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