org.expasy.mzjava.core.ms.spectrasim

Class DpSimFunc<X extends PeakAnnotation,Y extends PeakAnnotation>

java.lang.Object

org.expasy.mzjava.core.ms.spectrasim.AbstractSimFunc<X,Y>

org.expasy.mzjava.core.ms.spectrasim.DpSimFunc<X,Y>

All Implemented Interfaces:

PeakPairSink<X,Y>, SimFunc<X,Y>

public class DpSimFunc<X extends PeakAnnotation,Y extends PeakAnnotation>
extends AbstractSimFunc<X,Y>

Calculates the similarity between two PeakLists using the dot product (dp). A minimum peak count can be set so that NaN is returned for peak list pairs that do not have enough peaks to calculate a reliable dp.

Version:

1.0

Author:

Oliver Horlacher

Constructor Summary

Constructors

Constructor and Description
DpSimFunc(int minPeakCount, PeakListAligner<X,Y> peakListAligner, PeakPairProcessor<X,Y>... chain) Construct a NdpSimFunc that uses the supplied PeakListAligner and PeakPairProcessor chain to process and align the peak lists.
DpSimFunc(int minPeakCount, Tolerance tolerance) Construct a NdpSimFunc that uses the default peak list aligner.

Method Summary

Methods

Modifier and Type	Method and Description
double	calcSimilarity(PeakList<X> plX, PeakList<Y> plY) Calculate the similarity score of the two vectors.
double	getBestScore() Return the best score that can be returned by calls to calcSimilarity.
int	getTotalPeakCount() Returns the total number peaks in plX and plY from the last call to calcSimilarity
double	getWorstScore() Return the worst the score that can be returned by calls to calcSimilarity.
void	processPeakPair(double centroid, double xIntensity, double yIntensity, List<X> xAnnotations, List<Y> yAnnotations) Pushes the next peak pair to this sink

Methods inherited from class org.expasy.mzjava.core.ms.spectrasim.AbstractSimFunc

begin, end, vectorize

Methods inherited from class java.lang.Object

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

Constructor Detail

DpSimFunc

public DpSimFunc(int minPeakCount,
         Tolerance tolerance)

Construct a NdpSimFunc that uses the default peak list aligner.

Parameters:

minPeakCount - the minimum number of peaks that are required in order to calculate the similarity

tolerance - the tolerance to use when aligning the two PeakLists

DpSimFunc

public DpSimFunc(int minPeakCount,
         PeakListAligner<X,Y> peakListAligner,
         PeakPairProcessor<X,Y>... chain)

Construct a NdpSimFunc that uses the supplied PeakListAligner and PeakPairProcessor chain to process and align the peak lists.

Parameters:

minPeakCount - the minimum number of peaks that are required in order to calculate the ndp

peakListAligner - the object that is used to allign the PeakList pairs

chain - PeakPairProcessor chain that is used to pre-process the aligned peaks before calculating the similarity

Method Detail

calcSimilarity

public double calcSimilarity(PeakList<X> plX,
                    PeakList<Y> plY)

Description copied from interface: SimFunc

Calculate the similarity score of the two vectors. Returns the similarity score or NaN if the score cannot be calculated

Parameters:

plX - the fist peak list

plY - the second peak list

Returns:

the similarity score or NaN if the score cannot be calculated

getTotalPeakCount

public int getTotalPeakCount()

Description copied from interface: SimFunc

Returns the total number peaks in plX and plY from the last call to calcSimilarity

Returns:

the total number peaks in plX and plY from the last call to calcSimilarity

processPeakPair

public void processPeakPair(double centroid,
                   double xIntensity,
                   double yIntensity,
                   List<X> xAnnotations,
                   List<Y> yAnnotations)

Description copied from interface: PeakPairSink

Pushes the next peak pair to this sink

Parameters:

centroid - the m/z

xIntensity - the intensity of the first peak

yIntensity - the intensity of the second peak

xAnnotations - the annotations for the first peak

yAnnotations - the annotations for the second peak

getBestScore

public double getBestScore()

Description copied from interface: SimFunc

Return the best score that can be returned by calls to calcSimilarity. For similarity functions for which the best score has no upper limit Double.POSITIVE_INFINITY is returned and where the best score has no lower limit Double.NEGATIVE_INFINITY is returned.

Returns:

the best score that can be returned by calls to calcSimilarity

getWorstScore

public double getWorstScore()

Description copied from interface: SimFunc

Return the worst the score that can be returned by calls to calcSimilarity. For similarity functions for which the worst score has no upper limit Double.POSITIVE_INFINITY is returned and where the worst score has no lower limit Double.NEGATIVE_INFINITY is returned.

Returns:

the worst score that can be returned by calls to calcSimilarity