mikera.arrayz.NDArray Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of vectorz Show documentation
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.arrayz;

import java.nio.DoubleBuffer;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Iterator;
import java.util.List;

import mikera.arrayz.impl.BaseNDArray;
import mikera.arrayz.impl.IStridedArray;
import mikera.arrayz.impl.ImmutableArray;
import mikera.matrixx.Matrix;
import mikera.matrixx.Matrixx;
import mikera.vectorz.AVector;
import mikera.vectorz.IOperator;
import mikera.vectorz.Op;
import mikera.vectorz.Vector;
import mikera.vectorz.Vectorz;
import mikera.vectorz.impl.ArrayIndexScalar;
import mikera.vectorz.impl.ArraySubVector;
import mikera.vectorz.impl.SingleDoubleIterator;
import mikera.vectorz.impl.Vector0;
import mikera.vectorz.util.ErrorMessages;
import mikera.vectorz.util.IntArrays;
import mikera.vectorz.util.VectorzException;

/**
 * General purpose dense strided NDArray class.
 * 
 * Allows arbitrary strided access over a dense double[] array.
 * 
 * @author Mike
 *
 */
public final class NDArray extends BaseNDArray {
	private static final long serialVersionUID = -262272579159731240L;

	NDArray(int... shape) {
		super(new double[(int)IntArrays.arrayProduct(shape)],
				shape.length,
				0,
				shape,
				IntArrays.calcStrides(shape));
	}
	
	NDArray(double[] data, int offset, int[] shape, int[] stride) {
		this(data,shape.length,offset,shape,stride);
	}
	
	NDArray(double[] data, int dimensions, int offset, int[] shape, int[] stride) {
		super(data,shape.length,offset,shape,stride);
	}
	
	public static NDArray wrap(double[] data, int[] shape) {
		int dims=shape.length;
		return new NDArray(data,dims,0,shape,IntArrays.calcStrides(shape));
	}
	
	public static NDArray wrap(Vector v) {
		return wrap(v.getArray(),v.getShape());
	}

	public static NDArray wrap(Matrix m) {
		return wrap(m.data,m.getShape());
	}
	
	public static NDArray wrap(IStridedArray a) {
		return new NDArray(a.getArray(),a.getArrayOffset(),a.getShape(),a.getStrides());
	}
	
	public static NDArray wrap(INDArray a) {
		if (!(a instanceof IStridedArray)) throw new IllegalArgumentException(a.getClass()+" is not a strided array!");
		return wrap((IStridedArray)a);
	}
	
	public static NDArray newArray(int... shape) {
		return new NDArray(shape);
	}
	
	@Override
	public void set(double value) {
		if (dimensions==0) {
			data[offset]=value;
		} else if (dimensions==1) {
			int n=sliceCount();
			int st=getStride(0);
			for (int i=0; i getSlices() {
		if (dimensions==0) {
			throw new IllegalArgumentException(ErrorMessages.noSlices(this));
		} else {
			int n=getShape(0);
			ArrayList al=new ArrayList(n);
			for (int i=0; i elementIterator() {
		if (dimensionality()==0) {
			return new SingleDoubleIterator(data[offset]);
		} else {
			return super.elementIterator();
		}
	}
	
	@Override public void validate() {
		if (dimensions>shape.length) throw new VectorzException("Insufficient shape data");
		if (dimensions>stride.length) throw new VectorzException("Insufficient stride data");
		
		if ((offset<0)||(offset>=data.length)) throw new VectorzException("Offset out of bounds");
		int[] endIndex=IntArrays.decrementAll(shape);
		int endOffset=offset+IntArrays.dotProduct(endIndex, stride);
		if ((endOffset<0)||(endOffset>data.length)) throw new VectorzException("End offset out of bounds");
		super.validate();
	}
	
	@Override
	public INDArray immutable() {
		return ImmutableArray.create(this);
	}

	@Override
	public double[] getArray() {
		return data;
	}

	public static INDArray wrapStrided(double[] data, int offset,
			int[] shape, int[] strides) {
		return new NDArray(data,offset,shape,strides);
	}
}