skmeans - npm Package Compare versions

Comparing version 0.8.3 to 0.8.4

browser.js

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

dist/skmeans.js

@@ -53,25 +53,24 @@ "use strict";
 			    list = [];
-			var ks = [];
+			var ks = [],
+			    len = data.length;
 
-			data.forEach(function (d) {
+			for (var i = 0; i < len; i++) {
+				var d = data[i];
 				var key = JSON.stringify(d);
-				map[key] = map[k] || d;
-			});
-			for (var key in map) {
-				list.push(map[key]);
-			}if (k > list.length) {
+				if (!map[key]) {
+					map[key] = true;
+					list.push(d);
+				}
+			};
+
+			if (k > list.length) {
 				throw new Error("Cluster size greater than distinct data points");
 			} else {
-				var len = data.length,
-				    map = {};
-				for (var 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;
-						}
+				var l = list.length,
+				    m = {};
+				while (ks.length < k) {
+					var idx = Math.floor(Math.random() * l);
+					if (!m[idx]) {
+						m[idx] = true;
+						ks.push(list[idx]);
 					}
@@ -81,2 +80,3 @@ }
 
+			console.log(ks);
 			return ks;
@@ -83,0 +83,0 @@ }

dist/skmeans.min.js

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

Gruntfile.js

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

main.js

@@ -30,9 +30,13 @@ /*jshint esversion: 6 */
 	var map = {}, list = [];
-	var ks = [];
+	var ks = [], len = data.length
 
-	data.forEach(d=>{
+	for(let i=0;i<len;i++) {
+		let d = data[i];
 		var key = JSON.stringify(d);
-		map[key] = map[k]||d;
-	});
-	for(var key in map) list.push(map[key]);
+		if(!map[key]) {
+			map[key] = true;
+			list.push(d);
+		}
+	};
+
 	if(k>list.length) {
@@ -42,13 +46,8 @@ 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;
-				}
+		let l = list.length, m = {};
+		while(ks.length<k) {
+			let idx = Math.floor(Math.random()*l);
+			if(!m[idx]) {
+				m[idx] = true;
+				ks.push(list[idx]);
 			}
@@ -58,2 +57,3 @@ }
 
+	console.log(ks);
 	return ks;
@@ -60,0 +60,0 @@ }

package.json

 {
   "name": "skmeans",
-  "version": "0.8.3",
+  "version": "0.8.4",
   "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

@@ -0,0 +0,0 @@ # skmeans

test/multi.js

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

test/random.js

@@ -5,4 +5,4 @@ const skmeans = require("../main.js");
 for(var i=0;i<1000;i++) {
-	var res = skmeans(data,16);
-	console.log(res.it,res.centroids,"kmpp");
+	var res = skmeans(data,16,"kmrand");
+	console.log(res.it,res.centroids);
 }

test/test.js

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

test/uni.js

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

New alerts

Major refactor

Supply chain risk

Package has recently undergone a major refactor. It may be unstable or indicate significant internal changes. Use caution when updating to versions that include significant changes.

Found 1 instance in 1 package

Worsened metrics

Total package byte prevSize

54390

-67.67%

Number of package files

16

-5.88%

Lines of code

555

-85.25%

Number of medium supply chain risk alerts

1

Infinity%

No dependency changes