feat: add stats/base/ndarray/smeanors

lib/node_modules/@stdlib/stats/base/ndarray/smean/README.md → lib/node_modules/@stdlib/stats/base/ndarray/smeanors/README.md

@@ -18,9 +18,9 @@ limitations under the License.
 
 -->
 
-# smean
+# smeanors
 
-> Compute the [arithmetic mean][arithmetic-mean] of a one-dimensional single-precision floating-point ndarray.
+> Compute the [arithmetic mean][arithmetic-mean] of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation.
 
 <section class="intro">
 
@@ -48,12 +48,12 @@ The [arithmetic mean][arithmetic-mean] is defined as
 ## Usage
 
 ```javascript
-var smean = require( '@stdlib/stats/base/ndarray/smean' );
+var smeanors = require( '@stdlib/stats/base/ndarray/smeanors' );
 ```
 
-#### smean( arrays )
+#### smeanors( arrays )
 
-Computes the [arithmetic mean][arithmetic-mean] of a one-dimensional single-precision floating-point ndarray.
+Computes the [arithmetic mean][arithmetic-mean] of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -62,7 +62,7 @@ var ndarray = require( '@stdlib/ndarray/base/ctor' );
 var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
 var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
 
-var v = smean( [ x ] );
+var v = smeanors( [ x ] );
 // returns 2.5
 ```
 
@@ -79,6 +79,7 @@ The function has the following parameters:
 ## Notes
 
 -   If provided an empty one-dimensional ndarray, the function returns `NaN`.
+-   Ordinary recursive summation (i.e., a "simple" sum) is performant, but can incur significant numerical error. If performance is paramount and error tolerated, using ordinary recursive summation to compute an arithmetic mean is acceptable; in all other cases, exercise due caution.
 
 </section>
 
@@ -94,15 +95,15 @@ The function has the following parameters:
 var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var ndarray = require( '@stdlib/ndarray/base/ctor' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
-var smean = require( '@stdlib/stats/base/ndarray/smean' );
+var smeanors = require( '@stdlib/stats/base/ndarray/smeanors' );
 
 var xbuf = discreteUniform( 10, -50, 50, {
     'dtype': 'float32'
 });
 var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
 console.log( ndarray2array( x ) );
 
-var v = smean( [ x ] );
+var v = smeanors( [ x ] );
 console.log( v );
 ```
 

lib/node_modules/@stdlib/stats/base/ndarray/smean/benchmark/benchmark.js → lib/node_modules/@stdlib/stats/base/ndarray/smeanors/benchmark/benchmark.js

@@ -26,7 +26,7 @@ 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 pkg = require( './../package.json' ).name;
-var smean = require( './../lib' );
+var smeanors = require( './../lib' );
 
 
 // VARIABLES //
@@ -60,7 +60,7 @@ function createBenchmark( len ) {
 
 		b.tic();
 		for ( i = 0; i < b.iterations; i++ ) {
-			v = smean( [ x ] );
+			v = smeanors( [ x ] );
 			if ( isnan( v ) ) {
 				b.fail( 'should not return NaN' );
 			}

lib/node_modules/@stdlib/stats/base/ndarray/smean/docs/repl.txt → lib/node_modules/@stdlib/stats/base/ndarray/smeanors/docs/repl.txt

@@ -1,7 +1,7 @@
 
 {{alias}}( arrays )
     Computes the arithmetic mean of a one-dimensional single-precision floating-
-    point ndarray.
+    point ndarray using ordinary recursive summation.
 
     If provided an empty ndarray, the function returns `NaN`.
 

lib/node_modules/@stdlib/stats/base/ndarray/smean/docs/types/index.d.ts → lib/node_modules/@stdlib/stats/base/ndarray/smeanors/docs/types/index.d.ts

@@ -23,7 +23,7 @@
 import { float32ndarray } from '@stdlib/types/ndarray';
 
 /**
-* Computes the arithmetic mean of a one-dimensional single-precision floating-point ndarray.
+* Computes the arithmetic mean of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation.
 *
 * @param arrays - array-like object containing an input ndarray
 * @returns arithmetic mean
@@ -35,12 +35,12 @@ import { float32ndarray } from '@stdlib/types/ndarray';
 * var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
 * var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
 *
-* var v = smean( [ x ] );
+* var v = smeanors( [ x ] );
 * // returns 2.5
 */
-declare function smean( arrays: [ float32ndarray ] ): number;
+declare function smeanors( arrays: [ float32ndarray ] ): number;
 
 
 // EXPORTS //
 
-export = smean;
+export = smeanors;

lib/node_modules/@stdlib/stats/base/ndarray/smean/docs/types/test.ts → lib/node_modules/@stdlib/stats/base/ndarray/smeanors/docs/types/test.ts

@@ -19,7 +19,7 @@
 /* eslint-disable space-in-parens */
 
 import zeros = require( '@stdlib/ndarray/zeros' );
-import smean = require( './index' );
+import smeanors = require( './index' );
 
 
 // TESTS //
@@ -30,20 +30,20 @@ import smean = require( './index' );
 		'dtype': 'float32'
 	});
 
-	smean( [ x ] ); // $ExpectType number
+	smeanors( [ x ] ); // $ExpectType number
 }
 
 // The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
 {
-	smean( '10' ); // $ExpectError
-	smean( 10 ); // $ExpectError
-	smean( true ); // $ExpectError
-	smean( false ); // $ExpectError
-	smean( null ); // $ExpectError
-	smean( undefined ); // $ExpectError
-	smean( [] ); // $ExpectError
-	smean( {} ); // $ExpectError
-	smean( ( x: number ): number => x ); // $ExpectError
+	smeanors( '10' ); // $ExpectError
+	smeanors( 10 ); // $ExpectError
+	smeanors( true ); // $ExpectError
+	smeanors( false ); // $ExpectError
+	smeanors( null ); // $ExpectError
+	smeanors( undefined ); // $ExpectError
+	smeanors( [] ); // $ExpectError
+	smeanors( {} ); // $ExpectError
+	smeanors( ( x: number ): number => x ); // $ExpectError
 }
 
 // The compiler throws an error if the function is provided an unsupported number of arguments...
@@ -52,6 +52,6 @@ import smean = require( './index' );
 		'dtype': 'float32'
 	});
 
-	smean(); // $ExpectError
-	smean( [ x ], {} ); // $ExpectError
+	smeanors(); // $ExpectError
+	smeanors( [ x ], {} ); // $ExpectError
 }

lib/node_modules/@stdlib/stats/base/ndarray/smean/examples/index.js → lib/node_modules/@stdlib/stats/base/ndarray/smeanors/examples/index.js

@@ -21,13 +21,13 @@
 var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var ndarray = require( '@stdlib/ndarray/base/ctor' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
-var smean = require( './../lib' );
+var smeanors = require( './../lib' );
 
 var xbuf = discreteUniform( 10, -50, 50, {
 	'dtype': 'float32'
 });
 var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
 console.log( ndarray2array( x ) );
 
-var v = smean( [ x ] );
+var v = smeanors( [ x ] );
 console.log( v );

lib/node_modules/@stdlib/stats/base/ndarray/smean/lib/index.js → lib/node_modules/@stdlib/stats/base/ndarray/smeanors/lib/index.js

@@ -19,19 +19,19 @@
 'use strict';
 
 /**
-* Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray.
+* Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation.
 *
-* @module @stdlib/stats/base/ndarray/smean
+* @module @stdlib/stats/base/ndarray/smeanors
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 * var ndarray = require( '@stdlib/ndarray/base/ctor' );
-* var smean = require( '@stdlib/stats/base/ndarray/smean' );
+* var smeanors = require( '@stdlib/stats/base/ndarray/smeanors' );
 *
 * var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
 * var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
 *
-* var v = smean( [ x ] );
+* var v = smeanors( [ x ] );
 * // returns 2.5
 */
 

lib/node_modules/@stdlib/stats/base/ndarray/smean/lib/main.js → lib/node_modules/@stdlib/stats/base/ndarray/smeanors/lib/main.js

@@ -24,13 +24,13 @@ var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
 var getStride = require( '@stdlib/ndarray/base/stride' );
 var getOffset = require( '@stdlib/ndarray/base/offset' );
 var getData = require( '@stdlib/ndarray/base/data-buffer' );
-var strided = require( '@stdlib/stats/strided/smean' ).ndarray;
+var strided = require( '@stdlib/stats/strided/smeanors' ).ndarray;
 
 
 // MAIN //
 
 /**
-* Computes the arithmetic mean of a one-dimensional single-precision floating-point ndarray.
+* Computes the arithmetic mean of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation.
 *
 * @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray
 * @returns {number} arithmetic mean
@@ -42,15 +42,15 @@ var strided = require( '@stdlib/stats/strided/smean' ).ndarray;
 * var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
 * var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
 *
-* var v = smean( [ x ] );
+* var v = smeanors( [ x ] );
 * // returns 2.5
 */
-function smean( arrays ) {
+function smeanors( arrays ) {
 	var x = arrays[ 0 ];
 	return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len
 }
 
 
 // EXPORTS //
 
-module.exports = smean;
+module.exports = smeanors;

lib/node_modules/@stdlib/stats/base/ndarray/smean/package.json → lib/node_modules/@stdlib/stats/base/ndarray/smeanors/package.json

@@ -1,7 +1,7 @@
 {
-  "name": "@stdlib/stats/base/ndarray/smean",
+  "name": "@stdlib/stats/base/ndarray/smeanors",
   "version": "0.0.0",
-  "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray.",
+  "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation.",
   "license": "Apache-2.0",
   "author": {
     "name": "The Stdlib Authors",

lib/node_modules/@stdlib/stats/base/ndarray/smean/test/test.js → lib/node_modules/@stdlib/stats/base/ndarray/smeanors/test/test.js

@@ -25,7 +25,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float32Array = require( '@stdlib/array/float32' );
 var ndarray = require( '@stdlib/ndarray/base/ctor' );
-var smean = require( './../lib' );
+var smeanors = require( './../lib' );
 
 
 // FUNCTIONS //
@@ -49,12 +49,12 @@ function vector( buffer, length, stride, offset ) {
 
 tape( 'main export is a function', function test( t ) {
 	t.ok( true, __filename );
-	t.strictEqual( typeof smean, 'function', 'main export is a function' );
+	t.strictEqual( typeof smeanors, 'function', 'main export is a function' );
 	t.end();
 });
 
 tape( 'the function has an arity of 1', function test( t ) {
-	t.strictEqual( smean.length, 1, 'has expected arity' );
+	t.strictEqual( smeanors.length, 1, 'has expected arity' );
 	t.end();
 });
 
@@ -63,47 +63,47 @@ tape( 'the function calculates the arithmetic mean of a one-dimensional ndarray'
 	var v;
 
 	x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
-	v = smean( [ vector( x, 6, 1, 0 ) ] );
+	v = smeanors( [ vector( x, 6, 1, 0 ) ] );
 	t.strictEqual( v, 0.5, 'returns expected value' );
 
 	x = new Float32Array( [ -4.0, -5.0 ] );
-	v = smean( [ vector( x, 2, 1, 0 ) ] );
+	v = smeanors( [ vector( x, 2, 1, 0 ) ] );
 	t.strictEqual( v, -4.5, 'returns expected value' );
 
 	x = new Float32Array( [ -0.0, 0.0, -0.0 ] );
-	v = smean( [ vector( x, 3, 1, 0 ) ] );
+	v = smeanors( [ vector( x, 3, 1, 0 ) ] );
 	t.strictEqual( isPositiveZero( v ), true, 'returns expected value' );
 
 	x = new Float32Array( [ NaN ] );
-	v = smean( [ vector( x, 1, 1, 0 ) ] );
+	v = smeanors( [ vector( x, 1, 1, 0 ) ] );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
 	x = new Float32Array( [ NaN, NaN ] );
-	v = smean( [ vector( x, 2, 1, 0 ) ] );
+	v = smeanors( [ vector( x, 2, 1, 0 ) ] );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
 	t.end();
 });
 
-tape( 'if provided an empty vector, the function returns `NaN`', function test( t ) {
+tape( 'if provided an empty ndarray, the function returns `NaN`', function test( t ) {
 	var x;
 	var v;
 
 	x = new Float32Array( [] );
 
-	v = smean( [ vector( x, 0, 1, 0 ) ] );
+	v = smeanors( [ vector( x, 0, 1, 0 ) ] );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
 	t.end();
 });
 
-tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) {
+tape( 'if provided an ndarray containing a single element, the function returns that element', function test( t ) {
 	var x;
 	var v;
 
 	x = new Float32Array( [ 1.0 ] );
 
-	v = smean( [ vector( x, 1, 1, 0 ) ] );
+	v = smeanors( [ vector( x, 1, 1, 0 ) ] );
 	t.strictEqual( v, 1.0, 'returns expected value' );
 
 	t.end();
@@ -124,7 +124,7 @@ tape( 'the function supports one-dimensional ndarrays having non-unit strides',
 		2.0
 	]);
 
-	v = smean( [ vector( x, 4, 2, 0 ) ] );
+	v = smeanors( [ vector( x, 4, 2, 0 ) ] );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -145,7 +145,7 @@ tape( 'the function supports one-dimensional ndarrays having negative strides',
 		2.0
 	]);
 
-	v = smean( [ vector( x, 4, -2, 6 ) ] );
+	v = smeanors( [ vector( x, 4, -2, 6 ) ] );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -166,7 +166,7 @@ tape( 'the function supports one-dimensional ndarrays having non-zero offsets',
 		4.0   // 3
 	]);
 
-	v = smean( [ vector( x, 4, 2, 1 ) ] );
+	v = smeanors( [ vector( x, 4, 2, 1 ) ] );
 	t.strictEqual( v, 1.25, 'returns expected value' );
 
 	t.end();