SamplePartition

class SamplePartition(*args)

Select partition of samples.

Class to define subset of points, and select new ones, see getPeakOverThreshold().

Warning

This class is experimental and likely to be modified in future releases. To use it, import the openturns.experimental submodule.

Parameters:

sample2-d sequence of float

A sample of dimension 1.

indicessequence of int 2-tuple or sequence of int, optional

Flat indices of population in the partition or list of (start,end) ranges. If not provided the default is to consider one single group with all the sample values.

Methods

ExtractFromDataFrame(partial)	Extract a partition from a pandas dataframe as a SamplePartition.
draw(threshold)	Draw clusters and peaks.
getClassName()	Accessor to the object's name.
getIndicesCollection()	Partition indices accessor.
getName()	Accessor to the object's name.
getPeakOverThreshold(threshold, r)	Compute extreme values using Peaks Over Threshold (POT) method.
getSample()	Sample accessor.
hasName()	Test if the object is named.
setName(name)	Accessor to the object's name.

Examples

>>> import openturns as ot
>>> import openturns.experimental as otexp
>>> ref = ot.Uniform().getSample(10)
>>> sp1 = otexp.SamplePartition(ref, [[0, 3], [5, 9]])
>>> sp2 = otexp.SamplePartition(ref, [0, 1, 2, 3])

__init__(*args)

ExtractFromDataFrame(partial)

Extract a partition from a pandas dataframe as a SamplePartition.

Parameters:

fullpandas DataFrame

Full data

partialpandas DataFrame

Filtered data from the full Dataframe

Returns:

partitionopenturns.experimental.SamplePartition

The resulting partition

draw(threshold)

Draw clusters and peaks.

Parameters:

thresholdfloat

The threshold value

Returns:

graphGraph

Graph of clusters, peaks.

getClassName()

Accessor to the object’s name.

Returns:

class_namestr

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

getIndicesCollection()

Partition indices accessor.

Returns:

indicesCollectionIndicesCollection

List of partitions ranges as (start,end) indices.

getName()

Accessor to the object’s name.

Returns:

namestr

The name of the object.

getPeakOverThreshold(threshold, r)

Compute extreme values using Peaks Over Threshold (POT) method.

Parameters:

sample2-d sequence of float

A sample of dimension 1.

thresholdfloat

The threshold value

rint

Minimum number of consecutive values below the threshold between clusters

Returns:

peaksSample

The peaks for each cluster

clustersopenturns.experimental.SamplePartition

The clusters partition

getSample()

Sample accessor.

Returns:

sampleSample

The internal sample

hasName()

Test if the object is named.

Returns:

hasNamebool

True if the name is not empty.

setName(name)

Accessor to the object’s name.

Parameters:

namestr

The name of the object.

Examples using the class

Estimate a GPD on the Wooster temperature data

Estimate a GPD on the Wooster temperature data

Estimate a GPD on the Dow Jones Index data

Estimate a GPD on the Dow Jones Index data