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‎SmartSnakesCombine/Food.pde

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class Food {
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PVector pos;//position of food
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//constructor
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Food() {
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pos = new PVector();
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// set position to a random spot
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pos.x = 400+floor(random(0, 40)) * 10;
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pos.y = floor(random(0, 40)) * 10;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//show the food as a red square
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void show() {
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fill(255, 0, 0);
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rect(pos.x, pos.y, 10, 10);
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//return a clone of this food
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Food clone() {
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Food clone = new Food();
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clone.pos = new PVector(pos.x, pos.y);
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return clone;
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}
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}

‎SmartSnakesCombine/Matrix.pde

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class Matrix {
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//local variables
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int rows;
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int cols;
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float[][] matrix;
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//constructor
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Matrix(int r, int c) {
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rows = r;
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cols = c;
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matrix = new float[rows][cols];
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//constructor from 2D array
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Matrix(float[][] m) {
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matrix = m;
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cols = m.length;
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rows = m[0].length;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//print matrix
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void output() {
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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print(matrix[i][j] + " ");
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}
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println(" ");
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}
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println();
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//multiply by scalar
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void multiply(float n ) {
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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matrix[i][j] *= n;
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}
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}
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//return a matrix which is this matrix dot product parameter matrix
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Matrix dot(Matrix n) {
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Matrix result = new Matrix(rows, n.cols);
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if (cols == n.rows) {
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//for each spot in the new matrix
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<n.cols; j++) {
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float sum = 0;
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for (int k = 0; k<cols; k++) {
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sum+= matrix[i][k]*n.matrix[k][j];
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}
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result.matrix[i][j] = sum;
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}
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}
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}
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return result;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//set the matrix to random ints between -1 and 1
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void randomize() {
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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matrix[i][j] = random(-1, 1);
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}
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}
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//add a scalar to the matrix
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void Add(float n ) {
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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matrix[i][j] += n;
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}
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}
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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///return a matrix which is this matrix + parameter matrix
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Matrix add(Matrix n ) {
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Matrix newMatrix = new Matrix(rows, cols);
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if (cols == n.cols && rows == n.rows) {
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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newMatrix.matrix[i][j] = matrix[i][j] + n.matrix[i][j];
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}
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}
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}
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return newMatrix;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//return a matrix which is this matrix - parameter matrix
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Matrix subtract(Matrix n ) {
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Matrix newMatrix = new Matrix(cols, rows);
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if (cols == n.cols && rows == n.rows) {
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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newMatrix.matrix[i][j] = matrix[i][j] - n.matrix[i][j];
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}
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}
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}
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return newMatrix;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//return a matrix which is this matrix * parameter matrix (element wise multiplication)
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Matrix multiply(Matrix n ) {
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Matrix newMatrix = new Matrix(rows, cols);
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if (cols == n.cols && rows == n.rows) {
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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newMatrix.matrix[i][j] = matrix[i][j] * n.matrix[i][j];
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}
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}
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}
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return newMatrix;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//return a matrix which is the transpose of this matrix
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Matrix transpose() {
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Matrix n = new Matrix(cols, rows);
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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n.matrix[j][i] = matrix[i][j];
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}
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}
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return n;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//Creates a single column array from the parameter array
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Matrix singleColumnMatrixFromArray(float[] arr) {
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Matrix n = new Matrix(arr.length, 1);
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for (int i = 0; i< arr.length; i++) {
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n.matrix[i][0] = arr[i];
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}
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return n;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//sets this matrix from an array
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void fromArray(float[] arr) {
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for (int i = 0; i< rows; i++) {
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for (int j = 0; j< cols; j++) {
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matrix[i][j] = arr[j+i*cols];
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}
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}
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//returns an array which represents this matrix
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float[] toArray() {
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float[] arr = new float[rows*cols];
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for (int i = 0; i< rows; i++) {
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for (int j = 0; j< cols; j++) {
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arr[j+i*cols] = matrix[i][j];
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}
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}
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return arr;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//for ix1 matrixes adds one to the bottom
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Matrix addBias() {
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Matrix n = new Matrix(rows+1, 1);
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for (int i =0; i<rows; i++) {
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n.matrix[i][0] = matrix[i][0];
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}
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n.matrix[rows][0] = 1;
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return n;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//applies the activation function(sigmoid) to each element of the matrix
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Matrix activate() {
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Matrix n = new Matrix(rows, cols);
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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n.matrix[i][j] = sigmoid(matrix[i][j]);
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}
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}
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return n;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//sigmoid activation function
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float sigmoid(float x) {
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float y = 1 / (1 + pow((float)Math.E, -x));
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return y;
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}
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//returns the matrix that is the derived sigmoid function of the current matrix
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Matrix sigmoidDerived() {
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Matrix n = new Matrix(rows, cols);
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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n.matrix[i][j] = (matrix[i][j] * (1- matrix[i][j]));
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}
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}
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return n;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//returns the matrix which is this matrix with the bottom layer removed
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Matrix removeBottomLayer() {
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Matrix n = new Matrix(rows-1, cols);
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for (int i =0; i<n.rows; i++) {
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for (int j = 0; j<cols; j++) {
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n.matrix[i][j] = matrix[i][j];
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}
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}
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return n;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//Mutation function for genetic algorithm
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void mutate(float mutationRate) {
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//for each element in the matrix
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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float rand = random(1);
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if (rand<mutationRate) {//if chosen to be mutated
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matrix[i][j] += randomGaussian()/5;//add a random value to it(can be negative)
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//set the boundaries to 1 and -1
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if (matrix[i][j]>1) {
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matrix[i][j] = 1;
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}
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if (matrix[i][j] <-1) {
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matrix[i][j] = -1;
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}
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}
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}
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}
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//returns a matrix which has a random number of values from this matrix and the rest from the parameter matrix
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Matrix crossover(Matrix partner) {
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Matrix child = new Matrix(rows, cols);
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//pick a random point in the matrix
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int randC = floor(random(cols));
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int randR = floor(random(rows));
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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if ((i< randR)|| (i==randR && j<=randC)) { //if before the random point then copy from this matric
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child.matrix[i][j] = matrix[i][j];
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} else { //if after the random point then copy from the parameter array
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child.matrix[i][j] = partner.matrix[i][j];
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}
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}
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}
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return child;
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}
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//---------------------------------------------------------------------------------------------------------------------------------------------------------
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//return a copy of this matrix
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Matrix clone() {
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Matrix clone = new Matrix(rows, cols);
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for (int i =0; i<rows; i++) {
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for (int j = 0; j<cols; j++) {
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clone.matrix[i][j] = matrix[i][j];
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}
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}
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return clone;
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}
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}

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