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Standardise the Bloom filter shape equations.

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Equations match those in:

https://hur.st/bloomfilter/

Fixed documentation of the approximate value of the denominator. Compute
using a re-arrangement.
This commit is contained in:
Alex Herbert 2020-03-10 01:53:12 +00:00
parent 03543e5f9b
commit cb967680c3
1 changed files with 7 additions and 5 deletions
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12
src/main/java/org/apache/commons/collections4/bloomfilter/hasher/Shape.java
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@ -29,7 +29,7 @@ import java.util.Objects;
*
* <dl> <dt>Number of Items (AKA: {@code n})</dt>
* <dd>{@code n = ceil(m / (-k / log(1 - exp(log(p) / k))))}</dd> <dt>Probability of
* Collision (AKA: {@code p})</dt> <dd>{@code p = (1 - exp(-kn/m))^k}</dd> <dt>Number
* Collision (AKA: {@code p})</dt> <dd>{@code p = pow(1 - exp(-k / (m / n)), k)}</dd> <dt>Number
* of Bits (AKA: {@code m})</dt>
* <dd>{@code m = ceil((n * log(p)) / log(1 / pow(2, log(2))))}</dd> <dt>Number of
* Functions (AKA: {@code k})</dt> <dd>{@code k = round((m / n) * log(2))}</dd> </dl>
@ -46,14 +46,16 @@ import java.util.Objects;
public final class Shape {
/**
* The natural logarithm of 2. Used in several calculations. Approximately 0.693147180.
* The natural logarithm of 2. Used in several calculations. Approximately 0.693147180559945.
*/
private static final double LOG_OF_2 = Math.log(2.0);
/**
* 1 / 2^log(2). Used in calculating the number of bits. Approximately -0.090619058.
* log(1 / 2^log(2)). Used in calculating the number of bits. Approximately -0.480453013918201.
*
* <p>log(1 / 2^log(2)) = log(1) - log(2^log(2)) = -log(2) * log(2)
*/
private static final double DENOMINATOR = Math.log(1.0 / Math.pow(2.0, LOG_OF_2));
private static final double DENOMINATOR = -LOG_OF_2 * LOG_OF_2;
/**
* Number of items in the filter. AKA: {@code n}.
@ -402,7 +404,7 @@ public final class Shape {
/**
* Calculates the probability of false positives ({@code p}) given
* numberOfItems ({@code n}), numberOfBits ({@code m}) and numberOfHashFunctions ({@code k}).
* <pre>p = (1 - exp(-kn/m))^k</pre>
* <pre>p = pow(1 - exp(-k / (m / n)), k)</pre>
*
* <p>This is the probability that a Bloom filter will return true for the presence of an item
* when it does not contain the item.