diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/README.md index 8101cd54d391..88a2c7f940e4 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/README.md @@ -152,6 +152,229 @@ console.log( v.get().toString() ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/ndarray/sztest.h" +``` + +#### stdlib_stats_sztest( arrays ) + +Computes a one-sample Z-test for a one-dimensional single-precision floating-point ndarray. + +```c +#include "stdlib/stats/base/ztest/one-sample/results/float32.h" +#include "stdlib/stats/base/ztest/alternatives.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include + +// Create a one-dimensional input ndarray: +const float xbuf[] = { 1.0f, 3.0f, 4.0f, 2.0f }; +int64_t xshape[] = { 4 }; +int64_t xstrides[] = { STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; +int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; +struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)xbuf, 1, xshape, xstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Create a zero-dimensional output ndarray to hold the results (its buffer is written directly as a `stdlib_stats_ztest_one_sample_float32_results` struct): +uint8_t ybuf[ sizeof( struct stdlib_stats_ztest_one_sample_float32_results ) ]; +int64_t *zshape = NULL; +int64_t zstrides[] = { 0 }; +struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_UINT8, ybuf, 0, zshape, zstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 0, submodes ); + +// Create a zero-dimensional ndarray specifying the alternative hypothesis: +const int8_t altbuf[] = { STDLIB_STATS_ZTEST_TWO_SIDED }; +struct ndarray *alt = stdlib_ndarray_allocate( STDLIB_NDARRAY_INT8, (uint8_t *)altbuf, 0, zshape, zstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 0, submodes ); + +// Create a zero-dimensional ndarray specifying the significance level: +const float alphabuf[] = { 0.05f }; +struct ndarray *alpha = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)alphabuf, 0, zshape, zstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 0, submodes ); + +// Create a zero-dimensional ndarray specifying the mean under the null hypothesis: +const float mubuf[] = { 0.0f }; +struct ndarray *mu = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mubuf, 0, zshape, zstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 0, submodes ); + +// Create a zero-dimensional ndarray specifying the known standard deviation: +const float sigmabuf[] = { 1.0f }; +struct ndarray *sigma = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)sigmabuf, 0, zshape, zstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 0, submodes ); + +// Perform a Z-test: +const struct ndarray *arrays[] = { x, y, alt, alpha, mu, sigma }; +stdlib_stats_sztest( arrays ); + +// Interpret the output buffer as a results struct: +struct stdlib_stats_ztest_one_sample_float32_results *results = (struct stdlib_stats_ztest_one_sample_float32_results *)ybuf; +// results->rejected, results->statistic, results->pValue, etc. + +// Free allocated memory: +stdlib_ndarray_free( x ); +stdlib_ndarray_free( y ); +stdlib_ndarray_free( alt ); +stdlib_ndarray_free( alpha ); +stdlib_ndarray_free( mu ); +stdlib_ndarray_free( sigma ); +``` + +The function accepts the following arguments: + +- **arrays**: `[in] struct ndarray**` list containing, in order: a one-dimensional input ndarray; a zero-dimensional output ndarray whose underlying buffer is written with the test results as a `stdlib_stats_ztest_one_sample_float32_results` struct; a zero-dimensional ndarray (`int8`) specifying the alternative hypothesis; a zero-dimensional ndarray specifying the significance level; a zero-dimensional ndarray specifying the mean under the null hypothesis; and a zero-dimensional ndarray specifying the known standard deviation. + +```c +void stdlib_stats_sztest( const struct ndarray *arrays[] ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/ndarray/sztest.h" +#include "stdlib/stats/base/ztest/one-sample/results/float32.h" +#include "stdlib/stats/base/ztest/alternatives.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Create a one-dimensional input ndarray: + const float xbuf[] = { 1.0f, 3.0f, 4.0f, 2.0f, 5.0f, 3.0f, 6.0f, 2.0f }; + int64_t xshape[] = { 8 }; + int64_t xstrides[] = { STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)xbuf, 1, xshape, xstrides, 0, order, imode, 1, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a zero-dimensional output ndarray to hold the results: + uint8_t ybuf[ sizeof( struct stdlib_stats_ztest_one_sample_float32_results ) ]; + int64_t *yshape = NULL; + int64_t ystrides[] = { 0 }; + struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_UINT8, ybuf, 0, yshape, ystrides, 0, order, imode, 0, submodes ); + if ( y == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a zero-dimensional ndarray specifying the alternative hypothesis: + const int8_t altbuf[] = { STDLIB_STATS_ZTEST_TWO_SIDED }; + int64_t *altshape = NULL; + int64_t altstrides[] = { 0 }; + struct ndarray *alt = stdlib_ndarray_allocate( STDLIB_NDARRAY_INT8, (uint8_t *)altbuf, 0, altshape, altstrides, 0, order, imode, 0, submodes ); + if ( alt == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a zero-dimensional ndarray specifying the significance level: + const float alphabuf[] = { 0.05f }; + int64_t *alphashape = NULL; + int64_t alphastrides[] = { 0 }; + struct ndarray *alpha = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)alphabuf, 0, alphashape, alphastrides, 0, order, imode, 0, submodes ); + if ( alpha == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a zero-dimensional ndarray specifying the mean under the null hypothesis: + const float mubuf[] = { 0.0f }; + int64_t *mushape = NULL; + int64_t mustrides[] = { 0 }; + struct ndarray *mu = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mubuf, 0, mushape, mustrides, 0, order, imode, 0, submodes ); + if ( mu == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a zero-dimensional ndarray specifying the known standard deviation: + const float sigmabuf[] = { 1.0f }; + int64_t *sigmashape = NULL; + int64_t sigmastrides[] = { 0 }; + struct ndarray *sigma = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)sigmabuf, 0, sigmashape, sigmastrides, 0, order, imode, 0, submodes ); + if ( sigma == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x, y, alt, alpha, mu, sigma }; + + // Perform a Z-test: + stdlib_stats_sztest( arrays ); + + // Interpret the output buffer as a results struct: + struct stdlib_stats_ztest_one_sample_float32_results *results = (struct stdlib_stats_ztest_one_sample_float32_results *)ybuf; + + // Print the results: + printf( "rejected: %s\n", ( results->rejected ) ? "true" : "false" ); + printf( "statistic: %f\n", results->statistic ); + printf( "p-value: %f\n", results->pValue ); + printf( "ci: [%f, %f]\n", results->ci[ 0 ], results->ci[ 1 ] ); + + // Free allocated memory: + stdlib_ndarray_free( x ); + stdlib_ndarray_free( y ); + stdlib_ndarray_free( alt ); + stdlib_ndarray_free( alpha ); + stdlib_ndarray_free( mu ); + stdlib_ndarray_free( sigma ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/benchmark.native.js new file mode 100644 index 000000000000..13996f098f07 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/benchmark.native.js @@ -0,0 +1,129 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var normal = require( '@stdlib/random/normal' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var ndarray = require( '@stdlib/ndarray/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var Float32Results = require( '@stdlib/stats/base/ztest/one-sample/results/float32' ); +var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' ); +var structFactory = require( '@stdlib/array/struct-factory' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sztest = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( sztest instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; +var ResultsArray = structFactory( Float32Results ); + +var alt = scalar2ndarray( resolveEnum( 'two-sided' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 0.05, options ); +var mu = scalar2ndarray( 0.0, options ); +var sigma = scalar2ndarray( 1.0, options ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var obuf; + var out; + var x; + + x = normal( [ len ], 0.0, 1.0, options ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnanf( v.get().statistic ) || isnanf( v.get().pValue ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/c/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/c/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..02d19da35ca5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/benchmark/c/benchmark.length.c @@ -0,0 +1,205 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/sztest.h" +#include "stdlib/stats/base/ztest/one-sample/results/float32.h" +#include "stdlib/stats/base/ztest/alternatives.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include +#include +#include +#include + +#define NAME "sztest" +#define ITERATIONS 100000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0, 1). +* +* @return random number +*/ +static double rand_double( void ) { + return (double)rand() / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark( int iterations, int len ) { + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + uint8_t ybuf[ sizeof( struct stdlib_stats_ztest_one_sample_float32_results ) ]; + const int8_t altbuf[] = { STDLIB_STATS_ZTEST_TWO_SIDED }; + const float alphabuf[] = { 0.05f }; + const float mubuf[] = { 0.0f }; + const float sigmabuf[] = { 1.0f }; + int64_t *zshape = NULL; + int64_t zstrides[] = { 0 }; + int64_t xshape[ 1 ]; + int64_t xstrides[ 1 ]; + const struct ndarray *arrays[ 6 ]; + struct ndarray *x; + struct ndarray *y; + struct ndarray *alt; + struct ndarray *alpha; + struct ndarray *mu; + struct ndarray *sigma; + double elapsed; + float *data; + double t; + int i; + + xshape[ 0 ] = len; + xstrides[ 0 ] = STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT; + + data = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + data[ i ] = (float)( ( rand_double()*10.0 ) - 5.0 ); + } + // cppcheck-suppress invalidPointerCast + x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)data, 1, xshape, xstrides, 0, order, imode, 1, submodes ); + arrays[ 0 ] = x; + + // cppcheck-suppress invalidPointerCast + y = stdlib_ndarray_allocate( STDLIB_NDARRAY_UINT8, ybuf, 0, zshape, zstrides, 0, order, imode, 0, submodes ); + arrays[ 1 ] = y; + + // cppcheck-suppress invalidPointerCast + alt = stdlib_ndarray_allocate( STDLIB_NDARRAY_INT8, (uint8_t *)altbuf, 0, zshape, zstrides, 0, order, imode, 0, submodes ); + arrays[ 2 ] = alt; + + // cppcheck-suppress invalidPointerCast + alpha = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)alphabuf, 0, zshape, zstrides, 0, order, imode, 0, submodes ); + arrays[ 3 ] = alpha; + + // cppcheck-suppress invalidPointerCast + mu = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mubuf, 0, zshape, zstrides, 0, order, imode, 0, submodes ); + arrays[ 4 ] = mu; + + // cppcheck-suppress invalidPointerCast + sigma = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)sigmabuf, 0, zshape, zstrides, 0, order, imode, 0, submodes ); + arrays[ 5 ] = sigma; + + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_stats_sztest( arrays ); + } + elapsed = tic() - t; + + stdlib_ndarray_free( x ); + stdlib_ndarray_free( y ); + stdlib_ndarray_free( alt ); + stdlib_ndarray_free( alpha ); + stdlib_ndarray_free( mu ); + stdlib_ndarray_free( sigma ); + free( data ); + + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + 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:len=%d\n", NAME, len ); + elapsed = benchmark( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/binding.gyp b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/examples/c/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/examples/c/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/examples/c/example.c new file mode 100644 index 000000000000..abdf28c82e2a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/examples/c/example.c @@ -0,0 +1,131 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/sztest.h" +#include "stdlib/stats/base/ztest/one-sample/results/float32.h" +#include "stdlib/stats/base/ztest/alternatives.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/dtypes.h" +#include "stdlib/ndarray/index_modes.h" +#include "stdlib/ndarray/orders.h" +#include "stdlib/ndarray/base/bytes_per_element.h" +#include +#include +#include + +int main( void ) { + // Specify the index mode and subscript index modes (shared across all ndarrays): + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Create a one-dimensional input ndarray: + const float xbuf[] = { 1.0f, 3.0f, 4.0f, 2.0f, 5.0f, 3.0f, 6.0f, 2.0f }; + int64_t xshape[] = { 8 }; + int64_t xstrides[] = { STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; + + // cppcheck-suppress invalidPointerCast + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)xbuf, 1, xshape, xstrides, 0, order, imode, 1, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a zero-dimensional output ndarray to store the test results (tagged as raw bytes; the C API writes directly into its buffer as a `stdlib_stats_ztest_one_sample_float32_results` struct): + uint8_t ybuf[ sizeof( struct stdlib_stats_ztest_one_sample_float32_results ) ]; + int64_t *yshape = NULL; + int64_t ystrides[] = { 0 }; + + // cppcheck-suppress invalidPointerCast + struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_UINT8, ybuf, 0, yshape, ystrides, 0, order, imode, 0, submodes ); + if ( y == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a zero-dimensional ndarray specifying the alternative hypothesis: + const int8_t altbuf[] = { STDLIB_STATS_ZTEST_TWO_SIDED }; + int64_t *altshape = NULL; + int64_t altstrides[] = { 0 }; + + // cppcheck-suppress invalidPointerCast + struct ndarray *alt = stdlib_ndarray_allocate( STDLIB_NDARRAY_INT8, (uint8_t *)altbuf, 0, altshape, altstrides, 0, order, imode, 0, submodes ); + if ( alt == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a zero-dimensional ndarray specifying the significance level: + const float alphabuf[] = { 0.05f }; + int64_t *alphashape = NULL; + int64_t alphastrides[] = { 0 }; + + // cppcheck-suppress invalidPointerCast + struct ndarray *alpha = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)alphabuf, 0, alphashape, alphastrides, 0, order, imode, 0, submodes ); + if ( alpha == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a zero-dimensional ndarray specifying the mean under the null hypothesis: + const float mubuf[] = { 0.0f }; + int64_t *mushape = NULL; + int64_t mustrides[] = { 0 }; + + // cppcheck-suppress invalidPointerCast + struct ndarray *mu = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mubuf, 0, mushape, mustrides, 0, order, imode, 0, submodes ); + if ( mu == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a zero-dimensional ndarray specifying the known standard deviation: + const float sigmabuf[] = { 1.0f }; + int64_t *sigmashape = NULL; + int64_t sigmastrides[] = { 0 }; + + // cppcheck-suppress invalidPointerCast + struct ndarray *sigma = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)sigmabuf, 0, sigmashape, sigmastrides, 0, order, imode, 0, submodes ); + if ( sigma == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x, y, alt, alpha, mu, sigma }; + + // Perform a Z-test: + stdlib_stats_sztest( arrays ); + + // Interpret the output buffer as a results struct: + struct stdlib_stats_ztest_one_sample_float32_results *results = (struct stdlib_stats_ztest_one_sample_float32_results *)ybuf; + + // Print the results: + printf( "rejected: %s\n", ( results->rejected ) ? "true" : "false" ); + printf( "statistic: %f\n", results->statistic ); + printf( "p-value: %f\n", results->pValue ); + printf( "ci: [%f, %f]\n", results->ci[ 0 ], results->ci[ 1 ] ); + + // Free allocated memory: + stdlib_ndarray_free( x ); + stdlib_ndarray_free( y ); + stdlib_ndarray_free( alt ); + stdlib_ndarray_free( alpha ); + stdlib_ndarray_free( mu ); + stdlib_ndarray_free( sigma ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/include.gypi b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '} arrays - array-like object containing ndarrays +* @returns {ndarrayLike} output ndarray +* +* @example +* var Float32Results = require( '@stdlib/stats/base/ztest/one-sample/results/float32' ); +* var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' ); +* var structFactory = require( '@stdlib/array/struct-factory' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* +* var opts = { +* 'dtype': 'float32' +* }; +* +* var x = new Float32Vector( [ 1.0, 3.0, 4.0, 2.0 ] ); +* +* var alt = scalar2ndarray( resolveEnum( 'two-sided' ), { +* 'dtype': 'int8' +* }); +* +* var alpha = scalar2ndarray( 0.05, opts ); +* var mu = scalar2ndarray( 0.0, opts ); +* var sigma = scalar2ndarray( 1.0, opts ); +* +* var ResultsArray = structFactory( Float32Results ); +* var out = new ndarray( Float32Results, new ResultsArray( 1 ), [], [ 0 ], 0, 'row-major' ); +* +* var v = sztest( [ x, out, alt, alpha, mu, sigma ] ); +* // returns +* +* console.log( v.get().toString() ); +*/ +function sztest( arrays ) { + var sigma = arrays[ 5 ]; + var alpha = arrays[ 3 ]; + var alt = arrays[ 2 ]; + var mu = arrays[ 4 ]; + var x = arrays[ 0 ]; + var y = arrays[ 1 ]; + + addon( getData( x ), serialize( x ), getData( y ), serialize( y ), getData( alt ), serialize( alt ), getData( alpha ), serialize( alpha ), getData( mu ), serialize( mu ), getData( sigma ), serialize( sigma ) ); // eslint-disable-line max-len + + return y; +} + + +// EXPORTS // + +module.exports = sztest; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/manifest.json b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/manifest.json new file mode 100644 index 000000000000..f609eb0c98f9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/manifest.json @@ -0,0 +1,117 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/sztest", + "@stdlib/stats/base/ztest/one-sample/results/float32", + "@stdlib/stats/base/ztest/alternatives", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/base/napi/addon-arguments", + "@stdlib/napi/export", + "@stdlib/napi/argv" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/sztest", + "@stdlib/stats/base/ztest/one-sample/results/float32", + "@stdlib/stats/base/ztest/alternatives", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/sztest", + "@stdlib/stats/base/ztest/one-sample/results/float32", + "@stdlib/stats/base/ztest/alternatives", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/dtypes", + "@stdlib/ndarray/index-modes", + "@stdlib/ndarray/orders", + "@stdlib/ndarray/base/bytes-per-element" + ] + }, + { + "task": "", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/sztest", + "@stdlib/stats/base/ztest/one-sample/results/float32", + "@stdlib/stats/base/ztest/alternatives", + "@stdlib/ndarray/ctor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/package.json index 955deda79ff6..fbc1d92238ff 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/package.json @@ -14,11 +14,15 @@ } ], "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/src/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/src/addon.c b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/src/addon.c new file mode 100644 index 000000000000..1471b3c32a1f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/src/addon.c @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/sztest.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/ndarray/base/napi/addon_arguments.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include +#include + +/** +* Receives JavaScript callback invocation data. +* +* ## Notes +* +* - Each of the six input ndarrays is serialized on the JavaScript side into two raw arguments (its underlying data buffer and its serialized metadata), for a total of twelve raw arguments. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 12 ); + + // Process provided arguments: + struct ndarray *arrays[ 6 ]; + napi_value err; + napi_status status = stdlib_ndarray_napi_addon_arguments( env, argv, 12, 6, arrays, &err ); + assert( status == napi_ok ); + if ( err != NULL ) { + status = napi_throw( env, err ); + assert( status == napi_ok ); + return NULL; + } + // Create a const-qualified view of the argument pointer list: + const struct ndarray *arr[ 6 ] = { + arrays[ 0 ], + arrays[ 1 ], + arrays[ 2 ], + arrays[ 3 ], + arrays[ 4 ], + arrays[ 5 ] + }; + // Perform computation, writing results into the output (second) ndarray's underlying buffer: + stdlib_stats_sztest( arr ); + + // Free allocated memory: + stdlib_ndarray_free( arrays[ 0 ] ); + arrays[ 0 ] = NULL; + + stdlib_ndarray_free( arrays[ 1 ] ); + arrays[ 1 ] = NULL; + + stdlib_ndarray_free( arrays[ 2 ] ); + arrays[ 2 ] = NULL; + + stdlib_ndarray_free( arrays[ 3 ] ); + arrays[ 3 ] = NULL; + + stdlib_ndarray_free( arrays[ 4 ] ); + arrays[ 4 ] = NULL; + + stdlib_ndarray_free( arrays[ 5 ] ); + arrays[ 5 ] = NULL; + + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/src/main.c b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/src/main.c new file mode 100644 index 000000000000..4e844079ab39 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/src/main.c @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/ndarray/sztest.h" +#include "stdlib/stats/strided/sztest.h" +#include "stdlib/stats/base/ztest/one-sample/results/float32.h" +#include "stdlib/stats/base/ztest/alternatives.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes a one-sample Z-test for a one-dimensional single-precision floating-point ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional output ndarray whose underlying buffer is written with the test results (see `stdlib_stats_ztest_one_sample_float32_results`). +* - a zero-dimensional ndarray specifying the alternative hypothesis (as an `int8` value corresponding to `STDLIB_STATS_ZTEST_ALTERNATIVE`). +* - a zero-dimensional ndarray specifying the significance level. +* - a zero-dimensional ndarray specifying the mean under the null hypothesis. +* - a zero-dimensional ndarray specifying the known standard deviation. +* +* @param arrays list containing ndarrays +*/ +void stdlib_stats_sztest( const struct ndarray *arrays[] ) { + const struct ndarray *x = arrays[ 0 ]; + struct stdlib_stats_ztest_one_sample_float32_results *results; + int8_t alternative; + float alpha; + float mu; + float sigma; + + stdlib_ndarray_get_int8( arrays[ 2 ], NULL, &alternative ); + stdlib_ndarray_get_float32( arrays[ 3 ], NULL, &alpha ); + stdlib_ndarray_get_float32( arrays[ 4 ], NULL, &mu ); + stdlib_ndarray_get_float32( arrays[ 5 ], NULL, &sigma ); + + // Resolve a pointer to the output ndarray's sole (zero-dimensional) element, correctly accounting for the ndarray's byte offset: + results = (struct stdlib_stats_ztest_one_sample_float32_results *)stdlib_ndarray_get_ptr( arrays[ 1 ], NULL ); + + API_SUFFIX(stdlib_strided_sztest_ndarray)( stdlib_ndarray_dimension( x, 0 ), (enum STDLIB_STATS_ZTEST_ALTERNATIVE)alternative, alpha, mu, sigma, (const float *)stdlib_ndarray_data( x ), stdlib_ndarray_stride_elements( x, 0 ), stdlib_ndarray_offset_elements( x ), results ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/test/test.main.js b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/test/test.main.js new file mode 100644 index 000000000000..1b5c832ba825 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/test/test.main.js @@ -0,0 +1,298 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Results = require( '@stdlib/stats/base/ztest/one-sample/results/float32' ); +var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' ); +var structFactory = require( '@stdlib/array/struct-factory' ); +var normal = require( '@stdlib/random/strided/normal' ).ndarray; +var zeros = require( '@stdlib/array/zeros' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var sztest = require( './../lib/main.js' ); + + +// VARIABLES // + +var ResultsArray = structFactory( Float32Results ); +var RANDOM_OPTS = { + 'seed': 12345 +}; + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float32Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sztest, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( sztest.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs a Z-test over a one-dimensional ndarray (two-sided)', function test( t ) { + var alpha; + var sigma; + var opts; + var xbuf; + var obuf; + var alt; + var out; + var mu; + var x; + var v; + + alt = scalar2ndarray( resolveEnum( 'two-sided' ), { + 'dtype': 'int8' + }); + + opts = { + 'dtype': 'float32' + }; + alpha = scalar2ndarray( 0.05, opts ); + mu = scalar2ndarray( 0.0, opts ); + sigma = scalar2ndarray( 1.0, opts ); + + // Generate a large enough array to effectively guarantee results... + xbuf = zeros( 10000, opts.dtype ); + normal( xbuf.length, [ 0.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + x = vector( xbuf, xbuf.length, 1, 0 ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, false, 'returns expected value' ); + + normal( xbuf.length, [ 1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + normal( xbuf.length, [ -1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a Z-test over a one-dimensional ndarray (less)', function test( t ) { + var alpha; + var sigma; + var opts; + var xbuf; + var obuf; + var alt; + var out; + var mu; + var x; + var v; + + alt = scalar2ndarray( resolveEnum( 'less' ), { + 'dtype': 'int8' + }); + + opts = { + 'dtype': 'float32' + }; + alpha = scalar2ndarray( 0.05, opts ); + mu = scalar2ndarray( 0.0, opts ); + sigma = scalar2ndarray( 1.0, opts ); + + // Generate a large enough array to effectively guarantee results... + xbuf = zeros( 10000, opts.dtype ); + normal( xbuf.length, [ -1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + x = vector( xbuf, xbuf.length, 1, 0 ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + normal( xbuf.length, [ 1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a Z-test over a one-dimensional ndarray (greater)', function test( t ) { + var alpha; + var sigma; + var opts; + var xbuf; + var obuf; + var alt; + var out; + var mu; + var x; + var v; + + alt = scalar2ndarray( resolveEnum( 'greater' ), { + 'dtype': 'int8' + }); + + opts = { + 'dtype': 'float32' + }; + alpha = scalar2ndarray( 0.05, opts ); + mu = scalar2ndarray( 0.0, opts ); + sigma = scalar2ndarray( 1.0, opts ); + + // Generate a large enough array to effectively guarantee results... + xbuf = zeros( 10000, opts.dtype ); + normal( xbuf.length, [ -1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + x = vector( xbuf, xbuf.length, 1, 0 ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, false, 'returns expected value' ); + + normal( xbuf.length, [ 1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var alpha; + var sigma; + var opts; + var xbuf; + var obuf; + var alt; + var out; + var mu; + var x; + var v; + + alt = scalar2ndarray( resolveEnum( 'two-sided' ), { + 'dtype': 'int8' + }); + + opts = { + 'dtype': 'float32' + }; + alpha = scalar2ndarray( 0.05, opts ); + mu = scalar2ndarray( 0.0, opts ); + sigma = scalar2ndarray( 1.0, opts ); + + // Generate a large enough array to effectively guarantee results... + xbuf = zeros( 10000, opts.dtype ); + normal( 5000, [ 0.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 2, 0, RANDOM_OPTS ); + x = vector( xbuf, 5000, 2, 0 ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, false, 'returns expected value' ); + + normal( 5000, [ 1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 2, 0, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var alpha; + var sigma; + var opts; + var xbuf; + var obuf; + var alt; + var out; + var mu; + var x; + var v; + + alt = scalar2ndarray( resolveEnum( 'two-sided' ), { + 'dtype': 'int8' + }); + + opts = { + 'dtype': 'float32' + }; + alpha = scalar2ndarray( 0.05, opts ); + mu = scalar2ndarray( 0.0, opts ); + sigma = scalar2ndarray( 1.0, opts ); + + // Generate a large enough array to effectively guarantee results... + xbuf = zeros( 10000, opts.dtype ); + normal( 5000, [ 0.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 5000, RANDOM_OPTS ); + x = vector( xbuf, 5000, 1, 5000 ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, false, 'returns expected value' ); + + normal( 5000, [ 1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 5000, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/test/test.native.js b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/test/test.native.js new file mode 100644 index 000000000000..1a99f177138c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/test/test.native.js @@ -0,0 +1,303 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Results = require( '@stdlib/stats/base/ztest/one-sample/results/float32' ); +var resolveEnum = require( '@stdlib/stats/base/ztest/alternative-resolve-enum' ); +var structFactory = require( '@stdlib/array/struct-factory' ); +var normal = require( '@stdlib/random/strided/normal' ).ndarray; +var zeros = require( '@stdlib/array/zeros' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sztest = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( sztest instanceof Error ) +}; +var ResultsArray = structFactory( Float32Results ); +var RANDOM_OPTS = { + 'seed': 12345 +}; + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float32Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sztest, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', opts, function test( t ) { + t.strictEqual( sztest.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs a Z-test over a one-dimensional ndarray (two-sided)', opts, function test( t ) { + var alpha; + var sigma; + var optsD; + var xbuf; + var obuf; + var alt; + var out; + var mu; + var x; + var v; + + alt = scalar2ndarray( resolveEnum( 'two-sided' ), { + 'dtype': 'int8' + }); + + optsD = { + 'dtype': 'float32' + }; + alpha = scalar2ndarray( 0.05, optsD ); + mu = scalar2ndarray( 0.0, optsD ); + sigma = scalar2ndarray( 1.0, optsD ); + + // Generate a large enough array to effectively guarantee results... + xbuf = zeros( 10000, optsD.dtype ); + normal( xbuf.length, [ 0.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + x = vector( xbuf, xbuf.length, 1, 0 ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, false, 'returns expected value' ); + + normal( xbuf.length, [ 1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + normal( xbuf.length, [ -1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a Z-test over a one-dimensional ndarray (less)', opts, function test( t ) { + var alpha; + var sigma; + var optsD; + var xbuf; + var obuf; + var alt; + var out; + var mu; + var x; + var v; + + alt = scalar2ndarray( resolveEnum( 'less' ), { + 'dtype': 'int8' + }); + + optsD = { + 'dtype': 'float32' + }; + alpha = scalar2ndarray( 0.05, optsD ); + mu = scalar2ndarray( 0.0, optsD ); + sigma = scalar2ndarray( 1.0, optsD ); + + // Generate a large enough array to effectively guarantee results... + xbuf = zeros( 10000, optsD.dtype ); + normal( xbuf.length, [ -1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + x = vector( xbuf, xbuf.length, 1, 0 ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + normal( xbuf.length, [ 1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a Z-test over a one-dimensional ndarray (greater)', opts, function test( t ) { + var alpha; + var sigma; + var optsD; + var xbuf; + var obuf; + var alt; + var out; + var mu; + var x; + var v; + + alt = scalar2ndarray( resolveEnum( 'greater' ), { + 'dtype': 'int8' + }); + + optsD = { + 'dtype': 'float32' + }; + alpha = scalar2ndarray( 0.05, optsD ); + mu = scalar2ndarray( 0.0, optsD ); + sigma = scalar2ndarray( 1.0, optsD ); + + // Generate a large enough array to effectively guarantee results... + xbuf = zeros( 10000, optsD.dtype ); + normal( xbuf.length, [ -1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + x = vector( xbuf, xbuf.length, 1, 0 ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, false, 'returns expected value' ); + + normal( xbuf.length, [ 1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 0, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', opts, function test( t ) { + var alpha; + var sigma; + var optsD; + var xbuf; + var obuf; + var alt; + var out; + var mu; + var x; + var v; + + alt = scalar2ndarray( resolveEnum( 'two-sided' ), { + 'dtype': 'int8' + }); + + optsD = { + 'dtype': 'float32' + }; + alpha = scalar2ndarray( 0.05, optsD ); + mu = scalar2ndarray( 0.0, optsD ); + sigma = scalar2ndarray( 1.0, optsD ); + + // Generate a large enough array to effectively guarantee results... + xbuf = zeros( 10000, optsD.dtype ); + normal( 5000, [ 0.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 2, 0, RANDOM_OPTS ); + x = vector( xbuf, 5000, 2, 0 ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, false, 'returns expected value' ); + + normal( 5000, [ 1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 2, 0, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', opts, function test( t ) { + var alpha; + var sigma; + var optsD; + var xbuf; + var obuf; + var alt; + var out; + var mu; + var x; + var v; + + alt = scalar2ndarray( resolveEnum( 'two-sided' ), { + 'dtype': 'int8' + }); + + optsD = { + 'dtype': 'float32' + }; + alpha = scalar2ndarray( 0.05, optsD ); + mu = scalar2ndarray( 0.0, optsD ); + sigma = scalar2ndarray( 1.0, optsD ); + + // Generate a large enough array to effectively guarantee results... + xbuf = zeros( 10000, optsD.dtype ); + normal( 5000, [ 0.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 5000, RANDOM_OPTS ); + x = vector( xbuf, 5000, 1, 5000 ); + + obuf = new ResultsArray( 1 ); + out = new ndarray( Float32Results, obuf, [], [ 0 ], 0, 'row-major' ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, false, 'returns expected value' ); + + normal( 5000, [ 1000.0 ], 0, 0, [ 1.0 ], 0, 0, xbuf, 1, 5000, RANDOM_OPTS ); + + v = sztest( [ x, out, alt, alpha, mu, sigma ] ); + t.strictEqual( v, out, 'returns expected value' ); + t.strictEqual( out.get().rejected, true, 'returns expected value' ); + + t.end(); +});