แก้ coding style ภาค 2

.eslintrc

@@ -1,15 +1,41 @@
 parserOptions:
-    sourceType: module
+  sourceType: module
 
 extends:
-    "eslint:recommended"
+  "standard"
-
 rules:
-    no-cond-assign: 0
+  no-cond-assign: 0
-    no-console: 0
+  no-console: 0
-
+  semi:
+    - error
+    - always
+/*
+  no-extra-parens: 1
+  curly: 0
+  block-scoped-var: 1
+  no-tabs: 1
+  no-negated-condition: 1
+  block-spacing: 1
+  brace-style: 1
+  comma-spacing: 1
+  comma-style: 1
+  eol-last: 1
+  func-call-spacing: 1
+  indent:
+    - error
+    - 2
+  key-spacing: 1
+  linebreak-style: 1
+  no-lonely-if: 1
+*/
 env:
   es6: true
 
 globals:
   console: false
+/*
+plugins:
+  - import
+  - node
+  - promise
+*/

index.js

@@ -1,17 +1,17 @@
 export {default as forceNeighbourSampling}
-  from "./src/neighbourSampling";
+  from './src/neighbourSampling';
 
 export { default as forceBarnesHut}
-  from "./src/barnesHut";
+  from './src/barnesHut';
 
 export { default as tSNE}
-  from "./src/t-sne";
+  from './src/t-sne';
 
 export { default as forceLinkCompleteGraph}
-  from "./src/link";
+  from './src/link';
 
 export { default as hybridSimulation}
-  from "./src/hybridSimulation";
+  from './src/hybridSimulation';
 
 export { getStress as calculateStress }
-  from "./src/stress";
+  from './src/stress';

package.json

@@ -19,6 +19,11 @@
   },
   "devDependencies": {
     "eslint": "4",
+    "eslint-config-standard": "^11.0.0",
+    "eslint-plugin-import": "^2.9.0",
+    "eslint-plugin-node": "^6.0.1",
+    "eslint-plugin-promise": "^3.7.0",
+    "eslint-plugin-standard": "^3.0.1",
     "rollup": "0.36",
     "uglify-js": "git+https://github.com/mishoo/UglifyJS2.git#harmony"
   },

src/barnesHut.js

@@ -1,7 +1,7 @@
-import constant from "./constant";
+import constant from './constant';
-import jiggle from "./jiggle";
+import jiggle from './jiggle';
-import {x, y} from "./xy";
+import {x, y} from './xy';
-import {quadtree} from "d3-quadtree";
+import {quadtree} from 'd3-quadtree';
 
 /**
  * The refinement of the existing Barnes-Hut implementation in D3
@@ -12,7 +12,7 @@ import {quadtree} from "d3-quadtree";
  * The check to see if the nodes are far away was also changed to the one described in original Barnes-Hut paper.
  * @return {force} calculated forces.
  */
-export default function() {
+export default function () {
   var nodes,
     node,
     alpha,
@@ -25,7 +25,7 @@ export default function() {
    * @param  {number} _ - controls the stopping of the
    *     particle simulations.
    */
-  function force(_) {
+  function force (_) {
     var i, n = nodes.length, tree = quadtree(nodes, x, y).visitAfter(accumulate);
     for (alpha = _, i = 0; i < n; ++i) {
       node = nodes[i], tree.visit(apply);
@@ -38,7 +38,7 @@ export default function() {
    * nodes accumulate forces from coincident quadrants.
    * @param  {quadrant} quad - node representing the quadrant in quadtree.
    */
-  function accumulate(quad) {
+  function accumulate (quad) {
     var q, d, children = [];
 
     // For internal nodes, accumulate forces from child quadrants.
@@ -69,8 +69,7 @@ export default function() {
    * @param  {number} x2   - upper x bound of the node.
    * @return {boolean}     - true if the approximation was applied.
    */
-  function apply(quad, x1, _, x2) {
+  function apply (quad, x1, _, x2) {
-
     var x = quad.data.x + quad.data.vx - node.x - node.vx,
       y = quad.data.y + quad.data.vy - node.y - node.vy,
       w = x2 - x1,
@@ -98,13 +97,15 @@ export default function() {
       if (y === 0) y = jiggle(), l += y * y;
     }
 
-    do if (quad.data !== node) {
+    do {
-      l = (l - +distance(node, quad.data)) / l * alpha;
+      if (quad.data !== node) {
-      x *= l, y *= l;
+        l = (l - +distance(node, quad.data)) / l * alpha;
-      quad.data.vx -= x;
+        x *= l, y *= l;
-      quad.data.vy -= y;
+        quad.data.vx -= x;
-      node.vx += x;
+        quad.data.vy -= y;
-      node.vy += y;
+        node.vx += x;
+        node.vy += y;
+      }
     } while (quad = quad.next);
   }
 
@@ -114,37 +115,37 @@ export default function() {
     * the better layout.
     * @return {number} - stress of the layout.
     */
-  function getStress() {
+  function getStress () {
     var totalDiffSq = 0, totalHighDistSq = 0;
     for (var i = 0, source, target, realDist, highDist; i < nodes.length; i++) {
       for (var j = 0; j < nodes.length; j++) {
         if (i !== j) {
           source = nodes[i], target = nodes[j];
-          realDist = Math.hypot(target.x-source.x, target.y-source.y);
+          realDist = Math.hypot(target.x - source.x, target.y - source.y);
           highDist = +distance(nodes[i], nodes[j]);
-          totalDiffSq += Math.pow(realDist-highDist, 2);
+          totalDiffSq += Math.pow(realDist - highDist, 2);
           totalHighDistSq += highDist * highDist;
         }
       }
     }
-    return Math.sqrt(totalDiffSq/totalHighDistSq);
+    return Math.sqrt(totalDiffSq / totalHighDistSq);
   }
 
   // API for initializing the algorithm, setting parameters and querying
   // metrics.
-  force.initialize = function(_) {
+  force.initialize = function (_) {
     nodes = _;
   };
 
-  force.distance = function(_) {
+  force.distance = function (_) {
-    return arguments.length ? (distance = typeof _ === "function" ? _ : constant(+_), force) : distance;
+    return arguments.length ? (distance = typeof _ === 'function' ? _ : constant(+_), force) : distance;
   };
 
-  force.theta = function(_) {
+  force.theta = function (_) {
     return arguments.length ? (theta = _, force) : theta;
   };
 
-  force.stress = function() {
+  force.stress = function () {
     return getStress();
   };
 

src/constant.js

@@ -1,8 +1,8 @@
 /**
  * @return a constant defined by x.
  */
-export default function(x) {
+export default function (x) {
-  return function() {
+  return function () {
     return x;
   };
 }

src/interpolation/helpers.js

@@ -8,7 +8,7 @@
                       sample is the list of selected objects while
                       remainder is the list of those unselected.
  */
-export function takeSampleFrom(sourceList, amount) {
+export function takeSampleFrom (sourceList, amount) {
   let randElements = [],
     max = sourceList.length,
     swap = false;
@@ -18,7 +18,7 @@ export function takeSampleFrom(sourceList, amount) {
   }
 
   // If picking more than half of the entire set, random to pick the remainder instead
-  if (amount > Math.ceil(max/2)){
+  if (amount > Math.ceil(max / 2)) {
     amount = max - amount;
     swap = true;
   }
@@ -35,7 +35,7 @@ export function takeSampleFrom(sourceList, amount) {
     return !randElements.includes(obj);
   });
 
-  if(swap) {
+  if (swap) {
     return {
       sample: remainder,
       remainder: randElements
@@ -57,14 +57,14 @@ export function takeSampleFrom(sourceList, amount) {
  * @param {number} r
  * @return {object} - coordinate {x: number, y: number} of the point
  */
-export function pointOnCircle(h, k, angle, r) {
+export function pointOnCircle (h, k, angle, r) {
   return {
-    x: h + r*Math.cos(toRadians(angle)),
+    x: h + r * Math.cos(toRadians(angle)),
-    y: k + r*Math.sin(toRadians(angle))
+    y: k + r * Math.sin(toRadians(angle))
   };
 }
 
-function toRadians(degrees) {
+function toRadians (degrees) {
   return degrees * (Math.PI / 180);
 }
 
@@ -79,7 +79,7 @@ function toRadians(degrees) {
                                  that of samples.
  * @return {number} - Sum of distances differences
  */
-export function sumDistError(node, samples, realDistances) {
+export function sumDistError (node, samples, realDistances) {
   let total = 0.0;
   for (let i = 0; i < samples.length; i++) {
     let sample = samples[i];

src/jiggle.js

@@ -1,7 +1,7 @@
 /**
  * @return {number} a very small non-zero random number.
  */
-export default function() {
+export default function () {
   let rand;
   do {
     rand = (Math.random() - 0.5) * 1e-6;

src/link.js

@@ -1,5 +1,5 @@
-import constant from "./constant";
+import constant from './constant';
-import jiggle from "./jiggle";
+import jiggle from './jiggle';
 
 /**
  * Modified link force algorithm
@@ -8,7 +8,7 @@ import jiggle from "./jiggle";
  * - removed other unused functions
  * Alpha should be constant 1 for accurate simulation
  */
-export default function() {
+export default function () {
   var dataSizeFactor,
     distance = constant(30),
     distances = [],
@@ -18,11 +18,11 @@ export default function() {
     latestVelocityDiff = 0,
     iterations = 1;
 
-  function force(alpha) {
+  function force (alpha) {
     let n = nodes.length;
     // Cache old velocity for comparison later
-    if (stableVeloHandler!==null && stableVelocity>=0) {
+    if (stableVeloHandler !== null && stableVelocity >= 0) {
-      for (let i = n-1, node; i>=0; i--) {
+      for (let i = n - 1, node; i >= 0; i--) {
         node = nodes[i];
         node.oldvx = node.vx;
         node.oldvy = node.vy;
@@ -32,46 +32,48 @@ export default function() {
     // Each iteration in a tick
     for (var k = 0, source, target, i, j, x, y, l; k < iterations; ++k) {
       // For each link
-      for (i = 1; i < n; i++) for (j = 0; j < i; j++) {
+      for (i = 1; i < n; i++) {
+        for (j = 0; j < i; j++) {
         // jiggle so l won't be zero and divide by zero error after this
-        source = nodes[i];
+          source = nodes[i];
-        target = nodes[j];
+          target = nodes[j];
-        x = target.x + target.vx - source.x - source.vx || jiggle();
+          x = target.x + target.vx - source.x - source.vx || jiggle();
-        y = target.y + target.vy - source.y - source.vy || jiggle();
+          y = target.y + target.vy - source.y - source.vy || jiggle();
-        l = Math.sqrt(x * x + y * y);
+          l = Math.sqrt(x * x + y * y);
-        l = (l - distances[i*(i-1)/2+j]) / l  * dataSizeFactor * alpha;
+          l = (l - distances[i * (i - 1) / 2 + j]) / l * dataSizeFactor * alpha;
-        x *= l, y *= l;
+          x *= l, y *= l;
-        target.vx -= x;
+          target.vx -= x;
-        target.vy -= y;
+          target.vy -= y;
-        source.vx += x;
+          source.vx += x;
-        source.vy += y;
+          source.vy += y;
+        }
       }
     }
 
     // Calculate velocity changes, aka force applied.
-    if (stableVeloHandler!==null && stableVelocity>=0) {
+    if (stableVeloHandler !== null && stableVelocity >= 0) {
       let velocityDiff = 0;
-      for (let i = n-1, node; i>=0; i--) {
+      for (let i = n - 1, node; i >= 0; i--) {
         node = nodes[i];
-        velocityDiff += Math.abs(Math.hypot(node.vx-node.oldvx, node.vy-node.oldvy));
+        velocityDiff += Math.abs(Math.hypot(node.vx - node.oldvx, node.vy - node.oldvy));
       }
       velocityDiff /= n;
       latestVelocityDiff = velocityDiff;
 
-      if(velocityDiff<stableVelocity){
+      if (velocityDiff < stableVelocity) {
         stableVeloHandler();
       }
     }
   }
 
-  function initialize() {
+  function initialize () {
     if (!nodes) return;
     // 0.5 to divide the force to two part for source and target node
-    dataSizeFactor = 0.5/(nodes.length-1);
+    dataSizeFactor = 0.5 / (nodes.length - 1);
     initializeDistance();
   }
 
-  function initializeDistance() {
+  function initializeDistance () {
     if (!nodes) return;
     for (let i = 1, n = nodes.length; i < n; i++) {
       for (let j = 0; j < i; j++) {
@@ -80,17 +82,17 @@ export default function() {
     }
   }
 
-  force.initialize = function(_) {
+  force.initialize = function (_) {
     nodes = _;
     initialize();
   };
 
-  force.iterations = function(_) {
+  force.iterations = function (_) {
     return arguments.length ? (iterations = +_, force) : iterations;
   };
 
-  force.distance = function(_) {
+  force.distance = function (_) {
-    return arguments.length ? (distance = typeof _ === "function" ? _ : constant(+_), initializeDistance(), force) : distance;
+    return arguments.length ? (distance = typeof _ === 'function' ? _ : constant(+_), initializeDistance(), force) : distance;
   };
 
   force.latestAccel = function () {

src/neighbourSampling.js

@@ -1,12 +1,12 @@
-import constant from "./constant";
+import constant from './constant';
-import jiggle from "./jiggle";
+import jiggle from './jiggle';
 /**
  * An implementation of Chalmers' 1996 Neighbour and Sampling algorithm.
  * It uses random sampling to find the most suited neighbours from the
  * data set.
  */
 
-function sortDistances(a, b) {
+function sortDistances (a, b) {
   return b[1] - a[1];
 }
 
@@ -25,18 +25,18 @@ export default function () {
    * Apply spring forces at each simulation iteration.
    * @param  {number} alpha - multiplier for amount of force applied
    */
-  function force(alpha) {
+  function force (alpha) {
     let n = nodes.length;
     // Cache old velocity for comparison later
-    if (stableVeloHandler!==null && stableVelocity>=0) {
+    if (stableVeloHandler !== null && stableVelocity >= 0) {
-      for (let i = n-1, node; i>=0; i--) {
+      for (let i = n - 1, node; i >= 0; i--) {
         node = nodes[i];
         node.oldvx = node.vx;
         node.oldvy = node.vy;
       }
     }
 
-    for (let i = n-1, node, samples; i>=0; i--) {
+    for (let i = n - 1, node, samples; i >= 0; i--) {
       node = nodes[i];
       samples = createRandomSamples(i);
 
@@ -52,16 +52,16 @@ export default function () {
     }
 
     // Calculate velocity changes, aka force applied.
-    if (stableVeloHandler!==null && stableVelocity>=0) {
+    if (stableVeloHandler !== null && stableVelocity >= 0) {
       let velocityDiff = 0;
-      for (let i = n-1, node; i>=0; i--) {
+      for (let i = n - 1, node; i >= 0; i--) {
         node = nodes[i];
-        velocityDiff += Math.abs(Math.hypot(node.vx-node.oldvx, node.vy-node.oldvy));
+        velocityDiff += Math.abs(Math.hypot(node.vx - node.oldvx, node.vy - node.oldvy));
       }
       velocityDiff /= n;
       latestVelocityDiff = velocityDiff;
 
-      if(velocityDiff<stableVelocity){
+      if (velocityDiff < stableVelocity) {
         stableVeloHandler();
       }
     }
@@ -74,7 +74,7 @@ export default function () {
    * @param {number} dist    - high dimensional distance between the two nodes
    * @param {number} alpha   - multiplier for the amount of force applied
    */
-  function setVelocity(source, target, dist, alpha) {
+  function setVelocity (source, target, dist, alpha) {
     let x, y, l;
     // jiggle so l won't be zero and divide by zero error after this
     x = target.x + target.vx - source.x - source.vx || jiggle();
@@ -90,11 +90,11 @@ export default function () {
   }
 
   // Called on nodes change and added to a simulation
-  function initialize() {
+  function initialize () {
     if (!nodes) return;
 
     // Initialize for each node some random neighbours.
-    for (let i = nodes.length-1; i>=0; i--) {
+    for (let i = nodes.length - 1; i >= 0; i--) {
       let neighbs = pickRandomNodesFor(i, [i], neighbourSize);
       // Sort the neighbour set by the distances.
       neighbours[i] = new Map(neighbs.sort(sortDistances));
@@ -103,8 +103,8 @@ export default function () {
     initDataSizeFactor();
   }
 
-  function initDataSizeFactor(){
+  function initDataSizeFactor () {
-    dataSizeFactor = 0.5/(neighbourSize+sampleSize);
+    dataSizeFactor = 0.5 / (neighbourSize + sampleSize);
   }
 
   /**
@@ -116,7 +116,7 @@ export default function () {
    * @param  {number} size   - max number of elements in the map to return.
    * @return {array}
    */
-  function pickRandomNodesFor(index, exclude, size) {
+  function pickRandomNodesFor (index, exclude, size) {
     let randElements = [];
     let max = nodes.length;
 
@@ -133,7 +133,7 @@ export default function () {
       }
       randElements.push(rand);
     }
-    for(let i=randElements.length-1, rand; i>=0; i--){
+    for (let i = randElements.length - 1, rand; i >= 0; i--) {
       rand = randElements[i];
       randElements[i] = [rand, distance(nodes[index], nodes[rand])];
     }
@@ -146,7 +146,7 @@ export default function () {
    * @param  {number} index - index of the node to generate sample for
    * @return {map}
    */
-  function createRandomSamples(index) {
+  function createRandomSamples (index) {
     // Ignore the current neighbours of the node and itself.
     let exclude = [index];
     exclude = exclude.concat(Array.from(neighbours[index].keys()));
@@ -160,13 +160,12 @@ export default function () {
    * @param  {map} samples    - map of samples
    * @return {map}            - new map of neighbours
    */
-  function findNewNeighbours(neighbours, samples) {
+  function findNewNeighbours (neighbours, samples) {
     let combined = [...neighbours.entries()].concat([...samples.entries()]);
     combined = combined.sort(sortDistances);
     return new Map(combined.slice(0, neighbourSize));
   }
 
-
   // API for initializing the algorithm and setting parameters
   force.initialize = function (_) {
     nodes = _;
@@ -186,7 +185,7 @@ export default function () {
   };
 
   force.distance = function (_) {
-    return arguments.length ? (distance = typeof _ === "function" ? _ : constant(+_), force) : distance;
+    return arguments.length ? (distance = typeof _ === 'function' ? _ : constant(+_), force) : distance;
   };
 
   force.latestAccel = function () {

src/stress.js

@@ -4,10 +4,10 @@
   * to the better layout.
   * @return {number} - stress of the layout.
   */
-export function getStress(nodes, distance) {
+export function getStress (nodes, distance) {
-  let sumDiffSq = 0
+  let sumDiffSq = 0;
   let sumLowDDistSq = 0;
-  for (let j = nodes.length-1; j >= 1; j--) {
+  for (let j = nodes.length - 1; j >= 1; j--) {
     for (let i = 0; i < j; i++) {
       let source = nodes[i], target = nodes[j];
       let lowDDist = Math.hypot(target.x - source.x, target.y - source.y);

src/t-sne.js

@@ -1,5 +1,5 @@
 /* eslint-disable block-scoped-var */
-import constant from "./constant";
+import constant from './constant';
 
 /**
  * Set the node id accessor to the specified i.
@@ -7,7 +7,7 @@ import constant from "./constant";
  * @param  {accessor} i - id accessor.
  * @return {accessor}  - node id accessor.
  */
-function index(d, i) {
+function index (d, i) {
   return i;
 }
 
@@ -15,7 +15,7 @@ function index(d, i) {
  * t-SNE implementation in D3 by using the code existing in tsnejs
  * (https://github.com/karpathy/tsnejs) to compute the solution.
  */
-export default function() {
+export default function () {
   var id = index,
     distance = constant(300),
     nodes,
@@ -33,7 +33,7 @@ export default function() {
    * Make a step in t-SNE algorithm and set the velocities for the nodes
    * to accumulate the values from solution.
    */
-  function force() {
+  function force () {
     // Make a step at each iteration.
     step();
     var solution = getSolution();
@@ -49,7 +49,7 @@ export default function() {
    * Calculates the random number from Gaussian distribution.
    * @return {number} random number.
    */
-  function gaussRandom() {
+  function gaussRandom () {
     let u = 2 * Math.random() - 1;
     let v = 2 * Math.random() - 1;
     let r = u * u + v * v;
@@ -63,11 +63,11 @@ export default function() {
    * Return the normalized number.
    * @return {number} normalized random number from Gaussian distribution.
    */
-  function randomN() {
+  function randomN () {
     return gaussRandom() * 1e-4;
   }
 
-  function sign(x) {
+  function sign (x) {
     return x > 0 ? 1 : x < 0 ? -1 : 0;
   }
 
@@ -76,7 +76,7 @@ export default function() {
    * @param  {number} n - length of array.
    * @return {Float64Array}   - array of zeros with length n.
    */
-  function zeros(n) {
+  function zeros (n) {
     if (typeof n === 'undefined' || isNaN(n)) {
       return [];
     }
@@ -90,7 +90,7 @@ export default function() {
    * @param  {number} d - columns.
    * @return {array}   - 2d array
    */
-  function random2d(n, d) {
+  function random2d (n, d) {
     var x = [];
     for (var i = 0; i < n; i++) {
       var y = [];
@@ -109,7 +109,7 @@ export default function() {
    * @param  {number} tol        - limit for entropy difference.
    * @return {2d array}          - 2d matrix containing probabilities.
    */
-  function d2p(data, perplexity, tol) {
+  function d2p (data, perplexity, tol) {
     N = Math.floor(data.length);
     var Htarget = Math.log(perplexity); // target entropy of distribution.
     var P1 = zeros(N * N); // temporary probability matrix.
@@ -161,7 +161,6 @@ export default function() {
           } else {
             beta = (beta + betamax) / 2;
           }
-
         } else {
           // Converse case. Make distrubtion less peaky.
           betamax = beta;
@@ -183,7 +182,6 @@ export default function() {
       for (j = 0; j < N; j++) {
         P1[i * N + j] = prow[j];
       }
-
     }
 
     // Symmetrize P and normalize it to sum to 1 over all ij
@@ -200,7 +198,7 @@ export default function() {
   /**
    * Initialize a starting (random) solution.
    */
-  function initSolution() {
+  function initSolution () {
     Y = random2d(N, dim);
     // Step gains to accelerate progress in unchanging directions.
     gains = random2d(N, dim, 1.0);
@@ -212,7 +210,7 @@ export default function() {
   /**
    * @return {2d array} the solution.
    */
-  function getSolution() {
+  function getSolution () {
     return Y;
   }
 
@@ -220,7 +218,7 @@ export default function() {
    * Do a single step (iteration) for the layout.
    * @return {number} the current cost.
    */
-  function step() {
+  function step () {
     iteration += 1;
 
     var cg = costGrad(Y); // Evaluate gradient.
@@ -269,8 +267,7 @@ export default function() {
    * @param  {2d array} Y - the current solution to evaluate.
    * @return {object}   that contains a cost and a gradient.
    */
-  function costGrad(Y) {
+  function costGrad (Y) {
-
     var pmul = iteration < 100 ? 4 : 1;
 
     // Compute current Q distribution, unnormalized first.
@@ -326,7 +323,7 @@ export default function() {
    * the better layout.
    * @return {number} - stress of the layout.
    */
-  function getStress() {
+  function getStress () {
     var totalDiffSq = 0,
       totalHighDistSq = 0;
     for (var i = 0, source, target, realDist, highDist; i < nodes.length; i++) {
@@ -345,7 +342,7 @@ export default function() {
 
   // API for initializing the algorithm, setting parameters and querying
   // metrics.
-  force.initialize = function(_) {
+  force.initialize = function (_) {
     nodes = _;
     N = nodes.length;
     // Initialize the probability matrix.
@@ -353,23 +350,23 @@ export default function() {
     initSolution();
   };
 
-  force.id = function(_) {
+  force.id = function (_) {
     return arguments.length ? (id = _, force) : id;
   };
 
-  force.distance = function(_) {
+  force.distance = function (_) {
-    return arguments.length ? (distance = typeof _ === "function" ? _ : constant(+_), force) : distance;
+    return arguments.length ? (distance = typeof _ === 'function' ? _ : constant(+_), force) : distance;
   };
 
-  force.stress = function() {
+  force.stress = function () {
     return getStress();
   };
 
-  force.learningRate = function(_) {
+  force.learningRate = function (_) {
     return arguments.length ? (learningRate = +_, force) : learningRate;
   };
 
-  force.perplexity = function(_) {
+  force.perplexity = function (_) {
     return arguments.length ? (perplexity = +_, force) : perplexity;
   };
 

src/xy.js

@@ -1,13 +1,13 @@
 /**
  * @return x value of a node
  */
-export function x(d) {
+export function x (d) {
   return d.x;
 }
 
 /**
  * @return y value of a node
  */
-export function y(d) {
+export function y (d) {
   return d.y;
 }