xor example

Author: shiffman

examples/xor/sketch.js

@@ -1,34 +1,54 @@
+let nn;
 let training_data = [{
-    inputs: [0, 1],
-    targets: [1]
-  },
-  {
-    inputs: [1, 0],
-    targets: [1]
-  },
-  {
-    inputs: [0, 0],
-    targets: [0]
-  },
-  {
-    inputs: [1, 1],
-    targets: [0]
-  }
-];
+  inputs: [0, 0],
+  targets: [0]
+}, {
+  inputs: [1, 0],
+  targets: [1]
+}, {
+  inputs: [0, 1],
+  targets: [1]
+}, {
+  inputs: [1, 1],
+  targets: [0]
+}];
 
+let lr_slider;
 
 function setup() {
-  let nn = new NeuralNetwork(2, 2, 1);
+  createCanvas(400, 400);
+  nn = new NeuralNetwork(2, 2, 1);
+  lr_slider = createSlider(0.01, 0.1, 0.05, 0.01);
+}
+
+function draw() {
+  background(0);
+
+  nn.learning_rate = lr_slider.value();
 
-  for (let i = 0; i < 50000; i++) {
+  for (let i = 0; i < 5000; i++) {
     let data = random(training_data);
     nn.train(data.inputs, data.targets);
   }
 
-  console.log(nn.feedforward([1, 0]));
-  console.log(nn.feedforward([0, 1]));
-  console.log(nn.feedforward([1, 1]));
-  console.log(nn.feedforward([0, 0]));
+  let resolution = 20;
+  let cols = floor(width / resolution);
+  let rows = floor(height / resolution);
+
+  for (let i = 0; i < cols; i++) {
+    for (let j = 0; j < rows; j++) {
+      let x = i * resolution;
+      let y = j * resolution;
+      let input_1 = i / (cols - 1);
+      let input_2 = j / (rows - 1);
+      let output = nn.feedforward([input_1, input_2]);
+      let col = output[0] * 255;
+      fill(col);
+      noStroke();
+      rect(x, y, resolution, resolution);
+    }
+  }
+
 
 
 }