feat: add `stats/base/ndarray/dmeanstdev` #8525

Orthodox-64 · 2025-11-13T16:08:45Z

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feat: add stats/base/ndarray/dmeanstdev

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Coverage Report

Package	Statements	Branches	Functions	Lines
stats/base/ndarray/dmeanstdev	$\color{green}134/134$ $color{green}+100.00%$	$\color{green}3/3$ $color{green}+100.00%$	$\color{green}1/1$ $color{green}+100.00%$	$\color{green}134/134$ $color{green}+100.00%$

The above coverage report was generated for the changes in this PR.

kgryte · 2025-11-14T04:14:12Z

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

+
+<section class="intro">
+
+The [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are defined as


You should just copy the introduction from stats/strided/dmeanstdev instead of rolling your own. This makes find-and-replace easier when we are consistent in our docs across similar packages.

This comment still needs to be addressed.

kgryte · 2025-11-14T04:15:34Z

lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/lib/main.js

+function dmeanstdev( arrays ) {
+	var out = arrays[ 1 ];
+	var x = arrays[ 0 ];
+	return strided( numelDimension( x, 0 ), 1, getData( x ), getStride( x, 0 ), getOffset( x ), getData( out ), getStride( out, 0 ), getOffset( out ) ); // eslint-disable-line max-len


This is not what is desired. For a much more complicated API, see https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/ndarray/dztest. Notice there that scalar parameters, such as should be done for correction, are provided as ancillary arrays. Hardcoding 1 for the correction is not what we want.

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

kgryte

Left some initial comments.

Co-authored-by: Athan <kgryte@gmail.com> Signed-off-by: Sachin Pangal <151670745+Orthodox-64@users.noreply.github.com>

Orthodox-64 · 2025-11-14T18:04:20Z

@kgryte Done — I’ve applied all the requested changes.

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

Orthodox-64 · 2025-11-22T17:26:00Z

@kgryte Done with the above changes!.

Signed-off-by: Athan <kgryte@gmail.com>

kgryte · 2025-11-29T08:25:00Z

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

+-   **arrays**: array-like object containing the following ndarrays in order:
+
+    1.  a one-dimensional input ndarray.
+    2.  a one-dimensional output ndarray (of length 2) to store the [mean][arithmetic-mean] and [standard deviation][standard-deviation].


Suggested change

2. a one-dimensional output ndarray (of length 2) to store the [mean][arithmetic-mean] and [standard deviation][standard-deviation].

2. a one-dimensional output ndarray to store the [mean][arithmetic-mean] and [standard deviation][standard-deviation].

kgryte · 2025-11-29T08:26:26Z

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

+
+    1.  a one-dimensional input ndarray.
+    2.  a one-dimensional output ndarray (of length 2) to store the [mean][arithmetic-mean] and [standard deviation][standard-deviation].
+    3.  a zero-dimensional ndarray specifying the degrees of freedom adjustment.


Suggested change

3. a zero-dimensional ndarray specifying the degrees of freedom adjustment.

3. a zero-dimensional ndarray specifying the degrees of freedom adjustment. Setting this to a value other than `0` has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).

kgryte · 2025-11-29T08:26:54Z

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

+The output ndarray contains two elements: the [arithmetic mean][arithmetic-mean] at index 0 and the [standard deviation][standard-deviation] at index 1. The [standard deviation][standard-deviation] is computed using the provided degrees of freedom adjustment. Setting the correction parameter to `1` corresponds to Bessel's correction (i.e., the corrected sample standard deviation). Setting it to `0` computes the population standard deviation.
+


Suggested change

The output ndarray contains two elements: the [arithmetic mean][arithmetic-mean] at index 0 and the [standard deviation][standard-deviation] at index 1. The [standard deviation][standard-deviation] is computed using the provided degrees of freedom adjustment. Setting the correction parameter to `1` corresponds to Bessel's correction (i.e., the corrected sample standard deviation). Setting it to `0` computes the population standard deviation.

kgryte · 2025-11-29T08:28:11Z

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

+
+## Notes
+
+-   If provided an empty one-dimensional ndarray, the computed [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are equal to `NaN`.


Suggested change

- If provided an empty one-dimensional ndarray, the computed [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are equal to `NaN`.

- If provided an empty one-dimensional ndarray, the computed [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are equal to `NaN`.

- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), the computed [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are equal to `NaN`.

kgryte · 2025-11-29T08:29:22Z

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

+
+var correction = scalar2ndarray( 1.0, opts );
+
+var v = dmeanstdev( [ x, out, correction ] );


You should be able to use ndarray2array to display the (approximate) results.

kgryte · 2025-11-29T08:33:05Z

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

+
+	xbuf = uniform( len, -10.0, 10.0, options );
+	x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+	out = new ndarray( 'float64', new Float64Array( 2 ), [ 2 ], [ 1 ], 0, 'row-major' );


Rather than hardcoding float64 here, I suggest using ndarray/base/zeros.

kgryte · 2025-11-29T08:33:30Z

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

+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = dmeanstdev( [ x, out, correction ] );
+			if ( isnan( v[ 0 ] ) ) {


This is not correct. v[ 0 ] is undefined.

kgryte · 2025-11-29T08:33:37Z

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

+			}
+		}
+		b.toc();
+		if ( isnan( v[ 0 ] ) ) {


Same comment.

kgryte · 2025-11-29T08:34:02Z

lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/repl.txt

+        - a one-dimensional output ndarray (of length 2) to store the mean
+        and standard deviation.


Suggested change

- a one-dimensional output ndarray (of length 2) to store the mean

and standard deviation.

- a one-dimensional output ndarray to store the mean

and standard deviation.

kgryte · 2025-11-29T08:34:22Z

lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/repl.txt

+        - a one-dimensional input ndarray.
+        - a one-dimensional output ndarray (of length 2) to store the mean
+        and standard deviation.
+        - a zero-dimensional ndarray specifying the degrees of freedom


You need a longer description here. See README suggestion.

kgryte · 2025-11-29T08:36:33Z

lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/docs/repl.txt

+    > var opts = { 'dtype': dt };
+    > var correction = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts );
+    > {{alias}}( [ x, out, correction ] );
+    > {{alias:@stdlib/ndarray/to-array}}( out )


This is precisely the sort of thing you can do in that README example. Namely, use ndarray/to-array to convert the output ndarray to a nested array and then show approximate results as done on the next line.

kgryte · 2025-11-29T08:37:25Z

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

+/**
+* Computes the mean and standard deviation of a one-dimensional double-precision floating-point ndarray.
+*
+* @param arrays - array-like object containing input and output ndarrays, and a correction parameter ndarray


Suggested change

* @param arrays - array-like object containing input and output ndarrays, and a correction parameter ndarray

* @param arrays - array-like object containing an input ndarray, an output ndarray, and ndarray containing the degrees of freedom adjustment

kgryte · 2025-11-29T08:37:37Z

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

+* Computes the mean and standard deviation of a one-dimensional double-precision floating-point ndarray.
+*
+* @param arrays - array-like object containing input and output ndarrays, and a correction parameter ndarray
+* @returns output ndarray containing [ mean, stdev ]


Suggested change

* @returns output ndarray containing [ mean, stdev ]

* @returns output ndarray

kgryte · 2025-11-29T08:38:50Z

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

+*
+* var arr = ndarray2array( v );
+* // returns <Float64Array>[ ~1.25, ~2.5 ]


And this is even closer to what we want in the README example.

kgryte · 2025-11-29T08:40:18Z

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

+
+	dmeanstdev(); // $ExpectError
+	dmeanstdev( [ x, out ] ); // $ExpectError
+	dmeanstdev( [ x, out, correction, correction ] ); // $ExpectError


Suggested change

dmeanstdev( [ x, out, correction, correction ] ); // $ExpectError

dmeanstdev( [ x, out, correction, correction ] ); // $ExpectError

dmeanstdev( [ x, out, correction ], {} ); // $ExpectError

kgryte · 2025-11-29T08:41:05Z

lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/examples/index.js

+var xbuf = discreteUniform( 10, -50, 50, {
+	'dtype': 'float64'
+});


Suggested change

var xbuf = discreteUniform( 10, -50, 50, {

'dtype': 'float64'

});

var xbuf = discreteUniform( 10, -50, 50, opts );

kgryte · 2025-11-29T08:41:33Z

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

+var xbuf = discreteUniform( 10, -50, 50, {
+    'dtype': 'float64'
+});


Suggested change

var xbuf = discreteUniform( 10, -50, 50, {

'dtype': 'float64'

});

var xbuf = discreteUniform( 10, -50, 50, opts );

kgryte · 2025-11-29T08:44:25Z

lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/test/test.js

+	t.end();
+});
+
+tape( 'if provided an empty vector, the function returns `NaN` values', function test( t ) {


Suggested change

tape( 'if provided an empty vector, the function returns `NaN` values', function test( t ) {

tape( 'if provided an empty ndarray, the function returns `NaN` values', function test( t ) {

kgryte · 2025-11-29T08:45:13Z

lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/test/test.js

+* limitations under the License.
+*/
+
+'use strict';


Suggested change

'use strict';

/* eslint-disable max-len */

'use strict';

kgryte · 2025-11-29T08:48:27Z

lib/node_modules/@stdlib/stats/base/ndarray/dmeanstdev/test/test.js

+	t.end();
+});
+
+tape( 'if provided a vector containing a single element, the function returns that element as mean and `NaN` as standard deviation when using sample correction', function test( t ) {


Suggested change

tape( 'if provided a vector containing a single element, the function returns that element as mean and `NaN` as standard deviation when using sample correction', function test( t ) {

tape( 'if provided a correction value yielding `N-correction` less than or equal to `0`, the function returns a standard deviation equal to `NaN`', function test( t ) {

kgryte

Left another round of comments.

feat: add stats/base/ndarray/dmeanstdev

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}

}

b.toc();

if ( isnan( v[ 0 ] ) ) {

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		<section class="intro">

		The [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are defined as

	2. a one-dimensional output ndarray (of length 2) to store the [mean][arithmetic-mean] and [standard deviation][standard-deviation].
	2. a one-dimensional output ndarray to store the [mean][arithmetic-mean] and [standard deviation][standard-deviation].

		The output ndarray contains two elements: the [arithmetic mean][arithmetic-mean] at index 0 and the [standard deviation][standard-deviation] at index 1. The [standard deviation][standard-deviation] is computed using the provided degrees of freedom adjustment. Setting the correction parameter to `1` corresponds to Bessel's correction (i.e., the corrected sample standard deviation). Setting it to `0` computes the population standard deviation.


		## Notes

		- If provided an empty one-dimensional ndarray, the computed [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are equal to `NaN`.

	- If provided an empty one-dimensional ndarray, the computed [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are equal to `NaN`.
	- If provided an empty one-dimensional ndarray, the computed [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are equal to `NaN`.
	- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), the computed [arithmetic mean][arithmetic-mean] and [standard deviation][standard-deviation] are equal to `NaN`.


		var correction = scalar2ndarray( 1.0, opts );

		var v = dmeanstdev( [ x, out, correction ] );

		- a one-dimensional output ndarray (of length 2) to store the mean
		and standard deviation.

	* @param arrays - array-like object containing input and output ndarrays, and a correction parameter ndarray
	* @param arrays - array-like object containing an input ndarray, an output ndarray, and ndarray containing the degrees of freedom adjustment

	* @returns output ndarray containing [ mean, stdev ]
	* @returns output ndarray

	dmeanstdev( [ x, out, correction, correction ] ); // $ExpectError
	dmeanstdev( [ x, out, correction, correction ] ); // $ExpectError
	dmeanstdev( [ x, out, correction ], {} ); // $ExpectError

	tape( 'if provided an empty vector, the function returns `NaN` values', function test( t ) {
	tape( 'if provided an empty ndarray, the function returns `NaN` values', function test( t ) {

	tape( 'if provided a vector containing a single element, the function returns that element as mean and `NaN` as standard deviation when using sample correction', function test( t ) {
	tape( 'if provided a correction value yielding `N-correction` less than or equal to `0`, the function returns a standard deviation equal to `NaN`', function test( t ) {

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feat: add `stats/base/ndarray/dmeanstdev` #8525

feat: add `stats/base/ndarray/dmeanstdev` #8525

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