LocalPhotometry¶
- class lsst.pipe.tasks.functors.LocalPhotometry(instFluxCol, instFluxErrCol, photoCalibCol, photoCalibErrCol, **kwargs)¶
Bases:
Functor
Base class for calibrating the specified instrument flux column using the local photometric calibration.
- Parameters:
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 DataFrame/Handle objects
fail
(df)instFluxErrToMagnitudeErr
(instFlux, ...)Convert instrument flux err to nanojanskys.
instFluxErrToNanojanskyErr
(instFlux, ...)Convert instrument flux to nanojanskys.
instFluxToMagnitude
(instFlux, localCalib)Convert instrument flux to nanojanskys.
instFluxToNanojansky
(instFlux, localCalib)Convert instrument flux to nanojanskys.
multilevelColumns
(data[, columnIndex, ...])Returns columns needed by functor from multilevel dataset
Attributes Documentation
- columns¶
Columns required to perform calculation
- logNJanskyToAB = 31.4¶
- 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 DataFrame/Handle objects
- fail(df)¶
- instFluxErrToMagnitudeErr(instFlux, instFluxErr, localCalib, localCalibErr)¶
Convert instrument flux err to nanojanskys.
- Parameters:
- instFlux
numpy.ndarray
orpandas.Series
Array of instrument flux measurements
- instFluxErr
numpy.ndarray
orpandas.Series
Errors on associated
instFlux
values- localCalib
numpy.ndarray
orpandas.Series
Array of local photometric calibration estimates.
- localCalibErr
numpy.ndarray
orpandas.Series
Errors on associated
localCalib
values
- instFlux
- Returns:
- calibMagErr:
numpy.ndarray
orpandas.Series
Error on calibrated AB magnitudes.
- calibMagErr:
- instFluxErrToNanojanskyErr(instFlux, instFluxErr, localCalib, localCalibErr)¶
Convert instrument flux to nanojanskys.
- Parameters:
- instFlux
numpy.ndarray
orpandas.Series
Array of instrument flux measurements
- instFluxErr
numpy.ndarray
orpandas.Series
Errors on associated
instFlux
values- localCalib
numpy.ndarray
orpandas.Series
Array of local photometric calibration estimates.
- localCalibErr
numpy.ndarray
orpandas.Series
Errors on associated
localCalib
values
- instFlux
- Returns:
- calibFluxErr
numpy.ndarray
orpandas.Series
Errors on calibrated flux measurements.
- calibFluxErr
- instFluxToMagnitude(instFlux, localCalib)¶
Convert instrument flux to nanojanskys.
- Parameters:
- instFlux
numpy.ndarray
orpandas.Series
Array of instrument flux measurements
- localCalib
numpy.ndarray
orpandas.Series
Array of local photometric calibration estimates.
- instFlux
- Returns:
- calibMag
numpy.ndarray
orpandas.Series
Array of calibrated AB magnitudes.
- calibMag
- instFluxToNanojansky(instFlux, localCalib)¶
Convert instrument flux to nanojanskys.
- Parameters:
- instFlux
numpy.ndarray
orpandas.Series
Array of instrument flux measurements
- localCalib
numpy.ndarray
orpandas.Series
Array of local photometric calibration estimates.
- instFlux
- Returns:
- calibFlux
numpy.ndarray
orpandas.Series
Array of calibrated flux measurements.
- calibFlux
- multilevelColumns(data, columnIndex=None, returnTuple=False)¶
Returns columns needed by functor from multilevel dataset
To access tables with multilevel column structure, the
DeferredDatasetHandle
orInMemoryDatasetHandle
need to be passed either a list of tuples or a dictionary.- Parameters:
- datavarious
The data as either
DeferredDatasetHandle
, orInMemoryDatasetHandle
.- 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.