UniVariateFunction

class UniVariateFunction(*args)

Base class for univariate functions.

Methods

__call__(x)

Call self as a function.

draw(xMin, xMax, pointNumber)

Draw the function.

getClassName()

Accessor to the object's name.

getId()

Accessor to the object's id.

getImplementation()

Accessor to the underlying implementation.

getName()

Accessor to the object's name.

gradient(x)

Compute the gradient at point x.

hessian(x)

Compute the hessian at point x.

setName(name)

Accessor to the object's name.
__init__(*args)
draw(xMin, xMax, pointNumber)

Draw the function.

Parameters:
x_minfloat, optional

The starting value that is used for meshing the x-axis.

x_maxfloat, optional, x_{\max} > x_{\min}

The ending value that is used for meshing the x-axis.

n_pointsint, optional

The number of points that is used for meshing the x-axis.

Examples

>>> import openturns as ot
>>> from openturns.viewer import View
>>> f = ot.UniVariatePolynomial([1.0, 2.0, -3.0, 5.0])
>>> View(f.draw(-10.0, 10.0, 100)).show()
getClassName()

Accessor to the object’s name.

Returns:
class_namestr

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

getId()

Accessor to the object’s id.

Returns:
idint

Internal unique identifier.

getImplementation()

Accessor to the underlying implementation.

Returns:
implImplementation

A copy of the underlying implementation object.

getName()

Accessor to the object’s name.

Returns:
namestr

The name of the object.

gradient(x)

Compute the gradient at point x.

Returns:
gradientfloat

The value of the function’s first-order derivative at point x.

Examples

>>> import openturns as ot
>>> P = ot.UniVariatePolynomial([1.0, 2.0, 3.0])
>>> print(P.gradient(1.0))
8.0
hessian(x)

Compute the hessian at point x.

Parameters:
xfloat

Input value.

Returns:
hessianfloat

The value of the function’s second-order derivative at point x.

setName(name)

Accessor to the object’s name.

Parameters:
namestr

The name of the object.