DesignProxy

class DesignProxy(*args)

Design matrix cache.

Available constructors:

DesignProxy(x, basis)

DesignProxy(matrix)

Parameters:

xSample

Input sample

psisequence of Function

Basis

matrix2-d sequence of float

The design matrix

Notes

Helps to cache evaluations of the design matrix. Can be useful for an iterative least squares problem resolution or in interaction with LeastSquaresMethod to select the algorithm used for the resolution of linear least-squares problems.

Methods

computeDesign(indices)	Build the design matrix.
getBasis()	Accessor to the basis.
getClassName()	Accessor to the object's name.
getInputSample()	Input sample accessor.
getRowFilter()	Row filter accessor.
getSampleSize()	Sample size accessor.
getWeight()	Accessor to the weights.
hasRowFilter()	Row filter flag accessor.
hasWeight()	Weight flag accessor.
setRowFilter(rowFilter)	Row filter accessor.
setWeight(weight)	Accessor to the weights.

__init__(*args)

computeDesign(indices)

Build the design matrix.

Parameters:

indicessequence of int

Indices of the current basis in the global basis

Returns:

psiAkMatrix

The design matrix

getBasis()

Accessor to the basis.

Returns:

basiscollection of Function

Basis.

getClassName()

Accessor to the object’s name.

Returns:

class_namestr

The object class name (object.__class__.__name__).

getInputSample()

Input sample accessor.

Returns:

inputSampleSample

Input sample.

getRowFilter()

Row filter accessor.

Returns:

rowFilterIndices

Sub-indices in of the sample in the current indices

getSampleSize()

Sample size accessor.

Returns:

sampleSizeint

Size of sample accounting for row filter

getWeight()

Accessor to the weights.

Returns:

weightPoint

Weights on each basis term

hasRowFilter()

Row filter flag accessor.

Returns:

hasRowFilterbool

Whether sub-indices of the basis are set

hasWeight()

Weight flag accessor.

Returns:

hasWeightbool

Whether weights are set

setRowFilter(rowFilter)

Row filter accessor.

Parameters:

rowFiltersequence of int

Sub-indices in of the sample in the current indices

setWeight(weight)

Accessor to the weights.

Parameters:

weightsequence of float

Weights on each basis term