feat: refactored and added protocol support to stats/base/nanmeanwd

---
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
    status: passed
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: passed
  - task: lint_javascript_src
    status: passed
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: passed
  - 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: 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: passed
  - task: lint_license_headers
    status: passed
---

Author: prajjwalbajpai

lib/node_modules/@stdlib/stats/base/nanmeanwd/README.md

@@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as
 var nanmeanwd = require( '@stdlib/stats/base/nanmeanwd' );
 ```
 
-#### nanmeanwd( N, x, stride )
+#### nanmeanwd( N, x, strideX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a strided array `x`, ignoring `NaN` values and using Welford's algorithm.
 
@@ -67,38 +67,32 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
--   **stride**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
 
 ```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
 var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ];
-var N = floor( x.length / 2 );
 
-var v = nanmeanwd( N, x, 2 );
+var v = nanmeanwd( 5, x, 2 );
 // returns 1.25
 ```
 
 Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
 
-<!-- eslint-disable stdlib/capitalized-comments -->
+<!-- eslint-disable stdlib/capitalized-comments, max-len -->
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
-var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
+var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = nanmeanwd( N, x1, 2 );
+var v = nanmeanwd( 5, x1, 2 );
 // returns 1.25
 ```
 
-#### nanmeanwd.ndarray( N, x, stride, offset )
+#### nanmeanwd.ndarray( N, x, strideX, offsetX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
 
@@ -112,17 +106,16 @@ var v = nanmeanwd.ndarray( N, x, 1, 0 );
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-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 [arithmetic mean][arithmetic-mean] 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 parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in the strided array starting from the second element
 
 ```javascript
 var floor = require( '@stdlib/math/base/special/floor' );
 
-var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ];
-var N = floor( x.length / 2 );
+var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ];
 
-var v = nanmeanwd.ndarray( N, x, 2, 1 );
+var v = nanmeanwd.ndarray( 5, x, 2, 1 );
 // returns 1.25
 ```
 
@@ -135,6 +128,7 @@ var v = nanmeanwd.ndarray( N, x, 2, 1 );
 ## Notes
 
 -   If `N <= 0`, both functions return `NaN`.
+-   -   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]).
 -   If every indexed element is `NaN`, both functions return `NaN`.
 -   Depending on the environment, the typed versions ([`dnanmeanwd`][@stdlib/stats/base/dnanmeanwd], [`snanmeanwd`][@stdlib/stats/base/snanmeanwd], etc.) are likely to be significantly more performant.
 
@@ -149,22 +143,19 @@ var v = nanmeanwd.ndarray( N, x, 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 uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var nanmeanwd = require( '@stdlib/stats/base/nanmeanwd' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    if ( randu() < 0.2 ) {
-        x[ i ] = NaN;
-    } else {
-        x[ i ] = round( (randu()*100.0) - 50.0 );
+function rand() {
+    if ( bernoulli( 0.8 ) < 1 ) {
+        return NaN;
     }
+    return uniform( -50.0, 50.0 );
 }
+
+var x = filledarrayBy( 10, 'float64', rand );
 console.log( x );
 
 var v = nanmeanwd( x.length, x, 1 );
@@ -215,6 +206,8 @@ console.log( v );
 
 [mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
 
+[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
+
 [@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022
 
 [@vanreeken:1968a]: https://doi.org/10.1145/362929.362961

lib/node_modules/@stdlib/stats/base/nanmeanwd/benchmark/benchmark.js

@@ -21,15 +21,30 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
-var nanmeanwd = require( './../lib/nanmeanwd.js' );
+var nanmeanwd = require( './../lib/main.js' );
 
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -38,17 +53,7 @@ var nanmeanwd = require( './../lib/nanmeanwd.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = [];
-	for ( i = 0; i < len; i++ ) {
-		if ( randu() < 0.2 ) {
-			x.push( NaN );
-		} else {
-			x.push( ( randu()*20.0 ) - 10.0 );
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {

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

@@ -21,7 +21,9 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
@@ -30,6 +32,19 @@ var nanmeanwd = require( './../lib/ndarray.js' );
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -38,17 +53,7 @@ var nanmeanwd = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = [];
-	for ( i = 0; i < len; i++ ) {
-		if ( randu() < 0.2 ) {
-			x.push( NaN );
-		} else {
-			x.push( ( randu()*20.0 ) - 10.0 );
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {

lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/repl.txt

@@ -1,10 +1,10 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the arithmetic mean of a strided array, ignoring `NaN` values and
     using Welford's algorithm.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and `stride` parameters determine which elements
+    in the strided array are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -21,8 +21,8 @@
     x: Array<number>|TypedArray
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride length.
 
     Returns
     -------
@@ -38,20 +38,17 @@
 
     // Using `N` and `stride` parameters:
     > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 4, x, 2 )
     ~0.3333
 
     // Using view offsets:
-    > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
+    > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 4, x1, 2 )
     ~-0.3333
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the arithmetic mean of a strided array, ignoring `NaN` values and
     using Welford's algorithm and alternative indexing semantics.
 
@@ -67,10 +64,10 @@
     x: Array<number>|TypedArray
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -86,9 +83,8 @@
     ~0.3333
 
     // Using offset parameter:
-    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];
+    > {{alias}}.ndarray( 4, x, 2, 1 )
     ~-0.3333
 
     See Also

lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/types/index.d.ts

@@ -20,7 +20,12 @@
 
 /// <reference types="@stdlib/types"/>
 
-import { NumericArray } from '@stdlib/types/array';
+import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array';
+
+/**
+* Input array.
+*/
+type InputArray = NumericArray | Collection<number> | AccessorArrayLike<number>;
 
 /**
 * Interface describing `nanmeanwd`.
@@ -31,7 +36,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns arithmetic mean
 	*
 	* @example
@@ -40,7 +45,7 @@ interface Routine {
 	* var v = nanmeanwd( x.length, x, 1 );
 	* // returns ~0.3333
 	*/
-	( N: number, x: NumericArray, stride: number ): number;
+	( N: number, x: InputArray, strideX: number ): number;
 
 	/**
 	* Computes the arithmetic mean of a strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
@@ -57,15 +62,15 @@ interface Routine {
 	* var v = nanmeanwd.ndarray( x.length, x, 1, 0 );
 	* // returns ~0.3333
 	*/
-	ndarray( N: number, x: NumericArray, stride: number, offset: number ): number;
+	ndarray( N: number, x: InputArray, strideX: number, offset: number ): number;
 }
 
 /**
 * Computes the arithmetic mean of a strided array, ignoring `NaN` values and using Welford's algorithm.
 *
 * @param N - number of indexed elements
 * @param x - input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns arithmetic mean
 *
 * @example

lib/node_modules/@stdlib/stats/base/nanmeanwd/docs/types/test.ts

@@ -16,6 +16,7 @@
 * limitations under the License.
 */
 
+import AccessorArray = require( '@stdlib/array/base/accessor' );
 import nanmeanwd = require( './index' );
 
 
@@ -26,6 +27,8 @@ import nanmeanwd = require( './index' );
 	const x = new Float64Array( 10 );
 
 	nanmeanwd( x.length, x, 1 ); // $ExpectType number
+	nanmeanwd( x.length, new AccessorArray( x ), 1 ); // $ExpectType number
+
 }
 
 // The compiler throws an error if the function is provided a first argument which is not a number...
@@ -85,6 +88,8 @@ import nanmeanwd = require( './index' );
 	const x = new Float64Array( 10 );
 
 	nanmeanwd.ndarray( x.length, x, 1, 0 ); // $ExpectType number
+	nanmeanwd.ndarray( x.length, new AccessorArray( x ), 1, 0 ); // $ExpectType number
+
 }
 
 // The compiler throws an error if the `ndarray` method is provided a first argument which is not a number...