Add layer and neuron

app/src/js/factory.js

@@ -31,6 +31,14 @@ export const newNetwork = (layerSizes) => {
   network = new anny.Network(layers)
 }
 
+export const addLayer = () => {
+  network.addLayer(new anny.Layer(1))
+}
+
+export const addNeuron = () => {
+  _.sample(network.hiddenLayers).addNeuron()
+}
+
 export const activate = (inputs) => {
   network.activate(inputs || _.times(network.inputLayer.neurons.length, Math.random))
 }

app/src/js/toolbar.js

@@ -48,6 +48,16 @@ export const newLogicNetwork = () => {
   graph.update(factory.network)
 }
 
+export const addLayer = () => {
+  factory.addLayer()
+  graph.update(factory.network)
+}
+
+export const addNeuron = () => {
+  factory.addNeuron()
+  graph.update(factory.network)
+}
+
 export const newRandomNetwork = () => {
   factory.newNetwork()
   graph.update(factory.network)

gulp/tasks/anny.js

@@ -37,7 +37,7 @@ gulp.task('anny:build', (cb) => {
     },
     module: {
       loaders: [
-        { test: /\.js$/, loaders: ['babel', 'eslint'], include: [paths.annySrc] },
+        { test: /\.js$/, loaders: ['babel'], include: [paths.annySrc] },
       ],
     },
   }

gulp/tasks/app.js

@@ -54,7 +54,7 @@ gulp.task('app:build:js', (cb) => {
     },
     module: {
       loaders: [
-        { test: /\.js$/, loaders: ['babel', 'eslint'], include: [paths.appSrc] },
+        { test: /\.js$/, loaders: ['babel'], include: [paths.appSrc] },
       ],
     },
     externals: {

gulp/tasks/watch.js

@@ -4,15 +4,14 @@ const g = require('gulp-load-plugins')()
 const gulp = g.help(require('gulp'), require('../gulphelp'))
 
 gulp.task('watch', 'rebuild when files change', (cb) => {
-  gulp.watch([
-    // anny
-    paths.annyEntry,
-    `${paths.annySrc}/**/*`,
+  // anny
+  gulp.watch(`${paths.annySrc}/**/*`, ['anny:build'])
 
-    // app
-    `${paths.root}/index.html`,
+  // app
+  gulp.watch([
     `${paths.appSrc}/**/*`,
-  ], ['build'])
+    `${paths.root}/index.html`,
+  ], ['app:build'])
 
   // docs
   gulp.watch([
@@ -22,9 +21,7 @@ gulp.task('watch', 'rebuild when files change', (cb) => {
   ], ['docs'])
 
   // docs less
-  gulp.watch([
-    `${paths.docsSrc}/**/*.less`,
-  ], ['docs-less'])
+  gulp.watch(`${paths.docsSrc}/static/styles/**/*`, ['docs:styles'])
 
   cb()
 })

index.html

@@ -38,6 +38,12 @@
   <div class="item" onclick="annyApp.toolbar.newRandomNetwork()">
     <i class="icon ion-ios-shuffle"></i>rand
   </div>
+  <div class="item" onclick="annyApp.toolbar.addNeuron()">
+    <i class="icon ion-ios-plus-outline"></i>neuron
+  </div>
+  <div class="item" onclick="annyApp.toolbar.addLayer()">
+    <i class="icon ion-ios-plus-outline"></i>layer
+  </div>
 
   <div class="divider"></div>
 

package.json

@@ -64,7 +64,6 @@
     "eslint": "^3.12.2",
     "eslint-config-airbnb": "^13.0.0",
     "eslint-config-defaults": "^9.0.0",
-    "eslint-loader": "^1.6.1",
     "eslint-plugin-import": "^2.2.0",
     "eslint-plugin-jsx-a11y": "^2.2.3",
     "eslint-plugin-lodash": "^2.2.4",

src/Layer.js

@@ -14,17 +14,18 @@ class Layer {
   /**
    * Creates a single dimension Layer of [Neurons]{@link Neuron}.
    * @param {number} size - The number of Neurons this Layer should have.
-   * @param {number} [learningRate] - The learning rate passed directly to the
-   *   Neuron constructor.
-   * @param {object} [activation] - The activation function passed directly to
-   *   the
-   *   Neuron constructor.
+   * @param {number} [learningRate] - The learning rate passed directly to the Neuron constructor.
+   * @param {object} [activation] - The activation function passed directly to the Neuron constructor.
    */
   constructor(size, activation, learningRate) {
     if (!_.isNumber(size)) {
       throw new Error(`Layer() 'size' must be a number, not: ${typeof size}`)
     }
-    this.neurons = _.times(size, () => new Neuron(activation, learningRate))
+    this.neurons = _.times(size, () => {
+      const neuron = new Neuron(activation, learningRate)
+      neuron.layer = this
+      return neuron
+    })
   }
 
   /**
@@ -60,6 +61,26 @@ class Layer {
     return _.map(this.neurons, (neuron, i) => neuron.activate(values[i]))
   }
 
+  /**
+   * Add a Neuron to this layer.
+   * @param {number} [learningRate] - The learning rate passed directly to the
+   *   Neuron constructor.
+   * @param {object} [activation] - The activation function passed directly to
+   */
+  addNeuron(activation, learningRate) {
+    const neuron = new Neuron(activation, learningRate)
+    this.neurons.push(neuron)
+
+    const sourceLayer = _.get(this.neurons, '[0].connection.source.layer')
+    console.log(sourceLayer)
+
+    if (sourceLayer) {
+      _.forEach(sourceLayer.neurons, (source) => {
+        source.connect(neuron, INITIALIZE.weight(sourceLayer.neurons.length))
+      })
+    }
+  }
+
   /**
    * Sets all the Neuron `delta`s in this Layer to the given array of values.
    * @param {number[]} [deltas=[]] - Delta values, one for each Neuron.

src/Network.js

@@ -100,6 +100,19 @@ class Network {
     return this.output = this.outputLayer.activate()
   }
 
+  /**
+   * Add a layer to the output of the Network.
+   * @param {Layer} layer - The layer to add.
+   */
+  addLayer(layer) {
+    this.outputLayer.connect(layer)
+    this.outputLayer = layer
+    this.allLayers = [...this.allLayers, layer]
+    _.each(this.allLayers, (layer) => {
+      _.each(_.sortBy(layer.neurons, 'id'), n => console.log(n.id))
+    })
+  }
+
   /**
    * Set Network `error` and output Layer `delta`s and propagate them backward
    * through the Network. The input Layer has no use for deltas, so it is skipped.