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Merge branch 'develop' of https://github.com/stdlib-js/stdlib into develop
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.github/workflows/lint_changed_files.yml

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# Pin action to full length commit SHA
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uses: r-lib/actions/setup-r@6f6e5bc62fba3a704f74e7ad7ef7676c5c6a2590 # v2.11.4
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with:
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r-version: '3.5.3'
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r-version: '4.2.0'
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# Lint R files:
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- name: 'Lint R files'

.github/workflows/lint_random_files.yml

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# Pin action to full length commit SHA
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uses: r-lib/actions/setup-r@6f6e5bc62fba3a704f74e7ad7ef7676c5c6a2590 # v2.11.4
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with:
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r-version: '4.3.3'
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r-version: '4.2.0'
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# Lint R files:
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- name: 'Lint R files'

lib/node_modules/@stdlib/blas/ext/base/README.md

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- <span class="signature">[`cfill( N, alpha, x, strideX )`][@stdlib/blas/ext/base/cfill]</span><span class="delimiter">: </span><span class="description">fill a single-precision complex floating-point strided array with a specified scalar constant.</span>
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- <span class="signature">[`cindexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/cindex-of-row]</span><span class="delimiter">: </span><span class="description">return the index of the first row in a single-precision complex floating-point input matrix which has the same elements as a provided search vector.</span>
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- <span class="signature">[`coneTo( N, x, strideX )`][@stdlib/blas/ext/base/cone-to]</span><span class="delimiter">: </span><span class="description">fill a single-precision complex floating-point strided array with linearly spaced numeric elements which increment by `1` starting from one.</span>
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- <span class="signature">[`csum( N, x, strideX )`][@stdlib/blas/ext/base/csum]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision complex floating-point strided array elements.</span>
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- <span class="signature">[`csumkbn( N, x, strideX )`][@stdlib/blas/ext/base/csumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision complex floating-point strided array elements using an improved Kahan–Babuška algorithm.</span>
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- <span class="signature">[`czeroTo( N, x, strideX )`][@stdlib/blas/ext/base/czero-to]</span><span class="delimiter">: </span><span class="description">fill a single-precision complex floating-point strided array with linearly spaced numeric elements which increment by `1` starting from zero.</span>
@@ -259,6 +260,8 @@ console.log( objectKeys( ns ) );
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[@stdlib/blas/ext/base/cindex-of-row]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/cindex-of-row
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[@stdlib/blas/ext/base/cone-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/cone-to
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[@stdlib/blas/ext/base/csum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/csum
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[@stdlib/blas/ext/base/csumkbn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/csumkbn

lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md

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- <span class="signature">[`gnansumkbn2( arrays )`][@stdlib/blas/ext/base/ndarray/gnansumkbn2]</span><span class="delimiter">: </span><span class="description">compute the sum of a one-dimensional ndarray, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.</span>
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- <span class="signature">[`gnansumors( arrays )`][@stdlib/blas/ext/base/ndarray/gnansumors]</span><span class="delimiter">: </span><span class="description">compute the sum of a one-dimensional ndarray, ignoring `NaN` values and using ordinary recursive summation.</span>
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- <span class="signature">[`gnansumpw( arrays )`][@stdlib/blas/ext/base/ndarray/gnansumpw]</span><span class="delimiter">: </span><span class="description">compute the sum of a one-dimensional ndarray, ignoring `NaN` values and using pairwise summation.</span>
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- <span class="signature">[`goneTo( arrays )`][@stdlib/blas/ext/base/ndarray/gone-to]</span><span class="delimiter">: </span><span class="description">fill a one-dimensional ndarray with linearly spaced numeric elements which increment by `1` starting from one.</span>
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- <span class="signature">[`gsort( arrays )`][@stdlib/blas/ext/base/ndarray/gsort]</span><span class="delimiter">: </span><span class="description">sort a one-dimensional ndarray.</span>
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- <span class="signature">[`gsorthp( arrays )`][@stdlib/blas/ext/base/ndarray/gsorthp]</span><span class="delimiter">: </span><span class="description">sort a one-dimensional ndarray using heapsort.</span>
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- <span class="signature">[`gsum( arrays )`][@stdlib/blas/ext/base/ndarray/gsum]</span><span class="delimiter">: </span><span class="description">compute the sum of all elements in a one-dimensional ndarray.</span>
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[@stdlib/blas/ext/base/ndarray/gnansumpw]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gnansumpw
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[@stdlib/blas/ext/base/ndarray/gone-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gone-to
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[@stdlib/blas/ext/base/ndarray/gsort]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gsort
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[@stdlib/blas/ext/base/ndarray/gsorthp]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gsorthp

lib/node_modules/@stdlib/blas/ext/base/ndarray/docs/types/index.d.ts

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import gnansumkbn2 = require( '@stdlib/blas/ext/base/ndarray/gnansumkbn2' );
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import gnansumors = require( '@stdlib/blas/ext/base/ndarray/gnansumors' );
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import gnansumpw = require( '@stdlib/blas/ext/base/ndarray/gnansumpw' );
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import goneTo = require( '@stdlib/blas/ext/base/ndarray/gone-to' );
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import gsort = require( '@stdlib/blas/ext/base/ndarray/gsort' );
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import gsorthp = require( '@stdlib/blas/ext/base/ndarray/gsorthp' );
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import gsum = require( '@stdlib/blas/ext/base/ndarray/gsum' );
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*/
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gnansumpw: typeof gnansumpw;
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/**
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* Fills a one-dimensional ndarray with linearly spaced numeric elements which increment by `1` starting from one.
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*
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* @param arrays - array-like object containing a one-dimensional input ndarray
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* @returns input ndarray
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*
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* @example
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* var ndarray = require( '@stdlib/ndarray/base/ctor' );
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*
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* var xbuf = [ 0.0, 0.0, 0.0, 0.0 ];
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* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
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* // returns <ndarray>[ 0.0, 0.0, 0.0, 0.0 ]
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*
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* var out = ns.goneTo( [ x ] );
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* // returns <ndarray>[ 1.0, 2.0, 3.0, 4.0 ]
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*/
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goneTo: typeof goneTo;
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/**
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* Sorts a one-dimensional ndarray.
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*
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1+
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