sherlock.transient_catalogue_crossmatch (class)

class sherlock.transient_catalogue_crossmatch(log, dbConn=False, settings=False, colMaps=False, transients=[])[source]

crossmatch a list of transients against a suite of catalogues according to given search algorithm

Key Arguments:
  • dbConn – mysql database connection for the catalogues
  • log – logger
  • settings – the settings dictionary
  • colMaps – maps of the important column names for each table/view in the crossmatch-catalogues database
  • transients – the list of transients

Usage:

To setup your logger, settings and database connections, please use the fundamentals package (see tutorial here).

To initiate a transient_catalogue_crossmatch object, use the following:

from sherlock import transient_catalogue_crossmatch
xmatcher = transient_catalogue_crossmatch(
    log=log,
    settings=settings,
    dbConn=dbConn,
    colMaps=colMaps,
    transients=transients
)

Then to run the transient through the search algorithm found in the settings file, use the match method:

classifications = xmatcher.match()

Todo

  • update key arguments values and definitions with defaults
  • update return values and definitions
  • update usage examples and text
  • update docstring text
  • check sublime snippet exists
  • clip any useful text to docs mindmap
  • regenerate the docs and check redendering of this docstring

Methods

angular_crossmatch_against_catalogue(objectList) perform an angular separation crossmatch against a given catalogue in the database and annotate the crossmatch with some value added parameters (distances, physical separations, sub-type of transient etc)
match() match the transients against the sherlock-catalogues according to the search algorithm and return matches alongside the predicted classification(s)
physical_separation_crossmatch_against_catalogue(…) perform an physical separation crossmatch against a given catalogue in the database
_annotate_crossmatch_with_value_added_parameters(…) annotate each crossmatch with physical parameters such are distances etc
_bright_star_match(matchedObjects, …) perform a bright star match on the crossmatch results if required by the catalogue search
_galaxy_association_cuts(matchedObjects, …) perform a bright star match on the crossmatch results if required by the catalogue search
match()[source]

match the transients against the sherlock-catalogues according to the search algorithm and return matches alongside the predicted classification(s)

Return:
  • classification – the crossmatch results and classifications assigned to the transients

See the class docstring for usage.

Todo

  • update key arguments values and definitions with defaults
  • update return values and definitions
  • update usage examples and text
  • update docstring text
  • check sublime snippet exists
  • clip any useful text to docs mindmap
  • regenerate the docs and check redendering of this docstring
angular_crossmatch_against_catalogue(objectList, searchPara={}, search_name='', brightnessFilter=False, physicalSearch=False, classificationType=False)[source]

perform an angular separation crossmatch against a given catalogue in the database and annotate the crossmatch with some value added parameters (distances, physical separations, sub-type of transient etc)

Key Arguments:
  • objectList – the list of transient locations to match against the crossmatch catalogue
  • searchPara – the search parameters for this individual search as lifted from the search algorithm in the sherlock settings file
  • search_name – the name of the search as given in the sherlock settings file
  • brightnessFilter – is this search to be constrained by magnitude of the catalogue sources? Default False. [bright|faint|general]
  • physicalSearch – is this angular search a sub-part of a physical separation search
  • classificationType – synonym, association or annotation. Default False
Return:
  • matchedObjects – any sources matched against the object

Usage:

Take a list of transients from somewhere

transients = [
    {'ps1_designation': u'PS1-14aef',
     'name': u'4L3Piiq',
     'detection_list_id': 2,
     'local_comments': u'',
     'ra': 0.02548233704918263,
     'followup_id': 2065412L,
     'dec': -4.284933417540423,
     'id': 1000006110041705700L,
     'object_classification': 0L
     },

    {'ps1_designation': u'PS1-13dcr',
     'name': u'3I3Phzx',
     'detection_list_id': 2,
     'local_comments': u'',
     'ra': 4.754236999477372,
     'followup_id': 1140386L,
     'dec': 28.276703631398625,
     'id': 1001901011281636100L,
     'object_classification': 0L
     },

    {'ps1_designation': u'PS1-13dhc',
     'name': u'3I3Pixd',
     'detection_list_id': 2,
     'local_comments': u'',
     'ra': 1.3324973428505413,
     'followup_id': 1202386L,
     'dec': 32.98869220595689,
     'id': 1000519791325919200L,
     'object_classification': 0L
     }
]

Then run the angular_crossmatch_against_catalogue method to crossmatch against the catalogues and return results:

# ANGULAR CONESEARCH ON CATALOGUE
search_name = "ned_d spec sn"
searchPara = self.settings["search algorithm"][search_name]
matchedObjects = xmatcher.angular_crossmatch_against_catalogue(
    objectList=transients,
    searchPara=searchPara,
    search_name=search_name
)

Todo

  • update key arguments values and definitions with defaults
  • update return values and definitions
  • update usage examples and text
  • update docstring text
  • check sublime snippet exists
  • clip any useful text to docs mindmap
  • regenerate the docs and check redendering of this docstring
_annotate_crossmatch_with_value_added_parameters(crossmatchDict, catalogueName, searchPara, search_name)[source]

annotate each crossmatch with physical parameters such are distances etc

Key Arguments:
  • crossmatchDict – the crossmatch dictionary
  • catalogueName – the name of the catalogue the crossmatch results from
  • searchPara – the search parameters for this individual search as lifted from the search algorithm in the sherlock settings file
  • search_name – the name of the search as given in the sherlock settings file
Return:
  • crossmatchDict – the annotated crossmatch dictionary

Todo

  • update key arguments values and definitions with defaults
  • update return values and definitions
  • update usage examples and text
  • update docstring text
  • check sublime snippet exists
  • clip any useful text to docs mindmap
  • regenerate the docs and check redendering of this docstring
_bright_star_match(matchedObjects, catalogueName, magnitudeLimitFilter, lowerMagnitudeLimit)[source]

perform a bright star match on the crossmatch results if required by the catalogue search

Key Arguments:
  • matchedObjects – the list of matched sources from the catalogue crossmatch
  • catalogueName – the name of the catalogue the crossmatch results from
  • magnitudeLimitFilter – the name of the column containing the magnitude to filter on
  • lowerMagnitudeLimit – the lower magnitude limit to match bright stars against
Return:
  • brightStarMatches – the trimmed matched sources (bright stars associations only)

Todo

  • update key arguments values and definitions with defaults
  • update return values and definitions
  • update usage examples and text
  • update docstring text
  • check sublime snippet exists
  • clip any useful text to docs mindmap
  • regenerate the docs and check redendering of this docstring
_galaxy_association_cuts(matchedObjects, catalogueName, magnitudeLimitFilter, upperMagnitudeLimit, lowerMagnitudeLimit)[source]

perform a bright star match on the crossmatch results if required by the catalogue search

Key Arguments:
  • matchedObjects – the list of matched sources from the catalogue crossmatch
  • catalogueName – the name of the catalogue the crossmatch results from
  • magnitudeLimitFilter – the name of the column containing the magnitude to filter on
  • lowerMagnitudeLimit – the lower magnitude limit to match general galaxies against
  • upperMagnitudeLimit – the upper magnitude limit to match general galaxies against
Return:
  • galaxyMatches – the trimmed matched sources (associated galaxies only)

Todo

  • update key arguments values and definitions with defaults
  • update return values and definitions
  • update usage examples and text
  • update docstring text
  • check sublime snippet exists
  • clip any useful text to docs mindmap
  • regenerate the docs and check redendering of this docstring
physical_separation_crossmatch_against_catalogue(objectList, searchPara, search_name, brightnessFilter=False, classificationType=False)[source]

perform an physical separation crossmatch against a given catalogue in the database

This search is basically the same as the angular separation search except extra filtering is done to exclude sources outside the physical search radius (matched sources require distance info to calulate physical separations)

Key Arguments:
  • objectList – transients to be crossmatched
  • searchPara – parameters of the search (from settings file)
  • search_name – the name of the search
  • brightnessFilter – is this search to be constrained by magnitude of the catalogue sources? Default False. [bright|faint|general]
  • classificationType – synonym, association or annotation. Default False
Return:
  • matchedObjects – any sources matched against the object

To run a physical separation crossmatch, run in a similar way to the angular separation crossmatch:

Usage:

search_name = "ned spec sn"
searchPara = self.settings["search algorithm"][search_name]
matchedObjects = xmatcher.physical_separation_crossmatch_against_catalogue(
    objectList=transients,
    searchPara=searchPara,
    search_name=search_name
)

Todo

  • update key arguments values and definitions with defaults
  • update return values and definitions
  • update usage examples and text
  • update docstring text
  • check sublime snippet exists
  • clip any useful text to docs mindmap
  • regenerate the docs and check redendering of this docstring