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Apache-2.0\n\nCopyright (c) 2025 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# zsum\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 sum of all elements in a one-dimensional double-precision complex floating-point ndarray.\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/blas-ext-base-ndarray-zsum\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 zsum = require( '@stdlib/blas-ext-base-ndarray-zsum' );\n```\n\n#### zsum( arrays )\n\nComputes the sum of all elements in a one-dimensional double-precision complex floating-point ndarray.\n\n```javascript\nvar Complex128Array = require( '@stdlib/array-complex128' );\nvar ndarray = require( '@stdlib/ndarray-base-ctor' );\n\nvar xbuf = new Complex128Array( [ 1.0, 3.0, 4.0, 2.0 ] );\nvar x = new ndarray( 'complex128', xbuf, [ 2 ], [ 1 ], 0, 'row-major' );\n\nvar v = zsum( [ x ] );\n// returns \u003cComplex128\u003e[ 5.0, 5.0 ]\n```\n\nThe function has the following parameters:\n\n-   **arrays**: array-like object containing a one-dimensional input ndarray.\n\n\u003c/section\u003e\n\n\u003c!-- /.usage --\u003e\n\n\u003csection class=\"notes\"\u003e\n\n## Notes\n\n-   If provided an empty one-dimensional ndarray, the function returns `0.0 + 0.0i`.\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 discreteUniform = require( '@stdlib/random-array-discrete-uniform' );\nvar Complex128Array = require( '@stdlib/array-complex128' );\nvar ndarray = require( '@stdlib/ndarray-base-ctor' );\nvar ndarray2array = require( '@stdlib/ndarray-to-array' );\nvar zsum = require( '@stdlib/blas-ext-base-ndarray-zsum' );\n\nvar xbuf = discreteUniform( 10, -50, 50, {\n    'dtype': 'float64'\n});\nxbuf = new Complex128Array( xbuf );\n\nvar x = new ndarray( 'complex128', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );\nconsole.log( ndarray2array( x ) );\n\nvar v = zsum( [ x ] );\nconsole.log( v );\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/blas/ext/base/ndarray/zsum.h\"\n```\n\n#### stdlib_blas_ext_zsum( arrays )\n\nComputes the sum of all elements in a one-dimensional double-precision complex floating-point ndarray.\n\n```c\n#include \"stdlib/complex/float64/ctor.h\"\n#include \"stdlib/ndarray/ctor.h\"\n#include \"stdlib/ndarray/dtypes.h\"\n#include \"stdlib/ndarray/index_modes.h\"\n#include \"stdlib/ndarray/orders.h\"\n#include \"stdlib/ndarray/base/bytes_per_element.h\"\n#include \"stdlib/complex/float64/real.h\"\n#include \"stdlib/complex/float64/imag.h\"\n#include \u003cstdint.h\u003e\n\n// Create an ndarray:\nconst double data[] = { 1.0, 2.0, 3.0, 4.0 };\nint64_t shape[] = { 2 };\nint64_t strides[] = { STDLIB_NDARRAY_COMPLEX128_BYTES_PER_ELEMENT };\nint8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR };\n\nstruct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_COMPLEX128, (uint8_t *)data, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );\n\n// Compute the sum:\nconst struct ndarray *arrays[] = { x };\nstdlib_complex128_t v = stdlib_blas_ext_zsum( arrays );\n\ndouble re = stdlib_complex128_real( v );\n// returns 4.0\n\ndouble im = stdlib_complex128_imag( v );\n// returns 6.0\n\n// Free allocated memory:\nstdlib_ndarray_free( x );\n```\n\nThe function accepts the following arguments:\n\n-   **arrays**: `[in] struct ndarray**` list containing a one-dimensional input ndarray.\n\n```c\nstdlib_complex128_t stdlib_blas_ext_zsum( const struct ndarray *arrays[] );\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/blas/ext/base/ndarray/zsum.h\"\n#include \"stdlib/complex/float64/ctor.h\"\n#include \"stdlib/complex/float64/real.h\"\n#include \"stdlib/complex/float64/imag.h\"\n#include \"stdlib/ndarray/ctor.h\"\n#include \"stdlib/ndarray/dtypes.h\"\n#include \"stdlib/ndarray/index_modes.h\"\n#include \"stdlib/ndarray/orders.h\"\n#include \"stdlib/ndarray/base/bytes_per_element.h\"\n#include \u003cstdint.h\u003e\n#include \u003cstdlib.h\u003e\n#include \u003cstdio.h\u003e\n\nint main( void ) {\n    // Create a data buffer:\n    const double data[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };\n\n    // Specify the number of array dimensions:\n    const int64_t ndims = 1;\n\n    // Specify the array shape:\n    int64_t shape[] = { 4 };\n\n    // Specify the array strides:\n    int64_t strides[] = { STDLIB_NDARRAY_COMPLEX128_BYTES_PER_ELEMENT };\n\n    // Specify the byte offset:\n    const int64_t offset = 0;\n\n    // Specify the array order:\n    const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR;\n\n    // Specify the index mode:\n    const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR;\n\n    // Specify the subscript index modes:\n    int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR };\n    const int64_t nsubmodes = 1;\n\n    // Create an ndarray:\n    struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_COMPLEX128, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes );\n    if ( x == NULL ) {\n        fprintf( stderr, \"Error allocating memory.\\n\" );\n        exit( 1 );\n    }\n\n    // Define a list of ndarrays:\n    const struct ndarray *arrays[] = { x };\n\n    // Compute the sum:\n    stdlib_complex128_t v = stdlib_blas_ext_zsum( arrays );\n\n    // Print the result:\n    printf( \"sum: %lf + %lfi\\n\", stdlib_complex128_real( v ), stdlib_complex128_imag( v ) );\n\n    // Free allocated memory:\n    stdlib_ndarray_free( x );\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\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/blas-ext-base-ndarray-zsum.svg\n[npm-url]: https://npmjs.org/package/@stdlib/blas-ext-base-ndarray-zsum\n\n[test-image]: https://github.com/stdlib-js/blas-ext-base-ndarray-zsum/actions/workflows/test.yml/badge.svg?branch=main\n[test-url]: https://github.com/stdlib-js/blas-ext-base-ndarray-zsum/actions/workflows/test.yml?query=branch:main\n\n[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/blas-ext-base-ndarray-zsum/main.svg\n[coverage-url]: https://codecov.io/github/stdlib-js/blas-ext-base-ndarray-zsum?branch=main\n\n\u003c!--\n\n[dependencies-image]: https://img.shields.io/david/stdlib-js/blas-ext-base-ndarray-zsum.svg\n[dependencies-url]: https://david-dm.org/stdlib-js/blas-ext-base-ndarray-zsum/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/blas-ext-base-ndarray-zsum/tree/deno\n[deno-readme]: https://github.com/stdlib-js/blas-ext-base-ndarray-zsum/blob/deno/README.md\n[umd-url]: https://github.com/stdlib-js/blas-ext-base-ndarray-zsum/tree/umd\n[umd-readme]: https://github.com/stdlib-js/blas-ext-base-ndarray-zsum/blob/umd/README.md\n[esm-url]: https://github.com/stdlib-js/blas-ext-base-ndarray-zsum/tree/esm\n[esm-readme]: https://github.com/stdlib-js/blas-ext-base-ndarray-zsum/blob/esm/README.md\n[branches-url]: https://github.com/stdlib-js/blas-ext-base-ndarray-zsum/blob/main/branches.md\n\n[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/blas-ext-base-ndarray-zsum/main/LICENSE\n\n\u003c/section\u003e\n\n\u003c!-- /.links --\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstdlib-js%2Fblas-ext-base-ndarray-zsum","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstdlib-js%2Fblas-ext-base-ndarray-zsum","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstdlib-js%2Fblas-ext-base-ndarray-zsum/lists"}