@stdlib/stats-base-dnanmskrange

Calculate the range of a double-precision floating-point strided array according to a mask, ignoring NaN values.

https://github.com/stdlib-js/stats-base-dnanmskrange

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dispersion domain extent extremes javascript math mathematics max maximum min minimum node node-js nodejs range statistics stats stdlib strided strided-array

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Calculate the range of a double-precision floating-point strided array according to a mask, ignoring NaN values.

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Host: GitHub
Owner: stdlib-js
License: apache-2.0
Language: JavaScript
Default Branch: main
Homepage: https://github.com/stdlib-js/stdlib
Size: 561 KB

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dispersion domain extent extremes javascript math mathematics max maximum min minimum node node-js nodejs range statistics stats stdlib strided strided-array

Created over 4 years ago · Last pushed 7 months ago

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We 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.

The 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.

When 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.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

dnanmskrange

Calculate the range of a double-precision floating-point strided array according to a mask, ignoring NaN values.

The [**range**][range] is defined as the difference between the maximum and minimum values.

## Installation ```bash npm install @stdlib/stats-base-dnanmskrange ``` Alternatively, - 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]). - If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions). - 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]). The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships. To 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.

## Usage ```javascript var dnanmskrange = require( '@stdlib/stats-base-dnanmskrange' ); ``` #### dnanmskrange( N, x, strideX, mask, strideMask ) Computes the [range][range] of a double-precision floating-point strided array according to a `mask`, ignoring `NaN` values. ```javascript var Float64Array = require( '@stdlib/array-float64' ); var Uint8Array = require( '@stdlib/array-uint8' ); var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] ); var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] ); var v = dnanmskrange( x.length, x, 1, mask, 1 ); // returns 4.0 ``` The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float64Array`][@stdlib/array/float64]. - **strideX**: stride length for `x`. - **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation. - **strideMask**: stride length for `mask`. The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [range][range] of every other element in `x`, ```javascript var Float64Array = require( '@stdlib/array-float64' ); var Uint8Array = require( '@stdlib/array-uint8' ); var x = new Float64Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); var v = dnanmskrange( 4, x, 2, mask, 2 ); // returns 11.0 ``` Note that indexing is relative to the first index. To introduce offsets, use [`typed array`][mdn-typed-array] views. ```javascript var Float64Array = require( '@stdlib/array-float64' ); var Uint8Array = require( '@stdlib/array-uint8' ); var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var v = dnanmskrange( 4, x1, 2, mask1, 2 ); // returns 6.0 ``` #### dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ) Computes the [range][range] of a double-precision floating-point strided array according to a `mask`, ignoring `NaN` values and using alternative indexing semantics. ```javascript var Float64Array = require( '@stdlib/array-float64' ); var Uint8Array = require( '@stdlib/array-uint8' ); var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] ); var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] ); var v = dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 ); // returns 4.0 ``` The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetMask**: starting index for `mask`. While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to calculate the [range][range] for every other element in `x` starting from the second element ```javascript var Float64Array = require( '@stdlib/array-float64' ); var Uint8Array = require( '@stdlib/array-uint8' ); var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] ); var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] ); var v = dnanmskrange.ndarray( 4, x, 2, 1, mask, 2, 1 ); // returns 6.0 ```

## Notes - If `N <= 0`, both functions return `NaN`.

## Examples ```javascript var uniform = require( '@stdlib/random-base-uniform' ); var bernoulli = require( '@stdlib/random-base-bernoulli' ); var filledarrayBy = require( '@stdlib/array-filled-by' ); var dnanmskrange = require( '@stdlib/stats-base-dnanmskrange' ); function rand() { if ( bernoulli( 0.8 ) < 1 ) { return NaN; } return uniform( -50.0, 50.0 ); } var x = filledarrayBy( 10, 'float64', rand ); console.log( x ); var mask = filledarrayBy( x.length, 'uint8', bernoulli.factory( 0.2 ) ); console.log( mask ); var v = dnanmskrange( x.length, x, 1, mask, 1 ); console.log( v ); ```

## C APIs

### Usage ```c #include "stdlib/stats/base/dnanmskrange.h" ``` #### stdlib_strided_dnanmskrange( N, \*X, strideX, \*Mask, strideMask ) Computes the [range][range] of a double-precision floating-point strided array according to a `mask`, ignoring `NaN` values. ```c #include const double x[] = { 1.0, -2.0, 4.0, 2.0, 0.0/0.0 }; const uint8_t mask[] = { 0, 0, 1, 0, 0 }; double v = stdlib_strided_dnanmskrange( 5, x, 1, mask, 1 ); // returns 4.0 ``` The function accepts the following arguments: - **N**: `[in] CBLAS_INT` number of indexed elements. - **X**: `[in] double*` input array. - **strideX**: `[in] CBLAS_INT` stride length for `X`. - **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. - **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. ```c double stdlib_strided_dnanmskrange( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ); ``` #### stdlib_strided_dnanmskrange_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask ) Computes the [range][range] of a double-precision floating-point strided array according to a `mask`, ignoring `NaN` values and using alternative indexing semantics. ```c #include const double x[] = { 1.0, -2.0, 4.0, 2.0, 0.0/0.0 }; const uint8_t mask[] = { 0, 0, 1, 0, 0 }; double v = stdlib_strided_dnanmskrange_ndarray( 5, x, 1, 0, mask, 1, 0 ); // returns 4.0 ``` The function accepts the following arguments: - **N**: `[in] CBLAS_INT` number of indexed elements. - **X**: `[in] double*` input array. - **strideX**: `[in] CBLAS_INT` stride length for `X`. - **offsetX**: `[in] CBLAS_INT` starting index for `X`. - **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation. - **strideMask**: `[in] CBLAS_INT` stride length for `Mask`. - **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`. ```c double stdlib_strided_dnanmskrange_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ); ```

### Examples ```c #include "stdlib/stats/base/dnanmskrange.h" #include #include int main( void ) { // Create a strided array: const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 0.0/0.0, 0.0/0.0 }; // Create a mask array: const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }; // Specify the number of elements: const int N = 5; // Specify the stride lengths: const int strideX = 2; const int strideMask = 2; // Compute the range: double v = stdlib_strided_dnanmskrange( N, x, strideX, mask, strideMask ); // Print the result: printf( "range: %lf\n", v ); } ```

* * * ## Notice This 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. For 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]. #### Community [![Chat][chat-image]][chat-url] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

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Standard library for JavaScript.

Citation (CITATION.cff)

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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npmjs.org: @stdlib/stats-base-dnanmskrange

Calculate the range of a double-precision floating-point strided array according to a mask, ignoring NaN values.

Homepage: https://stdlib.io
License: Apache-2.0
Latest release: 0.2.2
published over 1 year ago

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tape git+https://github.com/kgryte/tape.git#fix/globby development
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@stdlib/math-base-assert-is-nan ^0.0.x
@stdlib/utils-define-nonenumerable-read-only-property ^0.0.x
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@stdlib/stats-base-dnanmskrange

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