lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter Class Reference

Inheritance diagram for lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter:

Public Member Functions
def	__init__ (self, record)
def	eval1d (self, dim, x)
def	eval2d (self, xDim, yDim, x, y)

Public Attributes
	samples
	parameters
	state
	accepted
	rejected
	lower
	upper
	points
	record
	pdf
	dimensions

Detailed Description

Definition at line 110 of file modelFitAdapters.py.

Constructor & Destructor Documentation

__init__()

def lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter.__init__	(		self,
			record
	)

Reimplemented from lsst.meas.modelfit.display.modelFitAdapters.ModelFitDataAdapter.

Definition at line 112 of file modelFitAdapters.py.

    def __init__(self, record):
        ModelFitDataAdapter.__init__(self, record)
        self.samples = record.getSamples().copy(deep=True)
        self.parameters = self.samples["parameters"]
        self.state = self.samples["state"]
        # The first point is neither accepted nor rejected, so we test on rejected and !rejected so
        # as to include the first point with the accepted points
        mask = (self.state & modelfitLib.Optimizer.STATUS_STEP_REJECTED).astype(bool)
        self.accepted = self.parameters[numpy.logical_not(mask)]
        # For each rejected point, we have three path points: the rejected point, the last accepted point,
        # and a NaN to tell matplotlib not to connect to the next one.
        # Note that the defaults for OptimizerTrackLayer use markevery=3 to only put markers on
        # the rejected points
        rejected = []
        current = self.parameters[0]
        nans = numpy.array([numpy.nan] * self.parameters.shape[1], dtype=float)
        for parameters, isRejected in zip(self.parameters, mask):
            if isRejected:
                rejected.extend([parameters, current, nans])
            else:
                current = parameters
        self.rejected = numpy.array(rejected)
        self.lower = {}
        self.upper = {}
        for i, dim in enumerate(self.dimensions):
            projected = self.pdf[0].project(i)
            mu = projected.getMu()
            sigma = projected.getSigma()**0.5
            self.lower[dim] = min(self.accepted[:, i].min(), mu - 3*sigma)
            self.upper[dim] = max(self.accepted[:, i].max(), mu + 3*sigma)
        # Now we setup some special points for a CrossPointsLayer
        self.points = numpy.zeros((2, self.parameters.shape[1]), dtype=float)
        record.getInterpreter().packParameters(
            self.record['initial.nonlinear'], self.record['initial.amplitudes'],
            self.points[0, :]
        )
        record.getInterpreter().packParameters(
            self.record['fit.nonlinear'], self.record['fit.amplitudes'],
            self.points[1, :]
        )

Member Function Documentation

eval1d()

def lsst.meas.modelfit.display.modelFitAdapters.ModelFitDataAdapter.eval1d (   self,   dim,   x  )

inherited

Definition at line 37 of file modelFitAdapters.py.

    def eval1d(self, dim, x):
        i = self.dimensions.index(dim)
        z = numpy.zeros(x.shape, dtype=float)
        if i >= self.pdf.getDimension():
            return None
        projection = self.pdf.project(i)
        projection.evaluate(x.reshape(x.shape + (1,)), z)
        return z
 

eval2d()

def lsst.meas.modelfit.display.modelFitAdapters.ModelFitDataAdapter.eval2d (   self,   xDim,   yDim,   x,   y  )

inherited

Definition at line 46 of file modelFitAdapters.py.

    def eval2d(self, xDim, yDim, x, y):
        i = self.dimensions.index(yDim)
        j = self.dimensions.index(xDim)
        z = numpy.zeros(x.size, dtype=float)
        if i >= self.pdf.getDimension() or j >= self.pdf.getDimension():
            return None
        projection = self.pdf.project(j, i)
        xy = numpy.zeros((x.size, 2), dtype=float)
        xy[:, 0] = x.flatten()
        xy[:, 1] = y.flatten()
        projection.evaluate(xy, z)
        return z.reshape(x.shape)
 
 

Member Data Documentation

accepted

lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter.accepted

Definition at line 120 of file modelFitAdapters.py.

dimensions

lsst.meas.modelfit.display.modelFitAdapters.ModelFitDataAdapter.dimensions

inherited

Definition at line 35 of file modelFitAdapters.py.

lower

lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter.lower

Definition at line 134 of file modelFitAdapters.py.

parameters

lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter.parameters

Definition at line 115 of file modelFitAdapters.py.

pdf

lsst.meas.modelfit.display.modelFitAdapters.ModelFitDataAdapter.pdf

inherited

Definition at line 34 of file modelFitAdapters.py.

points

lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter.points

Definition at line 143 of file modelFitAdapters.py.

record

lsst.meas.modelfit.display.modelFitAdapters.ModelFitDataAdapter.record

inherited

Definition at line 33 of file modelFitAdapters.py.

rejected

lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter.rejected

Definition at line 133 of file modelFitAdapters.py.

samples

lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter.samples

Definition at line 114 of file modelFitAdapters.py.

state

lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter.state

Definition at line 116 of file modelFitAdapters.py.

upper

lsst.meas.modelfit.display.modelFitAdapters.OptimizerDataAdapter.upper

Definition at line 135 of file modelFitAdapters.py.

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The documentation for this class was generated from the following file:

• /j/snowflake/release/lsstsw/stack/lsst-scipipe-0.7.0/Linux64/meas_modelfit/22.0.1-4-g44f2e3d+9e4ab0f4fa/python/lsst/meas/modelfit/display/modelFitAdapters.py