HistoryStrategy

class HistoryStrategy(*args)

History storage strategy.

Available constructors:

HistoryStrategy()

HistoryStrategy(historyStrategyImp)

Parameters
historyStrategyImpHistoryStrategyImplementation

An implementation of a history strategy which is provided by Compact, Full, Last or Null class.

See also

Compact, Full, Last, Null

Notes

In order to prevent a memory problem, the User has the possibility to choose the storage strategy used to save the numerical samples. Four strategies are proposed:

  • the Null strategy where nothing is stored. This class does not require to specify arguments.

  • the Full strategy where every point is stored. Be careful! The memory will be exhausted for huge samples. This class does not require to specify arguments.

  • the Last strategy where only the N last points are stored, where N is specified by the User. This class requires to specify the number of points to store.

  • the Compact strategy where a regularly spaced sub-sample is stored. The minimum size N of the stored numerical sample is specified by the User. It 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. This class requires to specify the number of points to store.

Methods

clear(self)

Clear the stored points.

getClassName(self)

Accessor to the object’s name.

getId(self)

Accessor to the object’s id.

getImplementation(self)

Accessor to the underlying implementation.

getName(self)

Accessor to the object’s name.

getSample(self)

Accessor to the stored sample.

setDimension(self, dimension)

Set the dimension of points to store.

setName(self, name)

Accessor to the object’s name.

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__).

getId(self)

Accessor to the object’s id.

Returns
idint

Internal unique identifier.

getImplementation(self)

Accessor to the underlying implementation.

Returns
implImplementation

The implementation class.

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.

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.

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.