Class DoubleVectorValueObject
- java.lang.Object
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- ubic.gemma.model.common.IdentifiableValueObject<DataVector>
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- ubic.gemma.model.expression.bioAssayData.DataVectorValueObject
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- ubic.gemma.model.expression.bioAssayData.DoubleVectorValueObject
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- All Implemented Interfaces:
Serializable
,Identifiable
- Direct Known Subclasses:
SlicedDoubleVectorValueObject
public class DoubleVectorValueObject extends DataVectorValueObject
Value object for aBulkExpressionDataVector
containing doubles.- Author:
- paul
- See Also:
- Serialized Form
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Field Summary
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Fields inherited from class ubic.gemma.model.common.IdentifiableValueObject
id
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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.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description DoubleVectorValueObject
copy()
Create a copy of this vector.boolean
equals(Object obj)
int
hashCode()
SlicedDoubleVectorValueObject
slice(ExpressionExperimentSubsetValueObject subset, BioAssayDimensionValueObject bad)
Crate a vector that is a slice of this one.double[]
standardize()
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Methods inherited from class ubic.gemma.model.expression.bioAssayData.DataVectorValueObject
getBioAssays, toString
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Methods inherited from class ubic.gemma.model.common.IdentifiableValueObject
getId, setId
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Constructor Detail
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DoubleVectorValueObject
public DoubleVectorValueObject()
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DoubleVectorValueObject
public DoubleVectorValueObject(BulkExpressionDataVector dedv, ExpressionExperimentValueObject eevo, QuantitationTypeValueObject qtvo, BioAssayDimensionValueObject badVo, ArrayDesignValueObject advo, @Nullable Collection<Long> genes)
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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:
dimToMatch
- ensure that the vector missing values to match the locations of any bioassays in dimToMatch that aren't in the dedv's bioAssayDimension.dedv
- dedveevo
- a VO for the experimentqtvo
- a VO for the quantitation typevectorsBadVo
- BA dimension vogenes
- a collection of gene IDs that correspond to the design element of this vector, or null to ignoredimToMatch
- a dimension that the data should be aligned with, this will result in "gaps" where the provided vector is lacking assays
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DoubleVectorValueObject
protected DoubleVectorValueObject(DoubleVectorValueObject dvvo)
Copy constructor.
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Method Detail
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equals
public boolean equals(Object obj)
- Overrides:
equals
in classDataVectorValueObject
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hashCode
public int hashCode()
- Overrides:
hashCode
in classDataVectorValueObject
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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.
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slice
public SlicedDoubleVectorValueObject slice(ExpressionExperimentSubsetValueObject subset, BioAssayDimensionValueObject bad)
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 slicingbad
- all we nee is the id, the name and the list of bioassays from this.S
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standardize
public double[] standardize()
- Returns:
- data adjusted to mean 0, variance 1.
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