stats-lite - npm Package Compare versions

Comparing version 1.0.3 to 2.0.0

package.json

 {
   "name": "stats-lite",
-  "version": "1.0.3",
+  "version": "2.0.0",
   "description": "A light statistical package that operates on numeric Arrays.",
   "main": "stats.js",
   "directories": {
+    "example": "examples",
     "test": "test"
@@ -35,2 +36,5 @@ },
   },
+  "engines": {
+    "node": ">=2.0.0"
+  },
   "dependencies": {
@@ -40,4 +44,5 @@ "isnumber": "~1.0.0"
   "devDependencies": {
-    "tape": "~2.10.2"
-  }
+    "tape": "~4.2.0"
+  },
+  "homepage": "https://github.com/brycebaril/node-stats-lite"
 }

README.md

@@ -43,2 +43,4 @@ stats-lite
 
+**Compatibility Notice**: Version 2.0.0+ of this library use features that require Node.js v4.0.0 and above
+
 API
@@ -69,3 +71,3 @@ ===
 
-Calculate the [mean](http://en.wikipedia.org/wiki/Mean) average value of vals.
+Calculate the [mean](http://en.wikipedia.org/wiki/Mean) average value of `vals`.
 
@@ -75,3 +77,3 @@ `median(vals)`
 
-Calculate the [median](http://en.wikipedia.org/wiki/Median) average value of vals.
+Calculate the [median](http://en.wikipedia.org/wiki/Median) average value of `vals`.
 
@@ -81,4 +83,6 @@ `mode(vals)`
 
-Calculate the [mode](http://en.wikipedia.org/wiki/Mode_statistics) average value of vals.
+Calculate the [mode](http://en.wikipedia.org/wiki/Mode_statistics) average value of `vals`.
 
+If `vals` is multi-modal (contains multiple modes), `mode(vals)` will return a ES6 Set of the modes.
+
 `variance(vals)`
@@ -85,0 +89,0 @@ ---

stats.js

@@ -0,1 +1,3 @@
+"use strict";
+
 module.exports.numbers = numbers
@@ -10,10 +12,10 @@ module.exports.sum = sum
 
-var isNumber = require("isnumber")
+const isNumber = require("isnumber")
 
 function numbers(vals) {
-  var nums = []
+  let nums = []
   if (vals == null)
     return nums
 
-  for (var i = 0; i < vals.length; i++) {
+  for (let i = 0; i < vals.length; i++) {
     if (isNumber(vals[i]))
@@ -26,3 +28,3 @@ nums.push(+vals[i])
 function nsort(vals) {
-  return vals.sort(function (a, b) { return a - b })
+  return vals.sort(function numericSort(a, b) { return a - b })
 }
@@ -32,4 +34,4 @@
   vals = numbers(vals)
-  var total = 0
-  for (var i = 0; i < vals.length; i++) {
+  let total = 0
+  for (let i = 0; i < vals.length; i++) {
     total += vals[i]
@@ -50,3 +52,3 @@ }
 
-  var half = (vals.length / 2) | 0
+  let half = (vals.length / 2) | 0
 
@@ -64,18 +66,36 @@ vals = nsort(vals)
 
-// Returns the mode of a unimodal dataset -- NaN for multi-modal or empty datasets.
+// Returns the mode of a unimodal dataset
+// If the dataset is multi-modal, returns a Set containing the modes
 function mode(vals) {
   vals = numbers(vals)
   if (vals.length === 0) return NaN
-  var mode = NaN
-  var dist = {}
-  vals.forEach(function (n) {
-    var me = dist[n] || 0
+  let mode = NaN
+  let dist = {}
+
+  for (let i = 0; i < vals.length; i++) {
+    let value = vals[i]
+    let me = dist[value] || 0
     me++
-    dist[n] = me
-  })
-  var rank = numbers(Object.keys(dist).sort(function (a, b) { return dist[b] - dist[a] }))
+    dist[value] = me
+  }
+
+  let rank = numbers(Object.keys(dist).sort(function sortMembers(a, b) { return dist[b] - dist[a] }))
   mode = rank[0]
   if (dist[rank[1]] == dist[mode]) {
-    // Multiple modes found, abort
-    return NaN
+    // multi-modal
+    if (rank.length == vals.length) {
+      // all values are modes
+      return vals
+    }
+    let modes = new Set([mode])
+    let modeCount = dist[mode]
+    for (let i = 1; i < rank.length; i++) {
+      if (dist[rank[i]] == modeCount) {
+        modes.add(rank[i])
+      }
+      else {
+        break
+      }
+    }
+    return modes
   }
@@ -88,5 +108,5 @@ return mode
   vals = numbers(vals)
-  var avg = mean(vals)
-  var diffs = []
-  for (var i = 0; i < vals.length; i++) {
+  let avg = mean(vals)
+  let diffs = []
+  for (let i = 0; i < vals.length; i++) {
     diffs.push(Math.pow((vals[i] - avg), 2))
@@ -109,8 +129,8 @@ }
   vals = nsort(vals)
-  var i = (vals.length * ptile) - 0.5
+  let i = (vals.length * ptile) - 0.5
   if ((i | 0) === i) return vals[i]
   // interpolated percentile -- using Estimation method
-  var int_part = i | 0
-  var fract = i - int_part
+  let int_part = i | 0
+  let fract = i - int_part
   return (1 - fract) * vals[int_part] + fract * vals[int_part + 1]
-}
+}

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Improved metrics

Total package byte prevSize

7631

increased by10.85%

Lines of code

112

increased by19.15%

Number of low quality alerts

0

decreased by-100%

Number of lines in readme file

103

increased by4.04%

Worsened metrics

Number of package files

4

decreased by-20%

No dependency changes