本文整理了Java中gov.sandia.cognition.math.matrix.Vector.stack()
方法的一些代码示例,展示了Vector.stack()
的具体用法。这些代码示例主要来源于Github
/Stackoverflow
/Maven
等平台,是从一些精选项目中提取出来的代码,具有较强的参考意义,能在一定程度帮忙到你。Vector.stack()
方法的具体详情如下:
包路径:gov.sandia.cognition.math.matrix.Vector
类名称:Vector
方法名:stack
[英]Stacks "other" below "this" and returns the stacked Vector
[中]在“this”下面叠加“other”并返回叠加向量
代码示例来源:origin: gov.sandia.foundry/gov-sandia-cognition-learning-core
@Override
public Vector convertToVector()
{
Vector p = super.convertToVector();
return p.stack( this.getBias() );
}
代码示例来源:origin: gov.sandia.foundry/gov-sandia-cognition-common-core
public Vector convertToVector()
{
return this.getAutoRegressiveCoefficients().stack(
this.getMovingAverageCoefficients() );
}
代码示例来源:origin: gov.sandia.foundry/gov-sandia-cognition-learning-core
public Vector convertToVector()
{
Vector c = VectorFactory.getDefault().copyValues( this.covarianceDivisor );
c = c.stack( this.gaussian.getMean() );
return c.stack( this.inverseWishart.convertToVector() );
}
代码示例来源:origin: gov.sandia.foundry/gov-sandia-cognition-learning-core
@Override
public Vector convertToVector()
{
return this.mean.stack(this.getCovariance().convertToVector());
}
代码示例来源:origin: algorithmfoundry/Foundry
public Vector convertToVector()
{
Vector c = VectorFactory.getDefault().copyValues( this.covarianceDivisor );
c = c.stack( this.gaussian.getMean() );
return c.stack( this.inverseWishart.convertToVector() );
}
代码示例来源:origin: algorithmfoundry/Foundry
@Override
public Vector convertToVector()
{
return this.mean.stack(this.getCovariance().convertToVector());
}
代码示例来源:origin: algorithmfoundry/Foundry
@Override
public Vector convertToVector()
{
return this.mean.stack(this.getCovariance().convertToVector());
}
代码示例来源:origin: algorithmfoundry/Foundry
public Vector convertToVector()
{
Vector c = VectorFactory.getDefault().copyValues( this.covarianceDivisor );
c = c.stack( this.gaussian.getMean() );
return c.stack( this.inverseWishart.convertToVector() );
}
代码示例来源:origin: algorithmfoundry/Foundry
public Vector convertToVector()
{
return this.getAutoRegressiveCoefficients().stack(
this.getMovingAverageCoefficients() );
}
代码示例来源:origin: algorithmfoundry/Foundry
@Override
public Vector convertToVector()
{
Vector p = super.convertToVector();
return p.stack( this.getBias() );
}
代码示例来源:origin: gov.sandia.foundry/gov-sandia-cognition-learning-core
public Vector convertToVector()
{
Vector parameters = VectorFactory.getDefault().copyValues(
this.getDegreesOfFreedom() );
parameters = parameters.stack( this.getMean() );
parameters = parameters.stack( this.getPrecision().convertToVector() );
return parameters;
}
代码示例来源:origin: algorithmfoundry/Foundry
public Vector convertToVector()
{
Vector parameters = VectorFactory.getDefault().copyValues(
this.getDegreesOfFreedom() );
parameters = parameters.stack( this.getMean() );
parameters = parameters.stack( this.getPrecision().convertToVector() );
return parameters;
}
代码示例来源:origin: algorithmfoundry/Foundry
public Vector convertToVector()
{
Vector parameters = VectorFactory.getDefault().copyValues(
this.getDegreesOfFreedom() );
parameters = parameters.stack( this.getMean() );
parameters = parameters.stack( this.getPrecision().convertToVector() );
return parameters;
}
代码示例来源:origin: algorithmfoundry/Foundry
@Override
public Vector convertToVector()
{
return this.getGaussian().convertToVector().stack(
this.getInverseGamma().convertToVector() );
}
代码示例来源:origin: gov.sandia.foundry/gov-sandia-cognition-learning-core
@Override
public Vector convertToVector()
{
return this.getGaussian().convertToVector().stack(
this.getInverseGamma().convertToVector() );
}
代码示例来源:origin: gov.sandia.foundry/gov-sandia-cognition-text-core
@Override
protected void growVectors(
final int newDimensionality)
{
super.growVectors(newDimensionality);
this.termEntropiesSum = this.termEntropiesSum.stack(
this.getVectorFactory().createVector(
newDimensionality - this.termEntropiesSum.getDimensionality()));
}
代码示例来源:origin: algorithmfoundry/Foundry
@Override
protected void growVectors(
final int newDimensionality)
{
super.growVectors(newDimensionality);
this.termEntropiesSum = this.termEntropiesSum.stack(
this.getVectorFactory().createVector(
newDimensionality - this.termEntropiesSum.getDimensionality()));
}
代码示例来源:origin: gov.sandia.foundry/gov-sandia-cognition-learning-core
@Override
public Vector convertToVector()
{
Vector dof =
VectorFactory.getDefault().copyValues( this.getDegreesOfFreedom() );
Vector matrix = this.getInverseScale().convertToVector();
return dof.stack(matrix);
}
代码示例来源:origin: algorithmfoundry/Foundry
@Override
public Vector convertToVector()
{
Vector dof =
VectorFactory.getDefault().copyValues( this.getDegreesOfFreedom() );
Vector matrix = this.getInverseScale().convertToVector();
return dof.stack(matrix);
}
代码示例来源:origin: algorithmfoundry/Foundry
@Override
public Vector convertToVector()
{
Vector dof =
VectorFactory.getDefault().copyValues( this.getDegreesOfFreedom() );
Vector matrix = this.getInverseScale().convertToVector();
return dof.stack(matrix);
}
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