neural net perf tweaks - training time in half

lib/neuralnetwork.js

@@ -60,10 +60,8 @@ NeuralNetwork.prototype = {
   },
 
   train : function(data, iterations, errorThresh, callback, resolution) {
-    if(!iterations)
-      iterations = 20000;
-    if(!errorThresh)
-      errorThresh = 0.007;
+    iterations = iterations || 20000;
+    errorThresh = errorThresh || 0.007;
 
     var error = 1;
     for(var i = 0; i < iterations && error > errorThresh; i++) {
@@ -177,12 +175,14 @@ Layer.prototype = {
   },
 
   getError : function() {
-    var sum = this.reduce(function(sum, node) { return sum + Math.pow(node.error, 2);}, 0);
+    var sum = this.reduce(function(sum, node) {
+      return sum + Math.pow(node.error, 2);
+    }, 0);
     return Math.sqrt(sum) / this.getSize(); // mean squared error
   },
 
   getSize : function() {
-    return this.reduce(function(count) { return ++count;}, 0);
+    return this.reduce(function(count) { return ++count; }, 0);
   },
 
   map : function(callback) {
@@ -225,15 +225,18 @@ Layer.prototype = {
   },
 
   calcOutputs : function() {
-    this.map(function(node) { node.calcOutput(); });
+    for(var id in this.nodes)
+      this.nodes[id].calcOutput();
   },
 
   calcErrors : function(targets) {
-    this.map(function(node) { node.calcError(targets); });
+    for(var id in this.nodes)
+      this.nodes[id].calcError(targets);
   },
 
   adjustWeights : function() {
-    this.map(function(node) { node.adjustWeights(); });
+    for(var id in this.nodes)
+      this.nodes[id].adjustWeights();
   },
 
   toJSON : function() {
@@ -268,8 +271,6 @@ function Node(layer, id, json) {
 }
 
 Node.prototype = {
-  getInputs : function() { return this.layer.prevLayer.getOutputs(); },
-
   getIncoming : function() { return this.layer.prevLayer.nodes; },
 
   getOutgoing : function() { return this.layer.nextLayer.nodes; },
@@ -293,8 +294,9 @@ Node.prototype = {
 
   calcOutput : function() {
     var sum = this.bias;
+    var inputs = this.getIncoming();
     for(var id in this.weights)
-      sum += this.weights[id] * this.getInputs()[id];
+      sum += this.weights[id] * inputs[id].output;
     this.output = this.sigmoid(sum);
   },
 
@@ -316,9 +318,9 @@ Node.prototype = {
     var rate = this.layer.network.learningRate;
     var momentum = this.layer.network.momentum;
 
-    var inputs = this.getInputs();
+    var inputs = this.getIncoming();
     for(var id in inputs) {
-      var change = rate * this.delta * inputs[id] + momentum * this.change[id];
+      var change = rate * this.delta * inputs[id].output + momentum * this.change[id];
       this.change[id] = change;
       this.weights[id] += change;
     }