all these changes

frontend/node_modules/density-clustering/test/DBSCAN.test.js

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+require('should');
+var DBSCAN = require('../lib/index.js').DBSCAN;
+
+describe('DBSCAN', function() {
+
+  describe('run', function() {
+    it('should return correct clusters for regular density set', function() {
+      var dbscan = new DBSCAN();
+      var dataset = [
+        [1, 1], [0, 1], [1, 0],
+        [10, 10], [10, 13], [13, 13],
+        [30, 30], [30, 33], [49, 49], [33, 33], [36, 36]
+      ];
+
+      // small radius
+      dbscan.run(dataset, 5, 2)
+        .should.be.eql([
+          [0, 1, 2],
+          [3, 4, 5],
+          [6, 7, 9, 10]
+        ]);
+
+      dbscan.noise.should.eql([8]);
+
+      // big radius
+      dbscan.run(dataset, 50, 2).should.be.eql([
+        [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 8]
+      ]);
+
+      dbscan.noise.should.eql([]);
+    });
+  });
+
+  describe('regionQuery', function() {
+    it('should return nearest neighborhood of a point', function() {
+      var dataset = [
+        [1, 1], [2, 2], [3, 3],
+        [50, 50], [51, 51]
+      ];
+      var dbscan = new DBSCAN(dataset);
+
+      dbscan.epsilon = 1;
+      dbscan._regionQuery(1).should.eql([1]);
+
+      dbscan.epsilon = 2;
+      dbscan._regionQuery(1).should.eql([0, 1, 2]);
+      dbscan._regionQuery(4).should.eql([3, 4]);
+
+      dbscan.epsilon = 100;
+      dbscan._regionQuery(1).should.eql([0, 1, 2, 3, 4]);
+    });
+  });
+
+  describe('mergeArrays', function() {
+    it('should merge two arrays', function() {
+      var dbscan = new DBSCAN();
+      dbscan._mergeArrays([1, 2, 3], [2, 3, 4, 5])
+        .should.eql([1, 2, 3, 4, 5]);
+
+      dbscan._mergeArrays([2, 3, 4, 5], [1, 2, 3])
+        .should.eql([2, 3, 4, 5, 1]);
+    });
+  });
+
+  describe('euclideanDistance', function() {
+    it('should return distance between two points', function() {
+      var dbscan = new DBSCAN();
+      dbscan._euclideanDistance([1, 1], [3, 1]).should.eql(2);
+      dbscan._euclideanDistance([1, 1], [1, 3]).should.eql(2);
+    });
+  });
+
+});

frontend/node_modules/density-clustering/test/KMEANS.test.js

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+require('should');
+var KMEANS = require('../lib/index.js').KMEANS;
+
+describe('KMEANS', function() {
+
+  describe('run', function() {
+    it('should return correct clusters', function() {
+      var kmeans = new KMEANS();
+      var k = 3;
+      var dataset = [
+        [1,1],[0,1],[1,0],
+        [10,10],[10,13],[13,13],
+        [54,54],[55,55],[89,89],[57,55]
+      ];
+
+      var clusters = kmeans.run(dataset, k);
+      clusters.should.have.lengthOf(k);
+      clusters.forEach(function(cluster) {
+        (cluster instanceof Array).should.be.true;
+        cluster.length.should.be.greaterThan(0);
+      });
+
+    });
+
+    it('should return correct clusters for high dimensional data', function() {
+      var kmeans = new KMEANS();
+      var k = 4;
+      var dataset = generateData(k, 10, 10);
+
+      var clusters = kmeans.run(dataset, k);
+      clusters.should.have.lengthOf(k);
+      clusters.forEach(function(cluster) {
+        (cluster instanceof Array).should.be.true;
+        cluster.length.should.be.greaterThan(0);
+      });
+
+    });
+
+  });
+
+  describe('randomCentroid', function() {
+    it('should return extremes', function() {
+      var dataset = [
+        [-10, -20], [0,0], [30, 20]
+      ];
+      var kmeans = new KMEANS(dataset);
+
+      var centroid = kmeans.randomCentroid();
+      centroid[0].should.be.within(-10, 30);
+      centroid[1].should.be.within(-20, 20);
+    });
+  });
+
+});
+
+function generateData(clusters, points, dimensions) {
+  var dataset = [];
+
+  for (var i = 0; i < clusters; i++) {
+    for (var p = 0; p < points; p++) {
+      var point = new Array(dimensions);
+      for (var d = 0; d < dimensions; d++) {
+        point[d] = Math.random() + (i * 100);
+      }
+      dataset.push(point);
+    }
+  }
+
+  return dataset;
+}

frontend/node_modules/density-clustering/test/OPTICS.test.js

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+require('should');
+var clustering = require('../lib/index.js');
+var OPTICS = clustering.OPTICS;
+
+describe('OPTICS', function() {
+
+  describe('run', function() {
+    it('should test regular density set', function() {
+      var dataset = [
+        [1, 1], [0, 1], [1, 0],
+        [10, 10], [10, 11], [11, 10],
+        [50, 50], [51, 50], [50, 51],
+        [100, 100]
+      ];
+
+      var optics = new OPTICS();
+      var clusters = optics.run(dataset, 2, 2);
+
+      clusters.should.be.eql([
+        [0, 1, 2],
+        [3, 4, 5],
+        [6, 7, 8],
+        [9]
+      ]);
+    });
+
+    it('should test various density set', function() {
+      var dataset = [
+        [0, 0], [6, 0], [-1, 0], [0, 1], [0, -1],
+        [45, 45], [45.1, 45.2], [45.1, 45.3], [45.8, 45.5],
+        [45.2, 45.3],
+        [50, 50], [56, 50], [50, 52], [50, 55], [50, 51]
+      ];
+      var optics = new OPTICS();
+      var clusters = optics.run(dataset, 6, 2);
+
+      clusters.should.be.eql([
+        [0, 2, 3, 4],
+        [1],
+        [5, 6, 7, 9, 8],
+        [10, 14, 12, 13],
+        [11]
+      ]);
+    });
+  });
+
+  describe('regionQuery', function() {
+    it('should return nearest neighborhood of a point', function() {
+      var optics = new OPTICS();
+      optics.dataset = [
+        [1, 1], [2, 2], [3, 3],
+        [50, 50], [51, 51]
+      ];
+      optics.epsilon = 2;
+      optics._regionQuery(1).should.eql([0, 1, 2]);
+      optics._regionQuery(4).should.eql([3, 4]);
+
+      optics.epsilon = 100;
+      optics._regionQuery(1).should.eql([0, 1, 2, 3, 4]);
+    });
+  });
+
+  describe('euclideanDistance', function() {
+    it('should return distance between two points', function() {
+      var optics = new OPTICS();
+      optics._euclideanDistance([1, 1], [3, 1]).should.eql(2);
+      optics._euclideanDistance([1, 1], [1, 3]).should.eql(2);
+    });
+  });
+
+  describe('getReachabilityPlot', function() {
+    it('should return reachability plot', function() {
+      var optics = new OPTICS();
+      var plot;
+
+      var dataset = [
+        [1, 1], [0, 1], [1, 0],
+        [10, 10], [10, 11], [11, 10]
+      ];
+
+      optics.run(dataset, 2, 2);
+      plot = optics.getReachabilityPlot();
+      plot.should.eql([
+        [0, undefined], [1, 1], [2, 1],
+        [3, undefined], [4, 1], [5, 1]
+      ]);
+
+      // reachability plot should be always the same for different epsilon values
+      optics.run(dataset, 10, 2);
+      plot = optics.getReachabilityPlot();
+      plot.should.eql([
+        [0, undefined], [1, 1], [2, 1],
+        [3, undefined], [4, 1], [5, 1]
+      ]);
+    });
+  });
+
+});

frontend/node_modules/density-clustering/test/PriorityQueue.test.js

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+require('should');
+var PriorityQueue = require('../lib/index.js').PriorityQueue;
+
+describe('PriorityQueue', function() {
+
+  describe('insert', function() {
+    it('should return correct result', function() {
+      var p = new PriorityQueue();
+      p.insert(1, 4);
+      p.insert(2, 1);
+      p.insert(3, 2);
+      p.insert(4, 3);
+
+      p.getElements().should.eql([1, 4, 3, 2]);
+      p.getPriorities().should.eql([4, 3, 2, 1]);
+    });
+  });
+
+  describe('init', function() {
+    it('should initialize queue correctly', function() {
+      var p = new PriorityQueue([1, 2, 3, 4], [4, 1, 2, 3]);
+
+      p.getElements().should.eql([1, 4, 3, 2]);
+      p.getPriorities().should.eql([4, 3, 2, 1]);
+    });
+  });
+});