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Apache-2.0\n\nCopyright (c) 2021 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--\u003e\n\n\n\u003cdetails\u003e\n  \u003csummary\u003e\n    About stdlib...\n  \u003c/summary\u003e\n  \u003cp\u003eWe 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.\u003c/p\u003e\n  \u003cp\u003eThe 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.\u003c/p\u003e\n  \u003cp\u003eWhen 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.\u003c/p\u003e\n  \u003cp\u003eTo join us in bringing numerical computing to the web, get started by checking us out on \u003ca href=\"https://github.com/stdlib-js/stdlib\"\u003eGitHub\u003c/a\u003e, and please consider \u003ca href=\"https://opencollective.com/stdlib\"\u003efinancially supporting stdlib\u003c/a\u003e. We greatly appreciate your continued support!\u003c/p\u003e\n\u003c/details\u003e\n\n# dmskcbrt\n\n[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] \u003c!-- [![dependencies][dependencies-image]][dependencies-url] --\u003e\n\n\u003e Compute the [cube root][@stdlib/math/base/special/cbrt] for each element in a double-precision floating-point strided array according to a strided mask array.\n\n\u003csection class=\"intro\"\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.intro --\u003e\n\n\u003csection class=\"installation\"\u003e\n\n## Installation\n\n```bash\nnpm install @stdlib/math-strided-special-dmskcbrt\n```\n\nAlternatively,\n\n-   To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]).\n-   If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions).\n-   For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]).\n\nThe [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships.\n\nTo view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.\n\n\u003c/section\u003e\n\n\u003csection class=\"usage\"\u003e\n\n## Usage\n\n```javascript\nvar dmskcbrt = require( '@stdlib/math-strided-special-dmskcbrt' );\n```\n\n#### dmskcbrt( N, x, sx, m, sm, y, sy )\n\nComputes the [cube root][@stdlib/math/base/special/cbrt] for each element in a double-precision floating-point strided array `x` according to a strided mask array and assigns the results to elements in a double-precision floating-point strided array `y`.\n\n```javascript\nvar Float64Array = require( '@stdlib/array-float64' );\nvar Uint8Array = require( '@stdlib/array-uint8' );\n\nvar x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0, 64.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0, 1 ] );\nvar y = new Float64Array( x.length );\n\ndmskcbrt( x.length, x, 1, m, 1, y, 1 );\n// y =\u003e \u003cFloat64Array\u003e[ 0.0, 1.0, 0.0, 3.0, 0.0 ]\n```\n\nThe function accepts the following arguments:\n\n-   **N**: number of indexed elements.\n-   **x**: input [`Float64Array`][@stdlib/array/float64].\n-   **sx**: index increment for `x`.\n-   **m**: mask [`Uint8Array`][@stdlib/array/uint8].\n-   **sm**: index increment for `m`.\n-   **y**: output [`Float64Array`][@stdlib/array/float64].\n-   **sy**: index increment for `y`.\n\nThe `N` and stride parameters determine which strided array elements are accessed at runtime. For example, to index every other value in `x` and to index the first `N` elements of `y` in reverse order,\n\n```javascript\nvar Float64Array = require( '@stdlib/array-float64' );\nvar Uint8Array = require( '@stdlib/array-uint8' );\n\nvar x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0, 64.0, 125.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0, 1, 1 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n\ndmskcbrt( 3, x, 2, m, 2, y, -1 );\n// y =\u003e \u003cFloat64Array\u003e[ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]\n```\n\nNote that indexing is relative to the first index. To introduce an offset, use [`typed array`][@stdlib/array/float64] views.\n\n```javascript\nvar Float64Array = require( '@stdlib/array-float64' );\nvar Uint8Array = require( '@stdlib/array-uint8' );\n\n// Initial arrays...\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0, 64.0, 125.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0, 1, 1 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n\n// Create offset views...\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 ); // start at 2nd element\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element\n\ndmskcbrt( 3, x1, -2, m1, -2, y1, 1 );\n// y0 =\u003e \u003cFloat64Array\u003e[ 0.0, 0.0, 0.0, 0.0, 3.0, 1.0 ]\n```\n\n#### dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n\nComputes the [cube root][@stdlib/math/base/special/cbrt] for each element in a double-precision floating-point strided array `x` according to a strided mask array and assigns the results to elements in a double-precision floating-point strided array `y` using alternative indexing semantics.\n\n```javascript\nvar Float64Array = require( '@stdlib/array-float64' );\nvar Uint8Array = require( '@stdlib/array-uint8' );\n\nvar x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0, 64.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0, 1 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n\ndmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 );\n// y =\u003e \u003cFloat64Array\u003e[ 0.0, 1.0, 0.0, 3.0, 0.0 ]\n```\n\nThe function accepts the following additional arguments:\n\n-   **ox**: starting index for `x`.\n-   **om**: starting index for `m`.\n-   **oy**: starting index for `y`.\n\nWhile [`typed array`][@stdlib/array/float64] views mandate a view offset based on the underlying `buffer`, the offset parameters support indexing semantics based on starting indices. For example, to index every other value in `x` starting from the second value and to index the last `N` elements in `y`,\n\n```javascript\nvar Float64Array = require( '@stdlib/array-float64' );\nvar Uint8Array = require( '@stdlib/array-uint8' );\n\nvar x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0, 64.0, 125.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0, 1, 1 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n\ndmskcbrt.ndarray( 3, x, 2, 1, m, 2, 1, y, -1, y.length-1 );\n// y =\u003e \u003cFloat64Array\u003e[ 0.0, 0.0, 0.0, 0.0, 3.0, 1.0 ]\n```\n\n\u003c/section\u003e\n\n\u003c!-- /.usage --\u003e\n\n\u003csection class=\"notes\"\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.notes --\u003e\n\n\u003csection class=\"examples\"\u003e\n\n## Examples\n\n\u003c!-- eslint no-undef: \"error\" --\u003e\n\n```javascript\nvar uniform = require( '@stdlib/random-base-uniform' );\nvar Float64Array = require( '@stdlib/array-float64' );\nvar Uint8Array = require( '@stdlib/array-uint8' );\nvar dmskcbrt = require( '@stdlib/math-strided-special-dmskcbrt' );\n\nvar x = new Float64Array( 10 );\nvar m = new Uint8Array( 10 );\nvar y = new Float64Array( 10 );\n\nvar i;\nfor ( i = 0; i \u003c x.length; i++ ) {\n    x[ i ] = uniform( -100.0, 100.0 );\n    if ( uniform( 0.0, 1.0 ) \u003c 0.5 ) {\n        m[ i ] = 1;\n    }\n}\nconsole.log( x );\nconsole.log( m );\nconsole.log( y );\n\ndmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, -1, y.length-1 );\nconsole.log( y );\n```\n\n\u003c/section\u003e\n\n\u003c!-- /.examples --\u003e\n\n\u003c!-- C interface documentation. --\u003e\n\n* * *\n\n\u003csection class=\"c\"\u003e\n\n## C APIs\n\n\u003c!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. --\u003e\n\n\u003csection class=\"intro\"\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.intro --\u003e\n\n\u003c!-- C usage documentation. --\u003e\n\n\u003csection class=\"usage\"\u003e\n\n### Usage\n\n```c\n#include \"stdlib/math/strided/special/dmskcbrt.h\"\n```\n\n#### stdlib_strided_dmskcbrt( N, \\*X, strideX, \\*Mask, strideMask, \\*Y, strideY )\n\nComputes the [cube root][@stdlib/math/base/special/cbrt] for each element in a double-precision floating-point strided array `X` according to a strided mask array and assigns the results to elements in a double-precision floating-point strided array `Y`.\n\n```c\n#include \u003cstdint.h\u003e\n\nconst double X[] = { 0.0, 1.0, 8.0, 27.0, 64.0, 125.0, 216.0, 343.0 };\nconst uint8_t Mask[] = { 0, 0, 1, 0, 1, 1, 0, 0 };\ndouble Y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };\n\nconst int64_t N = 4;\n\nstdlib_strided_dmskcbrt( N, X, 2, Mask, 2, Y, 2 );\n```\n\nThe function accepts the following arguments:\n\n-   **N**: `[in] int64_t` number of indexed elements.\n-   **X**: `[in] double*` input array.\n-   **strideX**: `[in] int64_t` index increment for `X`.\n-   **Mask**: `[in] uint8_t*` mask array.\n-   **strideMask**: `[in] int64_t` index increment for `Mask`.\n-   **Y**: `[out] double*` output array.\n-   **strideY**: `[in] int64_t` index increment for `Y`.\n\n```c\nvoid stdlib_strided_dmskcbrt( const int64_t N, const double *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask, double *Y, const int64_t strideY );\n```\n\n\u003c/section\u003e\n\n\u003c!-- /.usage --\u003e\n\n\u003c!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. --\u003e\n\n\u003csection class=\"notes\"\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.notes --\u003e\n\n\u003c!-- C API usage examples. --\u003e\n\n\u003csection class=\"examples\"\u003e\n\n### Examples\n\n```c\n#include \"stdlib/math/strided/special/dmskcbrt.h\"\n#include \u003cstdint.h\u003e\n#include \u003cstdio.h\u003e\n\nint main( void ) {\n    // Create an input strided array:\n    const double X[] = { 0.0, 1.0, 8.0, 27.0, 64.0, 125.0, 216.0, 343.0 };\n\n    // Create a mask strided array:\n    const uint8_t M[] = { 0, 0, 1, 0, 1, 1, 0, 0 };\n\n    // Create an output strided array:\n    double Y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };\n\n    // Specify the number of elements:\n    const int64_t N = 4;\n\n    // Specify the stride lengths:\n    const int64_t strideX = 2;\n    const int64_t strideM = 2;\n    const int64_t strideY = 2;\n\n    // Compute the results:\n    stdlib_strided_dmskcbrt( N, X, strideX, M, strideM, Y, strideY );\n\n    // Print the results:\n    for ( int i = 0; i \u003c 8; i++ ) {\n        printf( \"Y[ %i ] = %lf\\n\", i, Y[ i ] );\n    }\n}\n```\n\n\u003c/section\u003e\n\n\u003c!-- /.examples --\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.c --\u003e\n\n\u003c!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. --\u003e\n\n\u003csection class=\"related\"\u003e\n\n* * *\n\n## See Also\n\n-   \u003cspan class=\"package-name\"\u003e[`@stdlib/math-strided/special/dcbrt`][@stdlib/math/strided/special/dcbrt]\u003c/span\u003e\u003cspan class=\"delimiter\"\u003e: \u003c/span\u003e\u003cspan class=\"description\"\u003ecompute the cube root of each element in a double-precision floating-point strided array.\u003c/span\u003e\n-   \u003cspan class=\"package-name\"\u003e[`@stdlib/math-strided/special/dmsksqrt`][@stdlib/math/strided/special/dmsksqrt]\u003c/span\u003e\u003cspan class=\"delimiter\"\u003e: \u003c/span\u003e\u003cspan class=\"description\"\u003ecompute the principal square root for each element in a double-precision floating-point strided array according to a strided mask array.\u003c/span\u003e\n-   \u003cspan class=\"package-name\"\u003e[`@stdlib/math-strided/special/smskcbrt`][@stdlib/math/strided/special/smskcbrt]\u003c/span\u003e\u003cspan class=\"delimiter\"\u003e: \u003c/span\u003e\u003cspan class=\"description\"\u003ecompute the cube root for each element in a single-precision floating-point strided array according to a strided mask array.\u003c/span\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.related --\u003e\n\n\u003c!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. --\u003e\n\n\n\u003csection class=\"main-repo\" \u003e\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 \u0026copy; 2016-2026. The Stdlib [Authors][stdlib-authors].\n\n\u003c/section\u003e\n\n\u003c!-- /.stdlib --\u003e\n\n\u003c!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. --\u003e\n\n\u003csection class=\"links\"\u003e\n\n[npm-image]: http://img.shields.io/npm/v/@stdlib/math-strided-special-dmskcbrt.svg\n[npm-url]: https://npmjs.org/package/@stdlib/math-strided-special-dmskcbrt\n\n[test-image]: https://github.com/stdlib-js/math-strided-special-dmskcbrt/actions/workflows/test.yml/badge.svg?branch=v0.2.3\n[test-url]: https://github.com/stdlib-js/math-strided-special-dmskcbrt/actions/workflows/test.yml?query=branch:v0.2.3\n\n[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/math-strided-special-dmskcbrt/main.svg\n[coverage-url]: https://codecov.io/github/stdlib-js/math-strided-special-dmskcbrt?branch=main\n\n\u003c!--\n\n[dependencies-image]: https://img.shields.io/david/stdlib-js/math-strided-special-dmskcbrt.svg\n[dependencies-url]: https://david-dm.org/stdlib-js/math-strided-special-dmskcbrt/main\n\n--\u003e\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/math-strided-special-dmskcbrt/tree/deno\n[deno-readme]: https://github.com/stdlib-js/math-strided-special-dmskcbrt/blob/deno/README.md\n[umd-url]: https://github.com/stdlib-js/math-strided-special-dmskcbrt/tree/umd\n[umd-readme]: https://github.com/stdlib-js/math-strided-special-dmskcbrt/blob/umd/README.md\n[esm-url]: https://github.com/stdlib-js/math-strided-special-dmskcbrt/tree/esm\n[esm-readme]: https://github.com/stdlib-js/math-strided-special-dmskcbrt/blob/esm/README.md\n[branches-url]: https://github.com/stdlib-js/math-strided-special-dmskcbrt/blob/main/branches.md\n\n[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/math-strided-special-dmskcbrt/main/LICENSE\n\n[@stdlib/array/float64]: https://github.com/stdlib-js/array-float64\n\n[@stdlib/math/base/special/cbrt]: https://github.com/stdlib-js/math-base-special-cbrt\n\n[@stdlib/array/uint8]: https://github.com/stdlib-js/array-uint8\n\n\u003c!-- \u003crelated-links\u003e --\u003e\n\n[@stdlib/math/strided/special/dcbrt]: https://github.com/stdlib-js/math-strided-special-dcbrt\n\n[@stdlib/math/strided/special/dmsksqrt]: https://github.com/stdlib-js/math-strided-special-dmsksqrt\n\n[@stdlib/math/strided/special/smskcbrt]: https://github.com/stdlib-js/math-strided-special-smskcbrt\n\n\u003c!-- \u003c/related-links\u003e --\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.links --\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstdlib-js%2Fmath-strided-special-dmskcbrt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstdlib-js%2Fmath-strided-special-dmskcbrt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstdlib-js%2Fmath-strided-special-dmskcbrt/lists"}