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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.vectorz.impl;

import mikera.indexz.Index;
import mikera.matrixx.AMatrix;
import mikera.matrixx.impl.AVectorMatrix;
import mikera.vectorz.AVector;
import mikera.vectorz.Op;
import mikera.vectorz.Vector;
import mikera.vectorz.util.DoubleArrays;
import mikera.vectorz.util.ErrorMessages;
import mikera.vectorz.util.VectorzException;

/**
 * Indexed sparse immutable vector
 * 
 * Efficient for sparse vectors. Maintains a indexed array of strictly non-zero elements. 
 * 
 * Guaranteed to contain at least one non-sparse index value
 * 
 * @author Mike
 *
 */
public class SparseImmutableVector extends ASparseIndexedVector {
	private static final long serialVersionUID = 750093598603613879L;

	private final Index index;
	private final double[] data;
	private final int dataLength;
	
	private SparseImmutableVector(int length, Index index) {
		this(length,index,new double[index.length()]);
	}
	
	private SparseImmutableVector(int length, Index index, double[] nonSparseValues) {
		super(length);
		this.index=index;
		this.data=nonSparseValues;
		dataLength=nonSparseValues.length;
	}
	
	private SparseImmutableVector(int length, Index index, AVector nonSparseValues) {
		this(length,index,nonSparseValues.toDoubleArray());
	}
	
	/**
	 * Creates a SparseImmutableVector with the specified index and data values.
	 * 
	 * WARNING: Performs no checking - Index must be distinct and sorted, and data must be non-zero.
	 */
	public static SparseImmutableVector wrap(int length, Index index, double[] nonSparseValues) {
		assert(index.length()==nonSparseValues.length);
		assert(index.isDistinctSorted());
		return new SparseImmutableVector(length, index,nonSparseValues);
	}
	
	@Override
	double[] internalData() {
		return data;
	}

	@Override
	Index internalIndex() {
		return index;
	}
	
	/**
	 * Creates a SparseImmutableVector using the given sorted Index to identify the indexes of non-zero values,
	 * and a double[] array to specify all the non-zero element values
	 */
	public static AVector create(int length, Index sparseIndex, double[] sparseValues) {
		int dataLength=sparseValues.length;
		if (!sparseIndex.isDistinctSorted()) {
			throw new IllegalArgumentException("Index must be sorted and distinct");
		}
		if (!(sparseIndex.length()==dataLength)) {
			throw new IllegalArgumentException("Length of index: mismatch woth data");			
		}
		if (dataLength==0) return ZeroVector.create(length);
		if (dataLength==length) return ImmutableVector.create(sparseValues);
		return new SparseImmutableVector(length, sparseIndex.clone(),DoubleArrays.copyOf(sparseValues));
	}
	
	/**
	 * Creates a SparseImmutableVector using the given sorted Index to identify the indexes of non-zero values,
	 * and a dense vector to specify all the non-zero element values
	 */
	public static AVector create(int length, Index sparseIndex, AVector sparseValues) {
		int dataLength=sparseValues.length();
		if (!sparseIndex.isDistinctSorted()) {
			throw new IllegalArgumentException("Index must be sorted and distinct");
		}
		if (!(sparseIndex.length()==dataLength)) {
			throw new IllegalArgumentException("Length of index: mismatch woth data");			
		}
		if (dataLength==0) return ZeroVector.create(length);
		if (dataLength==length) return ImmutableVector.create(sparseValues);
		return wrap(length, sparseIndex.clone(), sparseValues.toDoubleArray());
	}
	
	/** 
	 * Creates a sparse immutable vector from the given vector, ignoring the zeros in the source.
	 * 
	 */
	public static AVector create(AVector source) {
		int length = source.length();
		if (length==0) return Vector0.INSTANCE;
		
		int dataLength=(int) source.nonZeroCount();
		if (dataLength==0) return ZeroVector.create(length);
		if (dataLength*3>=length) return ImmutableVector.create(source); // no point making sparse
		
		int[] indexes=new int[dataLength];
		double[] vals=new double[dataLength];
		int pos=0;
		for (int i=0; iresult) result=d; 
		}
		return result;
	}
	
	@Override
	public int maxElementIndex(){
		double result=data[0];
		int di=0;
		for (int i=1; iresult) {
				result=d; 
				di=i;
			}
		}
		if (result<0.0) { // see if we can find a zero element
			int ind=index.findMissing();
			if (ind>=0) return ind;
		}
		return index.get(di);
	}
	
 
	@Override
	public int maxAbsElementIndex(){
		double result=Math.abs(data[0]);
		int di=0;
		for (int i=1; iresult) {
				result=d; 
				di=i;
			}
		}
		return index.get(di);
	}
	
	@Override
	public int minElementIndex(){
		double result=data[0];
		int di=0;
		for (int i=1; i0.0) { // see if we can find a zero element
			int ind=index.findMissing();
			if (ind>=0) return ind;
		}
		return index.get(di);
	}
	
	@Override
	public void negate() {
		throw new UnsupportedOperationException(ErrorMessages.immutable(this));
	}
	
	@Override
	public void applyOp(Op op) {
		throw new UnsupportedOperationException(ErrorMessages.immutable(this));
	}
	
	@Override
	public void abs() {
		throw new UnsupportedOperationException(ErrorMessages.immutable(this));
	}

	@Override
	public double get(int i) {
		checkIndex(i);
		return unsafeGet(i);
	}
	
	@Override
	public double unsafeGet(int i) {
		int ip=index.indexPosition(i);
		if (ip<0) return 0.0;
		return data[ip];
	}
	
	@Override
	public boolean isFullyMutable() {
		return false;
	}
	
	@Override
	public boolean isMutable() {
		return false;
	}
	
	@Override
	public long nonZeroCount() {
		return dataLength;
	}
	
	@Override
	public int[] nonZeroIndices() {
		return index.data.clone();
	}

	@Override
	public void add(ASparseVector v) {
		throw new UnsupportedOperationException(ErrorMessages.immutable(this));
	}
	
	@Override
	public void set(AVector v) {
		throw new UnsupportedOperationException(ErrorMessages.immutable(this));
	}

	@Override
	public void set(int i, double value) {
		throw new UnsupportedOperationException(ErrorMessages.immutable(this));

	}
	
	@Override
	public void addAt(int i, double value) {
		throw new UnsupportedOperationException(ErrorMessages.immutable(this));
	}

	@Override
	public Vector nonSparseValues() {
		return Vector.wrap(data);
	}
	
	@Override
	public double[] nonZeroValues() {
		return DoubleArrays.copyOf(data);
	}
	
	@Override
	public Index nonSparseIndex() {
		return index;
	}

	@Override
	public boolean includesIndex(int i) {
		return index.indexPosition(i)>=0;
	}
	
	@Override
	public Vector dense() {
		Vector v=Vector.createLength(length);
		addToArray(v.data,0);
		return v;
	}
	
	@Override
	public SparseIndexedVector mutable() {
		return SparseIndexedVector.create(length, index, data);
	}
	
	@Override
	public SparseIndexedVector clone() {
		return SparseIndexedVector.create(length, index, data);
	}
	
	@Override
	public SparseIndexedVector sparseClone() {
		return SparseIndexedVector.create(length, index, data);
	}
	
	@Override
	public SparseImmutableVector exactClone() {
		return new SparseImmutableVector(length,index.clone(),data.clone());
	}
	
	@Override
	public void validate() {
		if (data.length==0) throw new VectorzException("SparseImmutableVector must have some non-zero values");
		if (index.length()!=data.length) throw new VectorzException("Inconsistent data and index!");
		if (!index.isDistinctSorted()) throw new VectorzException("Invalid index: "+index);
		for (int i=0; i