feat:node-modules

node_modules/mathjs/lib/esm/function/statistics/median.js

@@ -0,0 +1,108 @@
+import { containsCollections } from '../../utils/collection.js';
+import { flatten } from '../../utils/array.js';
+import { factory } from '../../utils/factory.js';
+import { improveErrorMessage } from './utils/improveErrorMessage.js';
+var name = 'median';
+var dependencies = ['typed', 'add', 'divide', 'compare', 'partitionSelect'];
+export var createMedian = /* #__PURE__ */factory(name, dependencies, _ref => {
+  var {
+    typed,
+    add,
+    divide,
+    compare,
+    partitionSelect
+  } = _ref;
+  /**
+   * Recursively calculate the median of an n-dimensional array
+   * @param {Array} array
+   * @return {Number} median
+   * @private
+   */
+  function _median(array) {
+    try {
+      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 improveErrorMessage(err, 'median');
+    }
+  }
+
+  // helper function to type check the middle value of the array
+  var middle = typed({
+    'number | BigNumber | Complex | Unit': function number__BigNumber__Complex__Unit(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 number__BigNumber__Complex__Unit_number__BigNumber__Complex__Unit(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 Array__Matrix_number__BigNumber(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 (containsCollections(args)) {
+        throw new TypeError('Scalar values expected in function median');
+      }
+      return _median(args);
+    }
+  });
+});