Quality Assessment class for Kernel Candidates
Definition at line 37 of file kernelCandidateQa.py.
def lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.__init__ |
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self, |
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nKernelSpatial |
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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.
@param nKernelSpatial : Number of terms in the spatial model; needed to initialize per-basis QA arrays
Definition at line 40 of file kernelCandidateQa.py.
def lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa._calculateStats |
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self, |
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di, |
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dof = 0. |
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private |
def lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.addToSchema |
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self, |
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inSourceCatalog |
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def lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.aggregate |
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self, |
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sourceCatalog, |
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metadata, |
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wcsresids, |
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diaSources = None |
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Generate aggregate metrics (e.g. total numbers of false
positives) from all the Sources in the sourceCatalog
Definition at line 288 of file kernelCandidateQa.py.
def lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.apply |
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self, |
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candidateList, |
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spatialKernel, |
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spatialBackground, |
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dof = 0 |
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Evaluate the QA metrics for all KernelCandidates in the
candidateList; set the values of the metrics in their
associated Sources
Definition at line 193 of file kernelCandidateQa.py.
def lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.makeMetricMap |
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self | ) |
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lsst.ip.diffim.kernelCandidateQa.KernelCandidateQa.fields |
The documentation for this class was generated from the following file: