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## org.apache.commons.math.stat.ranking
Class NaturalRanking

    java.lang.Object
      org.apache.commons.math.stat.ranking.NaturalRanking

All Implemented Interfaces:
  RankingAlgorithm

    public class NaturalRanking

extends java.lang.Object
implements RankingAlgorithm

Ranking based on the natural ordering on doubles.

NaNs are treated according to the configured `NaNStrategy` and ties are handled using the selected `TiesStrategy`. Configuration settings are supplied in optional constructor arguments. Defaults are `NaNStrategy.MAXIMAL` and `TiesStrategy.AVERAGE`, respectively. When using `TiesStrategy.RANDOM`, a `RandomGenerator` may be supplied as a constructor argument.

Examples:

Input data: (20, 17, 30, 42.3, 17, 50, Double.NaN, Double.NEGATIVE_INFINITY, 17)
NaNStrategy | TiesStrategy | `rank(data)`
--- | --- | ---
default (NaNs maximal) | default (ties averaged) | (5, 3, 6, 7, 3, 8, 9, 1, 3)
default (NaNs maximal) | MINIMUM | (5, 2, 6, 7, 2, 8, 9, 1, 2)
MINIMAL | default (ties averaged) | (6, 4, 7, 8, 4, 9, 1.5, 1.5, 4)
REMOVED | SEQUENTIAL | (5, 2, 6, 7, 3, 8, 1, 4)
MINIMAL | MAXIMUM | (6, 5, 7, 8, 5, 9, 2, 2, 5)

Since:
  2.0
Version:
  $Revision: 811827 $ $Date: 2009-09-06 11:32:50 -0400 (Sun, 06 Sep 2009) $

Nested Class Summary
`private static class` | `NaturalRanking.IntDoublePair` Represents the position of a double value in an ordering.

Field Summary
`static NaNStrategy` | `DEFAULT_NAN_STRATEGY` default NaN strategy
`static TiesStrategy` | `DEFAULT_TIES_STRATEGY` default ties strategy
`private NaNStrategy` | `nanStrategy` NaN strategy - defaults to NaNs maximal
`private RandomData` | `randomData` Source of random data - used only when ties strategy is RANDOM
`private TiesStrategy` | `tiesStrategy` Ties strategy - defaults to ties averaged

Constructor Summary
`NaturalRanking()` Create a NaturalRanking with default strategies for handling ties and NaNs.
`NaturalRanking(NaNStrategy nanStrategy)` Create a NaturalRanking with the given NaNStrategy.
`NaturalRanking(NaNStrategy nanStrategy, RandomGenerator randomGenerator)` Create a NaturalRanking with the given NaNStrategy, TiesStrategy.RANDOM and the given source of random data.
`NaturalRanking(NaNStrategy nanStrategy, TiesStrategy tiesStrategy)` Create a NaturalRanking with the given NaNStrategy and TiesStrategy.
`NaturalRanking(RandomGenerator randomGenerator)` Create a NaturalRanking with TiesStrategy.RANDOM and the given RandomGenerator as the source of random data.
`NaturalRanking(TiesStrategy tiesStrategy)` Create a NaturalRanking with the given TiesStrategy.

Method Summary
`private boolean` | `containsNaNs(NaturalRanking.IntDoublePair[] ranks)` Checks for presence of NaNs in `ranks.`
`private void` | `fill(double[] data, java.util.List<java.lang.Integer> tiesTrace, double value)` Sets`data[i] = value` for each i in `tiesTrace.`
`private java.util.List<java.lang.Integer>` | `getNanPositions(NaturalRanking.IntDoublePair[] ranks)` Returns a list of indexes where `ranks` is `NaN.`
`NaNStrategy` | `getNanStrategy()` Return the NaNStrategy
`TiesStrategy` | `getTiesStrategy()` Return the TiesStrategy
`double[]` | `rank(double[] data)` Rank `data` using the natural ordering on Doubles, with NaN values handled according to `nanStrategy` and ties resolved using `tiesStrategy.`
`private void` | `recodeNaNs(NaturalRanking.IntDoublePair[] ranks, double value)` Recodes NaN values to the given value.
`private NaturalRanking.IntDoublePair[]` | `removeNaNs(NaturalRanking.IntDoublePair[] ranks)` Returns an array that is a copy of the input array with IntDoublePairs having NaN values removed.
`private void` | `resolveTie(double[] ranks, java.util.List<java.lang.Integer> tiesTrace)` Resolve a sequence of ties, using the configured `TiesStrategy`.
`private void` | `restoreNaNs(double[] ranks, java.util.List<java.lang.Integer> nanPositions)` Set `ranks[i] = Double.NaN` for each i in `nanPositions.`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Field Detail

### DEFAULT_NAN_STRATEGY

    public static final NaNStrategy DEFAULT_NAN_STRATEGY

  default NaN strategy

### DEFAULT_TIES_STRATEGY

    public static final TiesStrategy DEFAULT_TIES_STRATEGY

  default ties strategy

### nanStrategy

    private final NaNStrategy nanStrategy

  NaN strategy - defaults to NaNs maximal

### tiesStrategy

    private final TiesStrategy tiesStrategy

  Ties strategy - defaults to ties averaged

### randomData

    private final RandomData randomData

  Source of random data - used only when ties strategy is RANDOM

Constructor Detail

### NaturalRanking

    public NaturalRanking()

  Create a NaturalRanking with default strategies for handling ties and NaNs.

### NaturalRanking

    public NaturalRanking(TiesStrategy tiesStrategy)

  Create a NaturalRanking with the given TiesStrategy.

  Parameters:
    `tiesStrategy` - the TiesStrategy to use

### NaturalRanking

    public NaturalRanking(NaNStrategy nanStrategy)

  Create a NaturalRanking with the given NaNStrategy.

  Parameters:
    `nanStrategy` - the NaNStrategy to use

### NaturalRanking

    public NaturalRanking(NaNStrategy nanStrategy,
                          TiesStrategy tiesStrategy)

  Create a NaturalRanking with the given NaNStrategy and TiesStrategy.

  Parameters:
    `nanStrategy` - NaNStrategy to use
    `tiesStrategy` - TiesStrategy to use

### NaturalRanking

    public NaturalRanking(RandomGenerator randomGenerator)

  Create a NaturalRanking with TiesStrategy.RANDOM and the given RandomGenerator as the source of random data.

  Parameters:
    `randomGenerator` - source of random data

### NaturalRanking

    public NaturalRanking(NaNStrategy nanStrategy,
                          RandomGenerator randomGenerator)

  Create a NaturalRanking with the given NaNStrategy, TiesStrategy.RANDOM and the given source of random data.

  Parameters:
    `nanStrategy` - NaNStrategy to use
    `randomGenerator` - source of random data

Method Detail

### getNanStrategy

    public NaNStrategy getNanStrategy()

  Return the NaNStrategy

  Returns:
    returns the NaNStrategy

### getTiesStrategy

    public TiesStrategy getTiesStrategy()

  Return the TiesStrategy

  Returns:
    the TiesStrategy

### rank

    public double[] rank(double[] data)

  Rank `data` using the natural ordering on Doubles, with NaN values handled according to `nanStrategy` and ties resolved using `tiesStrategy.`

  Specified by:
    `rank` in interface `RankingAlgorithm`
  Parameters:
    `data` - array to be ranked
  Returns:
    array of ranks

### removeNaNs

    private NaturalRanking.IntDoublePair[] removeNaNs(NaturalRanking.IntDoublePair[] ranks)

  Returns an array that is a copy of the input array with IntDoublePairs having NaN values removed.

  Parameters:
    `ranks` - input array
  Returns:
    array with NaN-valued entries removed

### recodeNaNs

    private void recodeNaNs(NaturalRanking.IntDoublePair[] ranks,
                            double value)

  Recodes NaN values to the given value.

  Parameters:
    `ranks` - array to recode
    `value` - the value to replace NaNs with

### containsNaNs

    private boolean containsNaNs(NaturalRanking.IntDoublePair[] ranks)

  Checks for presence of NaNs in `ranks.`

  Parameters:
    `ranks` - array to be searched for NaNs
  Returns:
    true iff ranks contains one or more NaNs

### resolveTie

    private void resolveTie(double[] ranks,
                            java.util.List<java.lang.Integer> tiesTrace)

  Resolve a sequence of ties, using the configured `TiesStrategy`. The input `ranks` array is expected to take the same value for all indices in `tiesTrace`. The common value is recoded according to the tiesStrategy. For example, if ranks = <5,8,2,6,2,7,1,2>, tiesTrace = <2,4,7> and tiesStrategy is MINIMUM, ranks will be unchanged. The same array and trace with tiesStrategy AVERAGE will come out <5,8,3,6,3,7,1,3>.

  Parameters:
    `ranks` - array of ranks
    `tiesTrace` - list of indices where `ranks` is constant -- that is, for any i and j in TiesTrace, `ranks[i] == ranks[j]`

### fill

    private void fill(double[] data,
                      java.util.List<java.lang.Integer> tiesTrace,
                      double value)

  Sets`data[i] = value` for each i in `tiesTrace.`

  Parameters:
    `data` - array to modify
    `tiesTrace` - list of index values to set
    `value` - value to set

### restoreNaNs

    private void restoreNaNs(double[] ranks,
                             java.util.List<java.lang.Integer> nanPositions)

  Set `ranks[i] = Double.NaN` for each i in `nanPositions.`

  Parameters:
    `ranks` - array to modify
    `nanPositions` - list of index values to set to `Double.NaN`

### getNanPositions

    private java.util.List<java.lang.Integer> getNanPositions(NaturalRanking.IntDoublePair[] ranks)

  Returns a list of indexes where `ranks` is `NaN.`

  Parameters:
    `ranks` - array to search for `NaNs`
  Returns:
    list of indexes i such that `ranks[i] = NaN`

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