Compact¶
- class Compact(*args)¶
Compact history storage strategy.
- Available constructors:
Compact(N)
- Parameters:
- Ninteger
minimum number of points to store.
See also
Notes
The compact strategy stores a regularly spaced sub-sample where the minimum size of the stored numerical sample is . OpenTURNS proceeds as follows :
it stores the first simulations : the size of the stored sample is ,
it selects only 1 out of 2 of the stored simulations : then the size of the stored sample decreases to (this is the compact step),
it stores the next simulations when selecting 1 out of 2 of the next simulations : the size of the stored sample is ,
it selects only 1 out of 2 of the stored simulations : then the size of the stored sample decreases to ,
it stores the next simulations when selecting 1 out of 4 of the next simulations : the size of the stored sample is ,
then it keeps on until reaching the stopping criteria.
The stored numerical sample will have a size within and if at least one cycle has been done, else it will be at most .
Methods
clear
()Clear the stored points.
Accessor to the object's name.
Accessor to the half maximum number of points to store.
getId
()Accessor to the object's id.
getIndex
()Accessor to the index.
getName
()Accessor to the object's name.
Accessor to the stored sample.
Accessor to the object's shadowed id.
Accessor to the object's visibility state.
hasName
()Test if the object is named.
Test if the object has a distinguishable name.
setDimension
(dimension)Set the dimension of points to store.
setName
(name)Accessor to the object's name.
setShadowedId
(id)Accessor to the object's shadowed id.
setVisibility
(visible)Accessor to the object's visibility state.
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__).
- getHalfMaximumSize()¶
Accessor to the half maximum number of points to store.
- Returns:
- Ninteger
The half maximum number of points to store.
- getId()¶
Accessor to the object’s id.
- Returns:
- idint
Internal unique identifier.
- getIndex()¶
Accessor to the index.
- Returns:
- indexinteger
The number of the stored points.
- getName()¶
Accessor to the object’s name.
- Returns:
- namestr
The name of the object.
- getSample()¶
Accessor to the stored sample.
- Returns:
- sample
Sample
Numerical sample which is the collection of points stored by the history strategy.
- sample
- getShadowedId()¶
Accessor to the object’s shadowed id.
- Returns:
- idint
Internal unique identifier.
- getVisibility()¶
Accessor to the object’s visibility state.
- Returns:
- visiblebool
Visibility flag.
- hasName()¶
Test if the object is named.
- Returns:
- hasNamebool
True if the name is not empty.
- hasVisibleName()¶
Test if the object has a distinguishable name.
- Returns:
- hasVisibleNamebool
True if the name is not empty and not the default one.
- 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.
- setShadowedId(id)¶
Accessor to the object’s shadowed id.
- Parameters:
- idint
Internal unique identifier.
- setVisibility(visible)¶
Accessor to the object’s visibility state.
- Parameters:
- visiblebool
Visibility flag.
- 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¶
Specify a simulation algorithm
Exploitation of simulation algorithm results