AggregatedProcess¶
(Source code, png, hires.png, pdf)

class
AggregatedProcess
(*args)¶ Aggregation of several processes in one process.
 Available constructor:
AggregatedProcess(collProc)
 Parameters
 collProcsequence of
Process
Collection of processes which all have the same input dimension.
 collProcsequence of
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
Accessor to the object’s name.
Get a continuous realization.
Accessor to the covariance model.
Get the description of the process.
getFuture
(*args)Prediction of the future iterations of the process.
getId
()Accessor to the object’s id.
Get the dimension of the domain .
getMarginal
(*args)Accessor the marginal processes.
getMesh
()Get the mesh.
getName
()Accessor to the object’s name.
Get the dimension of the domain .
Get the collection of processes.
Get one realization of the aggregated process.
getSample
(size)Get realizations of the process.
Accessor to the object’s shadowed id.
Get the time grid of observation of the process.
getTrend
()Accessor to the trend.
Accessor to the object’s visibility state.
hasName
()Test if the object is named.
Test if the object has a distinguishable name.
Test whether the process is composite or not.
isNormal
()Test whether the process is normal or not.
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_namestr
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 .
 realization

getCovarianceModel
()¶ Accessor to the covariance model.
 Returns
 cov_model
CovarianceModel
Covariance model, if any.
 cov_model

getDescription
()¶ Get the description of the process.
 Returns
 description
Description
Description of the process.
 description

getFuture
(*args)¶ Prediction of the future iterations of the process.
 Parameters
 stepNumberint,
Number of future steps.
 sizeint, , optional
Number of futures needed. Default is 1.
 Returns
 prediction
ProcessSample
orTimeSeries
future iterations of the process. If , prediction is a
TimeSeries
. Otherwise, it is aProcessSample
.
 prediction

getId
()¶ Accessor to the object’s id.
 Returns
 idint
Internal unique identifier.

getInputDimension
()¶ Get the dimension of the domain .
 Returns
 nint
Dimension of the domain : .

getMarginal
(*args)¶ Accessor the marginal processes.
 Available usages:
getMarginal(index)
getMarginal(indices)
 Parameters
 indexint
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]).

getName
()¶ Accessor to the object’s name.
 Returns
 namestr
The name of the object.

getOutputDimension
()¶ Get the dimension of the domain .
 Returns
 dint
Dimension of the domain .

getProcessCollection
()¶ Get the collection of processes.
 Returns
 collProc
ProcessCollection
Collection of processes which all have the same input dimension.
 collProc

getRealization
()¶ Get one realization of the aggregated process.
 Returns
 realization
Field
Each process of the collection is realized on the common mesh defined on .
 realization

getSample
(size)¶ Get realizations of the process.
 Parameters
 nint,
Number of realizations of the process needed.
 Returns
 processSample
ProcessSample
realizations of the random process. A process sample is a collection of fields which share the same mesh .
 processSample

getShadowedId
()¶ Accessor to the object’s shadowed id.
 Returns
 idint
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).
 timeGrid

getTrend
()¶ Accessor to the trend.
 Returns
 trend
TrendTransform
Trend, if any.
 trend

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.

isComposite
()¶ Test whether the process is composite or not.
 Returns
 isCompositebool
True if the process is composite (built upon a function and a process).

isNormal
()¶ Test whether the process is normal or not.
 Returns
 isNormalbool
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
 isStationarybool
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
 descriptionsequence of str
Description of the process.

setName
(name)¶ Accessor to the object’s name.
 Parameters
 namestr
The name of the object.

setProcessCollection
(coll)¶ Set the collection of processes.
 Parameters
 collProcsequence of
Process
Collection of processes which all have the same input dimension.
 collProcsequence of

setShadowedId
(id)¶ Accessor to the object’s shadowed id.
 Parameters
 idint
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).
 timeGrid

setVisibility
(visible)¶ Accessor to the object’s visibility state.
 Parameters
 visiblebool
Visibility flag.