Merge pull request #5 from will-newmarch/release-0.4.0

Release 0.4.0

package.json

@@ -1,6 +1,6 @@
 {
   "name": "intuitive-neural-network",
-  "version": "0.3.0",
+  "version": "0.4.0",
   "description": "An intuitive, object-orientated approach to a Neural Network library.",
   "main": "src/Network.js",
   "scripts": {
@@ -26,5 +26,8 @@
   "homepage": "https://github.com/will-newmarch/intuitive-neural-network#readme",
   "devDependencies": {
     "jest": "^24.5.0"
+  },
+  "dependencies": {
+    "fs": "0.0.1-security"
   }
 }

src/Layer.js

@@ -44,6 +44,12 @@ class Layer {
 		}
 		return totalError;
 	}
+
+	toObject() {
+		return {
+			neurons: this.neurons.map(n => n.toObject())
+		};
+	}
 };
 
 module.exports = Layer;

src/Network.js

@@ -1,3 +1,5 @@
+const fs 		= require('fs');
+
 const Layer 	= require('./Layer.js');
 const Input 	= require('./neuron/Input.js');
 const Hidden 	= require('./neuron/Hidden.js');
@@ -175,14 +177,16 @@ class Network {
 		return this;
 	}
 
-	/**
-	 * Log the network in a human readable fashion
-	 */
-	log(synapses = false) { // This could definitely be improved...
-		this.layers.map(l => {
-			l.neurons.map(n => console.log(n.label,n.outputs.map(s => s.weight)));
+	toJSON() {
+		return JSON.stringify({
+			layers: this.layers.map(l => l.toObject())
 		});
 	}
+
+	save(filename,callback) {
+		const model = this.toJSON();
+		fs.writeFile(filename, model, callback);
+	}
 };
 
 module.exports = Network;

src/Synapse.js

@@ -47,6 +47,16 @@ class Synapse {
 	applyError(learningRate) {
 		this.weight -= learningRate * this.error;
 	}
+
+	toObject() {
+		return {
+			type: this.constructor.name,
+			label: this.label,
+			inputLabel: this.input.label,
+			outputLabel: this.output.label,
+			weight: this.weight
+		}
+	}
 };
 
 module.exports = Synapse;

src/neuron/Hidden.js

@@ -9,13 +9,6 @@ class Hidden extends Neuron {
 	 */
 	constructor(label) {
 		super(label);
-
-		this.inputs 		= [];        // Reference to the input synapses
-		this.inputSignals 	= [];        // Array to collect signals from inputs (when firing)
-		this.outputs 		= [];    	 // Reference to the output synapses
-		this.outputSignals 	= [];    	 // Array to collect signals FROM outputs (when backpropagating)
-		this.activation 	= 0;     	 // Activation of the neuron
-		this.error 			= 0;     	 // Error to be persisted (not actually used in Input neuron, more kept for interest)
 	}
 
 	/**

src/neuron/Input.js

@@ -8,11 +8,6 @@ class Input extends Neuron {
 	 */
 	constructor(label) {
 		super(label);
-
-		this.outputs 		= [];    // Reference to the output synapses
-		this.outputSignals 	= [];    // Array to collect signals FROM outputs (when backpropagating)
-		this.activation 	= 0;     // Activation of the neuron
-		this.error 			= 0;     // Error to be persisted (not actually used in Input neuron, more kept for interest)
 	}
 
 	/**

src/neuron/Neuron.js

@@ -8,6 +8,10 @@ class Neuron {
 	 */
 	constructor(label) {
 		this.label 			= label; 	 // Human readable label
+		this.inputs 		= [];        // Reference to the input synapses
+		this.inputSignals 	= [];        // Array to collect signals from inputs (when firing)
+		this.outputs 		= [];    	 // Reference to the output synapses
+		this.outputSignals 	= [];    	 // Array to collect signals FROM outputs (when backpropagating)
 		this.activation 	= 0;     	 // Activation of the neuron
 		this.error 			= 0;     	 // Error to be persisted (not actually used in Input neuron, more kept for interest)
 		this.setActivationType('sigmoid'); // Neuron activation function (defaulting to sigmoid)
@@ -46,6 +50,15 @@ class Neuron {
 	backPropagate(backSignal) {
 		throw 'backPropagate method must be overidden!';
 	}
+
+	toObject() {
+		return {
+			type: this.constructor.name,
+			label: this.label,
+			activationType: this.activationType,
+			outputs: this.outputs.map(o => o.toObject())
+		};
+	}
 };
 
 module.exports = Neuron;

src/neuron/Output.js

@@ -9,12 +9,6 @@ class Output extends Neuron {
 	 */
 	constructor(label) {
 		super(label);
-
-		this.inputs 		= [];        // Reference to the input synapses
-		this.inputSignals 	= [];        // Array to collect signals from inputs (when firing)
-		this.activation 	= 0;         // Activation of the neuron
-        this.error 			= 0;         // Error to be persisted and applied by network
-
     }
 
     /**

tests/model-to-json.test.js

@@ -0,0 +1,27 @@
+'use strict';
+
+const Network = require('../src/Network.js');
+
+test('library can convert a model to JSON', () => {
+
+    // Build the network...
+    var network = new Network({
+        layers: [2,2,1],
+        bias: false
+    });
+
+    // Hard-code weights to create exact JSON
+    network.layers.map(l => {
+        l.neurons.map(n => {
+            n.outputs.map(o => {
+                o.weight = 0.5;
+            });
+        });
+    });
+
+    const expectedJSON = '{"layers":[{"neurons":[{"type":"Input","label":"input-0","activationType":"sigmoid","outputs":[{"type":"Synapse","label":"input-0--hidden-0","inputLabel":"input-0","outputLabel":"hidden-0","weight":0.5},{"type":"Synapse","label":"input-0--hidden-1","inputLabel":"input-0","outputLabel":"hidden-1","weight":0.5}]},{"type":"Input","label":"input-1","activationType":"sigmoid","outputs":[{"type":"Synapse","label":"input-1--hidden-0","inputLabel":"input-1","outputLabel":"hidden-0","weight":0.5},{"type":"Synapse","label":"input-1--hidden-1","inputLabel":"input-1","outputLabel":"hidden-1","weight":0.5}]}]},{"neurons":[{"type":"Hidden","label":"hidden-0","activationType":"sigmoid","outputs":[{"type":"Synapse","label":"hidden-0--output-0","inputLabel":"hidden-0","outputLabel":"output-0","weight":0.5}]},{"type":"Hidden","label":"hidden-1","activationType":"sigmoid","outputs":[{"type":"Synapse","label":"hidden-1--output-0","inputLabel":"hidden-1","outputLabel":"output-0","weight":0.5}]}]},{"neurons":[{"type":"Output","label":"output-0","activationType":"identity","outputs":[]}]}]}';
+
+    expect(network.toJSON()).toBe(expectedJSON);
+
+});
+

tests/saves-models-to-file.test.js

@@ -0,0 +1,28 @@
+'use strict';
+
+const fs = require('fs');
+
+const Network = require('../src/Network.js');
+
+test('library can convert a model to JSON', (done) => {
+
+    // Build the network...
+    var network = new Network({
+        layers: [2,2,1],
+        bias: false
+    });
+
+    const filename = './temp.json';
+
+    network.save(filename,() => {
+
+        expect(fs.existsSync(filename)).toBe(true);
+
+        fs.unlinkSync(filename);
+
+        done();
+
+    });
+
+});
+

xor-problem.test.js → tests/xor-problem.test.js

@@ -1,6 +1,6 @@
 'use strict';
 
-const Network = require('./src/Network.js');
+const Network = require('../src/Network.js');
 
 test('library solves XOR problem', () => {