# AggregatedProcess¶

class AggregatedProcess(*args)

Aggregation of several processes in one process.

Available constructor:
AggregatedProcess(collProc)
Parameters: collProc : sequence of Process Collection of processes which all have the same input dimension.

Notes

If we note for the collection of processes, where for all . Then the resulting aggregated process where . The mesh of the first process has been assigned to the process .

Examples

Create an aggregated process:

>>> import openturns as ot
>>> myMesher = ot.IntervalMesher(ot.Indices([5,10]))
>>> lowerbound = [0.0, 0.0]
>>> upperBound = [2.0, 4.0]
>>> myInterval = ot.Interval(lowerbound, upperBound)
>>> myMesh = myMesher.build(myInterval)
>>> myProcess1 = ot.WhiteNoise(ot.Normal(), myMesh)
>>> myProcess2 = ot.WhiteNoise(ot.Triangular(), myMesh)
>>> myAggregatedProcess = ot.AggregatedProcess([myProcess1, myProcess2])


Draw one realization:

>>> myGraph = myAggregatedProcess.getRealization().drawMarginal(0)


Methods

 getClassName() Accessor to the object’s name. getContinuousRealization() Get a continuous realization. getCovarianceModel() Accessor to the covariance model. getDescription() Get the description of the process. getFuture(*args) Prediction of the future iterations of the process. getId() Accessor to the object’s id. getInputDimension() Get the dimension of the domain . getMarginal(*args) Accessor the marginal processes. getMesh() Get the mesh. getName() Accessor to the object’s name. getOutputDimension() Get the dimension of the domain . getProcessCollection() Get the collection of processes. getRealization() Get one realization of the aggregated process. getSample(size) Get realizations of the process. getShadowedId() Accessor to the object’s shadowed id. getTimeGrid() Get the time grid of observation of the process. getTrend() Accessor to the trend. getVisibility() Accessor to the object’s visibility state. hasName() Test if the object is named. hasVisibleName() Test if the object has a distinguishable name. isComposite() Test whether the process is composite or not. isNormal() Test whether the process is normal or not. isStationary() Test whether the process is stationary or not. setDescription(description) Set the description of the process. setMesh(mesh) Set the mesh. setName(name) Accessor to the object’s name. setProcessCollection(coll) Set the collection of processes. setShadowedId(id) Accessor to the object’s shadowed id. setTimeGrid(timeGrid) Set the time grid of observation of the process. setVisibility(visible) Accessor to the object’s visibility state.
__init__(*args)

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

getClassName()

Accessor to the object’s name.

Returns: class_name : str The object class name (object.__class__.__name__).
getContinuousRealization()

Get a continuous realization.

Returns: realization : Function Each process of the collection is continuously realized on the common domain .
getCovarianceModel()

Accessor to the covariance model.

Returns: cov_model : CovarianceModel Covariance model, if any.
getDescription()

Get the description of the process.

Returns: description : Description Description of the process.
getFuture(*args)

Prediction of the future iterations of the process.

Parameters: stepNumber : int, Number of future steps. size : int, , optional Number of futures needed. Default is 1. prediction : future iterations of the process. If , prediction is a TimeSeries. Otherwise, it is a ProcessSample.
getId()

Accessor to the object’s id.

Returns: id : int Internal unique identifier.
getInputDimension()

Get the dimension of the domain .

Returns: n : int Dimension of the domain : .
getMarginal(*args)

Accessor the marginal processes.

Available usages:

getMarginal(index)

getMarginal(indices)

Parameters: index : int Index of the selected marginal process. indices : Indices List of indices of the selected marginal processes.

Notes

The selected marginal processes are extracted if the list of indices does not mingle the processes of the initial collection: take care to extract all the marginal processes process by process. For example, if , and then you can extract Indices([1,0,2,4,6]) but not Indices([1,2,0,4,6]).

getMesh()

Get the mesh.

Returns: mesh : Mesh Mesh over which the domain is discretized.
getName()

Accessor to the object’s name.

Returns: name : str The name of the object.
getOutputDimension()

Get the dimension of the domain .

Returns: d : int Dimension of the domain .
getProcessCollection()

Get the collection of processes.

Returns: collProc : ProcessCollection Collection of processes which all have the same input dimension.
getRealization()

Get one realization of the aggregated process.

Returns: realization : Field Each process of the collection is realized on the common mesh defined on .
getSample(size)

Get realizations of the process.

Parameters: n : int, Number of realizations of the process needed. processSample : ProcessSample realizations of the random process. A process sample is a collection of fields which share the same mesh .
getShadowedId()

Accessor to the object’s shadowed id.

Returns: id : int Internal unique identifier.
getTimeGrid()

Get the time grid of observation of the process.

Returns: timeGrid : RegularGrid Time grid of a process when the mesh associated to the process can be interpreted as a RegularGrid. We check if the vertices of the mesh are scalar and are regularly spaced in but we don’t check if the connectivity of the mesh is conform to the one of a regular grid (without any hole and composed of ordered instants).
getTrend()

Accessor to the trend.

Returns: trend : TrendTransform Trend, if any.
getVisibility()

Accessor to the object’s visibility state.

Returns: visible : bool Visibility flag.
hasName()

Test if the object is named.

Returns: hasName : bool True if the name is not empty.
hasVisibleName()

Test if the object has a distinguishable name.

Returns: hasVisibleName : bool True if the name is not empty and not the default one.
isComposite()

Test whether the process is composite or not.

Returns: isComposite : bool True if the process is composite (built upon a function and a process).
isNormal()

Test whether the process is normal or not.

Returns: isNormal : bool True if the process is normal.

Notes

A stochastic process is normal if all its finite dimensional joint distributions are normal, which means that for all and , with , there is and such that:

where , and and is the symmetric matrix:

A Gaussian process is entirely defined by its mean function and its covariance function (or correlation function ).

isStationary()

Test whether the process is stationary or not.

Returns: isStationary : bool True if the process is stationary.

Notes

A process is stationary if its distribution is invariant by translation: , , , we have:

setDescription(description)

Set the description of the process.

Parameters: description : sequence of str Description of the process.
setMesh(mesh)

Set the mesh.

Parameters: mesh : Mesh Mesh over which the domain is discretized.
setName(name)

Accessor to the object’s name.

Parameters: name : str The name of the object.
setProcessCollection(coll)

Set the collection of processes.

Parameters: collProc : sequence of Process Collection of processes which all have the same input dimension.
setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters: id : int Internal unique identifier.
setTimeGrid(timeGrid)

Set the time grid of observation of the process.

Returns: timeGrid : RegularGrid Time grid of observation of the process when the mesh associated to the process can be interpreted as a RegularGrid. We check if the vertices of the mesh are scalar and are regularly spaced in but we don’t check if the connectivity of the mesh is conform to the one of a regular grid (without any hole and composed of ordered instants).
setVisibility(visible)

Accessor to the object’s visibility state.

Parameters: visible : bool Visibility flag.