class PHPExcel_Logarithmic_Best_Fit in Loft Data Grids 7.2

PHPExcel_Logarithmic_Best_Fit

@category PHPExcel @package PHPExcel_Shared_Trend @copyright Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)

Hierarchy

• class \PHPExcel_Best_Fit
  • class \PHPExcel_Logarithmic_Best_Fit

File

vendor/phpoffice/phpexcel/Classes/PHPExcel/Shared/trend/logarithmicBestFitClass.php, line 39

class PHPExcel_Logarithmic_Best_Fit extends PHPExcel_Best_Fit {

  /**
   * Algorithm type to use for best-fit
   * (Name of this trend class)
   *
   * @var	string
   **/
  protected $_bestFitType = 'logarithmic';

  /**
   * Return the Y-Value for a specified value of X
   *
   * @param	 float		$xValue			X-Value
   * @return	 float						Y-Value
   **/
  public function getValueOfYForX($xValue) {
    return $this
      ->getIntersect() + $this
      ->getSlope() * log($xValue - $this->_Xoffset);
  }

  //	function getValueOfYForX()

  /**
   * Return the X-Value for a specified value of Y
   *
   * @param	 float		$yValue			Y-Value
   * @return	 float						X-Value
   **/
  public function getValueOfXForY($yValue) {
    return exp(($yValue - $this
      ->getIntersect()) / $this
      ->getSlope());
  }

  //	function getValueOfXForY()

  /**
   * Return the Equation of the best-fit line
   *
   * @param	 int		$dp		Number of places of decimal precision to display
   * @return	 string
   **/
  public function getEquation($dp = 0) {
    $slope = $this
      ->getSlope($dp);
    $intersect = $this
      ->getIntersect($dp);
    return 'Y = ' . $intersect . ' + ' . $slope . ' * log(X)';
  }

  //	function getEquation()

  /**
   * Execute the regression and calculate the goodness of fit for a set of X and Y data values
   *
   * @param	 float[]	$yValues	The set of Y-values for this regression
   * @param	 float[]	$xValues	The set of X-values for this regression
   * @param	 boolean	$const
   */
  private function _logarithmic_regression($yValues, $xValues, $const) {
    foreach ($xValues as &$value) {
      if ($value < 0.0) {
        $value = 0 - log(abs($value));
      }
      elseif ($value > 0.0) {
        $value = log($value);
      }
    }
    unset($value);
    $this
      ->_leastSquareFit($yValues, $xValues, $const);
  }

  //	function _logarithmic_regression()

  /**
   * Define the regression and calculate the goodness of fit for a set of X and Y data values
   *
   * @param	float[]		$yValues	The set of Y-values for this regression
   * @param	float[]		$xValues	The set of X-values for this regression
   * @param	boolean		$const
   */
  function __construct($yValues, $xValues = array(), $const = True) {
    if (parent::__construct($yValues, $xValues) !== False) {
      $this
        ->_logarithmic_regression($yValues, $xValues, $const);
    }
  }

}

Members

Name	Modifiers	Type	Description	Overrides
PHPExcel_Best_Fit::$_adjustToZero	protected	property	* Flag indicating whether values should be adjusted to Y=0 * * *
PHPExcel_Best_Fit::$_correlation	protected	property
PHPExcel_Best_Fit::$_covariance	protected	property
PHPExcel_Best_Fit::$_DFResiduals	protected	property
PHPExcel_Best_Fit::$_error	protected	property	* Indicator flag for a calculation error * * *
PHPExcel_Best_Fit::$_F	protected	property
PHPExcel_Best_Fit::$_goodnessOfFit	protected	property
PHPExcel_Best_Fit::$_intersect	protected	property
PHPExcel_Best_Fit::$_intersectSE	protected	property
PHPExcel_Best_Fit::$_slope	protected	property
PHPExcel_Best_Fit::$_slopeSE	protected	property
PHPExcel_Best_Fit::$_SSRegression	protected	property
PHPExcel_Best_Fit::$_SSResiduals	protected	property
PHPExcel_Best_Fit::$_stdevOfResiduals	protected	property
PHPExcel_Best_Fit::$_valueCount	protected	property	* Number of entries in the sets of x- and y-value arrays * * *
PHPExcel_Best_Fit::$_Xoffset	protected	property
PHPExcel_Best_Fit::$_xValues	protected	property	* X-value dataseries of values * * *
PHPExcel_Best_Fit::$_yBestFitValues	protected	property	* Y-value series of best-fit values * * *
PHPExcel_Best_Fit::$_Yoffset	protected	property
PHPExcel_Best_Fit::$_yValues	protected	property	* Y-value dataseries of values * * *
PHPExcel_Best_Fit::getBestFitType	public	function
PHPExcel_Best_Fit::getCorrelation	public	function
PHPExcel_Best_Fit::getCovariance	public	function
PHPExcel_Best_Fit::getDFResiduals	public	function
PHPExcel_Best_Fit::getError	public	function
PHPExcel_Best_Fit::getF	public	function
PHPExcel_Best_Fit::getGoodnessOfFit	public	function	* Return the goodness of fit for this regression * *
PHPExcel_Best_Fit::getGoodnessOfFitPercent	public	function
PHPExcel_Best_Fit::getIntersect	public	function	* Return the Value of X where it intersects Y = 0 * *	2
PHPExcel_Best_Fit::getIntersectSE	public	function	* Return the standard error of the Intersect * *
PHPExcel_Best_Fit::getSlope	public	function	* Return the Slope of the line * *	2
PHPExcel_Best_Fit::getSlopeSE	public	function	* Return the standard error of the Slope * *
PHPExcel_Best_Fit::getSSRegression	public	function
PHPExcel_Best_Fit::getSSResiduals	public	function
PHPExcel_Best_Fit::getStdevOfResiduals	public	function	* Return the standard deviation of the residuals for this regression * *
PHPExcel_Best_Fit::getXValues	public	function	* Return the original set of X-Values * *
PHPExcel_Best_Fit::getYBestFitValues	public	function
PHPExcel_Best_Fit::_calculateGoodnessOfFit	protected	function
PHPExcel_Best_Fit::_leastSquareFit	protected	function
PHPExcel_Logarithmic_Best_Fit::$_bestFitType	protected	property	* Algorithm type to use for best-fit * (Name of this trend class) * * * Overrides PHPExcel_Best_Fit::$_bestFitType
PHPExcel_Logarithmic_Best_Fit::getEquation	public	function	* Return the Equation of the best-fit line * * Overrides PHPExcel_Best_Fit::getEquation
PHPExcel_Logarithmic_Best_Fit::getValueOfXForY	public	function	* Return the X-Value for a specified value of Y * * Overrides PHPExcel_Best_Fit::getValueOfXForY
PHPExcel_Logarithmic_Best_Fit::getValueOfYForX	public	function	* Return the Y-Value for a specified value of X * * Overrides PHPExcel_Best_Fit::getValueOfYForX
PHPExcel_Logarithmic_Best_Fit::_logarithmic_regression	private	function	* Execute the regression and calculate the goodness of fit for a set of X and Y data values * *
PHPExcel_Logarithmic_Best_Fit::__construct		function	* Define the regression and calculate the goodness of fit for a set of X and Y data values * * Overrides PHPExcel_Best_Fit::__construct