From 7c14b5f21c98052f18222849b1abe39ab4f17845 Mon Sep 17 00:00:00 2001 From: Mayur Jogade Date: Tue, 15 Sep 2026 18:42:12 +0530 Subject: [PATCH 1/2] feat: add C implementation for `stats/base/ndarray/scovarmtk` Ref: https://github.com/stdlib-js/stdlib/issues/14034 --- type: pre_commit_static_analysis_report description: Results of running static analysis checks when committing changes. report: - task: lint_filenames status: passed - task: lint_editorconfig status: passed - task: lint_markdown_pkg_readmes status: passed - task: lint_markdown_docs status: na - task: lint_markdown status: na - task: lint_package_json status: passed - task: lint_repl_help status: na - task: lint_javascript_src status: passed - task: lint_javascript_cli status: na - task: lint_javascript_examples status: na - task: lint_javascript_tests status: passed - task: lint_javascript_benchmarks status: passed - task: lint_python status: na - task: lint_r status: na - task: lint_c_src status: missing_dependencies - task: lint_c_examples status: missing_dependencies - task: lint_c_benchmarks status: missing_dependencies - task: lint_c_tests_fixtures status: na - task: lint_shell status: na - task: lint_typescript_declarations status: passed - task: lint_typescript_tests status: na - task: lint_license_headers status: passed --- --- .../stats/base/ndarray/scovarmtk/README.md | 213 ++++++++++++++ .../ndarray/scovarmtk/benchmark/benchmark.js | 2 +- .../scovarmtk/benchmark/benchmark.native.js | 114 ++++++++ .../ndarray/scovarmtk/benchmark/c/Makefile | 146 ++++++++++ .../scovarmtk/benchmark/c/benchmark.length.c | 228 +++++++++++++++ .../stats/base/ndarray/scovarmtk/binding.gyp | 170 +++++++++++ .../ndarray/scovarmtk/examples/c/Makefile | 146 ++++++++++ .../ndarray/scovarmtk/examples/c/example.c | 121 ++++++++ .../stats/base/ndarray/scovarmtk/include.gypi | 53 ++++ .../stdlib/stats/base/ndarray/scovarmtk.h | 40 +++ .../stats/base/ndarray/scovarmtk/lib/index.js | 16 +- .../base/ndarray/scovarmtk/lib/native.js | 84 ++++++ .../base/ndarray/scovarmtk/manifest.json | 110 +++++++ .../stats/base/ndarray/scovarmtk/package.json | 4 + .../stats/base/ndarray/scovarmtk/src/Makefile | 70 +++++ .../stats/base/ndarray/scovarmtk/src/addon.c | 74 +++++ .../stats/base/ndarray/scovarmtk/src/main.c | 52 ++++ .../stats/base/ndarray/scovarmtk/test/test.js | 238 ++-------------- .../base/ndarray/scovarmtk/test/test.main.js | 263 +++++++++++++++++ .../ndarray/scovarmtk/test/test.native.js | 268 ++++++++++++++++++ 20 files changed, 2198 insertions(+), 214 deletions(-) create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.native.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/c/Makefile create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/c/benchmark.length.c create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/binding.gyp create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/examples/c/Makefile create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/examples/c/example.c create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/include.gypi create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/include/stdlib/stats/base/ndarray/scovarmtk.h create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/lib/native.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/manifest.json create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/src/Makefile create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/src/addon.c create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/src/main.c create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.main.js create mode 100644 lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.native.js diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/README.md index dbe0cdd9c9dc..78e480192f76 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/README.md +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/README.md @@ -186,6 +186,219 @@ console.log( v ); + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/ndarray/scovarmtk.h" +``` + +#### stdlib_stats_scovarmtk( arrays ) + +Computes the covariance of two one-dimensional single-precision floating-point ndarrays provided known means and using a one-pass textbook algorithm. + +```c +#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 input ndarrays: +const float xdata[] = { 1.0f, -2.0f, 2.0f }; +const float ydata[] = { 2.0f, -2.0f, 1.0f }; +int64_t shape[] = { 3 }; +int64_t strides[] = { STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; +int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + +struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)xdata, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); +struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)ydata, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Create an ndarray for specifying the degrees of freedom adjustment: +const float cdata[] = { 1.0f }; +int64_t cstrides[] = { 0 }; +struct ndarray *corr = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)cdata, 0, NULL, cstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Create ndarrays for specifying the known means: +const float mxdata[] = { 1.0f/3.0f }; +const float mydata[] = { 1.0f/3.0f }; +struct ndarray *meanx = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mxdata, 0, NULL, cstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); +struct ndarray *meany = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mydata, 0, NULL, cstrides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); + +// Compute the result: +const struct ndarray *arrays[] = { x, y, corr, meanx, meany }; +float v = stdlib_stats_scovarmtk( arrays ); +// returns ~3.8333f + +// Free allocated memory: +stdlib_ndarray_free( x ); +stdlib_ndarray_free( y ); +stdlib_ndarray_free( corr ); +stdlib_ndarray_free( meanx ); +stdlib_ndarray_free( meany ); +``` + +The function accepts the following arguments: + +- **arrays**: `[in] struct ndarray**` list containing the following ndarrays: + + - `[in] struct ndarray*` first one-dimensional input ndarray. + - `[in] struct ndarray*` second one-dimensional input ndarray. + - `[in] struct ndarray*` a zero-dimensional ndarray specifying the 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 [covariance][covariance] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment and `N` corresponds to the number of elements in each input ndarray. When computing the population [covariance][covariance], setting this parameter to `0` is the standard choice (i.e., the provided arrays contain data constituting entire populations). When computing the unbiased sample [covariance][covariance], setting this parameter to `1` is the standard choice (i.e., the provided arrays contain data sampled from larger populations; this is commonly referred to as Bessel's correction). + - `[in] struct ndarray*` a zero-dimensional ndarray specifying the mean of the first one-dimensional ndarray. + - `[in] struct ndarray*` a zero-dimensional ndarray specifying the mean of the second one-dimensional ndarray. + +```c +float stdlib_stats_scovarmtk( const struct ndarray *arrays[] ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/ndarray/scovarmtk.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 ) { + // Create data buffers: + const float xdata[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + const float ydata[] = { 2.0f, -1.0f, 1.0f, -3.0f, 3.0f, -5.0f, 5.0f, -7.0f }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2 * STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create the first input ndarray: + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)xdata, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create the second input ndarray: + struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)ydata, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( y == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a data buffer for an ndarray specifying the degrees of freedom adjustment: + const float cdata[] = { 1.0f }; + + // Create data buffers for ndarrays specifying the means of the input ndarrays: + const float mxdata[] = { 4.0f }; + const float mydata[] = { 2.75f }; + + // Specify the array strides for zero-dimensional ndarrays: + int64_t cstrides[] = { 0 }; + + // Create an ndarray for the degrees of freedom adjustment: + struct ndarray *corr = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)cdata, 0, NULL, cstrides, 0, order, imode, nsubmodes, submodes ); + if ( corr == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create an ndarray for the mean of the first input ndarray: + struct ndarray *meanx = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mxdata, 0, NULL, cstrides, 0, order, imode, nsubmodes, submodes ); + if ( meanx == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create an ndarray for the mean of the second input ndarray: + struct ndarray *meany = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mydata, 0, NULL, cstrides, 0, order, imode, nsubmodes, submodes ); + if ( meany == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x, y, corr, meanx, meany }; + + // Compute the result: + float v = stdlib_stats_scovarmtk( arrays ); + + // Print the result: + printf( "result: %f\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); + stdlib_ndarray_free( y ); + stdlib_ndarray_free( corr ); + stdlib_ndarray_free( meanx ); + stdlib_ndarray_free( meany ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.js index 6ac6b03f6a65..4962131f6a63 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.js @@ -27,7 +27,7 @@ var pow = require( '@stdlib/math/base/special/pow' ); var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var scovarmtk = require( './../lib' ); +var scovarmtk = require( './../lib/main.js' ); // VARIABLES // diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.native.js new file mode 100644 index 000000000000..6ee1976d22ce --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/benchmark.native.js @@ -0,0 +1,114 @@ +/** +* @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 uniform = require( '@stdlib/random/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var scovarmtk = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( scovarmtk instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + +var correction = scalar2ndarray( 1.0, options ); +var meanx = scalar2ndarray( 0.0, options ); +var meany = scalar2ndarray( 0.0, options ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( [ len ], -10.0, 10.0, options ); + var y = uniform( [ len ], -10.0, 10.0, options ); + 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 = scovarmtk( [ x, y, correction, meanx, meany ] ); + if ( isnanf( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( v ) ) { + 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/scovarmtk/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @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 + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..0507a5fa6bb8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/benchmark/c/benchmark.length.c @@ -0,0 +1,228 @@ +/** +* @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/scovarmtk.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 "scovarmtk" +#define ITERATIONS 1000000 +#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 float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark( int iterations, int len ) { + enum STDLIB_NDARRAY_INDEX_MODE imode; + const struct ndarray *arrays[ 5 ]; + enum STDLIB_NDARRAY_ORDER order; + struct ndarray *correction; + struct ndarray *meanx; + struct ndarray *meany; + int64_t cstrides[ 1 ]; + int8_t submodes[ 1 ]; + int64_t strides[ 1 ]; + int64_t shape[ 1 ]; + float mxdata[ 1 ]; + float mydata[ 1 ]; + int64_t nsubmodes; + struct ndarray *x; + struct ndarray *y; + float cdata[ 1 ]; + int64_t offset; + double elapsed; + int64_t ndims; + float *xdata; + float *ydata; + double t; + float v; + int i; + + ndims = 1; + shape[ 0 ] = len; + strides[ 0 ] = STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT; + offset = 0; + order = STDLIB_NDARRAY_ROW_MAJOR; + imode = STDLIB_NDARRAY_INDEX_ERROR; + submodes[ 0 ] = imode; + nsubmodes = 1; + + xdata = (float *)malloc( len * sizeof( float ) ); + ydata = (float *)malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + xdata[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + ydata[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + // cppcheck-suppress invalidPointerCast + x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)xdata, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + + // cppcheck-suppress invalidPointerCast + y = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)ydata, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + + ndims = 0; + cstrides[ 0 ] = 0; + + cdata[ 0 ] = 1.0f; + // cppcheck-suppress invalidPointerCast + correction = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)cdata, ndims, NULL, cstrides, offset, order, imode, nsubmodes, submodes ); + + mxdata[ 0 ] = 0.0f; + // cppcheck-suppress invalidPointerCast + meanx = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mxdata, ndims, NULL, cstrides, offset, order, imode, nsubmodes, submodes ); + + mydata[ 0 ] = 0.0f; + // cppcheck-suppress invalidPointerCast + meany = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mydata, ndims, NULL, cstrides, offset, order, imode, nsubmodes, submodes ); + + arrays[ 0 ] = x; + arrays[ 1 ] = y; + arrays[ 2 ] = correction; + arrays[ 3 ] = meanx; + arrays[ 4 ] = meany; + + v = 0.0f; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + v = stdlib_stats_scovarmtk( arrays ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + stdlib_ndarray_free( x ); + stdlib_ndarray_free( y ); + stdlib_ndarray_free( correction ); + stdlib_ndarray_free( meanx ); + stdlib_ndarray_free( meany ); + free( xdata ); + free( ydata ); + arrays[ 0 ] = NULL; + arrays[ 1 ] = NULL; + arrays[ 2 ] = NULL; + arrays[ 3 ] = NULL; + arrays[ 4 ] = NULL; + + 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/scovarmtk/binding.gyp b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/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/scovarmtk/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @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 + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/examples/c/example.c new file mode 100644 index 000000000000..d9b5565a7093 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/examples/c/example.c @@ -0,0 +1,121 @@ +/** +* @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/scovarmtk.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 ) { + // Create data buffers: + const float xdata[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + const float ydata[] = { 2.0f, -1.0f, 1.0f, -3.0f, 3.0f, -5.0f, 5.0f, -7.0f }; + + // Specify the number of array dimensions: + const int64_t ndims = 1; + + // Specify the array shape: + int64_t shape[] = { 4 }; + + // Specify the array strides: + int64_t strides[] = { 2 * STDLIB_NDARRAY_FLOAT32_BYTES_PER_ELEMENT }; + + // Specify the byte offset: + const int64_t offset = 0; + + // Specify the array order: + const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; + + // Specify the index mode: + const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; + + // Specify the subscript index modes: + int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; + const int64_t nsubmodes = 1; + + // Create the first input ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)xdata, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( x == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create the second input ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *y = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)ydata, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); + if ( y == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create a data buffer for an ndarray specifying the degrees of freedom adjustment: + const float cdata[] = { 1.0f }; + + // Create data buffers for ndarrays specifying the means of the input ndarrays: + const float mxdata[] = { 4.0f }; + const float mydata[] = { 2.75f }; + + // Specify the array strides for zero-dimensional ndarrays: + int64_t cstrides[] = { 0 }; + + // Create an ndarray for the degrees of freedom adjustment: + // cppcheck-suppress invalidPointerCast + struct ndarray *corr = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)cdata, 0, NULL, cstrides, 0, order, imode, nsubmodes, submodes ); + if ( corr == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create an ndarray for the mean of the first input ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *meanx = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mxdata, 0, NULL, cstrides, 0, order, imode, nsubmodes, submodes ); + if ( meanx == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Create an ndarray for the mean of the second input ndarray: + // cppcheck-suppress invalidPointerCast + struct ndarray *meany = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)mydata, 0, NULL, cstrides, 0, order, imode, nsubmodes, submodes ); + if ( meany == NULL ) { + fprintf( stderr, "Error allocating memory.\n" ); + exit( 1 ); + } + + // Define a list of ndarrays: + const struct ndarray *arrays[] = { x, y, corr, meanx, meany }; + + // Compute the result: + float v = stdlib_stats_scovarmtk( arrays ); + + // Print the result: + printf( "result: %f\n", v ); + + // Free allocated memory: + stdlib_ndarray_free( x ); + stdlib_ndarray_free( y ); + stdlib_ndarray_free( corr ); + stdlib_ndarray_free( meanx ); + stdlib_ndarray_free( meany ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/include.gypi b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/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 {number} covariance +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var opts = { +* 'dtype': 'float32' +* }; +* +* var x = new Float32Vector( [ 1.0, -2.0, 2.0 ] ); +* var y = new Float32Vector( [ 2.0, -2.0, 1.0 ] ); +* +* var meanx = scalar2ndarray( 1.0/3.0, opts ); +* var meany = scalar2ndarray( 1.0/3.0, opts ); +* var correction = scalar2ndarray( 1.0, opts ); +* +* var v = scovarmtk( [ x, y, correction, meanx, meany ] ); +* // returns ~3.8333 +*/ +function scovarmtk( arrays ) { + var correction; + var meanx; + var meany; + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + correction = arrays[ 2 ]; + meanx = arrays[ 3 ]; + meany = arrays[ 4 ]; + + return addon( getData( x ), serialize( x ), getData( y ), serialize( y ), getData( correction ), serialize( correction ), getData( meanx ), serialize( meanx ), getData( meany ), serialize( meany ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = scovarmtk; diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/manifest.json b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/manifest.json new file mode 100644 index 000000000000..a39375ece2db --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/manifest.json @@ -0,0 +1,110 @@ +{ + "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/scovarmtk", + "@stdlib/ndarray/ctor", + "@stdlib/ndarray/base/napi/addon-arguments", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/create-double" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/stats/strided/scovarmtk", + "@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/scovarmtk", + "@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/scovarmtk", + "@stdlib/ndarray/ctor" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/package.json index 92c7d0489027..0fec5ad4cec3 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/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/scovarmtk/src/Makefile b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/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/scovarmtk/src/addon.c b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/src/addon.c new file mode 100644 index 000000000000..9be2194ab8df --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/src/addon.c @@ -0,0 +1,74 @@ +/** +* @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/scovarmtk.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 "stdlib/napi/create_double.h" +#include +#include + +/** +* 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( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 10 ); + + // Process provided arguments: + struct ndarray *arrays[ 5 ]; + napi_value err; + napi_status status = stdlib_ndarray_napi_addon_arguments( env, argv, 10, 5, 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[ 5 ] = { + arrays[ 0 ], + arrays[ 1 ], + arrays[ 2 ], + arrays[ 3 ], + arrays[ 4 ] + }; + // Perform computation: + STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_stats_scovarmtk( arr ), v ); + + // Free allocated memory: + stdlib_ndarray_free( arrays[ 0 ] ); + stdlib_ndarray_free( arrays[ 1 ] ); + stdlib_ndarray_free( arrays[ 2 ] ); + stdlib_ndarray_free( arrays[ 3 ] ); + stdlib_ndarray_free( arrays[ 4 ] ); + arrays[ 0 ] = NULL; + arrays[ 1 ] = NULL; + arrays[ 2 ] = NULL; + arrays[ 3 ] = NULL; + arrays[ 4 ] = NULL; + + return v; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/src/main.c b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/src/main.c new file mode 100644 index 000000000000..9484ffffc13d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/src/main.c @@ -0,0 +1,52 @@ +/** +* @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/scovarmtk.h" +#include "stdlib/stats/strided/scovarmtk.h" +#include "stdlib/ndarray/ctor.h" +#include "stdlib/blas/base/shared.h" + +/** +* Computes the covariance of two one-dimensional single-precision floating-point ndarrays provided known means and using a one-pass textbook algorithm. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - first one-dimensional input ndarray. +* - second one-dimensional input ndarray. +* - a zero-dimensional ndarray specifying the degrees of freedom adjustment. +* - a zero-dimensional ndarray specifying the mean of the first one-dimensional ndarray. +* - a zero-dimensional ndarray specifying the mean of the second one-dimensional ndarray. +* +* @param arrays list containing ndarrays +* @return covariance +*/ +float stdlib_stats_scovarmtk( const struct ndarray *arrays[] ) { + const struct ndarray *x = arrays[ 0 ]; + const struct ndarray *y = arrays[ 1 ]; + + float correction; + float meanx; + float meany; + stdlib_ndarray_get_float32( arrays[ 2 ], NULL, &correction ); + stdlib_ndarray_get_float32( arrays[ 3 ], NULL, &meanx ); + stdlib_ndarray_get_float32( arrays[ 4 ], NULL, &meany ); + + return API_SUFFIX(stdlib_strided_scovarmtk_ndarray)( stdlib_ndarray_dimension( x, 0 ), correction, meanx, (const float *)stdlib_ndarray_data( x ), stdlib_ndarray_stride_elements( x, 0 ), stdlib_ndarray_offset_elements( x ), meany, (const float *)stdlib_ndarray_data( y ), stdlib_ndarray_stride_elements( y, 0 ), stdlib_ndarray_offset_elements( y ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.js index 7f3697c18d03..2bb986c1e047 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.js @@ -21,38 +21,18 @@ // MODULES // var tape = require( 'tape' ); -var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); -var Float32Array = require( '@stdlib/array/float32' ); -var ndarray = require( '@stdlib/ndarray/base/ctor' ); -var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); -var f32 = require( '@stdlib/number/float64/base/to-float32' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); var scovarmtk = require( './../lib' ); // VARIABLES // -var options = { - 'dtype': 'float32' +var opts = { + 'skip': IS_BROWSER }; -// 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 ) { @@ -61,203 +41,37 @@ tape( 'main export is a function', function test( t ) { t.end(); }); -tape( 'the function has an arity of 1', function test( t ) { - t.strictEqual( scovarmtk.length, 1, 'has expected arity' ); - t.end(); -}); - -tape( 'the function calculates the population covariance of two one-dimensional single-precision floating-point ndarrays provided known means', function test( t ) { - var correction; - var meanx; - var meany; - var x; - var y; - var v; - - correction = scalar2ndarray( 0.0, options ); - - x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - y = new Float32Array( [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ] ); - meanx = scalar2ndarray( 0.5, options ); - meany = scalar2ndarray( 0.5, options ); - v = scovarmtk( [ vector( x, 6, 1, 0 ), vector( y, 6, 1, 0 ), correction, meanx, meany ] ); // eslint-disable-line max-len - t.strictEqual( v, f32( -45.5/x.length ), 'returns expected value' ); - - x = new Float32Array( [ -4.0, -4.0 ] ); - meanx = scalar2ndarray( -4.0, options ); - v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len - t.strictEqual( v, 0.0, 'returns expected value' ); - - x = new Float32Array( [ NaN, 4.0 ] ); - meanx = scalar2ndarray( 4.0, options ); - v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len - t.strictEqual( isnanf( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'the function calculates the sample covariance of two one-dimensional single-precision floating-point ndarrays provided known means', function test( t ) { - var correction; - var meanx; - var meany; - var x; - var y; - var v; - - correction = scalar2ndarray( 1.0, options ); - - x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); - y = new Float32Array( [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ] ); - meanx = scalar2ndarray( 0.5, options ); - meany = scalar2ndarray( 0.5, options ); - v = scovarmtk( [ vector( x, 6, 1, 0 ), vector( y, 6, 1, 0 ), correction, meanx, meany ] ); // eslint-disable-line max-len - t.strictEqual( v, f32( -45.5/(x.length-1) ), 'returns expected value' ); - - x = new Float32Array( [ -4.0, -4.0 ] ); - meanx = scalar2ndarray( -4.0, options ); - v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len - t.strictEqual( v, 0.0, 'returns expected value' ); - - x = new Float32Array( [ NaN, 4.0 ] ); - meanx = scalar2ndarray( 4.0, options ); - v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len - t.strictEqual( isnanf( v ), true, 'returns expected value' ); - - t.end(); -}); - -tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { - var correction; - var meanx; - var x; - var v; - - x = new Float32Array( [] ); - meanx = scalar2ndarray( 0.5, options ); - correction = scalar2ndarray( 1.0, options ); - - v = scovarmtk( [ vector( x, 0, 1, 0 ), vector( x, 0, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len - t.strictEqual( isnanf( v ), true, 'returns expected value' ); +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var scovarmtk = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + t.strictEqual( scovarmtk, mock, 'returns expected value' ); t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { - var correction; - var meanx; - var meany; - var x; - var y; - var v; - - correction = scalar2ndarray( 1.0, options ); - - x = new Float32Array([ - 1.0, // 0 - 2.0, - 2.0, // 1 - -7.0, - -2.0, // 2 - 3.0, - 4.0, // 3 - 2.0 - ]); - meanx = scalar2ndarray( 1.25, options ); - - y = new Float32Array([ - 2.0, // 0 - 2.0, - 1.0, // 1 - -7.0, - 4.0, // 2 - 3.0, - -2.0, // 3 - 2.0 - ]); - meany = scalar2ndarray( 1.25, options ); - v = scovarmtk( [ vector( x, 4, 2, 0 ), vector( y, 4, 2, 0 ), correction, meanx, meany ] ); // eslint-disable-line max-len + function tryRequire() { + return mock; + } - t.strictEqual( v, f32( -18.25/3 ), 'returns expected value' ); - t.end(); + function mock() { + // Mock... + } }); -tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { - var correction; - var meanx; - var meany; - var x; - var y; - var v; - - correction = scalar2ndarray( 1.0, options ); - - x = new Float32Array([ - 1.0, // 3 - 2.0, - 2.0, // 2 - -7.0, - -2.0, // 1 - 3.0, - 4.0, // 0 - 2.0 - ]); - meanx = scalar2ndarray( 1.25, options ); +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var scovarmtk; + var main; - y = new Float32Array([ - 2.0, // 3 - 2.0, - 1.0, // 2 - -7.0, - 4.0, // 1 - 3.0, - -2.0, // 0 - 2.0 - ]); - meany = scalar2ndarray( 1.25, options ); + main = require( './../lib/main.js' ); - v = scovarmtk( [ vector( x, 4, -2, 6 ), vector( y, 4, -2, 6 ), correction, meanx, meany ] ); // eslint-disable-line max-len + scovarmtk = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); - t.strictEqual( v, f32( -18.25/3 ), 'returns expected value' ); + t.strictEqual( scovarmtk, main, 'returns expected value' ); t.end(); -}); - -tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { - var correction; - var meanx; - var meany; - var x; - var y; - var v; - correction = scalar2ndarray( 1.0, options ); - - x = new Float32Array([ - 2.0, - 1.0, // 0 - 2.0, - -2.0, // 1 - -2.0, - 2.0, // 2 - 3.0, - 4.0 // 3 - ]); - meanx = scalar2ndarray( 1.25, options ); - - y = new Float32Array([ - 2.0, - -2.0, // 0 - 2.0, - 1.0, // 1 - -2.0, - 4.0, // 2 - 3.0, - 2.0 // 3 - ]); - meany = scalar2ndarray( 1.25, options ); - - v = scovarmtk( [ vector( x, 4, 2, 1 ), vector( y, 4, 2, 1 ), correction, meanx, meany ] ); // eslint-disable-line max-len - t.strictEqual( v, f32( 5.75/3 ), 'returns expected value' ); - - t.end(); + function tryRequire() { + return new Error( 'Cannot find module' ); + } }); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.main.js b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.main.js new file mode 100644 index 000000000000..54153a6493a5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.main.js @@ -0,0 +1,263 @@ +/** +* @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 tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var Float32Array = require( '@stdlib/array/float32' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var f32 = require( '@stdlib/number/float64/base/to-float32' ); +var scovarmtk = require( './../lib/main.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// 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 scovarmtk, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( scovarmtk.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the population covariance of two one-dimensional single-precision floating-point ndarrays provided known means', function test( t ) { + var correction; + var meanx; + var meany; + var x; + var y; + var v; + + correction = scalar2ndarray( 0.0, options ); + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + y = new Float32Array( [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ] ); + meanx = scalar2ndarray( 0.5, options ); + meany = scalar2ndarray( 0.5, options ); + v = scovarmtk( [ vector( x, 6, 1, 0 ), vector( y, 6, 1, 0 ), correction, meanx, meany ] ); // eslint-disable-line max-len + t.strictEqual( v, f32( -45.5/x.length ), 'returns expected value' ); + + x = new Float32Array( [ -4.0, -4.0 ] ); + meanx = scalar2ndarray( -4.0, options ); + v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, 4.0 ] ); + meanx = scalar2ndarray( 4.0, options ); + v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the sample covariance of two one-dimensional single-precision floating-point ndarrays provided known means', function test( t ) { + var correction; + var meanx; + var meany; + var x; + var y; + var v; + + correction = scalar2ndarray( 1.0, options ); + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + y = new Float32Array( [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ] ); + meanx = scalar2ndarray( 0.5, options ); + meany = scalar2ndarray( 0.5, options ); + v = scovarmtk( [ vector( x, 6, 1, 0 ), vector( y, 6, 1, 0 ), correction, meanx, meany ] ); // eslint-disable-line max-len + t.strictEqual( v, f32( -45.5/(x.length-1) ), 'returns expected value' ); + + x = new Float32Array( [ -4.0, -4.0 ] ); + meanx = scalar2ndarray( -4.0, options ); + v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, 4.0 ] ); + meanx = scalar2ndarray( 4.0, options ); + v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) { + var correction; + var meanx; + var x; + var v; + + x = new Float32Array( [] ); + meanx = scalar2ndarray( 0.5, options ); + correction = scalar2ndarray( 1.0, options ); + + v = scovarmtk( [ vector( x, 0, 1, 0 ), vector( x, 0, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var correction; + var meanx; + var meany; + var x; + var y; + var v; + + correction = scalar2ndarray( 1.0, options ); + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + meanx = scalar2ndarray( 1.25, options ); + + y = new Float32Array([ + 2.0, // 0 + 2.0, + 1.0, // 1 + -7.0, + 4.0, // 2 + 3.0, + -2.0, // 3 + 2.0 + ]); + meany = scalar2ndarray( 1.25, options ); + + v = scovarmtk( [ vector( x, 4, 2, 0 ), vector( y, 4, 2, 0 ), correction, meanx, meany ] ); // eslint-disable-line max-len + + t.strictEqual( v, f32( -18.25/3 ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var correction; + var meanx; + var meany; + var x; + var y; + var v; + + correction = scalar2ndarray( 1.0, options ); + + x = new Float32Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + meanx = scalar2ndarray( 1.25, options ); + + y = new Float32Array([ + 2.0, // 3 + 2.0, + 1.0, // 2 + -7.0, + 4.0, // 1 + 3.0, + -2.0, // 0 + 2.0 + ]); + meany = scalar2ndarray( 1.25, options ); + + v = scovarmtk( [ vector( x, 4, -2, 6 ), vector( y, 4, -2, 6 ), correction, meanx, meany ] ); // eslint-disable-line max-len + + t.strictEqual( v, f32( -18.25/3 ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var correction; + var meanx; + var meany; + var x; + var y; + var v; + + correction = scalar2ndarray( 1.0, options ); + + x = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + meanx = scalar2ndarray( 1.25, options ); + + y = new Float32Array([ + 2.0, + -2.0, // 0 + 2.0, + 1.0, // 1 + -2.0, + 4.0, // 2 + 3.0, + 2.0 // 3 + ]); + meany = scalar2ndarray( 1.25, options ); + + v = scovarmtk( [ vector( x, 4, 2, 1 ), vector( y, 4, 2, 1 ), correction, meanx, meany ] ); // eslint-disable-line max-len + t.strictEqual( v, f32( 5.75/3 ), 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.native.js b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.native.js new file mode 100644 index 000000000000..50561cdc73a5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/test/test.native.js @@ -0,0 +1,268 @@ +/** +* @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 tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var Float32Array = require( '@stdlib/array/float32' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var f32 = require( '@stdlib/number/float64/base/to-float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var scovarmtk = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( scovarmtk instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// 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 scovarmtk, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', opts, function test( t ) { + t.strictEqual( scovarmtk.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function calculates the population covariance of two one-dimensional single-precision floating-point ndarrays provided known means', opts, function test( t ) { + var correction; + var meanx; + var meany; + var x; + var y; + var v; + + correction = scalar2ndarray( 0.0, options ); + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + y = new Float32Array( [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ] ); + meanx = scalar2ndarray( 0.5, options ); + meany = scalar2ndarray( 0.5, options ); + v = scovarmtk( [ vector( x, 6, 1, 0 ), vector( y, 6, 1, 0 ), correction, meanx, meany ] ); // eslint-disable-line max-len + t.strictEqual( v, f32( -45.5/x.length ), 'returns expected value' ); + + x = new Float32Array( [ -4.0, -4.0 ] ); + meanx = scalar2ndarray( -4.0, options ); + v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, 4.0 ] ); + meanx = scalar2ndarray( 4.0, options ); + v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function calculates the sample covariance of two one-dimensional single-precision floating-point ndarrays provided known means', opts, function test( t ) { + var correction; + var meanx; + var meany; + var x; + var y; + var v; + + correction = scalar2ndarray( 1.0, options ); + + x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ); + y = new Float32Array( [ -2.0, 1.0, 5.0, -4.0, 3.0, 0.0 ] ); + meanx = scalar2ndarray( 0.5, options ); + meany = scalar2ndarray( 0.5, options ); + v = scovarmtk( [ vector( x, 6, 1, 0 ), vector( y, 6, 1, 0 ), correction, meanx, meany ] ); // eslint-disable-line max-len + t.strictEqual( v, f32( -45.5/(x.length-1) ), 'returns expected value' ); + + x = new Float32Array( [ -4.0, -4.0 ] ); + meanx = scalar2ndarray( -4.0, options ); + v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len + t.strictEqual( v, 0.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, 4.0 ] ); + meanx = scalar2ndarray( 4.0, options ); + v = scovarmtk( [ vector( x, 2, 1, 0 ), vector( x, 2, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `NaN`', opts, function test( t ) { + var correction; + var meanx; + var x; + var v; + + x = new Float32Array( [] ); + meanx = scalar2ndarray( 0.5, options ); + correction = scalar2ndarray( 1.0, options ); + + v = scovarmtk( [ vector( x, 0, 1, 0 ), vector( x, 0, 1, 0 ), correction, meanx, meanx ] ); // eslint-disable-line max-len + t.strictEqual( isnanf( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', opts, function test( t ) { + var correction; + var meanx; + var meany; + var x; + var y; + var v; + + correction = scalar2ndarray( 1.0, options ); + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 2.0, // 1 + -7.0, + -2.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + meanx = scalar2ndarray( 1.25, options ); + + y = new Float32Array([ + 2.0, // 0 + 2.0, + 1.0, // 1 + -7.0, + 4.0, // 2 + 3.0, + -2.0, // 3 + 2.0 + ]); + meany = scalar2ndarray( 1.25, options ); + + v = scovarmtk( [ vector( x, 4, 2, 0 ), vector( y, 4, 2, 0 ), correction, meanx, meany ] ); // eslint-disable-line max-len + + t.strictEqual( v, f32( -18.25/3 ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', opts, function test( t ) { + var correction; + var meanx; + var meany; + var x; + var y; + var v; + + correction = scalar2ndarray( 1.0, options ); + + x = new Float32Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -7.0, + -2.0, // 1 + 3.0, + 4.0, // 0 + 2.0 + ]); + meanx = scalar2ndarray( 1.25, options ); + + y = new Float32Array([ + 2.0, // 3 + 2.0, + 1.0, // 2 + -7.0, + 4.0, // 1 + 3.0, + -2.0, // 0 + 2.0 + ]); + meany = scalar2ndarray( 1.25, options ); + + v = scovarmtk( [ vector( x, 4, -2, 6 ), vector( y, 4, -2, 6 ), correction, meanx, meany ] ); // eslint-disable-line max-len + + t.strictEqual( v, f32( -18.25/3 ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', opts, function test( t ) { + var correction; + var meanx; + var meany; + var x; + var y; + var v; + + correction = scalar2ndarray( 1.0, options ); + + x = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + meanx = scalar2ndarray( 1.25, options ); + + y = new Float32Array([ + 2.0, + -2.0, // 0 + 2.0, + 1.0, // 1 + -2.0, + 4.0, // 2 + 3.0, + 2.0 // 3 + ]); + meany = scalar2ndarray( 1.25, options ); + + v = scovarmtk( [ vector( x, 4, 2, 1 ), vector( y, 4, 2, 1 ), correction, meanx, meany ] ); // eslint-disable-line max-len + t.strictEqual( v, f32( 5.75/3 ), 'returns expected value' ); + + t.end(); +}); From ce9aede0b5dde6aebe065aaf253556db8b921e3c Mon Sep 17 00:00:00 2001 From: Mayur Jogade Date: Wed, 16 Sep 2026 11:00:35 +0530 Subject: [PATCH 2/2] style: update comments --- type: pre_commit_static_analysis_report description: Results of running static analysis checks when committing changes. report: - task: lint_filenames status: passed - task: lint_editorconfig status: passed - task: lint_markdown_pkg_readmes status: na - task: lint_markdown_docs status: na - task: lint_markdown status: na - task: lint_package_json status: na - task: lint_repl_help status: na - task: lint_javascript_src status: passed - task: lint_javascript_cli status: na - task: lint_javascript_examples status: na - task: lint_javascript_tests status: na - task: lint_javascript_benchmarks status: na - task: lint_python status: na - task: lint_r status: na - task: lint_c_src status: na - task: lint_c_examples status: na - task: lint_c_benchmarks status: na - task: lint_c_tests_fixtures status: na - task: lint_shell status: na - task: lint_typescript_declarations status: passed - task: lint_typescript_tests status: na - task: lint_license_headers status: passed --- --- .../@stdlib/stats/base/ndarray/scovarmtk/lib/native.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/lib/native.js b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/lib/native.js index 62ed43fc7a0d..0ce1e9a57c50 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/lib/native.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/scovarmtk/lib/native.js @@ -36,7 +36,7 @@ var addon = require( './../src/addon.node' ); * * - first one-dimensional input ndarray. * - second one-dimensional input ndarray. -* - a zero-dimensional ndarray specifying the 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 covariance according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment and `N` corresponds to the number of elements in each input ndarray. When computing the population covariance, setting this parameter to `0` is the standard choice (i.e., the provided arrays contain data constituting entire populations). When computing the unbiased sample covariance, setting this parameter to `1` is the standard choice (i.e., the provided arrays contain data sampled from larger populations; this is commonly referred to as Bessel's correction). +* - a zero-dimensional ndarray specifying the degrees of freedom adjustment. * - a zero-dimensional ndarray specifying the mean of the first one-dimensional ndarray. * - a zero-dimensional ndarray specifying the mean of the second one-dimensional ndarray. *