array-normalize - npm Package Compare versions

Comparing version 1.1.1 to 1.1.2

index.js

 'use strict'
 
+var getBounds = require('array-bounds')
+
 module.exports = normalize;
 
-function normalize (arr, dim) {
+function normalize (arr, dim, bounds) {
 	if (!arr || arr.length == null) throw Error('Argument should be an array')
 
 	if (dim == null) dim = 1
+	if (bounds == null) bounds = getBounds(arr, dim)
 
 	for (var offset = 0; offset < dim; offset++) {
-		var max = -Infinity, min = Infinity, i = offset, l = arr.length;
+		var max = bounds[dim + offset], min = bounds[offset], i = offset, l = arr.length;
 
-		for (; i < l; i+=dim) {
-			if (arr[i] > max) max = arr[i];
-			if (arr[i] < min) min = arr[i];
-		}
-
 		if (max === Infinity && min === -Infinity) {
@@ -19,0 +17,0 @@ for (i = offset; i < l; i+=dim) {

package.json

 {
   "name": "array-normalize",
-  "version": "1.1.1",
+  "version": "1.1.2",
   "description": "Normalize array (possibly n-dimensional) to zero mean and unit variance",
@@ -25,3 +25,6 @@ "main": "index.js",
   },
-  "homepage": "https://github.com/dfcreative/array-normalize#readme"
+  "homepage": "https://github.com/dfcreative/array-normalize#readme",
+  "dependencies": {
+    "array-bounds": "^1.0.0"
+  }
 }

readme.md

 # 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)
 
-Normalize array in-place to zero mean and unit variance.
+Normalize array to unit length, that is 0..1 range. See [feature scaling](https://en.wikipedia.org/wiki/Feature_scaling).
 
@@ -15,4 +15,4 @@ [![npm install array-normalize](https://nodei.co/npm/array-normalize.png?mini=true)](https://npmjs.org/package/array-normalize/)
 
-### array = normalize(array, n=1)
+### array = normalize(array, n=1, bounds?)
 
-Normalizes n-dimensional array in-place using dimensions `n` as stride, ie. for 1d array the expected data layout is `[x, x, x, ...]` for 2d is `[x, y, x, y, ...]`, etc. Every dimension is normalized independently, so 2d array is normalized to unit square `[0, 0, 1, 1]`.
+Normalizes n-dimensional array in-place using dimensions `n` as stride, ie. for 1d array the expected data layout is `[x, x, x, ...]` for 2d is `[x, y, x, y, ...]`, etc. Every dimension is normalized independently, so 2d array is normalized to unit square `[0, 0, 1, 1]`. Optionally pass `bounds` box if you know min/max values to optimize calculations.

test.js

@@ -5,2 +5,3 @@ 'use strict'
 const assert = require('assert')
+const getBounds = require('array-bounds')
 
@@ -18,1 +19,4 @@ let a = [-Infinity, -1, 0, 1, Infinity]
 assert.deepEqual(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])

No alert changes

Improved metrics

Total package byte prevSize

4704

increased by9.02%

Number of package files

7

increased by16.67%

Lines of code

91

increased by1.11%

Worsened metrics

Dependency count

1

increased byInfinity%

Dependency changes

• + Addedarray-bounds@^1.0.0

• + Addedarray-bounds@1.0.1(transitive)