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Perform the matrix-matrix operation
C = alpha*op(A)*op(B) + beta*C.
import dgemm from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-ndarray-dgemm@deno/mod.js';Performs the matrix-matrix operation C = alpha*op(A)*op(B) + beta*C, where op(X) is either op(X) = X or op(X) = X^T, alpha and beta are scalars, A, B, and C are matrices, with op(A) an M by K matrix, op(B) a K by N matrix, and C an M by N matrix.
import Float64Matrix from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-matrix-float64@deno/mod.js';
import scalar2ndarray from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-from-scalar@deno/mod.js';
import resolveEnum from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-transpose-operation-resolve-enum@deno/mod.js';
var A = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );
var B = new Float64Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] );
var C = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );
var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), {
'dtype': 'int32'
});
var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), {
'dtype': 'int32'
});
var alpha = scalar2ndarray( 1.0, {
'dtype': 'float64'
});
var beta = scalar2ndarray( 1.0, {
'dtype': 'float64'
});
var out = dgemm( [ A, B, C, transA, transB, alpha, beta ] );
// returns <ndarray>[ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ]
var bool = ( out === C );
// returns trueThe function has the following parameters:
-
arrays: array-like object containing the following ndarrays:
- a two-dimensional input ndarray corresponding to
A. - a two-dimensional input ndarray corresponding to
B. - a two-dimensional input/output ndarray corresponding to
C. - a zero-dimensional ndarray specifying whether
Ashould be transposed, conjugate-transposed, or not transposed. - a zero-dimensional ndarray specifying whether
Bshould be transposed, conjugate-transposed, or not transposed. - a zero-dimensional ndarray containing a scalar constant corresponding to
alpha. - a zero-dimensional ndarray containing a scalar constant corresponding to
beta.
- a two-dimensional input ndarray corresponding to
import discreteUniform from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-discrete-uniform@deno/mod.js';
import scalar2ndarray from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-from-scalar@deno/mod.js';
import resolveEnum from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-transpose-operation-resolve-enum@deno/mod.js';
import ndarray2array from 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-to-array@deno/mod.js';
import dgemm from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-base-ndarray-dgemm@deno/mod.js';
var opts = {
'dtype': 'float64'
};
var A = discreteUniform( [ 3, 4 ], 0, 10, opts );
var B = discreteUniform( [ 4, 2 ], 0, 10, opts );
var C = discreteUniform( [ 3, 2 ], 0, 10, opts );
var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), {
'dtype': 'int32'
});
var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), {
'dtype': 'int32'
});
var alpha = scalar2ndarray( 1.0, opts );
var beta = scalar2ndarray( 1.0, opts );
var out = dgemm( [ A, B, C, transA, transB, alpha, beta ] );
console.log( ndarray2array( out ) );This package is part of stdlib, a standard library with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
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