ConvertMultipleCellCoaddToExposureTask

class lsst.drp.tasks.assemble_cell_coadd.ConvertMultipleCellCoaddToExposureTask(*, config: PipelineTaskConfig | None = None, log: logging.Logger | LsstLogAdapter | None = None, initInputs: dict[str, Any] | None = None, **kwargs: Any)

Bases: PipelineTask

An after burner PipelineTask that converts a cell-based coadd from MultipleCellCoadd format to ExposureF format.

The run method stitches the cell-based coadd into contiguous exposure and returns it in as an Exposure object. This is lossy as it preserves only the pixels in the inner bounding box of the cells and discards the values in the buffer region.

Notes

This task has no configurable parameters.

Methods Summary

run(cellCoaddExposure)

Run task algorithm on in-memory data.

Methods Documentation

run(cellCoaddExposure)

Run task algorithm on in-memory data.

This method should be implemented in a subclass. This method will receive keyword-only arguments whose names will be the same as names of connection fields describing input dataset types. Argument values will be data objects retrieved from data butler. If a dataset type is configured with multiple field set to True then the argument value will be a list of objects, otherwise it will be a single object.

If the task needs to know its input or output DataIds then it also has to override the runQuantum method.

This method should return a Struct whose attributes share the same name as the connection fields describing output dataset types.

Parameters

**kwargsAny

Arbitrary parameters accepted by subclasses.

Returns

structStruct

Struct with attribute names corresponding to output connection fields.

Examples

Typical implementation of this method may look like:

def run(self, *, input, calib):
    # "input", "calib", and "output" are the names of the
    # connection fields.

    # Assuming that input/calib datasets are `scalar` they are
    # simple objects, do something with inputs and calibs, produce
    # output image.
    image = self.makeImage(input, calib)

    # If output dataset is `scalar` then return object, not list
    return Struct(output=image)