lsst.pipe.tasks.transformMeasurement.TransformTask Class Reference

Transform a SourceCatalog containing raw measurements to calibrated form. More...

Inheritance diagram for lsst.pipe.tasks.transformMeasurement.TransformTask:

Public Member Functions
def	__init__
	Initialize TransformTask. More...
def	getSchemaCatalogs
	Return a dict containing an empty catalog representative of this task's output. More...
def	run
	Transform raw source measurements to calibrated quantities. More...

Public Attributes
	outputDataset
	mapper
	transforms

Static Public Attributes
	ConfigClass = TransformConfig

Static Private Attributes
string	_DefaultName = "transform"

Detailed Description

Transform a SourceCatalog containing raw measurements to calibrated form.

Contents

• Description
• Task initialization
• Task invocation

Description

Given a set of measurement algorithms with their associated configuration, the table of source measurements they have produced, and information about an associated WCS and calibration, transform the raw measurement output to a calibrated form.

Transformations are defined on a per-measurement-plugin basis. In addition, a configurable set of fields may be simply copied from the input to the output catalog.

This task operates on an input SourceCatalog and returns a BaseCatalog containing the transformed results. It requires that the caller supply information on the configuration of the measurement task which produced the input data as well as the world coordinate system and calibration under which the transformation will take place. It provides no functionality for reading or writing data from a Butler: rather, per-dataset-type command line tasks are provided to obtain the appropriate information from a Butler (or elsewhere) and then delegate to this task.

Task initialization

Initialize TransformTask.

Parameters

[in]	measConfig	Configuration for the measurement task which produced the measurments being transformed.
[in]	inputSchema	The schema of the input catalog.
[in]	outputDataset	The butler dataset type of the output catalog.
[in]	*args	Passed through to pipeBase.Task.__init__()
[in]	*kwargs	Passed through to pipeBase.Task.__init__()

Task invocation

Transform raw source measurements to calibrated quantities.

Parameters

[in]	inputCat	SourceCatalog of sources to transform.
[in]	wcs	The world coordinate system under which transformations will take place.
[in]	calib	The calibration under which transformations will take place.

Returns

A BaseCatalog containing the transformed measurements.

Definition at line 54 of file transformMeasurement.py.

Constructor & Destructor Documentation

def lsst.pipe.tasks.transformMeasurement.TransformTask.__init__	(		self,
			measConfig,
			inputSchema,
			outputDataset,
			args,
			kwargs
	)

Initialize TransformTask.

Parameters

[in]	measConfig	Configuration for the measurement task which produced the measurments being transformed.
[in]	inputSchema	The schema of the input catalog.
[in]	outputDataset	The butler dataset type of the output catalog.
[in]	*args	Passed through to pipeBase.Task.__init__()
[in]	*kwargs	Passed through to pipeBase.Task.__init__()

Definition at line 97 of file transformMeasurement.py.

    def __init__(self, measConfig, inputSchema, outputDataset, *args, **kwargs):
        """!Initialize TransformTask.

        @param[in] measConfig      Configuration for the measurement task which
                                   produced the measurments being transformed.
        @param[in] inputSchema     The schema of the input catalog.
        @param[in] outputDataset   The butler dataset type of the output catalog.
        @param[in] *args           Passed through to pipeBase.Task.__init__()
        @param[in] *kwargs         Passed through to pipeBase.Task.__init__()
        """
        pipeBase.Task.__init__(self, *args, **kwargs)

        # This task can be used to generate multiple different output dataset types. We
        # need to be able to specify the output type together with its schema.
        self.outputDataset = outputDataset

        # Define a mapper and add the basic fields to be copied.
        self.mapper = afwTable.SchemaMapper(inputSchema)
        for field in self.config.copyFields:
            self.mapper.addMapping(inputSchema.find(field).key)

        # Build a list of all transforms that will be applied to the input. We
        # will iterate over this in run().
        self.transforms = []
        for name in measConfig.plugins.names:
            config = measConfig.plugins.get(name)
            transformClass = measConfig.plugins.registry.get(name).PluginClass.getTransformClass()
            self.transforms.append(transformClass(config, name, self.mapper))