Compact

class Compact(*args)

Compact history storage strategy.

Available constructors:

Compact(N)

Parameters
Ninteger

minimum number of points to store.

Notes

The compact strategy stores a regularly spaced sub-sample where the minimum size of the stored numerical sample is N. OpenTURNS proceeds as follows :

  1. it stores the first 2N simulations : the size of the stored sample is 2N,

  2. it selects only 1 out of 2 of the stored simulations : then the size of the stored sample decreases to N (this is the compact step),

  3. it stores the next N simulations when selecting 1 out of 2 of the next simulations : the size of the stored sample is 2N,

  4. it selects only 1 out of 2 of the stored simulations : then the size of the stored sample decreases to N,

  5. it stores the next N simulations when selecting 1 out of 4 of the next simulations : the size of the stored sample is 2N,

  6. then it keeps on until reaching the stopping criteria.

The stored numerical sample will have a size within N and 2N if at least one cycle has been done, else it will be at most N.

Methods

clear(self)

Clear the stored points.

getClassName(self)

Accessor to the object’s name.

getHalfMaximumSize(self)

Accessor to the half maximum number of points to store.

getId(self)

Accessor to the object’s id.

getIndex(self)

Accessor to the index.

getName(self)

Accessor to the object’s name.

getSample(self)

Accessor to the stored sample.

getShadowedId(self)

Accessor to the object’s shadowed id.

getVisibility(self)

Accessor to the object’s visibility state.

hasName(self)

Test if the object is named.

hasVisibleName(self)

Test if the object has a distinguishable name.

setDimension(self, dimension)

Set the dimension of points to store.

setName(self, name)

Accessor to the object’s name.

setShadowedId(self, id)

Accessor to the object’s shadowed id.

setVisibility(self, visible)

Accessor to the object’s visibility state.

store(self, \*args)

Store points or samples.

__init__(self, \*args)

Initialize self. See help(type(self)) for accurate signature.

clear(self)

Clear the stored points.

Notes

It erases the previously stored points

getClassName(self)

Accessor to the object’s name.

Returns
class_namestr

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

getHalfMaximumSize(self)

Accessor to the half maximum number of points to store.

Returns
Ninteger

The half maximum number of points to store.

getId(self)

Accessor to the object’s id.

Returns
idint

Internal unique identifier.

getIndex(self)

Accessor to the index.

Returns
indexinteger

The number of the stored points.

getName(self)

Accessor to the object’s name.

Returns
namestr

The name of the object.

getSample(self)

Accessor to the stored sample.

Returns
sampleSample

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

getShadowedId(self)

Accessor to the object’s shadowed id.

Returns
idint

Internal unique identifier.

getVisibility(self)

Accessor to the object’s visibility state.

Returns
visiblebool

Visibility flag.

hasName(self)

Test if the object is named.

Returns
hasNamebool

True if the name is not empty.

hasVisibleName(self)

Test if the object has a distinguishable name.

Returns
hasVisibleNamebool

True if the name is not empty and not the default one.

setDimension(self, 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(self, name)

Accessor to the object’s name.

Parameters
namestr

The name of the object.

setShadowedId(self, id)

Accessor to the object’s shadowed id.

Parameters
idint

Internal unique identifier.

setVisibility(self, visible)

Accessor to the object’s visibility state.

Parameters
visiblebool

Visibility flag.

store(self, \*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.