191 lines
5.3 KiB
Markdown
191 lines
5.3 KiB
Markdown
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<!--
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@license Apache-2.0
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Copyright (c) 2020 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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# dnansumpw
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> Calculate the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation.
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<section class="intro">
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</section>
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<!-- /.intro -->
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<section class="usage">
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## Usage
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```javascript
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var dnansumpw = require( '@stdlib/blas/ext/base/dnansumpw' );
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```
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#### dnansumpw( N, x, stride )
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Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation.
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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, NaN, 2.0 ] );
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var N = x.length;
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var v = dnansumpw( N, x, 1 );
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// returns 1.0
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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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- **x**: input [`Float64Array`][@stdlib/array/float64].
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- **stride**: index increment for `x`.
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The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the sum of every other element in `x`,
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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, NaN, -7.0, NaN, 3.0, 4.0, 2.0 ] );
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var N = floor( x.length / 2 );
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var v = dnansumpw( N, x, 2 );
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// returns 5.0
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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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var x0 = new Float64Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
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var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
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var N = floor( x0.length / 2 );
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var v = dnansumpw( N, x1, 2 );
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// returns 5.0
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```
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#### dnansumpw.ndarray( N, x, stride, offset )
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Computes the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation and 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, NaN, 2.0 ] );
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var N = x.length;
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var v = dnansumpw.ndarray( N, x, 1, 0 );
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// returns 1.0
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```
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The function has the following additional parameters:
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- **offset**: starting index for `x`.
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While [`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 calculate the sum of every other value in `x` starting from the second value
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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( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
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var N = floor( x.length / 2 );
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var v = dnansumpw.ndarray( N, x, 2, 1 );
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// returns 5.0
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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`, both functions return `0.0`.
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- In general, pairwise summation is more numerically stable than ordinary recursive summation (i.e., "simple" summation), with slightly worse performance. While not the most numerically stable summation technique (e.g., compensated summation techniques such as the Kahan–Babuška-Neumaier algorithm are generally more numerically stable), pairwise summation strikes a reasonable balance between numerical stability and performance. If either numerical stability or performance is more desirable for your use case, consider alternative summation techniques.
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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 dnansumpw = require( '@stdlib/blas/ext/base/dnansumpw' );
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var x;
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var i;
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x = new Float64Array( 10 );
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for ( i = 0; i < x.length; i++ ) {
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if ( randu() < 0.2 ) {
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x[ i ] = NaN;
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} else {
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x[ i ] = round( randu()*100.0 );
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}
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}
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console.log( x );
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var v = dnansumpw( x.length, x, 1 );
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console.log( v );
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```
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</section>
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<!-- /.examples -->
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* * *
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<section class="references">
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## References
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- Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050][@higham:1993a].
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</section>
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<!-- /.references -->
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<section class="links">
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[@stdlib/array/float64]: https://www.npmjs.com/package/@stdlib/array-float64
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[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
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[@higham:1993a]: https://doi.org/10.1137/0914050
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</section>
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<!-- /.links -->
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