Merge pull request #867 from nature-of-code/notion-update-docs

6-11 final touches

content/06_libraries.html

@@ -551,7 +551,6 @@ <h3 id="example-64-polygon-shapes">Example 6.4: Polygon Shapes</h3>
     vertices[2] = Vector.create(15, 0);
     vertices[3] = Vector.create(0, 10);
     vertices[4] = Vector.create(-20, 15);
-
     //{!2} Make a body shaped by the vertices.
     let options = { restitution: 1 };
     this.body = Bodies.fromVertices(x, y, vertices, options);
@@ -602,10 +601,8 @@ <h3 id="exercise-63">Exercise 6.3</h3>
 <pre class="codesplit" data-code-language="javascript">// Make the bodies.
 let part1 = Bodies.rectangle(x, y, w, h);
 let part2 = Bodies.circle(x, y, r);
-
 // Join the two bodies together in an array.
 let body = Body.create({ parts: [part1, part2] });
-
 // Add the compound body to the world.
 Composite.add(engine.world, body);</pre>
 <p>While this does create a compound body by combining two shapes, the code isn’t quite right. If you run it, you’ll see that both shapes are centered on the same (<em>x</em>, <em>y</em>) position, as in Figure 6.7.</p>

content/07_ca.html

@@ -336,7 +336,6 @@ <h3 id="example-71-wolfram-elementary-cellular-automata">Example 7.1: Wolfram El
 let generation = 0;
 // Cell size
 let w = 10;
-
 //{!1} Rule 90
 let ruleset = [0, 1, 0, 1, 1, 0, 1, 0];
 
@@ -370,7 +369,6 @@ <h3 id="example-71-wolfram-elementary-cellular-automata">Example 7.1: Wolfram El
     nextgen[i] = rules(left, me, right);
   }
   cells = nextgen;
-
   //{!1} The next generation
   generation++;
 }

content/08_fractals.html

@@ -281,7 +281,6 @@ <h3 id="the-monster-curve">The Monster Curve</h3>
 </div>
 <p>To accomplish the goal of treating each segment as an individual object, I must first decide what this object should be in the first place. What data should it store? What functions should it have? The Koch curve is a series of connected lines, and so I’ll think of each segment as a <em>KochLine</em>. Each <code>KochLine</code> object has a start point (a) and an end point (b). These points are represented as <code>p5.Vector</code> objects, and the line is drawn using the <code>line()</code> function:</p>
 <pre class="codesplit" data-code-language="javascript">class KochLine {
-
   //{!2} A line between two points: <code>a</code> and <code>b</code>
   constructor(a, b) {
     // <code>a</code> and <code>b</code> are <code>p5.Vector</code> objects.
@@ -489,13 +488,11 @@ <h3 id="the-deterministic-version">The Deterministic Version</h3>
 //{!1} The root
 line(0, 0, 0, -100);
 translate(0, -100);
-
 // Branch to the right
 push();
 rotate(PI / 6);
 line(0, 0, 0, -100);
 pop();
-
 // Branch to the left
 rotate(-PI / 6);
 line(0, 0, 0, -100);</pre>

content/10_nn.html

@@ -164,7 +164,6 @@ <h3 id="putting-it-all-together-1">Putting It All Together</h3>
 <p>With the sum, I can then compute the output:</p>
 <pre class="codesplit" data-code-language="javascript">// Step 3: Pass the sum through an activation function.
 let output = activate(sum);
-
 // The activation function
 function activate(sum) {
   //{!5} Return a 1 if positive, –1 if negative.
@@ -451,10 +450,8 @@ <h3 id="example-101-the-perceptron">Example 10.1: The Perceptron</h3>
 
 function setup() {
   createCanvas(640, 240);
-
   // The perceptron has three inputs (including bias) and a learning rate of 0.0001.
   perceptron = new Perceptron(3, 0.0001);
-
   //{!1} Make 2,000 training data points.
   for (let i = 0; i &#x3C; 2000; i++) {
     let x = random(-width / 2, width / 2);
@@ -468,12 +465,10 @@ <h3 id="example-101-the-perceptron">Example 10.1: The Perceptron</h3>
   // Reorient the canvas to match a traditional Cartesian plane.
   translate(width / 2, height / 2);
   scale(1, -1);
-
   // Draw the line.
   stroke(0);
   strokeWeight(2);
   line(-width / 2, f(-width / 2), width / 2, f(width / 2));
-
   // Get the current <code>(x, y)</code> of the training data.
   let x = training[count][0];
   let y = training[count][1];
@@ -484,10 +479,8 @@ <h3 id="example-101-the-perceptron">Example 10.1: The Perceptron</h3>
   }
   // Train the perceptron.
   perceptron.train(training[count], desired);
-
   // For animation, train one point at a time.
   count = (count + 1) % training.length;
-
   // Draw all the points and color according to the output of the perceptron.
   for (let dataPoint of training) {
     let guess = perceptron.feedforward(dataPoint);

content/11_nn_ga.html

@@ -688,7 +688,6 @@ <h3 id="sensing-the-environment">Sensing the Environment</h3>
     this.r = 16;
     // The creature has an array of sensors.
     this.sensors = [];
-
     // The creature has eight sensors.
     let totalSensors = 8;
     for (let i = 0; i &#x3C; totalSensors; i++) {