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feat: refactor and add protocol support to stats/base/nanmskmin #6326

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240734a
feat: refactor and add protocol support to stats/base/nanmskmin #5663
Kaushikgtm Mar 16, 2025
ef0e17d
Merge branch 'stdlib-js:develop' into develop
Kaushikgtm Mar 20, 2025
5052304
Merge branch 'stdlib-js:develop' into develop
Kaushikgtm Mar 21, 2025
c089fa8
refactor and add protocol support to stats/base/nanmskmin
Kaushikgtm Mar 23, 2025
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139 changes: 58 additions & 81 deletions lib/node_modules/@stdlib/stats/base/nanmskmin/README.md
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Expand Up @@ -2,7 +2,7 @@

@license Apache-2.0

Copyright (c) 2020 The Stdlib Authors.
Copyright (c) 2025 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.
Expand Down Expand Up @@ -33,39 +33,36 @@ limitations under the License.
## Usage

```javascript
var nanmskmin = require( '@stdlib/stats/base/nanmskmin' );
var nanmskmin = require("@stdlib/stats/base/nanmskmin");
```

#### nanmskmin( N, x, strideX, mask, strideMask )

Computes the minimum value of a strided array `x` according to a `mask`, ignoring `NaN` values.

```javascript
var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];
var mask = [ 0, 0, 1, 0, 0 ];
var x = [1.0, -2.0, -4.0, 2.0, NaN];
var mask = [0, 0, 1, 0, 0];

var v = nanmskmin( x.length, x, 1, mask, 1 );
var v = nanmskmin(x.length, x, 1, mask, 1);
// returns -2.0
```

The function has the following parameters:

- **N**: number of indexed elements.
- **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
- **strideX**: index increment for `x`.
- **mask**: mask [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation.
- **strideMask**: index increment for `mask`.
- **N**: number of indexed elements.
- **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
- **strideX**: stride length for `x`.
- **mask**: mask [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation.
- **strideMask**: stride length for `mask`.

The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
The `N` and `stride` parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the minimum value of every other element in `x`,

```javascript
var floor = require( '@stdlib/math/base/special/floor' );
var x = [1.0, 2.0, -7.0, -2.0, 4.0, 3.0, -5.0, -6.0];
var mask = [0, 0, 0, 0, 0, 0, 1, 1];

var x = [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, -5.0, -6.0 ];
var mask = [ 0, 0, 0, 0, 0, 0, 1, 1 ];
var N = floor( x.length / 2 );

var v = nanmskmin( N, x, 2, mask, 2 );
var v = nanmskmin(4, x, 2, mask, 2);
// returns -7.0
```

Expand All @@ -74,19 +71,16 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t
<!-- eslint-disable stdlib/capitalized-comments -->

```javascript
var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
var floor = require( '@stdlib/math/base/special/floor' );

var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var Float64Array = require("@stdlib/array/float64");
var Uint8Array = require("@stdlib/array/uint8");

var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var x0 = new Float64Array([2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0]);
var x1 = new Float64Array(x0.buffer, x0.BYTES_PER_ELEMENT * 1); // start at 2nd element

var N = floor( x0.length / 2 );
var mask0 = new Uint8Array([0, 0, 0, 0, 0, 0, 1, 1]);
var mask1 = new Uint8Array(mask0.buffer, mask0.BYTES_PER_ELEMENT * 1); // start at 2nd element

var v = nanmskmin( N, x1, 2, mask1, 2 );
var v = nanmskmin(4, x1, 2, mask1, 2);
// returns -2.0
```

Expand All @@ -95,28 +89,27 @@ var v = nanmskmin( N, x1, 2, mask1, 2 );
Computes the minimum value of a strided array according to a `mask`, ignoring `NaN` values and using alternative indexing semantics.

```javascript
var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];
var mask = [ 0, 0, 1, 0, 0 ];
var x = [1.0, -2.0, -4.0, 2.0, NaN];
var mask = [0, 0, 1, 0, 0];

var v = nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 );
var v = nanmskmin.ndarray(x.length, x, 1, 0, mask, 1, 0);
// returns -2.0
```

The function has the following additional parameters:

- **offsetX**: starting index for `x`.
- **offsetMask**: starting index for `mask`.
- **offsetX**: starting index for `x`.
- **offsetMask**: starting index for `mask`.

While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value
While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset
indexing semantics based on
starting indices. For example, to calculate the minimum value for every other value in `x` starting from the second value

```javascript
var floor = require( '@stdlib/math/base/special/floor' );
var x = [2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0];
var mask = [0, 0, 0, 0, 0, 0, 1, 1];

var x = [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ];
var mask = [ 0, 0, 0, 0, 0, 0, 1, 1 ];
var N = floor( x.length / 2 );

var v = nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
var v = nanmskmin.ndarray(4, x, 2, 1, mask, 2, 1);
// returns -2.0
```

Expand All @@ -128,8 +121,9 @@ var v = nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 );

## Notes

- If `N <= 0`, both functions return `NaN`.
- Depending on the environment, the typed versions ([`dnanmskmin`][@stdlib/stats/base/dnanmskmin], [`snanmskmin`][@stdlib/stats/base/snanmskmin], etc.) are likely to be significantly more performant.
- If `N <= 0`, both functions return `NaN`.
- Depending on the environment, the typed versions ([`dnanmskmin`][@stdlib/stats/base/dnanmskmin], [`snanmskmin`][@stdlib/stats/base/snanmskmin], etc.) are likely to be significantly more performant.
- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]).

</section>

Expand All @@ -142,35 +136,22 @@ var v = nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
<!-- eslint no-undef: "error" -->

```javascript
var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var Float64Array = require( '@stdlib/array/float64' );
var Uint8Array = require( '@stdlib/array/uint8' );
var nanmskmin = require( '@stdlib/stats/base/nanmskmin' );

var mask;
var x;
var i;

x = new Float64Array( 10 );
mask = new Uint8Array( x.length );
for ( i = 0; i < x.length; i++ ) {
if ( randu() < 0.2 ) {
mask[ i ] = 1;
} else {
mask[ i ] = 0;
}
if ( randu() < 0.1 ) {
x[ i ] = NaN;
} else {
x[ i ] = round( (randu()*100.0) - 50.0 );
}
}
console.log( x );
console.log( mask );

var v = nanmskmin( x.length, x, 1, mask, 1 );
console.log( v );
var uniform = require("@stdlib/random/array/uniform");
var bernoulli = require("@stdlib/random/array/bernoulli");
var nanmskmin = require("@stdlib/stats/base/nanmskmin");

var x = uniform(10, -50.0, 50.0, {
dtype: "float64",
});
console.log(x);

var mask = bernoulli(x.length, 0.2, {
dtype: "uint8",
});
console.log(mask);

var v = nanmskmin(x.length, x, 1, mask, 1);
console.log(v);
```

</section>
Expand All @@ -181,15 +162,15 @@ console.log( v );

<section class="related">

* * *
---

## See Also

- <span class="package-name">[`@stdlib/stats/base/dnanmskmin`][@stdlib/stats/base/dnanmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array according to a mask, ignoring NaN values.</span>
- <span class="package-name">[`@stdlib/stats/base/mskmin`][@stdlib/stats/base/mskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a strided array according to a mask.</span>
- <span class="package-name">[`@stdlib/stats/base/nanmin`][@stdlib/stats/base/nanmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a strided array, ignoring NaN values.</span>
- <span class="package-name">[`@stdlib/stats/base/nanmskmax`][@stdlib/stats/base/nanmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a strided array according to a mask, ignoring NaN values.</span>
- <span class="package-name">[`@stdlib/stats/base/snanmskmin`][@stdlib/stats/base/snanmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a single-precision floating-point strided array according to a mask, ignoring NaN values.</span>
- <span class="package-name">[`@stdlib/stats/base/dnanmskmin`][@stdlib/stats/base/dnanmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array according to a mask, ignoring NaN values.</span>
- <span class="package-name">[`@stdlib/stats/base/mskmin`][@stdlib/stats/base/mskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a strided array according to a mask.</span>
- <span class="package-name">[`@stdlib/stats/base/nanmin`][@stdlib/stats/base/nanmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a strided array, ignoring NaN values.</span>
- <span class="package-name">[`@stdlib/stats/base/nanmskmax`][@stdlib/stats/base/nanmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a strided array according to a mask, ignoring NaN values.</span>
- <span class="package-name">[`@stdlib/stats/base/snanmskmin`][@stdlib/stats/base/snanmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a single-precision floating-point strided array according to a mask, ignoring NaN values.</span>

</section>

Expand All @@ -200,19 +181,15 @@ console.log( v );
<section class="links">

[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array

[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray

<!-- <related-links> -->

[@stdlib/stats/base/dnanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dnanmskmin

[@stdlib/stats/base/mskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/mskmin

[@stdlib/stats/base/nanmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/nanmin

[@stdlib/stats/base/nanmskmax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/nanmskmax

[@stdlib/stats/base/snanmskmin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/snanmskmin

<!-- </related-links> -->
Expand Down
115 changes: 54 additions & 61 deletions lib/node_modules/@stdlib/stats/base/nanmskmin/benchmark/benchmark.js
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@@ -1,87 +1,80 @@
/**
* @license Apache-2.0
*
* Copyright (c) 2020 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.
*/
* @license Apache-2.0
*
* Copyright (c) 2025 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';
"use strict";

// MODULES //

var bench = require( '@stdlib/bench' );
var randu = require( '@stdlib/random/base/randu' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pow = require( '@stdlib/math/base/special/pow' );
var pkg = require( './../package.json' ).name;
var nanmskmin = require( './../lib/nanmskmin.js' );
var bench = require("@stdlib/bench");
var isnan = require("@stdlib/math/base/assert/is-nan");
var uniform = require("@stdlib/random/array/uniform");
var bernoulli = require("@stdlib/random/array/bernoulli");
var pow = require("@stdlib/math/base/special/pow");
var pkg = require("./../package.json").name;
var nanmskmin = require("./../lib/nanmskmin.js");

// VARIABLES //

var options = {
dtype: "generic",
};

// FUNCTIONS //

/**
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} len - array length
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
var mask;
var x;
var i;

x = [];
mask = [];
for ( i = 0; i < len; i++ ) {
if ( randu() < 0.2 ) {
mask.push( 1 );
} else {
mask.push( 0 );
}
x.push( ( randu()*20.0 ) - 10.0 );
}
* Creates a benchmark function.
*
* @private
* @param {PositiveInteger} len - array length
* @returns {Function} benchmark function
*/
function createBenchmark(len) {
var mask = bernoulli(len, 0.2, options);
var x = uniform(len, -10.0, 10.0, options);
return benchmark;

function benchmark( b ) {
function benchmark(b) {
var v;
var i;

b.tic();
for ( i = 0; i < b.iterations; i++ ) {
v = nanmskmin( x.length, x, 1, mask, 1 );
if ( isnan( v ) ) {
b.fail( 'should not return NaN' );
for (i = 0; i < b.iterations; i++) {
v = nanmskmin(x.length, x, 1, mask, 1);
if (isnan(v)) {
b.fail("should not return NaN");
}
}
b.toc();
if ( isnan( v ) ) {
b.fail( 'should not return NaN' );
if (isnan(v)) {
b.fail("should not return NaN");
}
b.pass( 'benchmark finished' );
b.pass("benchmark finished");
b.end();
}
}


// MAIN //

/**
* Main execution sequence.
*
* @private
*/
* Main execution sequence.
*
* @private
*/
function main() {
var len;
var min;
Expand All @@ -92,10 +85,10 @@ function main() {
min = 1; // 10^min
max = 6; // 10^max

for ( i = min; i <= max; i++ ) {
len = pow( 10, i );
f = createBenchmark( len );
bench( pkg+':len='+len, f );
for (i = min; i <= max; i++) {
len = pow(10, i);
f = createBenchmark(len);
bench(pkg + ":len=" + len, f);
}
}

Expand Down
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