magpie.data.utilities.filters

Class CompositionDistanceFilter

java.lang.Object

magpie.data.utilities.filters.BaseDatasetFilter

magpie.data.utilities.filters.CompositionDistanceFilter

All Implemented Interfaces:

java.io.Serializable, Options

public class CompositionDistanceFilter
extends BaseDatasetFilter

Filter compositions based on distance from a target composition. Filters any composition where the maximum change in any element is less than a certain value.

Usage: <composition> <distance>
composition: Target composition
distance: Maximum change an the fraction of any element in %.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
CompositionDistanceFilter()

Method Summary

Modifier and Type	Method and Description
static double	computeDistance(CompositionEntry entry1, CompositionEntry entry2, int p) Compute the distance between two entries.
boolean[]	label(Dataset D) Given a dataset, determine which entries passes the filter.
java.lang.String	printUsage() Print out required format for options.
void	setDistanceThreshold(double distance) Define the threshold composition distance.
void	setOptions(java.util.List<java.lang.Object> Options) Set any options for this object.
void	setTargetComposition(CompositionEntry composition) Define the target composition
void	train(Dataset TrainingSet) Train a dataset splitter, if necessary

Methods inherited from class magpie.data.utilities.filters.BaseDatasetFilter

filter, parallelLabel, parallelMinimum, setExclude, toExclude

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

CompositionDistanceFilter

public CompositionDistanceFilter()

Method Detail

computeDistance

public static double computeDistance(CompositionEntry entry1,
                                     CompositionEntry entry2,
                                     int p)

Compute the distance between two entries. Distance is defined as the L_p norm of the distance between the element fractions.

Parameters:

entry1 - Entry A

entry2 - Entry B

p - Desired L_p norm (must be ≥ 0)

Returns:

Distance

setOptions

public void setOptions(java.util.List<java.lang.Object> Options)
                throws java.lang.Exception

Description copied from interface: Options

Set any options for this object. If parsing the options fails, return an Exception with the usage as its message.

Parameters:

Options - Array of options as Objects - can be null

Throws:

java.lang.Exception - if problem with inputs

printUsage

public java.lang.String printUsage()

Description copied from interface: Options

Print out required format for options. For consistency, should start with "Usage: ".

Returns:

Usage for this function

setTargetComposition

public void setTargetComposition(CompositionEntry composition)

Define the target composition

Parameters:

composition - Target composition

setDistanceThreshold

public void setDistanceThreshold(double distance)

Define the threshold composition distance. Here, distance is defined as the maximum change in the fraction of any element.

Parameters:

distance - Target threshold in %

train

public void train(Dataset TrainingSet)

Description copied from class: BaseDatasetFilter

Train a dataset splitter, if necessary

Specified by:

train in class BaseDatasetFilter

Parameters:

TrainingSet - Dataset to use for training

label

public boolean[] label(Dataset D)

Description copied from class: BaseDatasetFilter

Given a dataset, determine which entries passes the filter. Please ensure that D remains unaltered (clone if you must)

Specified by:

label in class BaseDatasetFilter

Parameters:

D - Dataset to be labeled

Returns:

A list of booleans marking whether an entry passes