java.lang.Object
- elki.math.linearalgebra.VMath

```
@Title("Vector and Matrix Math Library")
public final class VMath
extends java.lang.Object
```
Class providing basic vector mathematics, for low-level vectors stored as double[]. While this is less nice syntactically, it reduces memory usage and VM overhead.

Since:

0.5.0

Author:

Erich Schubert

Field Summary

Fields
Modifier and Type	Field	Description
`private static double`	`DELTA`	A small number to handle numbers near 0 as 0.
`protected static java.lang.String`	`ERR_DIMENSIONS`	Error message when dimensionalities do not agree.
`protected static java.lang.String`	`ERR_INVALID_RANGE`	Error message when min > max is given as a range.
`protected static java.lang.String`	`ERR_MATRIX_DIMENSIONS`	Error message when matrix dimensionalities do not agree.
`protected static java.lang.String`	`ERR_MATRIX_INNERDIM`	Error message when matrix dimensionalities do not agree.
`protected static java.lang.String`	`ERR_MATRIX_NONSQUARE`	Error when a non-square matrix is used with determinant.
`protected static java.lang.String`	`ERR_MATRIX_NOT_SPD`	When a symmetric positive definite matrix is required.
`protected static java.lang.String`	`ERR_MATRIX_RANK_DEFICIENT`	When a matrix is rank deficient.
`protected static java.lang.String`	`ERR_SINGULAR`	Error with a singular matrix.
`protected static java.lang.String`	`ERR_VEC_DIMENSIONS`	Error message when vector dimensionalities do not agree.

Constructor Summary

Constructors
Modifier Constructor Description

private VMath()
Fake constructor.

Method Summary

All Methods Static Methods Concrete Methods Deprecated Methods
Modifier and Type	Method	Description
`static boolean`	`almostEquals(double[][] m1, double[][] m2)`	Compare two matrices with a delta parameter to take numerical errors into account.
`static boolean`	`almostEquals(double[][] m1, double[][] m2, double maxdelta)`	Compare two matrices with a delta parameter to take numerical errors into account.
`static boolean`	`almostEquals(double[] m1, double[] m2)`	Compare two matrices with a delta parameter to take numerical errors into account.
`static boolean`	`almostEquals(double[] m1, double[] m2, double maxdelta)`	Compare two matrices with a delta parameter to take numerical errors into account.
`static double`	`angle(double[] v1, double[] v2)`	Compute the cosine of the angle between two vectors, where the smaller angle between those vectors is viewed.
`static double`	`angle(double[] v1, double[] v2, double[] o)`	Compute the cosine of the angle between two vectors, where the smaller angle between those vectors is viewed.
`static double[][]`	`appendColumns(double[][] m1, double[][] m2)`	Returns a matrix which consists of this matrix and the specified columns.
`static int`	`argmax(double[] v)`	Find the maximum value.
`static int`	`argmax(double[] v, int start, int end)`	Find the maximum value.
`static int`	`argmin(double[] v)`	Find the minimum value.
`static int`	`argmin(double[] v, int start, int end)`	Find the minimum value.
`static void`	`clear(double[] v1)`	Reset the vector to 0.
`static void`	`clear(double[][] m)`	Reset the matrix to 0.
`static double[]`	`columnPackedCopy(double[][] m1)`	Make a one-dimensional column packed copy of the internal array.
`static double[]`	`copy(double[] v)`	Returns a copy of this vector.
`static double[][]`	`copy(double[][] m1)`	Make a deep copy of a matrix.
`static double[][]`	`diagonal(double[] v1)`	Returns a quadratic matrix consisting of zeros and of the given values on the diagonal.
`static double`	`dot(double[] v1, double[] v2)`	Returns the dot product (scalar product) of two vectors, v1·v2 = v1^T v2.
`static boolean`	`equals(double[][] m1, double[][] m2)`	Test for equality
`static boolean`	`equals(double[] v1, double[] v2)`	Compare for equality.
`static double`	`euclideanLength(double[] v1)`	Euclidean length of the vector sqrt(v1^T v1).
`static double[]`	`getCol(double[][] m1, int col)`	Get a column from a matrix as vector.
`static int`	`getColumnDimensionality(double[][] m1)`	Returns the dimensionality of the columns of this matrix.
`static double[]`	`getDiagonal(double[][] m1)`	getDiagonal returns array of diagonal-elements.
`static double[][]`	`getMatrix(double[][] m1, int[] r, int[] c)`	Get a submatrix.
`static double[][]`	`getMatrix(double[][] m1, int[] r, int c0, int c1)`	Get a submatrix.
`static double[][]`	`getMatrix(double[][] m1, int r0, int r1, int[] c)`	Get a submatrix.
`static double[][]`	`getMatrix(double[][] m1, int r0, int r1, int c0, int c1)`	Get a submatrix.
`static double[]`	`getRow(double[][] m1, int r)`	Returns the `r`th row of this matrix as vector.
`static int`	`getRowDimensionality(double[][] m1)`	Returns the dimensionality of the rows of this matrix.
`static int`	`hashCode(double[] v1)`	Compute the hash code for the vector.
`static int`	`hashCode(double[][] m1)`	Compute hash code
`static double[][]`	`identity(int m, int n)`	Generate unit / identity / "eye" matrix.
`static double[][]`	`inverse(double[][] A)`	Matrix inverse or pseudoinverse
`static double`	`mahalanobisDistance(double[][] B, double[] a, double[] c)`	Matrix multiplication, (a-c)^T * B * (a-c)
`static double[][]`	`minus(double[][] m1, double[][] m2)`	Component-wise matrix subtraction m3 = m1 - m2.
`static double[]`	`minus(double[] v1, double s1)`	Subtract component-wise v1 - s1.
`static double[]`	`minus(double[] v1, double[] v2)`	Computes component-wise v1 - v2.
`static double[][]`	`minusEquals(double[][] m1, double[][] m2)`	Component-wise matrix subtraction: m1 = m1 - m2, overwriting the existing matrix m1.
`static double[]`	`minusEquals(double[] v1, double s1)`	Subtract component-wise in-place v1 = v1 - s1, overwriting the vector v1.
`static double[]`	`minusEquals(double[] v1, double[] v2)`	Computes component-wise v1 = v1 - v2, overwriting the vector v1.
`static double[][]`	`minusTimes(double[][] m1, double[][] m2, double s2)`	Component-wise matrix operation: m3 = m1 - m2 * s2
`static double[]`	`minusTimes(double[] v1, double[] v2, double s2)`	Computes component-wise v1 - v2 * s2.
`static double[][]`	`minusTimesEquals(double[][] m1, double[][] m2, double s2)`	Component-wise matrix operation: m1 = m1 - m2 * s2, overwriting the existing matrix m1.
`static double[]`	`minusTimesEquals(double[] v1, double[] v2, double s2)`	Computes component-wise v1 = v1 - v2 * s2, overwriting the vector v1.
`static double[]`	`normalize(double[] v1)`	Normalizes v1 to the length of 1.0.
`static void`	`normalizeColumns(double[][] m1)`	Normalizes the columns of this matrix to length of 1.0.
`static double[]`	`normalizeEquals(double[] v1)`	Normalizes v1 to the length of 1.0 in place.
`static double`	`normF(double[][] elements)`	Frobenius norm
`static double[][]`	`orthonormalize(double[][] m1)`	Returns an orthonormalization of this matrix.
`static double[]`	`overwriteTimes(double[] v1, double[] v2, double s)`	Multiply component-wise v1 = v2 * s, overwriting the vector v1.
`static double[][]`	`plus(double[][] m1, double[][] m2)`	Component-wise matrix sum: m3 = m1 + m2.
`static double[]`	`plus(double[] v1, double s1)`	Computes component-wise v1 + s1.
`static double[]`	`plus(double[] v1, double[] v2)`	Computes component-wise v1 + v2 for vectors.
`static double[][]`	`plusEquals(double[][] m1, double[][] m2)`	Component-wise matrix operation: m1 = m1 + m2, overwriting the existing matrix m1.
`static double[]`	`plusEquals(double[] v1, double s1)`	Computes component-wise v1 = v1 + s1, overwriting the vector v1.
`static double[]`	`plusEquals(double[] v1, double[] v2)`	Computes component-wise v1 = v1 + v2, overwriting the vector v1.
`static double[][]`	`plusTimes(double[][] m1, double[][] m2, double s2)`	Component-wise matrix operation: m3 = m1 + m2 * s2.
`static double[]`	`plusTimes(double[] v1, double[] v2, double s2)`	Computes component-wise v1 + v2 * s2.
`static double[][]`	`plusTimesEquals(double[][] m1, double[][] m2, double s2)`	Component-wise matrix operation: m1 = m1 + m2 * s2, overwriting the existing matrix m1.
`static double[]`	`plusTimesEquals(double[] v1, double[] v2, double s2)`	Computes component-wise v1 = v1 + v2 * s2, overwriting the vector v1.
`static double[]`	`rotate90Equals(double[] v1)`	Rotate the two-dimensional vector by 90 degrees.
`static double[]`	`rowPackedCopy(double[][] m1)`	Make a one-dimensional row packed copy of the internal array.
`static double`	`scalarProduct(double[] v1, double[] v2)`	Returns the scalar product (dot product) of two vectors, <v1,v2> = v1^T v2.
`static void`	`setCol(double[][] m1, int c, double[] column)`	Sets the `c`th column of this matrix to the specified column.
`static void`	`setMatrix(double[][] m1, int[] r, int[] c, double[][] m2)`	Set a submatrix.
`static void`	`setMatrix(double[][] m1, int[] r, int c0, int c1, double[][] m2)`	Set a submatrix.
`static void`	`setMatrix(double[][] m1, int r0, int r1, int[] c, double[][] m2)`	Set a submatrix.
`static void`	`setMatrix(double[][] m1, int r0, int r1, int c0, int c1, double[][] m2)`	Set a submatrix.
`static void`	`setRow(double[][] m1, int r, double[] row)`	Sets the `r`th row of this matrix to the specified vector.
`static double[]`	`solve(double[][] A, double[] b)`	Solve A*X = b
`static double[][]`	`solve(double[][] A, double[][] B)`	Solve A*X = B
`static double`	`squareSum(double[] v1)`	Squared Euclidean length of the vector v1^T v1 = v1·v1.
`static double`	`sum(double[] v1)`	Sum of the vector components.
`static double[][]`	`times(double[][] m1, double s1)`	Multiply a matrix by a scalar component-wise, m3 = m1 * s1.
`static double[]`	`times(double[][] m1, double[] v2)`	Matrix with vector multiplication, m1 * v2.
`static double[][]`	`times(double[][] m1, double[][] m2)`	Matrix multiplication, m1 * m2.
`static double[]`	`times(double[] v1, double s1)`	Multiply component-wise v1 * s1.
`static double[][]`	`times(double[] v1, double[][] m2)`	Deprecated. this is fairly inefficient memory layout, rewriting your code
`static double[][]`	`timesEquals(double[][] m1, double s1)`	Multiply a matrix by a scalar component-wise in place, m1 = m1 * s1, overwriting the existing matrix m1.
`static double[]`	`timesEquals(double[] v1, double s)`	Multiply component-wise v1 = v1 * s1, overwriting the vector v1.
`static double[]`	`timesMinus(double[] v1, double s1, double[] v2)`	Computes component-wise v1 * s1 - v2.
`static double[]`	`timesMinusEquals(double[] v1, double s1, double[] v2)`	Computes component-wise v1 = v1 * s1 - v2, overwriting the vector v1.
`static double[]`	`timesMinusTimes(double[] v1, double s1, double[] v2, double s2)`	Computes component-wise v1 * s1 - v2 * s2.
`static double[]`	`timesMinusTimesEquals(double[] v1, double s1, double[] v2, double s2)`	Computes component-wise v1 = v1 * s1 - v2 * s2, overwriting the vector v1.
`static double[]`	`timesPlus(double[] v1, double s1, double[] v2)`	Computes component-wise v1 * s1 + v2.
`static double[]`	`timesPlusEquals(double[] v1, double s1, double[] v2)`	Computes component-wise v1 = v1 * s1 + v2, overwriting the vector v1.
`static double[]`	`timesPlusTimes(double[] v1, double s1, double[] v2, double s2)`	Computes component-wise v1 * s1 + v2 * s2.
`static double[]`	`timesPlusTimesEquals(double[] v1, double s1, double[] v2, double s2)`	Computes component-wise v1 = v1 * s1 + v2 * s2, overwriting the vector v1.
`static double[][]`	`timesTranspose(double[][] m1, double[][] m2)`	Matrix multiplication, m1 * m2^T
`static double[][]`	`timesTranspose(double[] v1, double[] v2)`	Vectors to matrix multiplication, v1 * v2^T.
`static double[][]`	`timesTranspose(double[] v1, double[][] m2)`	Deprecated. this is fairly inefficient memory layout, rewriting your code
`static double[][]`	`transpose(double[] v)`	Transpose vector to a matrix without copying.
`static double[][]`	`transpose(double[][] m1)`	Matrix transpose
`static double[][]`	`transposeDiagonalTimes(double[][] m1, double[] d2, double[][] m3)`	Matrix multiplication with diagonal, m1^T * d2 * m3
`static double[]`	`transposeTimes(double[][] m1, double[] v2)`	Transposed matrix with vector multiplication, m1^T * v2
`static double[][]`	`transposeTimes(double[][] m1, double[][] m2)`	Matrix multiplication, m1^T * m2
`static double`	`transposeTimes(double[] v1, double[] v2)`	Vector scalar product (dot product), v1^T v2 = v1·v2 = <v1,v2>.
`static double[][]`	`transposeTimes(double[] v1, double[][] m2)`	Vector to matrix multiplication, v1^T m2.
`static double`	`transposeTimesTimes(double[] v1, double[][] m2, double[] v3)`	Matrix multiplication, v1^T * m2 * v3
`static double[][]`	`transposeTimesTranspose(double[][] m1, double[][] m2)`	Matrix multiplication, m1^T * m2^T.
`static double[][]`	`unitMatrix(int dim)`	Returns the unit / identity / "eye" matrix of the specified dimension.
`static double[]`	`unitVector(int dimensionality, int i)`	Returns the ith unit vector of the specified dimensionality.
`static double[][]`	`zeroMatrix(int dim)`	Returns the zero matrix of the specified dimension.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - DELTA
```
private static final double DELTA
```
    A small number to handle numbers near 0 as 0.
    
    See Also:
    
    Constant Field Values
  - ERR_VEC_DIMENSIONS
```
protected static final java.lang.String ERR_VEC_DIMENSIONS
```
    Error message when vector dimensionalities do not agree.
    
    See Also:
    
    Constant Field Values
  - ERR_MATRIX_DIMENSIONS
```
protected static final java.lang.String ERR_MATRIX_DIMENSIONS
```
    Error message when matrix dimensionalities do not agree.
    
    See Also:
    
    Constant Field Values
  - ERR_MATRIX_INNERDIM
```
protected static final java.lang.String ERR_MATRIX_INNERDIM
```
    Error message when matrix dimensionalities do not agree.
    
    See Also:
    
    Constant Field Values
  - ERR_DIMENSIONS
```
protected static final java.lang.String ERR_DIMENSIONS
```
    Error message when dimensionalities do not agree.
    
    See Also:
    
    Constant Field Values
  - ERR_INVALID_RANGE
```
protected static final java.lang.String ERR_INVALID_RANGE
```
    Error message when min > max is given as a range.
    
    See Also:
    
    Constant Field Values
  - ERR_MATRIX_NONSQUARE
```
protected static final java.lang.String ERR_MATRIX_NONSQUARE
```
    Error when a non-square matrix is used with determinant.
    
    See Also:
    
    Constant Field Values
  - ERR_SINGULAR
```
protected static final java.lang.String ERR_SINGULAR
```
    Error with a singular matrix.
    
    See Also:
    
    Constant Field Values
  - ERR_MATRIX_NOT_SPD
```
protected static final java.lang.String ERR_MATRIX_NOT_SPD
```
    When a symmetric positive definite matrix is required.
    
    See Also:
    
    Constant Field Values
  - ERR_MATRIX_RANK_DEFICIENT
```
protected static final java.lang.String ERR_MATRIX_RANK_DEFICIENT
```
    When a matrix is rank deficient.
    
    See Also:
    
    Constant Field Values
- Constructor Detail
  - VMath
```
private VMath()
```
    Fake constructor. Static class.
- Method Detail
  - unitVector
```
public static double[] unitVector(int dimensionality,
                                  int i)
```
    Returns the ith unit vector of the specified dimensionality.
    
    Parameters:
    
    dimensionality - the dimensionality of the vector
    
    i - the index
    
    Returns:
    
    the ith unit vector of the specified dimensionality
  - copy
```
public static double[] copy(double[] v)
```
    Returns a copy of this vector.
    
    Parameters:
    
    v - original vector
    
    Returns:
    
    a copy of this vector
  - transpose
```
public static double[][] transpose(double[] v)
```
    Transpose vector to a matrix without copying.
    
    Parameters:
    
    v - Vector
    
    Returns:
    
    Matrix
  - plus
```
public static double[] plus(double[] v1,
                            double[] v2)
```
    Computes component-wise v1 + v2 for vectors.
    
    Parameters:
    
    v1 - first vector
    
    v2 - second vector
    
    Returns:
    
    the sum v1 + v2
  - plusTimes
```
public static double[] plusTimes(double[] v1,
                                 double[] v2,
                                 double s2)
```
    Computes component-wise v1 + v2 * s2.
    
    Parameters:
    
    v1 - first vector
    
    v2 - second vector
    
    s2 - the scalar
    
    Returns:
    
    the result of v1 + v2 * s2
  - timesPlus
```
public static double[] timesPlus(double[] v1,
                                 double s1,
                                 double[] v2)
```
    Computes component-wise v1 * s1 + v2.
    
    Parameters:
    
    v1 - first vector
    
    s1 - the scalar for v1
    
    v2 - second vector
    
    Returns:
    
    the result of v1 * s1 + v2
  - timesPlusTimes
```
public static double[] timesPlusTimes(double[] v1,
                                      double s1,
                                      double[] v2,
                                      double s2)
```
    Computes component-wise v1 * s1 + v2 * s2.
    
    Parameters:
    
    v1 - first vector
    
    s1 - the scalar for v1
    
    v2 - second vector
    
    s2 - the scalar for v2
    
    Returns:
    
    the result of v1 * s1 + v2 * s2
  - plusEquals
```
public static double[] plusEquals(double[] v1,
                                  double[] v2)
```
    Computes component-wise v1 = v1 + v2, overwriting the vector v1.
    
    Parameters:
    
    v1 - first vector (overwritten)
    
    v2 - second vector
    
    Returns:
    
    v1 = v1 + v2
  - plusTimesEquals
```
public static double[] plusTimesEquals(double[] v1,
                                       double[] v2,
                                       double s2)
```
    Computes component-wise v1 = v1 + v2 * s2, overwriting the vector v1.
    
    Parameters:
    
    v1 - first vector (overwritten)
    
    v2 - another vector
    
    s2 - scalar factor for v2
    
    Returns:
    
    v1 = v1 + v2 * s2
  - timesPlusEquals
```
public static double[] timesPlusEquals(double[] v1,
                                       double s1,
                                       double[] v2)
```
    Computes component-wise v1 = v1 * s1 + v2, overwriting the vector v1.
    
    Parameters:
    
    v1 - first vector (overwritten)
    
    s1 - scalar factor for v1
    
    v2 - another vector
    
    Returns:
    
    v1 = v1 * s1 + v2
  - timesPlusTimesEquals
```
public static double[] timesPlusTimesEquals(double[] v1,
                                            double s1,
                                            double[] v2,
                                            double s2)
```
    Computes component-wise v1 = v1 * s1 + v2 * s2, overwriting the vector v1.
    
    Parameters:
    
    v1 - first vector (overwritten)
    
    s1 - scalar for v1
    
    v2 - another vector
    
    s2 - scalar for v2
    
    Returns:
    
    v1 = v1 * s1 + v2 * s2
  - plus
```
public static double[] plus(double[] v1,
                            double s1)
```
    Computes component-wise v1 + s1.
    
    Parameters:
    
    v1 - vector to add to
    
    s1 - constant value to add
    
    Returns:
    
    v1 + s1
  - plusEquals
```
public static double[] plusEquals(double[] v1,
                                  double s1)
```
    Computes component-wise v1 = v1 + s1, overwriting the vector v1.
    
    Parameters:
    
    v1 - vector to add to (overwritten)
    
    s1 - constant value to add
    
    Returns:
    
    Modified vector
  - minus
```
public static double[] minus(double[] v1,
                             double[] v2)
```
    Computes component-wise v1 - v2.
    
    Parameters:
    
    v1 - first vector
    
    v2 - the vector to be subtracted from this vector
    
    Returns:
    
    v1 - v2
  - minusTimes
```
public static double[] minusTimes(double[] v1,
                                  double[] v2,
                                  double s2)
```
    Computes component-wise v1 - v2 * s2.
    
    Parameters:
    
    v1 - first vector
    
    v2 - the vector to be subtracted from this vector
    
    s2 - the scaling factor for v2
    
    Returns:
    
    v1 - v2 * s2
  - timesMinus
```
public static double[] timesMinus(double[] v1,
                                  double s1,
                                  double[] v2)
```
    Computes component-wise v1 * s1 - v2.
    
    Parameters:
    
    v1 - first vector
    
    s1 - the scaling factor for v1
    
    v2 - the vector to be subtracted from this vector
    
    Returns:
    
    v1 * s1 - v2
  - timesMinusTimes
```
public static double[] timesMinusTimes(double[] v1,
                                       double s1,
                                       double[] v2,
                                       double s2)
```
    Computes component-wise v1 * s1 - v2 * s2.
    
    Parameters:
    
    v1 - first vector
    
    s1 - the scaling factor for v1
    
    v2 - the vector to be subtracted from this vector
    
    s2 - the scaling factor for v2
    
    Returns:
    
    v1 * s1 - v2 * s2
  - minusEquals
```
public static double[] minusEquals(double[] v1,
                                   double[] v2)
```
    Computes component-wise v1 = v1 - v2, overwriting the vector v1.
    
    Parameters:
    
    v1 - vector
    
    v2 - another vector
    
    Returns:
    
    v1 = v1 - v2
  - minusTimesEquals
```
public static double[] minusTimesEquals(double[] v1,
                                        double[] v2,
                                        double s2)
```
    Computes component-wise v1 = v1 - v2 * s2, overwriting the vector v1.
    
    Parameters:
    
    v1 - vector
    
    v2 - another vector
    
    s2 - scalar for v2
    
    Returns:
    
    v1 = v1 - v2 * s2
  - timesMinusEquals
```
public static double[] timesMinusEquals(double[] v1,
                                        double s1,
                                        double[] v2)
```
    Computes component-wise v1 = v1 * s1 - v2, overwriting the vector v1.
    
    Parameters:
    
    v1 - vector
    
    s1 - scalar for v1
    
    v2 - another vector
    
    Returns:
    
    v1 = v1 * s1 - v2
  - timesMinusTimesEquals
```
public static double[] timesMinusTimesEquals(double[] v1,
                                             double s1,
                                             double[] v2,
                                             double s2)
```
    Computes component-wise v1 = v1 * s1 - v2 * s2, overwriting the vector v1.
    
    Parameters:
    
    v1 - vector
    
    s1 - scalar for v1
    
    v2 - another vector
    
    s2 - Scalar
    
    Returns:
    
    v1 = v1 * s1 - v2 * s2
  - minus
```
public static double[] minus(double[] v1,
                             double s1)
```
    Subtract component-wise v1 - s1.
    
    Parameters:
    
    v1 - original vector
    
    s1 - Value to subtract
    
    Returns:
    
    v1 - s1
  - minusEquals
```
public static double[] minusEquals(double[] v1,
                                   double s1)
```
    Subtract component-wise in-place v1 = v1 - s1, overwriting the vector v1.
    
    Parameters:
    
    v1 - original vector
    
    s1 - Value to subtract
    
    Returns:
    
    v1 = v1 - s1
  - times
```
public static double[] times(double[] v1,
                             double s1)
```
    Multiply component-wise v1 * s1.
    
    Parameters:
    
    v1 - original vector
    
    s1 - the scalar to be multiplied
    
    Returns:
    
    v1 * s1
  - timesEquals
```
public static double[] timesEquals(double[] v1,
                                   double s)
```
    Multiply component-wise v1 = v1 * s1, overwriting the vector v1.
    
    Parameters:
    
    v1 - original vector
    
    s - scalar
    
    Returns:
    
    v1 = v1 * s1
  - overwriteTimes
```
public static double[] overwriteTimes(double[] v1,
                                      double[] v2,
                                      double s)
```
    Multiply component-wise v1 = v2 * s, overwriting the vector v1.
    
    Parameters:
    
    v1 - output vector
    
    v2 - input vector
    
    s - scalar
    
    Returns:
    
    v1 with new values
  - times
```
@Deprecated
public static double[][] times(double[] v1,
                               double[][] m2)
```
    Deprecated.
    this is fairly inefficient memory layout, rewriting your code
    
    Matrix multiplication: v1 * m2 (m2 must have one row only).
    Note: this is an unusual operation, m2 must be a costly column matrix.
    This method is equivalent to the timesTranspose(double[], double[]) method with m2 being the second vector as matrix, but transposed.
    
    Parameters:
    
    v1 - vector
    
    m2 - other matrix, must have one row.
    
    Returns:
    
    Matrix product, v1 * m2
  - transposeTimes
```
public static double[][] transposeTimes(double[] v1,
                                        double[][] m2)
```
    Vector to matrix multiplication, v1^T m2.
    
    Parameters:
    
    v1 - vector
    
    m2 - other matrix
    
    Returns:
    
    Matrix product, v1^T * m2
  - transposeTimes
```
public static double transposeTimes(double[] v1,
                                    double[] v2)
```
    Vector scalar product (dot product), v1^T v2 = v1·v2 = <v1,v2>.
    
    Parameters:
    
    v1 - vector
    
    v2 - other vector
    
    Returns:
    
    scalar result of matrix product, v1^T * v2
  - timesTranspose
```
@Deprecated
public static double[][] timesTranspose(double[] v1,
                                        double[][] m2)
```
    Deprecated.
    this is fairly inefficient memory layout, rewriting your code
    
    Vector with transposed matrix multiplication, v1 * m2^T (m2 must have one row only).
    Note: this is an unusual operation, m2 must be a costly column matrix.
    This method is equivalent to the timesTranspose(double[], double[]) method with m2 being the second vector as matrix.
    
    Parameters:
    
    v1 - vector
    
    m2 - other matrix
    
    Returns:
    
    Matrix product, v1 * m2^T
  - timesTranspose
```
public static double[][] timesTranspose(double[] v1,
                                        double[] v2)
```
    Vectors to matrix multiplication, v1 * v2^T.
    
    Parameters:
    
    v1 - vector
    
    v2 - other vector
    
    Returns:
    
    Matrix product, v1 * v2^T
  - scalarProduct
```
public static double scalarProduct(double[] v1,
                                   double[] v2)
```
    Returns the scalar product (dot product) of two vectors, <v1,v2> = v1^T v2.
    This is the same as transposeTimes(double[], double[]).
    
    Parameters:
    
    v1 - vector
    
    v2 - other vector
    
    Returns:
    
    double the scalar product of vectors v1 and v2
  - dot
```
public static double dot(double[] v1,
                         double[] v2)
```
    Returns the dot product (scalar product) of two vectors, v1·v2 = v1^T v2.
    This is the same as transposeTimes(double[], double[]).
    
    Parameters:
    
    v1 - vector
    
    v2 - other vector
    
    Returns:
    
    double the scalar product of vectors v1 and v2
  - sum
```
public static double sum(double[] v1)
```
    Sum of the vector components.
    
    Parameters:
    
    v1 - vector
    
    Returns:
    
    sum of this vector
  - squareSum
```
public static double squareSum(double[] v1)
```
    Squared Euclidean length of the vector v1^T v1 = v1·v1.
    
    Parameters:
    
    v1 - vector
    
    Returns:
    
    squared Euclidean length of this vector
  - euclideanLength
```
public static double euclideanLength(double[] v1)
```
    Euclidean length of the vector sqrt(v1^T v1).
    
    Parameters:
    
    v1 - vector
    
    Returns:
    
    Euclidean length of this vector
  - argmax
```
public static int argmax(double[] v)
```
    Find the maximum value.
    
    Parameters:
    
    v - Vector
    
    Returns:
    
    Position of maximum
  - argmax
```
public static int argmax(double[] v,
                         int start,
                         int end)
```
    Find the maximum value.
    
    Parameters:
    
    v - Vector
    
    start - First to consider
    
    end - End of range (exclusive)
    
    Returns:
    
    Position of maximum, beginning at array index 0
  - argmin
```
public static int argmin(double[] v)
```
    Find the minimum value.
    
    Parameters:
    
    v - Vector
    
    Returns:
    
    Position of minimum
  - argmin
```
public static int argmin(double[] v,
                         int start,
                         int end)
```
    Find the minimum value.
    
    Parameters:
    
    v - Vector
    
    start - First to consider
    
    end - End of range (exclusive)
    
    Returns:
    
    Position of minimum, beginning at array index 0
  - normalize
```
public static double[] normalize(double[] v1)
```
    Normalizes v1 to the length of 1.0.
    
    Parameters:
    
    v1 - vector
    
    Returns:
    
    normalized copy of v1
  - normalizeEquals
```
public static double[] normalizeEquals(double[] v1)
```
    Normalizes v1 to the length of 1.0 in place.
    
    Parameters:
    
    v1 - vector (overwritten)
    
    Returns:
    
    normalized v1
  - hashCode
```
public static int hashCode(double[] v1)
```
    Compute the hash code for the vector.
    
    Parameters:
    
    v1 - elements
    
    Returns:
    
    hash code
  - equals
```
public static boolean equals(double[] v1,
                             double[] v2)
```
    Compare for equality.
    
    Parameters:
    
    v1 - first vector
    
    v2 - second vector
    
    Returns:
    
    comparison result
  - clear
```
public static void clear(double[] v1)
```
    Reset the vector to 0.
    
    Parameters:
    
    v1 - vector
  - clear
```
public static void clear(double[][] m)
```
    Reset the matrix to 0.
    
    Parameters:
    
    m - Matrix
  - rotate90Equals
```
public static double[] rotate90Equals(double[] v1)
```
    Rotate the two-dimensional vector by 90 degrees.
    
    Parameters:
    
    v1 - first vector
    
    Returns:
    
    modified v1, rotated by 90 degrees
  - unitMatrix
```
public static double[][] unitMatrix(int dim)
```
    Returns the unit / identity / "eye" matrix of the specified dimension.
    
    Parameters:
    
    dim - the dimensionality of the unit matrix
    
    Returns:
    
    the unit matrix of the specified dimension
  - zeroMatrix
```
public static double[][] zeroMatrix(int dim)
```
    Returns the zero matrix of the specified dimension.
    
    Parameters:
    
    dim - the dimensionality of the unit matrix
    
    Returns:
    
    the zero matrix of the specified dimension
  - identity
```
public static double[][] identity(int m,
                                  int n)
```
    Generate unit / identity / "eye" matrix.
    
    Parameters:
    
    m - Number of rows.
    
    n - Number of columns.
    
    Returns:
    
    An m-by-n matrix with ones on the diagonal and zeros elsewhere.
  - diagonal
```
public static double[][] diagonal(double[] v1)
```
    Returns a quadratic matrix consisting of zeros and of the given values on the diagonal.
    
    Parameters:
    
    v1 - the values on the diagonal
    
    Returns:
    
    the resulting matrix
  - copy
```
public static double[][] copy(double[][] m1)
```
    Make a deep copy of a matrix.
    
    Parameters:
    
    m1 - Input matrix
    
    Returns:
    
    a new matrix containing the same values as this matrix
  - rowPackedCopy
```
public static double[] rowPackedCopy(double[][] m1)
```
    Make a one-dimensional row packed copy of the internal array.
    
    Parameters:
    
    m1 - Input matrix
    
    Returns:
    
    Matrix elements packed in a one-dimensional array by rows.
  - columnPackedCopy
```
public static double[] columnPackedCopy(double[][] m1)
```
    Make a one-dimensional column packed copy of the internal array.
    
    Parameters:
    
    m1 - Input matrix
    
    Returns:
    
    Matrix elements packed in a one-dimensional array by columns.
  - getMatrix
```
public static double[][] getMatrix(double[][] m1,
                                   int r0,
                                   int r1,
                                   int c0,
                                   int c1)
```
    Get a submatrix.
    
    Parameters:
    
    m1 - Input matrix
    
    r0 - Initial row index
    
    r1 - Final row index (exclusive)
    
    c0 - Initial column index
    
    c1 - Final column index (exclusive)
    
    Returns:
    
    m1(r0:r1-1,c0:c1-1)
  - getMatrix
```
public static double[][] getMatrix(double[][] m1,
                                   int[] r,
                                   int[] c)
```
    Get a submatrix.
    
    Parameters:
    
    m1 - Input matrix
    
    r - Array of row indices.
    
    c - Array of column indices.
    
    Returns:
    
    m1(r(:),c(:))
  - getMatrix
```
public static double[][] getMatrix(double[][] m1,
                                   int[] r,
                                   int c0,
                                   int c1)
```
    Get a submatrix.
    
    Parameters:
    
    m1 - Input matrix
    
    r - Array of row indices.
    
    c0 - Initial column index
    
    c1 - Final column index (exclusive)
    
    Returns:
    
    m1(r(:),c0:c1-1)
  - getMatrix
```
public static double[][] getMatrix(double[][] m1,
                                   int r0,
                                   int r1,
                                   int[] c)
```
    Get a submatrix.
    
    Parameters:
    
    m1 - Input matrix
    
    r0 - Initial row index
    
    r1 - Final row index (exclusive)
    
    c - Array of column indices.
    
    Returns:
    
    m1(r0:r1-1,c(:))
  - setMatrix
```
public static void setMatrix(double[][] m1,
                             int r0,
                             int r1,
                             int c0,
                             int c1,
                             double[][] m2)
```
    Set a submatrix.
    
    Parameters:
    
    m1 - Original matrix
    
    r0 - Initial row index
    
    r1 - Final row index (exclusive)
    
    c0 - Initial column index
    
    c1 - Final column index (exclusive)
    
    m2 - New values for m1(r0:r1-1,c0:c1-1)
  - setMatrix
```
public static void setMatrix(double[][] m1,
                             int[] r,
                             int[] c,
                             double[][] m2)
```
    Set a submatrix.
    
    Parameters:
    
    m1 - Original matrix
    
    r - Array of row indices.
    
    c - Array of column indices.
    
    m2 - New values for m1(r(:),c(:))
  - setMatrix
```
public static void setMatrix(double[][] m1,
                             int[] r,
                             int c0,
                             int c1,
                             double[][] m2)
```
    Set a submatrix.
    
    Parameters:
    
    m1 - Input matrix
    
    r - Array of row indices.
    
    c0 - Initial column index
    
    c1 - Final column index (exclusive)
    
    m2 - New values for m1(r(:),c0:c1-1)
  - setMatrix
```
public static void setMatrix(double[][] m1,
                             int r0,
                             int r1,
                             int[] c,
                             double[][] m2)
```
    Set a submatrix.
    
    Parameters:
    
    m1 - Input matrix
    
    r0 - Initial row index
    
    r1 - Final row index
    
    c - Array of column indices.
    
    m2 - New values for m1(r0:r1-1,c(:))
  - getRow
```
public static double[] getRow(double[][] m1,
                              int r)
```
    Returns the rth row of this matrix as vector.
    
    Parameters:
    
    m1 - Input matrix
    
    r - the index of the row to be returned
    
    Returns:
    
    the rth row of this matrix
  - setRow
```
public static void setRow(double[][] m1,
                          int r,
                          double[] row)
```
    Sets the rth row of this matrix to the specified vector.
    
    Parameters:
    
    m1 - Original matrix
    
    r - the index of the column to be set
    
    row - the value of the column to be set
  - getCol
```
public static double[] getCol(double[][] m1,
                              int col)
```
    Get a column from a matrix as vector.
    
    Parameters:
    
    m1 - Matrix to extract the column from
    
    col - Column number
    
    Returns:
    
    Column
  - setCol
```
public static void setCol(double[][] m1,
                          int c,
                          double[] column)
```
    Sets the cth column of this matrix to the specified column.
    
    Parameters:
    
    m1 - Input matrix
    
    c - the index of the column to be set
    
    column - the value of the column to be set
  - transpose
```
public static double[][] transpose(double[][] m1)
```
    Matrix transpose
    
    Parameters:
    
    m1 - Input matrix
    
    Returns:
    
    m1^T as copy
  - plus
```
public static double[][] plus(double[][] m1,
                              double[][] m2)
```
    Component-wise matrix sum: m3 = m1 + m2.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - another matrix
    
    Returns:
    
    m1 + m1 in a new Matrix
  - plusTimes
```
public static double[][] plusTimes(double[][] m1,
                                   double[][] m2,
                                   double s2)
```
    Component-wise matrix operation: m3 = m1 + m2 * s2.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - another matrix
    
    s2 - scalar
    
    Returns:
    
    m1 + m2 * s2 in a new matrix
  - plusEquals
```
public static double[][] plusEquals(double[][] m1,
                                    double[][] m2)
```
    Component-wise matrix operation: m1 = m1 + m2, overwriting the existing matrix m1.
    
    Parameters:
    
    m1 - input matrix (overwritten)
    
    m2 - another matrix
    
    Returns:
    
    m1 = m1 + m2
  - plusTimesEquals
```
public static double[][] plusTimesEquals(double[][] m1,
                                         double[][] m2,
                                         double s2)
```
    Component-wise matrix operation: m1 = m1 + m2 * s2, overwriting the existing matrix m1.
    
    Parameters:
    
    m1 - input matrix (overwritten)
    
    m2 - another matrix
    
    s2 - scalar for s2
    
    Returns:
    
    m1 = m1 + m2 * s2, overwriting m1
  - minus
```
public static double[][] minus(double[][] m1,
                               double[][] m2)
```
    Component-wise matrix subtraction m3 = m1 - m2.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - another matrix
    
    Returns:
    
    m1 - m2 in a new matrix
  - minusTimes
```
public static double[][] minusTimes(double[][] m1,
                                    double[][] m2,
                                    double s2)
```
    Component-wise matrix operation: m3 = m1 - m2 * s2
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - another matrix
    
    s2 - Scalar
    
    Returns:
    
    m1 - m2 * s2 in a new Matrix
  - minusEquals
```
public static double[][] minusEquals(double[][] m1,
                                     double[][] m2)
```
    Component-wise matrix subtraction: m1 = m1 - m2, overwriting the existing matrix m1.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - another matrix
    
    Returns:
    
    m1 - m2, overwriting m1
  - minusTimesEquals
```
public static double[][] minusTimesEquals(double[][] m1,
                                          double[][] m2,
                                          double s2)
```
    Component-wise matrix operation: m1 = m1 - m2 * s2, overwriting the existing matrix m1.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - another matrix
    
    s2 - Scalar
    
    Returns:
    
    m1 = m1 - s2 * m2, overwriting m1
  - times
```
public static double[][] times(double[][] m1,
                               double s1)
```
    Multiply a matrix by a scalar component-wise, m3 = m1 * s1.
    
    Parameters:
    
    m1 - Input matrix
    
    s1 - scalar
    
    Returns:
    
    m1 * s1, in a new matrix
  - timesEquals
```
public static double[][] timesEquals(double[][] m1,
                                     double s1)
```
    Multiply a matrix by a scalar component-wise in place, m1 = m1 * s1, overwriting the existing matrix m1.
    
    Parameters:
    
    m1 - Input matrix
    
    s1 - scalar
    
    Returns:
    
    m1 = m1 * s1, overwriting m1
  - times
```
public static double[][] times(double[][] m1,
                               double[][] m2)
```
    Matrix multiplication, m1 * m2.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - another matrix
    
    Returns:
    
    Matrix product, m1 * m2
  - times
```
public static double[] times(double[][] m1,
                             double[] v2)
```
    Matrix with vector multiplication, m1 * v2.
    
    Parameters:
    
    m1 - Input matrix
    
    v2 - a vector
    
    Returns:
    
    Matrix product, m1 * v2
  - transposeTimes
```
public static double[] transposeTimes(double[][] m1,
                                      double[] v2)
```
    Transposed matrix with vector multiplication, m1^T * v2
    
    Parameters:
    
    m1 - Input matrix
    
    v2 - another matrix
    
    Returns:
    
    Matrix product, m1^T * v2
  - transposeTimes
```
public static double[][] transposeTimes(double[][] m1,
                                        double[][] m2)
```
    Matrix multiplication, m1^T * m2
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - another matrix
    
    Returns:
    
    Matrix product, m1^T * m2
  - transposeTimesTimes
```
public static double transposeTimesTimes(double[] v1,
                                         double[][] m2,
                                         double[] v3)
```
    Matrix multiplication, v1^T * m2 * v3
    
    Parameters:
    
    v1 - vector on the left
    
    m2 - matrix
    
    v3 - vector on the right
    
    Returns:
    
    Matrix product, v1^T * m2 * v3
  - timesTranspose
```
public static double[][] timesTranspose(double[][] m1,
                                        double[][] m2)
```
    Matrix multiplication, m1 * m2^T
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - another matrix
    
    Returns:
    
    Matrix product, m1 * m2^T
  - transposeTimesTranspose
```
public static double[][] transposeTimesTranspose(double[][] m1,
                                                 double[][] m2)
```
    Matrix multiplication, m1^T * m2^T. Computed as (m2*m1)^T
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - another matrix
    
    Returns:
    
    Matrix product, m1^T * m2^T
  - transposeDiagonalTimes
```
public static double[][] transposeDiagonalTimes(double[][] m1,
                                                double[] d2,
                                                double[][] m3)
```
    Matrix multiplication with diagonal, m1^T * d2 * m3
    
    Parameters:
    
    m1 - Left matrix
    
    d2 - Diagonal entries
    
    m3 - Right matrix
    
    Returns:
    
    m1^T * d2 * m3
  - mahalanobisDistance
```
@Reference(authors="P. C. Mahalanobis",
           title="On the generalized distance in statistics",
           booktitle="Proceedings of the National Institute of Sciences of India. 2 (1)",
           bibkey="journals/misc/Mahalanobis36")
public static double mahalanobisDistance(double[][] B,
                                         double[] a,
                                         double[] c)
```
    Matrix multiplication, (a-c)^T * B * (a-c)
    Note: it may (or may not) be more efficient to materialize (a-c), then use transposeTimesTimes(a_minus_c, B, a_minus_c) instead.
    
    Parameters:
    
    B - matrix
    
    a - First vector
    
    c - Center vector
    
    Returns:
    
    Matrix product, (a-c)^T * B * (a-c)
  - getDiagonal
```
public static double[] getDiagonal(double[][] m1)
```
    getDiagonal returns array of diagonal-elements.
    
    Parameters:
    
    m1 - Input matrix
    
    Returns:
    
    values on the diagonal of the Matrix
  - normalizeColumns
```
public static void normalizeColumns(double[][] m1)
```
    Normalizes the columns of this matrix to length of 1.0. Note: if a column has length 0, it will remain unmodified.
    
    Parameters:
    
    m1 - Input matrix
  - appendColumns
```
public static double[][] appendColumns(double[][] m1,
                                       double[][] m2)
```
    Returns a matrix which consists of this matrix and the specified columns.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - the columns to be appended
    
    Returns:
    
    the new matrix with the appended columns
  - orthonormalize
```
public static double[][] orthonormalize(double[][] m1)
```
    Returns an orthonormalization of this matrix.
    
    Parameters:
    
    m1 - Input matrix
    
    Returns:
    
    the orthonormalized matrix
  - solve
```
public static double[][] solve(double[][] A,
                               double[][] B)
```
    Solve A*X = B
    
    Parameters:
    
    B - right hand side
    
    Returns:
    
    solution if A is square, least squares solution otherwise
  - solve
```
public static double[] solve(double[][] A,
                             double[] b)
```
    Solve A*X = b
    
    Parameters:
    
    b - right hand side
    
    Returns:
    
    solution if A is square, least squares solution otherwise
  - inverse
```
public static double[][] inverse(double[][] A)
```
    Matrix inverse or pseudoinverse
    
    Parameters:
    
    A - matrix to invert
    
    Returns:
    
    inverse(A) if A is square, pseudoinverse otherwise.
  - normF
```
public static double normF(double[][] elements)
```
    Frobenius norm
    
    Parameters:
    
    elements - Matrix
    
    Returns:
    
    sqrt of sum of squares of all elements.
  - hashCode
```
public static int hashCode(double[][] m1)
```
    Compute hash code
    
    Parameters:
    
    m1 - Input matrix
    
    Returns:
    
    Hash code
  - equals
```
public static boolean equals(double[][] m1,
                             double[][] m2)
```
    Test for equality
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - Other matrix
    
    Returns:
    
    Equality
  - almostEquals
```
public static boolean almostEquals(double[][] m1,
                                   double[][] m2,
                                   double maxdelta)
```
    Compare two matrices with a delta parameter to take numerical errors into account.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - other matrix to compare with
    
    maxdelta - maximum delta allowed
    
    Returns:
    
    true if delta smaller than maximum
  - almostEquals
```
public static boolean almostEquals(double[][] m1,
                                   double[][] m2)
```
    Compare two matrices with a delta parameter to take numerical errors into account.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - other matrix to compare with
    
    Returns:
    
    almost equals with delta DELTA
  - almostEquals
```
public static boolean almostEquals(double[] m1,
                                   double[] m2,
                                   double maxdelta)
```
    Compare two matrices with a delta parameter to take numerical errors into account.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - other matrix to compare with
    
    maxdelta - maximum delta allowed
    
    Returns:
    
    true if delta smaller than maximum
  - almostEquals
```
public static boolean almostEquals(double[] m1,
                                   double[] m2)
```
    Compare two matrices with a delta parameter to take numerical errors into account.
    
    Parameters:
    
    m1 - Input matrix
    
    m2 - other matrix to compare with
    
    Returns:
    
    almost equals with delta DELTA
  - getRowDimensionality
```
public static int getRowDimensionality(double[][] m1)
```
    Returns the dimensionality of the rows of this matrix.
    
    Parameters:
    
    m1 - Input matrix
    
    Returns:
    
    the number of rows.
  - getColumnDimensionality
```
public static int getColumnDimensionality(double[][] m1)
```
    Returns the dimensionality of the columns of this matrix.
    
    Parameters:
    
    m1 - Input matrix
    
    Returns:
    
    the number of columns.
  - angle
```
public static double angle(double[] v1,
                           double[] v2)
```
    Compute the cosine of the angle between two vectors, where the smaller angle between those vectors is viewed.
    
    Parameters:
    
    v1 - first vector
    
    v2 - second vector
    
    Returns:
    
    cosine of the smaller angle
  - angle
```
public static double angle(double[] v1,
                           double[] v2,
                           double[] o)
```
    Compute the cosine of the angle between two vectors, where the smaller angle between those vectors is viewed.
    
    Parameters:
    
    v1 - first vector
    
    v2 - second vector
    
    o - Origin
    
    Returns:
    
    cosine of the smaller angle

Class VMath

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

DELTA

ERR_VEC_DIMENSIONS

ERR_MATRIX_DIMENSIONS

ERR_MATRIX_INNERDIM

ERR_DIMENSIONS

ERR_INVALID_RANGE

ERR_MATRIX_NONSQUARE

ERR_SINGULAR

ERR_MATRIX_NOT_SPD

ERR_MATRIX_RANK_DEFICIENT

Constructor Detail

VMath

Method Detail

unitVector

copy

transpose

plus

plusTimes

timesPlus

timesPlusTimes

plusEquals

plusTimesEquals

timesPlusEquals

timesPlusTimesEquals

plus

plusEquals

minus

minusTimes

timesMinus

timesMinusTimes

minusEquals

minusTimesEquals

timesMinusEquals

timesMinusTimesEquals

minus

minusEquals

times

timesEquals

overwriteTimes

times

transposeTimes

transposeTimes

timesTranspose

timesTranspose

scalarProduct

dot

sum

squareSum

euclideanLength

argmax

argmax

argmin

argmin

normalize

normalizeEquals

hashCode

equals

clear

clear

rotate90Equals

unitMatrix

zeroMatrix

identity

diagonal

copy

rowPackedCopy

columnPackedCopy

getMatrix

getMatrix

getMatrix

getMatrix

setMatrix

setMatrix

setMatrix