blas::ger() - Code Metrics - Inspection of "dtype float removed" - ghostjat/Np - Measure and Improve Code Quality continuously with Scrutinizer

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by Shubham

created 2021-06-15 11:48 UTC

blas::ger() A

↳ Parent: blas

Complexity

Conditions	1
Paths	1

Size

Total Lines	4
Code Lines	3

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	1
eloc	3
nc	1
nop	3
dl	0
loc	4
rs	10
c	0
b	0
f	0

<?php

namespace Np\core;

/**
 * OpenBlas
 * 
 * php interface for OpenBLAS
 * 
 * @package Np
 * @category Scientific Computing
 * @author ghost (Shubham Chaudhary)
 * @email [email protected]
 * @copyright (c) 2020-2021, Shubham Chaudhary
 */
class blas {

    const CblasLeft = 141, CblasRight = 142;
    const CblasUpper = 121, CblasLower = 122;
    const CblasNonUnit = 131, CblasUnit = 132;
    const CblasRowMajor = 101, CblasColMajor = 102;
    const CblasNoTrans = 111, CblasTrans = 112, CblasConjTrans = 113;

    public static $ffi_blas = null;

    public static function init() {
        if (is_null(self::$ffi_blas)) {
            self::$ffi_blas = \FFI::scope('blas');
        }
        return self::$ffi_blas;
    }

    public static function setNumThreads(int $num_threads) {
        self::init();
        self::$ffi_blas->openblas_set_num_threads($num_threads);
    }

    public static function getNumThreads(): int {
        self::init();
        return self::$ffi_blas->openblas_get_num_threads();
    }

    public static function getNumPorcs(): int {
        self::init();
        return self::$ffi_blas->openblas_get_num_procs();
    }

    public static function getConfig() {
        self::init();
        return self::$ffi_blas->openblas_get_config();
    }

    public static function getCoreName() {
        self::init();
        return self::$ffi_blas->openblas_get_corename();
    }

    public static function getNumParallel(): int {
        self::init();
        return self::$ffi_blas->openblas_get_parallel();
    }

    /**
     * Product of general matrix and general matrix
     *    C := alpha * AB + beta * C
     * @dtype Float
     * @param \Np\matrix $m1
     * @param \Np\matrix $m2
     * @param \Np\matrix $mr
     * @return \FFI\CData
     */
    public static function gemm(\Np\matrix $m1, \Np\matrix $m2, \Np\matrix $mr, int $trans1 = self::CblasNoTrans, int $trans2 = self::CblasNoTrans) {
        self::init();
        return self::$ffi_blas->cblas_dgemm(self::CblasRowMajor, $trans1, $trans2, $m1->row, $m2->col, $m1->col, 1.0, $m1->data, $m1->col, $m2->data, $m2->col, 0.0, $mr->data, $mr->col);
    }

    /**
     *  Product of symmetric matrix and general matrix
     *    C := alpha * AB + beta * C
     *            or
     *    C := alpha * BA + beta * C
     * 
     * @param \Np\matrix $m1
     * @param \Np\matrix $m2
     * @param \Np\matrix $mr
     */
    public static function symm(\Np\matrix $m1, \Np\matrix $m2, \Np\matrix $mr) {
        self::init();
        return self::$ffi_blas->cblas_dsymm(self::CblasRowMajor, self::CblasLeft, self::CblasUpper, $m1->row,
                        $m2->col, 1.0, $m1->data, $m1->row, $m2->data, $m2->row, 0.0, $mr->data, $mr->row);
    }

    /**
     * Update rank n of symmetric matrix
     *    C := alpha * A A^T + beta * C
     *            or
     *    C := alpha * A^T A + beta * C
     * 
     * @param \Np\matrix $m1
     * @param \Np\matrix $m2
     */
    public static function syrk(\Np\matrix $m1, \Np\matrix $m2) {
        self::init();
        return self::$ffi_blas->cblas_dsyrk(self::CblasRowMajor, self::CblasUpper,
                        self::CblasNoTrans, $m1->row, $m2->col, 1.0, $m1->data, $m1->row, 0.0, $m2->data, $m2->row);
    }

    /**
     * Update rank 2k of symmetric matrix
     *    C := alpha * A B^T + alpha B A^T + beta * C
     *            or
     *    C := alpha * B^T A + alpha A^T B + beta * C
     * 
     * @param \Np\matrix $m1
     * @param \Np\matrix $m2
     * @param \Np\matrix $mr
     */
    public static function syr2k(\Np\matrix $m1, \Np\matrix $m2, \Np\matrix $mr) {
        self::init();
        return self::$ffi_blas->cblas_dsyr2k(self::CblasRowMajor, self::CblasLower, self::CblasNoTrans,
                        $m1->col, $m2->row, 1.0, $m1->data, $m1->row, $m2->data, $m2->row, 0.0, $mr->data, $mr->row);
    }

    /**
     * @static
     * @dtype Double
     * @param \Np\matrix $m
     * @param \Np\vector $v
     * @param \Np\vector $mvr
     * @return \FFI\CData
     */
    public static function gemv(\Np\matrix $m, \Np\vector $v, \Np\vector $mvr) {
        self::init();
        return self::$ffi_blas->cblas_dgemv(self::CblasRowMajor, self::CblasNoTrans, $m->row, $m->col,
                        1.0, $m->data, $m->row, $v->data, 1, 1.0, $mvr->data, 1);
    }

    /**
     * Compute the product of a general matrix and a vector stored in band format.
     *    y := alpha * Ax + beta * y
     * @param int $KL   Number of elements in the lower left part
     * @param int $KU   Number of elements in the upper right part
     * @param double $alpha  Coefficient of scalar multiple of vector
     * @param double $beta   Coefficient of scalar multiple of  mvr
     * @param \Np\matrix $matrix
     * @param \Np\vector $vector
     * @param \Np\vector $mvr
     */
    public static function gbmv(int $KL, int $KU, float $alpha, float $beta, \Np\matrix $matrix, \Np\vector $vector, \Np\vector $mvr) {
        self::init();
        return self::$ffi_blas->cblas_dgbmv(self::CblasRowMajor,
                        self::CblasNoTrans, $matrix->row, $matrix->col,
                        $KL, $KU, $alpha,
                        $matrix->data, $matrix->row, $vector->data,
                        1, $beta, $mvr->data, 1);
    }

    /**
     * Compute the product of a column vector and a row vector. (Real number)
     *    A := alpha * x y^t + A
     * @param \Np\vector $v1
     * @param \Np\vector $v2
     * @param \Np\matrix $m
     * @return void
     */
    public static function ger(\Np\vector $v1, \Np\vector $v2, \Np\matrix $m) {
        self::init();
        return self::$ffi_blas->cblas_dger(self::CblasRowMajor, $v1->col, $v2->col,
                        1.0, $v1->data, 1, $v2->data, 1, $m->data, $m->row);
    }

    /**
     * @static
     * @dtype Double
     * @param \Np\vector $v1
     * @param \Np\vector $v2
     */
    public static function dot(\Np\vector $v1, \Np\vector $v2) {
        self::init();
        return self::$ffi_blas->cblas_ddot($v1->col, $v1->data, 1, $v2->data, 1);
    }

    /**
     * Calculates the index of the element with the largest absolute value in the vector.
     *  Note that this subscript starts from 1. If 0 is returned, n is invalid.
     *    ret := arg max |X(i)|
     *
     *  @param \Np\vector $v
     * @return int index of the element(Note that start from 0 according to cblas)
     */
    public static function max(\Np\vector $v) {
        self::init();
        return self::$ffi_blas->cblas_idamax($v->col, $v->data, 1);
    }

    /**
     *  Calculates the index of the element with the smallest absolute value in the vector.
     *  Note that this subscript starts from 1. If 0 is returned, n is invalid.
     *   ret := arg min |X(i)|
     * 
     * @param \Np\vector $v
     * @return int
     */
    public static function min(\Np\vector $v) {
        self::init();
        return self::$ffi_blas->cblas_idamin($v->col, $v->data, 1);
    }

    /**
     * Exchange the contents of the vector.
     *    X := Y
     *    Y := X
     * @param \Np\vector $v1
     * @param \Np\vector $v2
     * @param int $inv1
     * @param int $inv2
     */
    public static function swap(\Np\vector $v1, \Np\vector $v2, int $inv1 = 1, int $inv2 = 1) {
        self::init();
        return self::$ffi_blas->cblas_dswap($v1->col, $v1->data, $inv1, $v2->data, $inv2);
    }

    /**
     *  Copy the vector from X to Y.
     *    Y := X
     *  @param \Np\vector $vect_X        Vector X buffer
     *  @param \Np\vector $vect_Y        Vector Y buffer
     *  @param int $invX
     *  @param int $invY 
     *  @return void
     */
    public static function copy(\Np\vector $vect_X, \Np\vector $vect_Y, int $invX = 1, int $invY = 1) {
        self::init();
        return self::$ffi_blas->cblas_dcopy($vect_X->col, $vect_X->data, $invX,
                        $vect_Y->data, $invY);
    }

    /**
     * Compute the Euclidean norm of a vector.
     *    ret := ||X||
     * @param \Np\vector $v
     * @return float
     */
    public static function nrm2(\Np\vector $v): float {
        self::init();
        return self::$ffi_blas->cblas_dnrme($v->col, $v->data, 1);
    }

    /**
     *  Add vectors
     *    Y := alpha * X + Y
     *  @param float $alpha     Coefficient of scalar multiple of X vector
     *  @param \Np\vector $vect_X        Vector X buffer
     *  @param \Np\vector $vect_Y        Vector Y buffer
     *  @return void
     */
    public static function axpy(float $alpha, \Np\vector $vect_X, \Np\vector $vect_Y) {
        self::init();
        return self::$ffi_blas->cblas_daxpy($vect_X->col, $alpha, $vect_X->data,
                        1, $vect_Y->data, 1);
    }

    /**
     *  Calculates the sum of the absolute values of each component of the vector.
     *    ret := |x_1| + ... + |x_n|
     *  @param \Np\vector $v        Vector X buffer
     *  @return float
     */
    public static function asum(\Np\vector $v): float {
        self::init();
        return self::$ffi_blas->cblas_dasum($v->col, $v->data, 1);
    }

    /**
     * Rotate about a given point.
     *    X(i) := c * X(i) + s * Y(i)
     *    Y(i) :=-s * X(i) + c * Y(i)
     * @param \Np\vector $v1 Vector X buffer
     * @param \Np\vector $v2 Vector Y buffer
     * @param float $c         value of cos A(Value obtained with rotg function.)
     * @param float $s         value of sin A(Value obtained with rotg function.)
     * 
     */
    public static function rotate(\Np\vector $v1, \Np\vector $v2, float $c, float $s) {
        self::init();
        return self::$ffi_blas->cblas_drot($v1->col, $v1->data, 1, $v2->data, 1, $c, $s);
    }

    /**
     *  Give the point P (a, b).
     *  Rotate this point to givens and calculate the parameters a, b, c,
     *  and s to make the y coordinate zero.
     *    Conditions description:
     *       c * a + s * b = r
     *       -s * a + c * b = 0
     *       r = ||(a,b)||
     *       c^2 + s^2 = 1
     *       z=s if |a| > |b|
     *       z=1/c if |a| <= |b| and c != 0 and r != 0
     *    Find r, z, c, s that satisfies the above description.
     *    However, when r = 0, z = 0, c = 1, and s = 0 are returned.
     *    Also, if c = 0, | a | <= | b | and c! = 0 and r! = 0, z = 1 is returned.
     *  @param float $a     X-coordinate of P: The calculated r value is stored and returned
     *  @param float $b     Y-coordinate of P: The calculated z value is stored and returned
     *  @param float $c     Stores the calculated value of c
     *  @param float $s     Stores the calculated value of s
     *  @return void
     */
    public static function rotg(float $a, float $b, float $c, float $s) {
        self::init();
        return self::$ffi_blas->cblas_drotg($a, $b, $c, $s);
    }

    /**
     * Multiply vector by scalar.
     *
     * @param float $alpha Coefficient of scalar multiple of V vector
     * @param \Np\vector|\Np\matrix $v
     * @return \FFI\CData
     */
    public static function scale(float $alpha, \Np\vector|\Np\matrix $v) {
        self::init();
        return self::$ffi_blas->cblas_dscal($v->ndim, $alpha, $v->data, 1);
    }

}


1			<?php
2
3			namespace Np\core;
4
5			/**
6			* OpenBlas
7			*
8			* php interface for OpenBLAS
9			*
10			* @package Np
11			* @category Scientific Computing
12			* @author ghost (Shubham Chaudhary)
13			* @email [email protected]
14			* @copyright (c) 2020-2021, Shubham Chaudhary
15			*/
16			class blas {
17
18			const CblasLeft = 141, CblasRight = 142;
19			const CblasUpper = 121, CblasLower = 122;
20			const CblasNonUnit = 131, CblasUnit = 132;
21			const CblasRowMajor = 101, CblasColMajor = 102;
22			const CblasNoTrans = 111, CblasTrans = 112, CblasConjTrans = 113;
23
24			public static $ffi_blas = null;
25
26			public static function init() {
27			if (is_null(self::$ffi_blas)) {
28			self::$ffi_blas = \FFI::scope('blas');
29			}
30			return self::$ffi_blas;
31			}
32
33			public static function setNumThreads(int $num_threads) {
34			self::init();
35			self::$ffi_blas->openblas_set_num_threads($num_threads);
36			}
37
38			public static function getNumThreads(): int {
39			self::init();
40			return self::$ffi_blas->openblas_get_num_threads();
41			}
42
43			public static function getNumPorcs(): int {
44			self::init();
45			return self::$ffi_blas->openblas_get_num_procs();
46			}
47
48			public static function getConfig() {
49			self::init();
50			return self::$ffi_blas->openblas_get_config();
51			}
52
53			public static function getCoreName() {
54			self::init();
55			return self::$ffi_blas->openblas_get_corename();
56			}
57
58			public static function getNumParallel(): int {
59			self::init();
60			return self::$ffi_blas->openblas_get_parallel();
61			}
62
63			/**
64			* Product of general matrix and general matrix
65			* C := alpha * AB + beta * C
66			* @dtype Float
67			* @param \Np\matrix $m1
68			* @param \Np\matrix $m2
69			* @param \Np\matrix $mr
70			* @return \FFI\CData
71			*/
72			public static function gemm(\Np\matrix $m1, \Np\matrix $m2, \Np\matrix $mr, int $trans1 = self::CblasNoTrans, int $trans2 = self::CblasNoTrans) {
73			self::init();
74			return self::$ffi_blas->cblas_dgemm(self::CblasRowMajor, $trans1, $trans2, $m1->row, $m2->col, $m1->col, 1.0, $m1->data, $m1->col, $m2->data, $m2->col, 0.0, $mr->data, $mr->col);
75			}
76
77			/**
78			* Product of symmetric matrix and general matrix
79			* C := alpha * AB + beta * C
80			* or
81			* C := alpha * BA + beta * C
82			*
83			* @param \Np\matrix $m1
84			* @param \Np\matrix $m2
85			* @param \Np\matrix $mr
86			*/
87			public static function symm(\Np\matrix $m1, \Np\matrix $m2, \Np\matrix $mr) {
88			self::init();
89			return self::$ffi_blas->cblas_dsymm(self::CblasRowMajor, self::CblasLeft, self::CblasUpper, $m1->row,
90			$m2->col, 1.0, $m1->data, $m1->row, $m2->data, $m2->row, 0.0, $mr->data, $mr->row);
91			}
92
93			/**
94			* Update rank n of symmetric matrix
95			* C := alpha * A A^T + beta * C
96			* or
97			* C := alpha * A^T A + beta * C
98			*
99			* @param \Np\matrix $m1
100			* @param \Np\matrix $m2
101			*/
102			public static function syrk(\Np\matrix $m1, \Np\matrix $m2) {
103			self::init();
104			return self::$ffi_blas->cblas_dsyrk(self::CblasRowMajor, self::CblasUpper,
105			self::CblasNoTrans, $m1->row, $m2->col, 1.0, $m1->data, $m1->row, 0.0, $m2->data, $m2->row);
106			}
107
108			/**
109			* Update rank 2k of symmetric matrix
110			* C := alpha * A B^T + alpha B A^T + beta * C
111			* or
112			* C := alpha * B^T A + alpha A^T B + beta * C
113			*
114			* @param \Np\matrix $m1
115			* @param \Np\matrix $m2
116			* @param \Np\matrix $mr
117			*/
118			public static function syr2k(\Np\matrix $m1, \Np\matrix $m2, \Np\matrix $mr) {
119			self::init();
120			return self::$ffi_blas->cblas_dsyr2k(self::CblasRowMajor, self::CblasLower, self::CblasNoTrans,
121			$m1->col, $m2->row, 1.0, $m1->data, $m1->row, $m2->data, $m2->row, 0.0, $mr->data, $mr->row);
122			}
123
124			/**
125			* @static
126			* @dtype Double
127			* @param \Np\matrix $m
128			* @param \Np\vector $v
129			* @param \Np\vector $mvr
130			* @return \FFI\CData
131			*/
132			public static function gemv(\Np\matrix $m, \Np\vector $v, \Np\vector $mvr) {
133			self::init();
134			return self::$ffi_blas->cblas_dgemv(self::CblasRowMajor, self::CblasNoTrans, $m->row, $m->col,
135			1.0, $m->data, $m->row, $v->data, 1, 1.0, $mvr->data, 1);
136			}
137
138			/**
139			* Compute the product of a general matrix and a vector stored in band format.
140			* y := alpha * Ax + beta * y
141			* @param int $KL Number of elements in the lower left part
142			* @param int $KU Number of elements in the upper right part
143			* @param double $alpha Coefficient of scalar multiple of vector
144			* @param double $beta Coefficient of scalar multiple of mvr
145			* @param \Np\matrix $matrix
146			* @param \Np\vector $vector
147			* @param \Np\vector $mvr
148			*/
149			public static function gbmv(int $KL, int $KU, float $alpha, float $beta, \Np\matrix $matrix, \Np\vector $vector, \Np\vector $mvr) {
150			self::init();
151			return self::$ffi_blas->cblas_dgbmv(self::CblasRowMajor,
152			self::CblasNoTrans, $matrix->row, $matrix->col,
153			$KL, $KU, $alpha,
154			$matrix->data, $matrix->row, $vector->data,
155			1, $beta, $mvr->data, 1);
156			}
157
158			/**
159			* Compute the product of a column vector and a row vector. (Real number)
160			* A := alpha * x y^t + A
161			* @param \Np\vector $v1
162			* @param \Np\vector $v2
163			* @param \Np\matrix $m
164			* @return void
165			*/
166			public static function ger(\Np\vector $v1, \Np\vector $v2, \Np\matrix $m) {
167			self::init();
168			return self::$ffi_blas->cblas_dger(self::CblasRowMajor, $v1->col, $v2->col,
169			1.0, $v1->data, 1, $v2->data, 1, $m->data, $m->row);
170			}
171
172			/**
173			* @static
174			* @dtype Double
175			* @param \Np\vector $v1
176			* @param \Np\vector $v2
177			*/
178			public static function dot(\Np\vector $v1, \Np\vector $v2) {
179			self::init();
180			return self::$ffi_blas->cblas_ddot($v1->col, $v1->data, 1, $v2->data, 1);
181			}
182
183			/**
184			* Calculates the index of the element with the largest absolute value in the vector.
185			* Note that this subscript starts from 1. If 0 is returned, n is invalid.
186			* ret := arg max \|X(i)\|
187			*
188			* @param \Np\vector $v
189			* @return int index of the element(Note that start from 0 according to cblas)
190			*/
191			public static function max(\Np\vector $v) {
192			self::init();
193			return self::$ffi_blas->cblas_idamax($v->col, $v->data, 1);
194			}
195
196			/**
197			* Calculates the index of the element with the smallest absolute value in the vector.
198			* Note that this subscript starts from 1. If 0 is returned, n is invalid.
199			* ret := arg min \|X(i)\|
200			*
201			* @param \Np\vector $v
202			* @return int
203			*/
204			public static function min(\Np\vector $v) {
205			self::init();
206			return self::$ffi_blas->cblas_idamin($v->col, $v->data, 1);
207			}
208
209			/**
210			* Exchange the contents of the vector.
211			* X := Y
212			* Y := X
213			* @param \Np\vector $v1
214			* @param \Np\vector $v2
215			* @param int $inv1
216			* @param int $inv2
217			*/
218			public static function swap(\Np\vector $v1, \Np\vector $v2, int $inv1 = 1, int $inv2 = 1) {
219			self::init();
220			return self::$ffi_blas->cblas_dswap($v1->col, $v1->data, $inv1, $v2->data, $inv2);
221			}
222
223			/**
224			* Copy the vector from X to Y.
225			* Y := X
226			* @param \Np\vector $vect_X Vector X buffer
227			* @param \Np\vector $vect_Y Vector Y buffer
228			* @param int $invX
229			* @param int $invY
230			* @return void
231			*/
232			public static function copy(\Np\vector $vect_X, \Np\vector $vect_Y, int $invX = 1, int $invY = 1) {
233			self::init();
234			return self::$ffi_blas->cblas_dcopy($vect_X->col, $vect_X->data, $invX,
235			$vect_Y->data, $invY);
236			}
237
238			/**
239			* Compute the Euclidean norm of a vector.
240			* ret := \|\|X\|\|
241			* @param \Np\vector $v
242			* @return float
243			*/
244			public static function nrm2(\Np\vector $v): float {
245			self::init();
246			return self::$ffi_blas->cblas_dnrme($v->col, $v->data, 1);
247			}
248
249			/**
250			* Add vectors
251			* Y := alpha * X + Y
252			* @param float $alpha Coefficient of scalar multiple of X vector
253			* @param \Np\vector $vect_X Vector X buffer
254			* @param \Np\vector $vect_Y Vector Y buffer
255			* @return void
256			*/
257			public static function axpy(float $alpha, \Np\vector $vect_X, \Np\vector $vect_Y) {
258			self::init();
259			return self::$ffi_blas->cblas_daxpy($vect_X->col, $alpha, $vect_X->data,
260			1, $vect_Y->data, 1);
261			}
262
263			/**
264			* Calculates the sum of the absolute values of each component of the vector.
265			* ret := \|x_1\| + ... + \|x_n\|
266			* @param \Np\vector $v Vector X buffer
267			* @return float
268			*/
269			public static function asum(\Np\vector $v): float {
270			self::init();
271			return self::$ffi_blas->cblas_dasum($v->col, $v->data, 1);
272			}
273
274			/**
275			* Rotate about a given point.
276			* X(i) := c * X(i) + s * Y(i)
277			* Y(i) :=-s * X(i) + c * Y(i)
278			* @param \Np\vector $v1 Vector X buffer
279			* @param \Np\vector $v2 Vector Y buffer
280			* @param float $c value of cos A(Value obtained with rotg function.)
281			* @param float $s value of sin A(Value obtained with rotg function.)
282			*
283			*/
284			public static function rotate(\Np\vector $v1, \Np\vector $v2, float $c, float $s) {
285			self::init();
286			return self::$ffi_blas->cblas_drot($v1->col, $v1->data, 1, $v2->data, 1, $c, $s);
287			}
288
289			/**
290			* Give the point P (a, b).
291			* Rotate this point to givens and calculate the parameters a, b, c,
292			* and s to make the y coordinate zero.
293			* Conditions description:
294			* c * a + s * b = r
295			* -s * a + c * b = 0
296			* r = \|\|(a,b)\|\|
297			* c^2 + s^2 = 1
298			* z=s if \|a\| > \|b\|
299			* z=1/c if \|a\| <= \|b\| and c != 0 and r != 0
300			* Find r, z, c, s that satisfies the above description.
301			* However, when r = 0, z = 0, c = 1, and s = 0 are returned.
302			* Also, if c = 0, \| a \| <= \| b \| and c! = 0 and r! = 0, z = 1 is returned.
303			* @param float $a X-coordinate of P: The calculated r value is stored and returned
304			* @param float $b Y-coordinate of P: The calculated z value is stored and returned
305			* @param float $c Stores the calculated value of c
306			* @param float $s Stores the calculated value of s
307			* @return void
308			*/
309			public static function rotg(float $a, float $b, float $c, float $s) {
310			self::init();
311			return self::$ffi_blas->cblas_drotg($a, $b, $c, $s);
312			}
313
314			/**
315			* Multiply vector by scalar.
316			*
317			* @param float $alpha Coefficient of scalar multiple of V vector
318			* @param \Np\vector\|\Np\matrix $v
319			* @return \FFI\CData
320			*/
321			public static function scale(float $alpha, \Np\vector\|\Np\matrix $v) {
322			self::init();
323			return self::$ffi_blas->cblas_dscal($v->ndim, $alpha, $v->data, 1);
324			}
325
326			}
327

ghostjat / Np

Push — main ( b63ebb...d6f51d )

blas::ger() A

Complexity

Size

Duplication

Importance

Duplication Side-by-Side

Filter issues like