simple-squiggle

A restricted subset of Squiggle
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median.js (3700B)

      1 "use strict";
      2 
      3 Object.defineProperty(exports, "__esModule", {
      4   value: true
      5 });
      6 exports.createMedian = void 0;
      7 
      8 var _collection = require("../../utils/collection.js");
      9 
     10 var _array = require("../../utils/array.js");
     11 
     12 var _factory = require("../../utils/factory.js");
     13 
     14 var _improveErrorMessage = require("./utils/improveErrorMessage.js");
     15 
     16 var name = 'median';
     17 var dependencies = ['typed', 'add', 'divide', 'compare', 'partitionSelect'];
     18 var createMedian = /* #__PURE__ */(0, _factory.factory)(name, dependencies, function (_ref) {
     19   var typed = _ref.typed,
     20       add = _ref.add,
     21       divide = _ref.divide,
     22       compare = _ref.compare,
     23       partitionSelect = _ref.partitionSelect;
     24 
     25   /**
     26    * Recursively calculate the median of an n-dimensional array
     27    * @param {Array} array
     28    * @return {Number} median
     29    * @private
     30    */
     31   function _median(array) {
     32     try {
     33       array = (0, _array.flatten)(array.valueOf());
     34       var num = array.length;
     35 
     36       if (num === 0) {
     37         throw new Error('Cannot calculate median of an empty array');
     38       }
     39 
     40       if (num % 2 === 0) {
     41         // even: return the average of the two middle values
     42         var mid = num / 2 - 1;
     43         var right = partitionSelect(array, mid + 1); // array now partitioned at mid + 1, take max of left part
     44 
     45         var left = array[mid];
     46 
     47         for (var i = 0; i < mid; ++i) {
     48           if (compare(array[i], left) > 0) {
     49             left = array[i];
     50           }
     51         }
     52 
     53         return middle2(left, right);
     54       } else {
     55         // odd: return the middle value
     56         var m = partitionSelect(array, (num - 1) / 2);
     57         return middle(m);
     58       }
     59     } catch (err) {
     60       throw (0, _improveErrorMessage.improveErrorMessage)(err, 'median');
     61     }
     62   } // helper function to type check the middle value of the array
     63 
     64 
     65   var middle = typed({
     66     'number | BigNumber | Complex | Unit': function numberBigNumberComplexUnit(value) {
     67       return value;
     68     }
     69   }); // helper function to type check the two middle value of the array
     70 
     71   var middle2 = typed({
     72     'number | BigNumber | Complex | Unit, number | BigNumber | Complex | Unit': function numberBigNumberComplexUnitNumberBigNumberComplexUnit(left, right) {
     73       return divide(add(left, right), 2);
     74     }
     75   });
     76   /**
     77    * Compute the median of a matrix or a list with values. The values are
     78    * sorted and the middle value is returned. In case of an even number of
     79    * values, the average of the two middle values is returned.
     80    * Supported types of values are: Number, BigNumber, Unit
     81    *
     82    * In case of a (multi dimensional) array or matrix, the median of all
     83    * elements will be calculated.
     84    *
     85    * Syntax:
     86    *
     87    *     math.median(a, b, c, ...)
     88    *     math.median(A)
     89    *
     90    * Examples:
     91    *
     92    *     math.median(5, 2, 7)        // returns 5
     93    *     math.median([3, -1, 5, 7])  // returns 4
     94    *
     95    * See also:
     96    *
     97    *     mean, min, max, sum, prod, std, variance, quantileSeq
     98    *
     99    * @param {... *} args  A single matrix or or multiple scalar values
    100    * @return {*} The median
    101    */
    102 
    103   return typed(name, {
    104     // median([a, b, c, d, ...])
    105     'Array | Matrix': _median,
    106     // median([a, b, c, d, ...], dim)
    107     'Array | Matrix, number | BigNumber': function ArrayMatrixNumberBigNumber(array, dim) {
    108       // TODO: implement median(A, dim)
    109       throw new Error('median(A, dim) is not yet supported'); // return reduce(arguments[0], arguments[1], ...)
    110     },
    111     // median(a, b, c, d, ...)
    112     '...': function _(args) {
    113       if ((0, _collection.containsCollections)(args)) {
    114         throw new TypeError('Scalar values expected in function median');
    115       }
    116 
    117       return _median(args);
    118     }
    119   });
    120 });
    121 exports.createMedian = createMedian;