hepi.results

Results and postprocessing for the hepi package.

Attributes

required_numerical_uncertainty_factor
unv
usd

Classes

Result

General result class. All uncertainties are of numerical origin.

Functions

pdf_errors(li, dl[, ordernames, confidence_level, n_jobs])	Just like pdf_error but over a list of ordernames.
_pdf_error_single(members, i, dl, ordername[, ...])
pdf_error(li, dl[, ordername, confidence_level, n_jobs])	Computes Parton Density Function (PDF) uncertainties through lhapdf.set.uncertainty().
scale_errors(li, dl[, ordernames, n_jobs])	Just like scale_error but over a list of ordernames.
_scale_error_single(members, i, dl[, ordername])
scale_error(li, dl[, ordername, n_jobs])	Computes seven-point scale uncertainties from the results where the renormalization and factorization scales are varied by factors of 2 and relative factors of four are excluded (cf. seven_point_scan()).
combine_errors(dl[, ordernames])	Just like combine_error but over a list of ordernames.
combine_error(dl[, ordername])	Combines seven-point scale uncertainties and pdf uncertainties from the results by Pythagorean addition.
asym_to_sym_error(central, errminus, errplus)
add_errors(error1, error2)
asym_to_sym_combined_error(central, errminus1, ...)

Module Contents

hepi.results.required_numerical_uncertainty_factor = 5

hepi.results.unv

hepi.results.usd

class hepi.results.Result(lo=None, nlo=None, nlo_plus_nll=None, annlo_plus_nnll=None)

Bases: hepi.util.DictData

General result class. All uncertainties are of numerical origin.

Variables:

• LO (double) – Leading Order result. Defaults to None.

• NLO (double) – Next-to-Leading Order result. Defaults to None.

• NLO_PLUS_NLL (double) – Next-to-Leading Order plus Next-to-Leading Logarithm result. Defaults to None.

• K_LO (double) – LO divided by LO.

• K_NLO (double) – NLO divided by LO result.

• K_NLO_PLUS_NLL (double) – NLO+NLL divided by LO.

• K_aNNLO_PLUS_NNLL (double) – aNNLO+NNLL divided by LO.

• NLO_PLUS_NLL_OVER_NLO (double) – NLO+NLL divided by NLO.

• aNNLO_PLUS_NNLL_OVER_NLO (double) – aNNLO+NNLL divided by NLO.

Sets given and computes dependent Attributes.

Parameters:

• lo (double) – corresponds to LO.

• nlo (double) – corresponds to NLO.

• nlo_plus_nll (double) – corresponds to NLO_PLUS_NLL.

• annlo_plus_nnll (double) – corresponds to aNNLO_PLUS_NNLL.

LO = None

NLO = None

NLO_PLUS_NLL = None

aNNLO_PLUS_NNLL = None

hepi.results.pdf_errors(li, dl, ordernames=None, confidence_level=90, n_jobs=None)

Just like pdf_error but over a list of ordernames.

hepi.results._pdf_error_single(members, i, dl, ordername, confidence_level=90)

hepi.results.pdf_error(li, dl, ordername='LO', confidence_level=90, n_jobs=None)

Computes Parton Density Function (PDF) uncertainties through lhapdf.set.uncertainty().

Parameters:

• li (list of Input) – Input list.

• dl (dict) – Result dictionary with lists per entry.

• ordername (str) – Name of the order.

• confidence_level (double) – Confidence Level for PDF uncertainty

Returns:

Modified dl with new ordername_{PDF,PDF_CENTRAL,PDF_ERRPLUS,PDF_ERRMINUS,PDF_ERRSYM} entries.

• (ordername)_`PDF` contains a symmetrized uncertainties object.

Return type:

dict

hepi.results.scale_errors(li, dl, ordernames=None, n_jobs=None)

Just like scale_error but over a list of ordernames.

hepi.results._scale_error_single(members, i, dl, ordername='LO')

hepi.results.scale_error(li, dl, ordername='LO', n_jobs=None)

Computes seven-point scale uncertainties from the results where the renormalization and factorization scales are varied by factors of 2 and relative factors of four are excluded (cf. seven_point_scan()).

Parameters:

• li (list of Input) – Input list.

• dl (dict) – Result dictionary with lists per entry.

Returns:

Modified dl with new ordername_{SCALE,SCALE_ERRPLUS,SCALE_ERRMINUS} entries.

• ordername_SCALE contains a symmetrized uncertainties object.

Return type:

dict

hepi.results.combine_errors(dl, ordernames=None)

Just like combine_error but over a list of ordernames.

hepi.results.combine_error(dl, ordername='LO')

Combines seven-point scale uncertainties and pdf uncertainties from the results by Pythagorean addition.

Note

Running scale_errors() and pdf_errors() before is necessary.

Parameters:

dl (dict) – Result dictionary with lists per entry.

Returns:

Modified dl with new ordername_{COMBINED,ERRPLUS,ERRMINUS} entries.

• ordername_COMBINED contains a symmetrized uncertainties object.

Return type:

dict

hepi.results.asym_to_sym_error(central, errminus, errplus)

hepi.results.add_errors(error1, error2)

hepi.results.asym_to_sym_combined_error(central, errminus1, errplus1, errminus2, errplus2)