NanoJansky¶
- class lsst.pipe.tasks.functors.NanoJansky(colFlux, colFluxErr=None, calib=None, **kwargs)¶
Bases:
Photometry
Attributes Summary
Columns required to perform calculation
Full name of functor (suitable for figure labels)
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
dn2MagErr
(dn, dnErr, fluxMag0, fluxMag0Err)dn2flux
(dn, fluxMag0)dn2fluxErr
(dn, dnErr, fluxMag0, fluxMag0Err)dn2mag
(dn, fluxMag0)fail
(df)hypot
(a, b)multilevelColumns
(data[, columnIndex, ...])Returns columns needed by functor from multilevel dataset
Attributes Documentation
- AB_FLUX_SCALE = 3630780547701.003¶
- COADD_ZP = 27¶
- FIVE_OVER_2LOG10 = 1.0857362047581296¶
- LOG_AB_FLUX_SCALE = 12.56¶
- columns¶
- name¶
- 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
- dn2MagErr(dn, dnErr, fluxMag0, fluxMag0Err)¶
- dn2flux(dn, fluxMag0)¶
- dn2fluxErr(dn, dnErr, fluxMag0, fluxMag0Err)¶
- dn2mag(dn, fluxMag0)¶
- fail(df)¶
- classmethod hypot(a, b)¶
- multilevelColumns(data, columnIndex=None, returnTuple=False)¶
Returns columns needed by functor from multilevel dataset
To access tables with multilevel column structure, the
MultilevelParquetTable
orDeferredDatasetHandle
need to be passed either a list of tuples or a dictionary.- Parameters:
- data
MultilevelParquetTable
orDeferredDatasetHandle
- 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
byCompositeFunctor
in order to be able to combine columns from the various component functors.
- data