diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/README.md b/lib/node_modules/@stdlib/stats/base/nanstdevyc/README.md index 035d8a165c74..e6c93cea3ba4 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/README.md +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/README.md @@ -98,9 +98,9 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var nanstdevyc = require( '@stdlib/stats/base/nanstdevyc' ); ``` -#### nanstdevyc( N, correction, x, stride ) +#### nanstdevyc( N, correction, x, strideX ) -Computes the [standard deviation][standard-deviation] of a strided array `x` ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. +Computes the [standard deviation][standard-deviation] of a strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; @@ -114,61 +114,52 @@ The function has the following parameters: - **N**: number of indexed elements. - **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction). - **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **stride**: index increment for `x`. +- **strideX**: stride length for `x`. -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the [standard deviation][standard-deviation] of every other element in `x`, ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); +var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ]; -var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ]; -var N = floor( x.length / 2 ); - -var v = nanstdevyc( N, 1, x, 2 ); +var v = nanstdevyc( 5, 1, x, 2 ); // returns 2.5 ``` Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. - + ```javascript var Float64Array = require( '@stdlib/array/float64' ); -var floor = require( '@stdlib/math/base/special/floor' ); -var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); +var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = nanstdevyc( N, 1, x1, 2 ); +var v = nanstdevyc( 5, 1, x1, 2 ); // returns 2.5 ``` -#### nanstdevyc.ndarray( N, correction, x, stride, offset ) +#### nanstdevyc.ndarray( N, correction, x, strideX, offsetX ) Computes the [standard deviation][standard-deviation] of a strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. ```javascript var x = [ 1.0, -2.0, NaN, 2.0 ]; -var v = nanstdevyc.ndarray( x.length, 1, x, 1, 0 ); +var v = nanstdevyc.ndarray( 4, 1, x, 1, 0 ); // returns ~2.0817 ``` The function has the following additional parameters: -- **offset**: starting index for `x`. +- **offsetX**: starting index for `x`. -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 [standard deviation][standard-deviation] for every other value in `x` starting from the second value +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 [standard deviation][standard-deviation] for every other element in `x` starting from the second element ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); - var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ]; -var N = floor( x.length / 2 ); -var v = nanstdevyc.ndarray( N, 1, x, 2, 1 ); +var v = nanstdevyc.ndarray( 4, 1, x, 2, 1 ); // returns 2.5 ``` @@ -182,6 +173,7 @@ var v = nanstdevyc.ndarray( N, 1, x, 2, 1 ); - If `N <= 0`, both functions return `NaN`. - If `n - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements), both functions return `NaN`. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). - Depending on the environment, the typed versions ([`dnanstdevyc`][@stdlib/stats/base/dnanstdevyc], [`snanstdevyc`][@stdlib/stats/base/snanstdevyc], etc.) are likely to be significantly more performant. @@ -195,18 +187,19 @@ var v = nanstdevyc.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); var nanstdevyc = require( '@stdlib/stats/base/nanstdevyc' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - x[ i ] = round( (randu()*100.0) - 50.0 ); +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -50.0, 50.0 ); } + +var x = filledarrayBy( 10, 'generic', rand ); console.log( x ); var v = nanstdevyc( x.length, 1, x, 1 ); @@ -271,6 +264,8 @@ console.log( v ); [@stdlib/stats/base/stdevyc]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/stdevyc +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/nanstdevyc/benchmark/benchmark.js index 3fd11a307317..1b18daa3ae72 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/benchmark/benchmark.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var nanstdevyc = require( './../lib/nanstdevyc.js' ); // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var nanstdevyc = require( './../lib/nanstdevyc.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*20.0 ) - 10.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/nanstdevyc/benchmark/benchmark.ndarray.js index 5a4a06abcb6d..7d70a1556ee5 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/benchmark/benchmark.ndarray.js @@ -21,7 +21,9 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var randu = require( '@stdlib/random/base/randu' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); var pkg = require( './../package.json' ).name; @@ -30,6 +32,19 @@ var nanstdevyc = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random value or `NaN`. +* +* @private +* @returns {number} random number or `NaN` +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -38,17 +53,7 @@ var nanstdevyc = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = []; - for ( i = 0; i < len; i++ ) { - if ( randu() < 0.2 ) { - x.push( NaN ); - } else { - x.push( ( randu()*20.0 ) - 10.0 ); - } - } + var x = filledarrayBy( len, 'generic', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/repl.txt index 472d540962ea..8bf6a94907c4 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the standard deviation of a strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer. - The `N` and `stride` parameters determine which elements in `x` are accessed - at runtime. + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -33,8 +33,8 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -45,23 +45,22 @@ -------- // Standard Usage: > var x = [ 1.0, -2.0, NaN, 2.0 ]; - > {{alias}}( x.length, 1, x, 1 ) + > {{alias}}( 4, 1, x, 1 ) ~2.0817 // Using `N` and `stride` parameters: > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}( N, 1, x, 2 ) + > {{alias}}( 3, 1, x, 2 ) ~2.0817 // Using view offsets: > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > {{alias}}( N, 1, x1, 2 ) + > {{alias}}( 3, 1, x1, 2 ) ~2.0817 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the standard deviation of a strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -90,10 +89,10 @@ x: Array|TypedArray Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -105,13 +104,12 @@ -------- // Standard Usage: > var x = [ 1.0, -2.0, NaN, 2.0 ]; - > {{alias}}.ndarray( x.length, 1, x, 1, 0 ) + > {{alias}}.ndarray( 4, 1, x, 1, 0 ) ~2.0817 // Using offset parameter: > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ]; - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, 1, x, 2, 1 ) + > {{alias}}.ndarray( 3, 1, x, 2, 1 ) ~2.0817 See Also diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/types/index.d.ts index 7a73ae054757..c2e8c9ad6ce4 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/types/index.d.ts @@ -20,7 +20,12 @@ /// -import { NumericArray } from '@stdlib/types/array'; +import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = NumericArray | Collection | AccessorArrayLike; /** * Interface describing `nanstdevyc`. @@ -32,7 +37,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length + * @param strideX - stride length * @returns standard deviation * * @example @@ -41,7 +46,7 @@ interface Routine { * var v = nanstdevyc( x.length, 1, x, 1 ); * // returns ~2.0817 */ - ( N: number, correction: number, x: NumericArray, stride: number ): number; + ( N: number, correction: number, x: InputArray, strideX: number ): number; /** * Computes the standard deviation of a strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer and alternative indexing semantics. @@ -49,8 +54,8 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns standard deviation * * @example @@ -59,7 +64,7 @@ interface Routine { * var v = nanstdevyc.ndarray( x.length, 1, x, 1, 0 ); * // returns ~2.0817 */ - ndarray( N: number, correction: number, x: NumericArray, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: InputArray, strideX: number, offsetX: number ): number; } /** @@ -68,7 +73,7 @@ interface Routine { * @param N - number of indexed elements * @param correction - degrees of freedom adjustment * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns standard deviation * * @example diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/types/test.ts index 3680b56effb6..7d221ec4d740 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/types/test.ts +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/docs/types/test.ts @@ -16,6 +16,7 @@ * limitations under the License. */ +import AccessorArray = require( '@stdlib/array/base/accessor' ); import nanstdevyc = require( './index' ); @@ -26,6 +27,7 @@ import nanstdevyc = require( './index' ); const x = new Float64Array( 10 ); nanstdevyc( x.length, 1, x, 1 ); // $ExpectType number + nanstdevyc( x.length, 1, new AccessorArray( x ), 1 ); // $ExpectType number } // The compiler throws an error if the function is provided a first argument which is not a number... @@ -101,6 +103,7 @@ import nanstdevyc = require( './index' ); const x = new Float64Array( 10 ); nanstdevyc.ndarray( x.length, 1, x, 1, 0 ); // $ExpectType number + nanstdevyc.ndarray( x.length, 1, new AccessorArray( x ), 1, 0 ); // $ExpectType number } // The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/examples/index.js b/lib/node_modules/@stdlib/stats/base/nanstdevyc/examples/index.js index a6fc2a3e4f22..f1cf3b3ebb0e 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/examples/index.js @@ -18,22 +18,19 @@ 'use strict'; -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); var nanstdevyc = require( './../lib' ); -var x; -var i; - -x = new Float64Array( 10 ); -for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = round( (randu()*100.0) - 50.0 ); +function rand() { + if ( bernoulli( 0.8 ) > 1 ) { + return NaN; } + return uniform( -50.0, 50.0 ); } + +var x = filledarrayBy( 10, 'generic', rand ); console.log( x ); var v = nanstdevyc( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/index.js b/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/index.js index fa939e284336..d92fde596a43 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/index.js @@ -28,17 +28,15 @@ * * var x = [ 1.0, -2.0, NaN, 2.0 ]; * -* var v = nanstdevyc( x.length, 1, x, 1 ); +* var v = nanstdevyc( 4, 1, x, 1 ); * // returns ~2.0817 * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); * var nanstdevyc = require( '@stdlib/stats/base/nanstdevyc' ); * * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -* var N = floor( x.length / 2 ); * -* var v = nanstdevyc.ndarray( N, 1, x, 2, 1 ); +* var v = nanstdevyc.ndarray( 5, 1, x, 2, 1 ); * // returns 2.5 */ diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/nanstdevyc.js b/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/nanstdevyc.js index 2473ab4a31ec..e130b31b7c71 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/nanstdevyc.js +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/nanstdevyc.js @@ -20,8 +20,8 @@ // MODULES // -var nanvarianceyc = require( '@stdlib/stats/base/nanvarianceyc' ); -var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -32,17 +32,17 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {NumericArray} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} standard deviation * * @example * var x = [ 1.0, -2.0, NaN, 2.0 ]; * -* var v = nanstdevyc( x.length, 1, x, 1 ); +* var v = nanstdevyc( 4, 1, x, 1 ); * // returns ~2.0817 */ -function nanstdevyc( N, correction, x, stride ) { - return sqrt( nanvarianceyc( N, correction, x, stride ) ); +function nanstdevyc( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/ndarray.js index 81260ddecf0c..a3d4be1f9a97 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/lib/ndarray.js @@ -32,21 +32,18 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {NumericArray} x - input array -* @param {integer} stride - stride length -* @param {NonNegativeInteger} offset - starting index +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index * @returns {number} standard deviation * * @example -* var floor = require( '@stdlib/math/base/special/floor' ); -* * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ]; -* var N = floor( x.length / 2 ); * -* var v = nanstdevyc( N, 1, x, 2, 1 ); +* var v = nanstdevyc( 5, 1, x, 2, 1 ); * // returns 2.5 */ -function nanstdevyc( N, correction, x, stride, offset ) { - return sqrt( nanvarianceyc( N, correction, x, stride, offset ) ); +function nanstdevyc( N, correction, x, strideX, offsetX ) { + return sqrt( nanvarianceyc( N, correction, x, strideX, offsetX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/test/test.nanstdevyc.js b/lib/node_modules/@stdlib/stats/base/nanstdevyc/test/test.nanstdevyc.js index 122465300397..be36cee56377 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/test/test.nanstdevyc.js +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/test/test.nanstdevyc.js @@ -21,7 +21,7 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float64Array = require( '@stdlib/array/float64' ); @@ -95,6 +95,60 @@ tape( 'the function calculates the population standard deviation of a strided ar t.end(); }); +tape( 'the function calculates the population standard deviation of a strided array (ignoring `NaN` values) (accessors)', function test( t ) { + var x; + var v; + var i; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1 ); + t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' ); + + x = [ 1.0, NaN, NaN, -2.0, NaN, -4.0, NaN, 5.0, NaN, 0.0, 3.0, NaN ]; + + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1 ); + t.strictEqual( v, sqrt( 53.5/(x.length-6) ), 'returns expected value' ); + + x = [ -4.0, NaN ]; + + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, NaN ]; + + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN ]; + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ 4.0 ]; + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = []; + for ( i = 0; i < 1e3; i++ ) { + x.push( 100.0 ); + } + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN ]; + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = []; + for ( i = 0; i < 1e3; i++ ) { + x.push( NaN ); + } + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + tape( 'the function calculates the sample standard deviation of a strided array (ignoring `NaN` values)', function test( t ) { var x; var v; @@ -149,6 +203,60 @@ tape( 'the function calculates the sample standard deviation of a strided array t.end(); }); +tape( 'the function calculates the sample standard deviation of a strided array (ignoring `NaN` values) (accessors)', function test( t ) { + var x; + var v; + var i; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1 ); + t.strictEqual( v, sqrt( 53.5/(x.length-2) ), 'returns expected value' ); + + x = [ 1.0, NaN, NaN, -2.0, NaN, -4.0, NaN, 5.0, NaN, 0.0, 3.0, NaN ]; + + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1 ); + t.strictEqual( v, sqrt( 53.5/(x.length-7) ), 'returns expected value' ); + + x = [ -4.0, NaN ]; + + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN, NaN ]; + + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN ]; + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ 4.0 ]; + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = []; + for ( i = 0; i < 1e3; i++ ) { + x.push( 100.0 ); + } + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN ]; + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = []; + for ( i = 0; i < 1e3; i++ ) { + x.push( NaN ); + } + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) { var x; var v; @@ -214,7 +322,6 @@ tape( 'if provided a `correction` parameter yielding a correction term less than }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -231,15 +338,36 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = nanstdevyc( N, 1, x, 2 ); + v = nanstdevyc( 5, 1, x, 2 ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]; + + v = nanstdevyc( 5, 1, toAccessorArray( x ), 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; var i; @@ -256,9 +384,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 4.0, // 0 2.0 ]; - N = floor( x.length / 2 ); - v = nanstdevyc( N, 1, x, -2 ); + v = nanstdevyc( 5, 1, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); x = []; @@ -271,6 +398,37 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); +tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) { + var x; + var v; + var i; + + x = [ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = nanstdevyc( 5, 1, toAccessorArray( x ), -2 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + x = []; + for ( i = 0; i < 1e3; i++ ) { + x.push( 100.0 ); + } + v = nanstdevyc( x.length, 1, toAccessorArray( x ), -1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` provided the correction term is not less than `0` and the first element is not `NaN`', function test( t ) { var x; var v; @@ -296,7 +454,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` p tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float64Array([ @@ -314,9 +471,35 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = nanstdevyc( N, 1, x1, 2 ); + v = nanstdevyc( 5, 1, x1, 2 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets (accessors)', function test( t ) { + var x0; + var x1; + var v; + + x0 = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + 6.0, + NaN, // 4 + NaN + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + + v = nanstdevyc( 5, 1, toAccessorArray( x1 ), 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/nanstdevyc/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/nanstdevyc/test/test.ndarray.js index 0ccfd0d6d7b8..f0715ea6307e 100644 --- a/lib/node_modules/@stdlib/stats/base/nanstdevyc/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/nanstdevyc/test/test.ndarray.js @@ -21,7 +21,7 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var nanstdevyc = require( './../lib/ndarray.js' ); @@ -94,6 +94,60 @@ tape( 'the function calculates the population standard deviation of a strided ar t.end(); }); +tape( 'the function calculates the population standard deviation of a strided array (ignoring `NaN` values) (accessors)', function test( t ) { + var x; + var v; + var i; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, sqrt( 53.5/(x.length-1) ), 'returns expected value' ); + + x = [ 1.0, NaN, NaN, -2.0, NaN, -4.0, NaN, 5.0, NaN, 0.0, 3.0, NaN ]; + + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, sqrt( 53.5/(x.length-6) ), 'returns expected value' ); + + x = [ -4.0, NaN ]; + + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, NaN ]; + + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN ]; + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ 4.0 ]; + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = []; + for ( i = 0; i < 1e3; i++ ) { + x.push( 100.0 ); + } + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN ]; + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = []; + for ( i = 0; i < 1e3; i++ ) { + x.push( NaN ); + } + v = nanstdevyc( x.length, 0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + tape( 'the function calculates the sample standard deviation of a strided array (ignoring `NaN` values)', function test( t ) { var x; var v; @@ -148,6 +202,60 @@ tape( 'the function calculates the sample standard deviation of a strided array t.end(); }); +tape( 'the function calculates the sample standard deviation of a strided array (ignoring `NaN` values) (accessors)', function test( t ) { + var x; + var v; + var i; + + x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ]; + + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, sqrt( 53.5/(x.length-2) ), 'returns expected value' ); + + x = [ 1.0, NaN, NaN, -2.0, NaN, -4.0, NaN, 5.0, NaN, 0.0, 3.0, NaN ]; + + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, sqrt( 53.5/(x.length-7) ), 'returns expected value' ); + + x = [ -4.0, NaN ]; + + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN, NaN ]; + + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ NaN ]; + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = [ 4.0 ]; + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = []; + for ( i = 0; i < 1e3; i++ ) { + x.push( 100.0 ); + } + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = [ NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN ]; + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + x = []; + for ( i = 0; i < 1e3; i++ ) { + x.push( NaN ); + } + v = nanstdevyc( x.length, 1, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) { var x; var v; @@ -213,7 +321,6 @@ tape( 'if provided a `correction` parameter yielding a correction term less than }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -230,15 +337,36 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]; - N = floor( x.length / 2 ); - v = nanstdevyc( N, 1, x, 2, 0 ); + v = nanstdevyc( 5, 1, x, 2, 0 ); + + t.strictEqual( v, 2.5, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `stride` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0, + NaN, // 4 + NaN + ]; + + v = nanstdevyc( 5, 1, toAccessorArray( x ), 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; var i; @@ -255,9 +383,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 4.0, // 0 2.0 ]; - N = floor( x.length / 2 ); - v = nanstdevyc( N, 1, x, -2, 8 ); + v = nanstdevyc( 5, 1, x, -2, 8 ); t.strictEqual( v, 2.5, 'returns expected value' ); x = []; @@ -270,6 +397,37 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) t.end(); }); +tape( 'the function supports a negative `stride` parameter (accessors)', function test( t ) { + var x; + var v; + var i; + + x = [ + NaN, // 4 + NaN, + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]; + + v = nanstdevyc( 5, 1, toAccessorArray( x ), -2, 8 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + x = []; + for ( i = 0; i < 1e3; i++ ) { + x.push( 100.0 ); + } + v = nanstdevyc( x.length, 1, toAccessorArray( x ), -1, x.length-1 ); + t.strictEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` provided the correction term is not less than `0` and the first element is not `NaN`', function test( t ) { var x; var v; @@ -293,7 +451,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` p }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -309,9 +466,31 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]; - N = floor( x.length / 2 ); - v = nanstdevyc( N, 1, x, 2, 1 ); + v = nanstdevyc( 5, 1, x, 2, 1 ); + t.strictEqual( v, 2.5, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `offset` parameter (accessors)', function test( t ) { + var x; + var v; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0, // 3 + NaN, + NaN // 4 + ]; + + v = nanstdevyc( 5, 1, toAccessorArray( x ), 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end();