hepi.input

Attributes

`in_dir`	Input directory.
`out_dir`	Output directory.
`pre`	Prefix for run commands.
`multi_scan`
`scale_scan`
`seven_point_scan`
`pdf_scan`

Classes

Input

Input for computation and scans.

Functions

`get_input_dir`()	Get the input directory.
`get_output_dir`()	Get the output directory.
`get_pre`()	Gets the command prefix.
`set_input_dir`(ind)	Sets the input directory.
`set_output_dir`(outd[, create])	Sets the output directory.
`set_pre`(ppre)	Sets the command prefix.
`is_gluino`(iid)
`is_neutralino`(iid)
`is_chargino`(iid)
`is_weakino`(iid)
`is_squark`(iid)
`is_slepton`(iid)
`update_slha`(i)	Updates dependent parameters in Input i.
`scan`(input_list, var, rrange)	Scans a variable var over rrange in input_list.
`scan_multi`(li, **kwargs)	Magically scans the variables passed to this function.
`scan_scale`(l[, rrange, distance])	Scans scale by varying mu_f and mu_r.
`scan_seven_point`(input_list)	Scans scale by varying mu_f and mu_r by factors of two excluding relative factors of 4.
`keep_where`(input_list, condition)	Only keep the inputs where the condition is true.
`remove_where`(input_list, condition, **kwargs)	Remove elements in list which satisfy condition.
`change_where`(input_list, dicts, **kwargs)	Applies the values of dicts if the key value pairs in kwargs agree with a member of the list input_list.
`scan_invariant_mass`(input_list, diff, points[, low])	Logarithmic invariant_mass scan close to the production threshold.
`slha_write`(newname, d)
`masses_scan`(input_list, varis, rrange[, diff_L_R, negate])	Scans the PDG identified masses in varis over rrange in the list input_list.
`mass_scan`(input_list, var, rrange[, diff_L_R])	Scans the PDG identified mass var over rrange in the list l.
`slha_scan`(input_list, block, var, rrange)	Scan a generic
`slha_scan_rel`(input_list, lambdas, rrange)	Scan a generic slha variable.
`scan_pdf`(input_list)	Scans NLO PDF sets.

Module Contents

hepi.input.in_dir = './input/'[source]: Input directory.

hepi.input.out_dir = './output/'[source]: Output directory.

hepi.input.pre = 'nice -n 5'[source]: Prefix for run commands.

hepi.input.get_input_dir()[source]

Get the input directory.

Returns:: in_dir
Return type:: str

hepi.input.get_output_dir()[source]

Get the output directory.

Returns:: out_dir
Return type:: str

hepi.input.get_pre()[source]

Gets the command prefix.

Returns:: pre
Return type:: str

hepi.input.set_input_dir(ind)[source]

Sets the input directory.

Parameters:: ind (str) – new input directory.

hepi.input.set_output_dir(outd, create=True)[source]

Sets the output directory.

Parameters:

outd (str) – new output directory. create (bool): create directory if not existing
create (bool)

hepi.input.set_pre(ppre)[source]

Sets the command prefix.

Parameters:: ppre (str) – new command prefix.

class hepi.input.Input(order, energy, particle1, particle2, slha, pdf_lo, pdf_nlo, mu_f=1.0, mu_r=1.0, pdfset_lo=0, pdfset_nlo=0, precision=0.001, max_iters=50, invariant_mass='auto', result='total', pt='auto', id='', model='', update=True)[source]

Bases: hepi.util.DictData

Input for computation and scans.

Variables:

order (Order) – LO, NLO or NLO+NLL computation.
energy (int) – CMS energy in GeV.
energyhalf (int) – Halfed energy.
particle1 (int) – PDG identifier of the first final state particle.
particle2 (int) – PDG identifier of the second final state particle.
slha (str) – File path of for the base slha. Modified slha files will be used if a scan requires a change of the input.
pdf_lo (str) – LO PDF name.
pdf_nlo (str) – NLO PDF name.
pdfset_lo (int) – LO PDF member/set id.
pdfset_nlo (int) – NLO PDF member/set id.
pdf_lo_id (int) – LO PDF first member/set id.
pdf_nlo_id (int) – NLO PDF first member/set id.
mu (double) – central scale factor.
mu_f (double) – Factorization scale factor.
mu_r (double) – Renormalization scale factor.
precision (double) – Desired numerical relative precision.
max_iters (int) – Upper limit on integration iterations.
invariant_mass (str) – Invariant mass mode ‘auto = sqrt((p1+p2)^2)’ else value.
pt (str) – Transverse Momentum mode ‘auto’ or value.
result (str) – Result type ‘total’/’pt’/’ptj’/’m’.
id (str) – Set an id of this run.
model (str) – Path for MadGraph model.
update (bool) – Update dependent mu else set to zero.

Parameters:

order (hepi.order.Order)
energy (float)
particle1 (int)
particle2 (int)
slha (str)
pdf_lo (str)
pdf_nlo (str)

order[source]

energy[source]

energyhalf[source]

particle1[source]

particle2[source]

slha[source]

pdf_lo[source]

pdfset_lo = 0[source]

pdf_nlo[source]

pdfset_nlo = 0[source]

pdf_lo_id = 0[source]

pdf_nlo_id = 0[source]

mu_f = 1.0[source]

mu_r = 1.0[source]

precision = 0.001[source]

max_iters = 50[source]

invariant_mass = 'auto'[source]

pt = 'auto'[source]

result = 'total'[source]

id = ''[source]

model = ''[source]

mu = 0.0[source]

has_gluino()[source]

Return type:: bool

has_neutralino()[source]

Return type:: bool

has_charginos()[source]

Return type:: bool

has_weakino()[source]

Return type:: bool

has_squark()[source]

Return type:: bool

has_slepton()[source]

Return type:: bool

hepi.input.is_gluino(iid)[source]

Parameters:: iid (int)
Return type:: bool

hepi.input.is_neutralino(iid)[source]

Parameters:: iid (int)
Return type:: bool

hepi.input.is_chargino(iid)[source]

Parameters:: iid (int)
Return type:: bool

hepi.input.is_weakino(iid)[source]

Parameters:: iid (int)
Return type:: bool

hepi.input.is_squark(iid)[source]

Parameters:: iid (int)
Return type:: bool

hepi.input.is_slepton(iid)[source]

Parameters:: iid (int)
Return type:: bool

hepi.input.update_slha(i)[source]

Updates dependent parameters in Input i.

Mainly concerns the mu value used by madgraph.

Parameters:: i (Input)

hepi.input.scan(input_list, var, rrange)[source]

Scans a variable var over rrange in input_list.

Note

This function does not ensure that dependent vairables are updated (see energyhalf in Examples).

Parameters:

input_list (list of Input) – Input parameters that get scanned each.
var (str) – Scan variable name.
rrange (Iterable) – Range of var to be scanned.

Returns:

Modified list with scan runs added.

Return type:

list of Input

Examples

>>> li = [Input(Order.LO, 13000,  1000022,1000022, "None", "CT14lo","CT14lo",update=False)]
>>> li = scan(li,"energy",range(10000,13000,1000))
>>> for e in li:
...     print(e)
{'order': <Order.LO: 0>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 12000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
>>> for e in scan(li,"order",[Order.LO,Order.NLO,Order.NLO_PLUS_NLL]):
...     print(e)
{'order': <Order.LO: 0>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO_PLUS_NLL: 2>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO_PLUS_NLL: 2>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 12000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 12000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO_PLUS_NLL: 2>, 'energy': 12000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}

hepi.input.scan_multi(li, **kwargs)[source]

Magically scans the variables passed to this function.

Parameters:

**kwargs
li (List[Input])

Return type:

List[Input]

Examples

>>> oli = [Input(Order.LO, 13000,  1000022,1000022, "None", "CT14lo","CT14lo",update=False)]
>>> li = scan_multi(oli,energy=range(10000,13000,1000))
>>> for e in li:
...     print(e)
{'order': <Order.LO: 0>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 12000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
>>> for e in scan_multi(oli,energy=range(10000,13000,1000),order=[Order.LO,Order.NLO,Order.NLO_PLUS_NLL]):
...     print(e)
{'order': <Order.LO: 0>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO_PLUS_NLL: 2>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO_PLUS_NLL: 2>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 12000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 12000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO_PLUS_NLL: 2>, 'energy': 12000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}

hepi.input.multi_scan[source]

hepi.input.scan_scale(l, rrange=3, distance=2.0)[source]

Scans scale by varying mu_f and mu_r.

They take rrange values from 1/distance to distance in lograthmic spacing. Only points with mu_f`=`mu_r or mu_r/f`=1 or `mu_r/f`=`distance or mu_r/f`=1/`distance are returned.

Examples

>>> li = [Input(Order.LO, 13000,  1000022,1000022, "None", "CT14lo","CT14lo",update=False)]
>>> for e in scan_scale(li):
...     print(e)
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 0.5, 'mu_r': 0.5, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 0.5, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 0.5, 'mu_r': 2.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 0.5, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 2.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 2.0, 'mu_r': 0.5, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 2.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 2.0, 'mu_r': 2.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}

Parameters:: l (List[Input])

hepi.input.scale_scan[source]

hepi.input.scan_seven_point(input_list)[source]

Scans scale by varying mu_f and mu_r by factors of two excluding relative factors of 4.

Examples

>>> li = [Input(Order.LO, 13000,  1000022,1000022, "None", "CT14lo","CT14lo",update=False)]
>>> for e in scan_seven_point(li):
...     print(e)
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 0.5, 'mu_r': 0.5, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 0.5, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 0.5, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 2.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 2.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 2.0, 'mu_r': 2.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}

Parameters:: input_list (List[Input])

hepi.input.seven_point_scan[source]

hepi.input.keep_where(input_list, condition)[source]

Only keep the inputs where the condition is true.

Inversion of the remove_where function.

Parameters:

input_list (List[Input]) – List[Input] The list of inputs to filter.
condition – Callable[[Input.__dict__], bool] The condition to filter on.

hepi.input.remove_where(input_list, condition, **kwargs)[source]

Remove elements in list which satisfy condition.

Parameters:

input_list (List[Input]) – List[Input] The list of inputs to filter.
condition – Callable[[Input.__dict__], bool] The condition to filter on.

Examples

>>> li = scan_multi([Input(Order.LO, 13000,  1000022,1000022, "None", "CT14lo","CT14lo",update=False)],energy=range(10000,13000,1000))
>>> for e in remove_where(li,lambda dict : (dict["energy"] == 10000 or dict["energy"] == 11000)):
...     print(e)
{'order': <Order.LO: 0>, 'energy': 12000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}

hepi.input.change_where(input_list, dicts, **kwargs)[source]

Applies the values of dicts if the key value pairs in kwargs agree with a member of the list input_list.

The changes only applied to the matching list members.

Examples

>>> li = scan_multi([Input(Order.LO, 13000,  1000022,1000022, "None", "CT14lo","CT14lo",update=False)],energy=range(10000,13000,1000))
>>> for e in change_where(li,{'order':Order.NLO},energy=11000):
...     print(e)
{'order': <Order.LO: 0>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 12000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
>>> li = scan_multi([Input(Order.LO, 13000,  1000022,1000022, "None", "CT14lo","CT14lo",update=False)],energy=range(10000,12000,1000),mu_f=range(1,3))
>>> for e in change_where(li,{'order':Order.NLO},energy=11000,mu_f=1):
...     print(e)
{'order': <Order.LO: 0>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 10000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 2, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 1, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.LO: 0>, 'energy': 11000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14lo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13200, 'mu_f': 2, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}

Parameters:

input_list (List[Input])
dicts (dict)

hepi.input.scan_invariant_mass(input_list, diff, points, low=0.001)[source]

Logarithmic invariant_mass scan close to the production threshold.

Parameters:: input_list (List[Input])

hepi.input.slha_write(newname, d)[source]

hepi.input.masses_scan(input_list, varis, rrange, diff_L_R=None, negate=None)[source]

Scans the PDG identified masses in varis over rrange in the list input_list. diff_L_R allows to set a fixed difference between masses of left- and right-handed particles.

Parameters:

input_list (List[Input])
varis (List[int])

Return type:

List[Input]

hepi.input.mass_scan(input_list, var, rrange, diff_L_R=None)[source]

Scans the PDG identified mass var over rrange in the list l. diff_L_R allows to set a fixed difference between masses of left- and right-handed particles.

Parameters:

input_list (List[Input])
var (int)

Return type:

List[Input]

hepi.input.slha_scan(input_list, block, var, rrange)[source]

Scan a generic

Parameters:

input_list (List[Input])
rrange (List)

Return type:

List[Input]

hepi.input.slha_scan_rel(input_list, lambdas, rrange)[source]

Scan a generic slha variable.

Parameters:

input_list (List[Input])
rrange (List)

Return type:

List[Input]

hepi.input.scan_pdf(input_list)[source]

Scans NLO PDF sets.

The PDF sets are infered from lhapdf.getPDFSet with the argument of pdfset_nlo.

Examples

>>> li = [Input(Order.NLO, 13000,  1000022,1000022, "None", "CT14lo","CT14nlo",update=False)]
>>> for e in scan_pdf(li):
...     print(e)
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 0, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 1, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 2, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 3, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 4, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 5, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 6, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 7, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 8, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 9, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 10, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 11, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 12, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 13, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 14, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 15, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 16, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 17, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 18, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 19, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 20, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 21, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 22, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 23, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 24, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 25, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 26, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 27, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 28, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 29, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 30, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 31, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 32, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 33, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 34, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 35, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 36, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 37, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 38, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 39, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 40, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 41, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 42, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 43, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 44, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 45, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 46, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 47, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 48, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 49, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 50, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 51, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 52, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 53, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 54, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 55, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}
{'order': <Order.NLO: 1>, 'energy': 13000, 'energyhalf': 6500.0, 'particle1': 1000022, 'particle2': 1000022, 'slha': 'None', 'pdf_lo': 'CT14lo', 'pdfset_lo': 0, 'pdf_nlo': 'CT14nlo', 'pdfset_nlo': 56, 'pdf_lo_id': 13200, 'pdf_nlo_id': 13100, 'mu_f': 1.0, 'mu_r': 1.0, 'precision': 0.001, 'max_iters': 50, 'invariant_mass': 'auto', 'pt': 'auto', 'result': 'total', 'id': '', 'model': '', 'mu': 0.0}

Parameters:: input_list (List[Input])

hepi.input.pdf_scan[source]