Utility class for dipole measurement testing.
Generate an image with simulated dipoles and noise; store the original
"pre-subtraction" images and catalogs as well.
Used to generate test data for DMTN-007 (http://dmtn-007.lsst.io).
Definition at line 708 of file utils.py.
lsst.ip.diffim.utils.DipoleTestImage.detectDipoleSources |
( |
| self, |
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| doMerge = True, |
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| diffim = None, |
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| detectSigma = 5.5, |
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| grow = 3, |
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| minBinSize = 32 ) |
Utility function for detecting dipoles.
Detect pos/neg sources in the diffim, then merge them. A
bigger "grow" parameter leads to a larger footprint which
helps with dipole measurement for faint dipoles.
Parameters
----------
doMerge : `bool`
Whether to merge the positive and negagive detections into a single
source table.
diffim : `lsst.afw.image.exposure.exposure.ExposureF`
Difference image on which to perform detection.
detectSigma : `float`
Threshold for object detection.
grow : `int`
Number of pixels to grow the footprints before merging.
minBinSize : `int`
Minimum bin size for the background (re)estimation (only applies if
the default leads to min(nBinX, nBinY) < fit order so the default
config parameter needs to be decreased, but not to a value smaller
than ``minBinSize``, in which case the fitting algorithm will take
over and decrease the fit order appropriately.)
Returns
-------
sources : `lsst.afw.table.SourceCatalog`
If doMerge=True, the merged source catalog is returned OR
detectTask : `lsst.meas.algorithms.SourceDetectionTask`
schema : `lsst.afw.table.Schema`
If doMerge=False, the source detection task and its schema are
returned.
Definition at line 780 of file utils.py.