added array flatten to mean, median and mode

docs/statistic-methods.md

@@ -11,13 +11,13 @@ const Stat = require('total-serialism').Statistic;
 
 # Methods
 
-- sort
-- avarage
-- center
-- common
-- maximum
-- minimum
-- change
+- [sort](#sort)
+- [average](#average) (mean)
+- [center](#center) (median)
+- [common](#common) (mode)
+- [maximum](#maximum)
+- [minimum](#minimum)
+- [change](#change)
 
 ## sort
 
@@ -41,41 +41,60 @@ Measures of central tendencies (Mean, Median, Mode)
 
 Get the average (the artihmetic mean) value from an array
 
+**arguments**
+- {Array} -> the array to take the average of
+- {Bool} -> enable/disable the deep flag for n-dim arrays (default=true)
+
 ```js
 Stat.average([1, 2, 3, 4, 5, 6, 7, 8, 9]);
 //=> 5
-// Alternative: Stat.mean()
 
 Stat.average([2, -6, 2, 0, 10, 9, -2, 5, -8, -11, 1, -3]);
 //=> -0.0833
+
+// Alternative: Stat.mean()
 ```
 
 ## center
 
 Return the center value (the median) from an array
 
+**arguments**
+- {Array} -> the array to get the median from
+- {Bool} -> enable/disable the deep flag for n-dim arrays (default=true)
+
 ```js
 Stat.center([1, 5, 6, 9, 13]);
 //=> 6 
-// Alternative: Stat.median()
 
 // Returns average of 2 middle values for even listlengths
 // works with "official" statistics terminology
 Stat.center([1, 7, 4, 2, 9, 5]);
 //=> 4.5
+
+// Alternative: Stat.median()
 ```
 
 ## common
 
 Returns the most common value (the mode) from an array as an array
 
+**arguments**
+- {Array} -> the array to get the mode from
+- {Bool} -> enable/disable the deep flag for n-dim arrays (default=true)
+
 ```js
 Stat.common([8, 4, 3, 11, 9, 0, 11, 2, 10, 5, 11, 0]);
 //=> [ 11 ] 
 
+Stat.common([8, [4, 3], 9, [9, 0, [2, 10], 5], 11, 0, 11]);
+//=> [ 11 ] 
+
 // In the case of a multi-modal system the array contains all common values
 Stat.common([8, 4, 3, 9, 9, 0, 2, 10, 5, 11, 0, 11]);
 //=> [ 0, 9, 11 ] 
+
+// Alternative: Stat.mode()
 ```
 
 ## maximum

src/statistic.js

@@ -53,13 +53,16 @@ exports.min = Util.minimum;
 // The mean is a measure of central tendency
 // 
 // @param {NumberArray} -> input array of n-numbers
+// @param {Bool} -> enable/disable the deep flag for n-dim arrays (default=true)
 // @return {Number} -> mean
 // 
-function mean(a=[0]){
+function mean(a=[0], d=true){
 	if (!Array.isArray(a)) { return a; }
+	if (d) { a = Util.flatten(a); }
+
 	let s = 0;
 	for (let i in a){
-		s += a[i];
+		s += isNaN(a[i])? 0 : a[i];
 	}
 	return s / a.length;
 }
@@ -73,10 +76,13 @@ exports.average = mean;
 // Ignores other datatypes then Number and Boolean
 // 
 // @param {NumberArray} -> input array of n-numbers
+// @param {Bool} -> enable/disable the deep flag for n-dim arrays (default=true)
 // @return {Number} -> median
 // 
-function median(a=[0]){
+function median(a=[0], d=true){
 	if (!Array.isArray(a)) { return a; }
+	if (d) { a = Util.flatten(a); }
+
 	let arr = a.slice();
 	if (arr.map(x => typeof x).includes('string')) { 
 		arr = Mod.filterType(arr, ['number', 'boolean']);
@@ -97,10 +103,13 @@ exports.center = median;
 // Returns an array when multi-modal system
 // 
 // @param {NumberArray} -> input array of n-numbers
+// @param {Bool} -> enable/disable the deep flag for n-dim arrays (default=true)
 // @return {Number/Array} -> the mode or modes
 //
-function mode(a=[0]){
+function mode(a=[0], d=true){
 	if (!Array.isArray(a)) { return a; }
+	if (d) { a = Util.flatten(a); }
+
 	let arr = a.slice().sort((a,b) => { return a-b; });
 
 	let amount = 1;

test/serialism.test.js

@@ -68,8 +68,8 @@ function fullTest(){
 	// testGen();
 	// testAlgo();
 	// testRand();
-	testMod();
-	// testStat();
+	// testMod();
+	testStat();
 	// testTranslate();
 	// testUtil();
 
@@ -452,31 +452,51 @@ function testMod(){
 
 function testStat(){
 	pagebreak("Statistic");
-
+
+	test("Stat.sort()");
+	test("Stat.sort(3.14)");
+	test("Stat.sort('foo')");
 	test("Stat.sort([-10, 8, 6, -12, -6, -7, 2, 4, 3, 11], -1)");
 	test("Stat.sort([10, 3.14, 'foo', 'bar', 5, -6, 'foobar'])");
 	test("Stat.sort([-10, 8, 6, -12, -6, -7, 2, 4, 3, 11])");
-
+
+	test("Stat.mean()");
+	test("Stat.mean(3.14)");
+	test("Stat.mean('foo')");
 	test("Stat.mean([2, -6, 2, 0, 10, 9, -2, 5, -8, -11, 1, -3])");
-	test("Stat.average([1, 2, 3, 4, 5, 6, 7, 8, 9])");
-	test("Stat.average([2, -6, 2, 0, 10, 9, -2, 5, -8, -11, 1, -3])");
-
+	test("Stat.mean([1, 2, 3, 4, 5, 6, 7, 8, 9])");
+	test("Stat.mean([2, -6, 2, 0, 10, 9, -2, 5, -8, -11, 1, -3])");
+	test("Stat.mean([2, [-6, 2, 0], [10, [9, -2], 5], -8, [-11, 1], -3])");
+
 	test("Stat.median()");
+	test("Stat.median(3.14)");
 	test("Stat.median([1, 5, 6, 9, 13])");
+	test("Stat.median([2, -6, 2, 0, 10, 9, -2, 5, -8, -11, -3])");
+	test("Stat.median([2, [-6, 2, 0], [10, [9, -2], 5], -8, [-11], -3])");
 	test("Stat.median([1, 5, 6, 'foo', 'bar', 13,])");
 
 	test("Stat.center([1, 5, 11])");
 	test("Stat.center([1, 7, 4, 2, 9, 5])");
 	test("Stat.center([1, 7, 4, 2, 9, 5, 'foo', 'bar', true, true])");
 
+	test("Stat.mode()");
 	test("Stat.common([8, 4, 3, 11, 9, 0, 11, 2, 10, 5, 11, 0])");
 	test("Stat.common([8, 4, 3, 9, 9, 0, 2, 10, 5, 11, 0, 11])");
+	test("Stat.common([8, [4, 3], 9, [9, 0, [2, 10], 5], 11, 0, 11])");
 	test("Stat.common([8, 4, 3, 'foo', 'foo', 0, 2, 10, 5, 11, 0, 11])");
-
+
+	test("Stat.maximum()");
+	test("Stat.maximum(10)");
 	test("Stat.maximum([-38, -53, -6, 33, 88, 32, -8, 73])");
+
+	test("Stat.minimum()");
+	test("Stat.minimum(10)");
 	test("Stat.minimum([-38, -53, -6, 33, 88, 32, -8, 73])");
 	test("Stat.minimum([-38, -53, -6, 'foo', 33, 'bar'])");
-
+
+	test("Stat.change()");
+	test("Stat.change(4)");
+	test("Stat.change(['foo', 'bar'])");
 	test("Stat.change([0, 3, 7, 0, 12, 9, 5, 7])");
 }