skmeans - npm Package Compare versions

Comparing version 0.5.2 to 0.6.0

dist/skmeans.js

@@ -57,6 +57,6 @@ "use strict";
    */
-		function init(len, val) {
-			var v = [];
+		function init(len, val, v) {
+			v = v || [];
 			for (var i = 0; i < len; i++) {
-				v.push(val);
+				v[i] = val;
 			}return v;
@@ -66,4 +66,2 @@ }
 		function skmeans(data, k, initial, maxit) {
-			"use strict";
-
 			var ks = [],
@@ -74,3 +72,4 @@ idxs = [],
 			    it = maxit || MAX;
-			var multi = data[0].length;
+			var vlen = data[0].length,
+			    multi = vlen > 0;
 
@@ -109,3 +108,3 @@ if (!initial) {
 					count[_j] = 0;
-					sum[_j] = multi ? init(multi, 0) : 0;
+					sum[_j] = multi ? init(vlen, 0, sum[_j]) : 0;
 					old[_j] = ks[_j];
@@ -120,14 +119,31 @@ }
 					for (var _i2 = 0; _i2 < len; _i2++) {
-						for (var h = 0; h < multi; h++) {
-							sum[idxs[_i2]][h] += data[_i2][h];
+						var _idx = idxs[_i2],
+						    vsum = sum[_idx],
+						    vect = data[_i2];
+						for (var h = 0; h < vlen; h++) {
+							vsum[h] += vect[h];
 						}
-						count[idxs[_i2]]++;
+						count[_idx]++;
 					}
 					// Calculate de average for each centroid
 					// and de distance between old and new centroids
+					conv = true;
 					for (var _j3 = 0; _j3 < k; _j3++) {
-						for (var _h = 0; _h < multi; _h++) {
-							ks[_j3][_h] = sum[_j3][_h] / count[_j3] || 0;
-							dif += old[_j3][_h] - ks[_j3][_h];
+						var ksj = ks[_j3],
+						    sumj = sum[_j3],
+						    oldj = old[_j3],
+						    cj = count[_j3];
+						// New average
+						for (var _h = 0; _h < vlen; _h++) {
+							ksj[_h] = sumj[_h] / cj || 0;
 						}
+						// Find if centroids have moved
+						if (conv) {
+							for (var _h2 = 0; _h2 < vlen; _h2++) {
+								if (oldj[_h2] != ksj[_h2]) {
+									conv = false;
+									break;
+								}
+							}
+						}
 					}
@@ -146,7 +162,14 @@ }
 							ks[_j4] = sum[_j4] / count[_j4] || 0;
-							dif += old[_j4] - ks[_j4];
 						}
+						// Find if centroids have moved
+						conv = true;
+						for (var _j5 = 0; _j5 < k; _j5++) {
+							if (old[_j5] != ks[_j5]) {
+								conv = false;
+								break;
+							}
+						}
 					}
 
-				conv = dif === 0 || --it <= 0;
+				conv = conv || --it <= 0;
 			} while (!conv);
@@ -153,0 +176,0 @@

dist/skmeans.min.js

@@ -1,3 +0,3 @@
-/*! skmeans 2017-06-08 */
+/*! skmeans 2017-06-18 */
 
-"use strict";!function r(n,o,t){function e(a,i){if(!o[a]){if(!n[a]){var u="function"==typeof require&&require;if(!i&&u)return u(a,!0);if(f)return f(a,!0);var v=new Error("Cannot find module '"+a+"'");throw v.code="MODULE_NOT_FOUND",v}var s=o[a]={exports:{}};n[a][0].call(s.exports,function(r){var o=n[a][1][r];return e(o||r)},s,s.exports,r,n,o,t)}return o[a].exports}for(var f="function"==typeof require&&require,a=0;a<t.length;a++)e(t[a]);return e}({1:[function(r,n,o){!function(n){var o=r("./main.js");n.skmeans=o}(window)},{"./main.js":2}],2:[function(r,n,o){function t(r,n){for(var o=r.length,t=0,e=0;e<o;e++){var f=(r[e]||0)-(n[e]||0);t+=f*f}return Math.sqrt(t)}function e(r,n){for(var o=[],t=0;t<r;t++)o.push(n);return o}function f(r,n,o,f){var i=[],u=[],v=r.length,s=!1,c=f||a,h=r[0].length;if(o)i=o;else for(var l=0;l<n;l++)i.push(r[Math.floor(Math.random()*v)]);do{for(var p=0;p<v;p++){for(var d=1/0,x=0,m=0;m<n;m++){var q=h?t(r[p],i[m]):Math.abs(r[p]-i[m]);q<d&&(d=q,x=m)}u[p]=x}for(var w=[],M=[],g=[],O=0,j=0;j<n;j++)w[j]=0,M[j]=h?e(h,0):0,g[j]=i[j];if(h){for(var k=0;k<n;k++)i[k]=[];for(var y=0;y<v;y++){for(var D=0;D<h;D++)M[u[y]][D]+=r[y][D];w[u[y]]++}for(var E=0;E<n;E++)for(var N=0;N<h;N++)i[E][N]=M[E][N]/w[E]||0,O+=g[E][N]-i[E][N]}else{for(var U=0;U<v;U++)M[u[U]]+=r[U],w[u[U]]++;for(var _=0;_<n;_++)i[_]=M[_]/w[_]||0,O+=g[_]-i[_]}s=0===O||--c<=0}while(!s);return{it:a-c,k:n,idxs:u,centroids:i}}var a=1e4;n.exports=f},{}]},{},[1]);
+"use strict";!function r(o,n,e){function t(a,i){if(!n[a]){if(!o[a]){var u="function"==typeof require&&require;if(!i&&u)return u(a,!0);if(f)return f(a,!0);var v=new Error("Cannot find module '"+a+"'");throw v.code="MODULE_NOT_FOUND",v}var s=n[a]={exports:{}};o[a][0].call(s.exports,function(r){var n=o[a][1][r];return t(n||r)},s,s.exports,r,o,n,e)}return n[a].exports}for(var f="function"==typeof require&&require,a=0;a<e.length;a++)t(e[a]);return t}({1:[function(r,o,n){!function(o){var n=r("./main.js");o.skmeans=n}(window)},{"./main.js":2}],2:[function(r,o,n){function e(r,o){for(var n=r.length,e=0,t=0;t<n;t++){var f=(r[t]||0)-(o[t]||0);e+=f*f}return Math.sqrt(e)}function t(r,o,n){n=n||[];for(var e=0;e<r;e++)n[e]=o;return n}var f=1e4;o.exports=function(r,o,n,a){var i=[],u=[],v=r.length,s=!1,c=a||f,h=r[0].length,l=h>0;if(n)i=n;else for(var d=0;d<o;d++)i.push(r[Math.floor(Math.random()*v)]);do{for(var p=0;p<v;p++){for(var x=1/0,m=0,q=0;q<o;q++){var w=l?e(r[p],i[q]):Math.abs(r[p]-i[q]);w<x&&(x=w,m=q)}u[p]=m}for(var M=[],g=[],k=[],b=0;b<o;b++)M[b]=0,g[b]=l?t(h,0,g[b]):0,k[b]=i[b];if(l){for(var O=0;O<o;O++)i[O]=[];for(var j=0;j<v;j++){for(var y=u[j],D=g[y],E=r[j],N=0;N<h;N++)D[N]+=E[N];M[y]++}s=!0;for(var U=0;U<o;U++){for(var _=i[U],C=g[U],F=k[U],L=M[U],T=0;T<h;T++)_[T]=C[T]/L||0;if(s)for(var z=0;z<h;z++)if(F[z]!=_[z]){s=!1;break}}}else{for(var A=0;A<v;A++)g[u[A]]+=r[A],M[u[A]]++;for(var B=0;B<o;B++)i[B]=g[B]/M[B]||0;s=!0;for(var G=0;G<o;G++)if(k[G]!=i[G]){s=!1;break}}s=s||--c<=0}while(!s);return{it:f-c,k:o,idxs:u,centroids:i}}},{}]},{},[1]);

main.js

@@ -35,5 +35,5 @@ /*jshint esversion: 6 */
  */
-function init(len,val) {
-	var v = [];
-	for(let i=0;i<len;i++) v.push(val);
+function init(len,val,v) {
+	v = v || [];
+	for(let i=0;i<len;i++) v[i] = val;
 	return v;
@@ -45,3 +45,3 @@ }
 	var conv = false, it = maxit || MAX;
-	var multi = data[0].length;
+	var vlen = data[0].length, multi = vlen>0;
 
@@ -77,3 +77,3 @@ if(!initial) {
 			count[j] = 0;
-			sum[j] = multi? init(multi,0) : 0;
+			sum[j] = multi? init(vlen,0,sum[j]) : 0;
 			old[j] = ks[j];
@@ -88,14 +88,26 @@ }
 			for(let i=0;i<len;i++) {
-				for(let h=0;h<multi;h++) {
-					sum[idxs[i]][h] += data[i][h];
+				let idx = idxs[i], vsum = sum[idx], vect = data[i];
+				for(let h=0;h<vlen;h++) {
+					vsum[h] += vect[h];
 				}
-				count[idxs[i]]++;
+				count[idx]++;
 			}
 			// Calculate de average for each centroid
 			// and de distance between old and new centroids
+			conv = true;
 			for(let j=0;j<k;j++) {
-				for(let h=0;h<multi;h++) {
-					ks[j][h] = sum[j][h]/count[j] || 0;
-					dif += old[j][h] - ks[j][h];
+				let ksj = ks[j], sumj = sum[j],oldj = old[j], cj = count[j];
+				// New average
+				for(let h=0;h<vlen;h++) {
+					ksj[h] = sumj[h]/cj || 0;
 				}
+				// Find if centroids have moved
+				if(conv) {
+					for(let h=0;h<vlen;h++) {
+						if(oldj[h]!=ksj[h]) {
+							conv = false;
+							break;
+						}
+					}
+				}
 			}
@@ -114,7 +126,14 @@ }
 				ks[j] = sum[j]/count[j] || 0;
-				dif += old[j] - ks[j];
 			}
+			// Find if centroids have moved
+			conv = true;
+			for(let j=0;j<k;j++) {
+				if(old[j]!=ks[j]) {
+					conv = false;
+					break;
+				}
+			}
 		}
 
-		conv = (dif===0) || (--it<=0);
+		conv = conv || (--it<=0);
 	}while(!conv);
@@ -121,0 +140,0 @@

package.json

 {
   "name": "skmeans",
-  "version": "0.5.2",
+  "version": "0.6.0",
   "description": "Super fast simple kmeans clustering for unidimiensional data",
@@ -5,0 +5,0 @@ "author": "David Gómez Matarrodona <[e-mail]>",

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Improved metrics

Total package byte prevSize

24327

increased by9.02%

Lines of code

395

increased by12.22%

No dependency changes