LocalPhotometry¶
- class lsst.pipe.tasks.functors.LocalPhotometry(instFluxCol, instFluxErrCol, photoCalibCol, photoCalibErrCol, **kwargs)¶
Bases:
FunctorBase class for calibrating the specified instrument flux column using the local photometric calibration.
- Parameters:
See also
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.ndarrayorpandas.Series Array of instrument flux measurements
- instFluxErr
numpy.ndarrayorpandas.Series Errors on associated
instFluxvalues- localCalib
numpy.ndarrayorpandas.Series Array of local photometric calibration estimates.
- localCalibErr
numpy.ndarrayorpandas.Series Errors on associated
localCalibvalues
- instFlux
- Returns:
- calibMagErr:
numpy.ndarrayorpandas.Series Error on calibrated AB magnitudes.
- calibMagErr:
- instFluxErrToNanojanskyErr(instFlux, instFluxErr, localCalib, localCalibErr)¶
Convert instrument flux to nanojanskys.
- Parameters:
- instFlux
numpy.ndarrayorpandas.Series Array of instrument flux measurements
- instFluxErr
numpy.ndarrayorpandas.Series Errors on associated
instFluxvalues- localCalib
numpy.ndarrayorpandas.Series Array of local photometric calibration estimates.
- localCalibErr
numpy.ndarrayorpandas.Series Errors on associated
localCalibvalues
- instFlux
- Returns:
- calibFluxErr
numpy.ndarrayorpandas.Series Errors on calibrated flux measurements.
- calibFluxErr
- instFluxToMagnitude(instFlux, localCalib)¶
Convert instrument flux to nanojanskys.
- Parameters:
- instFlux
numpy.ndarrayorpandas.Series Array of instrument flux measurements
- localCalib
numpy.ndarrayorpandas.Series Array of local photometric calibration estimates.
- instFlux
- Returns:
- calibMag
numpy.ndarrayorpandas.Series Array of calibrated AB magnitudes.
- calibMag
- instFluxToNanojansky(instFlux, localCalib)¶
Convert instrument flux to nanojanskys.
- Parameters:
- instFlux
numpy.ndarrayorpandas.Series Array of instrument flux measurements
- localCalib
numpy.ndarrayorpandas.Series Array of local photometric calibration estimates.
- instFlux
- Returns:
- calibFlux
numpy.ndarrayorpandas.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
DeferredDatasetHandleorInMemoryDatasetHandleneed 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
TruebyCompositeFunctorin order to be able to combine columns from the various component functors.