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BloomFilter: set a lower bound on nHashFuncs of 1: there must always be at least one function. Thanks to Kalpesh Parmar for debugging this.

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Static import Math for shorter more readable code.
This commit is contained in:
Mike Hearn 2014-05-13 13:06:48 +02:00
parent cbd91c7ea1
commit 443b62481d
1 changed files with 7 additions and 5 deletions
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12
core/src/main/java/com/google/bitcoin/core/BloomFilter.java
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@ -23,6 +23,7 @@ import java.io.OutputStream;
import java.util.Arrays;
import static com.google.common.base.Preconditions.checkArgument;
import static java.lang.Math.*;
/**
* <p>A Bloom filter is a probabilistic data structure which can be sent to another client so that it can avoid
@ -101,11 +102,12 @@ public class BloomFilter extends Message {
public BloomFilter(int elements, double falsePositiveRate, long randomNonce, BloomUpdate updateFlag) {
// The following formulas were stolen from Wikipedia's page on Bloom Filters (with the addition of min(..., MAX_...))
// Size required for a given number of elements and false-positive rate
int size = Math.min((int)(-1 / (Math.pow(Math.log(2), 2)) * elements * Math.log(falsePositiveRate)),
(int)MAX_FILTER_SIZE * 8) / 8;
data = new byte[size <= 0 ? 1 : size];
int size = (int)(-1 / (pow(log(2), 2)) * elements * log(falsePositiveRate));
size = max(1, min(size, (int) MAX_FILTER_SIZE * 8) / 8);
data = new byte[size];
// Optimal number of hash functions for a given filter size and element count.
hashFuncs = Math.min((int)(data.length * 8 / (double)elements * Math.log(2)), MAX_HASH_FUNCS);
hashFuncs = (int)(data.length * 8 / (double)elements * log(2));
hashFuncs = max(1, min(hashFuncs, MAX_HASH_FUNCS));
this.nTweak = randomNonce;
this.nFlags = (byte)(0xff & updateFlag.ordinal());
}
@ -114,7 +116,7 @@ public class BloomFilter extends Message {
* Returns the theoretical false positive rate of this filter if were to contain the given number of elements.
*/
public double getFalsePositiveRate(int elements) {
return Math.pow(1 - Math.pow(Math.E, -1.0 * (hashFuncs * elements) / (data.length * 8)), hashFuncs);
return pow(1 - pow(E, -1.0 * (hashFuncs * elements) / (data.length * 8)), hashFuncs);
}
@Override