFT_LO"}
# - {dataset: CMS_TTBARW_8TEV_TOTAL, simu_fac: "EFT_LO"}
# - {dataset: CMS_TTBARW_13TEV_TOTAL, cfac: [QCD], simu_fac: "EFT_LO"}
# # # # singletop
# - {dataset: ATLAS_SINGLETOP_TCH_7TEV_T, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_TCH_7TEV_TB, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_TCH_DIFF_7TEV_T_RAP_NORM, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_TCH_DIFF_7TEV_TBAR_RAP_NORM, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_TCH_8TEV_T, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_TCH_8TEV_TB, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_TCH_DIFF_8TEV_T_RAP_NORM, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_TCH_DIFF_8TEV_TBAR_RAP_NORM, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_SCH_8TEV_TOTAL, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_TCH_13TEV_T, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_TCH_13TEV_TB, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOP_SCH_13TEV_TOTAL, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_SINGLETOP_TCH_TOT_7TEV, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_SINGLETOP_TCH_8TEV_T, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_SINGLETOP_TCH_8TEV_TB, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_SINGLETOP_SCH_8TEV_TOTAL, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_SINGLETOP_TCH_13TEV_T, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_SINGLETOP_TCH_13TEV_TB, cfac: [QCD], simu_fac: "EFT_NLO"}
# - {dataset: CMS_SINGLETOP_TCH_13TEV_YTNORM, cfac: [QCD], simu_fac: "EFT_NLO"}
# # # # tW
# - {dataset: ATLAS_SINGLETOPW_8TEV_TOTAL, simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOPW_8TEV_SLEP_TOTAL, simu_fac: "EFT_NLO"}
# - {dataset: ATLAS_SINGLETOPW_13TEV_TOTAL, simu_fac: "EFT_NLO"}
# - {dataset: CMS_SINGLETOPW_8TEV_TOTAL, simu_fac: "EFT_NLO"}
# - {dataset: CMS_SINGLETOPW_13TEV_TOTAL, simu_fac: "EFT_NLO"}
# - {dataset: CMS_SINGLETOPW_13TEV_SLEP_TOTAL, simu_fac: "EFT_NLO"}
# # Whel
# - {dataset: ATLAS_WHEL_13TEV, simu_fac: "EFT_NLO", use_fixed_predictions: True}
# - {dataset: ATLAS_CMS_WHEL_8TEV, simu_fac: "EFT_NLO", use_fixed_predictions: True}
# # # ttgamma
# - {dataset: ATLAS_TTBARGAMMA_8TEV_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: CMS_TTBARGAMMA_8TEV_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# # 4Heavy
# - {dataset: ATLAS_4TOP_13TEV_MULTILEP_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: ATLAS_4TOP_13TEV_SLEP_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: CMS_4TOP_13TEV_MULTILEP_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: CMS_4TOP_13TEV_SLEP_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: CMS_TTBB_13TEV_ALLJET_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: CMS_TTBB_13TEV_DILEPTON_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: CMS_TTBB_13TEV_LJETS_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: ATLAS_TTBB_13TEV_LJETS_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# # # tz
# - {dataset: ATLAS_SINGLETOPZ_13TEV_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: CMS_SINGLETOPZ_13TEV_TOTAL, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: CMS_SINGLETOPZ_13TEV_PTT, simu_fac: "EFT_LO", use_fixed_predictions: True}

# EWPO
- {dataset: LEP_ZDATA, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: LEP_BRW, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: LEP_BHABHA, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: LEP_ALPHAEW, simu_fac: "EFT_LO", use_fixed_predictions: True}

# # Higgs
# - {dataset: ATLAS_CMS_SSINC_RUNI, simu_fac: "EFT_NLO", use_fixed_predictions: True}
# - {dataset: CMS_SSINC_RUNII, simu_fac: "EFT_NLO", use_fixed_predictions: True}
# - {dataset: ATLAS_STXS_RUNII, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: ATLAS_SSINC_RUNII_ZGAM, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: ATLAS_SSINC_RUNII_MUMU, simu_fac: "EFT_LO", use_fixed_predictions: True}

# # Diboson
# - {dataset: LEP_EEWW_182GEV, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: LEP_EEWW_189GEV, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: LEP_EEWW_198GEV, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: LEP_EEWW_206GEV, simu_fac: "EFT_LO", use_fixed_predictions: True}
# - {dataset: ATLAS_WW_13TEV_2016_MEMU, simu_fac: "EFT_NLO", use_fixed_predictions: True}
# - {dataset: ATLAS_WZ_13TEV_2016_MTWZ, simu_fac: "EFT_NLO", use_fixed_predictions: True}
# - {dataset: CMS_WZ_13TEV_2016_PTZ, simu_fac: "EFT_NLO", use_fixed_predictions: True}
# - {dataset: ATLAS_ZJJ_13TEV_2016, simu_fac: "EFT_LO", use_fixed_predictions: True}

fixed_pdf_fit: False
# load_weights_from_fit: 221103-jmm-no_top_1000_iterated # If this is uncommented, training starts here.

simu_parameters:
# Dipoles
- {name: 'OtZ', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OtW', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OtG', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
# Quark Currents
- {name: 'Opt', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'O3pQ3', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'O3pq', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OpQM', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OpqMi', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Opui', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Opdi', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
# Lepton currents
- {name: 'O3pl', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Opl', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Ope', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
# 4 Fermions 4Q
- {name: 'O1qd', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'O1qu', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'O1dt', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}} 
- {name: 'O1qt', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}} 
- {name: 'O1ut', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}} 
- {name: 'O11qq', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}} 
- {name: 'O13qq', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}} 
- {name: 'O8qd', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'O8qu', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'O8dt', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}} 
- {name: 'O8qt', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}} 
- {name: 'O8ut', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}} 
- {name: 'O81qq', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}} 
- {name: 'O83qq', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
# 4 Fermions 4HeavyQ
- {name: 'OQQ1', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OQQ8', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OQt1', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OQt8', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Ott1', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
# 4 Fermions 2L2Q
- {name: 'Oeu', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Olu', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Oed', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Olq3', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Olq1', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Oqe', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Old', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
# 4 Fermions 4L
- {name: 'Oll', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
# Yukawa
- {name: 'Omup', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Otap', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Otp', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Obp', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Ocp', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
# Bosonic
- {name: 'OG', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OWWW', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OpG', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OpW', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OpB', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OpWB', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'Opd', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}
- {name: 'OpD', scale: 0.01, initialisation: {type: uniform, minval: -1, maxval: 1}}

############################################################
datacuts:
  t0pdfset: 221103-jmm-no_top_1000_iterated # PDF set to generate t0 covmat
  q2min: 3.49                        # Q2 minimum
  w2min: 12.5                        # W2 minimum

############################################################
theory:
  theoryid: 200     # database id

############################################################
trvlseed: 475038818
nnseed: 2394641471
mcseed: 1831662593
save: "weights.h5"
genrep: true      # true = generate MC replicas, false = use real data

############################################################

parameters: # This defines the parameter dictionary that is passed to the Model Trainer
  nodes_per_layer: [25, 20, 8]
  activation_per_layer: [tanh, tanh, linear]
  initializer: glorot_normal
  optimizer:
    clipnorm: 6.073e-6
    learning_rate: 2.621e-3
    optimizer_name: Nadam
  epochs: 20000
  positivity:
    initial: 184.8
    multiplier:
  integrability:
    initial: 184.8
    multiplier:
  stopping_patience: 0.2
  layer_type: dense
  dropout: 0.0
  threshold_chi2: 3.5

fitting:
  # EVOL(QED) = sng=0,g=1,v=2,v3=3,v8=4,t3=5,t8=6,(pht=7)
  # EVOLS(QED)= sng=0,g=1,v=2,v8=4,t3=4,t8=5,ds=6,(pht=7)
  # FLVR(QED) = g=0, u=1, ubar=2, d=3, dbar=4, s=5, sbar=6, (pht=7)
  fitbasis: EVOL  # EVOL (7), EVOLQED (8), etc.
  basis:
  - {fl: sng, pos: false, trainable: false, mutsize: [15], mutprob: [0.05], smallx: [
      1.093, 1.121], largex: [1.486, 3.287]}
  - {fl: g, pos: false, trainable: false, mutsize: [15], mutprob: [0.05], smallx: [
      0.8329, 1.071], largex: [3.084, 6.767]}
  - {fl: v, pos: false, trainable: false, mutsize: [15], mutprob: [0.05], smallx: [
      0.5202, 0.7431], largex: [1.556, 3.639]}
  - {fl: v3, pos: false, trainable: false, mutsize: [15], mutprob: [0.05], smallx: [
      0.1205, 0.4839], largex: [1.736, 3.622]}
  - {fl: v8, pos: false, trainable: false, mutsize: [15], mutprob: [0.05], smallx: [
      0.5864, 0.7987], largex: [1.559, 3.569]}
  - {fl: t3, pos: false, trainable: false, mutsize: [15], mutprob: [0.05], smallx: [
      -0.5019, 1.126], largex: [1.754, 3.479]}
  - {fl: t8, pos: false, trainable: false, mutsize: [15], mutprob: [0.05], smallx: [
      0.6305, 0.8806], largex: [1.544, 3.481]}
  - {fl: t15, pos: false, trainable: false, mutsize: [15], mutprob: [0.05], smallx: [
      1.087, 1.139], largex: [1.48, 3.365]}

############################################################
positivity:
  posdatasets:
  - {dataset: POSF2U, maxlambda: 1e6}        # Positivity Lagrange Multiplier
  - {dataset: POSF2DW, maxlambda: 1e6}
  - {dataset: POSF2S, maxlambda: 1e6}
  - {dataset: POSFLL, maxlambda: 1e6}
  - {dataset: POSDYU, maxlambda: 1e10}
  - {dataset: POSDYD, maxlambda: 1e10}
  - {dataset: POSDYS, maxlambda: 1e10}
  - {dataset: POSF2C, maxlambda: 1e6}
  - {dataset: POSXUQ, maxlambda: 1e6}        # Positivity of MSbar PDFs
  - {dataset: POSXUB, maxlambda: 1e6}
  - {dataset: POSXDQ, maxlambda: 1e6}
  - {dataset: POSXDB, maxlambda: 1e6}
  - {dataset: POSXSQ, maxlambda: 1e6}
  - {dataset: POSXSB, maxlambda: 1e6}
  - {dataset: POSXGL, maxlambda: 1e6}

############################################################
integrability:
  integdatasets:
  - {dataset: INTEGXT8, maxlambda: 1e2}
  - {dataset: INTEGXT3, maxlambda: 1e2}

############################################################
debug: false
maxcores: 4
comane commented 11 months ago

Hi @LucaMantani , is this still an issue? It seems more related to your simunet environment installation rather than on the simunet code itself.

Running vp-setupfit with the card by you specified works as expected for me

LucaMantani commented 11 months ago

It's weird, so I wouldn't be surprised if it's related to come specific thing of my env...

comane commented 10 months ago

@LucaMantani can we close this?

LucaMantani commented 10 months ago

Yes.