View Code - 20260723

LogNormal.php | 20260723_000646.php Initial Domain Snapshot

<?php

namespace PhpOffice\PhpSpreadsheet\Calculation\Statistical\Distributions;

use PhpOffice\PhpSpreadsheet\Calculation\ArrayEnabled;
use PhpOffice\PhpSpreadsheet\Calculation\Exception;
use PhpOffice\PhpSpreadsheet\Calculation\Information\ExcelError;

class LogNormal
{
    use ArrayEnabled;

/**
     * LOGNORMDIST.
     *
     * Returns the cumulative lognormal distribution of x, where ln(x) is normally distributed
     * with parameters mean and standard_dev.
     *
     * @param mixed $value Float value for which we want the probability
     *                      Or can be an array of values
     * @param mixed $mean Mean value as a float
     *                      Or can be an array of values
     * @param mixed $stdDev Standard Deviation as a float
     *                      Or can be an array of values
     *
     * @return array<mixed>|float|string The result, or a string containing an error
     *         If an array of numbers is passed as an argument, then the returned result will also be an array
     *            with the same dimensions
     */
    public static function cumulative(mixed $value, mixed $mean, mixed $stdDev)
    {
        if (is_array($value) || is_array($mean) || is_array($stdDev)) {
            return self::evaluateArrayArguments([self::class, __FUNCTION__], $value, $mean, $stdDev);
        }

try {
            $value = DistributionValidations::validateFloat($value);
            $mean = DistributionValidations::validateFloat($mean);
            $stdDev = DistributionValidations::validateFloat($stdDev);
        } catch (Exception $e) {
            return $e->getMessage();
        }

if (($value <= 0) || ($stdDev <= 0)) {
            return ExcelError::NAN();
        }

return StandardNormal::cumulative((log($value) - $mean) / $stdDev);
    }

/**
     * LOGNORM.DIST.
     *
     * Returns the lognormal distribution of x, where ln(x) is normally distributed
     * with parameters mean and standard_dev.
     *
     * @param mixed $value Float value for which we want the probability
     *                      Or can be an array of values
     * @param mixed $mean Mean value as a float
     *                      Or can be an array of values
     * @param mixed $stdDev Standard Deviation as a float
     *                      Or can be an array of values
     * @param mixed $cumulative Boolean value indicating if we want the cdf (true) or the pdf (false)
     *                      Or can be an array of values
     *
     * @return array<mixed>|float|string The result, or a string containing an error
     *         If an array of numbers is passed as an argument, then the returned result will also be an array
     *            with the same dimensions
     */
    public static function distribution(mixed $value, mixed $mean, mixed $stdDev, mixed $cumulative = false)
    {
        if (is_array($value) || is_array($mean) || is_array($stdDev) || is_array($cumulative)) {
            return self::evaluateArrayArguments([self::class, __FUNCTION__], $value, $mean, $stdDev, $cumulative);
        }

try {
            $value = DistributionValidations::validateFloat($value);
            $mean = DistributionValidations::validateFloat($mean);
            $stdDev = DistributionValidations::validateFloat($stdDev);
            $cumulative = DistributionValidations::validateBool($cumulative);
        } catch (Exception $e) {
            return $e->getMessage();
        }

if (($value <= 0) || ($stdDev <= 0)) {
            return ExcelError::NAN();
        }

if ($cumulative === true) {
            return StandardNormal::distribution((log($value) - $mean) / $stdDev, true);
        }

return (1 / (sqrt(2 * M_PI) * $stdDev * $value))
            * exp(0 - ((log($value) - $mean) ** 2 / (2 * $stdDev ** 2)));
    }

/**
     * LOGINV.
     *
     * Returns the inverse of the lognormal cumulative distribution
     *
     * @param mixed $probability Float probability for which we want the value
     *                      Or can be an array of values
     * @param mixed $mean Mean Value as a float
     *                      Or can be an array of values
     * @param mixed $stdDev Standard Deviation as a float
     *                      Or can be an array of values
     *
     * @return array<mixed>|float|string The result, or a string containing an error
     *         If an array of numbers is passed as an argument, then the returned result will also be an array
     *            with the same dimensions
     *
     * @TODO    Try implementing P J Acklam's refinement algorithm for greater
     *            accuracy if I can get my head round the mathematics
     *            (as described at) http://home.online.no/~pjacklam/notes/invnorm/
     */
    public static function inverse(mixed $probability, mixed $mean, mixed $stdDev): array|string|float
    {
        if (is_array($probability) || is_array($mean) || is_array($stdDev)) {
            return self::evaluateArrayArguments([self::class, __FUNCTION__], $probability, $mean, $stdDev);
        }

try {
            $probability = DistributionValidations::validateProbability($probability);
            $mean = DistributionValidations::validateFloat($mean);
            $stdDev = DistributionValidations::validateFloat($stdDev);
        } catch (Exception $e) {
            return $e->getMessage();
        }

if ($stdDev <= 0) {
            return ExcelError::NAN();
        }
        /** @var float $inverse */
        $inverse = StandardNormal::inverse($probability);

return exp($mean + $stdDev * $inverse);
    }
}