LSSTApplications  19.0.0-14-gb0260a2+d60062ef16,20.0.0+1540ce6389,20.0.0+7c6b12c2f9,20.0.0+ae956f52c5,20.0.0+be870186d9,20.0.0+e2e26847c2,20.0.0-1-g10df615+7683e4f082,20.0.0-1-g253301a+7c6b12c2f9,20.0.0-1-g2b7511a+46a6078777,20.0.0-1-g3dda6ea+606b36f8c0,20.0.0-1-g4d801e7+901ee84527,20.0.0-1-g5b95a8c+a5fa15ec54,20.0.0-1-gb058bd0+46a6078777,20.0.0-1-gb88604f+acecce4127,20.0.0-1-gc96f8cb+61a4a056b1,20.0.0-1-gedffbd8+4f0e391d5e,20.0.0-10-g0891cd99+aadc987f3e,20.0.0-10-g9a20bd332+576ca7b471,20.0.0-17-gcdbda88+ed0d4927ab,20.0.0-2-g4dae9ad+61a4a056b1,20.0.0-2-g61b8584+85c46248f3,20.0.0-2-gb780d76+f45b7d88f4,20.0.0-2-gf072044+7c6b12c2f9,20.0.0-21-g9bbb7f7+61a4a056b1,20.0.0-22-gc512666+9eba1c4719,20.0.0-23-g8900aa8+68630f7098,20.0.0-3-g1653f94+85c46248f3,20.0.0-3-g4cc78c6+63636aeed8,20.0.0-3-g750bffe+e05f822de9,20.0.0-3-gbd60e8c+ff10c6d78d,20.0.0-32-g15a0e07c+ff1c9f120b,20.0.0-4-g97dc21a+68630f7098,20.0.0-4-gfea843c+f45b7d88f4,20.0.0-5-g357b56b+f45b7d88f4,20.0.0-6-g9a5b7a1+2c4171520d,20.0.0-61-g4de25fb+e4dd172200,20.0.0-7-gcda7bf1+85e953d7e4,w.2020.43
LSSTDataManagementBasePackage
Public Member Functions | Public Attributes | Static Public Attributes | List of all members
lsst.cp.pipe.cpCertify.CertifyCalibration Class Reference
Inheritance diagram for lsst.cp.pipe.cpCertify.CertifyCalibration:

Public Member Functions

def __init__ (self, *registry, inputCollection, outputCollection, lastRunOnly=True, **kwargs)
 
def run (self, datasetTypeName, timespan)
 

Public Attributes

 registry
 
 inputCollection
 
 outputCollection
 

Static Public Attributes

 ConfigClass = pexConfig.Config
 

Detailed Description

Create a way to bless existing calibration products.

The inputs are assumed to have been constructed via cp_pipe, and
already exist in the butler.

Parameters
----------
registry : `lsst.daf.butler.Registry`
    Registry pointing at the butler repository to operate on.
inputCollection : `str`
    Data collection to pull calibrations from.  Usually an existing
    `~CollectionType.RUN` or `~CollectionType.CHAINED` collection, and may
    _not_ be a `~CollectionType.CALIBRATION` collection or a nonexistent
    collection.
outputCollection : `str`
    Data collection to store final calibrations.  If it already exists, it
    must be a `~CollectionType.CALIBRATION` collection.  If not, a new
    `~CollectionType.CALIBRATION` collection with this name will be
    registered.
lastRunOnly : `bool`, optional
    If `True` (default) and ``inputCollection`` is a
    `~CollectionType.CHAINED` collection, only search its first child
    collection (which usually corresponds to the last processing run),
    instead of all child collections in the chain.  This behavior ensures
    that datasets in a collection used as input to that processing run
    are never included in the certification.
**kwargs :
    Additional arguments forwarded to `lsst.pipe.base.Task.__init__`.

Definition at line 27 of file cpCertify.py.

Constructor & Destructor Documentation

◆ __init__()

def lsst.cp.pipe.cpCertify.CertifyCalibration.__init__ (   self,
registry,
  inputCollection,
  outputCollection,
  lastRunOnly = True,
**  kwargs 
)

Definition at line 60 of file cpCertify.py.

60  def __init__(self, *, registry, inputCollection, outputCollection, lastRunOnly=True, **kwargs):
61  super().__init__(**kwargs)
62  self.registry = registry
63  if lastRunOnly:
64  try:
65  inputCollection, _ = next(iter(self.registry.getCollectionChain(inputCollection)))
66  except TypeError:
67  # Not a CHAINED collection; do nothing.
68  pass
69  self.inputCollection = inputCollection
70  self.outputCollection = outputCollection
71 

Member Function Documentation

◆ run()

def lsst.cp.pipe.cpCertify.CertifyCalibration.run (   self,
  datasetTypeName,
  timespan 
)
Certify all of the datasets of the given type in the input
collection.

Parameters
----------
datasetTypeName : `str`
    Name of the dataset type to certify.
timespan : `lsst.daf.butler.Timespan`
    Timespan for the validity range.

Definition at line 72 of file cpCertify.py.

72  def run(self, datasetTypeName, timespan):
73  """Certify all of the datasets of the given type in the input
74  collection.
75 
76  Parameters
77  ----------
78  datasetTypeName : `str`
79  Name of the dataset type to certify.
80  timespan : `lsst.daf.butler.Timespan`
81  Timespan for the validity range.
82  """
83  refs = set(self.registry.queryDatasets(datasetTypeName, collections=[self.inputCollection]))
84  if not refs:
85  raise RuntimeError(f"No inputs found for dataset {datasetTypeName} in {self.inputCollection}.")
86  self.registry.registerCollection(self.outputCollection, type=CollectionType.CALIBRATION)
87  self.registry.certify(self.outputCollection, refs, timespan)

Member Data Documentation

◆ ConfigClass

lsst.cp.pipe.cpCertify.CertifyCalibration.ConfigClass = pexConfig.Config
static

Definition at line 58 of file cpCertify.py.

◆ inputCollection

lsst.cp.pipe.cpCertify.CertifyCalibration.inputCollection

Definition at line 69 of file cpCertify.py.

◆ outputCollection

lsst.cp.pipe.cpCertify.CertifyCalibration.outputCollection

Definition at line 70 of file cpCertify.py.

◆ registry

lsst.cp.pipe.cpCertify.CertifyCalibration.registry

Definition at line 62 of file cpCertify.py.


The documentation for this class was generated from the following file:
astshim.fitsChanContinued.next
def next(self)
Definition: fitsChanContinued.py:105
lsst.pipe.tasks.assembleCoadd.run
def run(self, skyInfo, tempExpRefList, imageScalerList, weightList, altMaskList=None, mask=None, supplementaryData=None)
Definition: assembleCoadd.py:720
set
daf::base::PropertySet * set
Definition: fits.cc:912
astshim.fitsChanContinued.iter
def iter(self)
Definition: fitsChanContinued.py:88