142 lines
4.2 KiB
PHP
142 lines
4.2 KiB
PHP
<?php
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declare(strict_types=1);
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namespace Phpml\Math\Statistic;
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use Phpml\Exception\InvalidArgumentException;
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/**
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* Analysis of variance
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* https://en.wikipedia.org/wiki/Analysis_of_variance
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*/
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final class ANOVA
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{
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/**
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* The one-way ANOVA tests the null hypothesis that 2 or more groups have
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* the same population mean. The test is applied to samples from two or
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* more groups, possibly with differing sizes.
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*
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* @param array[] $samples - each row is class samples
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*
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* @return float[]
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*/
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public static function oneWayF(array $samples): array
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{
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$classes = count($samples);
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if ($classes < 2) {
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throw new InvalidArgumentException('The array must have at least 2 elements');
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}
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$samplesPerClass = array_map(static function (array $class): int {
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return count($class);
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}, $samples);
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$allSamples = (int) array_sum($samplesPerClass);
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$ssAllSamples = self::sumOfSquaresPerFeature($samples);
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$sumSamples = self::sumOfFeaturesPerClass($samples);
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$squareSumSamples = self::sumOfSquares($sumSamples);
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$sumSamplesSquare = self::squaresSum($sumSamples);
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$ssbn = self::calculateSsbn($samples, $sumSamplesSquare, $samplesPerClass, $squareSumSamples, $allSamples);
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$sswn = self::calculateSswn($ssbn, $ssAllSamples, $squareSumSamples, $allSamples);
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$dfbn = $classes - 1;
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$dfwn = $allSamples - $classes;
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$msb = array_map(static function ($s) use ($dfbn) {
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return $s / $dfbn;
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}, $ssbn);
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$msw = array_map(static function ($s) use ($dfwn) {
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if ($dfwn === 0) {
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return 1;
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}
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return $s / $dfwn;
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}, $sswn);
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$f = [];
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foreach ($msb as $index => $msbValue) {
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$f[$index] = $msbValue / $msw[$index];
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}
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return $f;
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}
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private static function sumOfSquaresPerFeature(array $samples): array
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{
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$sum = array_fill(0, count($samples[0][0]), 0);
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foreach ($samples as $class) {
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foreach ($class as $sample) {
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foreach ($sample as $index => $feature) {
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$sum[$index] += $feature ** 2;
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}
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}
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}
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return $sum;
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}
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private static function sumOfFeaturesPerClass(array $samples): array
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{
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return array_map(static function (array $class): array {
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$sum = array_fill(0, count($class[0]), 0);
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foreach ($class as $sample) {
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foreach ($sample as $index => $feature) {
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$sum[$index] += $feature;
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}
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}
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return $sum;
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}, $samples);
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}
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private static function sumOfSquares(array $sums): array
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{
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$squares = array_fill(0, count($sums[0]), 0);
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foreach ($sums as $row) {
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foreach ($row as $index => $sum) {
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$squares[$index] += $sum;
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}
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}
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return array_map(static function ($sum) {
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return $sum ** 2;
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}, $squares);
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}
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private static function squaresSum(array $sums): array
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{
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foreach ($sums as &$row) {
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foreach ($row as &$sum) {
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$sum **= 2;
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}
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}
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return $sums;
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}
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private static function calculateSsbn(array $samples, array $sumSamplesSquare, array $samplesPerClass, array $squareSumSamples, int $allSamples): array
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{
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$ssbn = array_fill(0, count($samples[0][0]), 0);
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foreach ($sumSamplesSquare as $classIndex => $class) {
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foreach ($class as $index => $feature) {
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$ssbn[$index] += $feature / $samplesPerClass[$classIndex];
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}
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}
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foreach ($squareSumSamples as $index => $sum) {
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$ssbn[$index] -= $sum / $allSamples;
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}
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return $ssbn;
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}
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private static function calculateSswn(array $ssbn, array $ssAllSamples, array $squareSumSamples, int $allSamples): array
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{
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$sswn = [];
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foreach ($ssAllSamples as $index => $ss) {
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$sswn[$index] = ($ss - $squareSumSamples[$index] / $allSamples) - $ssbn[$index];
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}
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return $sswn;
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}
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}
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