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Fast double-precision vector and matrix maths library for Java, supporting N-dimensional numeric arrays.
There is a newer version: 0.67.0
package mikera.matrixx.impl;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

import mikera.arrayz.INDArray;
import mikera.arrayz.ISparse;
import mikera.matrixx.AMatrix;
import mikera.matrixx.Matrixx;
import mikera.vectorz.AVector;
import mikera.vectorz.Vector;
import mikera.vectorz.Vectorz;
import mikera.vectorz.impl.IndexedElementVisitor;
import mikera.vectorz.impl.GrowableIndexedVector;
import mikera.vectorz.impl.SingleElementVector;
import mikera.vectorz.impl.SparseIndexedVector;
import mikera.vectorz.impl.ZeroVector;
import mikera.vectorz.util.ErrorMessages;
import mikera.vectorz.util.VectorzException;

/**
 * Matrix stored as a collection of normally sparse row vectors.
 * 
 * This format is especially efficient for:
 * - innerProduct() with another matrix, especially one with efficient
 *   column access like SparseColumnMatrix
 * - access via getRow() operation
 * - transpose into SparseColumnMatrix
 * 
 * @author Mike
 * 
 */
public class SparseRowMatrix extends ASparseRCMatrix implements ISparse, IFastRows {
	private static final long serialVersionUID = 8646257152425415773L;

	private static final long SPARSE_ELEMENT_THRESHOLD = 1000L;
	
	private final AVector emptyRow;

	protected SparseRowMatrix(int rowCount, int columnCount) {
		this(new AVector[rowCount],rowCount,columnCount);
	}

	protected SparseRowMatrix(AVector[] data, int rowCount, int columnCount) {
		super(rowCount,columnCount,data);
        if (data.length != rowCount)
            throw new IllegalArgumentException(ErrorMessages.incompatibleShapes(rowCount, data.length));
		emptyRow=Vectorz.createZeroVector(columnCount);
	}

	protected SparseRowMatrix(AVector... vectors) {
		this(vectors, vectors.length, vectors[0].length());
	}

	protected SparseRowMatrix(List data, int rowCount, int columnCount) {
		this(data.toArray(new AVector[0]),rowCount,columnCount);
	}

	protected SparseRowMatrix(List data) {
		this(data.toArray(new AVector[0]));
	}

//  	protected SparseRowMatrix(HashMap data, int rowCount, int columnCount) {
//  		super(rowCount,columnCount,data);
//  		emptyColumn=Vectorz.createZeroVector(rowCount);
//  	}

	public static SparseRowMatrix create(int rows, int cols) {
		return new SparseRowMatrix(rows, cols);
	}

	public static SparseRowMatrix create(AVector[] data, int rows, int cols) {
		return new SparseRowMatrix(data, rows, cols);
	}

	public static SparseRowMatrix create(AVector... vecs) {
		return new SparseRowMatrix(vecs);
        // don't validate; user can call validate() if they want it.
	}
	
	public static SparseRowMatrix create(List rows) {
		return create(rows.toArray(new AVector[rows.size()]));
	}
	
	public static INDArray create(ArrayList slices, int rows, int cols) {
		AVector[] vecs=new AVector[rows];
		for (int i=0; i rows=source.getRows();
		for (int i = 0; i < rc; i++) {
			AVector row = rows.get(i);
			if (!row.isZero()) {
			    data[i] = Vectorz.createSparse(row);
			}
		}
		return SparseRowMatrix.wrap(data,rc,cc);
	}

	public static SparseRowMatrix wrap(List vecs) {
		return create(vecs);
	}
	
//	public static SparseRowMatrix wrap(HashMap data, int rows, int cols) {
//		return new SparseRowMatrix(data, rows, cols);
//	}

	@Override
	public int componentCount() {
		return rows;
	}
	
	@Override
	public AVector getComponent(int k) {
		AVector v=data[k];
		if (v==null) return emptyRow;
		return v;
	}

	@Override
	protected int lineLength() {
		return cols;
	}

	@Override
	public double get(int i, int j) {
		return getRow(i).get(j);
	}

	@Override
	public void set(int i, int j, double value) {
		checkIndex(i,j);
		unsafeSet(i,j,value);
	}

	@Override
	public double unsafeGet(int row, int column) {
		return getRow(row).unsafeGet(column);
	}

	@Override
	public void unsafeSet(int i, int j, double value) {
		AVector v = unsafeGetVector(i);
		if (v == null) {
			if (value == 0.0)
				return;
			v = SingleElementVector.create(value, j, cols);
		} else if (v.isFullyMutable()) {
			v.set(j, value);
			return;
		} else {
			v = v.sparseClone();
			v.unsafeSet(j, value);
		}
		unsafeSetVec(i, v);
	}
	
	@Override
	public void set(AMatrix a) {
		checkSameShape(a);
		List srows=a.getRows();
		for (int i=0; i getColumns() {
    	// initial arraylist with nulls for each column
        final ArrayList columns=new ArrayList();
        for (int j=0; j getRows() {
        ArrayList rowList = new ArrayList(rows);
		for (int i = 0; i < rows; i++) {
            AVector v = unsafeGetVector(i);
            if (v == null) v=emptyRow;
            rowList.add(v);
        }
		return rowList;
	}
	
	@Override
	public AVector getRowView(int i) {
		return ensureMutableRow(i);
	}
	
	@Override
	public boolean isUpperTriangular() {
		int rc=rowCount();
		for (int i=1; i mrows=m.getRows();
		for (int i=0; i