[jira] [Created] (STATISTICS-63) Port o.a.c.math.stat.ranking to a commons-statistics-ranking module

["Alex Herbert (Jira)" <ji...@apache.org>]

Alex Herbert created STATISTICS-63:
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             Summary: Port o.a.c.math.stat.ranking to a commons-statistics-ranking module
                 Key: STATISTICS-63
                 URL: https://issues.apache.org/jira/browse/STATISTICS-63
             Project: Commons Statistics
          Issue Type: New Feature
          Components: ranking
    Affects Versions: 1.0
            Reporter: Alex Herbert


The o.a.c.math4.legacy.stat.ranking package contains:
{noformat}
NaNStrategy.java
NaturalRanking.java
RankingAlgorithm.java
TiesStrategy.java{noformat}
There are no dependencies on other math packages.

The TiesStrategy enum contains a RANDOM option:
{noformat}
"Ties get a random integral value from among applicable ranks."{noformat}
I would suggest this is changed to
{noformat}
"Ties get a randomly assigned unique value from among applicable ranks."{noformat}
This is a minor change. But it allows ties to always be distinguished, which seems to be the purpose of a tie strategy. The current implementation in math just picks a random number and so ties can be resolved by assigning the same rank to multiple points (thus not resolving anything).

For example:
{noformat}
[0, 1, 1, 1, 2]{noformat}
Can have an output of:
{noformat}
[0, 1, 2, 3, 4]
[0, 1, 1, 1, 4]
[0, 3, 3, 3, 4]
etc{noformat}
The suggested change would enumerate the ranks for the ties and then shuffle them. All ranks would then be unique:
{noformat}
[0, 1, 2, 3, 4]
[0, 1, 3, 2, 4]
[0, 3, 2, 1, 4]
etc{noformat}
A second issue with the ranking package is it brings in a dependency on UniformRandomProvider. If you do not supply one then an instance is created (which may not be needed).

Given that we now support JDK 8 I suggest the default uses an instance of {{{}SplittableRandom{}}}. The user can override this by supplying a source of random bits as a {{{}LongSupplier{}}}. This can be used as a source of randomness for UniformRandomProvider from RNG. This is a functional interface and using the long bits it can create random rank indices as required. The package then does not expose non-JDK interfaces in its public API.

Currently the NaturalRanking class has 6 constructors to set combinations for the three properties: TiesStrategy; NaNStragtegy; and source of randomness. Current API:
{noformat}
public NaturalRanking()
public NaturalRanking(TiesStrategy)
public NaturalRanking(NaNStrategy)
public NaturalRanking(NaNStrategy, TiesStrategy)
public NaturalRanking(UniformRandomProvider)
public NaturalRanking(NaNStrategy, UniformRandomProvider){noformat}
The constructors that accept a TiesStrategy create a generator even though the TiesStrategy may not require it (i.e. is not RANDOM). The generator should be created on demand when ties occur in the data.

Note: The set of constructors could be changed to a builder pattern. This would add builder object creation overhead for any new strategy. It also does not allow implicit setting of the TiesStrategy to RANDOM if a constructor with a source of randomness is used. An initial port can maintain the current 6 constructors. It can be changed before the first release.



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