gov.sandia.cognition.math.matrix
Interface Vectorizable

All Superinterfaces:
Cloneable, CloneableSerializable, Serializable
All Known Subinterfaces:
ClosedFormComputableDiscreteDistribution<DataType>, ClosedFormComputableDistribution<DataType>, ClosedFormCumulativeDistributionFunction<DomainType>, ClosedFormDiscreteUnivariateDistribution<DomainType>, ClosedFormDistribution<DataType>, ClosedFormUnivariateDistribution<NumberType>, DiagonalMatrix, DiscreteTimeFilter<StateType>, GradientDescendable, Matrix, ParameterGradientEvaluator<InputOutputType,GradientType>, ProbabilityDensityFunction<DataType>, Quaternion, SmoothCumulativeDistributionFunction, SmoothUnivariateDistribution, UnivariateProbabilityDensityFunction, Vector, Vector1D, Vector2D, Vector3D, VectorizableDifferentiableVectorFunction, VectorizableVectorFunction
All Known Implementing Classes:
AbstractClosedFormSmoothUnivariateDistribution, AbstractClosedFormUnivariateDistribution, AbstractMatrix, AbstractMTJMatrix, AbstractMTJVector, AbstractSparseMatrix, AbstractVector, AtanFunction, AutoRegressiveMovingAverageFilter, BernoulliDistribution, BernoulliDistribution.CDF, BernoulliDistribution.PMF, BetaBinomialDistribution, BetaBinomialDistribution.CDF, BetaBinomialDistribution.PMF, BetaDistribution, BetaDistribution.CDF, BetaDistribution.PDF, BinomialDistribution, BinomialDistribution.CDF, BinomialDistribution.PMF, CategoricalDistribution, CategoricalDistribution.PMF, CauchyDistribution, CauchyDistribution.CDF, CauchyDistribution.PDF, ChineseRestaurantProcess, ChineseRestaurantProcess.PMF, ChiSquareDistribution, ChiSquareDistribution.CDF, ChiSquareDistribution.PDF, CosineFunction, DenseMatrix, DenseVector, DeterministicDistribution, DeterministicDistribution.CDF, DeterministicDistribution.PMF, DiagonalMatrixMTJ, DifferentiableFeedforwardNeuralNetwork, DifferentiableGeneralizedLinearModel, DirichletDistribution, DirichletDistribution.PDF, ExponentialDistribution, ExponentialDistribution.CDF, ExponentialDistribution.PDF, FeedforwardNeuralNetwork, GammaDistribution, GammaDistribution.CDF, GammaDistribution.PDF, GeneralizedLinearModel, GeometricDistribution, GeometricDistribution.CDF, GeometricDistribution.PMF, GradientDescendableApproximator, InverseGammaDistribution, InverseGammaDistribution.CDF, InverseGammaDistribution.PDF, InverseWishartDistribution, InverseWishartDistribution.PDF, KolmogorovDistribution, KolmogorovDistribution.CDF, LaplaceDistribution, LaplaceDistribution.CDF, LaplaceDistribution.PDF, LinearCombinationFunction, LinearCombinationScalarFunction, LinearCombinationVectorFunction, LinearDiscriminant, LinearDiscriminantWithBias, LinearDynamicalSystem, LogisticDistribution, LogisticDistribution.CDF, LogisticDistribution.PDF, LogisticRegression.Function, LogNormalDistribution, LogNormalDistribution.CDF, LogNormalDistribution.PDF, MixtureOfGaussians.PDF, MovingAverageFilter, MultinomialDistribution, MultinomialDistribution.PMF, MultivariateDiscriminant, MultivariateDiscriminantWithBias, MultivariateGaussian, MultivariateGaussian.PDF, MultivariateGaussianInverseGammaDistribution, MultivariateMixtureDensityModel, MultivariateMixtureDensityModel.PDF, MultivariatePolyaDistribution, MultivariatePolyaDistribution.PMF, MultivariateStudentTDistribution, MultivariateStudentTDistribution.PDF, MutableDouble, MutableInteger, MutableLong, NegativeBinomialDistribution, NegativeBinomialDistribution.CDF, NegativeBinomialDistribution.PMF, NormalInverseGammaDistribution, NormalInverseGammaDistribution.PDF, NormalInverseWishartDistribution, NormalInverseWishartDistribution.PDF, ParetoDistribution, ParetoDistribution.CDF, ParetoDistribution.PDF, PoissonDistribution, PoissonDistribution.CDF, PoissonDistribution.PMF, PolynomialFunction, ScalarMixtureDensityModel, ScalarMixtureDensityModel.CDF, ScalarMixtureDensityModel.PDF, ScalarThresholdBinaryCategorizer, SnedecorFDistribution, SnedecorFDistribution.CDF, SparseColumnMatrix, SparseMatrix, SparseRowMatrix, SparseVector, StudentizedRangeDistribution, StudentizedRangeDistribution.CDF, StudentTDistribution, StudentTDistribution.CDF, StudentTDistribution.PDF, ThreeLayerFeedforwardNeuralNetwork, ThresholdFunction, UniformDistribution, UniformDistribution.CDF, UniformDistribution.PDF, UnivariateGaussian, UnivariateGaussian.CDF, UnivariateGaussian.CDF.Inverse, UnivariateGaussian.PDF, Vector1, Vector2, Vector3, VectorEntryFunction, VectorFunctionLinearDiscriminant, WeibullDistribution, WeibullDistribution.CDF, WeibullDistribution.PDF, YuleSimonDistribution, YuleSimonDistribution.CDF, YuleSimonDistribution.PMF

@CodeReview(reviewer="Jonathan McClain",
            date="2006-05-17",
            changesNeeded=false,
            comments="Looks fine.")
public interface Vectorizable
extends CloneableSerializable

The Vectorizable interface is an interface for an object that can be converted to and from a Vector.

Since:
1.0
Author:
Justin Basilico, Kevin R. Dixon

Method Summary
 Vectorizable clone()
          Creates a new clone (shallow copy) of this object.
 void convertFromVector(Vector parameters)
          Converts the object from a Vector of parameters.
 Vector convertToVector()
          Converts the object to a vector.
 

Method Detail

clone

Vectorizable clone()
Description copied from interface: CloneableSerializable
Creates a new clone (shallow copy) of this object.

Specified by:
clone in interface CloneableSerializable
Returns:
A new clone (shallow copy) of this object.

convertToVector

Vector convertToVector()
Converts the object to a vector.

Returns:
The Vector form of the object.

convertFromVector

void convertFromVector(Vector parameters)
Converts the object from a Vector of parameters.

Parameters:
parameters - The parameters to incorporate.