109 lines
3.0 KiB
JavaScript
109 lines
3.0 KiB
JavaScript
"use strict";
|
|
|
|
Object.defineProperty(exports, "__esModule", {
|
|
value: true
|
|
});
|
|
exports.createMean = void 0;
|
|
|
|
var _collection = require("../../utils/collection.js");
|
|
|
|
var _array = require("../../utils/array.js");
|
|
|
|
var _factory = require("../../utils/factory.js");
|
|
|
|
var _improveErrorMessage = require("./utils/improveErrorMessage.js");
|
|
|
|
var name = 'mean';
|
|
var dependencies = ['typed', 'add', 'divide'];
|
|
var createMean = /* #__PURE__ */(0, _factory.factory)(name, dependencies, function (_ref) {
|
|
var typed = _ref.typed,
|
|
add = _ref.add,
|
|
divide = _ref.divide;
|
|
|
|
/**
|
|
* 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 ((0, _collection.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 = (0, _collection.reduce)(array, dim, add);
|
|
var s = Array.isArray(array) ? (0, _array.arraySize)(array) : array.size();
|
|
return divide(sum, s[dim]);
|
|
} catch (err) {
|
|
throw (0, _improveErrorMessage.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;
|
|
(0, _collection.deepForEach)(array, function (value) {
|
|
try {
|
|
sum = sum === undefined ? value : add(sum, value);
|
|
num++;
|
|
} catch (err) {
|
|
throw (0, _improveErrorMessage.improveErrorMessage)(err, 'mean', value);
|
|
}
|
|
});
|
|
|
|
if (num === 0) {
|
|
throw new Error('Cannot calculate the mean of an empty array');
|
|
}
|
|
|
|
return divide(sum, num);
|
|
}
|
|
});
|
|
exports.createMean = createMean; |