CustomFunctor

class lsst.pipe.tasks.functors.CustomFunctor(expr, **kwargs)

Bases: lsst.pipe.tasks.functors.Functor

Arbitrary computation on a catalog

Column names (and thus the columns to be loaded from catalog) are found by finding all words and trying to ignore all “math-y” words.

Parameters:

expr : str

Expression to evaluate, to be parsed and executed by mag_aware_eval.

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.