192 lines
5.5 KiB
Markdown
192 lines
5.5 KiB
Markdown
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<!--
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@license Apache-2.0
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Copyright (c) 2018 The Stdlib Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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-->
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# daxpy
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> Multiply a vector `x` by a constant `alpha` and add the result to `y`.
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<section class="usage">
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## Usage
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```javascript
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var daxpy = require( '@stdlib/blas/base/daxpy' );
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```
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#### daxpy( N, alpha, x, strideX, y, strideY )
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Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
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var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
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var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );
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var alpha = 5.0;
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daxpy( x.length, alpha, x, 1, y, 1 );
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// y => <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]
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```
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The function has the following parameters:
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- **N**: number of indexed elements.
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- **alpha**: `numeric` constant.
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- **x**: input [`Float64Array`][mdn-float64array].
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- **strideX**: index increment for `x`.
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- **y**: input [`Float64Array`][mdn-float64array].
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- **strideY**: index increment for `y`.
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The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to multiply every other value in `x` by `alpha` and add the result to the first `N` elements of `y` in reverse order,
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
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var floor = require( '@stdlib/math/base/special/floor' );
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var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
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var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
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var alpha = 5.0;
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var N = floor( x.length / 2 );
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daxpy( N, alpha, x, 2, y, -1 );
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// y => <Float64Array>[ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]
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```
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Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
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<!-- eslint-disable stdlib/capitalized-comments -->
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
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var floor = require( '@stdlib/math/base/special/floor' );
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// Initial arrays...
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var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
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var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
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// Create offset views...
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var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
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var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element
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var N = floor( x0.length / 2 );
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daxpy( N, 5.0, x1, -2, y1, 1 );
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// y0 => <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]
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```
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#### daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )
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Multiplies a vector `x` by a constant `alpha` and adds the result to `y` using alternative indexing semantics.
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
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var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
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var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );
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var alpha = 5.0;
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daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 );
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// y => <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]
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```
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The function has the following additional parameters:
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- **offsetX**: starting index for `x`.
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- **offsetY**: starting index for `y`.
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While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offsetX` and `offsetY` parameters support indexing semantics based on starting indices. For example, to multiply every other value in `x` by a constant `alpha` starting from the second value and add to the last `N` elements in `y` where `x[i] -> y[n]`, `x[i+2] -> y[n-1]`,...,
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```javascript
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var Float64Array = require( '@stdlib/array/float64' );
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var floor = require( '@stdlib/math/base/special/floor' );
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var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
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var y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
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var alpha = 5.0;
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var N = floor( x.length / 2 );
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daxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 );
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// y => <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]
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```
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</section>
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<!-- /.usage -->
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<section class="notes">
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## Notes
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- If `N <= 0` or `alpha == 0`, both functions return `y` unchanged.
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- `daxpy()` corresponds to the [BLAS][blas] level 1 function [`daxpy`][daxpy].
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</section>
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<!-- /.notes -->
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<section class="examples">
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## Examples
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<!-- eslint no-undef: "error" -->
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```javascript
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var randu = require( '@stdlib/random/base/randu' );
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var round = require( '@stdlib/math/base/special/round' );
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var Float64Array = require( '@stdlib/array/float64' );
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var daxpy = require( '@stdlib/blas/base/daxpy' );
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var x;
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var y;
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var i;
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x = new Float64Array( 10 );
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y = new Float64Array( 10 );
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for ( i = 0; i < x.length; i++ ) {
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x[ i ] = round( randu() * 100.0 );
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y[ i ] = round( randu() * 10.0 );
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}
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console.log( x );
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console.log( y );
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daxpy.ndarray( x.length, 5.0, x, 1, 0, y, -1, y.length-1 );
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console.log( y );
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```
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</section>
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<!-- /.examples -->
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<section class="links">
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[blas]: http://www.netlib.org/blas
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[daxpy]: http://www.netlib.org/lapack/explore-html/de/da4/group__double__blas__level1.html
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[mdn-float64array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float64Array
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[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
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</section>
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<!-- /.links -->
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