diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/README.md b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/README.md index 93d13d5a9f6e..244eb79d876c 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/README.md +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/README.md @@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as var dsnanmeanwd = require( '@stdlib/stats/base/dsnanmeanwd' ); ``` -#### dsnanmeanwd( N, x, stride ) +#### dsnanmeanwd( N, x, strideX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array `x`, ignoring `NaN` values, using Welford's algorithm with extended accumulation, and returning an extended precision result. @@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); -var N = x.length; -var v = dsnanmeanwd( N, x, 1 ); +var v = dsnanmeanwd( x.length, x, 1 ); // returns ~0.3333 ``` @@ -69,39 +68,36 @@ The function has the following parameters: - **N**: number of indexed elements. - **x**: input [`Float32Array`][@stdlib/array/float32]. -- **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 [arithmetic mean][arithmetic-mean] of every other element in `x`, -The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`, + ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); -var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ] ); -var N = floor( x.length / 2 ); +var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ] ); -var v = dsnanmeanwd( N, x, 2 ); +var v = dsnanmeanwd( 5, x, 2 ); // returns 1.25 ``` Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. - + ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); -var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); +var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var N = floor( x0.length / 2 ); - -var v = dsnanmeanwd( N, x1, 2 ); +var v = dsnanmeanwd( 5, x1, 2 ); // returns 1.25 ``` -#### dsnanmeanwd.ndarray( N, x, stride, offset ) +#### dsnanmeanwd.ndarray( N, x, strideX, offsetX ) Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm with extended accumulation and alternative indexing semantics. @@ -109,26 +105,25 @@ Computes the [arithmetic mean][arithmetic-mean] of a single-precision floating-p var Float32Array = require( '@stdlib/array/float32' ); var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); -var N = x.length; -var v = dsnanmeanwd.ndarray( N, x, 1, 0 ); +var v = dsnanmeanwd.ndarray( x.length, x, 1, 0 ); // returns ~0.33333 ``` 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 [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element -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 [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value + ```javascript var Float32Array = require( '@stdlib/array/float32' ); -var floor = require( '@stdlib/math/base/special/floor' ); -var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -var N = floor( x.length / 2 ); +var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); -var v = dsnanmeanwd.ndarray( N, x, 2, 1 ); +var v = dsnanmeanwd.ndarray( 5, x, 2, 1 ); // returns 1.25 ``` @@ -181,6 +176,107 @@ console.log( v ); + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dsnanmeanwd.h" +``` + +#### stdlib_strided_dsnanmeanwd( N, \*X, strideX ) + +Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using Welford's algorithm with extended accumulation, and returning an extended precision result. + +```c +const float x[] = { 1.0f, 2.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 4.0f, 5.0f, 6.0f, 0.0f/0.0f, 7.0f, 8.0f, 0.0f/0.0f }; + +double v = stdlib_strided_dsnanmeanwd( 6, x, 2 ); +// returns ~4.6667 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +double stdlib_strided_dsnanmeanwd( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dsnanmeanwd_ndarray( N, \*X, strideX, offsetX ) + +Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm with extended accumulation and alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 4.0f, 5.0f, 6.0f, 0.0f/0.0f, 7.0f, 8.0f, 0.0f/0.0f }; + +double v = stdlib_strided_dsnanmeanwd_ndarray( 6, x, 2, 0 ); +// returns ~4.6667 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +double stdlib_strided_dsnanmeanwd_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dsnanmeanwd.h" +#include + +int main( void ) { + // Create a strided array: + const float x[] = { 1.0f, 2.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 4.0f, 5.0f, 6.0f, 0.0f/0.0f, 7.0f, 8.0f, 0.0f/0.0f }; + + // Specify the number of elements: + const int N = 6; + + // Specify the stride length: + const int strideX = 2; + + // Compute the arithmetic mean: + double v = stdlib_strided_dsnanmeanwd( N, x, strideX ); + + // Print the result: + printf( "mean: %f\n", v ); +} +``` + +
+ + + + + + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.js index 575114a709f7..c80542acf99b 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.js @@ -21,16 +21,30 @@ // 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 Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsnanmeanwd = require( './../lib/dsnanmeanwd.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -39,17 +53,7 @@ var dsnanmeanwd = require( './../lib/dsnanmeanwd.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float32', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.native.js index c34e6b4d376d..eb277bffd444 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.native.js @@ -22,10 +22,11 @@ var resolve = require( 'path' ).resolve; 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 Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -40,6 +41,19 @@ var opts = { // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -48,17 +62,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float32', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.ndarray.js index 4d1fbdbdf728..8437ee7a9781 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.ndarray.js @@ -21,16 +21,30 @@ // 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 Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var dsnanmeanwd = require( './../lib/ndarray.js' ); // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -39,17 +53,7 @@ var dsnanmeanwd = require( './../lib/ndarray.js' ); * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float32', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.ndarray.native.js index 6099d61b01fc..f18dcd568560 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/benchmark.ndarray.native.js @@ -22,10 +22,11 @@ var resolve = require( 'path' ).resolve; 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 Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -40,6 +41,19 @@ var opts = { // FUNCTIONS // +/** +* Returns a random number. +* +* @private +* @returns {number} random number +*/ +function rand() { + if ( bernoulli( 0.8 ) < 1 ) { + return NaN; + } + return uniform( -10.0, 10.0 ); +} + /** * Creates a benchmark function. * @@ -48,17 +62,7 @@ var opts = { * @returns {Function} benchmark function */ function createBenchmark( len ) { - var x; - var i; - - x = new Float32Array( len ); - for ( i = 0; i < x.length; i++ ) { - if ( randu() < 0.2 ) { - x[ i ] = NaN; - } else { - x[ i ] = ( randu()*20.0 ) - 10.0; - } - } + var x = filledarrayBy( len, 'float32', rand ); return benchmark; function benchmark( b ) { diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/c/benchmark.length.c index 39e750975707..8bbe71247540 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/benchmark/c/benchmark.length.c @@ -94,7 +94,7 @@ static float rand_float( void ) { * @param len array length * @return elapsed time in seconds */ -static double benchmark( int iterations, int len ) { +static double benchmark1( int iterations, int len ) { double elapsed; float x[ len ]; double v; @@ -102,11 +102,16 @@ static double benchmark( int iterations, int len ) { int i; for ( i = 0; i < len; i++ ) { - x[ i ] = ( rand_float()*20000.0f ) - 10000.0f; + if ( rand_float() < 0.2f ) { + x[ i ] = 0.0f / 0.0f; // NaN + } else { + x[ i ] = ( rand_float()*20000.0f ) - 10000.0f; + } } v = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_dsnanmeanwd( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); @@ -120,6 +125,44 @@ static double benchmark( int iterations, int len ) { return elapsed; } +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float x[ len ]; + double v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_float() < 0.2f ) { + x[ i ] = 0.0f / 0.0f; // NaN + } else { + x[ i ] = ( rand_float()*20000.0f ) - 10000.0f; + } + } + v = 0.0; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_dsnanmeanwd_ndarray( len, x, 1, 0 ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + /** * Main execution sequence. */ @@ -142,7 +185,18 @@ int main( void ) { for ( j = 0; j < REPEATS; j++ ) { count += 1; printf( "# c::%s:len=%d\n", NAME, len ); - elapsed = benchmark( iter, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); print_results( iter, elapsed ); printf( "ok %d benchmark finished\n", count ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/docs/repl.txt index 418ac4c8d5a7..d78eb8a9b22a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/docs/repl.txt @@ -1,11 +1,11 @@ -{{alias}}( N, x, stride ) +{{alias}}( N, x, strideX ) Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using Welford's algorithm with extended accumulation, and returning an extended precision result. - 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. @@ -22,8 +22,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -37,28 +37,25 @@ > {{alias}}( x.length, x, 1 ) ~0.3333 - // Using `N` and `stride` parameters: - > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > var stride = 2; - > {{alias}}( N, x, stride ) + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] ); + > {{alias}}( 4, x, 2 ) ~0.3333 // Using view offsets: - > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] ); + > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); - > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 ); - > stride = 2; - > {{alias}}( N, x1, stride ) + > {{alias}}( 4, x1, 2 ) ~-0.3333 -{{alias}}.ndarray( N, x, stride, offset ) + +{{alias}}.ndarray( N, x, strideX, offsetX ) Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm with extended accumulation and alternative indexing semantics. While typed array views mandate a view offset based on the underlying - buffer, the `offset` parameter supports indexing semantics based on a + buffer, the offset parameter supports indexing semantics based on a starting index. Parameters @@ -69,10 +66,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -88,9 +85,8 @@ ~0.3333 // Using offset parameter: - > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] ); - > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 ); - > {{alias}}.ndarray( N, x, 2, 1 ) + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); + > {{alias}}.ndarray( 4, x, 2, 1 ) ~-0.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/docs/types/index.d.ts index 0c2119fa87cc..f989e4f30962 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/docs/types/index.d.ts @@ -38,15 +38,15 @@ interface Routine { * var v = dsnanmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ - ( N: number, x: Float32Array, stride: number ): number; + ( N: number, x: Float32Array, strideX: number ): number; /** * Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm with extended accumulation and alternative indexing semantics. * * @param N - number of indexed elements * @param x - input array - * @param stride - stride length - * @param offset - starting index + * @param strideX - stride length + * @param offsetX - starting index * @returns arithmetic mean * * @example @@ -57,7 +57,7 @@ interface Routine { * var v = dsnanmeanwd.ndarray( x.length, x, 1, 0 ); * // returns ~0.3333 */ - ndarray( N: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -65,7 +65,7 @@ interface Routine { * * @param N - number of indexed elements * @param x - input array -* @param stride - stride length +* @param strideX - stride length * @returns arithmetic mean * * @example diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/examples/c/example.c index 06a583cc1edd..40de65e3f2c3 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/dsnanmeanwd.h" -#include #include int main( void ) { // Create a strided array: - float x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 }; + const float x[] = { 1.0f, 2.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 4.0f, 5.0f, 6.0f, 0.0f/0.0f, 7.0f, 8.0f, 0.0f/0.0f }; // Specify the number of elements: - int64_t N = 6; + const int N = 6; // Specify the stride length: - int64_t stride = 2; + const int strideX = 2; // Compute the arithmetic mean: - double v = stdlib_strided_dsnanmeanwd( N, x, stride ); + double v = stdlib_strided_dsnanmeanwd( N, x, strideX ); // Print the result: printf( "mean: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/include/stdlib/stats/base/dsnanmeanwd.h b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/include/stdlib/stats/base/dsnanmeanwd.h index d86cf4f5de03..2aa8e140b1ac 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/include/stdlib/stats/base/dsnanmeanwd.h +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/include/stdlib/stats/base/dsnanmeanwd.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_DSNANMEANWD_H #define STDLIB_STATS_BASE_DSNANMEANWD_H -#include +#include "stdlib/blas/base/shared.h" /* * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. @@ -31,7 +31,12 @@ extern "C" { /** * Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using Welford's algorithm with extended accumulation, and return an extended precision result. */ -double stdlib_strided_dsnanmeanwd( const int64_t N, const float *X, const int64_t stride ); +double API_SUFFIX(stdlib_strided_dsnanmeanwd)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm with extended accumulation and alternative indexing semantics. +*/ +double API_SUFFIX(stdlib_strided_dsnanmeanwd_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/dsnanmeanwd.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/dsnanmeanwd.js index d0dc54b65649..64f2c96f730a 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/dsnanmeanwd.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/dsnanmeanwd.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + // MAIN // /** @@ -43,50 +49,19 @@ * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = x.length; * -* var v = dsnanmeanwd( N, x, 1 ); +* var v = dsnanmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ -function dsnanmeanwd( N, x, stride ) { - var mu; - var ix; - var v; - var n; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - return x[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - mu = 0.0; - n = 0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - if ( v === v ) { - n += 1; - mu += ( v-mu ) / n; - } - ix += stride; - } - if ( n === 0 ) { - return NaN; - } - return mu; +function dsnanmeanwd( N, x, strideX ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/dsnanmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/dsnanmeanwd.native.js index f6075d835429..a45ed43370ec 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/dsnanmeanwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/dsnanmeanwd.native.js @@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = x.length; * -* var v = dsnanmeanwd( N, x, 1 ); +* var v = dsnanmeanwd( x.length, x, 1 ); * // returns ~0.3333 */ -function dsnanmeanwd( N, x, stride ) { - return addon( N, x, stride ); +function dsnanmeanwd( N, x, strideX ) { + return addon( N, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/index.js index b24b76ac2575..3e4f56921892 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/index.js @@ -28,20 +28,17 @@ * var dsnanmeanwd = require( '@stdlib/stats/base/dsnanmeanwd' ); * * var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = x.length; * -* var v = dsnanmeanwd( N, x, 1 ); +* var v = dsnanmeanwd( x.length, x, 1 ); * // returns ~0.3333 * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var dsnanmeanwd = require( '@stdlib/stats/base/dsnanmeanwd' ); * -* var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -* var N = floor( x.length / 2 ); +* var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); * -* var v = dsnanmeanwd.ndarray( N, x, 2, 1 ); +* var v = dsnanmeanwd.ndarray( 5, x, 2, 1 ); * // returns 1.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/ndarray.js index a73ce982cd6b..1bffaa94930e 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/ndarray.js @@ -43,21 +43,19 @@ * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} 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} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * -* var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -* var N = floor( x.length / 2 ); +* var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); * -* var v = dsnanmeanwd( N, x, 2, 1 ); +* var v = dsnanmeanwd( 5, x, 2, 1 ); * // returns 1.25 */ -function dsnanmeanwd( N, x, stride, offset ) { +function dsnanmeanwd( N, x, strideX, offsetX ) { var mu; var ix; var v; @@ -67,10 +65,10 @@ function dsnanmeanwd( N, x, stride, offset ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - return x[ offset ]; + if ( N === 1 || strideX === 0 ) { + return x[ offsetX ]; } - ix = offset; + ix = offsetX; mu = 0.0; n = 0; for ( i = 0; i < N; i++ ) { @@ -79,7 +77,7 @@ function dsnanmeanwd( N, x, stride, offset ) { n += 1; mu += ( v-mu ) / n; } - ix += stride; + ix += strideX; } if ( n === 0 ) { return NaN; diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/ndarray.native.js index e4433f7c17ea..48de24e45c2b 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './dsnanmeanwd.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -31,27 +30,20 @@ var addon = require( './dsnanmeanwd.native.js' ); * * @param {PositiveInteger} N - number of indexed elements * @param {Float32Array} 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} arithmetic mean * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * -* var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] ); -* var N = floor( x.length / 2 ); +* var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] ); * -* var v = dsnanmeanwd( N, x, 2, 1 ); +* var v = dsnanmeanwd( 5, x, 2, 1 ); * // returns 1.25 */ -function dsnanmeanwd( N, x, stride, offset ) { - var view; - if ( stride < 0 ) { - offset += (N-1) * stride; - } - view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len - return addon( N, view, stride ); +function dsnanmeanwd( N, x, strideX, offsetX ) { + return addon.ndarray( N, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/manifest.json b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/manifest.json index fa8b90ba5510..7a0fdb1d890b 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/manifest.json @@ -1,5 +1,8 @@ { - "options": {}, + "options": { + "task": "build", + "wasm": false + }, "fields": [ { "field": "src", @@ -25,17 +28,18 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/dsnanmeanwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -45,31 +49,51 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/dsnanmeanwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/dsnanmeanwd.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/src/addon.c b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/src/addon.c index 8d875d33e024..a9abf98676f9 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/src/addon.c @@ -22,6 +22,7 @@ #include "stdlib/napi/argv_int64.h" #include "stdlib/napi/argv_strided_float32array.h" #include "stdlib/napi/create_double.h" +#include "stdlib/blas/base/shared.h" #include /** @@ -34,10 +35,27 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dsnanmeanwd( N, X, stride ), v ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsnanmeanwd)( N, X, strideX ), v ); return v; } -STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dsnanmeanwd_ndarray)( N, X, strideX, offsetX ), v ); + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/src/dsnanmeanwd.c b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/src/main.c similarity index 64% rename from lib/node_modules/@stdlib/stats/base/dsnanmeanwd/src/dsnanmeanwd.c rename to lib/node_modules/@stdlib/stats/base/dsnanmeanwd/src/main.c index d4ce81c47fd8..bf6a8e29b459 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/src/dsnanmeanwd.c +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/src/main.c @@ -17,7 +17,8 @@ */ #include "stdlib/stats/base/dsnanmeanwd.h" -#include +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" /** * Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values, using Welford's algorithm with extended accumulation, and returning an extended precision result. @@ -40,29 +41,39 @@ * - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). * - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). * -* @param N number of indexed elements -* @param X input array -* @param stride stride length -* @return output value +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return output value */ -double stdlib_strided_dsnanmeanwd( const int64_t N, const float *X, const int64_t stride ) { - int64_t ix; - int64_t i; - int64_t n; +double API_SUFFIX(stdlib_strided_dsnanmeanwd)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dsnanmeanwd_ndarray)( N, X, strideX, ox ); +} + +/** +* Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm with extended accumulation and alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index for X +* @return output value +*/ +double API_SUFFIX(stdlib_strided_dsnanmeanwd_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + CBLAS_INT n; double mu; double v; if ( N <= 0 ) { return 0.0 / 0.0; // NaN } - if ( N == 1 || stride == 0 ) { - return X[ 0 ]; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; + if ( N == 1 || strideX == 0 ) { + return X[ offsetX ]; } + ix = offsetX; mu = 0.0; n = 0; for ( i = 0; i < N; i++ ) { @@ -71,7 +82,7 @@ double stdlib_strided_dsnanmeanwd( const int64_t N, const float *X, const int64_ n += 1; mu += ( v-mu ) / (double)n; } - ix += stride; + ix += strideX; } if ( n == 0 ) { return 0.0 / 0.0; // NaN diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.dsnanmeanwd.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.dsnanmeanwd.js index 986c58b23b23..9478023accb9 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.dsnanmeanwd.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.dsnanmeanwd.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsnanmeanwd = require( './../lib/dsnanmeanwd.js' ); @@ -90,7 +89,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -106,15 +104,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dsnanmeanwd( N, x, 2 ); + v = dsnanmeanwd( 5, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -130,8 +126,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) NaN // 0 ]); - N = floor( x.length / 2 ); - v = dsnanmeanwd( N, x, -2 ); + v = dsnanmeanwd( 5, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -152,7 +147,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -169,9 +163,8 @@ tape( 'the function supports view offsets', function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsnanmeanwd( N, x1, 2 ); + v = dsnanmeanwd( 5, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.dsnanmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.dsnanmeanwd.native.js index 031edd6f6001..82f684bc9c3e 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.dsnanmeanwd.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.dsnanmeanwd.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -181,7 +180,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -197,15 +195,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dsnanmeanwd( N, x, 2 ); + v = dsnanmeanwd( 5, x, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -221,8 +217,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test NaN // 0 ]); - N = floor( x.length / 2 ); - v = dsnanmeanwd( N, x, -2 ); + v = dsnanmeanwd( 5, x, -2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -243,7 +238,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -260,9 +254,8 @@ tape( 'the function supports view offsets', opts, function test( t ) { ]); x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - N = floor(x1.length / 2); - v = dsnanmeanwd( N, x1, 2 ); + v = dsnanmeanwd( 5, x1, 2 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.ndarray.js index be773e2d611b..395d3beba256 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var dsnanmeanwd = require( './../lib/ndarray.js' ); @@ -90,7 +89,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', function test( t ) { - var N; var x; var v; @@ -106,15 +104,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dsnanmeanwd( N, x, 2, 0 ); + v = dsnanmeanwd( 5, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', function test( t ) { - var N; var x; var v; @@ -130,8 +126,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) NaN // 0 ]); - N = floor( x.length / 2 ); - v = dsnanmeanwd( N, x, -2, 6 ); + v = dsnanmeanwd( 5, x, -2, 8 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -150,7 +145,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', function test( t ) { - var N; var x; var v; @@ -166,9 +160,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]); - N = floor( x.length / 2 ); - v = dsnanmeanwd( N, x, 2, 1 ); + v = dsnanmeanwd( 5, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.ndarray.native.js index 9622342c1110..49babbb1d7b6 100644 --- a/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/dsnanmeanwd/test/test.ndarray.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -99,7 +98,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -115,15 +113,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { NaN // 4 ]); - N = floor( x.length / 2 ); - v = dsnanmeanwd( N, x, 2, 0 ); + v = dsnanmeanwd( 5, x, 2, 0 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -139,8 +135,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test NaN // 0 ]); - N = floor( x.length / 2 ); - v = dsnanmeanwd( N, x, -2, 6 ); + v = dsnanmeanwd( 5, x, -2, 8 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end(); @@ -159,7 +154,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -175,9 +169,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { NaN, NaN // 4 ]); - N = floor( x.length / 2 ); - v = dsnanmeanwd( N, x, 2, 1 ); + v = dsnanmeanwd( 5, x, 2, 1 ); t.strictEqual( v, 1.25, 'returns expected value' ); t.end();