本文整理了Java中gov.sandia.cognition.math.matrix.Vector.assertDimensionalityEquals()方法的一些代码示例，展示了Vector.assertDimensionalityEquals()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.assertDimensionalityEquals()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：assertDimensionalityEquals

Vector.assertDimensionalityEquals介绍

[英]Asserts that the dimensionality of this vector equals the given dimensionality. If this assertion fails, a DimensionalityMismatchException is thrown.
[中]

代码示例

代码示例来源：origin: algorithmfoundry/Foundry

@Override
public void convertFromVector(
  final Vector parameters)
{
  parameters.assertDimensionalityEquals(0);
}

代码示例来源：origin: gov.sandia.foundry/gov-sandia-cognition-common-core

@Override
public void convertFromVector(
  final Vector parameters)
{
  parameters.assertDimensionalityEquals(1);
  this.value = parameters.getElement(0);
}

代码示例来源：origin: algorithmfoundry/Foundry

@Override
  public void convertFromVector(
    final Vector parameters)
  {
    parameters.assertDimensionalityEquals(1);
    this.value = (long) parameters.getElement(0);
  }
}

代码示例来源：origin: algorithmfoundry/Foundry

@Override
  public void convertFromVector(
    final Vector parameters)
  {
    parameters.assertDimensionalityEquals(1);
    this.value = (int) parameters.getElement(0);
  }
}

代码示例来源：origin: algorithmfoundry/Foundry

@Override
public void convertFromVector(
  final Vector parameters)
{
  parameters.assertDimensionalityEquals(1);
  this.value = parameters.getElement(0);
}

代码示例来源：origin: gov.sandia.foundry/gov-sandia-cognition-learning-core

@Override
public void convertFromVector(
  final Vector parameters)
{
  parameters.assertDimensionalityEquals(1);
  this.setRate( parameters.getElement(0) );
}

代码示例来源：origin: gov.sandia.foundry/gov-sandia-cognition-learning-core

@Override
public void convertFromVector(
  Vector parameters)
{
  parameters.assertDimensionalityEquals(1);
  this.setP( parameters.getElement(0) );
}

代码示例来源：origin: algorithmfoundry/Foundry

@Override
public void convertFromVector(
  final Vector parameters)
{
  parameters.assertDimensionalityEquals(2);
  final int a = (int) parameters.getElement(0);
  final int b = (int) parameters.getElement(1);
  this.setMinSupport(Math.min(a, b));
  this.setMaxSupport(Math.max(a, b));
}

代码示例来源：origin: gov.sandia.foundry/gov-sandia-cognition-learning-core

@Override
public void convertFromVector(
  final Vector parameters)
{
  parameters.assertDimensionalityEquals(2);
  this.setAlpha( parameters.getElement(0) );
  this.setNumCustomers( (int) Math.round( parameters.getElement(1) ) );
}

代码示例来源：origin: algorithmfoundry/Foundry

@Override
public void convertFromVector(
  final Vector parameters)
{
  parameters.assertDimensionalityEquals(2);
  this.setAlpha( parameters.getElement(0) );
  this.setNumCustomers( (int) Math.round( parameters.getElement(1) ) );
}

代码示例来源：origin: algorithmfoundry/Foundry

@Override
public void convertFromVector(
  final Vector parameters)
{
  parameters.assertDimensionalityEquals(2);
  this.setLocation( parameters.getElement(0) );
  this.setScale( parameters.getElement(1) );
}

代码示例来源：origin: algorithmfoundry/Foundry

@Override
public void convertFromVector(
  final Vector parameters)
{
  parameters.assertDimensionalityEquals(2);
  this.setMean( parameters.getElement(0) );
  this.setScale( parameters.getElement(1) );
}

代码示例来源：origin: gov.sandia.foundry/gov-sandia-cognition-learning-core

@Override
public void convertFromVector(
  final Vector parameters)
{
  parameters.assertDimensionalityEquals(2);
  this.setMean( parameters.getElement(0) );
  this.setScale( parameters.getElement(1) );
}

代码示例来源：origin: algorithmfoundry/Foundry

@Override
public void convertFromVector(
  Vector parameters)
{
  final int dim = this.getInputDimensionality() + 1;
  parameters.assertDimensionalityEquals( dim );
  this.setWeightVector( parameters.subVector(0, dim-2) );
  this.setBias( parameters.getElement(dim-1) );
}

代码示例来源：origin: gov.sandia.foundry/gov-sandia-cognition-learning-core

@Override
public void convertFromVector(
  Vector parameters)
{
  final int dim = this.getInputDimensionality() + 1;
  parameters.assertDimensionalityEquals( dim );
  this.setWeightVector( parameters.subVector(0, dim-2) );
  this.setBias( parameters.getElement(dim-1) );
}

代码示例来源：origin: gov.sandia.foundry/gov-sandia-cognition-learning-core

public void convertFromVector(
  Vector parameters)
{
  parameters.assertDimensionalityEquals(4);
  this.setLocation( parameters.getElement(0) );
  this.setPrecision( parameters.getElement(1) );
  this.setShape( parameters.getElement(2) );
  this.setScale( parameters.getElement(3) );
}

代码示例来源：origin: gov.sandia.foundry/gov-sandia-cognition-learning-core

@Override
public void convertFromVector(
  Vector parameters)
{
  final int num =
    this.getInputDimensionality() * this.getOutputDimensionality();
  parameters.assertDimensionalityEquals(num + this.getOutputDimensionality());
  Vector mp = parameters.subVector(0,num-1);
  Vector bp = parameters.subVector(num, num+this.getOutputDimensionality()-1);
  super.convertFromVector( mp );
  this.bias.convertFromVector(bp);
}

代码示例来源：origin: algorithmfoundry/Foundry

public void convertFromVector(
  Vector parameters)
{
  parameters.assertDimensionalityEquals(4);
  this.setLocation( parameters.getElement(0) );
  this.setPrecision( parameters.getElement(1) );
  this.setShape( parameters.getElement(2) );
  this.setScale( parameters.getElement(3) );
}

代码示例来源：origin: algorithmfoundry/Foundry

public void convertFromVector(
  Vector parameters)
{
  final int d = this.getInputDimensionality();
  parameters.assertDimensionalityEquals( 1+d + 1+d*d );
  this.setCovarianceDivisor( parameters.getElement(0) );
  Vector mean = parameters.subVector(1, d);
  this.gaussian.setMean(mean);
  Vector iwp = parameters.subVector(d+1, parameters.getDimensionality()-1);
  this.inverseWishart.convertFromVector(iwp);
}

代码示例来源：origin: algorithmfoundry/Foundry

@Override
public void convertFromVector(
  Vector parameters)
{
  final int num =
    this.getInputDimensionality() * this.getOutputDimensionality();
  parameters.assertDimensionalityEquals(num + this.getOutputDimensionality());
  Vector mp = parameters.subVector(0,num-1);
  Vector bp = parameters.subVector(num, num+this.getOutputDimensionality()-1);
  super.convertFromVector( mp );
  this.bias.convertFromVector(bp);
}