LocalPhotometry

class lsst.pipe.tasks.functors.LocalPhotometry(instFluxCol, instFluxErrCol, photoCalibCol, photoCalibErrCol, **kwargs)

Bases: Functor

Base class for calibrating the specified instrument flux column using the local photometric calibration.

Parameters:
instFluxColstr

Name of the instrument flux column.

instFluxErrColstr

Name of the assocated error columns for instFluxCol.

photoCalibColstr

Name of local calibration column.

photoCalibErrColstr

Error associated with photoCalibCol

Attributes Summary

columns

Columns required to perform calculation

logNJanskyToAB

name

Full name of functor (suitable for figure labels)

noDup

shortname

Short name of functor (suitable for column name/dict key)

Methods Summary

__call__(data[, dropna])

Call self as a function.

difference(data1, data2, **kwargs)

Computes difference between functor called on two different ParquetTable objects

fail(df)

instFluxErrToMagnitudeErr(instFlux, ...)

Convert instrument flux err to nanojanskys.

instFluxErrToNanojanskyErr(instFlux, ...)

Convert instrument flux to nanojanskys.

instFluxToMagnitude(instFlux, localCalib)

Convert instrument flux to nanojanskys.

instFluxToNanojansky(instFlux, localCalib)

Convert instrument flux to nanojanskys.

multilevelColumns(data[, columnIndex, ...])

Returns columns needed by functor from multilevel dataset

Attributes Documentation

columns

Columns required to perform calculation

logNJanskyToAB = 31.4
name

Full name of functor (suitable for figure labels)

noDup
shortname

Short name of functor (suitable for column name/dict key)

Methods Documentation

__call__(data, dropna=False)

Call self as a function.

difference(data1, data2, **kwargs)

Computes difference between functor called on two different ParquetTable objects

fail(df)
instFluxErrToMagnitudeErr(instFlux, instFluxErr, localCalib, localCalibErr)

Convert instrument flux err to nanojanskys.

Parameters:
instFluxnumpy.ndarray or pandas.Series

Array of instrument flux measurements

instFluxErrnumpy.ndarray or pandas.Series

Errors on associated instFlux values

localCalibnumpy.ndarray or pandas.Series

Array of local photometric calibration estimates.

localCalibErrnumpy.ndarray or pandas.Series

Errors on associated localCalib values

Returns:
calibMagErr: numpy.ndarray or pandas.Series

Error on calibrated AB magnitudes.

instFluxErrToNanojanskyErr(instFlux, instFluxErr, localCalib, localCalibErr)

Convert instrument flux to nanojanskys.

Parameters:
instFluxnumpy.ndarray or pandas.Series

Array of instrument flux measurements

instFluxErrnumpy.ndarray or pandas.Series

Errors on associated instFlux values

localCalibnumpy.ndarray or pandas.Series

Array of local photometric calibration estimates.

localCalibErrnumpy.ndarray or pandas.Series

Errors on associated localCalib values

Returns:
calibFluxErrnumpy.ndarray or pandas.Series

Errors on calibrated flux measurements.

instFluxToMagnitude(instFlux, localCalib)

Convert instrument flux to nanojanskys.

Parameters:
instFluxnumpy.ndarray or pandas.Series

Array of instrument flux measurements

localCalibnumpy.ndarray or pandas.Series

Array of local photometric calibration estimates.

Returns:
calibMagnumpy.ndarray or pandas.Series

Array of calibrated AB magnitudes.

instFluxToNanojansky(instFlux, localCalib)

Convert instrument flux to nanojanskys.

Parameters:
instFluxnumpy.ndarray or pandas.Series

Array of instrument flux measurements

localCalibnumpy.ndarray or pandas.Series

Array of local photometric calibration estimates.

Returns:
calibFluxnumpy.ndarray or pandas.Series

Array of calibrated flux measurements.

multilevelColumns(data, columnIndex=None, returnTuple=False)

Returns columns needed by functor from multilevel dataset

To access tables with multilevel column structure, the MultilevelParquetTable or DeferredDatasetHandle need to be passed either a list of tuples or a dictionary.

Parameters:
dataMultilevelParquetTable or DeferredDatasetHandle
columnIndex (optional): pandas `Index` object

either passed or read in from DeferredDatasetHandle.

`returnTuple`bool

If true, then return a list of tuples rather than the column dictionary specification. This is set to True by CompositeFunctor in order to be able to combine columns from the various component functors.