<?php

namespace PhpOffice\PhpSpreadsheet\Shared\Trend;

abstract class BestFit
{
    /**
     * Indicator flag for a calculation error.
     *
     * @var bool
     */
    protected $error = false;

    /**
     * Algorithm type to use for best-fit.
     *
     * @var string
     */
    protected $bestFitType = 'undetermined';

    /**
     * Number of entries in the sets of x- and y-value arrays.
     *
     * @var int
     */
    protected $valueCount = 0;

    /**
     * X-value dataseries of values.
     *
     * @var float[]
     */
    protected $xValues = [];

    /**
     * Y-value dataseries of values.
     *
     * @var float[]
     */
    protected $yValues = [];

    /**
     * Flag indicating whether values should be adjusted to Y=0.
     *
     * @var bool
     */
    protected $adjustToZero = false;

    /**
     * Y-value series of best-fit values.
     *
     * @var float[]
     */
    protected $yBestFitValues = [];

    /** @var float */
    protected $goodnessOfFit = 1;

    /** @var float */
    protected $stdevOfResiduals = 0;

    /** @var float */
    protected $covariance = 0;

    /** @var float */
    protected $correlation = 0;

    /** @var float */
    protected $SSRegression = 0;

    /** @var float */
    protected $SSResiduals = 0;

    /** @var float */
    protected $DFResiduals = 0;

    /** @var float */
    protected $f = 0;

    /** @var float */
    protected $slope = 0;

    /** @var float */
    protected $slopeSE = 0;

    /** @var float */
    protected $intersect = 0;

    /** @var float */
    protected $intersectSE = 0;

    /** @var float */
    protected $xOffset = 0;

    /** @var float */
    protected $yOffset = 0;

    /** @return bool */
    public function getError()
    {
        return $this->error;
    }

    /** @return string */
    public function getBestFitType()
    {
        return $this->bestFitType;
    }

    /**
     * Return the Y-Value for a specified value of X.
     *
     * @param float $xValue X-Value
     *
     * @return float Y-Value
     */
    abstract public function getValueOfYForX($xValue);

    /**
     * Return the X-Value for a specified value of Y.
     *
     * @param float $yValue Y-Value
     *
     * @return float X-Value
     */
    abstract public function getValueOfXForY($yValue);

    /**
     * Return the original set of X-Values.
     *
     * @return float[] X-Values
     */
    public function getXValues()
    {
        return $this->xValues;
    }

    /**
     * Return the Equation of the best-fit line.
     *
     * @param int $dp Number of places of decimal precision to display
     *
     * @return string
     */
    abstract public function getEquation($dp = 0);

    /**
     * Return the Slope of the line.
     *
     * @param int $dp Number of places of decimal precision to display
     *
     * @return float
     */
    public function getSlope($dp = 0)
    {
        if ($dp != 0) {
            return round($this->slope, $dp);
        }

        return $this->slope;
    }

    /**
     * Return the standard error of the Slope.
     *
     * @param int $dp Number of places of decimal precision to display
     *
     * @return float
     */
    public function getSlopeSE($dp = 0)
    {
        if ($dp != 0) {
            return round($this->slopeSE, $dp);
        }

        return $this->slopeSE;
    }

    /**
     * Return the Value of X where it intersects Y = 0.
     *
     * @param int $dp Number of places of decimal precision to display
     *
     * @return float
     */
    public function getIntersect($dp = 0)
    {
        if ($dp != 0) {
            return round($this->intersect, $dp);
        }

        return $this->intersect;
    }

    /**
     * Return the standard error of the Intersect.
     *
     * @param int $dp Number of places of decimal precision to display
     *
     * @return float
     */
    public function getIntersectSE($dp = 0)
    {
        if ($dp != 0) {
            return round($this->intersectSE, $dp);
        }

        return $this->intersectSE;
    }

    /**
     * Return the goodness of fit for this regression.
     *
     * @param int $dp Number of places of decimal precision to return
     *
     * @return float
     */
    public function getGoodnessOfFit($dp = 0)
    {
        if ($dp != 0) {
            return round($this->goodnessOfFit, $dp);
        }

        return $this->goodnessOfFit;
    }

    /**
     * Return the goodness of fit for this regression.
     *
     * @param int $dp Number of places of decimal precision to return
     *
     * @return float
     */
    public function getGoodnessOfFitPercent($dp = 0)
    {
        if ($dp != 0) {
            return round($this->goodnessOfFit * 100, $dp);
        }

        return $this->goodnessOfFit * 100;
    }

    /**
     * Return the standard deviation of the residuals for this regression.
     *
     * @param int $dp Number of places of decimal precision to return
     *
     * @return float
     */
    public function getStdevOfResiduals($dp = 0)
    {
        if ($dp != 0) {
            return round($this->stdevOfResiduals, $dp);
        }

        return $this->stdevOfResiduals;
    }

    /**
     * @param int $dp Number of places of decimal precision to return
     *
     * @return float
     */
    public function getSSRegression($dp = 0)
    {
        if ($dp != 0) {
            return round($this->SSRegression, $dp);
        }

        return $this->SSRegression;
    }

    /**
     * @param int $dp Number of places of decimal precision to return
     *
     * @return float
     */
    public function getSSResiduals($dp = 0)
    {
        if ($dp != 0) {
            return round($this->SSResiduals, $dp);
        }

        return $this->SSResiduals;
    }

    /**
     * @param int $dp Number of places of decimal precision to return
     *
     * @return float
     */
    public function getDFResiduals($dp = 0)
    {
        if ($dp != 0) {
            return round($this->DFResiduals, $dp);
        }

        return $this->DFResiduals;
    }

    /**
     * @param int $dp Number of places of decimal precision to return
     *
     * @return float
     */
    public function getF($dp = 0)
    {
        if ($dp != 0) {
            return round($this->f, $dp);
        }

        return $this->f;
    }

    /**
     * @param int $dp Number of places of decimal precision to return
     *
     * @return float
     */
    public function getCovariance($dp = 0)
    {
        if ($dp != 0) {
            return round($this->covariance, $dp);
        }

        return $this->covariance;
    }

    /**
     * @param int $dp Number of places of decimal precision to return
     *
     * @return float
     */
    public function getCorrelation($dp = 0)
    {
        if ($dp != 0) {
            return round($this->correlation, $dp);
        }

        return $this->correlation;
    }

    /**
     * @return float[]
     */
    public function getYBestFitValues()
    {
        return $this->yBestFitValues;
    }

    /** @var mixed */
    private static $scrutinizerZeroPointZero = 0.0;

    /**
     * @param mixed $x
     * @param mixed $y
     */
    private static function scrutinizerLooseCompare($x, $y): bool
    {
        return $x == $y;
    }

    /**
     * @param float $sumX
     * @param float $sumY
     * @param float $sumX2
     * @param float $sumY2
     * @param float $sumXY
     * @param float $meanX
     * @param float $meanY
     * @param bool|int $const
     */
    protected function calculateGoodnessOfFit($sumX, $sumY, $sumX2, $sumY2, $sumXY, $meanX, $meanY, $const): void
    {
        $SSres = $SScov = $SStot = $SSsex = 0.0;
        foreach ($this->xValues as $xKey => $xValue) {
            $bestFitY = $this->yBestFitValues[$xKey] = $this->getValueOfYForX($xValue);

            $SSres += ($this->yValues[$xKey] - $bestFitY) * ($this->yValues[$xKey] - $bestFitY);
            if ($const === true) {
                $SStot += ($this->yValues[$xKey] - $meanY) * ($this->yValues[$xKey] - $meanY);
            } else {
                $SStot += $this->yValues[$xKey] * $this->yValues[$xKey];
            }
            $SScov += ($this->xValues[$xKey] - $meanX) * ($this->yValues[$xKey] - $meanY);
            if ($const === true) {
                $SSsex += ($this->xValues[$xKey] - $meanX) * ($this->xValues[$xKey] - $meanX);
            } else {
                $SSsex += $this->xValues[$xKey] * $this->xValues[$xKey];
            }
        }

        $this->SSResiduals = $SSres;
        $this->DFResiduals = $this->valueCount - 1 - ($const === true ? 1 : 0);

        if ($this->DFResiduals == 0.0) {
            $this->stdevOfResiduals = 0.0;
        } else {
            $this->stdevOfResiduals = sqrt($SSres / $this->DFResiduals);
        }
        // Scrutinizer thinks $SSres == $SStot is always true. It is wrong.
        if ($SStot == self::$scrutinizerZeroPointZero || self::scrutinizerLooseCompare($SSres, $SStot)) {
            $this->goodnessOfFit = 1;
        } else {
            $this->goodnessOfFit = 1 - ($SSres / $SStot);
        }

        $this->SSRegression = $this->goodnessOfFit * $SStot;
        $this->covariance = $SScov / $this->valueCount;
        $this->correlation = ($this->valueCount * $sumXY - $sumX * $sumY) / sqrt(($this->valueCount * $sumX2 - $sumX ** 2) * ($this->valueCount * $sumY2 - $sumY ** 2));
        $this->slopeSE = $this->stdevOfResiduals / sqrt($SSsex);
        $this->intersectSE = $this->stdevOfResiduals * sqrt(1 / ($this->valueCount - ($sumX * $sumX) / $sumX2));
        if ($this->SSResiduals != 0.0) {
            if ($this->DFResiduals == 0.0) {
                $this->f = 0.0;
            } else {
                $this->f = $this->SSRegression / ($this->SSResiduals / $this->DFResiduals);
            }
        } else {
            if ($this->DFResiduals == 0.0) {
                $this->f = 0.0;
            } else {
                $this->f = $this->SSRegression / $this->DFResiduals;
            }
        }
    }

    /** @return float|int */
    private function sumSquares(array $values)
    {
        return array_sum(
            array_map(
                function ($value) {
                    return $value ** 2;
                },
                $values
            )
        );
    }

    /**
     * @param float[] $yValues
     * @param float[] $xValues
     */
    protected function leastSquareFit(array $yValues, array $xValues, bool $const): void
    {
        // calculate sums
        $sumValuesX = array_sum($xValues);
        $sumValuesY = array_sum($yValues);
        $meanValueX = $sumValuesX / $this->valueCount;
        $meanValueY = $sumValuesY / $this->valueCount;
        $sumSquaresX = $this->sumSquares($xValues);
        $sumSquaresY = $this->sumSquares($yValues);
        $mBase = $mDivisor = 0.0;
        $xy_sum = 0.0;
        for ($i = 0; $i < $this->valueCount; ++$i) {
            $xy_sum += $xValues[$i] * $yValues[$i];

            if ($const === true) {
                $mBase += ($xValues[$i] - $meanValueX) * ($yValues[$i] - $meanValueY);
                $mDivisor += ($xValues[$i] - $meanValueX) * ($xValues[$i] - $meanValueX);
            } else {
                $mBase += $xValues[$i] * $yValues[$i];
                $mDivisor += $xValues[$i] * $xValues[$i];
            }
        }

        // calculate slope
        $this->slope = $mBase / $mDivisor;

        // calculate intersect
        $this->intersect = ($const === true) ? $meanValueY - ($this->slope * $meanValueX) : 0.0;

        $this->calculateGoodnessOfFit($sumValuesX, $sumValuesY, $sumSquaresX, $sumSquaresY, $xy_sum, $meanValueX, $meanValueY, $const);
    }

    /**
     * Define the regression.
     *
     * @param float[] $yValues The set of Y-values for this regression
     * @param float[] $xValues The set of X-values for this regression
     */
    public function __construct($yValues, $xValues = [])
    {
        //    Calculate number of points
        $yValueCount = count($yValues);
        $xValueCount = count($xValues);

        //    Define X Values if necessary
        if ($xValueCount === 0) {
            $xValues = range(1, $yValueCount);
        } elseif ($yValueCount !== $xValueCount) {
            //    Ensure both arrays of points are the same size
            $this->error = true;
        }

        $this->valueCount = $yValueCount;
        $this->xValues = $xValues;
        $this->yValues = $yValues;
    }
}

• [F] BestFit.php
  Delete
• [F] ExponentialBestFit.php
  Delete
• [F] LinearBestFit.php
  Delete
• [F] LogarithmicBestFit.php
  Delete
• [F] PolynomialBestFit.php
  Delete
• [F] PowerBestFit.php
  Delete
• [F] Trend.php
  Delete

About Section

About NFC Pay: Our Story and Mission

NFC Pay was founded with a vision to transform the way people handle transactions. Our journey is defined by a commitment to innovation, security, and convenience. We strive to deliver seamless, user-friendly payment solutions that make everyday transactions effortless and secure. Our mission is to empower you to pay with ease and confidence, anytime, anywhere.

• Simplifying Payments, One Tap at a Time.
• Reinventing Your Wallet for Modern Convenience.
• Smart Payments for a Effortless Lifestyle.
• Experience the Ease of Tap and Pay.
• Innovative Solutions for Your Daily Transactions.

FAQ Section

Frequently Asked Questions About NFC Pay

Here are answers to some common questions about NFC Pay. We aim to provide clear and concise information to help you understand how our platform works and how it can benefit you. If you have any further inquiries, please don’t hesitate to contact our support team.

How do I register for NFC Pay?

Download the app and sign up using your email or phone number, then complete the verification process.

Is my payment information secure?

Yes, we use advanced encryption and security protocols to protect your payment details.

Can I add multiple cards to my NFC Pay wallet?

Absolutely, you can link multiple debit or credit cards to your wallet.

How do I transfer money to another user?

Go to the transfer section, select the recipient, enter the amount, and authorize the transfer.

What should I do if I forget my PIN?

Use the “Forgot PIN” feature in the app to reset it following the provided instructions.

How can I activate my merchant account?

Sign up for a merchant account through the app and follow the setup instructions to start accepting payments.

Can I track my payment status?

Yes, you can view and track your payment status in the account dashboard