แก้ coding style ภาค 10

examples/js/algos/hybrid.js

@@ -1,10 +1,10 @@
 /**
  * Initialize the hybrid layout algorithm and start simulation.
  */
-function startHybridSimulation() {
+function startHybridSimulation () {
-  console.log("startHybridSimulation");
+  console.log('startHybridSimulation');
   springForce = false;
-  d3.selectAll(".nodes").remove();
+  d3.selectAll('.nodes').remove();
   manualStop = false;
   simulation.stop();
   p1 = performance.now();
@@ -17,33 +17,33 @@ function startHybridSimulation() {
     .neighbourSize(NEIGHBOUR_SIZE)
     .sampleSize(SAMPLE_SIZE)
     .stableVelocity(0) // Change here
-    .distance(distance)
+    .distance(distance);
 
   let forceFull = d3.forceNeighbourSampling()
     .neighbourSize(FULL_NEIGHBOUR_SIZE)
     .sampleSize(FULL_SAMPLE_SIZE)
     .stableVelocity(0) // Change here
-    .distance(distance)
+    .distance(distance);
 
   let hybridSimulation = d3.hybridSimulation(simulation, forceSample, forceFull)
     .sampleIterations(ITERATIONS)
     .fullIterations(FULL_ITERATIONS)
-    .numPivots(PIVOTS ? NUM_PIVOTS:-1)
+    .numPivots(PIVOTS ? NUM_PIVOTS : -1)
     .interpFindTuneIts(INTERP_ENDING_ITS)
     .interpDistanceFn(distance)
-    .on("sampleTick", ticked)
+    .on('sampleTick', ticked)
-    .on("fullTick", ticked)
+    .on('fullTick', ticked)
-    .on("startInterp", startedFull)
+    .on('startInterp', startedFull)
-    .on("end", ended);
+    .on('end', ended);
 
   let sample = hybridSimulation.subSet();
   addNodesToDOM(sample);
 
   hybridSimulation.restart();
 
-  function startedFull() {
+  function startedFull () {
-    console.log("startedFull");
+    console.log('startedFull');
-    d3.selectAll(".nodes").remove();
+    d3.selectAll('.nodes').remove();
     addNodesToDOM(nodes);
   }
 }

examples/js/algos/linkForce.js

@@ -1,8 +1,8 @@
 /**
  * Initialize the link force algorithm and start simulation.
  */
-function startLinkSimulation() {
+function startLinkSimulation () {
-  console.log("startLinkSimulation")
+  console.log('startLinkSimulation');
   springForce = false;
   alreadyRanIterations = 0;
   manualStop = true;
@@ -12,26 +12,25 @@ function startLinkSimulation() {
 
   if (tweakedVerOfLink) {
     force = d3.forceLinkCompleteGraph()
-              .distance(function (n, m) {
+      .distance(function (n, m) {
-                return distanceFunction(n, m, props, norm);
+        return distanceFunction(n, m, props, norm);
-              })
+      })
-              .stableVelocity(0) // Change here
+      .stableVelocity(0) // Change here
-              .onStableVelo(ended);
+      .onStableVelo(ended);
-  }
+  } else {
-  else {
+    for (i = nodes.length - 1; i >= 1; i--) {
-    for (i = nodes.length-1; i >= 1; i--) {
+      for (j = i - 1; j >= 0; j--) {
-      for (j = i-1; j >= 0; j--) {
         links.push({
           source: nodes[i],
-          target: nodes[j],
+          target: nodes[j]
         });
       }
     }
     force = d3.forceLink()
-              .distance(function (n) {
+      .distance(function (n) {
-               return distanceFunction(n.source, n.target, props, norm);
+        return distanceFunction(n.source, n.target, props, norm);
-              })
+      })
-             .links(links);
+      .links(links);
   }
 
   /* Add force
@@ -51,9 +50,9 @@ function startLinkSimulation() {
   simulation
     .alphaDecay(0)
     .alpha(1)
-    .on("tick", ticked)
+    .on('tick', ticked)
-    .on("end", ended)
+    .on('end', ended)
-    //.velocityDecay(0.8)
+    // .velocityDecay(0.8)
-    .force(forceName,force)
+    .force(forceName, force)
     .restart();
 }

examples/js/algos/neighbourSampling.js

@@ -1,28 +1,28 @@
 /**
  * Initialize the Chalmers' 1996 algorithm and start simulation.
  */
-function startNeighbourSamplingSimulation() {
+function startNeighbourSamplingSimulation () {
-  console.log("startNeighbourSamplingSimulation");
+  console.log('startNeighbourSamplingSimulation');
-  //springForce = true;
+  // springForce = true;
   alreadyRanIterations = 0;
   manualStop = true;
   simulation.stop();
   p1 = performance.now();
 
   let force = d3.forceNeighbourSampling()
-                  .neighbourSize(NEIGHBOUR_SIZE)
+    .neighbourSize(NEIGHBOUR_SIZE)
-                  .sampleSize(SAMPLE_SIZE)
+    .sampleSize(SAMPLE_SIZE)
-                  .distance(function (s, t) {
+    .distance(function (s, t) {
-                    return distanceFunction(s, t, props, norm);
+      return distanceFunction(s, t, props, norm);
-                  })
+    })
-                  .stableVelocity(0) // Change here
+    .stableVelocity(0) // Change here
-                  .onStableVelo(ended);
+    .onStableVelo(ended);
 
   simulation
     .alphaDecay(0)
     .alpha(1)
-    .on("tick", ticked)
+    .on('tick', ticked)
-    .on("end", ended)
+    .on('end', ended)
     .force(forceName, force);
   // Restart the simulation.
   simulation.restart();

examples/js/algos/otherAlgo.js

@@ -1,7 +1,7 @@
 /**
  * Initialize the t-SNE algorithm and start simulation.
 */
-function starttSNE() {
+function starttSNE () {
   springForce = false;
   simulation.stop();
   p1 = performance.now();
@@ -25,20 +25,20 @@ function starttSNE() {
 /**
  * Initialize the Barnes-Hut algorithm and start simulation.
 */
-function startBarnesHutSimulation() {
+function startBarnesHutSimulation () {
-  console.log("startBarnesHutSimulation")
+  console.log('startBarnesHutSimulation');
   alreadyRanIterations = 0;
   manualStop = false;
   springForce = false;
   p1 = performance.now();
 
   simulation.alphaDecay(1 - Math.pow(0.001, 1 / ITERATIONS))
-      .on("tick", ticked)
+    .on('tick', ticked)
-      .on("end", ended)
+    .on('end', ended)
-      .force(forceName, d3.forceBarnesHut()
+    .force(forceName, d3.forceBarnesHut()
-        // The distance function that will be used to calculate distances
+    // The distance function that will be used to calculate distances
-        //  between nodes.
+    //  between nodes.
-        .distance(function(s, t) { return distanceFunction(s, t, props, norm); }));
+      .distance(function (s, t) { return distanceFunction(s, t, props, norm); }));
   // Restart the simulation.
   simulation.alpha(1).restart();
 }

examples/js/distances/cosineSimilarity.js

@@ -5,14 +5,14 @@
  * @param  {array} properties - the properties of the nodes.
  * @return {number}            the distance between source and target nodes.
  */
-function calculateCosineSimilarity(source, target, properties, normArgs) {
+function calculateCosineSimilarity (source, target, properties, normArgs) {
   var numerator = 0.0;
 
   // console.log(properties);
   // Iterate through every column of data
   for (var i = 0; i < properties.length; i++) {
     property = properties[i];
-    if (property.toLowerCase() !== "class" && property.toLowerCase() !== "app" && property.toLowerCase() !== "user" && property.toLowerCase() !== "weekday") {
+    if (property.toLowerCase() !== 'class' && property.toLowerCase() !== 'app' && property.toLowerCase() !== 'user' && property.toLowerCase() !== 'weekday') {
       var s = source[property],
         t = target[property];
 
@@ -26,7 +26,7 @@ function calculateCosineSimilarity(source, target, properties, normArgs) {
   return Math.abs(numerator / denominator);
 }
 
-function squareRooted(node, properties, normArgs) {
+function squareRooted (node, properties, normArgs) {
   var sum = 0.0;
 
   for (var i = 0, s; i < properties.length; i++) {

examples/js/distances/diceDissimilarity.js

@@ -5,14 +5,14 @@
  * @param  {array} properties - the properties of the nodes.
  * @return {number}            the distance between source and target nodes.
  */
-function calculateDiceDissimilarity(source, target, properties, normArgs) {
+function calculateDiceDissimilarity (source, target, properties, normArgs) {
   var notShared = 0.0;
 
   // console.log(properties);
   // Iterate through every column of data
   for (var i = 0; i < properties.length; i++) {
     property = properties[i];
-    if (property.toLowerCase() !== "class" && property.toLowerCase() !== "app" && property.toLowerCase() !== "user" && property.toLowerCase() !== "weekday") {
+    if (property.toLowerCase() !== 'class' && property.toLowerCase() !== 'app' && property.toLowerCase() !== 'user' && property.toLowerCase() !== 'weekday') {
       var s = source[property],
         t = target[property];
 

examples/js/distances/distance.js

@@ -6,23 +6,23 @@
  * @param  {object} normArgs   - the normalization arguments.
  * @return {number}            the distance between source and target nodes.
  */
-function calculateDistance(source, target, properties, normArgs) {
+function calculateDistance (source, target, properties, normArgs) {
   var val1 = 0.0, val2 = 0.0,
-      sumDiff = 0.0,
+    sumDiff = 0.0,
-      ordDiff = 1.0,
+    ordDiff = 1.0,
-      ORD_FACTOR = 0.75,
+    ORD_FACTOR = 0.75,
-      cols = 0,
+    cols = 0,
-      average = normArgs.avg,
+    average = normArgs.avg,
-      sigma = normArgs.sig,
+    sigma = normArgs.sig,
-      st_dev = normArgs.st_d;
+    st_dev = normArgs.st_d;
 
   // Iterate through every column of data
   for (var i = 0; i < properties.length; i++) {
     property = properties[i];
-    if (source.hasOwnProperty(property) && target.hasOwnProperty(property)
+    if (source.hasOwnProperty(property) && target.hasOwnProperty(property) &&
-        && property.toLowerCase() !== "index" && property.toLowerCase() !== "type") {
+        property.toLowerCase() !== 'index' && property.toLowerCase() !== 'type') {
       var s = source[property],
-          t = target[property];
+        t = target[property];
 
       // Comparing Floats and Integers
       if ((isNumeric(s) && isNumeric(t))) {
@@ -32,7 +32,7 @@ function calculateDistance(source, target, properties, normArgs) {
           val1 = (val1 - average[i]) / (st_dev[i] * sigma[i]);
           val2 = (val2 - average[i]) / (st_dev[i] * sigma[i]);
         }
-        sumDiff += (val1-val2) * (val1-val2);
+        sumDiff += (val1 - val2) * (val1 - val2);
         cols++;
       // Comparing strings
       } else if (/[a-zA-Z]/.test(s) && /[a-zA-Z]/.test(t) && s === t) {
@@ -42,9 +42,8 @@ function calculateDistance(source, target, properties, normArgs) {
         // Comparing Dates
         var parsedDateS = Date.parse(s);
         var parsedDateT = Date.parse(t);
-        if (isNaN(s) && !isNaN(parsedDateS)
+        if (isNaN(s) && !isNaN(parsedDateS) &&
-            && isNaN(t) && !isNaN(parsedDateT)) {
+            isNaN(t) && !isNaN(parsedDateT)) {
-
           val1 = parsedDateS.valueOf(),
           val2 = parsedDateT.valueOf();
 
@@ -52,7 +51,7 @@ function calculateDistance(source, target, properties, normArgs) {
             val1 = (val1 - average[i]) / (st_dev[i] * sigma[i]);
             val2 = (val2 - average[i]) / (st_dev[i] * sigma[i]);
           }
-          sumDiff += (val1-val2) * (val1-val2);
+          sumDiff += (val1 - val2) * (val1 - val2);
           cols++;
         }
       }
@@ -62,9 +61,9 @@ function calculateDistance(source, target, properties, normArgs) {
   sumDiff *= ordDiff;
 
   if (cols > 0) {
-    sumDiff *= properties.length/cols;
+    sumDiff *= properties.length / cols;
   }
 
-  //console.log(sumDiff);
+  // console.log(sumDiff);
   return sumDiff;
 }

examples/js/distances/distancePokerHands.js

@@ -6,33 +6,33 @@
  * @param  {node} target
  * @return {number}      the distance between source and target nodes.
  */
-function calculateDistancePoker(source, target) {
+function calculateDistancePoker (source, target) {
   var sumDiff = 0.0,
-      ordDiff = 1.0,
+    ordDiff = 1.0,
-      ORD_FACTOR = 1.5,
+    ORD_FACTOR = 1.5,
-      cards = ["C1", "C2", "C3", "C4", "C5"],
+    cards = ['C1', 'C2', 'C3', 'C4', 'C5'],
-      cols = 0;
+    cols = 0;
 
   // Iterate through cards
   for (var i = 0; i < cards.length; i++) {
     card = cards[i];
     if (source.hasOwnProperty(card) && target.hasOwnProperty(card)) {
       var s = parseInt(source[card]),
-          t = parseInt(target[card]);
+        t = parseInt(target[card]);
       // Calculate the squared difference.
-      sumDiff += (s-t) * (s-t);
+      sumDiff += (s - t) * (s - t);
     }
   }
 
   // Class of poker hands describes the similarities the best
   // so give it more priority than checking the differences between cards.
-  if (source.hasOwnProperty("CLASS") && target.hasOwnProperty("CLASS")) {
+  if (source.hasOwnProperty('CLASS') && target.hasOwnProperty('CLASS')) {
-    var s = parseInt(source["CLASS"]),
+    var s = parseInt(source['CLASS']),
-        t = parseInt(target["CLASS"]);
+      t = parseInt(target['CLASS']);
 
     // If classes differ, then scale them by a factor.
     if (s !== t) {
-      ordDiff *= (ORD_FACTOR * (Math.abs(s-t)))
+      ordDiff *= (ORD_FACTOR * (Math.abs(s - t)));
     }
   }
 
@@ -40,4 +40,4 @@ function calculateDistancePoker(source, target) {
   sumDiff *= ordDiff;
 
   return sumDiff;
-}
+}

examples/js/distances/euclideanDistance.js

@@ -5,14 +5,14 @@
  * @param  {array} properties - the properties of the nodes.
  * @return {number}            the distance between source and target nodes.
  */
-function calculateEuclideanDistance(source, target, properties, normArgs) {
+function calculateEuclideanDistance (source, target, properties, normArgs) {
   var sumDiff = 0.0;
 
   // console.log(normArgs);
   // Iterate through every column of data
   for (var i = 0; i < properties.length; i++) {
     property = properties[i];
-    if (property.toLowerCase() !== "class" && property.toLowerCase() !== "app" && property.toLowerCase() !== "user" && property.toLowerCase() !== "weekday" && property.toLowerCase() !== "type") {
+    if (property.toLowerCase() !== 'class' && property.toLowerCase() !== 'app' && property.toLowerCase() !== 'user' && property.toLowerCase() !== 'weekday' && property.toLowerCase() !== 'type') {
       var s = source[property],
         t = target[property];
 

examples/js/distances/euclideanDistanceInTSNE.js

@@ -5,7 +5,7 @@
  * @param  {array} properties - the properties of the nodes.
  * @return {number}            the distance between source and target nodes.
  */
-function calculateEuclideanDistanceTSNE(source, target, properties, normArgs) {
+function calculateEuclideanDistanceTSNE (source, target, properties, normArgs) {
   var dotProduct = 0.0,
     sumX = 0.0,
     sumY = 0.0;
@@ -15,7 +15,7 @@ function calculateEuclideanDistanceTSNE(source, target, properties, normArgs) {
   for (var i = 0; i < properties.length; i++) {
     property = properties[i];
     if (source.hasOwnProperty(property) && target.hasOwnProperty(property) &&
-      property.toLowerCase() !== "class") {
+      property.toLowerCase() !== 'class') {
       var s = source[property],
         t = target[property];
 

examples/js/distances/jaccardDissimilarity.js

@@ -5,14 +5,14 @@
  * @param  {array} properties - the properties of the nodes.
  * @return {number}            the distance between source and target nodes.
  */
-function calculateJaccardDissimilarity(source, target, properties, normArgs) {
+function calculateJaccardDissimilarity (source, target, properties, normArgs) {
   var notShared = 0.0;
 
   // console.log(properties);
   // Iterate through every column of data
   for (var i = 0; i < properties.length; i++) {
     property = properties[i];
-    if (property.toLowerCase() !== "class" && property.toLowerCase() !== "app" && property.toLowerCase() !== "user" && property.toLowerCase() !== "weekday") {
+    if (property.toLowerCase() !== 'class' && property.toLowerCase() !== 'app' && property.toLowerCase() !== 'user' && property.toLowerCase() !== 'weekday') {
       var s = source[property],
         t = target[property];
 

examples/js/distances/manhattanDistance.js

@@ -5,7 +5,7 @@
  * @param  {array} properties - the properties of the nodes.
  * @return {number}            the distance between source and target nodes.
  */
-function calculateManhattanDistance(source, target, properties, normArgs) {
+function calculateManhattanDistance (source, target, properties, normArgs) {
   var sum = 0.0,
     cols = 0;
 
@@ -13,7 +13,7 @@ function calculateManhattanDistance(source, target, properties, normArgs) {
   // Iterate through every column of data
   for (var i = 0; i < properties.length; i++) {
     property = properties[i];
-    if (property.toLowerCase() !== "class" && property.toLowerCase() !== "app" && property.toLowerCase() !== "user" && property.toLowerCase() !== "weekday") {
+    if (property.toLowerCase() !== 'class' && property.toLowerCase() !== 'app' && property.toLowerCase() !== 'user' && property.toLowerCase() !== 'weekday') {
       var s = source[property],
         t = target[property];
 

examples/js/distances/normalization.js

@@ -3,7 +3,7 @@
  * @param  {array} nodes
  * @return {object}    that contains the normalization parameters.
  */
-function calculateNormalization(nodes) {
+function calculateNormalization (nodes) {
   var STANDARD_DEV = 2.0,
     properties = Object.keys(nodes[0]),
     sums = calculateSums(nodes, properties),
@@ -23,10 +23,8 @@ function calculateNormalization(nodes) {
   };
 }
 
-
+function standardDevation (nodes, properties, avg) {
-function standardDevation(nodes, properties, avg) {
+  var stDev = new Array(properties.length).fill(0);
-
-  var stDev = new Array(properties.length).fill(0)
 
   for (var i = 0; i < properties.length; i++) {
     var sum = 0;
@@ -48,11 +46,10 @@ function standardDevation(nodes, properties, avg) {
       sum += Math.pow(val - propAvg, 2);
     });
 
-    stDev[i] = Math.sqrt(sum/nodes.length);
+    stDev[i] = Math.sqrt(sum / nodes.length);
   }
 
-  return stDev;
+  return stDev;
-
 }
 
 // Calculate the sum of values and the squared sum
@@ -63,7 +60,7 @@ function standardDevation(nodes, properties, avg) {
  * @return {object}       that contains arrays with sum of values
  *     and the squared sums.
  */
-function calculateSums(nodes, properties) {
+function calculateSums (nodes, properties) {
   var sumOfValues = new Array(properties.length).fill(0),
     sumOfSquares = new Array(properties.length).fill(0);
 
@@ -90,4 +87,4 @@ function calculateSums(nodes, properties) {
     sumOfVal: sumOfValues,
     sumOfSq: sumOfSquares
   };
-}
+}

examples/js/distances/numeric.js

@@ -3,6 +3,6 @@
  * @param  {object}  n - object to check.
  * @return {Boolean}   true, if it is a number, false otherwise.
  */
-function isNumeric(n) {
+function isNumeric (n) {
   return !isNaN(parseFloat(n)) && isFinite(n);
-}
+}