xlinear

Class MatrixOperations

java.lang.Object

xlinear.MatrixOperations

public class MatrixOperations
extends java.lang.Object

Method Summary

Modifier and Type	Method and Description
static DenseMatrix	dense(int nRows)
static DenseMatrix	dense(int nRows, int nCols)
static DenseMatrix	denseCopy(double[] data)
static DenseMatrix	denseCopy(double[][] data) Design note: we avoid copy(double [][] data) in a dispatch method because it then doesn't work with copy(#[#[1.2, 4.5]]) idiom (Xtend only translates #[..] to double [] if it can infer from static analysis)
static DenseMatrix	denseCopy(org.jblas.DoubleMatrix jblasMatrix)
static DenseMatrix	denseCopy(org.apache.commons.math3.linear.RealMatrix commonsMatrix)
static DenseMatrix	denseCopy(org.apache.commons.math3.linear.RealVector commonsMatrix)
static SparseMatrix	identity(int size)
static DenseMatrix	ones(int size)
static DenseMatrix	ones(int rows, int cols)
static DenseMatrix	sampleNormalByCovariance(java.util.Random random, CholeskyDecomposition covariance)
static DenseMatrix	sampleNormalByCovariance(java.util.Random random, Matrix covariance)
static DenseMatrix	sampleNormalByPrecision(java.util.Random random, CholeskyDecomposition precision)
static DenseMatrix	sampleNormalByPrecision(java.util.Random random, Matrix precision)
static DenseMatrix	sampleStandardNormal(java.util.Random random, int dim)
static SparseMatrix	sparse(int nRows)
static SparseMatrix	sparse(int nRows, int nCols)
static SparseMatrix	sparseCopy(double[] data)
static SparseMatrix	sparseCopy(double[][] data)
static DenseMatrix	standardNormalVector(java.util.Random random, int dim)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

dense

public static DenseMatrix dense(int nRows,
                                int nCols)

sparse

public static SparseMatrix sparse(int nRows,
                                  int nCols)

dense

public static DenseMatrix dense(int nRows)

sparse

public static SparseMatrix sparse(int nRows)

identity

public static SparseMatrix identity(int size)

ones

public static DenseMatrix ones(int rows,
                               int cols)

ones

public static DenseMatrix ones(int size)

denseCopy

public static DenseMatrix denseCopy(double[][] data)

Design note: we avoid copy(double [][] data) in a dispatch method because it then doesn't work with copy(#[#[1.2, 4.5]]) idiom (Xtend only translates #[..] to double [] if it can infer from static analysis)

denseCopy

public static DenseMatrix denseCopy(double[] data)

denseCopy

public static DenseMatrix denseCopy(org.jblas.DoubleMatrix jblasMatrix)

denseCopy

public static DenseMatrix denseCopy(org.apache.commons.math3.linear.RealMatrix commonsMatrix)

denseCopy

public static DenseMatrix denseCopy(org.apache.commons.math3.linear.RealVector commonsMatrix)

sparseCopy

public static SparseMatrix sparseCopy(double[][] data)

sparseCopy

public static SparseMatrix sparseCopy(double[] data)

standardNormalVector

public static DenseMatrix standardNormalVector(java.util.Random random,
                                               int dim)

sampleStandardNormal

public static DenseMatrix sampleStandardNormal(java.util.Random random,
                                               int dim)

sampleNormalByCovariance

public static DenseMatrix sampleNormalByCovariance(java.util.Random random,
                                                   Matrix covariance)

sampleNormalByCovariance

public static DenseMatrix sampleNormalByCovariance(java.util.Random random,
                                                   CholeskyDecomposition covariance)

sampleNormalByPrecision

public static DenseMatrix sampleNormalByPrecision(java.util.Random random,
                                                  Matrix precision)

sampleNormalByPrecision

public static DenseMatrix sampleNormalByPrecision(java.util.Random random,
                                                  CholeskyDecomposition precision)