/* Define the number of nodes in each layer. */
const noinput = 2;
const nohidden = 50000;
const nooutput = 1;

/* Define the exemplars to learn from. */
let training_data = [
    { inputs: [0, 0], outputs: [0] },
    { inputs: [0, 1], outputs: [1] },
    { inputs: [1, 0], outputs: [1] },
    { inputs: [1, 1], outputs: [0] }
];

/* An object to represent our neural network. */
var nn;

/* Our learning rate, when training our neural network. */
const learningrate = 0.1;

/* The amount of time for which the network should be trained per draw() cycle. */
const notrain = 10;

/* The step at which a screenshot should be taken. */
AB.screenshotStep  = 200;   

/* Whether or not we should show all squares or just the corner squares. */
var showall = false;

/* The size of our canvas, and each individual square within. */
const canvassize = 400;
const squaresize = 40;

/* The number of columns and rows to display in our canvas. */
const cols = 10;
const rows = 10;

/* Generate a random weight for each of our nodes. */
function randomWeight() {
    var randomWeight = (AB.randomFloatAtoB(-0.5, 0.5));
    console.log("Initialising random weight at: " + randomWeight);
    return randomWeight;
}

/* Initialise our neural network. */
function setup() {
    createCanvas(canvassize, canvassize);
    
    $.getScript("/uploads/codingtrain/matrix.js", function() {
        $.getScript("/uploads/codingtrain/nn.js", function() {
            nn = new NeuralNetwork(noinput, nohidden, nooutput);
        });
   });
}

/* Draw the graphical representation of our neural network being trained. */
function draw() {
    /* Determine whether or not our libraries have been loaded yet. */
    if (typeof nn == 'undefined') return;
    
    /* Set the learning rate for our neural network. */
    nn.setLearningRate(learningrate);
    
    /* Set the background colour. */
    background('#ffffcc'); 
    
    /* Train our neural network 'n' times. */
    for (let i = 0; i < notrain ; i++) {
        let data = random(training_data);
        nn.train(data.inputs, data.outputs);
    }
    
    /* Draw either some, or all of the squares. */
    if (showall) {
        for (let i = 0; i < cols; i++) {
            for (let j = 0; j < rows; j++) {
                drawsquare(i, j);
            }
        }
    } else {
        for (let i = 0; i < cols; i = i + cols - 1) {
            for (let j = 0; j < rows; j = j + rows - 1) {
                drawsquare(i, j);
            }
        }
    }
}  
     
/* Draw a square at the specified coordinates. */
function drawsquare(i, j) {
    let x1 = i / cols;
    let x2 = j / rows;
    let inputs = [x1, x2];
    let y = nn.predict(inputs);
    console.log("Output (" + i + ", " + j + "): " + y);

    strokeWeight(2);
    stroke('black');
    fill(y * 255);
      
    rect(i * squaresize, j * squaresize, squaresize, squaresize);
}