Package ubic.gemma.model.expression.bioAssayData

Class DoubleVectorValueObject

java.lang.Object

ubic.gemma.model.common.IdentifiableValueObject<DataVector>

ubic.gemma.model.expression.bioAssayData.DataVectorValueObject

ubic.gemma.model.expression.bioAssayData.DoubleVectorValueObject

All Implemented Interfaces:

Serializable, Identifiable

Direct Known Subclasses:

SlicedDoubleVectorValueObject

public class DoubleVectorValueObject
extends DataVectorValueObject

Value object for a BulkExpressionDataVector containing doubles.

Author:

paul

See Also:

• Serialized Form

Field Summary

Fields inherited from class ubic.gemma.model.common.IdentifiableValueObject

id

Constructor Summary

Constructors

Modifier	Constructor	Description
	DoubleVectorValueObject()
	DoubleVectorValueObject(BulkExpressionDataVector dedv, ExpressionExperimentValueObject eevo, QuantitationTypeValueObject qtvo, BioAssayDimensionValueObject badVo, ArrayDesignValueObject advo, Collection<Long> genes)
	DoubleVectorValueObject(BulkExpressionDataVector dedv, ExpressionExperimentValueObject eevo, QuantitationTypeValueObject qtvo, BioAssayDimensionValueObject vectorsBadVo, ArrayDesignValueObject advo, Collection<Long> genes, BioAssayDimensionValueObject dimToMatch)	Create a vector where we expect to have to create one or more gaps to match other vectors, defined by dimToMatch.
protected	DoubleVectorValueObject(DoubleVectorValueObject dvvo)	Copy constructor.

Method Summary

Modifier and Type	Method	Description
DoubleVectorValueObject	copy()	Create a copy of this vector.
boolean	equals(Object obj)
double[]	getData()	The data of this vector.
int[]	getNumberOfCells()
Double	getPvalue()	If this vector is associated to a statistical test (i.e.
Double	getRank()
Double	getRankByMax()
Double	getRankByMean()
int	hashCode()
boolean	isMasked()	Indicate if this vector is "masked", i.e.
boolean	isReorganized()	True if the data has been rearranged relative to the bioassay dimension (as a matter of practice the bioassay dimension should be set to null if it is not valid; this boolean is an additional check)
void	setData(double[] data)	The data of this vector.
void	setMasked(boolean masked)	Indicate if this vector is "masked", i.e.
void	setNumberOfCells(int[] numberOfCells)
void	setPvalue(Double pvalue)	If this vector is associated to a statistical test (i.e.
void	setRank(Double rank)
void	setRankByMax(Double rankByMax)
void	setRankByMean(Double rankByMean)
void	setReorganized(boolean reorganized)	True if the data has been rearranged relative to the bioassay dimension (as a matter of practice the bioassay dimension should be set to null if it is not valid; this boolean is an additional check)
SlicedDoubleVectorValueObject	slice(ExpressionExperimentSubsetValueObject subset, BioAssayDimensionValueObject slicedBad)
SlicedDoubleVectorValueObject	slice(ExpressionExperimentSubsetValueObject subset, BioAssayDimensionValueObject slicedBad, int[] bioAssayIndex)	Crate a vector that is a slice of this one.
double[]	standardize()
String	toString()

Methods inherited from class ubic.gemma.model.expression.bioAssayData.DataVectorValueObject

getBioAssayDimension, getBioAssays, getDesignElement, getExpressionExperiment, getGenes, getQuantitationType, setBioAssayDimension, setDesignElement, setExpressionExperiment, setGenes, setQuantitationType

Methods inherited from class ubic.gemma.model.common.IdentifiableValueObject

canEqual, getId, setId

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Details

DoubleVectorValueObject

public DoubleVectorValueObject()

DoubleVectorValueObject

public DoubleVectorValueObject(BulkExpressionDataVector dedv,
 ExpressionExperimentValueObject eevo,
 QuantitationTypeValueObject qtvo,
 BioAssayDimensionValueObject badVo,
 ArrayDesignValueObject advo,
 @Nullable
 Collection<Long> genes)

See Also:

• DoubleVectorValueObject(BulkExpressionDataVector, ExpressionExperimentValueObject, QuantitationTypeValueObject, BioAssayDimensionValueObject, ArrayDesignValueObject, Collection)

DoubleVectorValueObject

public DoubleVectorValueObject(BulkExpressionDataVector dedv,
 ExpressionExperimentValueObject eevo,
 QuantitationTypeValueObject qtvo,
 BioAssayDimensionValueObject vectorsBadVo,
 ArrayDesignValueObject advo,
 @Nullable
 Collection<Long> genes,
 BioAssayDimensionValueObject dimToMatch)

Create a vector where we expect to have to create one or more gaps to match other vectors, defined by dimToMatch.

Parameters:

dedv - dedv

eevo - a VO for the experiment

qtvo - a VO for the quantitation type

vectorsBadVo - BA dimension vo

genes - a collection of gene IDs that correspond to the design element of this vector, or null to ignore

dimToMatch - ensure that the vector missing values to match the locations of any bioassays in dimToMatch that aren't in the dedv's bioAssayDimension. This will result in "gaps" where the provided vector is lacking assays.

DoubleVectorValueObject

protected DoubleVectorValueObject(DoubleVectorValueObject dvvo)

Copy constructor.

Method Details

equals

public boolean equals(Object obj)

Overrides:

equals in class DataVectorValueObject

hashCode

public int hashCode()

Overrides:

hashCode in class DataVectorValueObject

copy

public DoubleVectorValueObject copy()

Create a copy of this vector.

Use this if you intend to modify it as the original might be stored in a shared cache.

slice

public SlicedDoubleVectorValueObject slice(ExpressionExperimentSubsetValueObject subset,
 BioAssayDimensionValueObject slicedBad)

slice

public SlicedDoubleVectorValueObject slice(ExpressionExperimentSubsetValueObject subset,
 BioAssayDimensionValueObject slicedBad,
 int[] bioAssayIndex)

Crate a vector that is a slice of this one.

Create a vector that is a slice of another one. The bioassays chosen are as given in the supplied bioassay dimension.

Parameters:

subset - a subset by which we are slicing

slicedBad - all we need is the id, the name and the list of bioassays from this.

bioAssayIndex - position of each sliced bioassay in the original vector's dimension to avoid costly recomputation

standardize

public double[] standardize()

Returns:

data adjusted to mean 0, variance 1.

getData

public double[] getData()

The data of this vector.

getNumberOfCells

@Nullable
public int[] getNumberOfCells()

isMasked

public boolean isMasked()

Indicate if this vector is "masked", i.e. it is processed.

isReorganized

public boolean isReorganized()

True if the data has been rearranged relative to the bioassay dimension (as a matter of practice the bioassay dimension should be set to null if it is not valid; this boolean is an additional check)

getRank

public Double getRank()

getRankByMax

public Double getRankByMax()

getRankByMean

public Double getRankByMean()

getPvalue

@Nullable
public Double getPvalue()

If this vector is associated to a statistical test (i.e. from a DE analysis), this is the P-value.

setData

public void setData(double[] data)

The data of this vector.

setNumberOfCells

public void setNumberOfCells(@Nullable
 int[] numberOfCells)

setMasked

public void setMasked(boolean masked)

Indicate if this vector is "masked", i.e. it is processed.

setReorganized

public void setReorganized(boolean reorganized)

True if the data has been rearranged relative to the bioassay dimension (as a matter of practice the bioassay dimension should be set to null if it is not valid; this boolean is an additional check)

setRank

public void setRank(Double rank)

setRankByMax

public void setRankByMax(Double rankByMax)

setRankByMean

public void setRankByMean(Double rankByMean)

setPvalue

public void setPvalue(@Nullable
 Double pvalue)

If this vector is associated to a statistical test (i.e. from a DE analysis), this is the P-value.

toString

public String toString()

Overrides:

toString in class DataVectorValueObject