Exact port Simple Script's ckmeans algorithm (https://github.com/simple-statistics/simple-statistics) to PHP. Useful for creating choropleth breaks and such.

kmeans.php

<?php

function makeMatrix($columns, $rows) {
  $matrix = array();
  for ($i = 0; $i < $columns; $i ++) {
    $column = array();
    for ($j = 0; $j < $rows; $j ++) {
      $column[] = 0;
    }
    $matrix[] = $column;
  } 
  return $matrix;
}

function uniqueCountSorted($input) {
  $uniqueValueCount = 0;
  $lastSeenValue = FALSE;
  for ($i = 0; $i < count($input); $i++) {
    if ($i === 0 || $input[$i] !== $lastSeenValue) {
      $lastSeenValue = $input[$i];
      $uniqueValueCount ++;
    }
  }
  return $uniqueValueCount;
}

function ckmeans($data, $nClusters) {
  if ($nClusters > count($data)) {
    throw Exception('Cannot generate more classes than there are data values');
  }
  sort($data);
  $sorted = $data;
  $uniqueCount = uniqueCountSorted($sorted);  
  
  $matrix = makeMatrix($nClusters, count($data));
  $backtrackMatrix = makeMatrix($nClusters, count($data));

  for ($cluster = 0; $cluster < $nClusters; $cluster ++) {
    $firstClusterMean = $sorted[0];
    for ($sortedIdx = max($cluster, 1); $sortedIdx < count($sorted); $sortedIdx ++) {
      if ($cluster === 0) {
        $squaredDifference = pow($sorted[$sortedIdx] - $firstClusterMean, 2);
        $matrix[$cluster][$sortedIdx] = $matrix[$cluster][$sortedIdx - 1] + ($sortedIdx / ($sortedIdx + 1)) * $squaredDifference;
        $newSum = $sortedIdx * $firstClusterMean + $sorted[$sortedIdx];
        $firstClusterMean = $newSum / ($sortedIdx + 1);
      }
      else {
        $sumSquaredDistances = 0;
        $meanXJ = 0;
        
        for ($j = $sortedIdx; $j >= $cluster; $j --) {
          $sumSquaredDistances += ($sortedIdx - $j) / ($sortedIdx - $j + 1) * pow($sorted[$j] - $meanXJ, 2);
          
          $meanXJ = ($sorted[$j] + ($sortedIdx - $j) * $meanXJ) / ($sortedIdx - $j + 1);

          if ($j === $sortedIdx) {
            $matrix[$cluster][$sortedIdx] = $sumSquaredDistances;
            $backtrackMatrix[$cluster][$sortedIdx] = $j;
            if ($j > 0) {
              $matrix[$cluster][$sortedIdx] += $matrix[$cluster - 1][$j - 1];
            }
          }
          else {
            if ($j === 0) {
              if ($sumSquaredDistances <= $matrix[$cluster][$sortedIdx]) {
                $matrix[$cluster][$sortedIdx] = $sumSquaredDistances;
                $backtrackMatrix[$cluster][$sortedIdx] = $j;
              }
            }
            else if ($sumSquaredDistances + $matrix[$cluster - 1][$j - 1] < $matrix[$cluster][$sortedIdx]) {
              $matrix[$cluster][$sortedIdx] = $sumSquaredDistances + $matrix[$cluster - 1][$j - 1];
              $backtrackMatrix[$cluster][$sortedIdx] = $j;
            }
          }
        }
      }
    }
  }
  
  $clusters = array();
  $clusterRight = count($backtrackMatrix[0]) - 1;
  
  for ($cluster = count($backtrackMatrix) - 1; $cluster >= 0; $cluster --) {
    $clusterLeft = $backtrackMatrix[$cluster][$clusterRight];

    $clusters[$cluster] = array_slice($sorted, $clusterLeft, ($clusterRight + 1) - $clusterLeft);
    if ($cluster > 0) {
      $clusterRight = $clusterLeft - 1;
    } 
  }

  return $clusters;
}

?>