IterativeExtrema

class IterativeExtrema(*args)

Iterative minimum and maximum.

Parameters:
dimensionint

Dimension of the input data

See also

IterativeAlgorithm

Notes

This class iteratively computes the minimum and maximum over an iteratively increasing dataset without storing any data in memory.

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> dim = 5
>>> myExtrema = ot.IterativeExtrema(dim)
>>> n = ot.Normal(dim)
>>> size = 50

Increment the data one point at a time:

>>> for i in range(size):
...     point = n.getRealization()
...     myExtrema.increment(point)
>>> print(myExtrema.getIterationNumber())
50
>>> print(myExtrema.getMin())
[-2.4067,-2.53986,-2.29006,-3.09737,-2.18139]
>>> print(myExtrema.getMax())
[3.01263,3.02799,1.85579,2.11968,1.36783]

Increment with 50 additional points simultaneously and recompute the extrema:

>>> sample = n.getSample(size)
>>> myExtrema.increment(sample)
>>> print(myExtrema.getIterationNumber())
100
>>> print(myExtrema.getMin())
[-2.4067,-2.53986,-2.72106,-3.09737,-2.18139]
>>> print(myExtrema.getMax())
[3.01263,3.02799,2.24097,2.11968,2.55533]

Methods

getClassName()

Accessor to the object's name.

getDimension()

Get the dimension of the algorithm

getId()

Accessor to the object's id.

getIterationNumber()

Get the current iteration of the algorithm

getMax()

Returns the values of the maximum over the inputs component per component

getMin()

Returns the values of the minimum over the inputs component per component

getName()

Accessor to the object's name.

getShadowedId()

Accessor to the object's shadowed id.

getVisibility()

Accessor to the object's visibility state.

hasName()

Test if the object is named.

hasVisibleName()

Test if the object has a distinguishable name.

increment(*args)

Increment the internal data.

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.
__init__(*args)
getClassName()

Accessor to the object’s name.

Returns:
class_namestr

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

getDimension()

Get the dimension of the algorithm

Returns:
dimensionint

Dimension of the algorithm

getId()

Accessor to the object’s id.

Returns:
idint

Internal unique identifier.

getIterationNumber()

Get the current iteration of the algorithm

Returns:
iterationint

Current iteration of the algorithm

getMax()

Returns the values of the maximum over the inputs component per component

Returns:
maxPoint

current values of the iterative maximum.

getMin()

Returns the values of the minimum over the inputs component per component

Returns:
minPoint

current values of the iterative minimum.

getName()

Accessor to the object’s name.

Returns:
namestr

The name of the object.

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.

increment(*args)

Increment the internal data.

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

New input point or sample.

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.

Examples using the class

Estimate extrema iteratively

Estimate extrema iteratively