magpie.optimization.rankers

Class CompositionDistanceRanker

java.lang.Object

magpie.optimization.rankers.BaseEntryRanker

magpie.optimization.rankers.CompositionDistanceRanker

All Implemented Interfaces:

java.lang.Cloneable, Options

public class CompositionDistanceRanker
extends BaseEntryRanker

Rank entries based on distance from compositions in a user-provided dataset. Use this if, for instance, you are interested in materials not included in a training set.

Usage: <-manhanttan|-euclidean>
dataset: CompositionDataset containing all compositions being considered
-manhattan: Use Manhattan distance metric
-euclidean: Use Euclidean distance metric

See Also:

CompositionSetDistanceFilter

Constructor Summary

Constructors

Constructor and Description
CompositionDistanceRanker()

Method Summary

Modifier and Type	Method and Description
void	addComposition(CompositionEntry entry) Add a new composition to the dataset.
void	addCompositions(java.util.Collection<CompositionEntry> comps) Add a list of compositions to the set
void	clearCompositions() Clear the list of compositions in set
CompositionDistanceRanker	clone()
double	objectiveFunction(BaseEntry Entry) Some kind of objective function that returns a double when given an entry.
java.lang.String	printUsage() Print out required format for options.
void	setCompositions(CompositionDataset data) Set the list of compositions to be considered
void	setOptions(java.util.List<java.lang.Object> Options) Set any options for this object.
void	setUseManhattan(boolean manhattan) Set whether to use
void	train(Dataset data) Train ranker.

Methods inherited from class magpie.optimization.rankers.BaseEntryRanker

isMaximizing, isUsingMeasured, rankEntries, rankEntries, rankEntries, runObjectiveFunction, setMaximizeFunction, setUseMeasured, sortByRanking

Methods inherited from class java.lang.Object

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

Constructor Detail

CompositionDistanceRanker

public CompositionDistanceRanker()

Method Detail

clone

public CompositionDistanceRanker clone()

Overrides:

clone in class BaseEntryRanker

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

clearCompositions

public void clearCompositions()

Clear the list of compositions in set

addComposition

public void addComposition(CompositionEntry entry)

Add a new composition to the dataset.

Parameters:

entry - Entry to be added

addCompositions

public void addCompositions(java.util.Collection<CompositionEntry> comps)

Add a list of compositions to the set

Parameters:

comps - Collection of compositions to be added

setCompositions

public void setCompositions(CompositionDataset data)

Set the list of compositions to be considered

Parameters:

data - Dataset containing compositions to use as dataset

setUseManhattan

public void setUseManhattan(boolean manhattan)

Set whether to use

Parameters:

manhattan -

train

public void train(Dataset data)

Description copied from class: BaseEntryRanker

Train ranker.

Specified by:

train in class BaseEntryRanker

Parameters:

data - Data to use as training set

objectiveFunction

public double objectiveFunction(BaseEntry Entry)

Description copied from class: BaseEntryRanker

Some kind of objective function that returns a double when given an entry.

NOTE: This function needs to support using either the measured or predicted class depending on the settings

Specified by:

objectiveFunction in class BaseEntryRanker

Parameters:

Entry - Entry to be analyzed

Returns:

Evaluation of target function