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<?php |
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declare(strict_types=1); |
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namespace Np; |
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use Np\core\{ |
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nd, |
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blas, |
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lapack |
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}; |
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use Np\exceptions\{ |
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invalidArgumentException, |
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dimensionalityMismatch, |
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dtypeException, |
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}; |
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/** A fast lite memory efficient Scientific Computing in php |
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* Vector (rank-1) |
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* |
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* @package NumPhp |
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* @version V0.0.alpha |
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* @category Php Scientific Library |
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* @author ghost (Shubham Chaudhary) |
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* @email [email protected] |
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* @copyright (c) 2020-2021, Shubham Chaudhary |
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* |
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*/ |
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class vector extends nd { |
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/** |
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* Factory method to build a new vector. |
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* |
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* @param int $col |
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* @param int $dtype |
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* @return vector |
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*/ |
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public static function factory(int $col, int $dtype = self::FLOAT): vector { |
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return new self($col, $dtype); |
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} |
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/** |
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* Build a new vector from a php array. |
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* |
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* @param array $data |
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* @param int $dtype |
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* @return vector |
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*/ |
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public static function ar(array $data, int $dtype = self::FLOAT): vector { |
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if (is_array($data) && !is_array($data[0])) { |
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$ar = self::factory(count($data), $dtype); |
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$ar->setData($data); |
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return $ar; |
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} else { |
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self::_err('data must be of same dimensions'); |
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} |
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} |
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/** |
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* Return vector with random values |
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* @param int $col |
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* @param int $dtype |
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* @return vector |
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*/ |
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public static function randn(int $col, int $dtype = self::FLOAT): vector { |
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$ar = self::factory($col, $dtype); |
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$max = getrandmax(); |
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for ($i = 0; $i < $ar->col; ++$i) { |
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$ar->data[$i] = rand() / $max; |
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} |
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return $ar; |
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} |
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/** |
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* Return vector with uniform values |
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* @param int $col |
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* @param int $dtype |
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* @return vector |
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*/ |
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public static function uniform(int $col, int $dtype = self::FLOAT): vector { |
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$ar = self::factory($col, $dtype); |
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$max = getrandmax(); |
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for ($i = 0; $i < $col; ++$i) { |
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$ar->data[$i] = rand(-$max, $max) / $max; |
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} |
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return $ar; |
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} |
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/** |
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* Build a vector of zeros with n elements. |
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* |
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* @param int $col |
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* @param int $dtype |
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* @return vector |
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*/ |
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public static function zeros(int $col, int $dtype = self::FLOAT): vector { |
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$ar = self::factory($col, $dtype); |
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for ($i = 0; $i < $col; ++$i) { |
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$ar->data[$i] = 0; |
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} |
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return $ar; |
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} |
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/** |
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* create one like vector |
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* |
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* @param int $col |
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* @return vector |
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*/ |
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public static function ones(int $col, int $dtype = self::FLOAT): vector { |
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$ar = self::factory($col, $dtype); |
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for ($i = 0; $i < $col; ++$i) { |
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$ar->data[$i] = 1; |
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} |
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return $ar; |
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} |
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/** |
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* create a null like vector |
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* @param int $col |
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* @return vector |
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*/ |
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public static function null(int $col, int $dtype = self::FLOAT): vector { |
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$ar = self::factory($col, $dtype); |
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for ($i = 0; $i < $col; ++$i) { |
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$ar->data[$i] = null; |
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} |
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return $ar; |
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} |
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/** |
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* create a vector with given scalar value |
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* @param int $col |
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* @param int|float|double $val |
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* @param int $dtype |
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* @return vector |
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*/ |
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public static function full(int $col, int|float $val, int $dtype = self::FLOAT): vector { |
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$ar = self::factory($col, $dtype); |
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for ($i = 0; $i < $col; ++$i) { |
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$ar->data[$i] = $val; |
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} |
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return $ar; |
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} |
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/** |
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* Return evenly spaced values within a given interval. |
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* |
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* @param int|float $start |
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* @param int|float $end |
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* @param int|float $interval |
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* @param int $dtype |
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* @return vector |
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*/ |
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public static function range(int|float $start, int|float $end, int|float $interval = 1, int $dtype = self::FLOAT): vector { |
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return self::ar(range($start, $end, $interval)); |
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} |
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/** |
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* Return a Gaussian random vector with mean 0 |
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* and unit variance. |
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* |
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* @param int $n |
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* @param int $dtype |
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* @return self |
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*/ |
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public static function gaussian(int $n, int $dtype = self::FLOAT): vector { |
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$max = getrandmax(); |
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$a = new self($n, $dtype); |
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while (count($a) < $n) { |
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$r = sqrt(-2.0 * log(rand() / $max)); |
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$phi = rand() / $max * (2. * M_PI); |
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$a[] = $r * sin($phi); |
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$a[] = $r * cos($phi); |
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} |
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if (count($a) > $n) { |
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$a = array_slice($a, 0, $n); |
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} |
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return self::ar($a, $dtype); |
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} |
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/** |
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* Generate a vector with n elements from a Poisson distribution. |
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* |
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* @param int $n |
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* @param float $lambda |
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* @param int $dtype |
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* @return vector |
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*/ |
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public static function poisson(int $n, float $lambda = 1.0, int $dtype = self::FLOAT): vector { |
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$max = getrandmax(); |
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$l = exp(-$lambda); |
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$a = new self($n, $dtype); |
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for ($i = 0; $i < $n; ++$i) { |
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$k = 0; |
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$p = 1.0; |
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while ($p > $l) { |
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++$k; |
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$p *= rand() / $max; |
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} |
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$a->data[$i] = $k - 1; |
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} |
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return $a; |
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} |
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/** |
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* Return a vector of n evenly spaced numbers between minimum and maximum. |
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* |
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* @param float $min |
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* @param float $max |
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* @param int $n |
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* @param int $dtype |
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* @throws invalidArgumentException |
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* @return vector |
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*/ |
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public static function linspace(float $min, float $max, int $n, int $dtype = self::FLOAT): vector { |
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if ($min > $max) { |
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throw new invalidArgumentException('Minimum must be less than maximum.'); |
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} |
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if ($n < 2) { |
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throw new invalidArgumentException('Number of elements must be greater than 1.'); |
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} |
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$k = $n - 1; |
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$interval = abs($max - $min) / $k; |
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$a = [$min]; |
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while (count($a) < $k) { |
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$a[] = end($a) + $interval; |
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} |
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$a[] = $max; |
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return self::ar($a); |
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} |
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/** |
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* make a copy of vector |
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* @return vector |
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*/ |
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public function copyVector(): vector { |
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return clone $this; |
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} |
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/** |
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* Return the element-wise maximum of given vector with current vector |
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* |
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* @param \Np\vector $vector |
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* @return vector |
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*/ |
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public function maximum(\Np\vector $vector): vector { |
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if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
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$v = new self($this->ndim, $this->dtype); |
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for($i = 0; $i<$v->ndim; ++$i) { |
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$v->data[$i] = max($this->data[$i],$vector->data[$i]); |
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} |
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return $v; |
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} |
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} |
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/** |
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* Return the element-wise minium of given vector with current vector |
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* |
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* @param \Np\vector $vector |
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* @return vector |
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*/ |
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public function minium(\Np\vector $vector): vector { |
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if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
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$v = new self($this->ndim, $this->dtype); |
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for($i = 0; $i<$v->ndim; ++$i) { |
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$v->data[$i] = min($this->data[$i],$vector->data[$i]); |
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} |
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return $v; |
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} |
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} |
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/** |
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* Return the index of the minimum element in the vector. |
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* |
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* @return int |
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*/ |
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public function argMin():int { |
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return blas::min($this); |
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} |
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/** |
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* Return the index of the maximum element in the vector. |
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* |
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* @return int |
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*/ |
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public function argMx():int { |
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return blas::max($this); |
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} |
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/** |
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* vector-vector dot product |
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* @param \Np\vector $vector |
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* @param int $incX |
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* @param int $incY |
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* @return vector |
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*/ |
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public function dotVector(\Np\vector $v) { |
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if ($this->checkDtype($v)) { |
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return blas::dot($this, $v); |
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} |
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} |
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/** |
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* |
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* @return float |
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*/ |
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public function sum(): float { |
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return blas::asum($this); |
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} |
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/** |
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* Return the product of the vector. |
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* @return int|float |
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*/ |
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public function product(): float { |
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$r = 1.0; |
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for ($i = 0; $i < $this->col; ++$i) { |
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$r *= $this->data[$i]; |
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} |
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return $r; |
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} |
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/** |
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* Compute the vector-matrix dot product of this vector and matrix . |
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* @param \Np\matrix $m |
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* @return vector |
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*/ |
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public function dotMatrix(\Np\matrix $m): vector { |
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if ($this->dtype != $m->dtype) { |
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self::_err('Mismatch Dtype of given matrix'); |
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} |
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$mvr = self::factory($this->col, $this->dtype); |
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core\blas::gemv($m, $this, $mvr); |
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return $mvr; |
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} |
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/** |
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* |
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* @param int|float|matrix|vector $d |
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* @return matrix|vector |
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*/ |
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public function divide(int|float|matrix|vector $d): matrix|vector { |
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if ($d instanceof matrix) { |
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return $this->divideMatrix($d); |
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} elseif ($d instanceof self) { |
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return $this->divideVector($d); |
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} else { |
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return $this->divideScalar($d); |
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} |
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} |
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/** |
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* |
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* @param \Np\matrix $m |
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* @return matrix |
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*/ |
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protected function divideMatrix(\Np\matrix $m): matrix { |
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if ($this->col == $m->col && $this->dtype == $m->dtype) { |
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$vr = matrix::factory($m->row, $m->col, $m->dtype); |
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for ($i = 0; $i < $m->row; ++$i) { |
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for ($j = 0; $j < $m->col; ++$j) { |
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$vr->data[$i * $m->col + $j] = $this->data[$j] / $m->data[$i * $m->col + $j]; |
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} |
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} |
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return $vr; |
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} |
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} |
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/** |
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* |
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* @param vector $v |
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* @return vector |
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*/ |
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protected function divideVector(vector $v): vector { |
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|
|
if ($this->checkDimensions($v) && $this->checkDtype($v)) { |
377
|
|
|
$vr = self::factory($this->col, $this->dtype); |
378
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
379
|
|
|
$vr->data[$i] = $this->data[$i] / $v->data[$i]; |
380
|
|
|
} |
381
|
|
|
return $vr; |
382
|
|
|
} |
|
|
|
|
383
|
|
|
} |
384
|
|
|
|
385
|
|
|
/** |
386
|
|
|
* |
387
|
|
|
* @param int|float $s |
388
|
|
|
* @return vector |
389
|
|
|
*/ |
390
|
|
|
protected function divideScalar(int|float $s): vector { |
391
|
|
|
$vr = self::factory($this->col, $this->dtype); |
392
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
393
|
|
|
$vr->data[$i] = $this->data[$i] / $s; |
394
|
|
|
} |
395
|
|
|
return $vr; |
396
|
|
|
} |
397
|
|
|
|
398
|
|
|
/** |
399
|
|
|
* |
400
|
|
|
* @param int|float|matrix|vector $d |
401
|
|
|
* @return matrix|vector |
402
|
|
|
*/ |
403
|
|
|
public function multiply(int|float|matrix|vector $d): matrix|vector { |
404
|
|
|
if ($d instanceof matrix) { |
405
|
|
|
return $this->multiplyMatrix($d); |
406
|
|
|
} elseif ($d instanceof self) { |
407
|
|
|
return $this->multiplyVector($d); |
408
|
|
|
} else { |
409
|
|
|
return $this->multiplyScalar($d); |
410
|
|
|
} |
411
|
|
|
} |
412
|
|
|
|
413
|
|
|
/** |
414
|
|
|
* |
415
|
|
|
* @param \Np\matrix $m |
416
|
|
|
* @return matrix |
417
|
|
|
*/ |
418
|
|
|
protected function multiplyMatrix(\Np\matrix $m): matrix { |
419
|
|
|
if ($this->col == $m->col && $this->dtype == $m->dtype) { |
420
|
|
|
$vr = matrix::factory($m->row, $m->col, $m->dtype); |
421
|
|
|
for ($i = 0; $i < $m->row; ++$i) { |
422
|
|
|
for ($j = 0; $j < $m->col; ++$j) { |
423
|
|
|
$vr->data[$i * $m->col + $j] = $this->data[$j] * $m->data[$i * $m->col + $j]; |
424
|
|
|
} |
425
|
|
|
} |
426
|
|
|
return $vr; |
427
|
|
|
} |
|
|
|
|
428
|
|
|
} |
429
|
|
|
|
430
|
|
|
/** |
431
|
|
|
* |
432
|
|
|
* @param \Np\vector $vector |
433
|
|
|
* @return vector |
434
|
|
|
*/ |
435
|
|
|
protected function multiplyVector(\Np\vector $vector): vector { |
436
|
|
|
if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
437
|
|
|
$vr = self::factory($this->col, $this->dtype); |
438
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
439
|
|
|
$vr->data[$i] = $this->data[$i] * $vector->data[$i]; |
440
|
|
|
} |
441
|
|
|
return $vr; |
442
|
|
|
} |
|
|
|
|
443
|
|
|
} |
444
|
|
|
|
445
|
|
|
/** |
446
|
|
|
* |
447
|
|
|
* @param int|float $s |
448
|
|
|
* @return vector |
449
|
|
|
*/ |
450
|
|
|
protected function multiplyScalar(int|float $s): vector { |
451
|
|
|
$vr = $this->copyVector(); |
452
|
|
|
blas::scale($s, $vr); |
453
|
|
|
return $vr; |
454
|
|
|
} |
455
|
|
|
|
456
|
|
|
/** |
457
|
|
|
* |
458
|
|
|
* @param int|float|matrix|vector $d |
459
|
|
|
* @return matrix|vector |
460
|
|
|
*/ |
461
|
|
|
public function add(int|float|matrix|vector $d): matrix|vector { |
462
|
|
|
if ($d instanceof matrix) { |
463
|
|
|
return $this->addMatrix($d); |
464
|
|
|
} elseif ($d instanceof self) { |
465
|
|
|
return $this->addVector($d); |
466
|
|
|
} else { |
467
|
|
|
return $this->addScalar($d); |
468
|
|
|
} |
469
|
|
|
} |
470
|
|
|
|
471
|
|
|
/** |
472
|
|
|
* |
473
|
|
|
* @param \Np\matrix $m |
474
|
|
|
* @return matrix |
475
|
|
|
*/ |
476
|
|
|
protected function addMatrix(\Np\matrix $m): matrix { |
477
|
|
|
if ($this->col == $m->col && $this->dtype == $m->dtype) { |
478
|
|
|
$vr = matrix::factory($m->row, $m->col, $m->dtype); |
479
|
|
|
for ($i = 0; $i < $m->row; ++$i) { |
480
|
|
|
for ($j = 0; $j < $m->col; ++$j) { |
481
|
|
|
$vr->data[$i * $m->col + $j] = $this->data[$j] + $m->data[$i * $m->col + $j]; |
482
|
|
|
} |
483
|
|
|
} |
484
|
|
|
return $vr; |
485
|
|
|
} |
486
|
|
|
self::_invalidArgument(''); |
|
|
|
|
487
|
|
|
} |
488
|
|
|
|
489
|
|
|
/** |
490
|
|
|
* |
491
|
|
|
* @param \Np\vector $vector |
492
|
|
|
* @return vector |
493
|
|
|
*/ |
494
|
|
|
protected function addVector(\Np\vector $vector): vector { |
495
|
|
|
if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
496
|
|
|
$vr = self::factory($this->col, $this->dtype); |
497
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
498
|
|
|
$vr->data[$i] = $this->data[$i] + $vector->data[$i]; |
499
|
|
|
} |
500
|
|
|
return $vr; |
501
|
|
|
} |
|
|
|
|
502
|
|
|
} |
503
|
|
|
|
504
|
|
|
/** |
505
|
|
|
* |
506
|
|
|
* @param int|float $s |
507
|
|
|
* @return vector |
508
|
|
|
*/ |
509
|
|
|
protected function addScalar(int|float $s): vector { |
510
|
|
|
$vr = $this->copyVector(); |
511
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
512
|
|
|
$vr->data[$i] += $s; |
513
|
|
|
} |
514
|
|
|
return $vr; |
515
|
|
|
} |
516
|
|
|
|
517
|
|
|
/** |
518
|
|
|
* |
519
|
|
|
* @param \Np\vector $vector |
520
|
|
|
* @return vector |
521
|
|
|
*/ |
522
|
|
|
public function powVector(\Np\vector $vector): vector { |
523
|
|
|
if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
524
|
|
|
$vr = self::factory($this->col, $this->dtype); |
525
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
526
|
|
|
$vr->data[$i] = $this->data[$i] ** $vector->data[$i]; |
527
|
|
|
} |
528
|
|
|
return $vr; |
529
|
|
|
} |
|
|
|
|
530
|
|
|
} |
531
|
|
|
|
532
|
|
|
/** |
533
|
|
|
* |
534
|
|
|
* @param \Np\vector $vector |
535
|
|
|
* @return vector |
536
|
|
|
*/ |
537
|
|
|
public function modVector(\Np\vector $vector): vector { |
538
|
|
|
if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
539
|
|
|
$vr = self::factory($this->col, $this->dtype); |
540
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
541
|
|
|
$vr->data[$i] = $this->data[$i] % $vector->data[$i]; |
542
|
|
|
} |
543
|
|
|
return $vr; |
544
|
|
|
} |
|
|
|
|
545
|
|
|
} |
546
|
|
|
|
547
|
|
|
/** |
548
|
|
|
* |
549
|
|
|
* @param int|float|matrix|vector $d |
550
|
|
|
* @return matrix|vector |
551
|
|
|
*/ |
552
|
|
|
public function subtract(int|float|matrix|vector $d): matrix|vector { |
553
|
|
|
if ($d instanceof matrix) { |
554
|
|
|
return $this->subtractMatrix($d); |
555
|
|
|
} elseif ($d instanceof self) { |
556
|
|
|
return $this->subtractVector($d); |
557
|
|
|
} else { |
558
|
|
|
return $this->substractScalar($d); |
559
|
|
|
} |
560
|
|
|
} |
561
|
|
|
|
562
|
|
|
/** |
563
|
|
|
* |
564
|
|
|
* @param \Np\matrix $m |
565
|
|
|
* @return matrix |
566
|
|
|
*/ |
567
|
|
|
protected function subtractMatrix(\Np\matrix $m): matrix { |
568
|
|
|
if ($this->col == $m->col && $this->dtype == $m->dtype) { |
569
|
|
|
$vr = matrix::factory($m->row, $m->col, $m->dtype); |
570
|
|
|
for ($i = 0; $i < $m->row; ++$i) { |
571
|
|
|
for ($j = 0; $j < $m->col; ++$j) { |
572
|
|
|
$vr->data[$i * $m->col + $j] = $this->data[$j] - $m->data[$i * $m->col + $j]; |
573
|
|
|
} |
574
|
|
|
} |
575
|
|
|
return $vr; |
576
|
|
|
} |
577
|
|
|
self::_invalidArgument(''); |
|
|
|
|
578
|
|
|
} |
579
|
|
|
|
580
|
|
|
/** |
581
|
|
|
* |
582
|
|
|
* @param \Np\vector $vector |
583
|
|
|
* @return vector |
584
|
|
|
*/ |
585
|
|
|
protected function subtractVector(\Np\vector $vector): vector { |
586
|
|
|
if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
587
|
|
|
$vr = self::factory($this->col, $this->dtype); |
588
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
589
|
|
|
$vr->data[$i] = $this->data[$i] - $vector->data[$i]; |
590
|
|
|
} |
591
|
|
|
return $vr; |
592
|
|
|
} |
|
|
|
|
593
|
|
|
} |
594
|
|
|
|
595
|
|
|
/** |
596
|
|
|
* |
597
|
|
|
* @param \Np\vector $scalar |
598
|
|
|
* @return \Np\vector |
599
|
|
|
*/ |
600
|
|
|
protected function substractScalar(int|float $scalar): vector { |
601
|
|
|
$vr = self::factory($this->col, $this->dtype); |
602
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
603
|
|
|
$vr->data[$i] = $this->data[$i] - $scalar; |
604
|
|
|
} |
605
|
|
|
return $vr; |
606
|
|
|
} |
607
|
|
|
|
608
|
|
|
/** |
609
|
|
|
* |
610
|
|
|
* @param \Np\vector $v |
611
|
|
|
* @param int $stride |
612
|
|
|
* @return vector |
613
|
|
|
*/ |
614
|
|
|
public function convolve(\Np\vector $v, int $stride = 1): vector { |
615
|
|
|
return convolve::conv1D($this, $v, $stride); |
616
|
|
|
} |
617
|
|
|
|
618
|
|
|
/** |
619
|
|
|
* Return the inner product of two vectors. |
620
|
|
|
* |
621
|
|
|
* @param \Np\vector $vector |
622
|
|
|
* @return float |
623
|
|
|
*/ |
624
|
|
|
public function inner(\Np\vector $vector) { |
625
|
|
|
return $this->dotVector($vector); |
|
|
|
|
626
|
|
|
} |
627
|
|
|
|
628
|
|
|
public function l1_norm() { |
629
|
|
|
|
630
|
|
|
} |
631
|
|
|
|
632
|
|
|
public function l2_norm() { |
633
|
|
|
|
634
|
|
|
} |
635
|
|
|
|
636
|
|
|
/** |
637
|
|
|
* sort the vector |
638
|
|
|
* @param string $type i or d |
639
|
|
|
* |
640
|
|
|
*/ |
641
|
|
|
public function sort($type = 'i') { |
642
|
|
|
lapack::sort($this, $type); |
643
|
|
|
return $this; |
644
|
|
|
} |
645
|
|
|
|
646
|
|
|
/** |
647
|
|
|
* set data to vector |
648
|
|
|
* @param int|float|array $data |
649
|
|
|
*/ |
650
|
|
|
public function setData(int|float|array $data) { |
651
|
|
|
if (is_array($data) && !is_array($data[0])) { |
652
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
653
|
|
|
$this->data[$i] = $data[$i]; |
654
|
|
|
} |
655
|
|
|
} elseif (is_numeric($data)) { |
656
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
657
|
|
|
$this->data[$i] = $data; |
658
|
|
|
} |
659
|
|
|
} |
660
|
|
|
} |
661
|
|
|
|
662
|
|
|
public function asMatrix(): matrix { |
663
|
|
|
$size = (int) sqrt($this->col); |
664
|
|
|
$ar = matrix::factory($size, $size, $this->dtype); |
665
|
|
|
for ($i = 0; $i < $ar->ndim; ++$i) { |
666
|
|
|
$ar->data[$i] = $this->data[$i]; |
667
|
|
|
} |
668
|
|
|
return $ar; |
669
|
|
|
} |
670
|
|
|
|
671
|
|
|
/** |
672
|
|
|
* get the shape of matrix |
673
|
|
|
* @return int |
674
|
|
|
*/ |
675
|
|
|
public function getShape(): int { |
676
|
|
|
return $this->col; |
677
|
|
|
} |
678
|
|
|
|
679
|
|
|
public function getDtype() { |
680
|
|
|
return $this->dtype; |
681
|
|
|
} |
682
|
|
|
|
683
|
|
|
public function asArray() { |
684
|
|
|
$ar = array_fill(0, $this->col, null); |
685
|
|
|
for ($i = 0; $i < $this->col; ++$i) { |
686
|
|
|
$ar[$i] = $this->data[$i]; |
687
|
|
|
} |
688
|
|
|
return $ar; |
689
|
|
|
} |
690
|
|
|
|
691
|
|
|
public function printVector() { |
692
|
|
|
for ($j = 0; $j < $this->col; ++$j) { |
693
|
|
|
printf('%lf ', $this->data[$j]); |
694
|
|
|
} |
695
|
|
|
echo PHP_EOL; |
696
|
|
|
} |
697
|
|
|
|
698
|
|
|
public function __toString() { |
699
|
|
|
return (string) $this->printVector(); |
|
|
|
|
700
|
|
|
} |
701
|
|
|
|
702
|
|
|
protected function checkDimensions(vector $vector) { |
703
|
|
|
if ($this->col != $vector->col) { |
704
|
|
|
throw new dimensionalityMismatch('Mismatch Dimensions of given vectors'); |
705
|
|
|
} |
706
|
|
|
return true; |
707
|
|
|
} |
708
|
|
|
|
709
|
|
|
protected function checkDtype(vector $vector) { |
710
|
|
|
if ($this->dtype != $vector->dtype) { |
711
|
|
|
throw new dtypeException('Mismatch dtype of given vector'); |
712
|
|
|
} |
713
|
|
|
return true; |
714
|
|
|
} |
715
|
|
|
|
716
|
|
|
protected function __construct(int $col, int $dtype = self::FLOAT) { |
717
|
|
|
if ($col < 1) { |
718
|
|
|
throw new invalidArgumentException('* To create Numphp/Vector col must be greater than 0!, Op Failed! * '); |
719
|
|
|
} |
720
|
|
|
parent::__construct($col, $dtype); |
721
|
|
|
$this->col = $col; |
|
|
|
|
722
|
|
|
return $this; |
723
|
|
|
} |
724
|
|
|
|
725
|
|
|
} |
726
|
|
|
|
For hinted functions/methods where all return statements with the correct type are only reachable via conditions, ?null? gets implicitly returned which may be incompatible with the hinted type. Let?s take a look at an example: