org.nield.kotlinstatistics.LongStatistics.kt Maven / Gradle / Ivy

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Statistical and analytical extensions for Kotlin
There is a newer version: 1.2.1
package org.nield.kotlinstatistics

import org.apache.commons.math3.stat.StatUtils
import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

val LongArray.descriptiveStatistics: Descriptives get() = DescriptiveStatistics().apply { forEach { addValue(it.toDouble()) } }.let(::ApacheDescriptives)
fun LongArray.geometricMean() = StatUtils.geometricMean(asSequence().map { it.toDouble() }.toList().toDoubleArray() )
fun LongArray.median() = percentile(50.0)
fun LongArray.percentile(percentile: Double) = StatUtils.percentile(asSequence().map { it.toDouble() }.toList().toDoubleArray(), percentile)
fun LongArray.variance() = StatUtils.variance(asSequence().map { it.toDouble() }.toList().toDoubleArray())
fun LongArray.sumOfSquares() = StatUtils.sumSq(asSequence().map { it.toDouble() }.toList().toDoubleArray())
fun LongArray.standardDeviation() = descriptiveStatistics.standardDeviation
fun LongArray.normalize() = StatUtils.normalize(asSequence().map { it.toDouble() }.toList().toDoubleArray())
val LongArray.kurtosis get() = descriptiveStatistics.kurtosis
val LongArray.skewness get() = descriptiveStatistics.skewness



// AGGREGATION OPERATORS

inline fun  Sequence.sumBy(crossinline keySelector: (T) -> K, crossinline longSelector: (T) -> Long) =
        groupApply(keySelector, longSelector) { it.sum() }

inline fun  Iterable.sumBy(crossinline keySelector: (T) -> K, crossinline longSelector: (T) -> Long) =
        asSequence().sumBy(keySelector, longSelector)


fun  Sequence>.sumBy() =
        groupApply({it.first}, {it.second}) { it.sum() }

fun  Iterable>.sumBy() = asSequence().sumBy()






inline fun  Sequence.averageBy(crossinline keySelector: (T) -> K, crossinline longSelector: (T) -> Long) =
        groupApply(keySelector, longSelector) { it.average() }

inline fun  Iterable.averageBy(crossinline keySelector: (T) -> K, crossinline valueSelector: (T) -> Long) =
        asSequence().averageBy(keySelector, valueSelector)


fun  Sequence>.averageBy() =
        groupApply({it.first}, {it.second}) { it.average() }

fun  Iterable>.averageBy() = asSequence().averageBy()



// bin operators

inline fun  Sequence.binByLong(binSize: Long,
                                     crossinline valueSelector: (T) -> Long,
                                     rangeStart: Long? = null
) = toList().binByLong(binSize, valueSelector, rangeStart)


inline fun  Sequence.binByLong(binSize: Long,
                                        crossinline valueSelector: (T) -> Long,
                                        crossinline groupOp: (List) -> G,
                                        rangeStart: Long? = null
) = toList().binByLong(binSize, valueSelector, groupOp, rangeStart)



inline fun  Iterable.binByLong(binSize: Long,
                                 crossinline valueSelector: (T) -> Long,
                                 rangeStart: Long? = null
): BinModel, Long> = toList().binByLong(binSize, valueSelector, { it }, rangeStart)


inline fun  Iterable.binByLong(binSize: Long,
                                    crossinline valueSelector: (T) -> Long,
                                    crossinline groupOp: (List) -> G,
                                    rangeStart: Long? = null
) = toList().binByLong(binSize, valueSelector, groupOp, rangeStart)


inline fun  List.binByLong(binSize: Long,
                                       crossinline valueSelector: (T) -> Long,
                                       rangeStart: Long? = null
): BinModel, Long> = binByLong(binSize, valueSelector, { it }, rangeStart)

inline fun  List.binByLong(binSize: Long,
                                    crossinline valueSelector: (T) -> Long,
                                    crossinline groupOp: (List) -> G,
                                    rangeStart: Long? = null
): BinModel {

    val groupedByC = asSequence().groupBy(valueSelector)
    val minC = rangeStart?:groupedByC.keys.min()!!
    val maxC = groupedByC.keys.max()!!

    val bins = mutableListOf>().apply {
        var currentRangeStart = minC
        var currentRangeEnd = minC
        while  (currentRangeEnd < maxC) {
            currentRangeEnd = currentRangeStart + binSize - 1L
            add(currentRangeStart..currentRangeEnd)
            currentRangeStart = currentRangeEnd + 1L
        }
    }

    return bins.asSequence()
            .map { it to mutableListOf() }
            .map { binWithList ->
                groupedByC.entries.asSequence()
                        .filter { it.key in binWithList.first }
                        .forEach { binWithList.second.addAll(it.value) }
                binWithList
            }.map { Bin(it.first, groupOp(it.second)) }
            .toList()
            .let(::BinModel)
}