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Differences Between: [Versions 310 and 401] [Versions 311 and 401] [Versions 39 and 401]

   1  <?php
   2  
   3  namespace PhpOffice\PhpSpreadsheet\Shared\Trend;
   4  
   5  class ExponentialBestFit extends BestFit
   6  {
   7      /**
   8       * Algorithm type to use for best-fit
   9       * (Name of this Trend class).
  10       *
  11       * @var string
  12       */
  13      protected $bestFitType = 'exponential';
  14  
  15      /**
  16       * Return the Y-Value for a specified value of X.
  17       *
  18       * @param float $xValue X-Value
  19       *
  20       * @return float Y-Value
  21       */
  22      public function getValueOfYForX($xValue)
  23      {
  24          return $this->getIntersect() * $this->getSlope() ** ($xValue - $this->xOffset);
  25      }
  26  
  27      /**
  28       * Return the X-Value for a specified value of Y.
  29       *
  30       * @param float $yValue Y-Value
  31       *
  32       * @return float X-Value
  33       */
  34      public function getValueOfXForY($yValue)
  35      {
  36          return log(($yValue + $this->yOffset) / $this->getIntersect()) / log($this->getSlope());
  37      }
  38  
  39      /**
  40       * Return the Equation of the best-fit line.
  41       *
  42       * @param int $dp Number of places of decimal precision to display
  43       *
  44       * @return string
  45       */
  46      public function getEquation($dp = 0)
  47      {
  48          $slope = $this->getSlope($dp);
  49          $intersect = $this->getIntersect($dp);
  50  
  51          return 'Y = ' . $intersect . ' * ' . $slope . '^X';
  52      }
  53  
  54      /**
  55       * Return the Slope of the line.
  56       *
  57       * @param int $dp Number of places of decimal precision to display
  58       *
  59       * @return float
  60       */
  61      public function getSlope($dp = 0)
  62      {
  63          if ($dp != 0) {
  64              return round(exp($this->slope), $dp);
  65          }
  66  
  67          return exp($this->slope);
  68      }
  69  
  70      /**
  71       * Return the Value of X where it intersects Y = 0.
  72       *
  73       * @param int $dp Number of places of decimal precision to display
  74       *
  75       * @return float
  76       */
  77      public function getIntersect($dp = 0)
  78      {
  79          if ($dp != 0) {
  80              return round(exp($this->intersect), $dp);
  81          }
  82  
  83          return exp($this->intersect);
  84      }
  85  
  86      /**
  87       * Execute the regression and calculate the goodness of fit for a set of X and Y data values.
  88       *
  89       * @param float[] $yValues The set of Y-values for this regression
  90       * @param float[] $xValues The set of X-values for this regression
  91       */
  92      private function exponentialRegression(array $yValues, array $xValues, bool $const): void
  93      {
  94          $adjustedYValues = array_map(
  95              function ($value) {
  96                  return ($value < 0.0) ? 0 - log(abs($value)) : log($value);
  97              },
  98              $yValues
  99          );
 100  
 101          $this->leastSquareFit($adjustedYValues, $xValues, $const);
 102      }
 103  
 104      /**
 105       * Define the regression and calculate the goodness of fit for a set of X and Y data values.
 106       *
 107       * @param float[] $yValues The set of Y-values for this regression
 108       * @param float[] $xValues The set of X-values for this regression
 109       * @param bool $const
 110       */
 111      public function __construct($yValues, $xValues = [], $const = true)
 112      {
 113          parent::__construct($yValues, $xValues);
 114  
 115          if (!$this->error) {
 116              $this->exponentialRegression($yValues, $xValues, (bool) $const);
 117          }
 118      }
 119  }