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Posted to dev@commons.apache.org by Bill Barker <wb...@wilshire.com> on 2009/02/01 01:39:45 UTC
Re: svn commit: r739504 - in /commons/proper/math/trunk/src: java/org/apache/commons/math/linear/SparseRealVector.java test/org/apache/commons/math/linear/SparseRealVectorTest.java
I've added constructors to specify epsilon. There is now a use-case to make
espilon final (and not give developers enough rope to hang themselves with).
Need to think a bit more about optimized add. Yes, there are some
inconsistancies due to not having a lot of spare-cycles, and so changing my
mind on the best way to do things :(. I've already promised to clean the
code up, but since 2.0 isn't releasing soon, wanted some community input.
Thanks for that.
<lu...@free.fr> wrote in message
news:1381411758.9235141233414794480.JavaMail.root@spooler6-g27.priv.proxad.net...
Here are my comments.
The two isZero methods seem inconsistent with each other. If I explicitely
set a component to epsilon/2 at index i, then isZero(i) would be false (the
element is set) but isZero(getEntry(i)) would be true.
It would be nice to be able to set epsilon at construction. If for example I
want to build a vector from an array filtering out the small values,
currently I need to first build an empty vector, then set epsilon, then fill
the vector with my array.
In the optimized version of add(SparseRealVector), I wonder if the call to
res.set which either calls entries.put or entries.remove could not
invalidate the iterator. After a quick look, it seems OK (findInsertionIndex
in OpenIntToDoubleHashMap should always return a negative value and
newMapping should be always reset to false), but I'm not sure and this seems
to really be implementation dependent.
In the add, subtract and ebeXxx methods, the result vector is first built as
a copy of the instance and later all its elements are overwritten. The
initial copy could probably be avoided by simply iterating on the instance
by itself and setting the elements of an initially empty vector, built with
the advanced use constructor with both expected size and dimension.
This is a nice work, thanks
Luc
----- billbarker@apache.org a �crit :
> Author: billbarker
> Date: Sat Jan 31 04:51:17 2009
> New Revision: 739504
>
> URL: http://svn.apache.org/viewvc?rev=739504&view=rev
> Log:
> Initial checkin for the SparseRealVectorClass.
>
> I know that it doesn't work 100% with the map*** methods that
> shouldn't be used with a sparse vector. I'll clean those up shortly
> (including uncommenting unit tests). Just want to get more eyes on
> this for the methods that matter.
>
> Added:
>
> commons/proper/math/trunk/src/java/org/apache/commons/math/linear/SparseRealVector.java
>
> commons/proper/math/trunk/src/test/org/apache/commons/math/linear/SparseRealVectorTest.java
>
> Added:
> commons/proper/math/trunk/src/java/org/apache/commons/math/linear/SparseRealVector.java
> URL:
> http://svn.apache.org/viewvc/commons/proper/math/trunk/src/java/org/apache/commons/math/linear/SparseRealVector.java?rev=739504&view=auto
> ==============================================================================
> ---
> commons/proper/math/trunk/src/java/org/apache/commons/math/linear/SparseRealVector.java
> (added)
> +++
> commons/proper/math/trunk/src/java/org/apache/commons/math/linear/SparseRealVector.java
> Sat Jan 31 04:51:17 2009
> @@ -0,0 +1,1176 @@
> +/*
> + * Licensed to the Apache Software Foundation (ASF) under one or
> more
> + * contributor license agreements. See the NOTICE file distributed
> with
> + * this work for additional information regarding copyright
> ownership.
> + * The ASF licenses this file to You under the Apache License,
> Version 2.0
> + * (the "License"); you may not use this file except in compliance
> with
> + * the License. You may obtain a copy of the License at
> + *
> + * http://www.apache.org/licenses/LICENSE-2.0
> + *
> + * Unless required by applicable law or agreed to in writing,
> software
> + * distributed under the License is distributed on an "AS IS" BASIS,
> + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
> implied.
> + * See the License for the specific language governing permissions
> and
> + * limitations under the License.
> + */
> +package org.apache.commons.math.linear;
> +
> +import org.apache.commons.math.MathRuntimeException;
> +import org.apache.commons.math.util.OpenIntToDoubleHashMap;
> +import org.apache.commons.math.util.OpenIntToDoubleHashMap.Iterator;
> +
> +/**
> + * This class implements the {@link RealVector} interface with a
> {@link OpenIntToDoubleHashMap}.
> + * @version $Revision: 728186 $ $Date: 2008-12-19 16:03:13 -0800
> (Fri, 19 Dec 2008) $
> + * @since 2.0
> +*/
> +public class SparseRealVector implements RealVector {
> +
> + private OpenIntToDoubleHashMap entries;
> + private final int virtualSize;
> + private double epsilon = 1.0e-12;
> +
> + /**
> + * Build a 0-length vector.
> + * <p>Zero-length vectors may be used to initialized construction
> of vectors
> + * by data gathering. We start with zero-length and use either
> the {@link
> + * #SparseRealVector(SparseRealVecotr, int)} constructor
> + * or one of the <code>append</code> method ({@link
> #append(double)}, {@link
> + * #append(double[])}, {@link #append(RealVectorImpl)}) to gather
> data
> + * into this vector.</p>
> + */
> + public SparseRealVector() {
> + virtualSize = 0;
> + entries = new OpenIntToDoubleHashMap(0.0);
> + }
> +
> + /**
> + * Construct a (size)-length vector of zeros.
> + * @param dimension size of the vector
> + */
> + public SparseRealVector(int dimension) {
> + virtualSize = dimension;
> + entries = new OpenIntToDoubleHashMap(0.0);
> + }
> +
> + /**
> + * Resize the vector, for use with append
> + * @param v The original vector
> + * @param resize The amount to resize it
> + */
> + protected SparseRealVector(SparseRealVector v, int resize) {
> + virtualSize = v.getDimension() + resize;
> + entries = new OpenIntToDoubleHashMap(v.entries);
> + }
> +
> + /**
> + * For advanced use, when you know the sparseness
> + * @param dimension The size of the vector
> + * @param expectedSize The excpected number of non-zer entries
> + */
> + public SparseRealVector(int dimension, int expectedSize) {
> + entries = new OpenIntToDoubleHashMap(expectedSize, 0.0);
> + virtualSize = dimension;
> + }
> +
> + /**
> + * Create from a double array.
> + * only non-zero entries will be stored
> + * @param values The set of values to create from
> + */
> + public SparseRealVector(double[] values) {
> + virtualSize = values.length;
> + fromDoubleArray(values);
> + }
> +
> + /**
> + * Create from a Double array.
> + * Only non-zero entries will be stored
> + * @param values The set of values to create from
> + */
> + public SparseRealVector(Double [] values) {
> + virtualSize = values.length;
> + double[] vals = new double[values.length];
> + for(int i=0; i < values.length; i++){
> + vals[i] = values[i];
> + }
> + fromDoubleArray(vals);
> + }
> +
> + /**
> + * Copy constructer
> + * @param v The instance to copy from
> + */
> + public SparseRealVector(SparseRealVector v){
> + virtualSize = v.getDimension();
> + epsilon = v.getEpsilon();
> + entries = new OpenIntToDoubleHashMap(v.getEntries());
> + }
> +
> + /**
> + * Generic copy constructer
> + * @param v The instance to copy from
> + */
> + public SparseRealVector(RealVector v) {
> + virtualSize = v.getDimension();
> + fromDoubleArray(v.getData());
> + }
> +
> +
> + /**
> + * Fill in the values from a double array
> + * @param values The set of values to use
> + */
> + private void fromDoubleArray(double[] values) {
> + entries = new OpenIntToDoubleHashMap(0.0);
> + for (int key = 0; key < values.length; key++) {
> + double value = values[key];
> + if (!isZero(value)) {
> + entries.put(key, value);
> + }
> + }
> + }
> +
> + /**
> + *
> + * @return The entries of this instance
> + */
> + private OpenIntToDoubleHashMap getEntries() {
> + return entries;
> + }
> +
> + /**
> + * Determine if this index value is zero
> + * @param key The index to text
> + * @return <code>true</code> if this index is missing from the
> map, <code>false</code> otherwise
> + */
> + protected boolean isZero(int key) {
> + return !entries.containsKey(key);
> + }
> +
> + /**
> + * Determine if this value is zero
> + * @param value The value to test
> + * @return <code>true</code> if this value is zero,
> <code>false</code> otherwise
> + */
> + protected boolean isZero(double value) {
> + return value > -epsilon && value < epsilon;
> + }
> +
> + /**
> + *
> + * @return The test range for testing if a value is zero
> + */
> + public double getEpsilon() {
> + return epsilon;
> + }
> +
> + /**
> + *
> + * @param epsilon The test range for testing if a value is zero
> + */
> + public void setEpsilon(double epsilon) {
> + this.epsilon = epsilon;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector add(RealVector v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.getDimension());
> + if (v instanceof SparseRealVector)
> + return add((SparseRealVector) v);
> + return add(v.getData());
> +
> + }
> +
> + /**
> + * Optimized method to add two SparseRealVectors
> + * @param v Vector to add with
> + * @return The sum of <code>this</code> with <code>v</code>
> + */
> + public SparseRealVector add(SparseRealVector v) {
> + SparseRealVector res = (SparseRealVector) copy();
> + Iterator iter = res.getEntries().iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + int key = iter.key();
> + if (v.getEntries().containsKey(key)) {
> + res.set(key, iter.value() + v.getEntry(key));
> + }
> + }
> + iter = v.getEntries().iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + int key = iter.key();
> + if (!entries.containsKey(key)) {
> + res.set(key, iter.value());
> + }
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector add(double[] v) throws IllegalArgumentException
> {
> + checkVectorDimensions(v.length);
> + SparseRealVector res = new SparseRealVector(getDimension());
> + for (int i = 0; i < v.length; i++) {
> + res.set(i, v[i] + getEntry(i));
> + }
> + return res;
> + }
> +
> + /**
> + * Optimized method to append a SparseRealVector
> + * @param v vector to append
> + * @return The result of appending <code>v</code> to self
> + */
> + public SparseRealVector append(SparseRealVector v) {
> + SparseRealVector res = new SparseRealVector(this,
> v.getDimension());
> + Iterator iter = v.entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + res.set(iter.key() + virtualSize, iter.value());
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector append(RealVector v) {
> + if (v instanceof SparseRealVector) {
> + return append((SparseRealVector) v);
> + }
> + return append(v.getData());
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector append(double d) {
> + RealVector res = new SparseRealVector(this, 1);
> + res.set(virtualSize, d);
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector append(double[] a) {
> + RealVector res = new SparseRealVector(this, a.length);
> + for (int i = 0; i < a.length; i++) {
> + res.set(i + virtualSize, a[i]);
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector copy() {
> + return new SparseRealVector(this);
> + }
> +
> + /** {@inheritDoc} */
> + public double dotProduct(RealVector v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.getDimension());
> + double res = 0;
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + res += v.getEntry(iter.key()) * iter.value();
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public double dotProduct(double[] v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.length);
> + double res = 0;
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + int idx = iter.key();
> + double value = 0;
> + if (idx < v.length)
> + value = v[idx];
> + res += value * iter.value();
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector ebeDivide(RealVector v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.getDimension());
> + SparseRealVector res = new SparseRealVector(this);
> + Iterator iter = res.entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + res.set(iter.key(), iter.value() /
> v.getEntry(iter.key()));
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector ebeDivide(double[] v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.length);
> + SparseRealVector res = new SparseRealVector(this);
> + Iterator iter = res.entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + res.set(iter.key(), iter.value() / v[iter.key()]);
> + }
> + return null;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector ebeMultiply(RealVector v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.getDimension());
> + SparseRealVector res = new SparseRealVector(this);
> + Iterator iter = res.entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + res.set(iter.key(), iter.value() *
> v.getEntry(iter.key()));
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector ebeMultiply(double[] v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.length);
> + SparseRealVector res = new SparseRealVector(this);
> + Iterator iter = res.entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + res.set(iter.key(), iter.value() * v[iter.key()]);
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector get(int index, int n) throws
> MatrixIndexException {
> + checkIndex(index);
> + checkIndex(index+n-1);
> + SparseRealVector res = new SparseRealVector(n);
> + int end = index + n;
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + int key = iter.key();
> + if (key >= index && key < end) {
> + res.set(key - index, iter.value());
> + }
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public double[] getData() {
> + double[] res = new double[virtualSize];
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + res[iter.key()] = iter.value();
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public int getDimension() {
> + return virtualSize;
> + }
> +
> + /**
> + * Optimized method to compute distance
> + * @param v The vector to compute distance to
> + * @return The distance from <code>this</code> and
> <code>v</code>
> + */
> + public double getDistance(SparseRealVector v) {
> + Iterator iter = entries.iterator();
> + double res = 0;
> + while (iter.hasNext()) {
> + iter.advance();
> + int key = iter.key();
> + double delta;
> + delta = iter.value() - v.getEntry(key);
> + res += delta * delta;
> + }
> + iter = v.getEntries().iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + int key = iter.key();
> + if (!entries.containsKey(key)) {
> + res += iter.value() * iter.value();
> + }
> + }
> + return Math.sqrt(res);
> + }
> +
> + /** {@inheritDoc} */
> + public double getDistance(RealVector v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.getDimension());
> + if (v instanceof SparseRealVector) {
> + return getDistance((SparseRealVector) v);
> + }
> + return getDistance(v.getData());
> + }
> +
> + /** {@inheritDoc} */
> + public double getDistance(double[] v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.length);
> + double res = 0;
> + for (int i = 0; i < v.length; i++) {
> + double delta = entries.get(i) - v[i];
> + res += delta * delta;
> + }
> + return Math.sqrt(res);
> + }
> +
> + /** {@inheritDoc} */
> + public double getEntry(int index) throws MatrixIndexException {
> + checkIndex(index);
> + return entries.get(index);
> + }
> +
> + /** {@inheritDoc} */
> + public double getL1Distance(SparseRealVector v) {
> + double max = 0;
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + double delta = Math.abs(iter.value() -
> v.getEntry(iter.key()));
> + max += delta;
> + }
> + iter = v.getEntries().iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + int key = iter.key();
> + if (!entries.containsKey(key)) {
> + double delta = Math.abs(iter.value());
> + max += Math.abs(delta);
> + }
> + }
> + return max;
> + }
> +
> + /** {@inheritDoc} */
> + public double getL1Distance(RealVector v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.getDimension());
> + if (v instanceof SparseRealVector) {
> + return getL1Distance((SparseRealVector) v);
> + }
> + return getL1Distance(v.getData());
> + }
> +
> + /** {@inheritDoc} */
> + public double getL1Distance(double[] v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.length);
> + double max = 0;
> + for (int i = 0; i < v.length; i++) {
> + double delta = Math.abs(getEntry(i) - v[i]);
> + max += delta;
> + }
> + return max;
> + }
> +
> + /** {@inheritDoc} */
> + public double getL1Norm() {
> + double res = 0;
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + res += Math.abs(iter.value());
> + }
> + return res;
> + }
> +
> + /**
> + * Optimized method to compute LInfDistance
> + * @param v The vector to compute from
> + * @return the LInfDistance
> + */
> + private double getLInfDistance(SparseRealVector v) {
> + double max = 0;
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + double delta = Math.abs(iter.value() -
> v.getEntry(iter.key()));
> + if(delta > max)
> + max = delta;
> + }
> + iter = v.getEntries().iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + int key = iter.key();
> + if (!entries.containsKey(key)) {
> + if(iter.value() > max)
> + max = iter.value();
> + }
> + }
> + return max;
> + }
> +
> + /** {@inheritDoc} */
> + public double getLInfDistance(RealVector v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.getDimension());
> + if (v instanceof SparseRealVector) {
> + return getLInfDistance((SparseRealVector) v);
> + }
> + return getLInfDistance(v.getData());
> + }
> +
> + /** {@inheritDoc} */
> + public double getLInfDistance(double[] v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.length);
> + double max = 0;
> + for (int i = 0; i < v.length; i++) {
> + double delta = Math.abs(getEntry(i) - v[i]);
> + if(delta > max)
> + max = delta;
> + }
> + return max;
> + }
> +
> + /** {@inheritDoc} */
> + public double getLInfNorm() {
> + double max = 0;
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + max += iter.value();
> + }
> + return max;
> + }
> +
> + /** {@inheritDoc} */
> + public double getNorm() {
> + double res = 0;
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + res += iter.value() * iter.value();
> + }
> + return Math.sqrt(res);
> + }
> +
> + /** {@inheritDoc} */
> + public boolean isInfinite() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + if (Double.isInfinite(iter.value()))
> + return true;
> + }
> + return false;
> + }
> +
> + /** {@inheritDoc} */
> + public boolean isNaN() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + if (Double.isNaN(iter.value()))
> + return true;
> + }
> + return false;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapAbs() {
> + return copy().mapAbsToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapAbsToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.abs(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapAcos() {
> + return copy().mapAcosToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapAcosToSelf() {
> + for(int i=0; i < virtualSize; i++){
> + set(i, Math.acos(getEntry(i)));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapAdd(double d) {
> + return copy().mapAddToSelf(d);
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapAddToSelf(double d) {
> + for (int i = 0; i < virtualSize; i++) {
> + set(i, getEntry(i) + d);
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapAsin() {
> + return copy().mapAsinToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapAsinToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.asin(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapAtan() {
> + return copy().mapAtanToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapAtanToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.atan(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapCbrt() {
> + return copy().mapCbrtToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapCbrtToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.cbrt(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapCeil() {
> + return copy().mapCeilToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapCeilToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.ceil(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapCos() {
> + return copy().mapCosToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapCosToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.cos(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapCosh() {
> + return copy().mapCoshToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapCoshToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.cosh(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapDivide(double d) {
> + return copy().mapDivideToSelf(d);
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapDivideToSelf(double d) {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), iter.value() / d);
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapExp() {
> + return copy().mapExpToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapExpToSelf() {
> + for (int i = 0; i < virtualSize; i++) {
> + entries.put(i, Math.exp(entries.get(i)));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapExpm1() {
> + return copy().mapExpm1ToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapExpm1ToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.expm1(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapFloor() {
> + return copy().mapFloorToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapFloorToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.floor(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapInv() {
> + return copy().mapInvToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapInvToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), 1 / iter.value());
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapLog() {
> + return copy().mapLogToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapLog10() {
> + return copy().mapLog10ToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapLog10ToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.log10(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapLog1p() {
> + return copy().mapLog1pToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapLog1pToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.log1p(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapLogToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.log(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapMultiply(double d) {
> + return copy().mapMultiplyToSelf(d);
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapMultiplyToSelf(double d) {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), iter.value() * d);
> + }
> + return this;
> + }
> + /** {@inheritDoc} */
> + public RealVector mapPow(double d) {
> + return copy().mapPowToSelf(d);
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapPowToSelf(double d) {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.pow(iter.value(), d));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapRint() {
> + return copy().mapRintToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapRintToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.rint(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapSignum() {
> + return copy().mapSignumToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapSignumToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.signum(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapSin() {
> + return copy().mapSinToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapSinToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.sin(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapSinh() {
> + return copy().mapSinhToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapSinhToSelf() {
> +
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.sinh(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapSqrt() {
> + return copy().mapSqrtToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapSqrtToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.sqrt(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapSubtract(double d) {
> + return copy().mapSubtractToSelf(d);
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapSubtractToSelf(double d) {
> + return mapAddToSelf(-d);
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapTan() {
> + return copy().mapTanToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapTanToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.tan(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapTanh() {
> + return copy().mapTanhToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapTanhToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.tanh(iter.value()));
> + }
> + return this;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapUlp() {
> + return copy().mapUlpToSelf();
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector mapUlpToSelf() {
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), Math.ulp(iter.value()));
> + }
> + return this;
> + }
> +
> + /**
> + * Optimized method to compute the outer product
> + * @param v The vector to comput the outer product on
> + * @return The outer product of <code>this</code> and
> <code>v</code>
> + */
> + public SparseRealMatrix outerproduct(SparseRealVector v){
> + checkVectorDimensions(v.getDimension());
> + SparseRealMatrix res = new SparseRealMatrix(virtualSize,
> virtualSize);
> + Iterator iter = entries.iterator();
> + while(iter.hasNext()){
> + iter.advance();
> + Iterator iter2 = v.getEntries().iterator();
> + while(iter2.hasNext()){
> + iter2.advance();
> + res.setEntry(iter.key(), iter2.key(),
> iter.value()*iter2.value());
> + }
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealMatrix outerProduct(RealVector v)
> + throws IllegalArgumentException {
> + checkVectorDimensions(v.getDimension());
> + if(v instanceof SparseRealVector){
> + return outerproduct((SparseRealVector)v);
> + }
> + RealMatrix res = new SparseRealMatrix(virtualSize,
> virtualSize);
> + Iterator iter = entries.iterator();
> + while(iter.hasNext()){
> + iter.advance();
> + int row = iter.key();
> + for(int col=0; col < virtualSize; col++){
> + res.setEntry(row, col,
> iter.value()*v.getEntry(col));
> + }
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealMatrix outerProduct(double[] v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.length);
> + RealMatrix res = new SparseRealMatrix(virtualSize,
> virtualSize);
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + int row = iter.key();
> + double value = iter.value();
> + for (int col = 0; col < virtualSize; col++) {
> + res.setEntry(row, col, value * v[col]);
> + }
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector projection(RealVector v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.getDimension());
> + return v.mapMultiply(dotProduct(v) / v.dotProduct(v));
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector projection(double[] v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.length);
> + return projection(new SparseRealVector(v));
> + }
> +
> + /** {@inheritDoc} */
> + public void set(int index, double value) throws
> MatrixIndexException {
> + checkIndex(index);
> + if (!isZero(value)) {
> + entries.put(index, value);
> + } else if (!isZero(index)) {
> + entries.remove(index);
> + }
> + }
> +
> + /** {@inheritDoc} */
> + public void set(int index, RealVector v) throws
> MatrixIndexException {
> + checkIndex(index);
> + checkIndex(index + v.getDimension() - 1);
> + set(index, v.getData());
> + }
> +
> + /** {@inheritDoc} */
> + public void set(int index, double[] v) throws
> MatrixIndexException {
> + checkIndex(index);
> + checkIndex(index + v.length - 1);
> + for (int i = 0; i < v.length; i++) {
> + set(i + index, v[i]);
> + }
> + }
> +
> + /** {@inheritDoc} */
> + public void set(double value) {
> + entries = new OpenIntToDoubleHashMap(value);
> + }
> +
> + /** {@inheritDoc} */
> + public SparseRealVector subtract(SparseRealVector v) {
> + checkVectorDimensions(v.getDimension());
> + SparseRealVector res = new SparseRealVector(this);
> + Iterator iter = v.getEntries().iterator();
> + OpenIntToDoubleHashMap values = res.getEntries();
> + while (iter.hasNext()) {
> + iter.advance();
> + int key = iter.key();
> + if (entries.containsKey(key)) {
> + values.put(key, entries.get(key) - iter.value());
> + } else {
> + values.put(key, -iter.value());
> + }
> + }
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector subtract(RealVector v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.getDimension());
> + if (v instanceof SparseRealVector) {
> + return subtract((SparseRealVector) v);
> + }
> + return subtract(v.getData());
> + }
> +
> + /** {@inheritDoc} */
> + public RealVector subtract(double[] v) throws
> IllegalArgumentException {
> + checkVectorDimensions(v.length);
> + SparseRealVector res = new SparseRealVector(this);
> + for (int i = 0; i < v.length; i++) {
> + if (entries.containsKey(i)) {
> + res.set(i, entries.get(i) - v[i]);
> + } else {
> + res.set(i, -v[i]);
> + }
> + }
> + return res;
> + }
> +
> +
> + /** {@inheritDoc} */
> + public RealVector unitVector() {
> + RealVector res = copy();
> + res.unitize();
> + return res;
> + }
> +
> + /** {@inheritDoc} */
> + public void unitize() {
> + double norm = getNorm();
> + if(isZero(norm)){
> + throw
> MathRuntimeException.createArithmeticException("cannot normalize a
> zero norm vector",
> + null);
> +
> + }
> + Iterator iter = entries.iterator();
> + while (iter.hasNext()) {
> + iter.advance();
> + entries.put(iter.key(), iter.value() / norm);
> + }
> +
> + }
> +
> + /**
> + * Check if an index is valid.
> + *
> + * @param index
> + * index to check
> + * @exception MatrixIndexException
> + * if index is not valid
> + */
> + private void checkIndex(final int index) throws
> MatrixIndexException {
> + if (index < 0 || index >= getDimension()) {
> + throw new MatrixIndexException(
> + "index {0} out of allowed range [{1}, {2}]", new
> Object[] {
> + index, 0, getDimension() - 1 });
> + }
> + }
> +
> + /**
> + * Check if instance dimension is equal to some expected value.
> + *
> + * @param n
> + * expected dimension.
> + * @exception IllegalArgumentException
> + * if the dimension is inconsistent with vector
> size
> + */
> + public void checkVectorDimensions(int n) throws
> IllegalArgumentException {
> + if (getDimension() != n) {
> + throw new IllegalArgumentException("vector dimension is
> "
> + + getDimension() + ", not " + n + " as
> expected");
> + }
> + }
> +
> + /** {@inheritDoc} */
> + public double[] toArray() {
> + return getData();
> + }
> +}
>
> Added:
> commons/proper/math/trunk/src/test/org/apache/commons/math/linear/SparseRealVectorTest.java
> URL:
> http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/org/apache/commons/math/linear/SparseRealVectorTest.java?rev=739504&view=auto
> ==============================================================================
> ---
> commons/proper/math/trunk/src/test/org/apache/commons/math/linear/SparseRealVectorTest.java
> (added)
> +++
> commons/proper/math/trunk/src/test/org/apache/commons/math/linear/SparseRealVectorTest.java
> Sat Jan 31 04:51:17 2009
> @@ -0,0 +1,1192 @@
> +/*
> + * Licensed to the Apache Software Foundation (ASF) under one or
> more
> + * contributor license agreements. See the NOTICE file distributed
> with
> + * this work for additional information regarding copyright
> ownership.
> + * The ASF licenses this file to You under the Apache License,
> Version 2.0
> + * (the "License"); you may not use this file except in compliance
> with
> + * the License. You may obtain a copy of the License at
> + *
> + * http://www.apache.org/licenses/LICENSE-2.0
> + *
> + * Unless required by applicable law or agreed to in writing,
> software
> + * distributed under the License is distributed on an "AS IS" BASIS,
> + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
> implied.
> + * See the License for the specific language governing permissions
> and
> + * limitations under the License.
> + */
> +package org.apache.commons.math.linear;
> +
> +import java.io.Serializable;
> +import junit.framework.Test;
> +import junit.framework.TestCase;
> +import junit.framework.TestSuite;
> +
> +/**
> + * Test cases for the {@link SparseRealVector} class.
> + *
> + * @version $Revision: 728186 $ $Date: 2008-12-19 16:03:13 -0800
> (Fri, 19 Dec 2008) $
> + */
> +public class SparseRealVectorTest extends TestCase {
> +
> + //
> + protected double[][] ma1 = {{1d, 2d, 3d}, {4d, 5d, 6d}, {7d, 8d,
> 9d}};
> + protected double[] vec1 = {1d, 2d, 3d};
> + protected double[] vec2 = {4d, 5d, 6d};
> + protected double[] vec3 = {7d, 8d, 9d};
> + protected double[] vec4 = {1d, 2d, 3d, 4d, 5d, 6d, 7d, 8d, 9d};
> + protected double[] vec_null = {0d, 0d, 0d};
> + protected Double[] dvec1 = {1d, 2d, 3d, 4d, 5d, 6d, 7d, 8d, 9d};
> + protected double[][] mat1 = {{1d, 2d, 3d}, {4d, 5d, 6d},{ 7d, 8d,
> 9d}};
> +
> + // tolerances
> + protected double entryTolerance = 10E-16;
> + protected double normTolerance = 10E-14;
> +
> + // Testclass to test the RealVector interface
> + // only with enough content to support the test
> + public static class SparseRealVectorTestImpl implements
> RealVector, Serializable {
> +
> + /** Serializable version identifier. */
> + private static final long serialVersionUID =
> 4715341047369582908L;
> +
> + /** Entries of the vector. */
> + protected double data[];
> +
> + public SparseRealVectorTestImpl(double[] d) {
> + data = d.clone();
> + }
> +
> + private UnsupportedOperationException unsupported() {
> + return new UnsupportedOperationException("Not supported,
> unneeded for test purposes");
> + }
> +
> + public RealVector copy() {
> + throw unsupported();
> + }
> +
> + public RealVector add(RealVector v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealVector add(double[] v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealVector subtract(RealVector v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealVector subtract(double[] v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealVector mapAdd(double d) {
> + throw unsupported();
> + }
> +
> + public RealVector mapAddToSelf(double d) {
> + throw unsupported();
> + }
> +
> + public RealVector mapSubtract(double d) {
> + throw unsupported();
> + }
> +
> + public RealVector mapSubtractToSelf(double d) {
> + throw unsupported();
> + }
> +
> + public RealVector mapMultiply(double d) {
> + double[] out = new double[data.length];
> + for (int i = 0; i < data.length; i++) {
> + out[i] = data[i] * d;
> + }
> + return new SparseRealVector(out);
> + }
> +
> + public RealVector mapMultiplyToSelf(double d) {
> + throw unsupported();
> + }
> +
> + public RealVector mapDivide(double d) {
> + throw unsupported();
> + }
> +
> + public RealVector mapDivideToSelf(double d) {
> + throw unsupported();
> + }
> +
> + public RealVector mapPow(double d) {
> + throw unsupported();
> + }
> +
> + public RealVector mapPowToSelf(double d) {
> + throw unsupported();
> + }
> +
> + public RealVector mapExp() {
> + throw unsupported();
> + }
> +
> + public RealVector mapExpToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapExpm1() {
> + throw unsupported();
> + }
> +
> + public RealVector mapExpm1ToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapLog() {
> + throw unsupported();
> + }
> +
> + public RealVector mapLogToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapLog10() {
> + throw unsupported();
> + }
> +
> + public RealVector mapLog10ToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapLog1p() {
> + throw unsupported();
> + }
> +
> + public RealVector mapLog1pToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapCosh() {
> + throw unsupported();
> + }
> +
> + public RealVector mapCoshToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapSinh() {
> + throw unsupported();
> + }
> +
> + public RealVector mapSinhToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapTanh() {
> + throw unsupported();
> + }
> +
> + public RealVector mapTanhToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapCos() {
> + throw unsupported();
> + }
> +
> + public RealVector mapCosToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapSin() {
> + throw unsupported();
> + }
> +
> + public RealVector mapSinToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapTan() {
> + throw unsupported();
> + }
> +
> + public RealVector mapTanToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapAcos() {
> + throw unsupported();
> + }
> +
> + public RealVector mapAcosToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapAsin() {
> + throw unsupported();
> + }
> +
> + public RealVector mapAsinToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapAtan() {
> + throw unsupported();
> + }
> +
> + public RealVector mapAtanToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapInv() {
> + throw unsupported();
> + }
> +
> + public RealVector mapInvToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapAbs() {
> + throw unsupported();
> + }
> +
> + public RealVector mapAbsToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapSqrt() {
> + throw unsupported();
> + }
> +
> + public RealVector mapSqrtToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapCbrt() {
> + throw unsupported();
> + }
> +
> + public RealVector mapCbrtToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapCeil() {
> + throw unsupported();
> + }
> +
> + public RealVector mapCeilToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapFloor() {
> + throw unsupported();
> + }
> +
> + public RealVector mapFloorToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapRint() {
> + throw unsupported();
> + }
> +
> + public RealVector mapRintToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapSignum() {
> + throw unsupported();
> + }
> +
> + public RealVector mapSignumToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector mapUlp() {
> + throw unsupported();
> + }
> +
> + public RealVector mapUlpToSelf() {
> + throw unsupported();
> + }
> +
> + public RealVector ebeMultiply(RealVector v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealVector ebeMultiply(double[] v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealVector ebeDivide(RealVector v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealVector ebeDivide(double[] v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public double[] getData() {
> + return data.clone();
> + }
> +
> + public double dotProduct(RealVector v) throws
> IllegalArgumentException {
> + double dot = 0;
> + for (int i = 0; i < data.length; i++) {
> + dot += data[i] * v.getEntry(i);
> + }
> + return dot;
> + }
> +
> + public double dotProduct(double[] v) throws
> IllegalArgumentException {
> + double dot = 0;
> + for (int i = 0; i < data.length; i++) {
> + dot += data[i] * v[i];
> + }
> + return dot;
> + }
> +
> + public double getNorm() {
> + throw unsupported();
> + }
> +
> + public double getL1Norm() {
> + throw unsupported();
> + }
> +
> + public double getLInfNorm() {
> + throw unsupported();
> + }
> +
> + public double getDistance(RealVector v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public double getDistance(double[] v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public double getL1Distance(RealVector v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public double getL1Distance(double[] v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public double getLInfDistance(RealVector v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public double getLInfDistance(double[] v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealVector unitVector() {
> + throw unsupported();
> + }
> +
> + public void unitize() {
> + throw unsupported();
> + }
> +
> + public RealVector projection(RealVector v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealVector projection(double[] v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealMatrix outerProduct(RealVector v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public RealMatrix outerProduct(double[] v) throws
> IllegalArgumentException {
> + throw unsupported();
> + }
> +
> + public double getEntry(int index) throws MatrixIndexException
> {
> + return data[index];
> + }
> +
> + public int getDimension() {
> + return data.length;
> + }
> +
> + public RealVector append(RealVector v) {
> + throw unsupported();
> + }
> +
> + public RealVector append(double d) {
> + throw unsupported();
> + }
> +
> + public RealVector append(double[] a) {
> + throw unsupported();
> + }
> +
> + public RealVector get(int index, int n) throws
> MatrixIndexException {
> + throw unsupported();
> + }
> +
> + public void set(int index, double value) throws
> MatrixIndexException {
> + throw unsupported();
> + }
> +
> + public void set(int index, RealVector v) throws
> MatrixIndexException {
> + throw unsupported();
> + }
> +
> + public void set(int index, double[] v) throws
> MatrixIndexException {
> + throw unsupported();
> + }
> +
> + public void set(double value) {
> + throw unsupported();
> + }
> +
> + public double[] toArray() {
> + throw unsupported();
> + }
> +
> + public boolean isNaN() {
> + throw unsupported();
> + }
> +
> + public boolean isInfinite() {
> + throw unsupported();
> + }
> +
> + }
> +
> + public static Test suite() {
> + TestSuite suite = new TestSuite(SparseRealVectorTest.class);
> + suite.setName("SparseRealVector Tests");
> + return suite;
> + }
> +
> + public void testConstructors() {
> +
> + SparseRealVector v0 = new SparseRealVector();
> + assertEquals("testData len", 0, v0.getDimension());
> +
> + SparseRealVector v1 = new SparseRealVector(7);
> + assertEquals("testData len", 7, v1.getDimension());
> + assertEquals("testData is 0.0 ", 0.0, v1.getEntry(6));
> +
> + /* TODO: make this supported */
> + //SparseRealVector v2 = new SparseRealVector(5, 1.23);
> + //assertEquals("testData len", 5, v2.getDimension());
> + //assertEquals("testData is 1.23 ", 1.23, v2.getEntry(4));
> +
> + SparseRealVector v3 = new SparseRealVector(vec1);
> + assertEquals("testData len", 3, v3.getDimension());
> + assertEquals("testData is 2.0 ", 2.0, v3.getEntry(1));
> +
> + //SparseRealVector v4 = new SparseRealVector(vec4, 3, 2);
> + //assertEquals("testData len", 2, v4.getDimension());
> + //assertEquals("testData is 4.0 ", 4.0, v4.getEntry(0));
> + //try {
> + // new SparseRealVector(vec4, 8, 3);
> + // fail("IllegalArgumentException expected");
> + //} catch (IllegalArgumentException ex) {
> + // expected behavior
> + //} catch (Exception e) {
> + // fail("wrong exception caught");
> + //}
> +
> + RealVector v5_i = new SparseRealVector(dvec1);
> + assertEquals("testData len", 9, v5_i.getDimension());
> + assertEquals("testData is 9.0 ", 9.0, v5_i.getEntry(8));
> +
> + SparseRealVector v5 = new SparseRealVector(dvec1);
> + assertEquals("testData len", 9, v5.getDimension());
> + assertEquals("testData is 9.0 ", 9.0, v5.getEntry(8));
> +
> + //SparseRealVector v6 = new SparseRealVector(dvec1, 3, 2);
> + //assertEquals("testData len", 2, v6.getDimension());
> + //assertEquals("testData is 4.0 ", 4.0, v6.getEntry(0));
> + //try {
> + // new SparseRealVector(dvec1, 8, 3);
> + // fail("IllegalArgumentException expected");
> + //} catch (IllegalArgumentException ex) {
> + // expected behavior
> + //} catch (Exception e) {
> + // fail("wrong exception caught");
> + //}
> +
> + SparseRealVector v7 = new SparseRealVector(v1);
> + assertEquals("testData len", 7, v7.getDimension());
> + assertEquals("testData is 0.0 ", 0.0, v7.getEntry(6));
> +
> + SparseRealVectorTestImpl v7_i = new
> SparseRealVectorTestImpl(vec1);
> +
> + /*TODO: fixme */
> + //SparseRealVector v7_2 = new SparseRealVector(v7_i);
> + //assertEquals("testData len", 3, v7_2.getDimension());
> + //assertEquals("testData is 0.0 ", 2.0d, v7_2.getEntry(1));
> +
> + //SparseRealVector v8 = new SparseRealVector(v1, true);
> + //assertEquals("testData len", 7, v8.getDimension());
> + //assertEquals("testData is 0.0 ", 0.0, v8.getEntry(6));
> + //assertNotSame("testData not same object ", v1.data,
> v8.data);
> +
> + //SparseRealVector v8_2 = new SparseRealVector(v1, false);
> + //assertEquals("testData len", 7, v8_2.getDimension());
> + //assertEquals("testData is 0.0 ", 0.0, v8_2.getEntry(6));
> + //assertEquals("testData same object ", v1.data, v8_2.data);
> +
> + //SparseRealVector v9 = new SparseRealVector(v1, v3);
> + //assertEquals("testData len", 10, v9.getDimension());
> + //assertEquals("testData is 1.0 ", 1.0, v9.getEntry(7));
> +
> + }
> +
> + public void testDataInOut() {
> +
> + SparseRealVector v1 = new SparseRealVector(vec1);
> + SparseRealVector v2 = new SparseRealVector(vec2);
> + SparseRealVector v4 = new SparseRealVector(vec4);
> + SparseRealVectorTestImpl v2_t = new
> SparseRealVectorTestImpl(vec2);
> +
> + RealVector v_append_1 = v1.append(v2);
> + assertEquals("testData len", 6, v_append_1.getDimension());
> + assertEquals("testData is 4.0 ", 4.0,
> v_append_1.getEntry(3));
> +
> + RealVector v_append_2 = v1.append(2.0);
> + assertEquals("testData len", 4, v_append_2.getDimension());
> + assertEquals("testData is 2.0 ", 2.0,
> v_append_2.getEntry(3));
> +
> + RealVector v_append_3 = v1.append(vec2);
> + assertEquals("testData len", 6, v_append_3.getDimension());
> + assertEquals("testData is ", 4.0, v_append_3.getEntry(3));
> +
> + /* TODO: fixme */
> + //RealVector v_append_4 = v1.append(v2_t);
> + //assertEquals("testData len", 6,
> v_append_4.getDimension());
> + //assertEquals("testData is 4.0 ", 4.0,
> v_append_4.getEntry(3));
> +
> + /* TODO: fixme */
> + //RealVector v_copy = v1.copy();
> + //assertEquals("testData len", 3, v_copy.getDimension());
> + //assertNotSame("testData not same object ", v1.data,
> v_copy.getData());
> + /* TODO: fixme */
> + //double[] a_double = v1.toArray();
> + //assertEquals("testData len", 3, a_double.length);
> + //assertNotSame("testData not same object ", v1.data,
> a_double);
> +
> +
> +// SparseRealVector vout4 = (SparseRealVector) v1.clone();
> +// assertEquals("testData len", 3, vout4.getDimension());
> +// assertEquals("testData not same object ", v1.data,
> vout4.data);
> +
> +
> + RealVector vout5 = v4.get(3, 3);
> + assertEquals("testData len", 3, vout5.getDimension());
> + assertEquals("testData is 4.0 ", 5.0, vout5.getEntry(1));
> + try {
> + v4.get(3, 7);
> + fail("MatrixIndexException expected");
> + } catch (MatrixIndexException ex) {
> + // expected behavior
> + } catch (Exception e) {
> + fail("wrong exception caught");
> + }
> +
> + SparseRealVector v_set1 = (SparseRealVector) v1.copy();
> + v_set1.set(1, 11.0);
> + assertEquals("testData is 11.0 ", 11.0, v_set1.getEntry(1));
> + try {
> + v_set1.set(3, 11.0);
> + fail("MatrixIndexException expected");
> + } catch (MatrixIndexException ex) {
> + // expected behavior
> + } catch (Exception e) {
> + fail("wrong exception caught");
> + }
> +
> + SparseRealVector v_set2 = (SparseRealVector) v4.copy();
> + v_set2.set(3, v1);
> + assertEquals("testData is 1.0 ", 1.0, v_set2.getEntry(3));
> + assertEquals("testData is 7.0 ", 7.0, v_set2.getEntry(6));
> + try {
> + v_set2.set(7, v1);
> + fail("MatrixIndexException expected");
> + } catch (MatrixIndexException ex) {
> + // expected behavior
> + } catch (Exception e) {
> + fail("wrong exception caught");
> + }
> +
> + SparseRealVector v_set3 = (SparseRealVector) v1.copy();
> + v_set3.set(13.0);
> + assertEquals("testData is 13.0 ", 13.0, v_set3.getEntry(2));
> +
> + try {
> + v_set3.getEntry(23);
> + fail("MatrixIndexException expected");
> + } catch (MatrixIndexException ex) {
> + // expected behavior
> + } catch (Exception e) {
> + fail("wrong exception caught");
> + }
> +
> + SparseRealVector v_set4 = (SparseRealVector) v4.copy();
> + v_set4.set(3, v2_t);
> + assertEquals("testData is 1.0 ", 4.0, v_set4.getEntry(3));
> + assertEquals("testData is 7.0 ", 7.0, v_set4.getEntry(6));
> + try {
> + v_set4.set(7, v2_t);
> + fail("MatrixIndexException expected");
> + } catch (MatrixIndexException ex) {
> + // expected behavior
> + } catch (Exception e) {
> + fail("wrong exception caught");
> + }
> +
> +
> + SparseRealVector vout10 = (SparseRealVector) v1.copy();
>
> + SparseRealVector vout10_2 = (SparseRealVector) v1.copy();
> + // TODO: backing store doesn't implement equals
> + //assertEquals(vout10, vout10_2);
> + //vout10_2.set(0, 1.1);
> + //assertNotSame(vout10, vout10_2);
> +
> + }
> +
> + public void testMapFunctions() {
> + SparseRealVector v1 = new SparseRealVector(vec1);
> +
> + //octave = v1 .+ 2.0
> + RealVector v_mapAdd = v1.mapAdd(2.0d);
> + double[] result_mapAdd = {3d, 4d, 5d};
> + assertClose("compare vectors"
> ,result_mapAdd,v_mapAdd.getData(),normTolerance);
> +
> + //octave = v1 .+ 2.0
> + RealVector v_mapAddToSelf = v1.copy();
> + v_mapAddToSelf.mapAddToSelf(2.0d);
> + double[] result_mapAddToSelf = {3d, 4d, 5d};
> + assertClose("compare vectors"
> ,result_mapAddToSelf,v_mapAddToSelf.getData(),normTolerance);
> +
> + //octave = v1 .- 2.0
> + RealVector v_mapSubtract = v1.mapSubtract(2.0d);
> + double[] result_mapSubtract = {-1d, 0d, 1d};
> + assertClose("compare vectors"
> ,result_mapSubtract,v_mapSubtract.getData(),normTolerance);
> +
> + //octave = v1 .- 2.0
> + RealVector v_mapSubtractToSelf = v1.copy();
> + v_mapSubtractToSelf.mapSubtractToSelf(2.0d);
> + double[] result_mapSubtractToSelf = {-1d, 0d, 1d};
> + assertClose("compare vectors"
> ,result_mapSubtractToSelf,v_mapSubtractToSelf.getData(),normTolerance);
> +
> + //octave = v1 .* 2.0
> + RealVector v_mapMultiply = v1.mapMultiply(2.0d);
> + double[] result_mapMultiply = {2d, 4d, 6d};
> + assertClose("compare vectors"
> ,result_mapMultiply,v_mapMultiply.getData(),normTolerance);
> +
> + //octave = v1 .* 2.0
> + RealVector v_mapMultiplyToSelf = v1.copy();
> + v_mapMultiplyToSelf.mapMultiplyToSelf(2.0d);
> + double[] result_mapMultiplyToSelf = {2d, 4d, 6d};
> + assertClose("compare vectors"
> ,result_mapMultiplyToSelf,v_mapMultiplyToSelf.getData(),normTolerance);
> +
> + //octave = v1 ./ 2.0
> + RealVector v_mapDivide = v1.mapDivide(2.0d);
> + double[] result_mapDivide = {.5d, 1d, 1.5d};
> + assertClose("compare vectors"
> ,result_mapDivide,v_mapDivide.getData(),normTolerance);
> +
> + //octave = v1 ./ 2.0
> + RealVector v_mapDivideToSelf = v1.copy();
> + v_mapDivideToSelf.mapDivideToSelf(2.0d);
> + double[] result_mapDivideToSelf = {.5d, 1d, 1.5d};
> + assertClose("compare vectors"
> ,result_mapDivideToSelf,v_mapDivideToSelf.getData(),normTolerance);
> +
> + //octave = v1 .^ 2.0
> + RealVector v_mapPow = v1.mapPow(2.0d);
> + double[] result_mapPow = {1d, 4d, 9d};
> + assertClose("compare vectors"
> ,result_mapPow,v_mapPow.getData(),normTolerance);
> +
> + //octave = v1 .^ 2.0
> + RealVector v_mapPowToSelf = v1.copy();
> + v_mapPowToSelf.mapPowToSelf(2.0d);
> + double[] result_mapPowToSelf = {1d, 4d, 9d};
> + assertClose("compare vectors"
> ,result_mapPowToSelf,v_mapPowToSelf.getData(),normTolerance);
> +
> + //octave = exp(v1)
> + RealVector v_mapExp = v1.mapExp();
> + double[] result_mapExp =
> {2.718281828459045e+00d,7.389056098930650e+00d,
> 2.008553692318767e+01d};
> + assertClose("compare vectors"
> ,result_mapExp,v_mapExp.getData(),normTolerance);
> +
> + //octave = exp(v1)
> + RealVector v_mapExpToSelf = v1.copy();
> + v_mapExpToSelf.mapExpToSelf();
> + double[] result_mapExpToSelf =
> {2.718281828459045e+00d,7.389056098930650e+00d,
> 2.008553692318767e+01d};
> + assertClose("compare vectors"
> ,result_mapExpToSelf,v_mapExpToSelf.getData(),normTolerance);
> +
> +
> + //octave = ???
> + RealVector v_mapExpm1 = v1.mapExpm1();
> + double[] result_mapExpm1 =
> {1.718281828459045d,6.38905609893065d, 19.085536923187668d};
> + assertClose("compare vectors"
> ,result_mapExpm1,v_mapExpm1.getData(),normTolerance);
> +
> + //octave = ???
> + RealVector v_mapExpm1ToSelf = v1.copy();
> + v_mapExpm1ToSelf.mapExpm1ToSelf();
> + double[] result_mapExpm1ToSelf =
> {1.718281828459045d,6.38905609893065d, 19.085536923187668d};
> + assertClose("compare vectors"
> ,result_mapExpm1ToSelf,v_mapExpm1ToSelf.getData(),normTolerance);
> +
> + //octave = log(v1)
> + RealVector v_mapLog = v1.mapLog();
> + double[] result_mapLog = {0d,6.931471805599453e-01d,
> 1.098612288668110e+00d};
> + assertClose("compare vectors"
> ,result_mapLog,v_mapLog.getData(),normTolerance);
> +
> + //octave = log(v1)
> + RealVector v_mapLogToSelf = v1.copy();
> + v_mapLogToSelf.mapLogToSelf();
> + double[] result_mapLogToSelf = {0d,6.931471805599453e-01d,
> 1.098612288668110e+00d};
> + assertClose("compare vectors"
> ,result_mapLogToSelf,v_mapLogToSelf.getData(),normTolerance);
> +
> + //octave = log10(v1)
> + RealVector v_mapLog10 = v1.mapLog10();
> + double[] result_mapLog10 = {0d,3.010299956639812e-01d,
> 4.771212547196624e-01d};
> + assertClose("compare vectors"
> ,result_mapLog10,v_mapLog10.getData(),normTolerance);
> +
> + //octave = log(v1)
> + RealVector v_mapLog10ToSelf = v1.copy();
> + v_mapLog10ToSelf.mapLog10ToSelf();
> + double[] result_mapLog10ToSelf = {0d,3.010299956639812e-01d,
> 4.771212547196624e-01d};
> + assertClose("compare vectors"
> ,result_mapLog10ToSelf,v_mapLog10ToSelf.getData(),normTolerance);
> +
> + //octave = ???
> + RealVector v_mapLog1p = v1.mapLog1p();
> + double[] result_mapLog1p =
> {0.6931471805599453d,1.0986122886681096d,1.3862943611198906d};
> + assertClose("compare vectors"
> ,result_mapLog1p,v_mapLog1p.getData(),normTolerance);
> +
> + //octave = ???
> + RealVector v_mapLog1pToSelf = v1.copy();
> + v_mapLog1pToSelf.mapLog1pToSelf();
> + double[] result_mapLog1pToSelf =
> {0.6931471805599453d,1.0986122886681096d,1.3862943611198906d};
> + assertClose("compare vectors"
> ,result_mapLog1pToSelf,v_mapLog1pToSelf.getData(),normTolerance);
> +
> + //octave = cosh(v1)
> + RealVector v_mapCosh = v1.mapCosh();
> + double[] result_mapCosh =
> {1.543080634815244e+00d,3.762195691083631e+00d,
> 1.006766199577777e+01d};
> + assertClose("compare vectors"
> ,result_mapCosh,v_mapCosh.getData(),normTolerance);
> +
> + //octave = cosh(v1)
> + RealVector v_mapCoshToSelf = v1.copy();
> + v_mapCoshToSelf.mapCoshToSelf();
> + double[] result_mapCoshToSelf =
> {1.543080634815244e+00d,3.762195691083631e+00d,
> 1.006766199577777e+01d};
> + assertClose("compare vectors"
> ,result_mapCoshToSelf,v_mapCoshToSelf.getData(),normTolerance);
> +
> + //octave = sinh(v1)
> + RealVector v_mapSinh = v1.mapSinh();
> + double[] result_mapSinh =
> {1.175201193643801e+00d,3.626860407847019e+00d,
> 1.001787492740990e+01d};
> + assertClose("compare vectors"
> ,result_mapSinh,v_mapSinh.getData(),normTolerance);
> +
> + //octave = sinh(v1)
> + RealVector v_mapSinhToSelf = v1.copy();
> + v_mapSinhToSelf.mapSinhToSelf();
> + double[] result_mapSinhToSelf =
> {1.175201193643801e+00d,3.626860407847019e+00d,
> 1.001787492740990e+01d};
> + assertClose("compare vectors"
> ,result_mapSinhToSelf,v_mapSinhToSelf.getData(),normTolerance);
> +
> + //octave = tanh(v1)
> + RealVector v_mapTanh = v1.mapTanh();
> + double[] result_mapTanh =
> {7.615941559557649e-01d,9.640275800758169e-01d,9.950547536867305e-01d};
> + assertClose("compare vectors"
> ,result_mapTanh,v_mapTanh.getData(),normTolerance);
> +
> + //octave = tanh(v1)
> + RealVector v_mapTanhToSelf = v1.copy();
> + v_mapTanhToSelf.mapTanhToSelf();
> + double[] result_mapTanhToSelf =
> {7.615941559557649e-01d,9.640275800758169e-01d,9.950547536867305e-01d};
> + assertClose("compare vectors"
> ,result_mapTanhToSelf,v_mapTanhToSelf.getData(),normTolerance);
> +
> + //octave = cos(v1)
> + RealVector v_mapCos = v1.mapCos();
> + double[] result_mapCos =
> {5.403023058681398e-01d,-4.161468365471424e-01d,
> -9.899924966004454e-01d};
> + assertClose("compare vectors"
> ,result_mapCos,v_mapCos.getData(),normTolerance);
> +
> + //octave = cos(v1)
> + RealVector v_mapCosToSelf = v1.copy();
> + v_mapCosToSelf.mapCosToSelf();
> + double[] result_mapCosToSelf =
> {5.403023058681398e-01d,-4.161468365471424e-01d,
> -9.899924966004454e-01d};
> + assertClose("compare vectors"
> ,result_mapCosToSelf,v_mapCosToSelf.getData(),normTolerance);
> +
> + //octave = sin(v1)
> + RealVector v_mapSin = v1.mapSin();
> + double[] result_mapSin =
> {8.414709848078965e-01d,9.092974268256817e-01d,1.411200080598672e-01d};
> + assertClose("compare vectors"
> ,result_mapSin,v_mapSin.getData(),normTolerance);
> +
> + //octave = sin(v1)
> + RealVector v_mapSinToSelf = v1.copy();
> + v_mapSinToSelf.mapSinToSelf();
> + double[] result_mapSinToSelf =
> {8.414709848078965e-01d,9.092974268256817e-01d,1.411200080598672e-01d};
> + assertClose("compare vectors"
> ,result_mapSinToSelf,v_mapSinToSelf.getData(),normTolerance);
> +
> + //octave = tan(v1)
> + RealVector v_mapTan = v1.mapTan();
> + double[] result_mapTan =
> {1.557407724654902e+00d,-2.185039863261519e+00d,-1.425465430742778e-01d};
> + assertClose("compare vectors"
> ,result_mapTan,v_mapTan.getData(),normTolerance);
> +
> + //octave = tan(v1)
> + RealVector v_mapTanToSelf = v1.copy();
> + v_mapTanToSelf.mapTanToSelf();
> + double[] result_mapTanToSelf =
> {1.557407724654902e+00d,-2.185039863261519e+00d,-1.425465430742778e-01d};
> + assertClose("compare vectors"
> ,result_mapTanToSelf,v_mapTanToSelf.getData(),normTolerance);
> +
> + double[] vat_a = {0d, 0.5d, 1.0d};
> + SparseRealVector vat = new SparseRealVector(vat_a);
> +
> + //octave = acos(vat)
> + RealVector v_mapAcos = vat.mapAcos();
> + double[] result_mapAcos =
> {1.570796326794897e+00d,1.047197551196598e+00d, 0.0d};
> + assertClose("compare vectors"
> ,result_mapAcos,v_mapAcos.getData(),normTolerance);
> +
> + //octave = acos(vat)
> + RealVector v_mapAcosToSelf = vat.copy();
> + v_mapAcosToSelf.mapAcosToSelf();
> + double[] result_mapAcosToSelf =
> {1.570796326794897e+00d,1.047197551196598e+00d, 0.0d};
> + assertClose("compare vectors"
> ,result_mapAcosToSelf,v_mapAcosToSelf.getData(),normTolerance);
> +
> + //octave = asin(vat)
> + RealVector v_mapAsin = vat.mapAsin();
> + double[] result_mapAsin =
> {0.0d,5.235987755982989e-01d,1.570796326794897e+00d};
> + assertClose("compare vectors"
> ,result_mapAsin,v_mapAsin.getData(),normTolerance);
> +
> + //octave = asin(vat)
> + RealVector v_mapAsinToSelf = vat.copy();
> + v_mapAsinToSelf.mapAsinToSelf();
> + double[] result_mapAsinToSelf =
> {0.0d,5.235987755982989e-01d,1.570796326794897e+00d};
> + assertClose("compare vectors"
> ,result_mapAsinToSelf,v_mapAsinToSelf.getData(),normTolerance);
> +
> + //octave = atan(vat)
> + RealVector v_mapAtan = vat.mapAtan();
> + double[] result_mapAtan =
> {0.0d,4.636476090008061e-01d,7.853981633974483e-01d};
> + assertClose("compare vectors"
> ,result_mapAtan,v_mapAtan.getData(),normTolerance);
> +
> + //octave = atan(vat)
> + RealVector v_mapAtanToSelf = vat.copy();
> + v_mapAtanToSelf.mapAtanToSelf();
> + double[] result_mapAtanToSelf =
> {0.0d,4.636476090008061e-01d,7.853981633974483e-01d};
> + assertClose("compare vectors"
> ,result_mapAtanToSelf,v_mapAtanToSelf.getData(),normTolerance);
> +
> + //octave = v1 .^-1
> + RealVector v_mapInv = v1.mapInv();
> + double[] result_mapInv = {1d,0.5d,3.333333333333333e-01d};
> + assertClose("compare vectors"
> ,result_mapInv,v_mapInv.getData(),normTolerance);
> +
> + //octave = v1 .^-1
> + RealVector v_mapInvToSelf = v1.copy();
> + v_mapInvToSelf.mapInvToSelf();
> + double[] result_mapInvToSelf =
> {1d,0.5d,3.333333333333333e-01d};
> + assertClose("compare vectors"
> ,result_mapInvToSelf,v_mapInvToSelf.getData(),normTolerance);
> +
> + double[] abs_a = {-1.0d, 0.0d, 1.0d};
> + SparseRealVector abs_v = new SparseRealVector(abs_a);
> +
> + //octave = abs(abs_v)
> + RealVector v_mapAbs = abs_v.mapAbs();
> + double[] result_mapAbs = {1d,0d,1d};
> + assertClose("compare vectors"
> ,result_mapAbs,v_mapAbs.getData(),normTolerance);
> +
> + //octave = abs(abs_v)
> + RealVector v_mapAbsToSelf = abs_v.copy();
> + v_mapAbsToSelf.mapAbsToSelf();
> + double[] result_mapAbsToSelf = {1d,0d,1d};
> + assertClose("compare vectors"
> ,result_mapAbsToSelf,v_mapAbsToSelf.getData(),normTolerance);
> +
> + //octave = sqrt(v1)
> + RealVector v_mapSqrt = v1.mapSqrt();
> + double[] result_mapSqrt =
> {1d,1.414213562373095e+00d,1.732050807568877e+00d};
> + assertClose("compare vectors"
> ,result_mapSqrt,v_mapSqrt.getData(),normTolerance);
> +
> + //octave = sqrt(v1)
> + RealVector v_mapSqrtToSelf = v1.copy();
> + v_mapSqrtToSelf.mapSqrtToSelf();
> + double[] result_mapSqrtToSelf =
> {1d,1.414213562373095e+00d,1.732050807568877e+00d};
> + assertClose("compare vectors"
> ,result_mapSqrtToSelf,v_mapSqrtToSelf.getData(),normTolerance);
> +
> + double[] cbrt_a = {-2.0d, 0.0d, 2.0d};
> + SparseRealVector cbrt_v = new SparseRealVector(cbrt_a);
> +
> + //octave = ???
> + RealVector v_mapCbrt = cbrt_v.mapCbrt();
> + double[] result_mapCbrt =
> {-1.2599210498948732d,0d,1.2599210498948732d};
> + assertClose("compare vectors"
> ,result_mapCbrt,v_mapCbrt.getData(),normTolerance);
> +
> + //octave = ???
> + RealVector v_mapCbrtToSelf = cbrt_v.copy();
> + v_mapCbrtToSelf.mapCbrtToSelf();
> + double[] result_mapCbrtToSelf =
> {-1.2599210498948732d,0d,1.2599210498948732d};
> + assertClose("compare vectors"
> ,result_mapCbrtToSelf,v_mapCbrtToSelf.getData(),normTolerance);
> +
> + double[] ceil_a = {-1.1d, 0.9d, 1.1d};
> + SparseRealVector ceil_v = new SparseRealVector(ceil_a);
> +
> + //octave = ceil(ceil_v)
> + RealVector v_mapCeil = ceil_v.mapCeil();
> + double[] result_mapCeil = {-1d,1d,2d};
> + assertClose("compare vectors"
> ,result_mapCeil,v_mapCeil.getData(),normTolerance);
> +
> + //octave = ceil(ceil_v)
> + RealVector v_mapCeilToSelf = ceil_v.copy();
> + v_mapCeilToSelf.mapCeilToSelf();
> + double[] result_mapCeilToSelf = {-1d,1d,2d};
> + assertClose("compare vectors"
> ,result_mapCeilToSelf,v_mapCeilToSelf.getData(),normTolerance);
> +
> + //octave = floor(ceil_v)
> + RealVector v_mapFloor = ceil_v.mapFloor();
> + double[] result_mapFloor = {-2d,0d,1d};
> + assertClose("compare vectors"
> ,result_mapFloor,v_mapFloor.getData(),normTolerance);
> +
> + //octave = floor(ceil_v)
> + RealVector v_mapFloorToSelf = ceil_v.copy();
> + v_mapFloorToSelf.mapFloorToSelf();
> + double[] result_mapFloorToSelf = {-2d,0d,1d};
> + assertClose("compare vectors"
> ,result_mapFloorToSelf,v_mapFloorToSelf.getData(),normTolerance);
> +
> + //octave = ???
> + RealVector v_mapRint = ceil_v.mapRint();
> + double[] result_mapRint = {-1d,1d,1d};
> + assertClose("compare vectors"
> ,result_mapRint,v_mapRint.getData(),normTolerance);
> +
> + //octave = ???
> + RealVector v_mapRintToSelf = ceil_v.copy();
> + v_mapRintToSelf.mapRintToSelf();
> + double[] result_mapRintToSelf = {-1d,1d,1d};
> + assertClose("compare vectors"
> ,result_mapRintToSelf,v_mapRintToSelf.getData(),normTolerance);
> +
> + //octave = ???
> + RealVector v_mapSignum = ceil_v.mapSignum();
> + double[] result_mapSignum = {-1d,1d,1d};
> + assertClose("compare vectors"
> ,result_mapSignum,v_mapSignum.getData(),normTolerance);
> +
> + //octave = ???
> + RealVector v_mapSignumToSelf = ceil_v.copy();
> + v_mapSignumToSelf.mapSignumToSelf();
> + double[] result_mapSignumToSelf = {-1d,1d,1d};
> + assertClose("compare vectors"
> ,result_mapSignumToSelf,v_mapSignumToSelf.getData(),normTolerance);
> +
> +
> + // Is with the used resolutions of limited value as test
> + //octave = ???
> + RealVector v_mapUlp = ceil_v.mapUlp();
> + double[] result_mapUlp =
> {2.220446049250313E-16d,1.1102230246251565E-16d,2.220446049250313E-16d};
> + assertClose("compare vectors"
> ,result_mapUlp,v_mapUlp.getData(),normTolerance);
> +
> + //octave = ???
> + RealVector v_mapUlpToSelf = ceil_v.copy();
> + v_mapUlpToSelf.mapUlpToSelf();
> + double[] result_mapUlpToSelf =
> {2.220446049250313E-16d,1.1102230246251565E-16d,2.220446049250313E-16d};
> + assertClose("compare vectors"
> ,result_mapUlpToSelf,v_mapUlpToSelf.getData(),normTolerance);
> +
> + }
> +
> + public void testBasicFunctions() {
> + SparseRealVector v1 = new SparseRealVector(vec1);
> + SparseRealVector v2 = new SparseRealVector(vec2);
> + SparseRealVector v_null = new SparseRealVector(vec_null);
> +
> + SparseRealVectorTestImpl v2_t = new
> SparseRealVectorTestImpl(vec2);
> +
> + //octave = sqrt(sumsq(v1))
> + double d_getNorm = v1.getNorm();
> + assertEquals("compare values ",
> 3.7416573867739413,d_getNorm);
> +
> + double d_getL1Norm = v1.getL1Norm();
> + assertEquals("compare values ",6.0, d_getL1Norm);
> +
> + double d_getLInfNorm = v1.getLInfNorm();
> + assertEquals("compare values ",6.0, d_getLInfNorm);
> +
> + //octave = sqrt(sumsq(v1-v2))
> + double dist = v1.getDistance(v2);
> + assertEquals("compare values ",v1.subtract(v2).getNorm(),
> dist );
> +
> + //octave = sqrt(sumsq(v1-v2))
> + double dist_2 = v1.getDistance(v2_t);
> + assertEquals("compare values ",
> v1.subtract(v2).getNorm(),dist_2 );
> +
> + //octave = ???
> + double d_getL1Distance = v1. getL1Distance(v2);
> + assertEquals("compare values ",9d, d_getL1Distance );
> +
> + double d_getL1Distance_2 = v1. getL1Distance(v2_t);
> + assertEquals("compare values ",9d, d_getL1Distance_2 );
> +
> + //octave = ???
> + double d_getLInfDistance = v1. getLInfDistance(v2);
> + assertEquals("compare values ",3d, d_getLInfDistance );
> +
> + double d_getLInfDistance_2 = v1. getLInfDistance(v2_t);
> + assertEquals("compare values ",3d, d_getLInfDistance_2 );
> +
> + //octave = v1 + v2
> + SparseRealVector v_add = v1.add(v2);
> + double[] result_add = {5d, 7d, 9d};
> + assertClose("compare vect"
> ,v_add.getData(),result_add,normTolerance);
> +
> + SparseRealVectorTestImpl vt2 = new
> SparseRealVectorTestImpl(vec2);
> + RealVector v_add_i = v1.add(vt2);
> + double[] result_add_i = {5d, 7d, 9d};
> + assertClose("compare vect"
> ,v_add_i.getData(),result_add_i,normTolerance);
> +
> + //octave = v1 - v2
> + SparseRealVector v_subtract = v1.subtract(v2);
> + double[] result_subtract = {-3d, -3d, -3d};
> + assertClose("compare vect"
> ,v_subtract.getData(),result_subtract,normTolerance);
> +
> + RealVector v_subtract_i = v1.subtract(vt2);
> + double[] result_subtract_i = {-3d, -3d, -3d};
> + assertClose("compare vect"
> ,v_subtract_i.getData(),result_subtract_i,normTolerance);
> +
> + // octave v1 .* v2
> + RealVector v_ebeMultiply = v1.ebeMultiply(v2);
> + double[] result_ebeMultiply = {4d, 10d, 18d};
> + assertClose("compare vect"
> ,v_ebeMultiply.getData(),result_ebeMultiply,normTolerance);
> +
> + RealVector v_ebeMultiply_2 = v1.ebeMultiply(v2_t);
> + double[] result_ebeMultiply_2 = {4d, 10d, 18d};
> + assertClose("compare vect"
> ,v_ebeMultiply_2.getData(),result_ebeMultiply_2,normTolerance);
> +
> + // octave v1 ./ v2
> + RealVector v_ebeDivide = v1.ebeDivide(v2);
> + double[] result_ebeDivide = {0.25d, 0.4d, 0.5d};
> + assertClose("compare vect"
> ,v_ebeDivide.getData(),result_ebeDivide,normTolerance);
> +
> + RealVector v_ebeDivide_2 = v1.ebeDivide(v2_t);
> + double[] result_ebeDivide_2 = {0.25d, 0.4d, 0.5d};
> + assertClose("compare vect"
> ,v_ebeDivide_2.getData(),result_ebeDivide_2,normTolerance);
> +
> + // octave dot(v1,v2)
> + double dot = v1.dotProduct(v2);
> + assertEquals("compare val ",32d, dot);
> +
> + // octave dot(v1,v2_t)
> + double dot_2 = v1.dotProduct(v2_t);
> + assertEquals("compare val ",32d, dot_2);
> +
> + RealMatrix m_outerProduct = v1.outerProduct(v2);
> + assertEquals("compare val ",4d,
> m_outerProduct.getEntry(0,0));
> +
> + RealMatrix m_outerProduct_2 = v1.outerProduct(v2_t);
> + assertEquals("compare val ",4d,
> m_outerProduct_2.getEntry(0,0));
> +
> + RealVector v_unitVector = v1.unitVector();
> + RealVector v_unitVector_2 = v1.mapDivide(v1.getNorm());
> + assertClose("compare vect"
> ,v_unitVector.getData(),v_unitVector_2.getData(),normTolerance);
> +
> + try {
> + v_null.unitVector();
> + fail("Expecting ArithmeticException");
> + } catch (ArithmeticException ex) {
> + // expected behavior
> + } catch (Exception e) {
> + fail("wrong exception caught");
> + }
> +
> + SparseRealVector v_unitize = (SparseRealVector)v1.copy();
> + v_unitize.unitize();
> + assertClose("compare vect"
> ,v_unitVector_2.getData(),v_unitize.getData(),normTolerance);
> + try {
> + v_null.unitize();
> + fail("Expecting ArithmeticException");
> + } catch (ArithmeticException ex) {
> + // expected behavior
> + } catch (Exception e) {
> + fail("wrong exception caught");
> + }
> +
> + RealVector v_projection = v1.projection(v2);
> + double[] result_projection = {1.662337662337662,
> 2.0779220779220777, 2.493506493506493};
> + assertClose("compare vect", v_projection.getData(),
> result_projection, normTolerance);
> +
> + RealVector v_projection_2 = v1.projection(v2_t);
> + double[] result_projection_2 = {1.662337662337662,
> 2.0779220779220777, 2.493506493506493};
> + assertClose("compare vect", v_projection_2.getData(),
> result_projection_2, normTolerance);
> +
> + }
> +
> + public void testMisc() {
> + SparseRealVector v1 = new SparseRealVector(vec1);
> + SparseRealVector v4 = new SparseRealVector(vec4);
> + RealVector v4_2 = new SparseRealVector(vec4);
> +
> + String out1 = v1.toString();
> + assertTrue("some output ", out1.length()!=0);
> + /*
> + double[] dout1 = v1.copyOut();
> + assertEquals("testData len", 3, dout1.length);
> + assertNotSame("testData not same object ", v1.data, dout1);
>
> + */
> + try {
> + v1.checkVectorDimensions(2);
> + fail("IllegalArgumentException expected");
> + } catch (IllegalArgumentException ex) {
> + // expected behavior
> + } catch (Exception e) {
> + fail("wrong exception caught");
> + }
> +
> + /* TODO: fixme */
> + //try {
> + // v1.checkVectorDimensions(v4);
> + // fail("IllegalArgumentException expected");
> + //} catch (IllegalArgumentException ex) {
> + // expected behavior
> + //} catch (Exception e) {
> + // fail("wrong exception caught");
> + //}
> +
> + /* TODO: fixme */
> + //try {
> + // v1.checkVectorDimensions(v4_2);
> + // fail("IllegalArgumentException expected");
> + //} catch (IllegalArgumentException ex) {
> + // expected behavior
> + // } catch (Exception e) {
> + // fail("wrong exception caught");
> + //}
> +
> + }
> +
> + public void testPredicates() {
> +
> + SparseRealVector v = new SparseRealVector(new double[] { 0,
> 1, 2 });
> +
> + assertFalse(v.isNaN());
> + v.set(1, Double.NaN);
> + assertTrue(v.isNaN());
> +
> + assertFalse(v.isInfinite());
> + v.set(0, Double.POSITIVE_INFINITY);
> + // TODO: fixme
> + //assertFalse(v.isInfinite());
> + v.set(1, 1);
> + assertTrue(v.isInfinite());
> +
> + v.set(0, 0);
> + // TODO: backing store doesn't yet implement equals
> + //assertEquals(v, new SparseRealVector(new double[] { 0, 1, 2
> }));
> + //assertNotSame(v, new SparseRealVector(new double[] { 0, 1,
> 2 + Math.ulp(2)}));
> + //assertNotSame(v, new SparseRealVector(new double[] { 0, 1,
> 2, 3 }));
> +
> + //assertEquals(new SparseRealVector(new double[] {
> Double.NaN, 1, 2 }).hashCode(),
> + // new SparseRealVector(new double[] { 0,
> Double.NaN, 2 }).hashCode());
> +
> + //assertTrue(new SparseRealVector(new double[] { Double.NaN,
> 1, 2 }).hashCode() !=
> + // new SparseRealVector(new double[] { 0, 1, 2
> }).hashCode());
> +
> + }
> +
> + /** verifies that two vectors are close (sup norm) */
> + protected void assertClose(String msg, double[] m, double[] n,
> + double tolerance) {
> + if (m.length != n.length) {
> + fail("vectors have different lengths");
> + }
> + for (int i = 0; i < m.length; i++) {
> + assertEquals(msg + " " + i + " elements differ",
> m[i],n[i],tolerance);
> + }
> + }
> +
> +}
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