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 734 of file utils.py.
def lsst.ip.diffim.utils.DipoleTestImage.detectDipoleSources |
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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 |
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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
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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 816 of file utils.py.