feat: add C implementation for stats/base/ndarray/snanmskmin

lib/node_modules/@stdlib/stats/base/ndarray/snanmskmax/lib/index.js

@@ -37,9 +37,23 @@
 
 // MODULES //
 
+var join = require( 'path' ).join;
+var tryRequire = require( '@stdlib/utils/try-require' );
+var isError = require( '@stdlib/assert/is-error' );
 var main = require( './main.js' );
 
 
+// MAIN //
+
+var snanmskmax;
+var tmp = tryRequire( join( __dirname, './native.js' ) );
+if ( isError( tmp ) ) {
+	snanmskmax = main;
+} else {
+	snanmskmax = tmp;
+}
+
+
 // EXPORTS //
 
-module.exports = main;
+module.exports = snanmskmax;

lib/node_modules/@stdlib/stats/base/ndarray/snanmskmin/README.md

@@ -2,7 +2,7 @@
 
 @license Apache-2.0
 
-Copyright (c) 2025 The Stdlib Authors.
+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.
@@ -103,6 +103,132 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C API documentation. -->
+
+<section class="c">
+
+## C APIs
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/ndarray/snanmskmin.h"
+```
+
+#### stdlib_stats_snanmskmin( arrays )
+
+Compute the minimum value of a one-dimensional single-precision floating-point ndarray according to a mask, ignoring `NaN` values.
+
+```c
+#include "stdlib/ndarray/ctor.h"
+#include "stdlib/ndarray/dtypes.h"
+#include "stdlib/ndarray/orders.h"
+#include "stdlib/ndarray/index_modes.h"
+#include <stdint.h>
+
+// ...
+
+// Create ndarray and mask...
+struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)data, ndims, shape, xstrides, offset, order, imode, nsubmodes, submodes );
+struct ndarray *mask = stdlib_ndarray_allocate( STDLIB_NDARRAY_UINT8, (uint8_t *)mdata, ndims, shape, mstrides, offset, order, imode, nsubmodes, submodes );
+
+const struct ndarray *arrays[] = { x, mask };
+
+float v = stdlib_stats_snanmskmin( arrays );
+
+// ...
+
+// Free memory:
+stdlib_ndarray_free( x );
+stdlib_ndarray_free( mask );
+```
+
+The function accepts the following arguments:
+
+-   **arrays**: `[2](const struct ndarray *)` array containing ndarrays (a one-dimensional input ndarray and a one-dimensional mask ndarray).
+
+```c
+float stdlib_stats_snanmskmin( const struct ndarray *arrays[] );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/ndarray/snanmskmin.h"
+#include "stdlib/ndarray/ctor.h"
+#include "stdlib/ndarray/dtypes.h"
+#include "stdlib/ndarray/orders.h"
+#include "stdlib/ndarray/index_modes.h"
+#include <stdint.h>
+#include <stdio.h>
+
+int main( void ) {
+    float x[] = { 1.0f, -2.0f, 4.0f, 2.0f, 0.0f/0.0f };
+    uint8_t mask[] = { 0, 0, 1, 0, 0 };
+
+    int64_t ndims = 1;
+    int64_t shape[] = { 5 };
+    int64_t strides[] = { 4 };
+    int64_t mstrides[] = { 1 };
+    int64_t offset = 0;
+    enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR;
+    enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR;
+    int8_t submodes[] = { imode };
+    int64_t nsubmodes = 1;
+
+    struct ndarray *X = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT32, (uint8_t *)x, ndims, shape, strides, offset, order, imode, nsubmodes, submodes );
+    if ( X == NULL ) {
+        printf( "Error allocating memory.\n" );
+        return 1;
+    }
+
+    struct ndarray *Mask = stdlib_ndarray_allocate( STDLIB_NDARRAY_UINT8, (uint8_t *)mask, ndims, shape, mstrides, offset, order, imode, nsubmodes, submodes );
+    if ( Mask == NULL ) {
+        printf( "Error allocating memory.\n" );
+        stdlib_ndarray_free( X );
+        return 1;
+    }
+
+    const struct ndarray *arrays[] = { X, Mask };
+
+    float v = stdlib_stats_snanmskmin( arrays );
+    printf( "min: %f\n", v );
+
+    stdlib_ndarray_free( X );
+    stdlib_ndarray_free( Mask );
+
+    return 0;
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">

lib/node_modules/@stdlib/stats/base/ndarray/snanmskmin/benchmark/benchmark.js

@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2025 The Stdlib Authors.
+* 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.

lib/node_modules/@stdlib/stats/base/ndarray/snanmskmin/benchmark/benchmark.native.js

@@ -0,0 +1,145 @@
+/**
+* @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/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var fillBy = require( '@stdlib/ndarray/fill-by' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var format = require( '@stdlib/string/format' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var isError = require( '@stdlib/assert/is-error' );
+var pkg = require( './../package.json' ).name;
+
+var snanmskmin = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': isError( snanmskmin )
+};
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+var moptions = {
+	'dtype': 'uint8'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
+/**
+* Returns a random mask value.
+*
+* @private
+* @returns {integer} random mask value
+*/
+function mrand() {
+	return bernoulli( 0.2 );
+}
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var mask;
+	var x;
+
+	x = fillBy( zeros( [ len ], options ), rand );
+	mask = fillBy( zeros( [ len ], moptions ), mrand );
+
+	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++ ) {
+			x.set( i%len, i );
+			v = snanmskmin( [ x, mask ] );
+			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();