<?php

namespace PhpOffice\PhpSpreadsheet\Shared\Trend;

/**
 * Copyright (c) 2006 - 2016 PhpSpreadsheet.
 *
 * This library is free software; you can redistribute it and/or
 * modify it under the terms of the GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this library; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
 *
 * @category   PhpSpreadsheet
 *
 * @copyright  Copyright (c) 2006 - 2016 PhpSpreadsheet (https://github.com/PHPOffice/PhpSpreadsheet)
 * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt    LGPL
 */
class LogarithmicBestFit extends BestFit
{
    /**
     * 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);
    }

    /**
     * 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());
    }

    /**
     * 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)';
    }

    /**
     * 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 bool $const
     */
    private function logarithmicRegression($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);
    }

    /**
     * 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 bool $const
     */
    public function __construct($yValues, $xValues = [], $const = true)
    {
        if (parent::__construct($yValues, $xValues) !== false) {
            $this->logarithmicRegression($yValues, $xValues, $const);
        }
    }
}