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

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import { containsCollections, deepForEach, reduce } from '../../utils/collection.js';
import { factory } from '../../utils/factory.js';
import { improveErrorMessage } from './utils/improveErrorMessage.js';
var name = 'sum';
var dependencies = ['typed', 'config', 'add', 'numeric'];
export var createSum = /* #__PURE__ */factory(name, dependencies, _ref => {
var {
typed,
config,
add,
numeric
} = _ref;
/**
* Compute the sum of a matrix or a list with values.
* In case of a (multi dimensional) array or matrix, the sum of all
* elements will be calculated.
*
* Syntax:
*
* math.sum(a, b, c, ...)
* math.sum(A)
*
* Examples:
*
* math.sum(2, 1, 4, 3) // returns 10
* math.sum([2, 1, 4, 3]) // returns 10
* math.sum([[2, 5], [4, 3], [1, 7]]) // returns 22
*
* See also:
*
* mean, median, min, max, prod, std, variance, cumsum
*
* @param {... *} args A single matrix or or multiple scalar values
* @return {*} The sum of all values
*/
return typed(name, {
// sum([a, b, c, d, ...])
'Array | Matrix': _sum,
// sum([a, b, c, d, ...], dim)
'Array | Matrix, number | BigNumber': _nsumDim,
// sum(a, b, c, d, ...)
'...': function _(args) {
if (containsCollections(args)) {
throw new TypeError('Scalar values expected in function sum');
}
return _sum(args);
}
});
/**
* Recursively calculate the sum of an n-dimensional array
* @param {Array | Matrix} array
* @return {number} sum
* @private
*/
function _sum(array) {
var sum;
deepForEach(array, function (value) {
try {
sum = sum === undefined ? value : add(sum, value);
} catch (err) {
throw improveErrorMessage(err, 'sum', value);
}
}); // make sure returning numeric value: parse a string into a numeric value
if (sum === undefined) {
sum = numeric(0, config.number);
}
if (typeof sum === 'string') {
sum = numeric(sum, config.number);
}
return sum;
}
function _nsumDim(array, dim) {
try {
var sum = reduce(array, dim, add);
return sum;
} catch (err) {
throw improveErrorMessage(err, 'sum');
}
}
});