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feat: add C implementation for stats/base/ndarray/dmeanors
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efd4545
feat: add C implementation for stats/base/ndarray/dmeanors
bhargava-d16 a2badb6
Update benchmark.native.js
Sachinn-64 959fb5f
Update example.c
Sachinn-64 1d5f384
Update test.main.js
Sachinn-64 8070604
Update test.native.js
Sachinn-64 0da37d8
Update example.c
Sachinn-64 dedbe3d
Update native.js
Sachinn-64 c8bac2e
Update main.c
Sachinn-64 27ff161
Update README.md
Sachinn-64 2861a4e
fix: added requested changes
bhargava-d16 008fe07
chore: update description
Planeshifter 8cdb195
chore: add colon
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@@ -111,6 +111,153 @@ console.log( v ); | |||||||||||||
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| <!-- /.examples --> | ||||||||||||||
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| <!-- C interface documentation. --> | ||||||||||||||
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| * * * | ||||||||||||||
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| <section class="c"> | ||||||||||||||
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| ## C APIs | ||||||||||||||
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| <!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. --> | ||||||||||||||
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| <section class="intro"> | ||||||||||||||
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| </section> | ||||||||||||||
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| <!-- /.intro --> | ||||||||||||||
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| <!-- C usage documentation. --> | ||||||||||||||
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| <section class="usage"> | ||||||||||||||
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| ### Usage | ||||||||||||||
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| ```c | ||||||||||||||
| #include "stdlib/stats/base/ndarray/dmeanors.h" | ||||||||||||||
| ``` | ||||||||||||||
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| #### stdlib_stats_dmeanors( arrays ) | ||||||||||||||
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| Computes the arithmetic mean of a one-dimensional double-precision floating-point ndarray using ordinary recursive summation. | ||||||||||||||
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| ```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 | ||||||||||||||
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| // Create an ndarray: | ||||||||||||||
| const double data[] = { 1.0, 2.0, 3.0, 4.0 }; | ||||||||||||||
| int64_t shape[] = { 4 }; | ||||||||||||||
| int64_t strides[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; | ||||||||||||||
| int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; | ||||||||||||||
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| struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes ); | ||||||||||||||
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| // Compute the mean value: | ||||||||||||||
| const struct ndarray *arrays[] = { x }; | ||||||||||||||
| double v = stdlib_stats_dmeanors( arrays ); | ||||||||||||||
| // returns 2.5 | ||||||||||||||
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| // Free allocated memory: | ||||||||||||||
| stdlib_ndarray_free( x ); | ||||||||||||||
| ``` | ||||||||||||||
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| The function accepts the following arguments: | ||||||||||||||
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| - **arrays**: `[in] struct ndarray**` list containing a one-dimensional input ndarray. | ||||||||||||||
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| ```c | ||||||||||||||
| double stdlib_stats_dmeanors( const struct ndarray *arrays[] ); | ||||||||||||||
| ``` | ||||||||||||||
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| </section> | ||||||||||||||
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| <!-- /.usage --> | ||||||||||||||
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| <!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. --> | ||||||||||||||
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| <section class="notes"> | ||||||||||||||
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| </section> | ||||||||||||||
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| <!-- /.notes --> | ||||||||||||||
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| <!-- C API usage examples. --> | ||||||||||||||
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| <section class="examples"> | ||||||||||||||
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| ### Examples | ||||||||||||||
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| ```c | ||||||||||||||
| #include "stdlib/stats/base/ndarray/dmeanors.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 | ||||||||||||||
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Suggested change
Make sure we include proper headers. |
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| int main( void ) { | ||||||||||||||
| // Create a data buffer: | ||||||||||||||
| const double data[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; | ||||||||||||||
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| // Specify the number of array dimensions: | ||||||||||||||
| const int64_t ndims = 1; | ||||||||||||||
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| // Specify the array shape: | ||||||||||||||
| int64_t shape[] = { 4 }; | ||||||||||||||
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| // Specify the array strides: | ||||||||||||||
| int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT }; | ||||||||||||||
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| // Specify the byte offset: | ||||||||||||||
| const int64_t offset = 0; | ||||||||||||||
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| // Specify the array order: | ||||||||||||||
| const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR; | ||||||||||||||
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| // Specify the index mode: | ||||||||||||||
| const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR; | ||||||||||||||
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| // Specify the subscript index modes: | ||||||||||||||
| int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR }; | ||||||||||||||
| const int64_t nsubmodes = 1; | ||||||||||||||
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| // Create an ndarray: | ||||||||||||||
| struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes ); | ||||||||||||||
| if ( x == NULL ) { | ||||||||||||||
| fprintf( stderr, "Error allocating memory.\n" ); | ||||||||||||||
| exit( 1 ); | ||||||||||||||
| } | ||||||||||||||
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| // Define a list of ndarrays: | ||||||||||||||
| const struct ndarray *arrays[] = { x }; | ||||||||||||||
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| // Compute the mean value: | ||||||||||||||
| double v = stdlib_stats_dmeanors( arrays ); | ||||||||||||||
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| // Print the result: | ||||||||||||||
| printf( "mean: %lf\n", v ); | ||||||||||||||
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| // Free allocated memory: | ||||||||||||||
| stdlib_ndarray_free( x ); | ||||||||||||||
| } | ||||||||||||||
| ``` | ||||||||||||||
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| </section> | ||||||||||||||
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| <!-- /.examples --> | ||||||||||||||
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| </section> | ||||||||||||||
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| <!-- /.c --> | ||||||||||||||
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| <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. --> | ||||||||||||||
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| <section class="related"> | ||||||||||||||
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114 changes: 114 additions & 0 deletions
114
lib/node_modules/@stdlib/stats/base/ndarray/dmeanors/benchmark/benchmark.native.js
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| Original file line number | Diff line number | Diff line change |
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| /** | ||
| * @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. | ||
| */ | ||
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| 'use strict'; | ||
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| // MODULES // | ||
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| var resolve = require( 'path' ).resolve; | ||
| var bench = require( '@stdlib/bench' ); | ||
| var uniform = require( '@stdlib/random/array/uniform' ); | ||
| var isnan = require( '@stdlib/math/base/assert/is-nan' ); | ||
| var pow = require( '@stdlib/math/base/special/pow' ); | ||
| var ndarray = require( '@stdlib/ndarray/base/ctor' ); | ||
| var format = require( '@stdlib/string/format' ); | ||
| var tryRequire = require( '@stdlib/utils/try-require' ); | ||
| var pkg = require( './../package.json' ).name; | ||
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| // VARIABLES // | ||
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| var dmeanors = tryRequire( resolve( __dirname, './../lib/native.js' ) ); | ||
| var opts = { | ||
| 'skip': ( dmeanors instanceof Error ) | ||
| }; | ||
| var options = { | ||
| 'dtype': 'float64' | ||
| }; | ||
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| // FUNCTIONS // | ||
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| /** | ||
| * Creates a benchmark function. | ||
| * | ||
| * @private | ||
| * @param {PositiveInteger} len - array length | ||
| * @returns {Function} benchmark function | ||
| */ | ||
| function createBenchmark( len ) { | ||
| var xbuf; | ||
| var x; | ||
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| xbuf = uniform( len, -10.0, 10.0, options ); | ||
| x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' ); | ||
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| return benchmark; | ||
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| /** | ||
| * Benchmark function. | ||
| * | ||
| * @private | ||
| * @param {Benchmark} b - benchmark instance | ||
| */ | ||
| function benchmark( b ) { | ||
| var v; | ||
| var i; | ||
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| b.tic(); | ||
| for ( i = 0; i < b.iterations; i++ ) { | ||
| v = dmeanors( [ x ] ); | ||
| if ( isnan( v ) ) { | ||
| b.fail( 'should not return NaN' ); | ||
| } | ||
| } | ||
| b.toc(); | ||
| if ( isnan( v ) ) { | ||
| b.fail( 'should not return NaN' ); | ||
| } | ||
| b.pass( 'benchmark finished' ); | ||
| b.end(); | ||
| } | ||
| } | ||
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| // MAIN // | ||
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| /** | ||
| * Main execution sequence. | ||
| * | ||
| * @private | ||
| */ | ||
| function main() { | ||
| var len; | ||
| var min; | ||
| var max; | ||
| var f; | ||
| var i; | ||
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| min = 1; // 10^min | ||
| max = 6; // 10^max | ||
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| for ( i = min; i <= max; i++ ) { | ||
| len = pow( 10, i ); | ||
| f = createBenchmark( len ); | ||
| bench( format( '%s::native:len=%d', pkg, len ), opts, f ); | ||
| } | ||
| } | ||
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| main(); |
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