lsst.pipe.tasks.skyCorrection Namespace Reference

Classes
class	SkyCorrectionConfig
class	SkyCorrectionConnections
class	SkyCorrectionTask

Functions
	_skyFrameLookup (datasetType, registry, quantumDataId, collections)
	_reorderAndPadList (inputList, inputKeys, outputKeys, padWith=None)

Function Documentation

_reorderAndPadList()

lsst.pipe.tasks.skyCorrection._reorderAndPadList ( inputList, inputKeys, outputKeys, padWith = None )

protected

Match the order of one list to another, padding if necessary.

Parameters
----------
inputList : `list`
    List to be reordered and padded. Elements can be any type.
inputKeys :  iterable
    Iterable of values to be compared with outputKeys.
    Length must match `inputList`.
outputKeys : iterable
    Iterable of values to be compared with inputKeys.
padWith :
    Any value to be inserted where one of inputKeys is not in outputKeys.

Returns
-------
outputList : `list`
    Copy of inputList reordered per outputKeys and padded with `padWith`
    so that the length matches length of outputKeys.

Definition at line 71 of file skyCorrection.py.

def _reorderAndPadList(inputList, inputKeys, outputKeys, padWith=None):
    """Match the order of one list to another, padding if necessary.
 
    Parameters
    ----------
    inputList : `list`
        List to be reordered and padded. Elements can be any type.
    inputKeys :  iterable
        Iterable of values to be compared with outputKeys.
        Length must match `inputList`.
    outputKeys : iterable
        Iterable of values to be compared with inputKeys.
    padWith :
        Any value to be inserted where one of inputKeys is not in outputKeys.
 
    Returns
    -------
    outputList : `list`
        Copy of inputList reordered per outputKeys and padded with `padWith`
        so that the length matches length of outputKeys.
    """
    outputList = []
    for outputKey in outputKeys:
        if outputKey in inputKeys:
            outputList.append(inputList[inputKeys.index(outputKey)])
        else:
            outputList.append(padWith)
    return outputList
 
 

_skyFrameLookup()

lsst.pipe.tasks.skyCorrection._skyFrameLookup ( datasetType, registry, quantumDataId, collections )

protected

Lookup function to identify sky frames.

Parameters
----------
datasetType : `lsst.daf.butler.DatasetType`
    Dataset to lookup.
registry : `lsst.daf.butler.Registry`
    Butler registry to query.
quantumDataId : `lsst.daf.butler.DataCoordinate`
    Data id to transform to find sky frames.
    The ``detector`` entry will be stripped.
collections : `lsst.daf.butler.CollectionSearch`
    Collections to search through.

Returns
-------
results : `list` [`lsst.daf.butler.DatasetRef`]
    List of datasets that will be used as sky calibration frames.

Definition at line 41 of file skyCorrection.py.

def _skyFrameLookup(datasetType, registry, quantumDataId, collections):
    """Lookup function to identify sky frames.
 
    Parameters
    ----------
    datasetType : `lsst.daf.butler.DatasetType`
        Dataset to lookup.
    registry : `lsst.daf.butler.Registry`
        Butler registry to query.
    quantumDataId : `lsst.daf.butler.DataCoordinate`
        Data id to transform to find sky frames.
        The ``detector`` entry will be stripped.
    collections : `lsst.daf.butler.CollectionSearch`
        Collections to search through.
 
    Returns
    -------
    results : `list` [`lsst.daf.butler.DatasetRef`]
        List of datasets that will be used as sky calibration frames.
    """
    newDataId = quantumDataId.subset(registry.dimensions.conform(["instrument", "visit"]))
    skyFrames = []
    for dataId in registry.queryDataIds(["visit", "detector"], dataId=newDataId).expanded():
        skyFrame = registry.findDataset(
            datasetType, dataId, collections=collections, timespan=dataId.timespan
        )
        skyFrames.append(skyFrame)
    return skyFrames