AdaptiveStieltjesAlgorithm¶
- class AdaptiveStieltjesAlgorithm(*args)¶
AdaptiveStieltjes algorithm used to build the orthonormal basis.
The algorithm builds a polynomial basis orthonormal with respect to a specific distribution.
- Parameters:
- measure
Distribution
A measure for which the orthonormal polynomial basis is built.
- measure
See also
Notes
It implements an adaptive Stieltjes algorithm that builds the polynomial family orthonormal with respect to the distribution measure, using the
GaussKronrod
adaptive integration method to compute the following dot-products: and where is the monic polynomial associated to the orthonormal polynomial , needed to compute the coefficients of the three-terms recurrence relation that defines (seeOrthogonalUniVariatePolynomialFamily
):where , , and .
Methods
Accessor to the object's name.
Accessor to the measure.
getName
()Accessor to the object's name.
Accessor to the recurrence coefficients.
hasName
()Test if the object is named.
setMeasure
(measure)Accessor to the measure.
setName
(name)Accessor to the object's name.
- __init__(*args)¶
- getClassName()¶
Accessor to the object’s name.
- Returns:
- class_namestr
The object class name (object.__class__.__name__).
- getMeasure()¶
Accessor to the measure.
- Returns:
- m
Distribution
The measure for which the orthonormal polynomial basis is built.
- m
- getName()¶
Accessor to the object’s name.
- Returns:
- namestr
The name of the object.
- getRecurrenceCoefficients(n)¶
Accessor to the recurrence coefficients.
- Parameters:
- nint
Index ot the recurrence step.
- Returns:
- coefsequence of float
Calculate the coefficients of recurrence , , such that .
- hasName()¶
Test if the object is named.
- Returns:
- hasNamebool
True if the name is not empty.
- setMeasure(measure)¶
Accessor to the measure.
- Parameters:
- m
Distribution
The measure for which the orthonormal polynomial basis is built.
- m
- setName(name)¶
Accessor to the object’s name.
- Parameters:
- namestr
The name of the object.