simple-squiggle/node_modules/mathjs/lib/esm/function/statistics/mean.js

99 lines
2.7 KiB
JavaScript

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