array-normalize - npm Package Compare versions

Comparing version 1.1.4 to 2.0.0

index.js

@@ -14,26 +14,21 @@ 'use strict'
 	for (var offset = 0; offset < dim; offset++) {
-		var max = bounds[dim + offset], min = bounds[offset], i = offset, l = arr.length;
+		var max = bounds[dim + offset], min = bounds[offset], i = offset, l = arr.length, range;
 
 		if (max === Infinity && min === -Infinity) {
-			for (i = offset; i < l; i+=dim) {
-				arr[i] = arr[i] === max ? 1 : arr[i] === min ? 0 : .5
-			}
+			for (i = offset; i < l; i+=dim) arr[i] = arr[i] === max ? 1 : arr[i] === min ? 0 : .5
 		}
 		else if (max === Infinity) {
-			for (i = offset; i < l; i+=dim) {
-				arr[i] = arr[i] === max ? 1 : 0
-			}
+			for (i = offset; i < l; i+=dim) arr[i] = arr[i] === max ? 1 : 0
 		}
 		else if (min === -Infinity) {
-			for (i = offset; i < l; i+=dim) {
-				arr[i] = arr[i] === min ? 0 : 1
-			}
+			for (i = offset; i < l; i+=dim) arr[i] = arr[i] === min ? 0 : 1
 		}
+		else if (min === max) {
+			for (i = offset; i < l; i+=dim) if (!isNaN(arr[i])) arr[i] =  .5
+		}
+		else if (min === 0) {
+			for (i = offset; i < l; i+=dim) arr[i] = arr[i] / max
+		}
 		else {
-			var range = max - min
-			for (i = offset; i < l; i+=dim) {
-				if (!isNaN(arr[i])) {
-					arr[i] = range === 0 ? .5 : (arr[i] - min) / range
-				}
-			}
+			for (i = offset, range = max - min; i < l; i+=dim) arr[i] = (arr[i] - min) / range
 		}
@@ -40,0 +35,0 @@ }

package.json

 {
   "name": "array-normalize",
-  "version": "1.1.4",
+  "version": "2.0.0",
   "description": "Normalize array (possibly n-dimensional) to zero mean and unit variance",
   "main": "index.js",
+  "browser": "index.js",
+  "module": "./index.mjs",
+  "exports": {
+    "require": "./index.js",
+    "import": "./index.mjs"
+  },
   "scripts": {
@@ -11,3 +17,3 @@ "test": "node test"
     "type": "git",
-    "url": "git+https://github.com/dfcreative/array-normalize.git"
+    "url": "git+https://github.com/dy/array-normalize.git"
   },
@@ -21,8 +27,8 @@ "keywords": [
   ],
-  "author": "Dima Yv <[e-mail]>",
+  "author": "Dima Iv <[e-mail]>",
   "license": "MIT",
   "bugs": {
-    "url": "https://github.com/dfcreative/array-normalize/issues"
+    "url": "https://github.com/dy/array-normalize/issues"
   },
-  "homepage": "https://github.com/dfcreative/array-normalize#readme",
+  "homepage": "https://github.com/dy/array-normalize#readme",
   "dependencies": {
@@ -29,0 +35,0 @@ "array-bounds": "^1.0.0"

readme.md

@@ -1,2 +0,2 @@
-# array-normalize  [![experimental](https://img.shields.io/badge/stability-unstable-yellow.svg)](http://github.com/badges/stability-badges) [![Build Status](https://img.shields.io/travis/dfcreative/array-normalize.svg)](https://travis-ci.org/dfcreative/array-normalize)
+# array-normalize  [![experimental](https://img.shields.io/badge/stability-unstable-yellow.svg)](http://github.com/badges/stability-badges) [![Build Status](https://img.shields.io/travis/dy/array-normalize.svg)](https://travis-ci.com/dy/array-normalize)
 
@@ -17,8 +17,10 @@ Normalize array to unit length, that is 0..1 range. See [feature scaling](https://en.wikipedia.org/wiki/Feature_scaling).
 
-### array = normalize(array, dimensions=1, bounds?)
+### array = normalize(array, stride=1, bounds?)
 
-Normalizes n-dimensional array in-place using `dimensions` as stride, ie. for 1d array the expected data layout is `[x, x, x, ...]` for 2d is `[x, y, x, y, ...]`, etc.
+Normalizes n-dimensional array in-place using optional stride for n-dimensions, ie. for 2d data layout is `[x, y, x, y, ...]`.
 
 Every dimension is normalized independently, eg. 2d array is normalized to unit square `[0, 0, 1, 1]`.
 
-Optional `bounds` box can predefine min/max to optimize calculations.
+Optional `bounds` box can predefine min/max to skip bounds detection.
+
+<p align="center">ॐ</p>

test.js

 'use strict'
 
-const norm = require('./')
+const norm = require('.')
 const assert = require('assert')
@@ -8,20 +8,20 @@ const getBounds = require('array-bounds')
 let a = [-Infinity, -1, 0, 1, Infinity]
-assert.deepEqual(norm(a.slice()), [0, 0.5, 0.5, 0.5, 1])
+assert.deepStrictEqual(norm(a.slice()), [0, 0.5, 0.5, 0.5, 1])
 
 let b = [0, .5, 1]
-assert.deepEqual(norm(b.slice()), b)
+assert.deepStrictEqual(norm(b.slice()), b)
 
 let c = [0, 50, 100]
-assert.deepEqual(norm(c.slice()), [0, .5, 1])
+assert.deepStrictEqual(norm(c.slice()), [0, .5, 1])
 
 let d = [0, 0, .1, .2, 1, 2]
-assert.deepEqual(norm(d.slice(), 2), [0, 0, .1, .1, 1, 1])
+assert.deepStrictEqual(norm(d.slice(), 2), [0, 0, .1, .1, 1, 1])
 
 let e = [0, 0, .1, .2, 1, 2]
-assert.deepEqual(norm(e.slice(), 2, getBounds(e, 2)), [0, 0, .1, .1, 1, 1])
+assert.deepStrictEqual(norm(e.slice(), 2, getBounds(e, 2)), [0, 0, .1, .1, 1, 1])
 
 let f = [0, .25, 1, .25]
-assert.deepEqual(norm(f, 2, [0, .5, 1, .5]), [0, .5, 1, .5])
+assert.deepStrictEqual(norm(f, 2, [0, .5, 1, .5]), [0, .5, 1, .5])
 
 let g = [0, 0, NaN, NaN, 1, 1]
-assert.deepEqual(norm(g, 2).map(v => isNaN(v) ? -1 : v), [0, 0, -1, -1, 1, 1])
+assert.deepStrictEqual(norm(g, 2).map(v => isNaN(v) ? -1 : v), [0, 0, -1, -1, 1, 1])

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Improved metrics

Total package byte prevSize

7192

increased by39.65%

Number of package files

8

increased by33.33%

Lines of code

138

increased by42.27%

Number of lines in readme file

26

increased by8.33%

Worsened metrics

Number of medium supply chain risk alerts

1

increased byInfinity%

No dependency changes