lsst.jointcal gdccb31ed8a+cdaa677055
Classes | Functions | Variables
lsst.jointcal.jointcal Namespace Reference

Classes

class  JointcalConfig
 
class  JointcalInputData
 
class  JointcalRunner
 
class  JointcalTask
 
class  JointcalTaskConnections
 

Functions

def add_measurement (job, name, value)
 
def lookupStaticCalibrations (datasetType, registry, quantumDataId, collections)
 
def lookupVisitRefCats (datasetType, registry, quantumDataId, collections)
 
def writeModel (model, filename, log)
 
def make_schema_table ()
 
def get_sourceTable_visit_columns (inColumns, config, sourceSelector)
 
def extract_detector_catalog_from_visit_catalog (table, visitCatalog, detectorId, detectorColumn, ixxColumns, sourceFluxType, log)
 

Variables

 Photometry = collections.namedtuple('Photometry', ('fit', 'model'))
 
 Astrometry = collections.namedtuple('Astrometry', ('fit', 'model', 'sky_to_tan_projection'))
 

Function Documentation

◆ add_measurement()

def lsst.jointcal.jointcal.add_measurement (   job,
  name,
  value 
)

Definition at line 60 of file jointcal.py.

◆ extract_detector_catalog_from_visit_catalog()

def lsst.jointcal.jointcal.extract_detector_catalog_from_visit_catalog (   table,
  visitCatalog,
  detectorId,
  detectorColumn,
  ixxColumns,
  sourceFluxType,
  log 
)
Return an afw SourceCatalog extracted from a visit-level dataframe,
limited to just one detector.

Parameters
----------
table : `lsst.afw.table.SourceTable`
    Table factory to use to make the SourceCatalog that will be
    populated with data from ``visitCatalog``.
visitCatalog : `pandas.DataFrame`
    DataFrame to extract a detector catalog from.
detectorId : `int`
    Numeric id of the detector to extract from ``visitCatalog``.
detectorColumn : `str`
    Name of the detector column in the catalog.
ixxColumns : `list` [`str`]
    Names of the ixx/iyy/ixy columns in the catalog.
sourceFluxType : `str`
    Name of the catalog field to load instFluxes from.
log : `lsst.log.Log`
    Logging instance to log to.

Returns
-------
catalog : `lsst.afw.table.SourceCatalog`, or `None`
    Detector-level catalog extracted from ``visitCatalog``, or `None`
    if there was no data to load.

Definition at line 1904 of file jointcal.py.

◆ get_sourceTable_visit_columns()

def lsst.jointcal.jointcal.get_sourceTable_visit_columns (   inColumns,
  config,
  sourceSelector 
)
Get the sourceTable_visit columns to load from the catalogs.

Parameters
----------
inColumns : `list`
    List of columns known to be available in the sourceTable_visit.
config : `JointcalConfig`
    A filled-in config to to help define column names.
sourceSelector : `lsst.meas.algorithms.BaseSourceSelectorTask`
    A configured source selector to define column names to load.

Returns
-------
columns : `list`
    List of columns to read from sourceTable_visit.
detectorColumn : `str`
    Name of the detector column.
ixxColumns : `list`
    Name of the ixx/iyy/ixy columns.

Definition at line 1852 of file jointcal.py.

◆ lookupStaticCalibrations()

def lsst.jointcal.jointcal.lookupStaticCalibrations (   datasetType,
  registry,
  quantumDataId,
  collections 
)
Lookup function that asserts/hopes that a static calibration dataset
exists in a particular collection, since this task can't provide a single
date/time to use to search for one properly.

This is mostly useful for the ``camera`` dataset, in cases where the task's
quantum dimensions do *not* include something temporal, like ``exposure``
or ``visit``.

Parameters
----------
datasetType : `lsst.daf.butler.DatasetType`
    Type of dataset being searched for.
registry : `lsst.daf.butler.Registry`
    Data repository registry to search.
quantumDataId : `lsst.daf.butler.DataCoordinate`
    Data ID of the quantum this camera should match.
collections : `Iterable` [ `str` ]
    Collections that should be searched - but this lookup function works
    by ignoring this in favor of a more-or-less hard-coded value.

Returns
-------
refs : `Iterator` [ `lsst.daf.butler.DatasetRef` ]
    Iterator over dataset references; should have only one element.

Notes
-----
This implementation duplicates one in fgcmcal, and is at least quite
similar to another in cp_pipe.  This duplicate has the most documentation.
Fixing this is DM-29661.

Definition at line 142 of file jointcal.py.

◆ lookupVisitRefCats()

def lsst.jointcal.jointcal.lookupVisitRefCats (   datasetType,
  registry,
  quantumDataId,
  collections 
)
Lookup function that finds all refcats for all visits that overlap a
tract, rather than just the refcats that directly overlap the tract.

Parameters
----------
datasetType : `lsst.daf.butler.DatasetType`
    Type of dataset being searched for.
registry : `lsst.daf.butler.Registry`
    Data repository registry to search.
quantumDataId : `lsst.daf.butler.DataCoordinate`
    Data ID of the quantum; expected to be something we can use as a
    constraint to query for overlapping visits.
collections : `Iterable` [ `str` ]
    Collections to search.

Returns
-------
refs : `Iterator` [ `lsst.daf.butler.DatasetRef` ]
    Iterator over refcat references.

Definition at line 182 of file jointcal.py.

◆ make_schema_table()

def lsst.jointcal.jointcal.make_schema_table ( )
Return an afw SourceTable to use as a base for creating the
SourceCatalog to insert values from the dataFrame into.

Returns
-------
table : `lsst.afw.table.SourceTable`
    Table with schema and slots to use to make SourceCatalogs.

Definition at line 1827 of file jointcal.py.

◆ writeModel()

def lsst.jointcal.jointcal.writeModel (   model,
  filename,
  log 
)
Write model to outfile.

Definition at line 632 of file jointcal.py.

Variable Documentation

◆ Astrometry

lsst.jointcal.jointcal.Astrometry = collections.namedtuple('Astrometry', ('fit', 'model', 'sky_to_tan_projection'))

Definition at line 56 of file jointcal.py.

◆ Photometry

lsst.jointcal.jointcal.Photometry = collections.namedtuple('Photometry', ('fit', 'model'))

Definition at line 55 of file jointcal.py.