Matrix (weka-dev 3.7.12 API)

java.lang.Object
- weka.core.matrix.Matrix

All Implemented Interfaces:

Serializable, Cloneable, RevisionHandler

Direct Known Subclasses:

ConfusionMatrix
```
public class Matrix
extends Object
implements Cloneable, Serializable, RevisionHandler
```
Jama = Java Matrix class.
The Java Matrix Class provides the fundamental operations of numerical linear algebra. Various constructors create Matrices from two dimensional arrays of double precision floating point numbers. Various "gets" and "sets" provide access to submatrices and matrix elements. Several methods implement basic matrix arithmetic, including matrix addition and multiplication, matrix norms, and element-by-element array operations. Methods for reading and printing matrices are also included. All the operations in this version of the Matrix Class involve real matrices. Complex matrices may be handled in a future version.
Five fundamental matrix decompositions, which consist of pairs or triples of matrices, permutation vectors, and the like, produce results in five decomposition classes. These decompositions are accessed by the Matrix class to compute solutions of simultaneous linear equations, determinants, inverses and other matrix functions. The five decompositions are:
- Cholesky Decomposition of symmetric, positive definite matrices.
- LU Decomposition of rectangular matrices.
- QR Decomposition of rectangular matrices.
- Singular Value Decomposition of rectangular matrices.
- Eigenvalue Decomposition of both symmetric and nonsymmetric square matrices.
Example of use:
Solve a linear system A x = b and compute the residual norm, ||b - A x||.
```
 double[][] vals = { { 1., 2., 3 }, { 4., 5., 6. }, { 7., 8., 10. } };
 Matrix A = new Matrix(vals);
 Matrix b = Matrix.random(3, 1);
 Matrix x = A.solve(b);
 Matrix r = A.times(x).minus(b);
 double rnorm = r.normInf();
 
```
Adapted from the JAMA package. Additional methods are tagged with the @author tag.
Version:

$Revision: 10203 $

Author:

The Mathworks and NIST, Fracpete (fracpete at waikato dot ac dot nz)

See Also:
Serialized Form

Constructor Summary

Constructors
Constructor and Description
`Matrix(double[][] A)` Construct a matrix from a 2-D array.
`Matrix(double[][] A, int m, int n)` Construct a matrix quickly without checking arguments.
`Matrix(double[] vals, int m)` Construct a matrix from a one-dimensional packed array
`Matrix(int m, int n)` Construct an m-by-n matrix of zeros.
`Matrix(int m, int n, double s)` Construct an m-by-n constant matrix.
`Matrix(Reader r)` Reads a matrix from a reader.

Method Summary

Methods
Modifier and Type	Method and Description
`Matrix`	`arrayLeftDivide(Matrix B)` Element-by-element left division, C = A.\B
`Matrix`	`arrayLeftDivideEquals(Matrix B)` Element-by-element left division in place, A = A.\B
`Matrix`	`arrayRightDivide(Matrix B)` Element-by-element right division, C = A./B
`Matrix`	`arrayRightDivideEquals(Matrix B)` Element-by-element right division in place, A = A./B
`Matrix`	`arrayTimes(Matrix B)` Element-by-element multiplication, C = A.*B
`Matrix`	`arrayTimesEquals(Matrix B)` Element-by-element multiplication in place, A = A.*B
`CholeskyDecomposition`	`chol()` Cholesky Decomposition
`Object`	`clone()` Clone the Matrix object.
`double`	`cond()` Matrix condition (2 norm)
`static Matrix`	`constructWithCopy(double[][] A)` Construct a matrix from a copy of a 2-D array.
`Matrix`	`copy()` Make a deep copy of a matrix
`double`	`det()` Matrix determinant
`EigenvalueDecomposition`	`eig()` Eigenvalue Decomposition
`double`	`get(int i, int j)` Get a single element.
`double[][]`	`getArray()` Access the internal two-dimensional array.
`double[][]`	`getArrayCopy()` Copy the internal two-dimensional array.
`int`	`getColumnDimension()` Get column dimension.
`double[]`	`getColumnPackedCopy()` Make a one-dimensional column packed copy of the internal array.
`Matrix`	`getMatrix(int[] r, int[] c)` Get a submatrix.
`Matrix`	`getMatrix(int[] r, int j0, int j1)` Get a submatrix.
`Matrix`	`getMatrix(int i0, int i1, int[] c)` Get a submatrix.
`Matrix`	`getMatrix(int i0, int i1, int j0, int j1)` Get a submatrix.
`String`	`getRevision()` Returns the revision string.
`int`	`getRowDimension()` Get row dimension.
`double[]`	`getRowPackedCopy()` Make a one-dimensional row packed copy of the internal array.
`static Matrix`	`identity(int m, int n)` Generate identity matrix
`Matrix`	`inverse()` Matrix inverse or pseudoinverse
`boolean`	`isSquare()` returns whether the matrix is a square matrix or not.
`boolean`	`isSymmetric()` Returns true if the matrix is symmetric.
`LUDecomposition`	`lu()` LU Decomposition
`static void`	`main(String[] args)` Main method for testing this class.
`Matrix`	`minus(Matrix B)` C = A - B
`Matrix`	`minusEquals(Matrix B)` A = A - B
`double`	`norm1()` One norm
`double`	`norm2()` Two norm
`double`	`normF()` Frobenius norm
`double`	`normInf()` Infinity norm
`static Matrix`	`parseMatlab(String matlab)` creates a matrix from the given Matlab string.
`Matrix`	`plus(Matrix B)` C = A + B
`Matrix`	`plusEquals(Matrix B)` A = A + B
`void`	`print(int w, int d)` Print the matrix to stdout.
`void`	`print(NumberFormat format, int width)` Print the matrix to stdout.
`void`	`print(PrintWriter output, int w, int d)` Print the matrix to the output stream.
`void`	`print(PrintWriter output, NumberFormat format, int width)` Print the matrix to the output stream.
`QRDecomposition`	`qr()` QR Decomposition
`static Matrix`	`random(int m, int n)` Generate matrix with random elements
`int`	`rank()` Matrix rank
`static Matrix`	`read(BufferedReader input)` Read a matrix from a stream.
`LinearRegression`	`regression(Matrix y, double ridge)` Performs a (ridged) linear regression.
`LinearRegression`	`regression(Matrix y, double[] w, double ridge)` Performs a weighted (ridged) linear regression.
`void`	`set(int i, int j, double s)` Set a single element.
`void`	`setMatrix(int[] r, int[] c, Matrix X)` Set a submatrix.
`void`	`setMatrix(int[] r, int j0, int j1, Matrix X)` Set a submatrix.
`void`	`setMatrix(int i0, int i1, int[] c, Matrix X)` Set a submatrix.
`void`	`setMatrix(int i0, int i1, int j0, int j1, Matrix X)` Set a submatrix.
`Matrix`	`solve(Matrix B)` Solve A*X = B
`Matrix`	`solveTranspose(Matrix B)` Solve XA = B, which is also A'X' = B'
`Matrix`	`sqrt()` returns the square root of the matrix, i.e., X from the equation XX = A. Steps in the Calculation (see `sqrtm` in Matlab): perform eigenvalue decomposition [V,D]=eig(A) take the square root of all elements in D (only the ones with positive sign are considered for further computation) S=sqrt(D) calculate the root X=VS/V, which can be also written as X=(V'\(VS)')' Note:* since this method uses other high-level methods, it generates several instances of matrices.
`SingularValueDecomposition`	`svd()` Singular Value Decomposition
`Matrix`	`times(double s)` Multiply a matrix by a scalar, C = s*A
`Matrix`	`times(Matrix B)` Linear algebraic matrix multiplication, A * B
`Matrix`	`timesEquals(double s)` Multiply a matrix by a scalar in place, A = s*A
`String`	`toMatlab()` converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
`String`	`toString()` Converts a matrix to a string.
`double`	`trace()` Matrix trace.
`Matrix`	`transpose()` Matrix transpose.
`Matrix`	`uminus()` Unary minus
`void`	`write(Writer w)` Writes out a matrix.

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

- Constructor Detail
  - Matrix
```
public Matrix(int m,
      int n)
```
    Construct an m-by-n matrix of zeros.
    
    Parameters:
    m - Number of rows.
    n - Number of colums.
  - Matrix
```
public Matrix(int m,
      int n,
      double s)
```
    Construct an m-by-n constant matrix.
    
    Parameters:
    m - Number of rows.
    n - Number of colums.
    s - Fill the matrix with this scalar value.
  - Matrix
```
public Matrix(double[][] A)
```
    Construct a matrix from a 2-D array.
    
    Parameters:
    A - Two-dimensional array of doubles.
    
    Throws:
    
    IllegalArgumentException - All rows must have the same length
    See Also:
    constructWithCopy(double[][])
  - Matrix
```
public Matrix(double[][] A,
      int m,
      int n)
```
    Construct a matrix quickly without checking arguments.
    
    Parameters:
    A - Two-dimensional array of doubles.
    m - Number of rows.
    n - Number of colums.
  - Matrix
```
public Matrix(double[] vals,
      int m)
```
    Construct a matrix from a one-dimensional packed array
    
    Parameters:
    vals - One-dimensional array of doubles, packed by columns (ala Fortran).
    m - Number of rows.
    
    Throws:
    
    IllegalArgumentException - Array length must be a multiple of m.
  - Matrix
```
public Matrix(Reader r)
       throws Exception
```
    Reads a matrix from a reader. The first line in the file should contain the number of rows and columns. Subsequent lines contain elements of the matrix. (FracPete: taken from old weka.core.Matrix class)
    
    Parameters:
    r - the reader containing the matrix
    
    Throws:
    
    Exception - if an error occurs
    See Also:
    write(Writer)
- Method Detail
  - constructWithCopy
```
public static Matrix constructWithCopy(double[][] A)
```
    Construct a matrix from a copy of a 2-D array.
    
    Parameters:
    A - Two-dimensional array of doubles.
    
    Throws:
    
    IllegalArgumentException - All rows must have the same length
  - copy
```
public Matrix copy()
```
    Make a deep copy of a matrix
  - clone
```
public Object clone()
```
    Clone the Matrix object.
    
    Overrides:
    
    clone in class Object
  - getArray
```
public double[][] getArray()
```
    Access the internal two-dimensional array.
    
    Returns:
    Pointer to the two-dimensional array of matrix elements.
  - getArrayCopy
```
public double[][] getArrayCopy()
```
    Copy the internal two-dimensional array.
    
    Returns:
    Two-dimensional array copy of matrix elements.
  - getColumnPackedCopy
```
public double[] getColumnPackedCopy()
```
    Make a one-dimensional column packed copy of the internal array.
    
    Returns:
    Matrix elements packed in a one-dimensional array by columns.
  - getRowPackedCopy
```
public double[] getRowPackedCopy()
```
    Make a one-dimensional row packed copy of the internal array.
    
    Returns:
    Matrix elements packed in a one-dimensional array by rows.
  - getRowDimension
```
public int getRowDimension()
```
    Get row dimension.
    
    Returns:
    m, the number of rows.
  - getColumnDimension
```
public int getColumnDimension()
```
    Get column dimension.
    
    Returns:
    n, the number of columns.
  - get
```
public double get(int i,
         int j)
```
    Get a single element.
    
    Parameters:
    i - Row index.
    j - Column index.
    
    Returns:
    A(i,j)
    
    Throws:
    
    ArrayIndexOutOfBoundsException
  - getMatrix
```
public Matrix getMatrix(int i0,
               int i1,
               int j0,
               int j1)
```
    Get a submatrix.
    
    Parameters:
    i0 - Initial row index
    i1 - Final row index
    j0 - Initial column index
    j1 - Final column index
    
    Returns:
    A(i0:i1,j0:j1)
    
    Throws:
    
    ArrayIndexOutOfBoundsException - Submatrix indices
  - getMatrix
```
public Matrix getMatrix(int[] r,
               int[] c)
```
    Get a submatrix.
    
    Parameters:
    r - Array of row indices.
    c - Array of column indices.
    
    Returns:
    A(r(:),c(:))
    
    Throws:
    
    ArrayIndexOutOfBoundsException - Submatrix indices
  - getMatrix
```
public Matrix getMatrix(int i0,
               int i1,
               int[] c)
```
    Get a submatrix.
    
    Parameters:
    i0 - Initial row index
    i1 - Final row index
    c - Array of column indices.
    
    Returns:
    A(i0:i1,c(:))
    
    Throws:
    
    ArrayIndexOutOfBoundsException - Submatrix indices
  - getMatrix
```
public Matrix getMatrix(int[] r,
               int j0,
               int j1)
```
    Get a submatrix.
    
    Parameters:
    r - Array of row indices.
    j0 - Initial column index
    j1 - Final column index
    
    Returns:
    A(r(:),j0:j1)
    
    Throws:
    
    ArrayIndexOutOfBoundsException - Submatrix indices
  - set
```
public void set(int i,
       int j,
       double s)
```
    Set a single element.
    
    Parameters:
    i - Row index.
    j - Column index.
    s - A(i,j).
    
    Throws:
    
    ArrayIndexOutOfBoundsException
  - setMatrix
```
public void setMatrix(int i0,
             int i1,
             int j0,
             int j1,
             Matrix X)
```
    Set a submatrix.
    
    Parameters:
    i0 - Initial row index
    i1 - Final row index
    j0 - Initial column index
    j1 - Final column index
    X - A(i0:i1,j0:j1)
    
    Throws:
    
    ArrayIndexOutOfBoundsException - Submatrix indices
  - setMatrix
```
public void setMatrix(int[] r,
             int[] c,
             Matrix X)
```
    Set a submatrix.
    
    Parameters:
    r - Array of row indices.
    c - Array of column indices.
    X - A(r(:),c(:))
    
    Throws:
    
    ArrayIndexOutOfBoundsException - Submatrix indices
  - setMatrix
```
public void setMatrix(int[] r,
             int j0,
             int j1,
             Matrix X)
```
    Set a submatrix.
    
    Parameters:
    r - Array of row indices.
    j0 - Initial column index
    j1 - Final column index
    X - A(r(:),j0:j1)
    
    Throws:
    
    ArrayIndexOutOfBoundsException - Submatrix indices
  - setMatrix
```
public void setMatrix(int i0,
             int i1,
             int[] c,
             Matrix X)
```
    Set a submatrix.
    
    Parameters:
    i0 - Initial row index
    i1 - Final row index
    c - Array of column indices.
    X - A(i0:i1,c(:))
    
    Throws:
    
    ArrayIndexOutOfBoundsException - Submatrix indices
  - isSymmetric
```
public boolean isSymmetric()
```
    Returns true if the matrix is symmetric. (FracPete: taken from old weka.core.Matrix class)
    
    Returns:
    boolean true if matrix is symmetric.
  - isSquare
```
public boolean isSquare()
```
    returns whether the matrix is a square matrix or not.
    
    Returns:
    true if the matrix is a square matrix
  - transpose
```
public Matrix transpose()
```
    Matrix transpose.
    
    Returns:
    A'
  - norm1
```
public double norm1()
```
    One norm
    
    Returns:
    maximum column sum.
  - norm2
```
public double norm2()
```
    Two norm
    
    Returns:
    maximum singular value.
  - normInf
```
public double normInf()
```
    Infinity norm
    
    Returns:
    maximum row sum.
  - normF
```
public double normF()
```
    Frobenius norm
    
    Returns:
    sqrt of sum of squares of all elements.
  - uminus
```
public Matrix uminus()
```
    Unary minus
    
    Returns:
    -A
  - plus
```
public Matrix plus(Matrix B)
```
    C = A + B
    
    Parameters:
    B - another matrix
    
    Returns:
    A + B
  - plusEquals
```
public Matrix plusEquals(Matrix B)
```
    A = A + B
    
    Parameters:
    B - another matrix
    
    Returns:
    A + B
  - minus
```
public Matrix minus(Matrix B)
```
    C = A - B
    
    Parameters:
    B - another matrix
    
    Returns:
    A - B
  - minusEquals
```
public Matrix minusEquals(Matrix B)
```
    A = A - B
    
    Parameters:
    B - another matrix
    
    Returns:
    A - B
  - arrayTimes
```
public Matrix arrayTimes(Matrix B)
```
    Element-by-element multiplication, C = A.*B
    
    Parameters:
    B - another matrix
    
    Returns:
    A.*B
  - arrayTimesEquals
```
public Matrix arrayTimesEquals(Matrix B)
```
    Element-by-element multiplication in place, A = A.*B
    
    Parameters:
    B - another matrix
    
    Returns:
    A.*B
  - arrayRightDivide
```
public Matrix arrayRightDivide(Matrix B)
```
    Element-by-element right division, C = A./B
    
    Parameters:
    B - another matrix
    
    Returns:
    A./B
  - arrayRightDivideEquals
```
public Matrix arrayRightDivideEquals(Matrix B)
```
    Element-by-element right division in place, A = A./B
    
    Parameters:
    B - another matrix
    
    Returns:
    A./B
  - arrayLeftDivide
```
public Matrix arrayLeftDivide(Matrix B)
```
    Element-by-element left division, C = A.\B
    
    Parameters:
    B - another matrix
    
    Returns:
    A.\B
  - arrayLeftDivideEquals
```
public Matrix arrayLeftDivideEquals(Matrix B)
```
    Element-by-element left division in place, A = A.\B
    
    Parameters:
    B - another matrix
    
    Returns:
    A.\B
  - times
```
public Matrix times(double s)
```
    Multiply a matrix by a scalar, C = s*A
    
    Parameters:
    s - scalar
    
    Returns:
    s*A
  - timesEquals
```
public Matrix timesEquals(double s)
```
    Multiply a matrix by a scalar in place, A = s*A
    
    Parameters:
    s - scalar
    
    Returns:
    replace A by s*A
  - times
```
public Matrix times(Matrix B)
```
    Linear algebraic matrix multiplication, A * B
    
    Parameters:
    B - another matrix
    
    Returns:
    Matrix product, A * B
    
    Throws:
    
    IllegalArgumentException - Matrix inner dimensions must agree.
  - lu
```
public LUDecomposition lu()
```
    LU Decomposition
    
    Returns:
    LUDecomposition
    See Also:
    LUDecomposition
  - qr
```
public QRDecomposition qr()
```
    QR Decomposition
    
    Returns:
    QRDecomposition
    See Also:
    QRDecomposition
  - chol
```
public CholeskyDecomposition chol()
```
    Cholesky Decomposition
    
    Returns:
    CholeskyDecomposition
    See Also:
    CholeskyDecomposition
  - svd
```
public SingularValueDecomposition svd()
```
    Singular Value Decomposition
    
    Returns:
    SingularValueDecomposition
    See Also:
    SingularValueDecomposition
  - eig
```
public EigenvalueDecomposition eig()
```
    Eigenvalue Decomposition
    
    Returns:
    EigenvalueDecomposition
    See Also:
    EigenvalueDecomposition
  - solve
```
public Matrix solve(Matrix B)
```
    Solve A*X = B
    
    Parameters:
    B - right hand side
    
    Returns:
    solution if A is square, least squares solution otherwise
  - solveTranspose
```
public Matrix solveTranspose(Matrix B)
```
    Solve X*A = B, which is also A'*X' = B'
    
    Parameters:
    B - right hand side
    
    Returns:
    solution if A is square, least squares solution otherwise.
  - inverse
```
public Matrix inverse()
```
    Matrix inverse or pseudoinverse
    
    Returns:
    inverse(A) if A is square, pseudoinverse otherwise.
  - sqrt
```
public Matrix sqrt()
```
    returns the square root of the matrix, i.e., X from the equation X*X = A.
    Steps in the Calculation (see sqrtm in Matlab):
    1. perform eigenvalue decomposition
      [V,D]=eig(A)
    2. take the square root of all elements in D (only the ones with positive sign are considered for further computation)
      S=sqrt(D)
    3. calculate the root
      X=V*S/V, which can be also written as X=(V'\(V*S)')'
    Note: since this method uses other high-level methods, it generates several instances of matrices. This can be problematic with large matrices.
    Examples:
    1. X = 5 -4 1 0 0 -4 6 -4 1 0 1 -4 6 -4 1 0 1 -4 6 -4 0 0 1 -4 5 sqrt(X) = 2 -1 -0 -0 -0 -1 2 -1 0 -0 0 -1 2 -1 0 -0 0 -1 2 -1 -0 -0 -0 -1 2 Matrix m = new Matrix(new double[][]{{5,-4,1,0,0},{-4,6,-4,1,0},{1,-4,6,-4,1},{0,1,-4,6,-4},{0,0,1,-4,5}});
    2. X = 7 10 15 22 sqrt(X) = 1.5667 1.7408 2.6112 4.1779 Matrix m = new Matrix(new double[][]{{7, 10},{15, 22}});
    Returns:
    sqrt(A)
  - regression
```
public LinearRegression regression(Matrix y,
                          double ridge)
```
    Performs a (ridged) linear regression. (FracPete: taken from old weka.core.Matrix class)
    
    Parameters:
    y - the dependent variable vector
    ridge - the ridge parameter
    
    Returns:
    the coefficients
    
    Throws:
    
    IllegalArgumentException - if not successful
  - regression
```
public final LinearRegression regression(Matrix y,
                          double[] w,
                          double ridge)
```
    Performs a weighted (ridged) linear regression. (FracPete: taken from old weka.core.Matrix class)
    
    Parameters:
    y - the dependent variable vector
    w - the array of data point weights
    ridge - the ridge parameter
    
    Returns:
    the coefficients
    
    Throws:
    
    IllegalArgumentException - if the wrong number of weights were provided.
  - det
```
public double det()
```
    Matrix determinant
    
    Returns:
    determinant
  - rank
```
public int rank()
```
    Matrix rank
    
    Returns:
    effective numerical rank, obtained from SVD.
  - cond
```
public double cond()
```
    Matrix condition (2 norm)
    
    Returns:
    ratio of largest to smallest singular value.
  - trace
```
public double trace()
```
    Matrix trace.
    
    Returns:
    sum of the diagonal elements.
  - random
```
public static Matrix random(int m,
            int n)
```
    Generate matrix with random elements
    
    Parameters:
    m - Number of rows.
    n - Number of colums.
    
    Returns:
    An m-by-n matrix with uniformly distributed random elements.
  - identity
```
public static Matrix identity(int m,
              int n)
```
    Generate identity matrix
    
    Parameters:
    m - Number of rows.
    n - Number of colums.
    
    Returns:
    An m-by-n matrix with ones on the diagonal and zeros elsewhere.
  - print
```
public void print(int w,
         int d)
```
    Print the matrix to stdout. Line the elements up in columns with a Fortran-like 'Fw.d' style format.
    
    Parameters:
    w - Column width.
    d - Number of digits after the decimal.
  - print
```
public void print(PrintWriter output,
         int w,
         int d)
```
    Print the matrix to the output stream. Line the elements up in columns with a Fortran-like 'Fw.d' style format.
    
    Parameters:
    output - Output stream.
    w - Column width.
    d - Number of digits after the decimal.
  - print
```
public void print(NumberFormat format,
         int width)
```
    Print the matrix to stdout. Line the elements up in columns. Use the format object, and right justify within columns of width characters. Note that is the matrix is to be read back in, you probably will want to use a NumberFormat that is set to US Locale.
    
    Parameters:
    format - A Formatting object for individual elements.
    width - Field width for each column.
    See Also:
    DecimalFormat.setDecimalFormatSymbols(java.text.DecimalFormatSymbols)
  - print
```
public void print(PrintWriter output,
         NumberFormat format,
         int width)
```
    Print the matrix to the output stream. Line the elements up in columns. Use the format object, and right justify within columns of width characters. Note that is the matrix is to be read back in, you probably will want to use a NumberFormat that is set to US Locale.
    
    Parameters:
    output - the output stream.
    format - A formatting object to format the matrix elements
    width - Column width.
    See Also:
    DecimalFormat.setDecimalFormatSymbols(java.text.DecimalFormatSymbols)
  - read
```
public static Matrix read(BufferedReader input)
                   throws IOException
```
    Read a matrix from a stream. The format is the same the print method, so printed matrices can be read back in (provided they were printed using US Locale). Elements are separated by whitespace, all the elements for each row appear on a single line, the last row is followed by a blank line.
    Note: This format differs from the one that can be read via the Matrix(Reader) constructor! For that format, the write(Writer) method is used (from the original weka.core.Matrix class).
    
    Parameters:
    input - the input stream.
    
    Throws:
    
    IOException
    See Also:
    Matrix(Reader), write(Writer)
  - write
```
public void write(Writer w)
           throws Exception
```
    Writes out a matrix. The format can be read via the Matrix(Reader) constructor. (FracPete: taken from old weka.core.Matrix class)
    
    Parameters:
    w - the output Writer
    
    Throws:
    
    Exception - if an error occurs
    See Also:
    Matrix(Reader)
  - toString
```
public String toString()
```
    Converts a matrix to a string. (FracPete: taken from old weka.core.Matrix class)
    
    Overrides:
    
    toString in class Object
    
    Returns:
    the converted string
  - toMatlab
```
public String toMatlab()
```
    converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
    
    Returns:
    the matrix in Matlab single line format
  - parseMatlab
```
public static Matrix parseMatlab(String matlab)
                          throws Exception
```
    creates a matrix from the given Matlab string.
    
    Parameters:
    matlab - the matrix in matlab format
    
    Returns:
    the matrix represented by the given string
    
    Throws:
    
    Exception
    See Also:
    toMatlab()
  - getRevision
```
public String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Returns:
    the revision
  - main
```
public static void main(String[] args)
```
    Main method for testing this class.

Class Matrix

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Matrix

Matrix

Matrix

Matrix

Matrix

Matrix

Method Detail

constructWithCopy

copy

clone

getArray

getArrayCopy

getColumnPackedCopy

getRowPackedCopy

getRowDimension

getColumnDimension

get

getMatrix

getMatrix

getMatrix

getMatrix

set

setMatrix

setMatrix

setMatrix

setMatrix

isSymmetric

isSquare

transpose

norm1

norm2

normInf

normF

uminus

plus

plusEquals

minus

minusEquals

arrayTimes

arrayTimesEquals

arrayRightDivide

arrayRightDivideEquals

arrayLeftDivide

arrayLeftDivideEquals

times

timesEquals

times

lu

qr

chol

svd

eig

solve

solveTranspose

inverse

sqrt

regression

regression

det

rank

cond

trace

random

identity

print

print

print

print

read

write

toString

toMatlab

parseMatlab

getRevision

main