Merge branch 'pickrandom-allow-any-array)' of https://github.com/KonradLinkowski/mathjs into develop

Author: josdejong

src/function/probability/pickRandom.js

@@ -1,7 +1,7 @@
 import { factory } from '../../utils/factory'
 import { isNumber } from '../../utils/is'
-import { arraySize } from '../../utils/array'
 import { createRng } from './util/seededRNG'
+import { flatten } from '../../utils/array'
 
 const name = 'pickRandom'
 const dependencies = ['typed', 'config', '?on']
@@ -76,15 +76,11 @@ export const createPickRandom = /* #__PURE__ */ factory(name, dependencies, ({ t
       number = 1
     }
 
-    possibles = possibles.valueOf() // get Array
+    possibles = flatten(possibles.valueOf()).valueOf() // get Array
     if (weights) {
       weights = weights.valueOf() // get Array
     }
 
-    if (arraySize(possibles).length > 1) {
-      throw new Error('Only one dimensional vectors supported')
-    }
-
     let totalWeights = 0
 
     if (typeof weights !== 'undefined') {

test/unit-tests/function/probability/pickRandom.test.js

@@ -1,6 +1,7 @@
 import assert from 'assert'
 import { filter, times } from 'lodash'
 import math from '../../../../src/bundleAny'
+import { flatten } from '../../../../src/utils/array'
 
 const math2 = math.create({ randomSeed: 'test2' })
 const pickRandom = math2.pickRandom
@@ -10,12 +11,6 @@ describe('pickRandom', function () {
     assert.strictEqual(typeof math.pickRandom, 'function')
   })
 
-  it('should throw an error when providing a multi dimensional matrix', function () {
-    assert.throws(function () {
-      pickRandom(math.matrix([[1, 2], [3, 4]]))
-    }, /Only one dimensional vectors supported/)
-  })
-
   it('should throw an error if the length of the weights does not match the length of the possibles', function () {
     const possibles = [11, 22, 33, 44, 55]
     const weights = [1, 5, 2, 4]
@@ -68,19 +63,19 @@ describe('pickRandom', function () {
     const weights = [1, 5, 2, 4, 6]
     const number = 5
 
-    assert.strictEqual(pickRandom(possibles, number), possibles)
-    assert.strictEqual(pickRandom(possibles, number, weights), possibles)
-    assert.strictEqual(pickRandom(possibles, weights, number), possibles)
+    pickRandom(possibles, number).forEach((element, index) => assert.strictEqual(element, possibles[index]))
+    pickRandom(possibles, number, weights).forEach((element, index) => assert.strictEqual(element, possibles[index]))
+    pickRandom(possibles, weights, number).forEach((element, index) => assert.strictEqual(element, possibles[index]))
   })
 
   it('should return the given array if the given number is greater than its length', function () {
     const possibles = [11, 22, 33, 44, 55]
     const weights = [1, 5, 2, 4, 6]
     const number = 6
 
-    assert.strictEqual(pickRandom(possibles, number), possibles)
-    assert.strictEqual(pickRandom(possibles, number, weights), possibles)
-    assert.strictEqual(pickRandom(possibles, weights, number), possibles)
+    pickRandom(possibles, number).forEach((element, index) => assert.strictEqual(element, possibles[index]))
+    pickRandom(possibles, number, weights).forEach((element, index) => assert.strictEqual(element, possibles[index]))
+    pickRandom(possibles, weights, number).forEach((element, index) => assert.strictEqual(element, possibles[index]))
   })
 
   it('should return an empty array if the given number is 0', function () {
@@ -117,6 +112,30 @@ describe('pickRandom', function () {
     assert.strictEqual(pickRandom(possibles, weights, number).length, number)
   })
 
+  it('should pick a number from the given multi dimensional array following an uniform distribution', function () {
+    const possibles = [[11, 12], [22, 23], [33, 34], [44, 45], [55, 56]]
+    const picked = []
+
+    times(1000, () => picked.push(pickRandom(possibles)))
+
+    flatten(possibles).forEach(possible => {
+      const count = filter(flatten(picked), val => val === possible).length
+      assert.strictEqual(math.round(count / picked.length, 1), 0.1)
+    })
+  })
+
+  it('should pick a value from the given multi dimensional array following an uniform distribution', function () {
+    // just to be sure that works for any kind of array
+    const possibles = [[[11], [12]], ['test', 45], 'another test', 10, false, [1.3, 4.5, true]]
+    const picked = []
+
+    times(1000, () => picked.push(pickRandom(possibles)))
+    flatten(possibles).forEach(possible => {
+      const count = filter(picked, val => val === possible).length
+      assert.strictEqual(math.round(count / picked.length, 1), 0.1)
+    })
+  })
+
   it('should pick a value from the given array following an uniform distribution if only possibles are passed', function () {
     const possibles = [11, 22, 33, 44, 55]
     const picked = []