diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/README.md b/lib/node_modules/@stdlib/stats/base/snanvariancepn/README.md index eb6a46aed57a..171e5820b7f9 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/README.md +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/README.md @@ -98,9 +98,9 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note, var snanvariancepn = require( '@stdlib/stats/base/snanvariancepn' ); ``` -#### snanvariancepn( N, correction, x, stride ) +#### snanvariancepn( N, correction, x, strideX ) -Computes the [variance][variance] of a single-precision floating-point strided array `x` ignoring `NaN` values and using a two-pass algorithm. +Computes the [variance][variance] of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm. ```javascript var Float32Array = require( '@stdlib/array/float32' ); @@ -116,39 +116,36 @@ 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 [variance][variance] according to `n-c` where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements. When computing the [variance][variance] 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 unbiased sample [variance][variance], 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 [`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 [variance][variance] of every other element in `x`, +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] 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 = snanvariancepn( N, 1, x, 2 ); +var v = snanvariancepn( 5, 1, x, 2 ); // returns 6.25 ``` 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 = snanvariancepn( N, 1, x1, 2 ); +var v = snanvariancepn( 5, 1, x1, 2 ); // returns 6.25 ``` -#### snanvariancepn.ndarray( N, correction, x, stride, offset ) +#### snanvariancepn.ndarray( N, correction, x, strideX, offsetX ) Computes the [variance][variance] of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics. @@ -163,18 +160,18 @@ var v = snanvariancepn.ndarray( x.length, 1, x, 1, 0 ); 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 [variance][variance] 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 [variance][variance] 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 ] ); -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 = snanvariancepn.ndarray( N, 1, x, 2, 1 ); +var v = snanvariancepn.ndarray( 5, 1, x, 2, 1 ); // returns 6.25 ``` @@ -200,18 +197,19 @@ var v = snanvariancepn.ndarray( N, 1, x, 2, 1 ); ```javascript -var randu = require( '@stdlib/random/base/randu' ); -var round = require( '@stdlib/math/base/special/round' ); -var Float32Array = require( '@stdlib/array/float32' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); var snanvariancepn = require( '@stdlib/stats/base/snanvariancepn' ); -var x; -var i; - -x = new Float32Array( 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, 'float32', rand ); console.log( x ); var v = snanvariancepn( x.length, 1, x, 1 ); @@ -222,6 +220,125 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/snanvariancepn.h" +``` + +#### stdlib_strided_snanvariancepn( N, correction, \*X, strideX ) + +Computes the [variance][variance] of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm. + +```c +const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f }; + +float v = stdlib_strided_snanvariancepn( 4, 1.0f, x, 1 ); +// returns ~4.3333f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` 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 [variance][variance] according to `n-c` where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements. When computing the [variance][variance] 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 unbiased sample [variance][variance], 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**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. + +```c +float stdlib_strided_snanvariancepn( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_snanvariancepn_ndarray( N, correction, \*X, strideX, offsetX ) + +Computes the [variance][variance] of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics. + +```c +const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f }; + +float v = stdlib_strided_snanvariancepn_ndarray( 4, 1.0f, x, 1, 0 ); +// returns ~4.3333f +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **correction**: `[in] float` 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 [variance][variance] according to `n-c` where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements. When computing the [variance][variance] 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 unbiased sample [variance][variance], 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**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. + +```c +float stdlib_strided_snanvariancepn_ndarray( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/snanvariancepn.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 variance: + float v = stdlib_strided_snanvariancepn( N, 1.0f, x, strideX ); + + // Print the result: + printf( "sample variance: %f\n", v ); +} +``` + +
+ + + +
+ + + * * *
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.js index 836a588556c5..9f2122f34287 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/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 isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var snanvariancepn = require( './../lib/snanvariancepn.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. * @@ -39,17 +53,7 @@ var snanvariancepn = require( './../lib/snanvariancepn.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/snanvariancepn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.native.js index 03c1f751db0b..8f7fa8621f6c 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/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 isnanf = require( '@stdlib/math/base/assert/is-nanf' ); 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 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. * @@ -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/snanvariancepn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.js index a42e8965bde5..2e2d6644ff88 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/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 isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); -var Float32Array = require( '@stdlib/array/float32' ); var pkg = require( './../package.json' ).name; var snanvariancepn = 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. * @@ -39,17 +53,7 @@ var snanvariancepn = 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/snanvariancepn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.native.js index 2e5e254b1cdc..56ce8a4f843b 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/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 isnanf = require( '@stdlib/math/base/assert/is-nanf' ); 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 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. * @@ -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/snanvariancepn/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/c/benchmark.length.c index de403cac8195..445fa95b5fda 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/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 ]; float 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() < 0.2 ) { + x[ i ] = 0.0f / 0.0f; // NaN + } else { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } } v = 0.0f; t = tic(); for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar v = stdlib_strided_snanvariancepn( len, 1.0f, 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 ]; + float v; + double t; + int i; + + for ( i = 0; i < len; i++ ) { + if ( rand_float() < 0.2 ) { + x[ i ] = 0.0f / 0.0f; // NaN + } else { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + } + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + v = stdlib_strided_snanvariancepn_ndarray( len, 1.0f, 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/snanvariancepn/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/repl.txt index 28f293820f68..60bae8809e43 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/repl.txt @@ -1,10 +1,10 @@ -{{alias}}( N, correction, x, stride ) +{{alias}}( N, correction, x, strideX ) Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm. - 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. @@ -34,8 +34,8 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. Returns ------- @@ -49,20 +49,19 @@ > {{alias}}( x.length, 1, x, 1 ) ~4.3333 - // Using `N` and `stride` parameters: - > x = new {{alias:@stdlib/array/float32}}( [ -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 ) + // 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, 1, x, 2 ) ~4.3333 // Using view offsets: - > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] ); + > 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 ); - > {{alias}}( N, 1, x1, 2 ) + > {{alias}}( 4, 1, x1, 2 ) ~4.3333 -{{alias}}.ndarray( N, correction, x, stride, offset ) + +{{alias}}.ndarray( N, correction, x, strideX, offsetX ) Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics. @@ -92,10 +91,10 @@ x: Float32Array Input array. - stride: integer - Index increment. + strideX: integer + Stride length. - offset: integer + offsetX: integer Starting index. Returns @@ -111,9 +110,8 @@ ~4.3333 // Using offset parameter: - > var x = new {{alias:@stdlib/array/float32}}( [ 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 ) + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] ); + > {{alias}}.ndarray( 4, 1, x, 2, 1 ) ~4.3333 See Also diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/types/index.d.ts index 2828ff3b1201..43bea31e3c51 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/types/index.d.ts @@ -28,7 +28,7 @@ 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 variance * * @example @@ -39,7 +39,7 @@ interface Routine { * var v = snanvariancepn( x.length, 1, x, 1 ); * // returns ~4.3333 */ - ( N: number, correction: number, x: Float32Array, stride: number ): number; + ( N: number, correction: number, x: Float32Array, strideX: number ): number; /** * Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics. @@ -47,8 +47,8 @@ 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 variance * * @example @@ -59,7 +59,7 @@ interface Routine { * var v = snanvariancepn.ndarray( x.length, 1, x, 1, 0 ); * // returns ~4.3333 */ - ndarray( N: number, correction: number, x: Float32Array, stride: number, offset: number ): number; + ndarray( N: number, correction: number, x: Float32Array, strideX: number, offsetX: number ): number; } /** @@ -68,7 +68,7 @@ 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 variance * * @example diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/c/example.c index 16fbdd6601d8..1aaf4a3635a0 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/c/example.c @@ -17,21 +17,20 @@ */ #include "stdlib/stats/base/snanvariancepn.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[] = { 1.0, 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 }; // 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 variance: - float v = stdlib_strided_snanvariancepn( N, 1.0f, x, stride ); + float v = stdlib_strided_snanvariancepn( N, 1.0f, x, strideX ); // Print the result: printf( "sample variance: %f\n", v ); diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/index.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/index.js index 94f2cd4343a0..5de2baf9dd0f 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/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 Float32Array = require( '@stdlib/array/float32' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var filledarrayBy = require( '@stdlib/array/filled-by' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); var snanvariancepn = require( './../lib' ); -var x; -var i; - -x = new Float32Array( 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, 'float32', rand ); console.log( x ); var v = snanvariancepn( x.length, 1, x, 1 ); diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/include/stdlib/stats/base/snanvariancepn.h b/lib/node_modules/@stdlib/stats/base/snanvariancepn/include/stdlib/stats/base/snanvariancepn.h index 3b068f12175c..e2faea345c0c 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/include/stdlib/stats/base/snanvariancepn.h +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/include/stdlib/stats/base/snanvariancepn.h @@ -19,7 +19,7 @@ #ifndef STDLIB_STATS_BASE_SNANVARIANCEPN_H #define STDLIB_STATS_BASE_SNANVARIANCEPN_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 variance of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm. */ -float stdlib_strided_snanvariancepn( const int64_t N, const float correction, const float *X, const int64_t stride ); +float API_SUFFIX(stdlib_strided_snanvariancepn)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ); + +/** +* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics. +*/ +float API_SUFFIX(stdlib_strided_snanvariancepn_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/index.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/index.js index 48ff38fb8922..5b711544871c 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/index.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/index.js @@ -34,13 +34,11 @@ * * @example * var Float32Array = require( '@stdlib/array/float32' ); -* var floor = require( '@stdlib/math/base/special/floor' ); * var snanvariancepn = require( '@stdlib/stats/base/snanvariancepn' ); * * var x = new Float32Array( [ 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 = snanvariancepn.ndarray( N, 1, x, 2, 1 ); +* var v = snanvariancepn.ndarray( 5, 1, x, 2, 1 ); * // returns 6.25 */ diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.js index dd341090edb8..8cb371241ed5 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.js @@ -46,21 +46,19 @@ var WORKSPACE = [ 0.0, 0 ]; * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @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} variance * * @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, NaN ] ); -* var N = floor( x.length / 2 ); * -* var v = snanvariancepn( N, 1, x, 2, 1 ); +* var v = snanvariancepn( 5, 1, x, 2, 1 ); * // returns 6.25 */ -function snanvariancepn( N, correction, x, stride, offset ) { +function snanvariancepn( N, correction, x, strideX, offsetX ) { var mu; var ix; var M2; @@ -74,19 +72,19 @@ function snanvariancepn( N, correction, x, stride, offset ) { if ( N <= 0 ) { return NaN; } - if ( N === 1 || stride === 0 ) { - v = x[ offset ]; + if ( N === 1 || strideX === 0 ) { + v = x[ offsetX ]; if ( v === v && N-correction > 0.0 ) { return 0.0; } return NaN; } - ix = offset; + ix = offsetX; // Compute an estimate for the mean... WORKSPACE[ 0 ] = 0.0; WORKSPACE[ 1 ] = 0; - snansumpw( N, WORKSPACE, x, stride, ix ); + snansumpw( N, WORKSPACE, x, strideX, ix ); n = WORKSPACE[ 1 ]; nc = n - correction; if ( nc <= 0.0 ) { @@ -105,7 +103,7 @@ function snanvariancepn( N, correction, x, stride, offset ) { M = float64ToFloat32( M + d ); n += 1; } - ix += stride; + ix += strideX; } return float64ToFloat32( float64ToFloat32(M2/nc) - float64ToFloat32(float64ToFloat32(M/n)*float64ToFloat32(M/nc)) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.native.js index 7a2ca055b51e..8c4c2e0486a8 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.native.js @@ -20,8 +20,7 @@ // MODULES // -var Float32Array = require( '@stdlib/array/float32' ); -var addon = require( './snanvariancepn.native.js' ); +var addon = require( './../src/addon.node' ); // MAIN // @@ -32,27 +31,20 @@ var addon = require( './snanvariancepn.native.js' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @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} variance * * @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, NaN ] ); -* var N = floor( x.length / 2 ); * -* var v = snanvariancepn( N, 1, x, 2, 1 ); +* var v = snanvariancepn( 5, 1, x, 2, 1 ); * // returns 6.25 */ -function snanvariancepn( N, correction, 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, correction, view, stride ); +function snanvariancepn( N, correction, x, strideX, offsetX ) { + return addon.ndarray( N, correction, x, strideX, offsetX ); } diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snansumpw.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snansumpw.js index e09fce5b3698..fc8ba7b4b62c 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snansumpw.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snansumpw.js @@ -47,22 +47,20 @@ var BLOCKSIZE = 128; * @param {PositiveInteger} N - number of indexed elements * @param {NumericArray} out - two-element output array whose first element is the accumulated sum and whose second element is the accumulated number of summed values * @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 {NumericArray} output array * * @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, NaN ] ); -* var N = floor( x.length / 2 ); * * var out = [ 0.0, 0 ]; -* var v = snansumpw( N, out, x, 2, 1 ); +* var v = snansumpw( 5, out, x, 2, 1 ); * // returns [ 5.0, 4 ] */ -function snansumpw( N, out, x, stride, offset ) { +function snansumpw( N, out, x, strideX, offsetX ) { var ix; var s0; var s1; @@ -78,7 +76,7 @@ function snansumpw( N, out, x, stride, offset ) { var v; var i; - ix = offset; + ix = offsetX; if ( N < 8 ) { // Use simple summation... s = 0.0; @@ -89,7 +87,7 @@ function snansumpw( N, out, x, stride, offset ) { s = float64ToFloat32( s + v ); n += 1; } - ix += stride; + ix += strideX; } out[ 0 ] = float64ToFloat32( out[ 0 ] + s ); out[ 1 ] += n; @@ -114,49 +112,49 @@ function snansumpw( N, out, x, stride, offset ) { s0 = float64ToFloat32( s0 + v ); n += 1; } - ix += stride; + ix += strideX; v = x[ ix ]; if ( v === v ) { s1 = float64ToFloat32( s1 + v ); n += 1; } - ix += stride; + ix += strideX; v = x[ ix ]; if ( v === v ) { s2 = float64ToFloat32( s2 + v ); n += 1; } - ix += stride; + ix += strideX; v = x[ ix ]; if ( v === v ) { s3 = float64ToFloat32( s3 + v ); n += 1; } - ix += stride; + ix += strideX; v = x[ ix ]; if ( v === v ) { s4 = float64ToFloat32( s4 + v ); n += 1; } - ix += stride; + ix += strideX; v = x[ ix ]; if ( v === v ) { s5 = float64ToFloat32( s5 + v ); n += 1; } - ix += stride; + ix += strideX; v = x[ ix ]; if ( v === v ) { s6 = float64ToFloat32( s6 + v ); n += 1; } - ix += stride; + ix += strideX; v = x[ ix ]; if ( v === v ) { s7 = float64ToFloat32( s7 + v ); n += 1; } - ix += stride; + ix += strideX; } // Pairwise sum the accumulators: s = float64ToFloat32( float64ToFloat32(float64ToFloat32(s0+s1) + float64ToFloat32(s2+s3)) + float64ToFloat32(float64ToFloat32(s4+s5) + float64ToFloat32(s6+s7)) ); // eslint-disable-line max-len @@ -168,7 +166,7 @@ function snansumpw( N, out, x, stride, offset ) { s = float64ToFloat32( s + v ); n += 1; } - ix += stride; + ix += strideX; } out[ 0 ] = float64ToFloat32( out[ 0 ] + s ); out[ 1 ] += n; @@ -177,7 +175,7 @@ function snansumpw( N, out, x, stride, offset ) { // Recurse by dividing by two, but avoiding non-multiples of unroll factor... n = floor( N/2 ); n -= n % 8; - return float64ToFloat32( snansumpw( n, out, x, stride, ix ) + snansumpw( N-n, out, x, stride, ix+(n*stride) ) ); // eslint-disable-line max-len + return float64ToFloat32( snansumpw( n, out, x, strideX, ix ) + snansumpw( N-n, out, x, strideX, ix+(n*strideX) ) ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.js index 4252fbec5e6e..6364de7bead4 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.js @@ -20,13 +20,8 @@ // MODULES // -var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); -var snansumpw = require( './snansumpw.js' ); - - -// VARIABLES // - -var WORKSPACE = [ 0.0, 0 ]; +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); // MAIN // @@ -46,69 +41,19 @@ var WORKSPACE = [ 0.0, 0 ]; * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = x.length; * -* var v = snanvariancepn( N, 1, x, 1 ); +* var v = snanvariancepn( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function snanvariancepn( N, correction, x, stride ) { - var mu; - var ix; - var M2; - var nc; - var M; - var d; - var v; - var n; - var i; - - if ( N <= 0 ) { - return NaN; - } - if ( N === 1 || stride === 0 ) { - v = x[ 0 ]; - if ( v === v && N-correction > 0.0 ) { - return 0.0; - } - return NaN; - } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - // Compute an estimate for the mean... - WORKSPACE[ 0 ] = 0.0; - WORKSPACE[ 1 ] = 0; - snansumpw( N, WORKSPACE, x, stride, ix ); - n = WORKSPACE[ 1 ]; - nc = n - correction; - if ( nc <= 0.0 ) { - return NaN; - } - mu = float64ToFloat32( WORKSPACE[ 0 ] / n ); - - // Compute the variance... - M2 = 0.0; - M = 0.0; - for ( i = 0; i < N; i++ ) { - v = x[ ix ]; - if ( v === v ) { - d = float64ToFloat32( v - mu ); - M2 = float64ToFloat32( M2 + float64ToFloat32( d*d ) ); - M = float64ToFloat32( M + d ); - n += 1; - } - ix += stride; - } - return float64ToFloat32( float64ToFloat32(M2/nc) - float64ToFloat32(float64ToFloat32(M/n)*float64ToFloat32(M/nc)) ); // eslint-disable-line max-len +function snanvariancepn( N, correction, x, strideX ) { + return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.native.js index 46b7e17eab5b..3cbe2d351c1d 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.native.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.native.js @@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' ); * @param {PositiveInteger} N - number of indexed elements * @param {number} correction - degrees of freedom adjustment * @param {Float32Array} x - input array -* @param {integer} stride - stride length +* @param {integer} strideX - stride length * @returns {number} variance * * @example * var Float32Array = require( '@stdlib/array/float32' ); * * var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] ); -* var N = x.length; * -* var v = snanvariancepn( N, 1, x, 1 ); +* var v = snanvariancepn( x.length, 1, x, 1 ); * // returns ~4.3333 */ -function snanvariancepn( N, correction, x, stride ) { - return addon( N, correction, x, stride ); +function snanvariancepn( N, correction, x, strideX ) { + return addon( N, correction, x, strideX ); } diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/manifest.json b/lib/node_modules/@stdlib/stats/base/snanvariancepn/manifest.json index 9e968d3aa6ae..d849b5d496d9 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/manifest.json +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/manifest.json @@ -1,6 +1,7 @@ { "options": { - "task": "build" + "task": "build", + "wasm": false }, "fields": [ { @@ -27,17 +28,19 @@ "confs": [ { "task": "build", + "wasm": false, "src": [ - "./src/snanvariancepn.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", "@stdlib/napi/export", "@stdlib/napi/argv", "@stdlib/napi/argv-int64", @@ -48,31 +51,54 @@ }, { "task": "benchmark", + "wasm": false, "src": [ - "./src/snanvariancepn.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" - ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf" + ] }, { "task": "examples", + "wasm": false, "src": [ - "./src/snanvariancepn.c" + "./src/main.c" ], "include": [ "./include" ], - "libraries": [ - "-lm" + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" ], + "include": [ + "./include" + ], + "libraries": [], "libpath": [], - "dependencies": [] + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf" + ] } ] } diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/addon.c index 5d2c9e66be5b..6bd8b68d752a 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/addon.c +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/addon.c @@ -17,6 +17,7 @@ */ #include "stdlib/stats/base/snanvariancepn.h" +#include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" #include "stdlib/napi/argv_int64.h" @@ -35,11 +36,29 @@ static napi_value addon( 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, 3 ); STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); - STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 ); - STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 ); - STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvariancepn( N, correction, X, stride ), v ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanvariancepn)( N, correction, 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, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanvariancepn_ndarray)( N, correction, 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/snanvariancepn/src/snanvariancepn.c b/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/main.c similarity index 55% rename from lib/node_modules/@stdlib/stats/base/snanvariancepn/src/snanvariancepn.c rename to lib/node_modules/@stdlib/stats/base/snanvariancepn/src/main.c index a945022c2afb..526ddce88ecd 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/snanvariancepn.c +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/main.c @@ -17,7 +17,9 @@ */ #include "stdlib/stats/base/snanvariancepn.h" -#include +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/math/base/assert/is_nanf.h" +#include "stdlib/blas/base/shared.h" /** * Computes the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation. @@ -30,20 +32,19 @@ * * - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050). * -* @param N number of indexed elements -* @param W two-element output array -* @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 +* @param offsetX starting index +* @param n pointer +* @return output value */ -static void snansumpw( const int64_t N, double *W, const float *X, const int64_t stride ) { - int64_t ix; - float *xp1; - float *xp2; +static float snansumpw( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, CBLAS_INT *n ) { + CBLAS_INT ix; + CBLAS_INT M; + CBLAS_INT m; + CBLAS_INT i; float sum; - int64_t M; - int64_t n; - int64_t i; float s0; float s1; float s2; @@ -54,26 +55,28 @@ static void snansumpw( const int64_t N, double *W, const float *X, const int64_t float s7; float v; - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; + sum = 0.0f; + ix = offsetX; + if ( strideX == 0 ) { + if ( stdlib_base_is_nanf( X[ ix ] ) ) { + return sum; + } + sum = X[ ix ] * N; + *n += N; + return sum; } if ( N < 8 ) { // Use simple summation... sum = 0.0f; - n = 0; for ( i = 0; i < N; i++ ) { v = X[ ix ]; if ( v == v ) { - sum += X[ ix ]; - n += 1; + sum += v; + *n += 1; } - ix += stride; + ix += strideX; } - W[ 0 ] += (double)sum; - W[ 1 ] += (double)n; - return; + return sum; } // Blocksize for pairwise summation: 128 (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.) if ( N <= 128 ) { @@ -86,87 +89,76 @@ static void snansumpw( const int64_t N, double *W, const float *X, const int64_t s5 = 0.0f; s6 = 0.0f; s7 = 0.0f; - n = 0; M = N % 8; for ( i = 0; i < N-M; i += 8 ) { v = X[ ix ]; if ( v == v ) { s0 += v; - n += 1; + *n += 1; } - ix += stride; + ix += strideX; v = X[ ix ]; if ( v == v ) { s1 += v; - n += 1; + *n += 1; } - ix += stride; + ix += strideX; v = X[ ix ]; if ( v == v ) { s2 += v; - n += 1; + *n += 1; } - ix += stride; + ix += strideX; v = X[ ix ]; if ( v == v ) { s3 += v; - n += 1; + *n += 1; } - ix += stride; + ix += strideX; v = X[ ix ]; if ( v == v ) { s4 += v; - n += 1; + *n += 1; } - ix += stride; + ix += strideX; v = X[ ix ]; if ( v == v ) { s5 += v; - n += 1; + *n += 1; } - ix += stride; + ix += strideX; v = X[ ix ]; if ( v == v ) { s6 += v; - n += 1; + *n += 1; } - ix += stride; + ix += strideX; v = X[ ix ]; if ( v == v ) { s7 += v; - n += 1; + *n += 1; } - ix += stride; + ix += strideX; } // Pairwise sum the accumulators: - sum = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7)); + sum = ( (s0+s1) + (s2+s3) ) + ( (s4+s5) + (s6+s7) ); // Clean-up loop... for (; i < N; i++ ) { v = X[ ix ]; if ( v == v ) { sum += X[ ix ]; - n += 1; + *n += 1; } - ix += stride; + ix += strideX; } - W[ 0 ] += (double)sum; - W[ 1 ] += (double)n; - return; + return sum; } // Recurse by dividing by two, but avoiding non-multiples of unroll factor... - n = N / 2; - n -= n % 8; - if ( stride < 0 ) { - xp1 = (float *)X + ( (n-N)*stride ); - xp2 = (float *)X; - } else { - xp1 = (float *)X; - xp2 = (float *)X + ( n*stride ); - } - snansumpw( n, W, xp1, stride ); - snansumpw( N-n, W, xp2, stride ); + m = N / 2; + m -= m % 8; + return snansumpw( m, X, strideX, ix, n ) + snansumpw( N-m, X, strideX, ix+(m*strideX), n ); } /** @@ -181,21 +173,46 @@ static void snansumpw( const int64_t N, double *W, const float *X, const int64_t * - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). * - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). * -* @param N number of indexed elements -* @param correction degrees of freedom adjustment -* @param X input array -* @param stride stride length -* @return output value +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @return output value */ -float stdlib_strided_snanvariancepn( const int64_t N, const float correction, const float *X, const int64_t stride ) { - double W[] = { 0.0, 0.0 }; - int64_t ix; - int64_t i; +float API_SUFFIX(stdlib_strided_snanvariancepn)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox; + ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_snanvariancepn_ndarray)( N, correction, X, strideX, ox ); +} + +/** +* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics. +* +* ## Method +* +* - This implementation uses a two-pass approach, as suggested by Neely (1966). +* +* ## References +* +* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958). +* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036). +* +* @param N number of indexed elements +* @param correction degrees of freedom adjustment +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return output value +*/ +float API_SUFFIX(stdlib_strided_snanvariancepn_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + CBLAS_INT n; double nc; double dM; - double n; - float M2; + float sum; float mu; + float M2; float M; float d; float v; @@ -203,26 +220,22 @@ float stdlib_strided_snanvariancepn( const int64_t N, const float correction, co if ( N <= 0 ) { return 0.0f / 0.0f; // NaN } - if ( N == 1 || stride == 0 ) { - v = X[ 0 ]; + if ( N == 1 || strideX == 0 ) { + v = X[ offsetX ]; if ( v == v && (double)N-(double)correction > 0.0 ) { return 0.0f; } return 0.0f / 0.0f; // NaN } // Compute an estimate for the mean... - snansumpw( N, W, X, stride ); - n = W[ 1 ]; + n = 0; + sum = snansumpw( N, X, strideX, offsetX, &n ); nc = n - (double)correction; if ( nc <= 0.0 ) { return 0.0f / 0.0f; // NaN } - if ( stride < 0 ) { - ix = (1-N) * stride; - } else { - ix = 0; - } - mu = (float)( W[ 0 ] / n ); + ix = offsetX; + mu = (float)( (double)sum / (double)n ); // Compute the variance... M2 = 0.0f; @@ -233,9 +246,8 @@ float stdlib_strided_snanvariancepn( const int64_t N, const float correction, co d = v - mu; M2 += d * d; M += d; - n += 1; } - ix += stride; + ix += strideX; } dM = (double)M; return (float)((double)M2/nc) - ( (float)(dM/n) * (float)(dM/nc) ); diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.js index 18a9eaf4be87..ee221ba51392 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -214,7 +213,6 @@ 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 +229,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]); - N = floor( x.length / 2 ); - v = snanvariancepn( N, 1, x, 2, 0 ); + v = snanvariancepn( 5, 1, x, 2, 0 ); t.strictEqual( v, 6.25, '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 +252,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 4.0, // 0 2.0 ]); - N = floor( x.length / 2 ); - v = snanvariancepn( N, 1, x, -2, 8 ); + v = snanvariancepn( 5, 1, x, -2, 8 ); t.strictEqual( v, 6.25, 'returns expected value' ); x = new Float32Array( 1e3 ); @@ -294,7 +289,6 @@ 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; @@ -310,9 +304,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) { NaN, NaN // 4 ]); - N = floor( x.length / 2 ); - v = snanvariancepn( N, 1, x, 2, 1 ); + v = snanvariancepn( 5, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.native.js index 506ec9192f9e..f3cd0e840545 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/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 isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -223,7 +222,6 @@ tape( 'if provided a `correction` parameter yielding a correction term less than }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -240,15 +238,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { NaN ]); - N = floor( x.length / 2 ); - v = snanvariancepn( N, 1, x, 2, 0 ); + v = snanvariancepn( 5, 1, x, 2, 0 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; var i; @@ -265,9 +261,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 4.0, // 0 2.0 ]); - N = floor( x.length / 2 ); - v = snanvariancepn( N, 1, x, -2, 8 ); + v = snanvariancepn( 5, 1, x, -2, 8 ); t.strictEqual( v, 6.25, 'returns expected value' ); x = new Float32Array( 1e3 ); @@ -303,7 +298,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` p }); tape( 'the function supports an `offset` parameter', opts, function test( t ) { - var N; var x; var v; @@ -319,9 +313,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { NaN, NaN // 4 ]); - N = floor( x.length / 2 ); - v = snanvariancepn( N, 1, x, 2, 1 ); + v = snanvariancepn( 5, 1, x, 2, 1 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.js index 6b7588a79921..73ac03fc1657 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.js @@ -21,7 +21,6 @@ // MODULES // var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -214,7 +213,6 @@ 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 +229,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) { NaN ]); - N = floor( x.length / 2 ); - v = snanvariancepn( N, 1, x, 2 ); + v = snanvariancepn( 5, 1, x, 2 ); t.strictEqual( v, 6.25, '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 +252,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 4.0, // 0 2.0 ]); - N = floor( x.length / 2 ); - v = snanvariancepn( N, 1, x, -2 ); + v = snanvariancepn( 5, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); x = new Float32Array( 1e3 ); @@ -296,7 +291,6 @@ 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 Float32Array([ @@ -314,9 +308,8 @@ 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 = snanvariancepn( N, 1, x1, 2 ); + v = snanvariancepn( 5, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.native.js index db52ef0db2d0..91fb98216d57 100644 --- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.native.js +++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.native.js @@ -22,7 +22,6 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var floor = require( '@stdlib/math/base/special/floor' ); var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -223,7 +222,6 @@ tape( 'if provided a `correction` parameter yielding a correction term less than }); tape( 'the function supports a `stride` parameter', opts, function test( t ) { - var N; var x; var v; @@ -240,15 +238,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { NaN ]); - N = floor( x.length / 2 ); - v = snanvariancepn( N, 1, x, 2 ); + v = snanvariancepn( 5, 1, x, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end(); }); tape( 'the function supports a negative `stride` parameter', opts, function test( t ) { - var N; var x; var v; var i; @@ -265,9 +261,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 4.0, // 0 2.0 ]); - N = floor( x.length / 2 ); - v = snanvariancepn( N, 1, x, -2 ); + v = snanvariancepn( 5, 1, x, -2 ); t.strictEqual( v, 6.25, 'returns expected value' ); x = new Float32Array( 1e3 ); @@ -305,7 +300,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` p tape( 'the function supports view offsets', opts, function test( t ) { var x0; var x1; - var N; var v; x0 = new Float32Array([ @@ -323,9 +317,8 @@ 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 = snanvariancepn( N, 1, x1, 2 ); + v = snanvariancepn( 5, 1, x1, 2 ); t.strictEqual( v, 6.25, 'returns expected value' ); t.end();