runningStatisticsBy()

Calculate summary statistics (count, sum, mean, min, max, variance, and standard deviation) of BigDecimal objects mapped from a Stream<INPUT> via a mappingFunction so far.

Implementation Notes

This implementation is suitable for mapping an arbitrary Stream<INPUT> to BigDecimal via a mappingFunction; for a version that operates directly on a Stream<BigDecimal>, see runningStatistics(). By default, nulls are ignored and play no part in calculations, see treatNullAs() and treatNullAsZero() below for ways to change this behavior. The default MathContext for all calculations is MathContext.DECIMAL64, but this can be overridden (see withMathContext(), below).

Each emitted StatisticalSummary record describes every mapped value seen so far:

Field	Meaning
`count`	How many values are summarized. Ignored `null` values are not counted.
`sum`	The sum of the values
`mean`	The arithmetic mean of the values
`min`	The smallest value
`max`	The largest value
`populationVariance`	The variance, treating the values as the entire dataset (divided by n)
`populationStandardDeviation`	The standard deviation, treating the values as the entire dataset
`sampleVariance`	The variance, treating the values as a sample of a larger population (divided by n - 1). May be `null`.
`sampleStandardDeviation`	The standard deviation, treating the values as a sample of a larger population. May be `null`.

The sample variance and sample standard deviation of a single value are undefined, so sampleVariance and sampleStandardDeviation are null until at least two values have been summarized. Every other field always has a value.

Every value is the same as the corresponding single-statistic gatherer would produce for the same input. Each summary calculates every field, including two square roots, so if you only need one statistic, the dedicated gatherer is cheaper.

Signatures

runningStatisticsBy(Function<INPUT, BigDecimal> mappingFunction)

mappingFunction - A non-null function to map stream INPUT elements into BigDecimal for calculation

Additional Methods

Method	Purpose
`treatNullAsZero()`	When encountering a `null` value in a stream, treat it as `BigDecimal.ZERO` instead. See example.
`treatNullAs(BigDecimal replacement)`	When encountering a `null` value in a stream, treat it as the given `replacement` value instead. See example.
`treatNullAsOne()`	When encountering a `null` value in a stream, treat it as `BigDecimal.ONE` instead.
`withMathContext(MathContext mathContext)`	Replace the `MathContext` used for all mathematical operations performed by this gatherer. See example.
`withOriginal()`	Include the original input value from the stream in addition to the calculated value in a `WithOriginal` record. See example.

Examples

Running statistics, mapped from an object

record NamedValue(String name, BigDecimal value) {}

Stream
    .of(
        new NamedValue("first",  new BigDecimal("1.0")),
        new NamedValue("second", new BigDecimal("2.0")),
        new NamedValue("third",  new BigDecimal("10.0")),
        new NamedValue("fourth", new BigDecimal("2.0"))
    )
    .gather(Gatherers4j.runningStatisticsBy(NamedValue::value))
    .toList();

// [
//   StatisticalSummary[count=1, sum=1.0, mean=1.0, min=1.0, max=1.0, populationVariance=0.00, populationStandardDeviation=0.0, sampleVariance=null, sampleStandardDeviation=null]
//   StatisticalSummary[count=2, sum=3.0, mean=1.5, min=1.0, max=2.0, populationVariance=0.25, populationStandardDeviation=0.5, sampleVariance=0.50, sampleStandardDeviation=0.7071067811865475]
//   StatisticalSummary[count=3, sum=13.0, mean=4.333333333333333, min=1.0, max=10.0, populationVariance=16.22222222222222, populationStandardDeviation=4.02768199119819, sampleVariance=24.33333333333333, sampleStandardDeviation=4.932882862316247]
//   StatisticalSummary[count=4, sum=15.0, mean=3.75, min=1.0, max=10.0, populationVariance=13.1875, populationStandardDeviation=3.631459761583488, sampleVariance=17.58333333333333, sampleStandardDeviation=4.193248541803041]
// ]

Showing nulls are ignored by default

record NamedValue(String name, BigDecimal value) {}

Stream
    .of(
        new NamedValue("first",  null),
        new NamedValue("second", null),
        new NamedValue("third",  new BigDecimal("10.0")),
        new NamedValue("fourth", new BigDecimal("2.0"))
    )
    .gather(Gatherers4j.runningStatisticsBy(NamedValue::value))
    .toList();

// [
//   StatisticalSummary[count=1, sum=10.0, mean=10.0, min=10.0, max=10.0, populationVariance=0.00, populationStandardDeviation=0.0, sampleVariance=null, sampleStandardDeviation=null]
//   StatisticalSummary[count=2, sum=12.0, mean=6.0, min=2.0, max=10.0, populationVariance=16.00, populationStandardDeviation=4.0, sampleVariance=32.00, sampleStandardDeviation=5.65685424949238]
// ]

Treating null as zero

record NamedValue(String name, BigDecimal value) {}

Stream
    .of(
        new NamedValue("first",  null),
        new NamedValue("second", null),
        new NamedValue("third",  new BigDecimal("10.0")),
        new NamedValue("fourth", new BigDecimal("2.0"))
    )
    .gather(Gatherers4j.runningStatisticsBy(NamedValue::value).treatNullAsZero())
    .toList();

// [
//   StatisticalSummary[count=1, sum=0, mean=0, min=0, max=0, populationVariance=0, populationStandardDeviation=0, sampleVariance=null, sampleStandardDeviation=null]
//   StatisticalSummary[count=2, sum=0, mean=0, min=0, max=0, populationVariance=0, populationStandardDeviation=0, sampleVariance=0, sampleStandardDeviation=0]
//   StatisticalSummary[count=3, sum=10.0, mean=3.333333333333333, min=0, max=10.0, populationVariance=22.22222222222222, populationStandardDeviation=4.714045207910317, sampleVariance=33.33333333333333, sampleStandardDeviation=5.773502691896257]
//   StatisticalSummary[count=4, sum=12.0, mean=3.0, min=0, max=10.0, populationVariance=17.00, populationStandardDeviation=4.123105625617661, sampleVariance=22.66666666666667, sampleStandardDeviation=4.760952285695234]
// ]

Replacing null with another `BigDecimal`

record NamedValue(String name, BigDecimal value) {}

Stream
    .of(
        new NamedValue("first",  null),
        new NamedValue("second", null),
        new NamedValue("third",  new BigDecimal("10.0")),
        new NamedValue("fourth", new BigDecimal("2.0"))
    )
    .gather(Gatherers4j.runningStatisticsBy(NamedValue::value).treatNullAs(new BigDecimal("3.5")))
    .toList();

// [
//   StatisticalSummary[count=1, sum=3.5, mean=3.5, min=3.5, max=3.5, populationVariance=0.00, populationStandardDeviation=0.0, sampleVariance=null, sampleStandardDeviation=null]
//   StatisticalSummary[count=2, sum=7.0, mean=3.5, min=3.5, max=3.5, populationVariance=0.00, populationStandardDeviation=0.0, sampleVariance=0.00, sampleStandardDeviation=0.0]
//   StatisticalSummary[count=3, sum=17.0, mean=5.666666666666667, min=3.5, max=10.0, populationVariance=9.388888888888889, populationStandardDeviation=3.064129385141706, sampleVariance=14.08333333333333, sampleStandardDeviation=3.752776749732567]
//   StatisticalSummary[count=4, sum=19.0, mean=4.75, min=2.0, max=10.0, populationVariance=9.5625, populationStandardDeviation=3.092329219213245, sampleVariance=12.75, sampleStandardDeviation=3.570714214271425]
// ]

Specifying a new `MathContext`

record NamedValue(String name, BigDecimal value) {}

Stream
    .of(
        new NamedValue("first",  new BigDecimal("1.0")),
        new NamedValue("second", new BigDecimal("2.0")),
        new NamedValue("third",  new BigDecimal("10.0")),
        new NamedValue("fourth", new BigDecimal("2.0"))
    )
    .gather(Gatherers4j
        .runningStatisticsBy(NamedValue::value)
        .withMathContext(new MathContext(3, RoundingMode.DOWN))
    )
    .toList();

// [
//   StatisticalSummary[count=1, sum=1.0, mean=1.0, min=1.0, max=1.0, populationVariance=0.00, populationStandardDeviation=0.0, sampleVariance=null, sampleStandardDeviation=null]
//   StatisticalSummary[count=2, sum=3.0, mean=1.5, min=1.0, max=2.0, populationVariance=0.25, populationStandardDeviation=0.5, sampleVariance=0.50, sampleStandardDeviation=0.707]
//   StatisticalSummary[count=3, sum=13.0, mean=4.33, min=1.0, max=10.0, populationVariance=16.2, populationStandardDeviation=4.02, sampleVariance=24.3, sampleStandardDeviation=4.92]
//   StatisticalSummary[count=4, sum=15.0, mean=3.75, min=1.0, max=10.0, populationVariance=13.1, populationStandardDeviation=3.61, sampleVariance=17.5, sampleStandardDeviation=4.18]
// ]

Emitting a record containing the original and calculated values

record NamedValue(String name, BigDecimal value) {}

Stream
    .of(
        new NamedValue("first",  new BigDecimal("1.0")),
        new NamedValue("second", new BigDecimal("2.0")),
        new NamedValue("third",  new BigDecimal("10.0")),
        new NamedValue("fourth", new BigDecimal("2.0"))
    )
    .gather(Gatherers4j.runningStatisticsBy(NamedValue::value).withOriginal())
    .toList();

// [
//   WithOriginal[original=NamedValue[name=first, value=1.0], calculated=StatisticalSummary[count=1, sum=1.0, mean=1.0, min=1.0, max=1.0, populationVariance=0.00, populationStandardDeviation=0.0, sampleVariance=null, sampleStandardDeviation=null]]
//   WithOriginal[original=NamedValue[name=second, value=2.0], calculated=StatisticalSummary[count=2, sum=3.0, mean=1.5, min=1.0, max=2.0, populationVariance=0.25, populationStandardDeviation=0.5, sampleVariance=0.50, sampleStandardDeviation=0.7071067811865475]]
//   WithOriginal[original=NamedValue[name=third, value=10.0], calculated=StatisticalSummary[count=3, sum=13.0, mean=4.333333333333333, min=1.0, max=10.0, populationVariance=16.22222222222222, populationStandardDeviation=4.02768199119819, sampleVariance=24.33333333333333, sampleStandardDeviation=4.932882862316247]]
//   WithOriginal[original=NamedValue[name=fourth, value=2.0], calculated=StatisticalSummary[count=4, sum=15.0, mean=3.75, min=1.0, max=10.0, populationVariance=13.1875, populationStandardDeviation=3.631459761583488, sampleVariance=17.58333333333333, sampleStandardDeviation=4.193248541803041]]
// ]