contur.data package

Submodules

contur.data.build_covariance module

class contur.data.build_covariance.CovarianceBuilder(ao)[source]

Bases: object

ao Yoda AO

Class to handle retrieval of annotations/errors from YODA objects

buildCovFromBreakdown(ignore_corrs=False)[source]

Build the covariance from error breakdown and return it

buildCovFromErrorBar(assume_correlated=False)[source]

Build the covariance from error bars and return it

getErrorBreakdown()[source]

return the breakdown of uncertainties

contur.data.static_db module

exception contur.data.static_db.InvalidPath[source]

Bases: Exception

contur.data.static_db.LumiFinder(h)[source]

Get the integrated luminosity, pool and subpool for a valid contur histogram. Else return INVALID.

Parameters

h – (string) yoda histogram path

contur.data.static_db.getAnalyses(pool=None, beam=None)[source]

Return a list of rivet analyses in the input pool. If no pool supplied, return all the ones Contur knows with the supplied beam. If no beam, return all of them regardless of beam or pool.

contur.data.static_db.getBeams(pool=None)[source]

Get the list of beam known configurations, specific to the named pool if given

contur.data.static_db.getDescription(pool)[source]

Get a short description of the named pool

contur.data.static_db.getNormInfo(h)
Parameters

h – (string) histogram path.

Returns:

  • isScaled - does this histogram need to be scaled to turn it into a differential cross section?

  • scaleFactor - the scale factor, if so (=1 otherwise)

  • nev_differential - factor for converting “number of events per something” plots (searches) into number of events. See analysis.sql for detailed description.

contur.data.static_db.getPools()[source]

Get the full list of analysis pools

contur.data.static_db.getTheoryDescription(ana)[source]

Retrun a list of the SM theory predictions for this analysis (if any). Otherwise return False.

contur.data.static_db.get_pool_info(path)[source]

Given the yoda path of a histogram, return the pool and the associated integrated lumi.

contur.data.static_db.hasBVeto(ana)[source]

Does this analysis have measurements with a b-jet-veto problem?

contur.data.static_db.hasHiggsWW(ana)[source]

Does this analysis have Higgs -> WW measurements?

contur.data.static_db.hasHiggsgg(ana)[source]

Does this analysis have Higgs -> photons measurements?

contur.data.static_db.hasMETRatio(ana)

Does this analysis have missing-energy ratio measurements?

contur.data.static_db.hasNuTrue(ana)[source]

Does this analysis have measurements with a truth-neutrino problem?

contur.data.static_db.hasRatio(ana)[source]

Does this analysis have ratio measurements?

contur.data.static_db.hasSearches(ana)[source]

Does this analysis have search measurements?

contur.data.static_db.init_dbs()[source]

The principle function to read the database and populate dictionaries using the data. it is invoked by the first access request.

contur.data.static_db.isMETRatio(h)

Is this a missing energy ratio plot?

contur.data.static_db.isNorm(h)[source]
Parameters

h – (string) histogram path.

Returns:

  • isScaled - does this histogram need to be scaled to turn it into a differential cross section?

  • scaleFactor - the scale factor, if so (=1 otherwise)

  • nev_differential - factor for converting “number of events per something” plots (searches) into number of events. See analysis.sql for detailed description.

contur.data.static_db.isRatio(h)[source]

Is this a ratio plot? :param h: (string) yoda histogram path

contur.data.static_db.isSearch(h)[source]

Is this a search event-count plot?

Parameters

h – (string) yoda histogram path

class contur.data.static_db.listdict[source]

Bases: dict

Dictionary which returns an empty list if the key is missing.

contur.data.static_db.splitPath(path)[source]

Take a yoda histogram path and return the analysis name and the histogram name

contur.data.static_db.theoryComp(h)[source]

If this histogram always requires a SM theory comparison, return True.

Parameters

h – (string) yoda histogram path

contur.data.static_db.validHisto(h, gotTheory=True)[source]

Tests a histo path to see if it is a valid contur histogram for this run (taking into account the run time flags).

contur.data.generate_rivet_anas module

contur.data.generate_rivet_anas.generate_rivet_anas(output_directory, webpages)[source]

Generate various rivet analysis listings from the Contur database.

  • the .ana files for Herwig running

  • the script to set the analysis list environment variables

  • (optionally) the contur webpage listings.

Parameters
  • output_directory – directory to write the shared files.

  • webpages – if true, also write out the contur webpage listings.

contur.data.generate_rivet_anas.write_sm_file(ana_name, pool, out_dir, text_string)[source]

Write an rst file describing the theory predictions available for this analysis.

Parameters
  • ana_name – name of the analysis (including any rivet option string)

  • out_dir – name of the directory the write to

  • text_string – an rst-style link, with text, will be appended to this and returned.

Module contents