Package org.elasticsearch.search.aggregations.pipeline.movavg.models

Class LinearModel

java.lang.Object

org.elasticsearch.search.aggregations.pipeline.movavg.models.MovAvgModel

org.elasticsearch.search.aggregations.pipeline.movavg.models.LinearModel

All Implemented Interfaces:

NamedWriteable, Writeable, ToXContent, ToXContentFragment

public class LinearModel
extends MovAvgModel

Calculate a linearly weighted moving average, such that older values are linearly less important. "Time" is determined by position in collection

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	LinearModel.LinearModelBuilder

Nested classes/interfaces inherited from class org.elasticsearch.search.aggregations.pipeline.movavg.models.MovAvgModel

MovAvgModel.AbstractModelParser

Nested classes/interfaces inherited from interface org.elasticsearch.common.xcontent.ToXContent

ToXContent.DelegatingMapParams, ToXContent.MapParams, ToXContent.Params

Nested classes/interfaces inherited from interface org.elasticsearch.common.io.stream.Writeable

Writeable.Reader<V>, Writeable.Writer<V>

Field Summary

Fields

Modifier and Type	Field	Description
static java.lang.String	NAME
static MovAvgModel.AbstractModelParser	PARSER

Fields inherited from interface org.elasticsearch.common.xcontent.ToXContent

EMPTY_PARAMS

Constructor Summary

Constructors

Constructor	Description
LinearModel()
LinearModel(StreamInput in)	Read from a stream.

Method Summary

Modifier and Type	Method	Description
boolean	canBeMinimized()	Returns if the model can be cost minimized.
MovAvgModel	clone()	Clone the model, returning an exact copy
protected double[]	doPredict(java.util.Collection<java.lang.Double> values, int numPredictions)	Calls to the model-specific implementation which actually generates the predictions
boolean	equals(java.lang.Object obj)
java.lang.String	getWriteableName()	Returns the name of the writeable object
int	hashCode()
MovAvgModel	neighboringModel()	Generates a "neighboring" model, where one of the tunable parameters has been randomly mutated within the allowed range.
double	next(java.util.Collection<java.lang.Double> values)	Returns the next value in the series, according to the underlying smoothing model
XContentBuilder	toXContent(XContentBuilder builder, ToXContent.Params params)
void	writeTo(StreamOutput out)	Write the model to the output stream

Methods inherited from class org.elasticsearch.search.aggregations.pipeline.movavg.models.MovAvgModel

emptyPredictions, hasValue, minimizeByDefault, predict

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.elasticsearch.common.xcontent.ToXContentFragment

isFragment

Field Detail

NAME

public static final java.lang.String NAME

See Also:

Constant Field Values

PARSER

public static final MovAvgModel.AbstractModelParser PARSER

Constructor Detail

LinearModel

public LinearModel()

LinearModel

public LinearModel(StreamInput in)

Read from a stream.

Method Detail

writeTo

public void writeTo(StreamOutput out)
             throws java.io.IOException

Description copied from class: MovAvgModel

Write the model to the output stream

Specified by:

writeTo in interface Writeable

Specified by:

writeTo in class MovAvgModel

Parameters:

out - Output stream

Throws:

java.io.IOException

getWriteableName

public java.lang.String getWriteableName()

Description copied from interface: NamedWriteable

Returns the name of the writeable object

canBeMinimized

public boolean canBeMinimized()

Description copied from class: MovAvgModel

Returns if the model can be cost minimized. Not all models have parameters which can be tuned / optimized.

Specified by:

canBeMinimized in class MovAvgModel

neighboringModel

public MovAvgModel neighboringModel()

Description copied from class: MovAvgModel

Generates a "neighboring" model, where one of the tunable parameters has been randomly mutated within the allowed range. Used for minimization

Specified by:

neighboringModel in class MovAvgModel

clone

public MovAvgModel clone()

Description copied from class: MovAvgModel

Clone the model, returning an exact copy

Specified by:

clone in class MovAvgModel

doPredict

protected double[] doPredict(java.util.Collection<java.lang.Double> values,
                             int numPredictions)

Description copied from class: MovAvgModel

Calls to the model-specific implementation which actually generates the predictions

Specified by:

doPredict in class MovAvgModel

Parameters:

values - Collection of numerics to movingAvg, usually windowed

numPredictions - Number of newly generated predictions to return

Returns:

Returns an array of doubles, since most smoothing methods operate on floating points

next

public double next(java.util.Collection<java.lang.Double> values)

Description copied from class: MovAvgModel

Returns the next value in the series, according to the underlying smoothing model

Specified by:

next in class MovAvgModel

Parameters:

values - Collection of numerics to movingAvg, usually windowed

Returns:

Returns a double, since most smoothing methods operate on floating points

toXContent

public XContentBuilder toXContent(XContentBuilder builder,
                                  ToXContent.Params params)
                           throws java.io.IOException

Throws:

java.io.IOException

hashCode

public int hashCode()

Specified by:

hashCode in class MovAvgModel

equals

public boolean equals(java.lang.Object obj)

Specified by:

equals in class MovAvgModel