LegendreFactory

(Source code, png)

../../_images/openturns-LegendreFactory-1.png
class LegendreFactory(*args)

Legendre specific orthonormal univariate polynomial family.

For the Uniform distribution.

Methods

build(degree)

Build the k-th order orthogonal univariate polynomial.

buildCoefficients(degree)

Build the k-th order orthogonal univariate polynomial coefficients.

buildRecurrenceCoefficientsCollection(degree)

Build the recurrence coefficients.

getClassName()

Accessor to the object's name.

getMeasure()

Accessor to the associated probability measure.

getName()

Accessor to the object's name.

getNodesAndWeights(n)

Build the k-th order quadrature scheme.

getRecurrenceCoefficients(n)

Accessor to the recurrence coefficients of the k-th order.

getRoots(n)

Accessor to the recurrence coefficients of the k-th order.

hasName()

Test if the object is named.

setName(name)

Accessor to the object's name.

See also

StandardDistributionPolynomialFactory

Notes

Any sequence of orthogonal polynomials has a recurrence formula relating any three consecutive polynomials as follows:

P_{i + 1} = (a_i x + b_i) P_i + c_i P_{i - 1}, \quad 1 < i

The recurrence coefficients for the Legendre polynomials come analytically and read:

\begin{array}{rcl} a_i & = & \displaystyle \frac{\sqrt{(2 i + 1) (2 i + 3)}} {i + 1} \\ b_i & = & 0 \\ c_i & = & \displaystyle - \frac{i \sqrt{2 i + 3}} {(i + 1) \sqrt{2 i - 1}} \end{array}, \quad 1 < i

Examples

>>> import openturns as ot
>>> polynomial_factory = ot.LegendreFactory()
>>> for i in range(3):
...     print(polynomial_factory.build(i))
1
1.73205 * X
-1.11803 + 3.3541 * X^2
__init__(*args)
build(degree)

Build the k-th order orthogonal univariate polynomial.

Parameters:
kint, 0 \leq k

Polynomial order.

Returns:
polynomialOrthogonalUniVariatePolynomial

Requested orthogonal univariate polynomial.

Examples

>>> import openturns as ot
>>> polynomial_factory = ot.HermiteFactory()
>>> print(polynomial_factory.build(2))
-0.707107 + 0.707107 * X^2
buildCoefficients(degree)

Build the k-th order orthogonal univariate polynomial coefficients.

Parameters:
kint, 0 \leq k

Polynomial order.

Returns:
coefficientsPoint

Coefficients of the requested orthogonal univariate polynomial.

Examples

>>> import openturns as ot
>>> polynomial_factory = ot.HermiteFactory()
>>> print(polynomial_factory.buildCoefficients(2))
[-0.707107,0,0.707107]
buildRecurrenceCoefficientsCollection(degree)

Build the recurrence coefficients.

Build the recurrence coefficients of the orthogonal univariate polynomial family up to the k-th order.

Parameters:
kint, 0 \leq k

Polynomial order.

Returns:
recurrence_coefficientslist of Point

All the tecurrence coefficients up to the requested order.

Examples

>>> import openturns as ot
>>> polynomial_factory = ot.HermiteFactory()
>>> print(polynomial_factory.buildRecurrenceCoefficientsCollection(2))
0 : [  1         0         0        ]
1 : [  0.707107  0        -0.707107 ]
getClassName()

Accessor to the object’s name.

Returns:
class_namestr

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

getMeasure()

Accessor to the associated probability measure.

Returns:
measureDistribution

The associated probability measure (according to which the polynomials are orthogonal).

Notes

Two polynomials P and Q are orthogonal with respect to the probability measure w(x) \di{x} if and only if their dot product:

\langle P, Q \rangle = \int_{\alpha}^{\beta} P(x) Q(x) w(x)\di{x} = 0

where \alpha \in \Rset \cup \{-\infty\} and \beta \in \Rset \cup \{+\infty\}.

Examples

>>> import openturns as ot
>>> polynomial_factory = ot.HermiteFactory()
>>> print(polynomial_factory.getMeasure())
Normal(mu = 0, sigma = 1)
getName()

Accessor to the object’s name.

Returns:
namestr

The name of the object.

getNodesAndWeights(n)

Build the k-th order quadrature scheme.

Associated with the orthogonal univariate polynomials family.

Parameters:
kint, 0 < k

Polynomial order.

Returns:
nodesPoint

The nodes of the k-th order quadrature scheme.

weightsPoint

The weights of the k-th order quadrature scheme.

Examples

>>> import openturns as ot
>>> polynomial_factory = ot.HermiteFactory()
>>> nodes, weights = polynomial_factory.getNodesAndWeights(3)
>>> print(nodes)
[-1.73205,...,1.73205]
>>> print(weights)
[0.166667,0.666667,0.166667]
getRecurrenceCoefficients(n)

Accessor to the recurrence coefficients of the k-th order.

Of the orthogonal univariate polynomial.

Parameters:
kint, 0 \leq k

Polynomial order.

Returns:
recurrence_coefficientsPoint

The recurrence coefficients of the k-th order orthogonal univariate polynomial.

Notes

Any sequence of orthogonal polynomials has a recurrence formula relating any three consecutive polynomials as follows:

P_{-1}=0, P_0=1, P_{n + 1} = (a_n x + b_n) P_n + c_n P_{n - 1}, \quad n > 1

Examples

>>> import openturns as ot
>>> polynomial_factory = ot.HermiteFactory()
>>> print(polynomial_factory.getRecurrenceCoefficients(3))
[0.5,0,-0.866025]
getRoots(n)

Accessor to the recurrence coefficients of the k-th order.

Of the orthogonal univariate polynomial.

Parameters:
kint, k > 0

Polynomial order.

Returns:
rootsPoint

The roots of the k-th order orthogonal univariate polynomial.

Examples

>>> import openturns as ot
>>> polynomial_factory = ot.HermiteFactory()
>>> print(polynomial_factory.getRoots(3))
[-1.73205,...,1.73205]
hasName()

Test if the object is named.

Returns:
hasNamebool

True if the name is not empty.

setName(name)

Accessor to the object’s name.

Parameters:
namestr

The name of the object.

Examples using the class

Mixture of experts

Mixture of experts

Advanced polynomial chaos construction

Advanced polynomial chaos construction

Kriging: choose an arbitrary trend

Kriging: choose an arbitrary trend

Create univariate functions

Create univariate functions

Create a multivariate basis of functions from scalar multivariable functions

Create a multivariate basis of functions from scalar multivariable functions