skmeans - npm Package Compare versions

Comparing version 0.8.0 to 0.8.1

browser.js

@@ -0,0 +0,0 @@ "use strict";

dist/skmeans.js

@@ -0,0 +0,0 @@ "use strict";

dist/skmeans.min.js

 /*! skmeans 2017-07-17 */
 
 "use strict";!function r(n,t,o){function a(f,i){if(!t[f]){if(!n[f]){var u="function"==typeof require&&require;if(!i&&u)return u(f,!0);if(e)return e(f,!0);var v=new Error("Cannot find module '"+f+"'");throw v.code="MODULE_NOT_FOUND",v}var c=t[f]={exports:{}};n[f][0].call(c.exports,function(r){var t=n[f][1][r];return a(t||r)},c,c.exports,r,n,t,o)}return t[f].exports}for(var e="function"==typeof require&&require,f=0;f<o.length;f++)a(o[f]);return a}({1:[function(r,n,t){!function(n){var t=r("./main.js");n.skmeans=t}(window)},{"./main.js":2}],2:[function(r,n,t){function o(r,n,t){for(var o=r.length,a=0,e=0;e<o;e++){var f=(r[e]||0)-(n[e]||0);a+=f*f}return t?Math.sqrt(a):a}function a(r,n,t){var o=Math.abs(r-n);return t?o:o*o}function e(r,n){var t=this,e=r[0].length?o:a,f=[],i=r.length,u=r[Math.floor(Math.random()*i)];f.push(u);for(;f.length<n;)!function(){var n=r.map(function(r){var n=f.map(function(n){return e(r,n)});return Math.min.apply(t,n)}),o=n.reduce(function(r,n){return r+n},0),a=n.map(function(n,t){return{i:t,v:r[t],pr:n/o}});a.sort(function(r,n){return r.pr-n.pr}),a.forEach(function(r,n){r.cs=r.pr+(n>0?a[n-1].cs:0)});var i=Math.random(),u=a.filter(function(r){return r.cs>=i});f.push(u[0].v)}();return f}function f(r,n,t){t=t||[];for(var o=0;o<r;o++)t[o]=n;return t}var i=1e4;n.exports=function(r,n,t,a){var u=[],v=[],c=[],s=[],h=!1,p=a||i,l=r.length,m=r[0].length,d=m>0;if(t)u="kmpp"==t?e(r,n):t;else for(var M=0;M<n;M++)u.push(r[Math.floor(Math.random()*l)]);do{for(var g=0;g<l;g++){for(var x=1/0,k=0,q=0;q<n;q++)(s=d?o(r[g],u[q]):Math.abs(r[g]-u[q]))<x&&(x=s,k=q);c[g]=k}for(var w=[],b=[],v=[],y=0;y<n;y++)w[y]=0,b[y]=d?f(m,0,b[y]):0,v[y]=u[y];if(d){for(var E=0;E<n;E++)u[E]=[];for(var O=0;O<l;O++){for(var j=c[O],D=b[j],N=r[O],U=0;U<m;U++)D[U]+=N[U];w[j]++}h=!0;for(var _=0;_<n;_++){for(var C=u[_],F=b[_],L=v[_],T=w[_],z=0;z<m;z++)C[z]=F[z]/T||0;if(h)for(var A=0;A<m;A++)if(L[A]!=C[A]){h=!1;break}}}else{for(var B=0;B<l;B++){var G=c[B];b[G]+=r[B],w[G]++}for(var H=0;H<n;H++)u[H]=b[H]/w[H]||0;h=!0;for(var I=0;I<n;I++)if(v[I]!=u[I]){h=!1;break}}h=h||--p<=0}while(!h);return{it:i-p,k:n,idxs:c,centroids:u}}},{}]},{},[1]);

Gruntfile.js

@@ -0,0 +0,0 @@ module.exports = function(grunt) {

main.js

@@ -28,2 +28,33 @@ /*jshint esversion: 6 */
 
+function kmrand(data,k) {
+	var map = {}, list = [];
+	var ks = [];
+
+	data.forEach(d=>{
+		var key = JSON.stringify(d);
+		map[key] = map[k]||d;
+	});
+	for(var key in map) list.push(map[key]);
+	if(k>list.length) {
+		throw new Error("Cluster size greater than distinct data points");
+	}
+	else {
+		var len = data.length, map = {};
+		for(let i=0;i<k;i++) {
+			var b = false;
+			while(!b) {
+				var v = list[Math.floor(Math.random()*len)];
+				var key = JSON.stringify(v);
+				if(!map[key]) {
+					ks.push(v);
+					map[key] = true;
+					b = true;
+				}
+			}
+		}
+	}
+
+	return ks;
+}
+
 /**
@@ -85,6 +116,8 @@ * K-means++ initial centroid selection
 	if(!initial) {
-		for(let i=0;i<k;i++) {
+		for(let i=0;i<k;i++)
 			ks.push(data[Math.floor(Math.random()*len)]);
-		}
 	}
+	else if(initial=="kmrand") {
+		ks = kmrand(data,k);
+	}
 	else if(initial=="kmpp") {
@@ -104,3 +137,3 @@ ks = kmpp(data,k);
 				var dist = multi? eudist(data[i],ks[j]) : Math.abs(data[i]-ks[j]);
-				if(dist<min) {
+				if(dist<=min) {
 					min = dist;
@@ -130,3 +163,3 @@ idx = j;
 					vsum = sum[idx],	// Sum values for this centroid
-					vect = data[i];		// Current vector
+					vect = data[idx];	// Current vector
 
@@ -150,2 +183,3 @@ // Accumulate value on the centroid for current vector
 					ksj[h] = sumj[h]/cj || 0;	// New centroid
+					if(ksj[h]==0) debugger;
 				}
@@ -152,0 +186,0 @@ // Find if centroids have moved

package.json

 {
   "name": "skmeans",
-  "version": "0.8.0",
+  "version": "0.8.1",
   "description": "Super fast simple kmeans clustering for unidimiensional and multidimensional data. Works in node and browser",
@@ -5,0 +5,0 @@ "author": "David Gómez Matarrodona <[e-mail]>",

README.md

@@ -53,3 +53,5 @@ # skmeans
 * **k** Number of clusters
-* **centroids** Optional. Initial centroid values. If not provided, the algorith will try to choose an apropiate ones. You can pass **"kmpp"** as argument, so the algorythm will use the [k-means++](https://en.wikipedia.org/wiki/K-means%2B%2B) cluster initialization method.
+* **centroids** Optional. Initial centroid values. If not provided, the algorith will try to choose an apropiate ones. Alternative values can be:
+  * **"kmrand"** Cluster initialization will be random, but with extra checking, so there will no be two equal initial centroids.
+  * **"kmpp"** The algorythm will use the [k-means++](https://en.wikipedia.org/wiki/K-means%2B%2B) cluster initialization method.
 * **iterations** Optional. Maximum number of iterations. If not provided, it will be set to 10000.
@@ -56,0 +58,0 @@

test/multi.js

@@ -0,0 +0,0 @@ const skmeans = require("../main.js");

test/test.js

@@ -0,0 +0,0 @@ const skmeans = require("../main.js");

test/uni.js

@@ -0,0 +0,0 @@ const skmeans = require("../main.js");

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Improved metrics

Total package byte prevSize

165206

increased by431.47%

Number of package files

17

increased by21.43%

Lines of code

3731

increased by662.99%

Number of lines in readme file

63

increased by3.28%

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Number of medium supply chain risk alerts

1

increased byInfinity%

No dependency changes