NanoJansky¶
- class lsst.pipe.tasks.functors.NanoJansky(colFlux, colFluxErr=None, **kwargs)¶
Bases:
Photometry
Convert instrumental flux to nanojanskys.
Attributes Summary
Columns required to perform calculation.
Full name of functor (suitable for figure labels).
Do not explode by band if used on object table.
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 DataFrame/Handle objects.
dn2MagErr
(dn, dnErr, fluxMag0, fluxMag0Err)Convert instrumental flux error to AB magnitude error.
dn2flux
(dn, fluxMag0)Convert instrumental flux to nanojanskys.
dn2fluxErr
(dn, dnErr, fluxMag0, fluxMag0Err)Convert instrumental flux error to nanojanskys.
dn2mag
(dn, fluxMag0)Convert instrumental flux to AB magnitude.
fail
(df)hypot
(a, b)Compute sqrt(a^2 + b^2) without under/overflow.
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¶
Do not explode by band if used on object table.
- 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 DataFrame/Handle objects.
- dn2MagErr(dn, dnErr, fluxMag0, fluxMag0Err)¶
Convert instrumental flux error to AB magnitude error.
- dn2flux(dn, fluxMag0)¶
Convert instrumental flux to nanojanskys.
- dn2fluxErr(dn, dnErr, fluxMag0, fluxMag0Err)¶
Convert instrumental flux error to nanojanskys.
- dn2mag(dn, fluxMag0)¶
Convert instrumental flux to AB magnitude.
- fail(df)¶
- classmethod hypot(a, b)¶
Compute sqrt(a^2 + b^2) without under/overflow.
- multilevelColumns(data, columnIndex=None, returnTuple=False)¶
Returns columns needed by functor from multilevel dataset.
To access tables with multilevel column structure, the
DeferredDatasetHandle
orInMemoryDatasetHandle
needs to be passed either a list of tuples or a dictionary.- Parameters:
- datavarious
The data as either
DeferredDatasetHandle
, orInMemoryDatasetHandle
.- columnIndex (optional): pandas `~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.