ImageMapReduceTask

class lsst.ip.diffim.ImageMapReduceTask(*args, **kwargs)

Bases: lsst.pipe.base.Task

Split an Exposure into subExposures (optionally on a grid) and perform the same operation on each.

Perform ‘simple’ operations on a gridded set of subExposures of a larger Exposure, and then (by default) have those subExposures stitched back together into a new, full-sized image.

Contrary to the expectation given by its name, this task does not perform these operations in parallel, although it could be updatd to provide such functionality.

The actual operations are performed by two subTasks passed to the config. The exposure passed to this task’s run method will be divided, and those subExposures will be passed to the subTasks, along with the original exposure. The reducing operation is performed by the second subtask.

Methods Summary

plotBoxes(fullBBox[, skip])	Plot both grids of boxes using matplotlib.
run(exposure, **kwargs)	Perform a map-reduce operation on the given exposure.

Methods Documentation

plotBoxes(fullBBox, skip=3)

Plot both grids of boxes using matplotlib.

Will compute the grid via _generateGrid if self.boxes0 and self.boxes1 have not already been set.

Parameters:

exposure : lsst.afw.image.Exposure

Exposure whose bounding box is gridded by this task.

skip : int

Plot every skip-ped box (help make plots less confusing)

run(exposure, **kwargs)

Perform a map-reduce operation on the given exposure.

Split the exposure into sub-expposures on a grid (parameters given by ImageMapReduceConfig) and perform config.mapper.run() on each. Reduce the resulting sub-exposures by running config.reducer.run().

Parameters:

exposure : lsst.afw.image.Exposure

the full exposure to process

kwargs :

additional keyword arguments to be passed to subtask run methods

Returns:

output of `reducer.run()`