Mag

class lsst.pipe.tasks.functors.Mag(col, calib=None, **kwargs)

Bases: lsst.pipe.tasks.functors.Functor

Compute calibrated magnitude

Takes a calib argument, which returns the flux at mag=0 as calib.getFluxMag0(). If not provided, then the default fluxMag0 is 63095734448.0194, which is default for HSC. This default should be removed in DM-21955

This calculation hides warnings about invalid values and dividing by zero.

As for all functors, a dataset and filt kwarg should be provided upon initialization. Unlike the default Functor, however, the default dataset for a Mag is 'meas', rather than 'ref'.

Parameters:

col : str

Name of flux column from which to compute magnitude. Can be parseable by lsst.pipe.tasks.functors.fluxName function—that is, you can pass 'modelfit_CModel' instead of 'modelfit_CModel_instFlux') and it will understand.

calib : lsst.afw.image.calib.Calib (optional)

Object that knows zero point.

Attributes Summary

columns	Columns required to perform calculation
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)
multilevelColumns(data[, columnIndex, …])	Returns columns needed by functor from multilevel dataset

Attributes Documentation

columns

Columns required to perform calculation

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)

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:

data : MultilevelParquetTable 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.