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def | runQuantum (self, butlerQC, inputRefs, outputRefs) |
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def | run (self, inputPtc, dummy, camera, inputDims) |
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def | averageCorrelations (self, xCorrList, name) |
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def | quadraticCorrelations (self, xCorrList, fluxList, name) |
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def | successiveOverRelax (self, source, maxIter=None, eLevel=None) |
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Measure appropriate Brighter-Fatter Kernel from the PTC dataset.
Definition at line 142 of file makeBrighterFatterKernel.py.
◆ averageCorrelations()
def lsst.cp.pipe.makeBrighterFatterKernel.BrighterFatterKernelSolveTask.averageCorrelations |
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self, |
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xCorrList, |
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name |
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Average input correlations.
Parameters
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xCorrList : `list` [`numpy.array`]
List of cross-correlations.
name : `str`
Name for log messages.
Returns
-------
meanXcorr : `numpy.array`
The averaged cross-correlation.
Definition at line 325 of file makeBrighterFatterKernel.py.
◆ quadraticCorrelations()
def lsst.cp.pipe.makeBrighterFatterKernel.BrighterFatterKernelSolveTask.quadraticCorrelations |
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self, |
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xCorrList, |
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fluxList, |
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name |
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Measure a quadratic correlation model.
Parameters
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xCorrList : `list` [`numpy.array`]
List of cross-correlations.
fluxList : `numpy.array`
Associated list of fluxes.
name : `str`
Name for log messages.
Returns
-------
meanXcorr : `numpy.array`
The averaged cross-correlation.
Definition at line 354 of file makeBrighterFatterKernel.py.
◆ run()
def lsst.cp.pipe.makeBrighterFatterKernel.BrighterFatterKernelSolveTask.run |
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self, |
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inputPtc, |
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dummy, |
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camera, |
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inputDims |
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Combine covariance information from PTC into brighter-fatter kernels.
Parameters
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inputPtc : `lsst.ip.isr.PhotonTransferCurveDataset`
PTC data containing per-amplifier covariance measurements.
dummy : `lsst.afw.image.Exposure
The exposure used to select the appropriate PTC dataset.
camera : `lsst.afw.cameraGeom.Camera`
Camera to use for camera geometry information.
inputDims : `lsst.daf.butler.DataCoordinate` or `dict`
DataIds to use to populate the output calibration.
Returns
-------
results : `lsst.pipe.base.Struct`
The resulst struct containing:
``outputBfk`` : `lsst.ip.isr.BrighterFatterKernel`
Resulting Brighter-Fatter Kernel.
Definition at line 169 of file makeBrighterFatterKernel.py.
◆ runQuantum()
def lsst.cp.pipe.makeBrighterFatterKernel.BrighterFatterKernelSolveTask.runQuantum |
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self, |
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butlerQC, |
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inputRefs, |
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outputRefs |
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Ensure that the input and output dimensions are passed along.
Parameters
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butlerQC : `lsst.daf.butler.butlerQuantumContext.ButlerQuantumContext`
Butler to operate on.
inputRefs : `lsst.pipe.base.connections.InputQuantizedConnection`
Input data refs to load.
ouptutRefs : `lsst.pipe.base.connections.OutputQuantizedConnection`
Output data refs to persist.
Definition at line 149 of file makeBrighterFatterKernel.py.
◆ successiveOverRelax()
def lsst.cp.pipe.makeBrighterFatterKernel.BrighterFatterKernelSolveTask.successiveOverRelax |
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self, |
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source, |
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maxIter = None , |
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eLevel = None |
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An implementation of the successive over relaxation (SOR) method.
A numerical method for solving a system of linear equations
with faster convergence than the Gauss-Seidel method.
Parameters:
-----------
source : `numpy.ndarray`
The input array.
maxIter : `int`, optional
Maximum number of iterations to attempt before aborting.
eLevel : `float`, optional
The target error level at which we deem convergence to have
occurred.
Returns:
--------
output : `numpy.ndarray`
The solution.
Definition at line 430 of file makeBrighterFatterKernel.py.
◆ ConfigClass
The documentation for this class was generated from the following file: