Quality Assessment class for Kernel Candidates
Definition at line 36 of file kernelCandidateQa.py.
◆ __init__()
lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.__init__ |
( |
| self, |
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| nKernelSpatial ) |
Class to undertake QA of KernelCandidates after modeling of
the Psf-matching kernel. Both directly--fitted diffim (LOCAL)
and spatially--interpolated kernel diffim (SPATIAL) metrics
are calculated, based on the distribution of residuals in the
KernelCandidates stamp.
Parameters
----------
nKernelSpatial : `int`
Number of terms in the spatial model; needed to initialize per-basis QA arrays
Definition at line 39 of file kernelCandidateQa.py.
◆ _calculateStats()
lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa._calculateStats |
( |
| di, |
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| dof = 0. ) |
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staticprotected |
◆ addToSchema()
lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.addToSchema |
( |
| self, |
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|
| inSourceCatalog ) |
◆ aggregate()
lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.aggregate |
( |
| sourceCatalog, |
|
|
| metadata, |
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| wcsresids, |
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| diaSources = None ) |
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static |
Generate aggregate metrics (e.g. total numbers of false
positives) from all the Sources in the sourceCatalog
Definition at line 296 of file kernelCandidateQa.py.
◆ apply()
lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.apply |
( |
| cls, |
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| candidateList, |
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| spatialKernel, |
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| spatialBackground, |
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| dof = 0 ) |
Evaluate the QA metrics for all KernelCandidates in the
candidateList; set the values of the metrics in their
associated Sources
Definition at line 200 of file kernelCandidateQa.py.
◆ makeMetricMap()
lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.makeMetricMap |
( |
| self | ) |
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◆ fields
lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.fields |
The documentation for this class was generated from the following file: