JSci.maths.matrices.DoubleSparseMatrix Maven / Gradle / Ivy
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JSci is a set of open source Java packages. The aim is to encapsulate scientific methods/principles in the most natural way possible. As such they should greatly aid the development of scientific based software.
It offers: abstract math interfaces, linear algebra (support for various matrix and vector types), statistics (including probability distributions), wavelets, newtonian mechanics, chart/graph components (AWT and Swing), MathML DOM implementation, ...
Note: some packages, like javax.comm, for the astro and instruments package aren't listed as dependencies (not available).
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package JSci.maths.matrices;
import JSci.GlobalSettings;
import JSci.maths.Mapping;
import JSci.maths.DimensionException;
import JSci.maths.vectors.AbstractDoubleVector;
import JSci.maths.vectors.DoubleVector;
import JSci.maths.vectors.DoubleSparseVector;
/**
* The DoubleSparseMatrix class provides an object for encapsulating sparse matrices.
* Uses compressed row storage (Yale sparse matrix format).
* @version 1.4
* @author Mark Hale
*/
public final class DoubleSparseMatrix extends AbstractDoubleMatrix {
/**
* Matrix elements.
*/
private double elements[];
/**
* Sparse indexing data.
* Contains the column positions of each element,
* e.g. colPos[n] is the column position
* of the nth element.
*/
private int colPos[];
/**
* Sparse indexing data.
* Contains the indices of the start of each row,
* e.g. rows[i] is the index
* where the ith row starts.
*/
private int rows[];
/**
* Amount by which to increase the capacity.
*/
private int capacityIncrement = 1;
/**
* Constructs an empty matrix.
* @param rowCount the number of rows
* @param colCount the number of columns
*/
public DoubleSparseMatrix(final int rowCount, final int colCount) {
super(rowCount, colCount);
elements=new double[0];
colPos=new int[0];
rows=new int[numRows+1];
}
public DoubleSparseMatrix(final int rowCount, final int colCount, int capacityIncrement) {
this(rowCount, colCount);
this.capacityIncrement = capacityIncrement;
}
/**
* Constructs a matrix from an array.
* @param array an assigned value
*/
public DoubleSparseMatrix(final double array[][]) {
super(array.length,array[0].length);
rows=new int[numRows+1];
int n=0;
for(int i=0;iGlobalSettings.ZERO_TOL)
n++;
}
}
elements=new double[n];
colPos=new int[n];
n=0;
for(int i=0;iGlobalSettings.ZERO_TOL) {
elements[n]=array[i][j];
colPos[n]=j;
n++;
}
}
}
rows[numRows]=n;
}
/**
* Compares two double sparse matrices for equality.
* @param m a double matrix
*/
public boolean equals(AbstractDoubleMatrix m, double tol) {
if(numRows==m.numRows && numCols==m.numCols) {
if(m instanceof DoubleSparseMatrix) {
return this.equals((DoubleSparseMatrix)m);
} else {
double sumSqr = 0;
for(int i=0;i=0 && i=0 && j=0 && i=0 && j GlobalSettings.ZERO_TOL) {
// expand
if(rows[numRows] == elements.length) {
// increase capacity
final double oldMatrix[]=elements;
final int oldColPos[]=colPos;
elements=new double[oldMatrix.length+capacityIncrement];
colPos=new int[oldColPos.length+capacityIncrement];
System.arraycopy(oldMatrix,0,elements,0,p);
System.arraycopy(oldColPos,0,colPos,0,p);
System.arraycopy(oldMatrix,p,elements,p+1,oldMatrix.length-p);
System.arraycopy(oldColPos,p,colPos,p+1,oldColPos.length-p);
} else {
System.arraycopy(elements,p,elements,p+1,rows[numRows]-p);
System.arraycopy(colPos,p,colPos,p+1,rows[numRows]-p);
}
elements[p]=x;
colPos[p]=j;
for(int k=i+1;k
-norm.
*/
public double infNorm() {
double result=0.0,tmpResult;
for(int i=0;iresult)
result=tmpResult;
}
return result;
}
/**
* Returns the Frobenius (l2) norm.
*/
public double frobeniusNorm() {
double result=0.0;
for(int i=0;i