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Merge pull request #2370 from NNPDF/nnpdf41_alpha_version_runcard
Add first NNPDF4.1 example runcard
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‎n3fit/runcards/example-nnpdf41.yml‎

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#
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# Configuration file for n3fit
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#
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######################################################################################
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description: Starting runcard for the NNPDF4.1 series of fits. Work In Progress
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######################################################################################
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dataset_inputs:
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- {dataset: NMC_NC_NOTFIXED_EM-F2, frac: 0.75, variant: legacy_dw}
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- {dataset: NMC_NC_NOTFIXED_P_EM-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: SLAC_NC_NOTFIXED_P_EM-F2, frac: 0.75, variant: legacy_dw}
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- {dataset: SLAC_NC_NOTFIXED_D_EM-F2, frac: 0.75, variant: legacy_dw}
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- {dataset: BCDMS_NC_NOTFIXED_P_EM-F2, frac: 0.75, variant: legacy_dw}
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- {dataset: BCDMS_NC_NOTFIXED_D_EM-F2, frac: 0.75, variant: legacy_dw}
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- {dataset: CHORUS_CC_NOTFIXED_PB_NU-SIGMARED, frac: 0.75, variant: legacy_dw}
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- {dataset: CHORUS_CC_NOTFIXED_PB_NB-SIGMARED, frac: 0.75, variant: legacy_dw}
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- {dataset: NUTEV_CC_NOTFIXED_FE_NU-SIGMARED, cfac: [MAS], frac: 0.75, variant: legacy_dw}
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- {dataset: NUTEV_CC_NOTFIXED_FE_NB-SIGMARED, cfac: [MAS], frac: 0.75, variant: legacy_dw}
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- {dataset: HERA_NC_318GEV_EM-SIGMARED, frac: 0.75}
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- {dataset: HERA_NC_225GEV_EP-SIGMARED, frac: 0.75}
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- {dataset: HERA_NC_251GEV_EP-SIGMARED, frac: 0.75}
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- {dataset: HERA_NC_300GEV_EP-SIGMARED, frac: 0.75}
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- {dataset: HERA_NC_318GEV_EP-SIGMARED, frac: 0.75}
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- {dataset: HERA_CC_318GEV_EM-SIGMARED, frac: 0.75}
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- {dataset: HERA_CC_318GEV_EP-SIGMARED, frac: 0.75}
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- {dataset: HERA_NC_318GEV_EAVG_CHARM-SIGMARED, frac: 0.75}
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- {dataset: HERA_NC_318GEV_EAVG_BOTTOM-SIGMARED, frac: 0.75}
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- {dataset: DYE866_Z0_800GEV_DW_RATIO_PDXSECRATIO, frac: 0.75}
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- {dataset: DYE866_Z0_800GEV_PXSEC, frac: 0.75}
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- {dataset: DYE605_Z0_38P8GEV_DW_PXSEC, frac: 0.75}
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# - {dataset: DYE906_Z0_120GEV_DW_PDXSECRATIO, frac: 0.75}
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- {dataset: CDF_Z0_1P96TEV_ZRAP, frac: 0.75}
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- {dataset: D0_Z0_1P96TEV_ZRAP, frac: 0.75}
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- {dataset: D0_WPWM_1P96TEV_ASY, frac: 0.75}
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- {dataset: ATLAS_WPWM_7TEV_36PB_ETA, frac: 0.75}
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- {dataset: ATLAS_Z0_7TEV_36PB_ETA, frac: 0.75}
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- {dataset: ATLAS_Z0_7TEV_49FB_HIMASS, frac: 0.75}
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- {dataset: ATLAS_Z0_7TEV_LOMASS_M, frac: 0.75}
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- {dataset: ATLAS_WPWM_7TEV_46FB_CC-ETA, frac: 0.75}
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- {dataset: ATLAS_Z0_7TEV_46FB_CC-Y, frac: 0.75}
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- {dataset: ATLAS_Z0_7TEV_46FB_CF-Y, frac: 0.75}
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- {dataset: ATLAS_Z0_8TEV_HIMASS_M-Y, frac: 0.75}
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# - {dataset: ATLAS_Z0_8TEV_LOWMASS_M-Y, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_Z0_13TEV_TOT, frac: 0.75, cfac: [NRM]}
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- {dataset: ATLAS_WPWM_13TEV_TOT, frac: 0.75, cfac: [NRM]}
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- {dataset: ATLAS_WJ_8TEV_WP-PT, frac: 0.75}
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- {dataset: ATLAS_WJ_8TEV_WM-PT, frac: 0.75}
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- {dataset: ATLAS_Z0J_8TEV_PT-M, frac: 0.75}
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- {dataset: ATLAS_Z0J_8TEV_PT-Y, frac: 0.75}
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- {dataset: ATLAS_TTBAR_7TEV_TOT_X-SEC, frac: 0.75}
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- {dataset: ATLAS_TTBAR_8TEV_TOT_X-SEC, frac: 0.75}
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- {dataset: ATLAS_TTBAR_13TEV_TOT_X-SEC, frac: 0.75}
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- {dataset: ATLAS_TTBAR_8TEV_LJ_DIF_YT-NORM, frac: 0.75}
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- {dataset: ATLAS_TTBAR_8TEV_LJ_DIF_YTTBAR-NORM, frac: 0.75}
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- {dataset: ATLAS_TTBAR_8TEV_2L_DIF_YTTBAR-NORM, frac: 0.75}
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- {dataset: ATLAS_1JET_8TEV_R06_PTY, frac: 0.75, variant: legacy_data}
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- {dataset: ATLAS_2JET_7TEV_R06_M12Y, frac: 0.75}
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- {dataset: ATLAS_PH_13TEV_XSEC, frac: 0.75, cfac: [EWK]}
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- {dataset: ATLAS_SINGLETOP_7TEV_TCHANNEL-XSEC, frac: 0.75}
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- {dataset: ATLAS_SINGLETOP_13TEV_TCHANNEL-XSEC, frac: 0.75}
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- {dataset: ATLAS_SINGLETOP_7TEV_T-Y-NORM, frac: 0.75}
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- {dataset: ATLAS_SINGLETOP_7TEV_TBAR-Y-NORM, frac: 0.75}
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- {dataset: ATLAS_SINGLETOP_8TEV_T-RAP-NORM, frac: 0.75}
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- {dataset: ATLAS_SINGLETOP_8TEV_TBAR-RAP-NORM, frac: 0.75}
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- {dataset: CMS_WPWM_7TEV_ELECTRON_ASY, frac: 0.75}
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- {dataset: CMS_WPWM_7TEV_MUON_ASY, frac: 0.75}
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- {dataset: CMS_Z0_7TEV_DIMUON_2D, frac: 0.75}
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- {dataset: CMS_WPWM_8TEV_MUON_Y, frac: 0.75}
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- {dataset: CMS_Z0J_8TEV_PT-Y, frac: 0.75, cfac: [NRM]}
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- {dataset: CMS_2JET_7TEV_M12-Y, frac: 0.75}
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- {dataset: CMS_1JET_8TEV_PTY, frac: 0.75, variant: legacy_data}
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- {dataset: CMS_TTBAR_7TEV_TOT_X-SEC, frac: 0.75}
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- {dataset: CMS_TTBAR_8TEV_TOT_X-SEC, frac: 0.75}
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- {dataset: CMS_TTBAR_13TEV_TOT_X-SEC, frac: 0.75}
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- {dataset: CMS_TTBAR_8TEV_LJ_DIF_YTTBAR-NORM, frac: 0.75}
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- {dataset: CMS_TTBAR_5TEV_TOT_X-SEC, frac: 0.75}
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- {dataset: CMS_TTBAR_8TEV_2L_DIF_MTTBAR-YT-NORM, frac: 0.75}
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- {dataset: CMS_TTBAR_13TEV_2L_DIF_YT, frac: 0.75}
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- {dataset: CMS_TTBAR_13TEV_LJ_DIF_YT, frac: 0.75}
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- {dataset: CMS_SINGLETOP_7TEV_TCHANNEL-XSEC, frac: 0.75}
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- {dataset: CMS_SINGLETOP_8TEV_TCHANNEL-XSEC, frac: 0.75}
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- {dataset: CMS_SINGLETOP_13TEV_TCHANNEL-XSEC, frac: 0.75}
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- {dataset: LHCB_Z0_7TEV_DIELECTRON_Y, frac: 0.75}
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- {dataset: LHCB_Z0_8TEV_DIELECTRON_Y, frac: 0.75}
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- {dataset: LHCB_WPWM_7TEV_MUON_Y, frac: 0.75, cfac: [NRM]}
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- {dataset: LHCB_Z0_7TEV_MUON_Y, frac: 0.75, cfac: [NRM]}
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- {dataset: LHCB_WPWM_8TEV_MUON_Y, frac: 0.75, cfac: [NRM]}
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- {dataset: LHCB_Z0_8TEV_MUON_Y, frac: 0.75, cfac: [NRM]}
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- {dataset: LHCB_Z0_13TEV_DIMUON-Y, frac: 0.75}
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- {dataset: LHCB_Z0_13TEV_DIELECTRON-Y, frac: 0.75}
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################################################################################
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datacuts:
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t0pdfset: 250917-jcm-001
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q2min: 3.49
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w2min: 12.5
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theory:
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theoryid: 41_000_000
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trvlseed: 1953065998
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nnseed: 1589400026
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mcseed: 2135943670
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genrep: true
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parameters: # This defines the parameter dictionary that is passed to the Model Trainer
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nodes_per_layer: [70, 50, 25, 20, 9]
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activation_per_layer: [tanh, tanh, tanh, tanh, linear]
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initializer: glorot_normal
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optimizer:
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clipnorm: 6.073e-6
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learning_rate: 2.621e-3
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optimizer_name: Nadam
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epochs: 27000
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positivity:
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initial: 184.8
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multiplier:
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integrability:
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initial: 10
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multiplier:
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stopping_patience: 0.1
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layer_type: dense
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dropout: 0.0
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threshold_chi2: 3.5
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interpolation_points: 5
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fitting:
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fitbasis: CCBAR_ASYMM # EVOL (7), EVOLQED (8), etc.
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savepseudodata: true
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basis:
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- {fl: sng, trainable: false, smallx: [1.103, 1.12], largex: [1.461, 3.778]}
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- {fl: g, trainable: false, smallx: [0.8737, 1.088], largex: [2.204, 4.431]}
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- {fl: v, trainable: false, smallx: [0.5051, 0.6847], largex: [1.526, 2.557]}
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- {fl: v3, trainable: false, smallx: [0.1932, 0.4309], largex: [1.73, 2.559]}
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- {fl: v8, trainable: false, smallx: [0.5645, 0.7228], largex: [1.566, 2.662]}
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- {fl: t3, trainable: false, smallx: [-0.4244, 1.0], largex: [1.75, 2.939]}
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- {fl: t8, trainable: false, smallx: [0.6677, 0.9282], largex: [1.55, 3.504]}
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- {fl: t15, trainable: false, smallx: [1.087, 1.136], largex: [1.503, 3.379]}
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- {fl: v15, trainable: false, smallx: [0.4713, 0.7641], largex: [1.464, 3.851]}
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################################################################################
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positivity:
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posdatasets:
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# Positivity Lagrange Multiplier
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- {dataset: NNPDF_POS_2P24GEV_F2U, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_F2D, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_F2S, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_FLL, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_DYU, maxlambda: 1e10}
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- {dataset: NNPDF_POS_2P24GEV_DYD, maxlambda: 1e10}
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- {dataset: NNPDF_POS_2P24GEV_DYS, maxlambda: 1e10}
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- {dataset: NNPDF_POS_2P24GEV_F2C-CCE, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_F2C-CCP, maxlambda: 1e6}
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# Positivity of MSbar PDFs
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- {dataset: NNPDF_POS_2P24GEV_XUQ, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XUB, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XDQ, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XDB, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XSQ, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XSB, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XGL, maxlambda: 1e6}
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added_filter_rules:
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- dataset: NNPDF_POS_2P24GEV_FLL
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rule: x > 5.0e-7
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- dataset: NNPDF_POS_2P24GEV_F2C-CCE
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rule: x < 0.74
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- dataset: NNPDF_POS_2P24GEV_F2C-CCP
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rule: x < 0.74
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- dataset: NNPDF_POS_2P24GEV_XGL
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rule: x > 0.1
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- dataset: NNPDF_POS_2P24GEV_XUQ
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rule: x > 0.1
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- dataset: NNPDF_POS_2P24GEV_XUB
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rule: x > 0.1
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- dataset: NNPDF_POS_2P24GEV_XDQ
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rule: x > 0.1
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- dataset: NNPDF_POS_2P24GEV_XDB
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rule: x > 0.1
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- dataset: NNPDF_POS_2P24GEV_XSQ
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rule: x > 0.1
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- dataset: NNPDF_POS_2P24GEV_XSB
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rule: x > 0.1
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integrability:
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integdatasets:
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- {dataset: NNPDF_INTEG_3GEV_XT8, maxlambda: 1e2}
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- {dataset: NNPDF_INTEG_3GEV_XT3, maxlambda: 1e2}
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################################################################################
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debug: false
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maxcores: 16

‎nnpdf_data/nnpdf_data/commondata/NNPDF_POS_2P24GEV/metadata.yaml‎

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- - NNPDF_POS_ANTI_UP
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- - NNPDF_POS_ANTI_DUP
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data_uncertainties: []
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- observable_name: F2C-CCP
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observable:
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description: Deep Inelastic Scattering
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label: 'positivity dataset: CC DIS $\bar{c}$ structure function $F_2^{W^+,c}$'
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units: ''
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process_type: POS_DIS
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tables: []
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npoints: []
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ndata: 20
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plotting:
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dataset_label: 'positivity dataset: CC DIS $\bar{c}$ structure function $F_2^{W^+,c}$'
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plot_x: x
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kinematic_coverage:
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- x
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- Q2
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kinematics:
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variables:
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x:
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description: Bjorken x
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label: x
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units: ''
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Q2:
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description: Factorization Scale
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label: Q2
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units: ''
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file: kinematics_F2C.yaml
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theory:
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FK_tables:
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- - NNPDF_POS_F2C_CCP_40
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data_uncertainties: []
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- observable_name: F2C-CCE
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observable:
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description: Deep Inelastic Scattering
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label: 'positivity dataset: DIS $c$ structure function $F_2^{W^-,c}$'
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units: ''
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process_type: POS_DIS
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tables: []
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npoints: []
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ndata: 20
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plotting:
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dataset_label: 'positivity dataset: DIS $c$ structure function $F_2^{W^-,c}$'
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plot_x: x
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kinematic_coverage:
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- x
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- Q2
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kinematics:
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variables:
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x:
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description: Bjorken x
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label: x
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units: ''
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Q2:
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description: Factorization Scale
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label: Q2
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units: ''
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file: kinematics_F2C.yaml
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theory:
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FK_tables:
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- - NNPDF_POS_F2C_CCE_40
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data_uncertainties: []

‎validphys2/src/validphys/loader.py‎

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raise PDFNotFound("PDF '%s' is neither an uploaded fit nor an " "LHAPDF set." % name)
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def download_theoryID(self, thid):
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thid = str(thid)
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thid = str(int(thid))
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remote = self.remote_theories
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if thid not in remote:
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raise TheoryNotFound("Theory %s not available." % thid)

‎validphys2/src/validphys/nnprofile_default.yaml‎

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# Remote resource locations
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fit_urls:
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- 'https://data.nnpdf.science/fits/'
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- 'https://nnpdf.web.cern.ch/nnpdf/fits/'
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fit_index: 'fitdata.json'
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hyperscan_index: 'hyperscandata.json'
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theory_urls:
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- 'https://nnpdf.nikhef.nl/nnpdf/theories/'
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- 'https://nnpdf.web.cern.ch/nnpdf/tables/'
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- 'https://nnpdf.web.cern.ch/nnpdf/tables_box/'
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theory_index: 'theorydata.json'
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eko_urls:
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- 'https://nnpdf.nikhef.nl/nnpdf/ekos/'
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- 'https://nnpdf.web.cern.ch/nnpdf/ekos/'
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- 'https://nnpdf.web.cern.ch/nnpdf/ekos_box/'
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