Full

class Full(*args)

Full history storage strategy.

Notes

The full strategy stores every points. Be careful! The memory will be exhausted for huge samples.

Methods

clear()

Clear the stored points.

getClassName()

Accessor to the object's name.

getName()

Accessor to the object's name.

getSample()

Accessor to the stored sample.

hasName()

Test if the object is named.

setDimension(dimension)

Set the dimension of points to store.

setName(name)

Accessor to the object's name.

store(*args)

Store points or samples.

__init__(*args)
clear()

Clear the stored points.

Notes

It erases the previously stored points

getClassName()

Accessor to the object’s name.

Returns:
class_namestr

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

getName()

Accessor to the object’s name.

Returns:
namestr

The name of the object.

getSample()

Accessor to the stored sample.

Returns:
sampleSample

Numerical sample which is the collection of points stored by the history strategy.

hasName()

Test if the object is named.

Returns:
hasNamebool

True if the name is not empty.

setDimension(dimension)

Set the dimension of points to store.

This method must be called before calling the store method.

Parameters:
dimension: int

Dimension of points to store

Notes

It erases the previously stored points

setName(name)

Accessor to the object’s name.

Parameters:
namestr

The name of the object.

store(*args)

Store points or samples.

Parameters:
datasequence of float or 2-d sequence of float

Point or sample to store.

Notes

It adds a unique point or all the point of the sample in the natural order to the history.

Examples using the class

Use the Adaptive Directional Stratification Algorithm

Use the Adaptive Directional Stratification Algorithm

Use the Directional Sampling Algorithm

Use the Directional Sampling Algorithm

Specify a simulation algorithm

Specify a simulation algorithm