hepi.results

Results and postprocessing for the hepi package.

Module Contents

Classes

Result

General result class.

Functions

pdf_errors(li, dl, ordernames=['LO', 'NLO', 'aNNLO_PLUS_NNLL'], confidence_level=90)

Just like pdf_error but over a list of ordernames.

pdf_error(li, dl, ordername='LO', confidence_level=90)

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

pdf_error_old(li, dl, confidence_level=90)

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

scale_errors(li, dl, ordernames=['LO', 'NLO', 'aNNLO_PLUS_NNLL'])

Just like scale_error but over a list of ordernames.

scale_error(li, dl, ordername='LO')

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()).

scale_error_old(li, dl)

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=['LO', 'NLO', 'aNNLO_PLUS_NNLL'])

Just like combine_error but over a list of ordernames.

combine_error(dl: dict, ordername='LO')

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

combine_errors_old(dl: dict)

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

Attributes

required_numerical_uncertainty_factor

If the numerical uncertainty is required_numerical_uncertainty_factor times higher than the scale or pdf uncertainty a warning is shown.
hepi.results.required_numerical_uncertainty_factor = 10[source]

If the numerical uncertainty is required_numerical_uncertainty_factor times higher than the scale or pdf uncertainty a warning is shown.

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

Bases: hepi.util.DictData

General result class.

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.

hepi.results.pdf_errors(li, dl, ordernames=['LO', 'NLO', 'aNNLO_PLUS_NNLL'], confidence_level=90)[source]

Just like pdf_error but over a list of ordernames.

hepi.results.pdf_error(li, dl, ordername='LO', confidence_level=90)[source]

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 LO/NLO/NLO_PLUS_NLL _ PDF/PDF_CENTRAL/PDF_ERRPLUS/PDF_ERRMINUS/PDF_ERRSYM entries.

  • LO/NLO/NLO_PLUS_NLL _ PDF contains a symmetrized uncertainties object.

Return type

dict

hepi.results.pdf_error_old(li, dl, confidence_level=90)[source]

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.

  • confidence_level (double) – Confidence Level for PDF uncertainty

Returns

Modified dl with new LO/NLO/NLO_PLUS_NLL _ PDF/PDF_CENTRAL/PDF_ERRPLUS/PDF_ERRMINUS/PDF_ERRSYM entries.

  • LO/NLO/NLO_PLUS_NLL _ PDF contains a symmetrized uncertainties object.

Return type

dict

hepi.results.scale_errors(li, dl, ordernames=['LO', 'NLO', 'aNNLO_PLUS_NNLL'])[source]

Just like scale_error but over a list of ordernames.

hepi.results.scale_error(li, dl, ordername='LO')[source]

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 LO/NLO/NLO_PLUS_NLL _ SCALE/SCALE_ERRPLUS/SCALE_ERRMINUS/SCALE_ERRSYM entries.

  • LO/NLO/NLO_PLUS_NLL _ SCALE contains a symmetrized uncertainties object.

Return type

dict

hepi.results.scale_error_old(li, dl)[source]

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 LO/NLO/NLO_PLUS_NLL _ SCALE/SCALE_ERRPLUS/SCALE_ERRMINUS/SCALE_ERRSYM entries.

  • LO/NLO/NLO_PLUS_NLL _ SCALE contains a symmetrized uncertainties object.

Return type

dict

hepi.results.combine_errors(dl, ordernames=['LO', 'NLO', 'aNNLO_PLUS_NNLL'])[source]

Just like combine_error but over a list of ordernames.

hepi.results.combine_error(dl: dict, ordername='LO')[source]

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 LO/NLO/NLO_PLUS_NLL _ COMBINED/ERRPLUS/ERRMINUS entries.

  • LO/NLO/NLO_PLUS_NLL _ COMBINED contains a symmetrized uncertainties object.

Return type

dict

hepi.results.combine_errors_old(dl: dict)[source]

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 LO/NLO/NLO_PLUS_NLL _ COMBINED/ERRPLUS/ERRMINUS entries.

  • LO/NLO/NLO_PLUS_NLL _ COMBINED contains a symmetrized uncertainties object.

Return type

dict