|
| | columns (self) |
| |
| | name (self) |
| |
| | hypot (cls, a, b) |
| |
| | dn2flux (self, dn, fluxMag0) |
| |
| | dn2mag (self, dn, fluxMag0) |
| |
| | dn2fluxErr (self, dn, dnErr, fluxMag0, fluxMag0Err) |
| |
| | dn2MagErr (self, dn, dnErr, fluxMag0, fluxMag0Err) |
| |
| | noDup (self) |
| |
| | multilevelColumns (self, data, columnIndex=None, returnTuple=False) |
| |
| | __call__ (self, data, dropna=False) |
| |
| | difference (self, data1, data2, **kwargs) |
| |
| | fail (self, df) |
| |
| | shortname (self) |
| |
|
| | vhypot = np.vectorize(self.hypot) |
| |
| | col = colFlux |
| |
| | colFluxErr = colFluxErr |
| |
| int | fluxMag0 = 1./np.power(10, -0.4*self.COADD_ZP) |
| |
| int | fluxMag0Err = 0. |
| |
| | filt = filt |
| |
| str | dataset = dataset if dataset is not None else self._defaultDataset |
| |
| | log = logging.getLogger(type(self).__name__) |
| |
|
| | _func (self, df) |
| |
| | _get_data_columnLevels (self, data, columnIndex=None) |
| |
| | _get_data_columnLevelNames (self, data, columnIndex=None) |
| |
| | _colsFromDict (self, colDict, columnIndex=None) |
| |
| | _get_columnIndex (self, data) |
| |
| | _get_data (self, data) |
| |
| | _setLevels (self, df) |
| |
| | _dropna (self, vals) |
| |
Convert instrumental flux to nanojanskys.
Definition at line 1658 of file functors.py.
◆ __call__()
| lsst.pipe.tasks.functors.Functor.__call__ |
( |
| self, |
|
|
| data, |
|
|
| dropna = False ) |
|
inherited |
◆ _colsFromDict()
| lsst.pipe.tasks.functors.Functor._colsFromDict |
( |
| self, |
|
|
| colDict, |
|
|
| columnIndex = None ) |
|
protectedinherited |
Converts dictionary column specficiation to a list of columns.
Definition at line 223 of file functors.py.
◆ _dropna()
| lsst.pipe.tasks.functors.Functor._dropna |
( |
| self, |
|
|
| vals ) |
|
protectedinherited |
◆ _func()
| lsst.pipe.tasks.functors.NanoJansky._func |
( |
| self, |
|
|
| df ) |
|
protected |
◆ _get_columnIndex()
| lsst.pipe.tasks.functors.Functor._get_columnIndex |
( |
| self, |
|
|
| data ) |
|
protectedinherited |
◆ _get_data()
| lsst.pipe.tasks.functors.Functor._get_data |
( |
| self, |
|
|
| data ) |
|
protectedinherited |
Retrieve DataFrame necessary for calculation.
The data argument can be a `~pandas.DataFrame`, a
`~lsst.daf.butler.DeferredDatasetHandle`, or
an `~lsst.pipe.base.InMemoryDatasetHandle`.
Returns a DataFrame upon which `self._func` can act.
Definition at line 307 of file functors.py.
◆ _get_data_columnLevelNames()
| lsst.pipe.tasks.functors.Functor._get_data_columnLevelNames |
( |
| self, |
|
|
| data, |
|
|
| columnIndex = None ) |
|
protectedinherited |
Gets the content of each of the column levels for a multilevel
table.
Definition at line 209 of file functors.py.
◆ _get_data_columnLevels()
| lsst.pipe.tasks.functors.Functor._get_data_columnLevels |
( |
| self, |
|
|
| data, |
|
|
| columnIndex = None ) |
|
protectedinherited |
Gets the names of the column index levels.
This should only be called in the context of a multilevel table.
Parameters
----------
data : various
The data to be read, can be a
`~lsst.daf.butler.DeferredDatasetHandle` or
`~lsst.pipe.base.InMemoryDatasetHandle`.
columnIndex (optional): pandas `~pandas.Index` object
If not passed, then it is read from the
`~lsst.daf.butler.DeferredDatasetHandle`
for `~lsst.pipe.base.InMemoryDatasetHandle`.
Definition at line 189 of file functors.py.
◆ _setLevels()
| lsst.pipe.tasks.functors.Functor._setLevels |
( |
| self, |
|
|
| df ) |
|
protectedinherited |
◆ columns()
| lsst.pipe.tasks.functors.Photometry.columns |
( |
| self | ) |
|
|
inherited |
◆ difference()
| lsst.pipe.tasks.functors.Functor.difference |
( |
| self, |
|
|
| data1, |
|
|
| data2, |
|
|
** | kwargs ) |
|
inherited |
Computes difference between functor called on two different
DataFrame/Handle objects.
Definition at line 365 of file functors.py.
◆ dn2flux()
| lsst.pipe.tasks.functors.Photometry.dn2flux |
( |
| self, |
|
|
| dn, |
|
|
| fluxMag0 ) |
|
inherited |
Convert instrumental flux to nanojanskys.
Definition at line 1635 of file functors.py.
◆ dn2fluxErr()
| lsst.pipe.tasks.functors.Photometry.dn2fluxErr |
( |
| self, |
|
|
| dn, |
|
|
| dnErr, |
|
|
| fluxMag0, |
|
|
| fluxMag0Err ) |
|
inherited |
Convert instrumental flux error to nanojanskys.
Definition at line 1646 of file functors.py.
◆ dn2mag()
| lsst.pipe.tasks.functors.Photometry.dn2mag |
( |
| self, |
|
|
| dn, |
|
|
| fluxMag0 ) |
|
inherited |
Convert instrumental flux to AB magnitude.
Definition at line 1639 of file functors.py.
◆ dn2MagErr()
| lsst.pipe.tasks.functors.Photometry.dn2MagErr |
( |
| self, |
|
|
| dn, |
|
|
| dnErr, |
|
|
| fluxMag0, |
|
|
| fluxMag0Err ) |
|
inherited |
Convert instrumental flux error to AB magnitude error.
Definition at line 1652 of file functors.py.
◆ fail()
| lsst.pipe.tasks.functors.Functor.fail |
( |
| self, |
|
|
| df ) |
|
inherited |
◆ hypot()
| lsst.pipe.tasks.functors.Photometry.hypot |
( |
| cls, |
|
|
| a, |
|
|
| b ) |
|
inherited |
Compute sqrt(a^2 + b^2) without under/overflow.
Definition at line 1626 of file functors.py.
◆ multilevelColumns()
| lsst.pipe.tasks.functors.Functor.multilevelColumns |
( |
| self, |
|
|
| data, |
|
|
| columnIndex = None, |
|
|
| returnTuple = False ) |
|
inherited |
Returns columns needed by functor from multilevel dataset.
To access tables with multilevel column structure, the
`~lsst.daf.butler.DeferredDatasetHandle` or
`~lsst.pipe.base.InMemoryDatasetHandle` needs to be passed
either a list of tuples or a dictionary.
Parameters
----------
data : various
The data as either `~lsst.daf.butler.DeferredDatasetHandle`, or
`~lsst.pipe.base.InMemoryDatasetHandle`.
columnIndex (optional): pandas `~pandas.Index` object
Either passed or read in from
`~lsst.daf.butler.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.
Reimplemented in lsst.pipe.tasks.functors.Color, and lsst.pipe.tasks.functors.CompositeFunctor.
Definition at line 242 of file functors.py.
◆ name()
| lsst.pipe.tasks.functors.Photometry.name |
( |
| self | ) |
|
|
inherited |
◆ noDup()
| lsst.pipe.tasks.functors.Functor.noDup |
( |
| self | ) |
|
|
inherited |
Do not explode by band if used on object table.
Definition at line 175 of file functors.py.
◆ shortname()
| lsst.pipe.tasks.functors.Functor.shortname |
( |
| self | ) |
|
|
inherited |
◆ _defaultDataset
| str lsst.pipe.tasks.functors.Functor._defaultDataset = 'ref' |
|
staticprotectedinherited |
◆ _defaultNoDup
| bool lsst.pipe.tasks.functors.Functor._defaultNoDup = False |
|
staticprotectedinherited |
◆ _dfLevels
| tuple lsst.pipe.tasks.functors.Functor._dfLevels = ('column',) |
|
staticprotectedinherited |
◆ _noDup
| lsst.pipe.tasks.functors.Functor._noDup = noDup |
|
protectedinherited |
◆ AB_FLUX_SCALE
| tuple lsst.pipe.tasks.functors.Photometry.AB_FLUX_SCALE = (0 * u.ABmag).to_value(u.nJy) |
|
staticinherited |
◆ COADD_ZP
| int lsst.pipe.tasks.functors.Photometry.COADD_ZP = 27 |
|
staticinherited |
◆ col
| lsst.pipe.tasks.functors.Photometry.col = colFlux |
|
inherited |
◆ colFluxErr
| lsst.pipe.tasks.functors.Photometry.colFluxErr = colFluxErr |
|
inherited |
◆ dataset
| str lsst.pipe.tasks.functors.Functor.dataset = dataset if dataset is not None else self._defaultDataset |
|
inherited |
◆ filt
| lsst.pipe.tasks.functors.Functor.filt = filt |
|
inherited |
◆ FIVE_OVER_2LOG10
| float lsst.pipe.tasks.functors.Photometry.FIVE_OVER_2LOG10 = 1.085736204758129569 |
|
staticinherited |
◆ fluxMag0
| int lsst.pipe.tasks.functors.Photometry.fluxMag0 = 1./np.power(10, -0.4*self.COADD_ZP) |
|
inherited |
◆ fluxMag0Err
| int lsst.pipe.tasks.functors.Photometry.fluxMag0Err = 0. |
|
inherited |
◆ log
| lsst.pipe.tasks.functors.Functor.log = logging.getLogger(type(self).__name__) |
|
inherited |
◆ LOG_AB_FLUX_SCALE
| float lsst.pipe.tasks.functors.Photometry.LOG_AB_FLUX_SCALE = 12.56 |
|
staticinherited |
◆ vhypot
| lsst.pipe.tasks.functors.Photometry.vhypot = np.vectorize(self.hypot) |
|
inherited |
The documentation for this class was generated from the following file: