Create network.js

network.js

@@ -0,0 +1,87 @@
+class NeuralNetwork{
+    constructor(neuronCounts){
+        this.levels=[];
+        for(let i=0;i<neuronCounts.length-1;i++){
+            this.levels.push(new Level(
+                neuronCounts[i],neuronCounts[i+1]
+            ));
+        }
+    }
+
+    static feedForward(givenInputs,network){
+        let outputs=Level.feedForward(
+            givenInputs,network.levels[0]);
+        for(let i=1;i<network.levels.length;i++){
+            outputs=Level.feedForward(
+                outputs,network.levels[i]);
+        }
+        return outputs;
+    }
+
+    static mutate(network,amount=1){
+        network.levels.forEach(level => {
+            for(let i=0;i<level.biases.length;i++){
+                level.biases[i]=lerp(
+                    level.biases[i],
+                    Math.random()*2-1,
+                    amount
+                )
+            }
+            for(let i=0;i<level.weights.length;i++){
+                for(let j=0;j<level.weights[i].length;j++){
+                    level.weights[i][j]=lerp(
+                        level.weights[i][j],
+                        Math.random()*2-1,
+                        amount
+                    )
+                }
+            }
+        });
+    }
+}
+
+class Level{
+    constructor(inputCount,outputCount){
+        this.inputs=new Array(inputCount);
+        this.outputs=new Array(outputCount);
+        this.biases=new Array(outputCount);
+
+        this.weights=[];
+        for(let i=0;i<inputCount;i++){
+            this.weights[i]=new Array(outputCount);
+        }
+
+        Level.#randomize(this);
+    }
+
+    static #randomize(level){
+        for(let i=0;i<level.inputs.length;i++){
+            for(let j=0;j<level.outputs.length;j++){
+                level.weights[i][j]=Math.random()*2-1;
+            }
+        }
+
+        for(let i=0;i<level.biases.length;i++){
+            level.biases[i]=Math.random()*2-1;
+        }
+    }
+
+    static feedForward(givenInputs,level){
+        level.inputs=[...givenInputs];
+
+        for(let i=0;i<level.outputs.length;i++){
+            let sum=0
+            for(let j=0;j<level.inputs.length;j++){
+                sum+=level.inputs[j]*level.weights[j][i];
+            }
+
+            if(sum>level.biases[i]){
+                level.outputs[i]=1;
+            }else{
+                level.outputs[i]=0;
+            }
+        }
+
+        return level.outputs;
+    }
+}