public void doTest2() {
final int totalGenerated = 1000000;
final int maxRandom = 100000;
final int bucketSize = 100;
final int iterations = 100;
// final int samplesPerIteration = 100;
ACETree aceTree;
ACETreeSearch aceTreeSearch = null;
ArrayList<Distribution> distributionsACETree = new ArrayList<Distribution>();
ArrayList<Distribution> distributionsRandom = new ArrayList<Distribution>();
/* Create data */
Data dataACETree = new Data(totalGenerated, maxRandom);
/* construct the ACETree */
int numbers[] = new int[dataACETree.d.size()];
for (int i = 0; i < numbers.length; i++) {
numbers[i] = dataACETree.d.get(i);
}
aceTree = new ACETree(numbers);
aceTreeSearch = new ACETreeSearch(aceTree, new Range(0, maxRandom));
/* create distribution for ACETree */
Buckets bucketsACETree = new Buckets(dataACETree, bucketSize, maxRandom);
Distribution distACETree = new Distribution("ACETree", dataACETree, bucketsACETree);
distACETree.print();
distributionsACETree.add(distACETree);
/* create distribution for RANDOM */
Data dataRandom = new Data(dataACETree);
Buckets bucketsRandom = new Buckets(dataRandom, bucketSize, maxRandom);
Distribution distRandom = new Distribution("Random", dataRandom, bucketsRandom);
distRandom.print();
distributionsRandom.add(distACETree);
Distribution dPrevACETree = distACETree;
Distribution dPrevRandom = distRandom;
for (int iter = 0; iter < iterations; iter++) {
/* Remove the samples from ACETree */
ArrayList<Integer> result = aceTreeSearch.search();
Util.log(Util.None, "[%d] Samples returned from the ACETree\n", result.size());
/* remove this from our bucket */
for (int i : result) {
dataACETree.d.remove(new Integer(i));
}
/* Remove the same number from Random */
for (int samples = 0; samples < result.size(); samples++) {
int index = (int) (dataRandom.d.size() * Math.random());
dataRandom.d.remove(index);
}
/* create a new distribution for ACETree: */
Buckets bNewACETree = new Buckets(dataACETree, bucketSize, maxRandom);
Distribution dNewACETree = new Distribution("ACETree", dataACETree, bNewACETree);
dNewACETree.print();
distributionsACETree.add(dNewACETree);
/* compare with the previous distribution */
// dNewACETree.compare(dPrevACETree);
dPrevACETree = dNewACETree;
/* create a new distribution for Random: */
Buckets bNewRandom = new Buckets(dataRandom, bucketSize, maxRandom);
Distribution dNewRandom = new Distribution("Random", dataRandom, bNewRandom);
dNewRandom.print();
distributionsRandom.add(dNewRandom);
/* compare with the previous distribution */
// dNewRandom.compare(dPrevRandom);
dPrevRandom = dNewRandom;
}
Distribution dFirst, dLast;
Util.log(Util.Minimal, "Size of distributions [%d]\n", distributionsACETree.size());
Util.log(Util.Minimal, "Comparing ACETree\n");
dLast = distributionsACETree.get(distributionsACETree.size() - 1);
dFirst = distributionsACETree.get(0);
dLast.compare(dFirst);
Util.log(Util.Minimal, "Comparing Random\n");
Util.log(Util.Minimal, "Size of distributions [%d]\n", distributionsRandom.size());
dLast = distributionsRandom.get(distributionsRandom.size() - 1);
dFirst = distributionsRandom.get(0);
dLast.compare(dFirst);
}
/*
*
* 1. Create random data. Create bucket for it and store it.
* 2. for a few iterations:
* 2. Draw some random samples from data.
* 3. Create another distribution.
* 4. Compare the distribution with the previous one for score.
*/
public void doTest(int sampleMethod) {
final int totalGenerated = 100000;
final int maxRandom = 10000;
final int bucketSize = 100;
final int iterations = 2;
final int samplesPerIteration = 100;
ACETree aceTree;
ACETreeSearch aceTreeSearch = null;
ArrayList<Distribution> distributions = new ArrayList<Distribution>();
/* Create data */
Data data = new Data(totalGenerated, maxRandom);
if (sampleMethod == ACETreeSample) {
int numbers[] = new int[data.d.size()];
for (int i = 0; i < numbers.length; i++) {
numbers[i] = data.d.get(i);
}
aceTree = new ACETree(numbers);
aceTreeSearch = new ACETreeSearch(aceTree, new Range(0, maxRandom));
}
Buckets buckets = new Buckets(data, bucketSize, maxRandom);
Distribution distribution =
new Distribution(sampleMethod == RandomSample ? "Random" : "ACETree", data, buckets);
distribution.print();
distributions.add(distribution);
Distribution dPrev = distribution;
for (int iter = 0; iter < iterations; iter++) {
/* remove a few samples */
if (sampleMethod == RandomSample) {
for (int samples = 0; samples < samplesPerIteration; samples++) {
int index = (int) (data.d.size() * Math.random());
data.d.remove(index);
}
} else if (sampleMethod == ACETreeSample) {
ArrayList<Integer> result = aceTreeSearch.search();
Util.log(Util.None, "[%d] Samples returned from the ACETree\n", result.size());
/* remove this from our bucket */
for (int i : result) {
data.d.remove(new Integer(i));
}
}
/* create a new distribution */
Buckets bNew = new Buckets(data, bucketSize, maxRandom);
Distribution dNew =
new Distribution(sampleMethod == RandomSample ? "Random" : "ACETree", data, bNew);
dNew.print();
distributions.add(dNew);
/* compare with the previous distribution */
dNew.compare(dPrev);
dPrev = dNew;
}
}
