Experiment with statistic - 1
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package scientifik.kmath.stat
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import scientifik.kmath.operations.Field
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import scientifik.kmath.operations.RealField
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import scientifik.kmath.operations.Ring
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import scientifik.kmath.operations.Space
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import scientifik.kmath.structures.NDStructure
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import kotlin.math.pow
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// TODO tailrec
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fun <T> Ring<T>.pow(element : T, n : Int) : T {
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if (n == 0 ){
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return one
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}
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if (n==1){
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return element
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}
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val temp = pow(element, n / 2)
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return if (n%2==0) temp*temp else element*temp*temp
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}
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//fun <T,R> NDStructure<T>.map(transform : (T) -> R) : NDStructure<R>{
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//
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//}
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/**
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* Context for sequence-like operations
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*/
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class CollectionsOperations<T>(val context: Space<T>){
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fun sum(structure: NDStructure<T>): T {
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return with(context){
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var sum = zero
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for (element in structure.elements()) {
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sum += element.second
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}
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sum
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}
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}
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}
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/**
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* Context for statistical operations
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*/
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open class Statistical<T>(val context : Field<T>){
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fun mean(data : NDStructure<T>) = moment(data, 1)
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fun variance(data: NDStructure<T>) = centralMomentum(data, 2)
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fun moment(data: NDStructure<T>, k : Int) : T{
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return with(context){
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var result = zero
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val number = data.shape.reduce { acc, i -> acc*i }
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for (element in data.elements()){
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result += pow(element.second, k)
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}
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result/number
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}
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}
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fun centralMomentum(data: NDStructure<T>, k: Int) = with(context){moment(data, k) - pow(mean(data), k)}
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}
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class RealStatistical : Statistical<Double>(RealField){
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fun std(data : NDStructure<Double>) = with(context){variance(data).pow(0.5)}
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}
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