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Stdlib Authors","url":"https://github.com/stdlib-js/stdlib/graphs/contributors"},"license":"Apache-2.0","homepage":"https://stdlib.io","keywords":["stdlib","stdmath","mathematics","math","blas","level 1","dscal","sscal","linear","algebra","scal","scale","subroutines","alpha","vector","array","ndarray","float64","double","float64array"],"repository":{"type":"git","url":"git://github.com/stdlib-js/blas-base-dscal.git"},"description":"Multiply a double-precision floating-point vector by a constant.","contributors":[{"name":"The Stdlib Authors","url":"https://github.com/stdlib-js/stdlib/graphs/contributors"}],"maintainers":[{"name":"stdlib-bot","email":"kgryte+stdlibbot@gmail.com"},{"name":"kgryte","email":"kgryte@gmail.com"},{"name":"planeshifter","email":"pgb@andrew.cmu.edu"},{"name":"rreusser","email":"rsreusser@gmail.com"}],"readme":"<!--\n\n@license Apache-2.0\n\nCopyright (c) 2020 The Stdlib Authors.\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n   http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n\n-->\n\n\n<details>\n  <summary>\n    About stdlib...\n  </summary>\n  <p>We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.</p>\n  <p>The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.</p>\n  <p>When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.</p>\n  <p>To join us in bringing numerical computing to the web, get started by checking us out on <a href=\"https://github.com/stdlib-js/stdlib\">GitHub</a>, and please consider <a href=\"https://opencollective.com/stdlib\">financially supporting stdlib</a>. We greatly appreciate your continued support!</p>\n</details>\n\n# dscal\n\n[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->\n\n> Multiply a double-precision floating-point vector `x` by a constant `alpha`.\n\n<section class=\"installation\">\n\n## Installation\n\n```bash\nnpm install @stdlib/blas-base-dscal\n```\n\n</section>\n\n<section class=\"usage\">\n\n## Usage\n\n```javascript\nvar dscal = require( '@stdlib/blas-base-dscal' );\n```\n\n#### dscal( N, alpha, x, stride )\n\nMultiplies a double-precision floating-point vector `x` by a constant `alpha`.\n\n```javascript\nvar Float64Array = require( '@stdlib/array-float64' );\n\nvar x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n\ndscal( x.length, 5.0, x, 1 );\n// x => <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n```\n\nThe function has the following parameters:\n\n-   **N**: number of indexed elements.\n-   **alpha**: scalar constant.\n-   **x**: input [`Float64Array`][@stdlib/array/float64].\n-   **stride**: index increment.\n\nThe `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to multiply every other value by a constant\n\n```javascript\nvar Float64Array = require( '@stdlib/array-float64' );\n\nvar x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n\ndscal( 4, 5.0, x, 2 );\n// x => <Float64Array>[ -10.0, 1.0, 15.0, -5.0, 20.0, 0.0, -5.0, -3.0 ]\n```\n\nNote that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.\n\n```javascript\nvar Float64Array = require( '@stdlib/array-float64' );\n\n// Initial array...\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n\n// Create an offset view...\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element\n\n// Scale every other value...\ndscal( 3, 5.0, x1, 2 );\n// x0 => <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n```\n\nIf `N` is less than or equal to `0`, the function returns `x` unchanged.\n\n#### dscal.ndarray( N, alpha, x, stride, offset )\n\nMultiplies a double-precision floating-point vector `x` by a constant `alpha` using alternative indexing semantics.\n\n```javascript\nvar Float64Array = require( '@stdlib/array-float64' );\n\nvar x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n\ndscal.ndarray( x.length, 5.0, x, 1, 0 );\n// x => <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n```\n\nThe function has the following additional parameters:\n\n-   **offset**: starting index.\n\nWhile [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the `offset` parameter supports indexing semantics based on a starting index. For example, to multiply the last three elements of `x` by a constant\n\n```javascript\nvar Float64Array = require( '@stdlib/array-float64' );\n\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n\ndscal.ndarray( 3, 5.0, x, 1, x.length-3 );\n// x => <Float64Array>[ 1.0, -2.0, 3.0, -20.0, 25.0, -30.0 ]\n```\n\n</section>\n\n<!-- /.usage -->\n\n<section class=\"notes\">\n\n## Notes\n\n-   If `N <= 0`, both functions return `x` unchanged.\n-   `dscal()` corresponds to the [BLAS][blas] level 1 function [`dscal`][dscal].\n\n</section>\n\n<!-- /.notes -->\n\n<section class=\"examples\">\n\n## Examples\n\n<!-- eslint no-undef: \"error\" -->\n\n```javascript\nvar discreteUniform = require( '@stdlib/random-array-discrete-uniform' );\nvar dscal = require( '@stdlib/blas-base-dscal' );\n\nvar opts = {\n    'dtype': 'float64'\n};\nvar x = discreteUniform( 10, -100, 100, opts );\nconsole.log( x );\n\ndscal( x.length, 5.0, x, 1 );\nconsole.log( x );\n```\n\n</section>\n\n<!-- /.examples -->\n\n<!-- C interface documentation. -->\n\n* * *\n\n<section class=\"c\">\n\n## C APIs\n\n<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->\n\n<section class=\"intro\">\n\n</section>\n\n<!-- /.intro -->\n\n<!-- C usage documentation. -->\n\n<section class=\"usage\">\n\n### Usage\n\n```c\n#include \"stdlib/blas/base/dscal.h\"\n```\n\n#### c_dscal( N, alpha, \\*X, stride )\n\nMultiplies each element of a double-precision floating-point vector by a constant.\n\n```c\ndouble x[] = { 1.0, 2.0, 3.0, 4.0 };\n\nc_dscal( 4, 5.0, x, 1 );\n```\n\nThe function accepts the following arguments:\n\n-   **N**: `[in] CBLAS_INT` number of indexed elements.\n-   **alpha**: `[in] double` scalar constant.\n-   **X**: `[inout] double*` input array.\n-   **stride**: `[in] CBLAS_INT` index increment for `X`.\n\n```c\nvoid c_dscal( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT stride );\n```\n\n#### c_dscal_ndarray( N, alpha, \\*X, stride, offset )\n\nMultiplies each element of a double-precision floating-point vector by a constant using alternative indexing semantics.\n\n```c\ndouble x[] = { 1.0, 2.0, 3.0, 4.0 };\n\nc_dscal_ndarray( 4, 5.0, x, 1, 0 );\n```\n\nThe function accepts the following arguments:\n\n-   **N**: `[in] CBLAS_INT` number of indexed elements.\n-   **alpha**: `[in] double` scalar constant.\n-   **X**: `[inout] double*` input array.\n-   **stride**: `[in] CBLAS_INT` index increment for `X`.\n-   **offset**: `[in] CBLAS_INT` starting index for `X`.\n\n```c\nvoid c_dscal_ndarray( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT stride, const CBLAS_INT offset );\n```\n\n</section>\n\n<!-- /.usage -->\n\n<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->\n\n<section class=\"notes\">\n\n</section>\n\n<!-- /.notes -->\n\n<!-- C API usage examples. -->\n\n<section class=\"examples\">\n\n### Examples\n\n```c\n#include \"stdlib/blas/base/dscal.h\"\n#include <stdio.h>\n\nint main( void ) {\n    // Create a strided array:\n    double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };\n\n    // Specify the number of elements:\n    const int N = 8;\n\n    // Specify a stride:\n    const int stride = 1;\n\n    // Scale the vector:\n    c_dscal( N, 5.0, x, stride );\n\n    // Print the result:\n    for ( int i = 0; i < 8; i++ ) {\n        printf( \"x[ %i ] = %lf\\n\", i, x[ i ] );\n    }\n\n    // Scale the vector:\n    c_dscal_ndarray( N, 5.0, x, -stride, N-1 );\n\n    // Print the result:\n    for ( int i = 0; i < 8; i++ ) {\n        printf( \"x[ %i ] = %lf\\n\", i, x[ i ] );\n    }\n}\n```\n\n</section>\n\n<!-- /.examples -->\n\n</section>\n\n<!-- /.c -->\n\n<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->\n\n<section class=\"related\">\n\n* * *\n\n## See Also\n\n-   <span class=\"package-name\">[`@stdlib/blas-base/daxpy`][@stdlib/blas/base/daxpy]</span><span class=\"delimiter\">: </span><span class=\"description\">multiply a vector `x` by a constant and add the result to `y`.</span>\n-   <span class=\"package-name\">[`@stdlib/blas-base/gscal`][@stdlib/blas/base/gscal]</span><span class=\"delimiter\">: </span><span class=\"description\">multiply a vector by a scalar constant.</span>\n-   <span class=\"package-name\">[`@stdlib/blas-base/sscal`][@stdlib/blas/base/sscal]</span><span class=\"delimiter\">: </span><span class=\"description\">multiply a single-precision floating-point vector by a constant.</span>\n-   <span class=\"package-name\">[`@stdlib/blas-base/saxpy`][@stdlib/blas/base/saxpy]</span><span class=\"delimiter\">: </span><span class=\"description\">multiply a vector `x` by a constant and add the result to `y`.</span>\n\n</section>\n\n<!-- /.related -->\n\n<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->\n\n\n<section class=\"main-repo\" >\n\n* * *\n\n## Notice\n\nThis package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, 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.\n\nFor more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib].\n\n#### Community\n\n[![Chat][chat-image]][chat-url]\n\n---\n\n## License\n\nSee [LICENSE][stdlib-license].\n\n\n## Copyright\n\nCopyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].\n\n</section>\n\n<!-- /.stdlib -->\n\n<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->\n\n<section class=\"links\">\n\n[npm-image]: http://img.shields.io/npm/v/@stdlib/blas-base-dscal.svg\n[npm-url]: https://npmjs.org/package/@stdlib/blas-base-dscal\n\n[test-image]: https://github.com/stdlib-js/blas-base-dscal/actions/workflows/test.yml/badge.svg?branch=v0.4.1\n[test-url]: https://github.com/stdlib-js/blas-base-dscal/actions/workflows/test.yml?query=branch:v0.4.1\n\n[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/blas-base-dscal/main.svg\n[coverage-url]: https://codecov.io/github/stdlib-js/blas-base-dscal?branch=main\n\n<!--\n\n[dependencies-image]: https://img.shields.io/david/stdlib-js/blas-base-dscal.svg\n[dependencies-url]: https://david-dm.org/stdlib-js/blas-base-dscal/main\n\n-->\n\n[chat-image]: https://img.shields.io/badge/zulip-join_chat-brightgreen.svg\n[chat-url]: https://stdlib.zulipchat.com\n\n[stdlib]: https://github.com/stdlib-js/stdlib\n\n[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors\n\n[umd]: https://github.com/umdjs/umd\n[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules\n\n[deno-url]: https://github.com/stdlib-js/blas-base-dscal/tree/deno\n[deno-readme]: https://github.com/stdlib-js/blas-base-dscal/blob/deno/README.md\n[umd-url]: https://github.com/stdlib-js/blas-base-dscal/tree/umd\n[umd-readme]: https://github.com/stdlib-js/blas-base-dscal/blob/umd/README.md\n[esm-url]: https://github.com/stdlib-js/blas-base-dscal/tree/esm\n[esm-readme]: https://github.com/stdlib-js/blas-base-dscal/blob/esm/README.md\n[branches-url]: https://github.com/stdlib-js/blas-base-dscal/blob/main/branches.md\n\n[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/blas-base-dscal/main/LICENSE\n\n[blas]: http://www.netlib.org/blas\n\n[dscal]: http://www.netlib.org/lapack/explore-html/de/da4/group__double__blas__level1.html\n\n[@stdlib/array/float64]: https://www.npmjs.com/package/@stdlib/array-float64\n\n[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray\n\n<!-- <related-links> -->\n\n[@stdlib/blas/base/daxpy]: https://www.npmjs.com/package/@stdlib/blas-base-daxpy\n\n[@stdlib/blas/base/gscal]: https://www.npmjs.com/package/@stdlib/blas-base-gscal\n\n[@stdlib/blas/base/sscal]: https://www.npmjs.com/package/@stdlib/blas-base-sscal\n\n[@stdlib/blas/base/saxpy]: https://www.npmjs.com/package/@stdlib/blas-base-saxpy\n\n<!-- </related-links> -->\n\n</section>\n\n<!-- /.links -->\n","readmeFilename":"README.md"}