Added 100x faster vectorized version #39
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| return Struct(sourceCat=result) | ||
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| def _getSchemaKeys(self, schema): | ||
| """Extract and save the necessary keys from schema with asKey.""" | ||
| self.parentKey = schema["parent"].asKey() | ||
| self.nChildKey = schema["deblend_nChild"].asKey() | ||
| self.centroidXKey = schema["slot_Centroid_x"].asKey() | ||
| self.centroidYKey = schema["slot_Centroid_y"].asKey() |
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I thought the field was "slot_Centroid" and it returned a tuple of the (y, x) centroid location. Does this also work?
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That works for individual sources, but I need the x/y centroids for the vectorized np.isfinite() test: there isn't an equivalent SourceCatalog thing to get a vector of tuples.
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Small correction: when used as a single key slot_Centroid will return afw.geom.Point2D, which is indexable as (x,y), not (y,x). The usage here is completely valid too, of course.
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Would be ~500x faster if we didn't have to do the footprint loop.
The if branch between vector and non-vectorized versions (and associated split in code logic) is unpleasant, but we'll have to live with it until we finalize the discussion here: https://community.lsst.org/t/memory-contiguity-and-python-execution-speed/884/12