本文整理汇总了PHP中PHPExcel_Best_Fit::__construct方法的典型用法代码示例。如果您正苦于以下问题：PHP PHPExcel_Best_Fit::__construct方法的具体用法？PHP PHPExcel_Best_Fit::__construct怎么用？PHP PHPExcel_Best_Fit::__construct使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类PHPExcel_Best_Fit的用法示例。
在下文中一共展示了PHPExcel_Best_Fit::__construct方法的7个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的PHP代码示例。
示例1: array
/**
* Define the regression and calculate the goodness of fit for a set of X and Y data values
*
* @param int $order Order of Polynomial for this regression
* @param float[] $yValues The set of Y-values for this regression
* @param float[] $xValues The set of X-values for this regression
* @param boolean $const
*/
function __construct($order, $yValues, $xValues = array(), $const = true)
{
if (parent::__construct($yValues, $xValues) !== false) {
if ($order < $this->_valueCount) {
$this->_bestFitType .= '_' . $order;
$this->_order = $order;
$this->_polynomial_regression($order, $yValues, $xValues, $const);
if ($this->getGoodnessOfFit() < 0.0 || $this->getGoodnessOfFit() > 1.0) {
$this->_error = true;
}
} else {
$this->_error = true;
}
}
}示例2: array
function __construct($yValues, $xValues = array(), $const = True)
{
if (parent::__construct($yValues, $xValues) !== False) {
$this->_logarithmic_regression($yValues, $xValues, $const);
}
}示例3: array
function __construct($yValues, $xValues = array(), $const = True)
{
if (parent::__construct($yValues, $xValues) !== False) {
$this->_exponential_regression($yValues, $xValues, $const);
}
}示例4: __construct
/**
* 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 $const
*/
public function __construct($yValues, $xValues = array(), $const = true)
{
if (parent::__construct($yValues, $xValues) !== false) {
$this->exponentialRegression($yValues, $xValues, $const);
}
}示例5: array
function __construct($yValues, $xValues = array(), $const = True) {
if (parent::__construct ( $yValues, $xValues ) !== False) {
$this->_power_regression ( $yValues, $xValues, $const );
}
} // function __construct()示例6: array
/**
* 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) {
$this->_linear_regression($yValues, $xValues, $const);
}
}示例7: __construct
/**
* 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 $const
*/
public function __construct($yValues, $xValues = array(), $const = true)
{
if (parent::__construct($yValues, $xValues) !== false) {
$this->logarithmicRegression($yValues, $xValues, $const);
}
}