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* @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 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 ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' );
var strided = require( '@stdlib/stats/strided/dmeanstdev' ).ndarray;
// MAIN //
/**
* Computes the mean and standard deviation of a one-dimensional double-precision floating-point ndarray.
*
* ## Notes
*
* - The function expects the following ndarrays:
*
* - a one-dimensional input ndarray.
* - a one-dimensional output ndarray.
* - a zero-dimensional ndarray specifying the degrees of freedom adjustment.
*
* @param {ArrayLikeObject<Object>} arrays - array-like object containing ndarrays
* @returns {ndarrayLike} output ndarray
*
* @example
* var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
*
* var opts = {
* 'dtype': 'float64'
* };
*
* var x = new Float64Vector( [ 1.0, 3.0, 4.0, 2.0 ] );
* var out = new Float64Vector( 2 );
*
* var correction = scalar2ndarray( 1.0, opts );
*
* var v = dmeanstdev( [ x, out, correction ] );
* // returns <ndarray>[ 2.5, ~1.2910 ]
*/
function dmeanstdev( arrays ) {
var correction;
var out;
var x;
x = arrays[ 0 ];
out = arrays[ 1 ];
correction = ndarraylike2scalar( arrays[ 2 ] );
strided( numelDimension( x, 0 ), correction, getData( x ), getStride( x, 0 ), getOffset( x ), getData( out ), getStride( out, 0 ), getOffset( out ) ); // eslint-disable-line max-len
return out;
}
// EXPORTS //
module.exports = dmeanstdev;
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