Result writing example

[1]:

import hepi
print(hepi.__version__)
import smpl
import numpy as np
import hepi.resummino as rs
import hepi.util as util
import matplotlib.pyplot as plt
rs.set_path("~/git/resummino_test")
print (rs.get_path())

0.1.4.38+dirty
~/git/resummino_test/

[2]:

params = [
    "mastercode_with_gm2.in",
]
pss = [
      (1000011,-1000011),
     ]

Print

[12]:

for pa,pb in pss:
    for param in params:
        i = hepi.Input(hepi.Order.NLO,13000,pa,pb,param,"cteq6l1","cteq66",1., 1.,id="5")
        #i = hepi.Input(hepi.Order.NLO,13000,pa,pb,param,"CT14lo","CT14lo",1., 1.,model_path=model_path,id="5")
        li = [i]
        li = hepi.mass_scan([i],pa, np.linspace(100,1000,9))
        rs_dl = rs.run(li,noskip=False)
        print(rs_dl)

Running: 9 jobs
skipRESTART None None None ./output/63c20af315a0b83edd39d21c3f06b2187b0b692d66bdcd1ce2ae2e16198666a5.out
RESTART None None None ./output/ca04855db906183d80c2d4fd4b13111163b3bcad0ab46329b245654a03957af6.out
RESTART None None None ./output/ccf140c56e3c9d05bdbfe705a842af550f6b2c7437edb5d25b76b9c716738805.out
RESTART None None None ./output/181cba7fdbdaf24f99cd5aa1a01e3231910ce4ffe46dfc815ba2e6b5b21d0765.out
RESTART None None None ./output/98262bf7beaf5b8c27bb7caf1e1ba5d36e9a1b630a5a6ce107ecc738994c84ad.out
RESTART None None None ./output/8c9890bc4fc87b5f95d2a02ea92732e501cbdd9bc86a00b9c3813b0347f61899.out
RESTART None None None ./output/ad88413ece0f8ad871ebd9b876c1da88b92cf416ca935200c3fc5f5cc44e7267.out
skip{'LO': array([0.19827892+/-0.00028789131, 0.013518169+/-1.7450437e-05,
       0.002574602+/-3.0875529e-06, 0.00072526924+/-8.2560628e-07,
       0.00025157404+/-2.7543847e-07, 9.9243804e-05+/-1.0541245e-07,
       4.2707337e-05+/-4.4261184e-08, 1.9557864e-05+/-1.9863726e-08,
       9.3808373e-06+/-9.3677641e-09], dtype=object), 'NLO': array([0.26266219+/-0.00035483454, 0.016796404+/-1.9662724e-05,
       0.0030864231+/-3.409076e-06, 0.00084837761+/-8.8924337e-07,
       0.00028882589+/-2.9046289e-07, 0.00011233356+/-1.0906148e-07,
       4.7848073e-05+/-4.5120962e-08, 2.1762029e-05+/-2.0001873e-08,
       1.0401314e-05+/-9.3348503e-09], dtype=object), 'NLO_PLUS_NLL': array([0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0,
       0.0+/-0, 0.0+/-0], dtype=object), 'K_LO': array([1.0+/-0, 1.0+/-0, 1.0+/-0, 1.0+/-0, 1.0+/-0, 1.0+/-0, 1.0+/-0,
       1.0+/-0, 1.0+/-0], dtype=object), 'K_NLO': array([1.3247106147239456+/-0.0026271840746797293,
       1.2425058452812656+/-0.002165247517208387,
       1.1987962022868+/-0.0019545055030903086,
       1.1697416120942894+/-0.0018100734503036571,
       1.1480750955066747+/-0.0017067699647146154,
       1.1318949442929456+/-0.0016288154485290425,
       1.120371260797647+/-0.00156985924333877,
       1.1126996792696788+/-0.0015241549475239749,
       1.1087831147012859+/-0.0014886891411263526], dtype=object), 'K_NLO_PLUS_NLL': array([0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0,
       0.0+/-0, 0.0+/-0], dtype=object), 'NLO_PLUS_NLL_OVER_NLO': array([0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0, 0.0+/-0,
       0.0+/-0, 0.0+/-0], dtype=object), 'VNLO': array([0.01041012+/-8.2978566e-05, 0.00062999549+/-4.5708582e-06,
       0.00011133857+/-7.5493641e-07, 2.9713222e-05+/-1.9382607e-07,
       9.8719518e-06+/-6.2280043e-08, 3.7594719e-06+/-2.3051296e-08,
       1.5719088e-06+/-9.405684e-09, 7.0350544e-07+/-4.1220062e-09,
       3.3146904e-07+/-1.9062864e-09], dtype=object), 'P_PLUS_K': array([0.029414681+/-0.00016576186, 0.0015021708+/-5.9227147e-06,
       0.00025936996+/-1.0100834e-06, 7.1877866e-05+/-2.4698419e-07,
       2.5296996e-05+/-7.8987327e-08, 1.0305499e-05+/-2.976772e-08,
       4.6222384e-06+/-1.2553489e-08, 2.2159232e-06+/-5.7139357e-09,
       1.1157919e-06+/-2.7409542e-09], dtype=object), 'RNLOG': array([-0.002174362+/-3.1345446e-05, -0.00010599703+/-1.9269272e-06,
       -1.5475813e-05+/-2.916778e-07, -3.4678567e-06+/-6.3252752e-08,
       -9.9356556e-07+/-1.7022619e-08, -3.3961422e-07+/-3.235463e-09,
       -1.2291711e-07+/-1.5537485e-09, -4.9023553e-08+/-8.929878e-10,
       -2.0154761e-08+/-3.9732887e-10], dtype=object), 'RNLOQ': array([0.0097501419+/-2.4417777e-05, 0.00037294223+/-8.6995618e-07,
       4.8418188e-05+/-1.0758592e-07, 1.0181537e-05+/-2.1571128e-08,
       2.7874734e-06+/-5.7017162e-09, 9.0199296e-07+/-1.7835078e-09,
       3.2755533e-07+/-6.274804e-10, 1.29343e-07+/-2.4269614e-10,
       5.4399032e-08+/-9.9166043e-11], dtype=object), 'VNLO_PLUS_P_PLUS_K': array([0.039824801+/-0.00018537107823518736,
       0.00213216629+/-7.48139653421093e-06,
       0.00037070852999999997+/-1.2610303160904768e-06,
       0.000101591088+/-3.139581747965818e-07,
       3.51689478e-05+/-1.005872834044482e-07,
       1.40649709e-05+/-3.7649427635463674e-08,
       6.1941472e-06+/-1.568620341513449e-08,
       2.91942864e-06+/-7.0455657187037104e-09,
       1.44726094e-06+/-3.3386760497722146e-09], dtype=object), 'RNLO': array([0.0075757799+/-3.973367361018416e-05,
       0.00026694520000000005+/-2.114207224758262e-06,
       3.2942374999999996e-05+/-3.1088690740377987e-07,
       6.7136803e-06+/-6.682981519326452e-08,
       1.7939078400000002e-06+/-1.795213428104033e-08,
       5.6237874e-07+/-3.6944716668327343e-09,
       2.0463822e-07+/-1.6756688376992663e-09,
       8.0319447e-08+/-9.253802609304672e-10,
       3.4244271e-08+/-4.095169532751419e-10], dtype=object), 'RNLO_PLUS_VNLO_PLUS_P_PLUS_K': array([0.0474005809+/-0.00018958164854393633,
       0.0023991114900000004+/-7.774391699118547e-06,
       0.000403650905+/-1.2987871755196593e-06,
       0.0001083047683+/-3.2099214900113506e-07,
       3.6962855640000004e-05+/-1.0217671313920449e-07,
       1.4627349640000001e-05+/-3.783025934586024e-08,
       6.39878542e-06+/-1.577545066343949e-08,
       2.999748087e-06+/-7.10607661961878e-09,
       1.481505211e-06+/-3.3636976529323134e-09], dtype=object), 'order': array([1, 1, 1, 1, 1, 1, 1, 1, 1]), 'energy': array([13000, 13000, 13000, 13000, 13000, 13000, 13000, 13000, 13000]), 'energyhalf': array([6500., 6500., 6500., 6500., 6500., 6500., 6500., 6500., 6500.]), 'particle1': array([1000011, 1000011, 1000011, 1000011, 1000011, 1000011, 1000011,
       1000011, 1000011]), 'particle2': array([-1000011, -1000011, -1000011, -1000011, -1000011, -1000011,
       -1000011, -1000011, -1000011]), 'slha': array(['mastercode_with_gm2.in_mass_1000011_100.0',
       'mastercode_with_gm2.in_mass_1000011_212.5',
       'mastercode_with_gm2.in_mass_1000011_325.0',
       'mastercode_with_gm2.in_mass_1000011_437.5',
       'mastercode_with_gm2.in_mass_1000011_550.0',
       'mastercode_with_gm2.in_mass_1000011_662.5',
       'mastercode_with_gm2.in_mass_1000011_775.0',
       'mastercode_with_gm2.in_mass_1000011_887.5',
       'mastercode_with_gm2.in_mass_1000011_1000.0'], dtype='<U42'), 'pdf_lo': array(['cteq6l1', 'cteq6l1', 'cteq6l1', 'cteq6l1', 'cteq6l1', 'cteq6l1',
       'cteq6l1', 'cteq6l1', 'cteq6l1'], dtype='<U7'), 'pdfset_lo': array([0, 0, 0, 0, 0, 0, 0, 0, 0]), 'pdf_nlo': array(['cteq66', 'cteq66', 'cteq66', 'cteq66', 'cteq66', 'cteq66',
       'cteq66', 'cteq66', 'cteq66'], dtype='<U6'), 'pdfset_nlo': array([0, 0, 0, 0, 0, 0, 0, 0, 0]), 'pdf_lo_id': array([10042, 10042, 10042, 10042, 10042, 10042, 10042, 10042, 10042]), 'pdf_nlo_id': array([10550, 10550, 10550, 10550, 10550, 10550, 10550, 10550, 10550]), 'mu_f': array([1., 1., 1., 1., 1., 1., 1., 1., 1.]), 'mu_r': array([1., 1., 1., 1., 1., 1., 1., 1., 1.]), 'precision': array([0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01]), 'max_iters': array([50, 50, 50, 50, 50, 50, 50, 50, 50]), 'invariant_mass': array(['auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',
       'auto'], dtype='<U4'), 'pt': array(['auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto', 'auto',
       'auto'], dtype='<U4'), 'result': array(['total', 'total', 'total', 'total', 'total', 'total', 'total',
       'total', 'total'], dtype='<U5'), 'id': array(['5', '5', '5', '5', '5', '5', '5', '5', '5'], dtype='<U1'), 'model_path': array(['/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO',
       '/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO',
       '/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO',
       '/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO',
       '/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO',
       '/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO',
       '/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO',
       '/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO',
       '/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO'], dtype='<U40'), 'mu': array([ 100. ,  212.5,  325. ,  437.5,  550. ,  662.5,  775. ,  887.5,
       1000. ]), 'mass_1000011': array([ 100. ,  212.5,  325. ,  437.5,  550. ,  662.5,  775. ,  887.5,
       1000. ]), 'code': array(['RS', 'RS', 'RS', 'RS', 'RS', 'RS', 'RS', 'RS', 'RS'], dtype='<U2')}

Pandas

[13]:

hepi.LD2DF(rs_dl)

[13]:

	LO	NLO	NLO_PLUS_NLL	K_LO	K_NLO	K_NLO_PLUS_NLL	NLO_PLUS_NLL_OVER_NLO	VNLO	P_PLUS_K	RNLOG	...	precision	max_iters	invariant_mass	pt	result	id	model_path	mu	mass_1000011	code
0	0.19828+/-0.00029	0.26266+/-0.00035	0.0+/-0	1.0+/-0	1.3247+/-0.0026	0.0+/-0	0.0+/-0	0.01041+/-0.00008	0.02941+/-0.00017	-0.002174+/-0.000031	...	0.01	50	auto	auto	total	5	/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO	100.0	100.0	RS
1	0.013518+/-0.000017	0.016796+/-0.000020	0.0+/-0	1.0+/-0	1.2425+/-0.0022	0.0+/-0	0.0+/-0	0.000630+/-0.000005	0.001502+/-0.000006	-0.0001060+/-0.0000019	...	0.01	50	auto	auto	total	5	/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO	212.5	212.5	RS
2	0.0025746+/-0.0000031	0.0030864+/-0.0000034	0.0+/-0	1.0+/-0	1.1988+/-0.0020	0.0+/-0	0.0+/-0	0.0001113+/-0.0000008	0.0002594+/-0.0000010	(-1.548+/-0.029)e-05	...	0.01	50	auto	auto	total	5	/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO	325.0	325.0	RS
3	0.0007253+/-0.0000008	0.0008484+/-0.0000009	0.0+/-0	1.0+/-0	1.1697+/-0.0018	0.0+/-0	0.0+/-0	(2.971+/-0.019)e-05	(7.188+/-0.025)e-05	(-3.47+/-0.06)e-06	...	0.01	50	auto	auto	total	5	/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO	437.5	437.5	RS
4	0.00025157+/-0.00000028	0.00028883+/-0.00000029	0.0+/-0	1.0+/-0	1.1481+/-0.0017	0.0+/-0	0.0+/-0	(9.87+/-0.06)e-06	(2.530+/-0.008)e-05	(-9.94+/-0.17)e-07	...	0.01	50	auto	auto	total	5	/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO	550.0	550.0	RS
5	(9.924+/-0.011)e-05	0.00011233+/-0.00000011	0.0+/-0	1.0+/-0	1.1319+/-0.0016	0.0+/-0	0.0+/-0	(3.759+/-0.023)e-06	(1.0305+/-0.0030)e-05	(-3.396+/-0.032)e-07	...	0.01	50	auto	auto	total	5	/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO	662.5	662.5	RS
6	(4.271+/-0.004)e-05	(4.785+/-0.005)e-05	0.0+/-0	1.0+/-0	1.1204+/-0.0016	0.0+/-0	0.0+/-0	(1.572+/-0.009)e-06	(4.622+/-0.013)e-06	(-1.229+/-0.016)e-07	...	0.01	50	auto	auto	total	5	/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO	775.0	775.0	RS
7	(1.9558+/-0.0020)e-05	(2.1762+/-0.0020)e-05	0.0+/-0	1.0+/-0	1.1127+/-0.0015	0.0+/-0	0.0+/-0	(7.04+/-0.04)e-07	(2.216+/-0.006)e-06	(-4.90+/-0.09)e-08	...	0.01	50	auto	auto	total	5	/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO	887.5	887.5	RS
8	(9.381+/-0.009)e-06	(1.0401+/-0.0009)e-05	0.0+/-0	1.0+/-0	1.1088+/-0.0015	0.0+/-0	0.0+/-0	(3.315+/-0.019)e-07	(1.1158+/-0.0027)e-06	(-2.02+/-0.04)e-08	...	0.01	50	auto	auto	total	5	/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO	1000.0	1000.0	RS

9 rows × 38 columns

CSV

[14]:

hepi.write_csv(rs_dl,"out.csv")
print(open('out.csv','r').read())

LO,NLO,NLO_PLUS_NLL,K_LO,K_NLO,K_NLO_PLUS_NLL,NLO_PLUS_NLL_OVER_NLO,VNLO,P_PLUS_K,RNLOG,RNLOQ,VNLO_PLUS_P_PLUS_K,RNLO,RNLO_PLUS_VNLO_PLUS_P_PLUS_K,order,energy,energyhalf,particle1,particle2,slha,pdf_lo,pdfset_lo,pdf_nlo,pdfset_nlo,pdf_lo_id,pdf_nlo_id,mu_f,mu_r,precision,max_iters,invariant_mass,pt,result,id,model_path,mu,mass_1000011,code
0.19828+/-0.00029,0.26266+/-0.00035,0.0+/-0,1.0+/-0,1.3247+/-0.0026,0.0+/-0,0.0+/-0,0.01041+/-0.00008,0.02941+/-0.00017,-0.002174+/-0.000031,0.009750+/-0.000024,0.03982+/-0.00019,0.00758+/-0.00004,0.04740+/-0.00019,1,13000,6500.0,1000011,-1000011,mastercode_with_gm2.in_mass_1000011_100.0,cteq6l1,0,cteq66,0,10042,10550,1.0,1.0,0.01,50,auto,auto,total,5,/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO,100.0,100.0,RS
0.013518+/-0.000017,0.016796+/-0.000020,0.0+/-0,1.0+/-0,1.2425+/-0.0022,0.0+/-0,0.0+/-0,0.000630+/-0.000005,0.001502+/-0.000006,-0.0001060+/-0.0000019,0.0003729+/-0.0000009,0.002132+/-0.000007,0.0002669+/-0.0000021,0.002399+/-0.000008,1,13000,6500.0,1000011,-1000011,mastercode_with_gm2.in_mass_1000011_212.5,cteq6l1,0,cteq66,0,10042,10550,1.0,1.0,0.01,50,auto,auto,total,5,/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO,212.5,212.5,RS
0.0025746+/-0.0000031,0.0030864+/-0.0000034,0.0+/-0,1.0+/-0,1.1988+/-0.0020,0.0+/-0,0.0+/-0,0.0001113+/-0.0000008,0.0002594+/-0.0000010,(-1.548+/-0.029)e-05,(4.842+/-0.011)e-05,0.0003707+/-0.0000013,(3.294+/-0.031)e-05,0.0004037+/-0.0000013,1,13000,6500.0,1000011,-1000011,mastercode_with_gm2.in_mass_1000011_325.0,cteq6l1,0,cteq66,0,10042,10550,1.0,1.0,0.01,50,auto,auto,total,5,/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO,325.0,325.0,RS
0.0007253+/-0.0000008,0.0008484+/-0.0000009,0.0+/-0,1.0+/-0,1.1697+/-0.0018,0.0+/-0,0.0+/-0,(2.971+/-0.019)e-05,(7.188+/-0.025)e-05,(-3.47+/-0.06)e-06,(1.0182+/-0.0022)e-05,0.00010159+/-0.00000031,(6.71+/-0.07)e-06,0.00010830+/-0.00000032,1,13000,6500.0,1000011,-1000011,mastercode_with_gm2.in_mass_1000011_437.5,cteq6l1,0,cteq66,0,10042,10550,1.0,1.0,0.01,50,auto,auto,total,5,/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO,437.5,437.5,RS
0.00025157+/-0.00000028,0.00028883+/-0.00000029,0.0+/-0,1.0+/-0,1.1481+/-0.0017,0.0+/-0,0.0+/-0,(9.87+/-0.06)e-06,(2.530+/-0.008)e-05,(-9.94+/-0.17)e-07,(2.787+/-0.006)e-06,(3.517+/-0.010)e-05,(1.794+/-0.018)e-06,(3.696+/-0.010)e-05,1,13000,6500.0,1000011,-1000011,mastercode_with_gm2.in_mass_1000011_550.0,cteq6l1,0,cteq66,0,10042,10550,1.0,1.0,0.01,50,auto,auto,total,5,/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO,550.0,550.0,RS
(9.924+/-0.011)e-05,0.00011233+/-0.00000011,0.0+/-0,1.0+/-0,1.1319+/-0.0016,0.0+/-0,0.0+/-0,(3.759+/-0.023)e-06,(1.0305+/-0.0030)e-05,(-3.396+/-0.032)e-07,(9.020+/-0.018)e-07,(1.406+/-0.004)e-05,(5.62+/-0.04)e-07,(1.463+/-0.004)e-05,1,13000,6500.0,1000011,-1000011,mastercode_with_gm2.in_mass_1000011_662.5,cteq6l1,0,cteq66,0,10042,10550,1.0,1.0,0.01,50,auto,auto,total,5,/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO,662.5,662.5,RS
(4.271+/-0.004)e-05,(4.785+/-0.005)e-05,0.0+/-0,1.0+/-0,1.1204+/-0.0016,0.0+/-0,0.0+/-0,(1.572+/-0.009)e-06,(4.622+/-0.013)e-06,(-1.229+/-0.016)e-07,(3.276+/-0.006)e-07,(6.194+/-0.016)e-06,(2.046+/-0.017)e-07,(6.399+/-0.016)e-06,1,13000,6500.0,1000011,-1000011,mastercode_with_gm2.in_mass_1000011_775.0,cteq6l1,0,cteq66,0,10042,10550,1.0,1.0,0.01,50,auto,auto,total,5,/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO,775.0,775.0,RS
(1.9558+/-0.0020)e-05,(2.1762+/-0.0020)e-05,0.0+/-0,1.0+/-0,1.1127+/-0.0015,0.0+/-0,0.0+/-0,(7.04+/-0.04)e-07,(2.216+/-0.006)e-06,(-4.90+/-0.09)e-08,(1.2934+/-0.0024)e-07,(2.919+/-0.007)e-06,(8.03+/-0.09)e-08,(3.000+/-0.007)e-06,1,13000,6500.0,1000011,-1000011,mastercode_with_gm2.in_mass_1000011_887.5,cteq6l1,0,cteq66,0,10042,10550,1.0,1.0,0.01,50,auto,auto,total,5,/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO,887.5,887.5,RS
(9.381+/-0.009)e-06,(1.0401+/-0.0009)e-05,0.0+/-0,1.0+/-0,1.1088+/-0.0015,0.0+/-0,0.0+/-0,(3.315+/-0.019)e-07,(1.1158+/-0.0027)e-06,(-2.02+/-0.04)e-08,(5.440+/-0.010)e-08,(1.4473+/-0.0033)e-06,(3.42+/-0.04)e-08,(1.4815+/-0.0034)e-06,1,13000,6500.0,1000011,-1000011,mastercode_with_gm2.in_mass_1000011_1000.0,cteq6l1,0,cteq66,0,10042,10550,1.0,1.0,0.01,50,auto,auto,total,5,/opt/MG5_aMC_v2_7_0/models/MSSMatNLO_UFO,1000.0,1000.0,RS

JSON

[15]:

hepi.write_json(rs_dl,hepi.Order.NLO,"mass_1000011","out.json",error_sym=True)
print(open('out.json','r').read())

{"initial state": "pp", "order": "NLO", "source": "HEPi", "contact": "?", "tool": "RS", "process_latex": "$\\tilde{e}_{L}^{-}\\tilde{e}_{L}^{+}$", "comment": "?", "reference": "?", "Ecom [GeV]": "13000", "process_id": "pp_13000_1000011_-1000011", "PDF set": "cteq66", "data": {"100.0": {"xsec_pb": 0.26266219, "unc_pb": 0.00035483454}, "212.5": {"xsec_pb": 0.016796404, "unc_pb": 1.9662724e-05}, "325.0": {"xsec_pb": 0.0030864231, "unc_pb": 3.409076e-06}, "437.5": {"xsec_pb": 0.00084837761, "unc_pb": 8.8924337e-07}, "550.0": {"xsec_pb": 0.00028882589, "unc_pb": 2.9046289e-07}, "662.5": {"xsec_pb": 0.00011233356, "unc_pb": 1.0906148e-07}, "775.0": {"xsec_pb": 4.7848073e-05, "unc_pb": 4.5120962e-08}, "887.5": {"xsec_pb": 2.1762029e-05, "unc_pb": 2.0001873e-08}, "1000.0": {"xsec_pb": 1.0401314e-05, "unc_pb": 9.3348503e-09}}, "parameters": "?"}

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