feat:node-modules
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node_modules/mathjs/lib/cjs/function/statistics/mean.js
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node_modules/mathjs/lib/cjs/function/statistics/mean.js
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"use strict";
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Object.defineProperty(exports, "__esModule", {
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value: true
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});
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exports.createMean = void 0;
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var _collection = require("../../utils/collection.js");
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var _array = require("../../utils/array.js");
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var _factory = require("../../utils/factory.js");
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var _improveErrorMessage = require("./utils/improveErrorMessage.js");
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const name = 'mean';
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const dependencies = ['typed', 'add', 'divide'];
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const createMean = exports.createMean = /* #__PURE__ */(0, _factory.factory)(name, dependencies, _ref => {
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let {
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typed,
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add,
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divide
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} = _ref;
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/**
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* Compute the mean value of matrix or a list with values.
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* In case of a multidimensional array, the mean of the flattened array
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* will be calculated. When `dim` is provided, the maximum over the selected
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* dimension will be calculated. Parameter `dim` is zero-based.
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*
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* Syntax:
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*
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* math.mean(a, b, c, ...)
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* math.mean(A)
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* math.mean(A, dimension)
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*
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* Examples:
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*
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* math.mean(2, 1, 4, 3) // returns 2.5
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* math.mean([1, 2.7, 3.2, 4]) // returns 2.725
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*
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* math.mean([[2, 5], [6, 3], [1, 7]], 0) // returns [3, 5]
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* math.mean([[2, 5], [6, 3], [1, 7]], 1) // returns [3.5, 4.5, 4]
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*
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* See also:
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*
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* median, min, max, sum, prod, std, variance
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*
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* @param {... *} args A single matrix or or multiple scalar values
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* @return {*} The mean of all values
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*/
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return typed(name, {
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// mean([a, b, c, d, ...])
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'Array | Matrix': _mean,
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// mean([a, b, c, d, ...], dim)
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'Array | Matrix, number | BigNumber': _nmeanDim,
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// mean(a, b, c, d, ...)
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'...': function (args) {
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if ((0, _collection.containsCollections)(args)) {
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throw new TypeError('Scalar values expected in function mean');
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}
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return _mean(args);
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}
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});
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/**
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* Calculate the mean value in an n-dimensional array, returning a
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* n-1 dimensional array
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* @param {Array} array
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* @param {number} dim
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* @return {number} mean
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* @private
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*/
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function _nmeanDim(array, dim) {
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try {
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const sum = (0, _collection.reduce)(array, dim, add);
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const s = Array.isArray(array) ? (0, _array.arraySize)(array) : array.size();
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return divide(sum, s[dim]);
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} catch (err) {
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throw (0, _improveErrorMessage.improveErrorMessage)(err, 'mean');
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}
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}
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/**
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* Recursively calculate the mean value in an n-dimensional array
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* @param {Array} array
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* @return {number} mean
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* @private
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*/
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function _mean(array) {
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let sum;
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let num = 0;
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(0, _collection.deepForEach)(array, function (value) {
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try {
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sum = sum === undefined ? value : add(sum, value);
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num++;
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} catch (err) {
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throw (0, _improveErrorMessage.improveErrorMessage)(err, 'mean', value);
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}
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});
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if (num === 0) {
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throw new Error('Cannot calculate the mean of an empty array');
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}
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return divide(sum, num);
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}
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});
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