package Jama;
import java.text.NumberFormat;
import java.text.DecimalFormat;
import java.text.DecimalFormatSymbols;
import java.util.Locale;
import java.text.FieldPosition;
import java.io.PrintWriter;
import java.io.BufferedReader;
import java.io.StreamTokenizer;
import Jama.util.*;
/**
Jama = Java Matrix class.
<P>
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.
<P>
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:
<P><UL>
<LI>Cholesky Decomposition of symmetric, positive definite matrices.
<LI>LU Decomposition of rectangular matrices.
<LI>QR Decomposition of rectangular matrices.
<LI>Singular Value Decomposition of rectangular matrices.
<LI>Eigenvalue Decomposition of both symmetric and nonsymmetric square matrices.
</UL>
<DL>
<DT><B>Example of use:</B></DT>
<P>
<DD>Solve a linear system A x = b and compute the residual norm, ||b - A x||.
<P><PRE>
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();
</PRE></DD>
</DL>
@author The MathWorks, Inc. and the National Institute of Standards and Technology.
@version 5 August 1998
*/
public class jMatrix implements Cloneable, java.io.Serializable {
/* ------------------------
Class variables
* ------------------------ */
/** Array for internal storage of elements.
@serial internal array storage.
*/
private double[][] A;
/** Row and column dimensions.
@serial row dimension.
@serial column dimension.
*/
private int m, n;
/* ------------------------
Constructors
* ------------------------ */
/** Construct an m-by-n matrix of zeros.
@param m Number of rows.
@param n Number of colums.
*/
public jMatrix (int m, int n) {
this.m = m;
this.n = n;
A = new double[m][n];
}
/** Construct an m-by-n constant matrix.
@param m Number of rows.
@param n Number of colums.
@param s Fill the matrix with this scalar value.
*/
public jMatrix (int m, int n, double s) {
this.m = m;
this.n = n;
A = new double[m][n];
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
A[i][j] = s;
}
}
}
/** Construct a matrix from a 2-D array.
@param A Two-dimensional array of doubles.
@exception IllegalArgumentException All rows must have the same length
@see #constructWithCopy
*/
public jMatrix (double[][] A) {
m = A.length;
n = A[0].length;
for (int i = 0; i < m; i++) {
if (A[i].length != n) {
throw new IllegalArgumentException("All rows must have the same length.");
}
}
this.A = A;
}
/** Construct a matrix quickly without checking arguments.
@param A Two-dimensional array of doubles.
@param m Number of rows.
@param n Number of colums.
*/
public jMatrix (double[][] A, int m, int n) {
this.A = A;
this.m = m;
this.n = n;
}
/** Construct a matrix from a one-dimensional packed array
@param vals One-dimensional array of doubles, packed by columns (ala Fortran).
@param m Number of rows.
@exception IllegalArgumentException Array length must be a multiple of m.
*/
public jMatrix (double vals[], int m) {
this.m = m;
n = (m != 0 ? vals.length/m : 0);
if (m*n != vals.length) {
throw new IllegalArgumentException("Array length must be a multiple of m.");
}
A = new double[m][n];
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
A[i][j] = vals[i+j*m];
}
}
}
/* ------------------------
Public Methods
* ------------------------ */
/** Construct a matrix from a copy of a 2-D array.
@param A Two-dimensional array of doubles.
@exception IllegalArgumentException All rows must have the same length
*/
public static jMatrix constructWithCopy(double[][] A) {
int m = A.length;
int n = A[0].length;
jMatrix X = new jMatrix(m,n);
double[][] C = X.getArray();
for (int i = 0; i < m; i++) {
if (A[i].length != n) {
throw new IllegalArgumentException
("All rows must have the same length.");
}
for (int j = 0; j < n; j++) {
C[i][j] = A[i][j];
}
}
return X;
}
/** Make a deep copy of a matrix
*/
public jMatrix copy () {
jMatrix X = new jMatrix(m,n);
double[][] C = X.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[i][j] = A[i][j];
}
}
return X;
}
/** Clone the Matrix object.
*/
public Object clone () {
return this.copy();
}
/** Access the internal two-dimensional array.
@return Pointer to the two-dimensional array of matrix elements.
*/
public double[][] getArray () {
return A;
}
/** Copy the internal two-dimensional array.
@return Two-dimensional array copy of matrix elements.
*/
public double[][] getArrayCopy () {
double[][] C = new double[m][n];
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[i][j] = A[i][j];
}
}
return C;
}
/** Make a one-dimensional column packed copy of the internal array.
@return Matrix elements packed in a one-dimensional array by columns.
*/
public double[] getColumnPackedCopy () {
double[] vals = new double[m*n];
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
vals[i+j*m] = A[i][j];
}
}
return vals;
}
public int getColumnsNumber() {
return n;
}
/** Make a one-dimensional row packed copy of the internal array.
@return Matrix elements packed in a one-dimensional array by rows.
*/
public double[] getRowPackedCopy () {
double[] vals = new double[m*n];
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
vals[i*n+j] = A[i][j];
}
}
return vals;
}
/** Get row dimension.
@return m, the number of rows.
*/
public int getRowDimension () {
return m;
}
/** Get column dimension.
@return n, the number of columns.
*/
public int getColumnDimension () {
return n;
}
/** Get a single element.
@param i Row index.
@param j Column index.
@return A(i,j)
@exception ArrayIndexOutOfBoundsException
*/
public double get (int i, int j) {
return A[i][j];
}
/** Get a submatrix.
@param i0 Initial row index
@param i1 Final row index
@param j0 Initial column index
@param j1 Final column index
@return A(i0:i1,j0:j1)
@exception ArrayIndexOutOfBoundsException Submatrix indices
*/
public jMatrix getMatrix (int i0, int i1, int j0, int j1) {
jMatrix X = new jMatrix(i1-i0+1,j1-j0+1);
double[][] B = X.getArray();
try {
for (int i = i0; i <= i1; i++) {
for (int j = j0; j <= j1; j++) {
B[i-i0][j-j0] = A[i][j];
}
}
} catch(ArrayIndexOutOfBoundsException e) {
throw new ArrayIndexOutOfBoundsException("Submatrix indices");
}
return X;
}
/** Get a submatrix.
@param r Array of row indices.
@param c Array of column indices.
@return A(r(:),c(:))
@exception ArrayIndexOutOfBoundsException Submatrix indices
*/
public jMatrix getMatrix (int[] r, int[] c) {
jMatrix X = new jMatrix(r.length,c.length);
double[][] B = X.getArray();
try {
for (int i = 0; i < r.length; i++) {
for (int j = 0; j < c.length; j++) {
B[i][j] = A[r[i]][c[j]];
}
}
} catch(ArrayIndexOutOfBoundsException e) {
throw new ArrayIndexOutOfBoundsException("Submatrix indices");
}
return X;
}
/** Get a submatrix.
@param i0 Initial row index
@param i1 Final row index
@param c Array of column indices.
@return A(i0:i1,c(:))
@exception ArrayIndexOutOfBoundsException Submatrix indices
*/
public jMatrix getMatrix (int i0, int i1, int[] c) {
jMatrix X = new jMatrix(i1-i0+1,c.length);
double[][] B = X.getArray();
try {
for (int i = i0; i <= i1; i++) {
for (int j = 0; j < c.length; j++) {
B[i-i0][j] = A[i][c[j]];
}
}
} catch(ArrayIndexOutOfBoundsException e) {
throw new ArrayIndexOutOfBoundsException("Submatrix indices");
}
return X;
}
/** Get a submatrix.
@param r Array of row indices.
@param i0 Initial column index
@param i1 Final column index
@return A(r(:),j0:j1)
@exception ArrayIndexOutOfBoundsException Submatrix indices
*/
public jMatrix getMatrix (int[] r, int j0, int j1) {
jMatrix X = new jMatrix(r.length,j1-j0+1);
double[][] B = X.getArray();
try {
for (int i = 0; i < r.length; i++) {
for (int j = j0; j <= j1; j++) {
B[i][j-j0] = A[r[i]][j];
}
}
} catch(ArrayIndexOutOfBoundsException e) {
throw new ArrayIndexOutOfBoundsException("Submatrix indices");
}
return X;
}
public int getRowsNumber() {
return m;
}
/** Set a single element.
@param i Row index.
@param j Column index.
@param s A(i,j).
@exception ArrayIndexOutOfBoundsException
*/
public void set (int i, int j, double s) {
A[i][j] = s;
}
/** Set a submatrix.
@param i0 Initial row index
@param i1 Final row index
@param j0 Initial column index
@param j1 Final column index
@param X A(i0:i1,j0:j1)
@exception ArrayIndexOutOfBoundsException Submatrix indices
*/
public void setMatrix (int i0, int i1, int j0, int j1, jMatrix X) {
try {
for (int i = i0; i <= i1; i++) {
for (int j = j0; j <= j1; j++) {
A[i][j] = X.get(i-i0,j-j0);
}
}
} catch(ArrayIndexOutOfBoundsException e) {
throw new ArrayIndexOutOfBoundsException("Submatrix indices");
}
}
/** Set a submatrix.
@param r Array of row indices.
@param c Array of column indices.
@param X A(r(:),c(:))
@exception ArrayIndexOutOfBoundsException Submatrix indices
*/
public void setMatrix (int[] r, int[] c, jMatrix X) {
try {
for (int i = 0; i < r.length; i++) {
for (int j = 0; j < c.length; j++) {
A[r[i]][c[j]] = X.get(i,j);
}
}
} catch(ArrayIndexOutOfBoundsException e) {
throw new ArrayIndexOutOfBoundsException("Submatrix indices");
}
}
/** Set a submatrix.
@param r Array of row indices.
@param j0 Initial column index
@param j1 Final column index
@param X A(r(:),j0:j1)
@exception ArrayIndexOutOfBoundsException Submatrix indices
*/
public void setMatrix (int[] r, int j0, int j1, jMatrix X) {
try {
for (int i = 0; i < r.length; i++) {
for (int j = j0; j <= j1; j++) {
A[r[i]][j] = X.get(i,j-j0);
}
}
} catch(ArrayIndexOutOfBoundsException e) {
throw new ArrayIndexOutOfBoundsException("Submatrix indices");
}
}
/** Set a submatrix.
@param i0 Initial row index
@param i1 Final row index
@param c Array of column indices.
@param X A(i0:i1,c(:))
@exception ArrayIndexOutOfBoundsException Submatrix indices
*/
public void setMatrix (int i0, int i1, int[] c, jMatrix X) {
try {
for (int i = i0; i <= i1; i++) {
for (int j = 0; j < c.length; j++) {
A[i][c[j]] = X.get(i-i0,j);
}
}
} catch(ArrayIndexOutOfBoundsException e) {
throw new ArrayIndexOutOfBoundsException("Submatrix indices");
}
}
/** Matrix transpose.
@return A'
*/
public jMatrix transpose () {
jMatrix X = new jMatrix(n,m);
double[][] C = X.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[j][i] = A[i][j];
}
}
return X;
}
/** One norm
@return maximum column sum.
*/
public double norm1 () {
double f = 0;
for (int j = 0; j < n; j++) {
double s = 0;
for (int i = 0; i < m; i++) {
s += Math.abs(A[i][j]);
}
f = Math.max(f,s);
}
return f;
}
/** Two norm
@return maximum singular value.
*/
public double norm2 () {
return (new JamaSingularValueDecomposition(this).norm2());
}
/** Infinity norm
@return maximum row sum.
*/
public double normInf () {
double f = 0;
for (int i = 0; i < m; i++) {
double s = 0;
for (int j = 0; j < n; j++) {
s += Math.abs(A[i][j]);
}
f = Math.max(f,s);
}
return f;
}
/** Frobenius norm
@return sqrt of sum of squares of all elements.
*/
public double normF () {
double f = 0;
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
f = Maths.hypot(f,A[i][j]);
}
}
return f;
}
/** Unary minus
@return -A
*/
public jMatrix uminus () {
jMatrix X = new jMatrix(m,n);
double[][] C = X.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[i][j] = -A[i][j];
}
}
return X;
}
/** C = A + B
@param B another matrix
@return A + B
*/
public jMatrix plus (jMatrix B) {
checkMatrixDimensions(B);
jMatrix X = new jMatrix(m,n);
double[][] C = X.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[i][j] = A[i][j] + B.A[i][j];
}
}
return X;
}
/** A = A + B
@param B another matrix
@return A + B
*/
public jMatrix plusEquals (jMatrix B) {
checkMatrixDimensions(B);
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
A[i][j] = A[i][j] + B.A[i][j];
}
}
return this;
}
/** C = A - B
@param B another matrix
@return A - B
*/
public jMatrix minus (jMatrix B) {
checkMatrixDimensions(B);
jMatrix X = new jMatrix(m,n);
double[][] C = X.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[i][j] = A[i][j] - B.A[i][j];
}
}
return X;
}
/** A = A - B
@param B another matrix
@return A - B
*/
public jMatrix minusEquals (jMatrix B) {
checkMatrixDimensions(B);
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
A[i][j] = A[i][j] - B.A[i][j];
}
}
return this;
}
/** Element-by-element multiplication, C = A.*B
@param B another matrix
@return A.*B
*/
public jMatrix arrayTimes (jMatrix B) {
checkMatrixDimensions(B);
jMatrix X = new jMatrix(m,n);
double[][] C = X.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[i][j] = A[i][j] * B.A[i][j];
}
}
return X;
}
/** Element-by-element multiplication in place, A = A.*B
@param B another matrix
@return A.*B
*/
public jMatrix arrayTimesEquals (jMatrix B) {
checkMatrixDimensions(B);
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
A[i][j] = A[i][j] * B.A[i][j];
}
}
return this;
}
/** Element-by-element right division, C = A./B
@param B another matrix
@return A./B
*/
public jMatrix arrayRightDivide (jMatrix B) {
checkMatrixDimensions(B);
jMatrix X = new jMatrix(m,n);
double[][] C = X.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[i][j] = A[i][j] / B.A[i][j];
}
}
return X;
}
/** Element-by-element right division in place, A = A./B
@param B another matrix
@return A./B
*/
public jMatrix arrayRightDivideEquals (jMatrix B) {
checkMatrixDimensions(B);
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
A[i][j] = A[i][j] / B.A[i][j];
}
}
return this;
}
/** Element-by-element left division, C = A.\B
@param B another matrix
@return A.\B
*/
public jMatrix arrayLeftDivide (jMatrix B) {
checkMatrixDimensions(B);
jMatrix X = new jMatrix(m,n);
double[][] C = X.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[i][j] = B.A[i][j] / A[i][j];
}
}
return X;
}
/** Element-by-element left division in place, A = A.\B
@param B another matrix
@return A.\B
*/
public jMatrix arrayLeftDivideEquals (jMatrix B) {
checkMatrixDimensions(B);
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
A[i][j] = B.A[i][j] / A[i][j];
}
}
return this;
}
/** Multiply a matrix by a scalar, C = s*A
@param s scalar
@return s*A
*/
public jMatrix times (double s) {
jMatrix X = new jMatrix(m,n);
double[][] C = X.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
C[i][j] = s*A[i][j];
}
}
return X;
}
/** Multiply a matrix by a scalar in place, A = s*A
@param s scalar
@return replace A by s*A
*/
public jMatrix timesEquals (double s) {
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
A[i][j] = s*A[i][j];
}
}
return this;
}
/** Linear algebraic matrix multiplication, A * B
@param B another matrix
@return Matrix product, A * B
@exception IllegalArgumentException Matrix inner dimensions must agree.
*/
public jMatrix times (jMatrix B) {
if (B.m != n) {
throw new IllegalArgumentException("Matrix inner dimensions must agree.");
}
jMatrix X = new jMatrix(m,B.n);
double[][] C = X.getArray();
double[] Bcolj = new double[n];
for (int j = 0; j < B.n; j++) {
for (int k = 0; k < n; k++) {
Bcolj[k] = B.A[k][j];
}
for (int i = 0; i < m; i++) {
double[] Arowi = A[i];
double s = 0;
for (int k = 0; k < n; k++) {
s += Arowi[k]*Bcolj[k];
}
C[i][j] = s;
}
}
return X;
}
/** LU Decomposition
@return LUDecomposition
@see LUDecomposition
*/
public JamaLUDecomposition lu () {
return new JamaLUDecomposition(this);
}
/** QR Decomposition
@return QRDecomposition
@see QRDecomposition
*/
public JamaQRDecomposition qr () {
return new JamaQRDecomposition(this);
}
/** Cholesky Decomposition
@return CholeskyDecomposition
@see CholeskyDecomposition
*/
public JamaCholeskyDecomposition chol () {
return new JamaCholeskyDecomposition(this);
}
/** Singular Value Decomposition
@return SingularValueDecomposition
@see SingularValueDecomposition
*/
public JamaSingularValueDecomposition svd () {
return new JamaSingularValueDecomposition(this);
}
/** Eigenvalue Decomposition
@return EigenvalueDecomposition
@see EigenvalueDecomposition
*/
public JamaEigenvalueDecomposition eig () {
return new JamaEigenvalueDecomposition(this);
}
/** Solve A*X = B
@param B right hand side
@return solution if A is square, least squares solution otherwise
*/
public jMatrix solve (jMatrix B) {
return (m == n ? (new JamaLUDecomposition(this)).solve(B) :
(new JamaQRDecomposition(this)).solve(B));
}
/** Solve X*A = B, which is also A'*X' = B'
@param B right hand side
@return solution if A is square, least squares solution otherwise.
*/
public jMatrix solveTranspose (jMatrix B) {
return transpose().solve(B.transpose());
}
/** Matrix inverse or pseudoinverse
@return inverse(A) if A is square, pseudoinverse otherwise.
*/
public jMatrix inverse () {
return solve(identity(m,m));
}
/** Matrix determinant
@return determinant
*/
public double det () {
return new JamaLUDecomposition(this).det();
}
/** Matrix rank
@return effective numerical rank, obtained from SVD.
*/
public int rank () {
return new JamaSingularValueDecomposition(this).rank();
}
/** Matrix condition (2 norm)
@return ratio of largest to smallest singular value.
*/
public double cond () {
return new JamaSingularValueDecomposition(this).cond();
}
/** Matrix trace.
@return sum of the diagonal elements.
*/
public double trace () {
double t = 0;
for (int i = 0; i < Math.min(m,n); i++) {
t += A[i][i];
}
return t;
}
/** Generate matrix with random elements
@param m Number of rows.
@param n Number of colums.
@return An m-by-n matrix with uniformly distributed random elements.
*/
public static jMatrix random (int m, int n) {
jMatrix A = new jMatrix(m,n);
double[][] X = A.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
X[i][j] = Math.random();
}
}
return A;
}
/** Generate identity matrix
@param m Number of rows.
@param n Number of colums.
@return An m-by-n matrix with ones on the diagonal and zeros elsewhere.
*/
public static jMatrix identity (int m, int n) {
jMatrix A = new jMatrix(m,n);
double[][] X = A.getArray();
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
X[i][j] = (i == j ? 1.0 : 0.0);
}
}
return A;
}
/** Print the matrix to stdout. Line the elements up in columns
* with a Fortran-like 'Fw.d' style format.
@param w Column width.
@param d Number of digits after the decimal.
*/
public void print (int w, int d) {
print(new PrintWriter(System.out,true),w,d); }
/** Print the matrix to the output stream. Line the elements up in
* columns with a Fortran-like 'Fw.d' style format.
@param output Output stream.
@param w Column width.
@param d Number of digits after the decimal.
*/
public void print (PrintWriter output, int w, int d) {
DecimalFormat format = new DecimalFormat();
format.setDecimalFormatSymbols(new DecimalFormatSymbols(Locale.US));
format.setMinimumIntegerDigits(1);
format.setMaximumFractionDigits(d);
format.setMinimumFractionDigits(d);
format.setGroupingUsed(false);
print(output,format,w+2);
}
/** 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.
@param format A Formatting object for individual elements.
@param width Field width for each column.
@see java.text.DecimalFormat#setDecimalFormatSymbols
*/
public void print (NumberFormat format, int width) {
print(new PrintWriter(System.out,true),format,width); }
// DecimalFormat is a little disappointing coming from Fortran or C's printf.
// Since it doesn't pad on the left, the elements will come out different
// widths. Consequently, we'll pass the desired column width in as an
// argument and do the extra padding ourselves.
/** 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.
@param output the output stream.
@param format A formatting object to format the matrix elements
@param width Column width.
@see java.text.DecimalFormat#setDecimalFormatSymbols
*/
public void print (PrintWriter output, NumberFormat format, int width) {
output.println(); // start on new line.
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
String s = format.format(A[i][j]); // format the number
int padding = Math.max(1,width-s.length()); // At _least_ 1 space
for (int k = 0; k < padding; k++)
output.print(' ');
output.print(s);
}
output.println();
}
output.println(); // end with blank line.
}
/** 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.
@param input the input stream.
*/
public static jMatrix read (BufferedReader input) throws java.io.IOException {
StreamTokenizer tokenizer= new StreamTokenizer(input);
// Although StreamTokenizer will parse numbers, it doesn't recognize
// scientific notation (E or D); however, Double.valueOf does.
// The strategy here is to disable StreamTokenizer's number parsing.
// We'll only get whitespace delimited words, EOL's and EOF's.
// These words should all be numbers, for Double.valueOf to parse.
tokenizer.resetSyntax();
tokenizer.wordChars(0,255);
tokenizer.whitespaceChars(0, ' ');
tokenizer.eolIsSignificant(true);
java.util.Vector v = new java.util.Vector();
// Ignore initial empty lines
while (tokenizer.nextToken() == StreamTokenizer.TT_EOL);
if (tokenizer.ttype == StreamTokenizer.TT_EOF)
throw new java.io.IOException("Unexpected EOF on matrix read.");
do {
v.addElement(Double.valueOf(tokenizer.sval)); // Read & store 1st row.
} while (tokenizer.nextToken() == StreamTokenizer.TT_WORD);
int n = v.size(); // Now we've got the number of columns!
double row[] = new double[n];
for (int j=0; j<n; j++) // extract the elements of the 1st row.
row[j]=((Double)v.elementAt(j)).doubleValue();
v.removeAllElements();
v.addElement(row); // Start storing rows instead of columns.
while (tokenizer.nextToken() == StreamTokenizer.TT_WORD) {
// While non-empty lines
v.addElement(row = new double[n]);
int j = 0;
do {
if (j >= n) throw new java.io.IOException
("Row " + v.size() + " is too long.");
row[j++] = Double.valueOf(tokenizer.sval).doubleValue();
} while (tokenizer.nextToken() == StreamTokenizer.TT_WORD);
if (j < n) throw new java.io.IOException
("Row " + v.size() + " is too short.");
}
int m = v.size(); // Now we've got the number of rows.
double[][] A = new double[m][];
v.copyInto(A); // copy the rows out of the vector
return new jMatrix(A);
}
/* ------------------------
Private Methods
* ------------------------ */
/** Check if size(A) == size(B) **/
private void checkMatrixDimensions (jMatrix B) {
if (B.m != m || B.n != n) {
throw new IllegalArgumentException("Matrix dimensions must agree.");
}
}
}