"use strict"; Object.defineProperty(exports, "__esModule", { value: true }); exports.createMedian = 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 = 'median'; var dependencies = ['typed', 'add', 'divide', 'compare', 'partitionSelect']; var createMedian = /* #__PURE__ */(0, _factory.factory)(name, dependencies, function (_ref) { var typed = _ref.typed, add = _ref.add, divide = _ref.divide, compare = _ref.compare, partitionSelect = _ref.partitionSelect; /** * Recursively calculate the median of an n-dimensional array * @param {Array} array * @return {Number} median * @private */ function _median(array) { try { array = (0, _array.flatten)(array.valueOf()); var num = array.length; if (num === 0) { throw new Error('Cannot calculate median of an empty array'); } if (num % 2 === 0) { // even: return the average of the two middle values var mid = num / 2 - 1; var right = partitionSelect(array, mid + 1); // array now partitioned at mid + 1, take max of left part var left = array[mid]; for (var i = 0; i < mid; ++i) { if (compare(array[i], left) > 0) { left = array[i]; } } return middle2(left, right); } else { // odd: return the middle value var m = partitionSelect(array, (num - 1) / 2); return middle(m); } } catch (err) { throw (0, _improveErrorMessage.improveErrorMessage)(err, 'median'); } } // helper function to type check the middle value of the array var middle = typed({ 'number | BigNumber | Complex | Unit': function numberBigNumberComplexUnit(value) { return value; } }); // helper function to type check the two middle value of the array var middle2 = typed({ 'number | BigNumber | Complex | Unit, number | BigNumber | Complex | Unit': function numberBigNumberComplexUnitNumberBigNumberComplexUnit(left, right) { return divide(add(left, right), 2); } }); /** * Compute the median of a matrix or a list with values. The values are * sorted and the middle value is returned. In case of an even number of * values, the average of the two middle values is returned. * Supported types of values are: Number, BigNumber, Unit * * In case of a (multi dimensional) array or matrix, the median of all * elements will be calculated. * * Syntax: * * math.median(a, b, c, ...) * math.median(A) * * Examples: * * math.median(5, 2, 7) // returns 5 * math.median([3, -1, 5, 7]) // returns 4 * * See also: * * mean, min, max, sum, prod, std, variance, quantileSeq * * @param {... *} args A single matrix or or multiple scalar values * @return {*} The median */ return typed(name, { // median([a, b, c, d, ...]) 'Array | Matrix': _median, // median([a, b, c, d, ...], dim) 'Array | Matrix, number | BigNumber': function ArrayMatrixNumberBigNumber(array, dim) { // TODO: implement median(A, dim) throw new Error('median(A, dim) is not yet supported'); // return reduce(arguments[0], arguments[1], ...) }, // median(a, b, c, d, ...) '...': function _(args) { if ((0, _collection.containsCollections)(args)) { throw new TypeError('Scalar values expected in function median'); } return _median(args); } }); }); exports.createMedian = createMedian;