data-mean.js

//     wink-statistics
//     Fast and Numerically Stable Statistical Analysis Utilities.
//
//     Copyright (C) 2017-18  GRAYPE Systems Private Limited
//
//     This file is part of “wink-statistics”.
//
//     “wink-statistics” is free software: you can redistribute it
//     and/or modify it under the terms of the GNU Affero
//     General Public License as published by the Free
//     Software Foundation, version 3 of the License.
//
//     “wink-statistics” is distributed in the hope that it will
//     be useful, but WITHOUT ANY WARRANTY; without even
//     the implied warranty of MERCHANTABILITY or FITNESS
//     FOR A PARTICULAR PURPOSE.  See the GNU Affero General
//     Public License for more details.
//
//     You should have received a copy of the GNU Affero
//     General Public License along with “wink-statistics”.
//     If not, see <http://www.gnu.org/licenses/>.

// ## data

// Load accessor.
var value = require( './accessor.js' );
// Load wink helpers for validation.
var helpers = require( 'wink-helpers' );

// ### mean
/**
 *
 * Comuptes the mean of numbers contained in the `x` array.
 * The computations are inspired by the method proposed by [B. P. Welford](http://dx.doi.org/10.1080/00401706.1962.10490022).
 *
 * @memberof data
 * @param {array} x array containing 1 or more elements.
 * @param {(string|number|function)} [accessor=undefined] required when elements of
 * `x` are objects or arrays instead of numbers.
 * For objects, use key (string) to access the value; in case of arrays, use
 * index (number) to access the value; or it could be a function
 * that extracts the value from the element passed to it.
 * @return {number} mean value.
 * @example
 * mean( [ 2, 3, 5, 7 ] )
 * // returns 4.25
 * mean( [ { x: 2 }, { x: 3 }, { x: 5 }, { x: 7 } ], 'x' )
 * // returns 4.25
 */
var mean = function ( x, accessor ) {
  var xi;
  var mean1 = 0;

  if ( !helpers.array.isArray( x ) || !x.length ) {
    throw Error( 'data-mean: x should be an array of length > 0, instead found: ' + JSON.stringify( x ) );
  }

  for ( var i = 0, imax = x.length; i < imax; i += 1 ) {
    xi = value( x[ i ], accessor );
    mean1 += ( xi - mean1 ) / ( i + 1 );
  }

  return mean1;
}; // max()

module.exports = mean;