package jcgp.population;

import java.util.ArrayList;

import jcgp.Parameters;
import jcgp.Utilities;
import jcgp.fitness.ParameterMismatchException;

public class Chromosome {

	private Input[] inputs;
	private Node[][] nodes;
	private Output[] outputs;

	private ArrayList<Node> activeNodes;

	private int fitness = 0;
	private boolean recomputeActiveNodes = true;

	/**
	 * Initialise a chromosome with the specified parameters. Random valid connections
	 * are created.
	 * 
	 * @param outputs 
	 * @param columns 
	 * @param rows 
	 * @param inputs 
	 * 
	 */
	public Chromosome() {
		// allocate memory for all elements of the chromosome
		instantiateElements();
		// set random connections so that the chromosome can be evaluated
		initialiseConnections();
	}

	/**
	 * Copy constructor.
	 * 
	 * Initialise a new chromosome with the exact same connections as a given instance of Chromosome.
	 * 
	 * @param clone the chromosome to be copied
	 */
	public Chromosome(Chromosome clone) {
		// allocate memory for all elements of the chromosome
		instantiateElements();
		// initialise all connections based on argument
		copyConnections(clone);
	}

	/**
	 *
	 */
	private void instantiateElements() {
		inputs = new Input[Parameters.getInputs()];
		for (int i = 0; i < Parameters.getInputs(); i++) {
			inputs[i] = new Input(i);
		}

		// rows first
		nodes = new Node[Parameters.getRows()][Parameters.getColumns()];
		for (int r = 0; r < Parameters.getRows(); r++) {
			for (int c = 0; c < Parameters.getColumns(); c++) {
				nodes[r][c] = new Node(this, r, c);
			}
		}
		outputs = new Output[Parameters.getOutputs()];
		for (int o = 0; o < Parameters.getOutputs(); o++) {
			outputs[o] = new Output(this, o);
		}
	}

	/**
	 * 
	 */
	private void initialiseConnections() {

		// initialise nodes - [rows][columns]
		for (int r = 0; r < nodes.length; r++) {
			for (int c = 0; c < nodes[r].length; c++) {
				Connection[] connections = new Connection[Parameters.getMaxArity()];
				for (int i = 0; i < connections.length; i++) {
					connections[i] = getRandomConnection(c);
				}
				nodes[r][c].initialise(Utilities.getRandomFunction(), connections);
			}
		}

		for (Output output : outputs) {
			output.setConnection(getRandomConnection());
		}

	}

	/**
	 * @param clone
	 */
	private void copyConnections(Chromosome clone) {
		// copy nodes - [rows][columns]
		for (int r = 0; r < nodes.length; r++) {
			for (int c = 0; c < nodes[r].length; c++) {
				// make array of connections to initialise with
				Connection[] connections = new Connection[Parameters.getMaxArity()];
				// populate with connections equivalent to clone
				Connection copyConnection;
				for (int i = 0; i < connections.length; i++) {
					copyConnection = clone.getNode(r, c).getConnection(i);
					if (copyConnection instanceof Input) {
						connections[i] = inputs[((Input) copyConnection).getIndex()];
					} else if (copyConnection instanceof Node) {
						connections[i] = nodes[((Node) copyConnection).getRow()][((Node) copyConnection).getColumn()];
					} else {
						System.out.println("Warning: Connection of subtype " + copyConnection.getClass().toString() + " is not explicitly handled by copy constructor.");
					}
				}
				// initialise with copied arguments
				nodes[r][c].initialise(clone.getNode(r, c).getFunction(), connections);
			}
		}

		// do the same to outputs
		Connection copyOutput;
		for (int o = 0; o < outputs.length; o++) {
			copyOutput = clone.getOutput(o).getSource();
			if (copyOutput instanceof Input) {
				outputs[o].setConnection(inputs[((Input) copyOutput).getIndex()]);
			} else if (copyOutput instanceof Node) {
				outputs[o].setConnection(nodes[((Node) copyOutput).getRow()][((Node) copyOutput).getColumn()]);
			} else {
				// something bad happened
				System.out.println("Warning: Connection of subtype " + copyOutput.getClass().toString() + " is not explicitly handled by copy constructor.");
			}
		}
	}

	public Node getNode(int row, int column) {
		return nodes[row][column];
	}

	public Output getOutput(int index) {
		return outputs[index];
	}

	public Input getInput(int index) {
		return inputs[index];
	}

	public int getFitness() {
		return fitness;
	}

	public void setFitness(int newFitness) {
		fitness = newFitness;
	}

	/**
	 * 
	 * @param values
	 * @throws ParameterMismatchException
	 */
	public void setInputs(int ... values) throws ParameterMismatchException {
		// if the values provided don't match the specified number of inputs, the user should be warned
		if (values.length == inputs.length) {
			// set inputs for evaluation
			for (int i = 0; i < values.length; i++) {
				inputs[i].setValue(values[i]);
			}
		} else {
			throw new ParameterMismatchException();
		}
	}

	/**
	 * This method is useful for mutating chromosomes.
	 * 
	 * @return a random element that can be mutated - Node or Output
	 */
	public MutableElement getRandomMutableElement() {
		// choose output or node
		int index = Utilities.getRandomInt(outputs.length + Parameters.getNodeCount());

		if (index < outputs.length) {
			// outputs
			return outputs[index];
		} else {
			// node	
			index -= outputs.length;
			return nodes[index / Parameters.getColumns()][index % Parameters.getColumns()];
		}
	}

	/**
	 * Returns a random allowed connection respecting levels back.</br>
	 * This method may always pick inputs, as they can be picked
	 * regardless of the column.
	 * 
	 * @param column the column to use as reference
	 * @return a random connection
	 */
	public Connection getRandomConnection(int column) {
		// work out the allowed range obeying levels back
		int allowedColumns = ((column >= Parameters.getLevelsBack()) ? Parameters.getLevelsBack() : column);
		int offset = ((column - allowedColumns) * nodes.length) - inputs.length;

		// choose input or allowed node
		int index = Utilities.getRandomInt(inputs.length + (nodes.length * allowedColumns));
		if (index < inputs.length) {
			// input
			return inputs[index];
		} else {
			// node	
			// offset it to address the right columns
			index += offset;
			return nodes[index % nodes.length][index / nodes.length];
		}
	}

	/**
	 * This method will pick a completely random connection, independently
	 * of levels back, including inputs.
	 * 
	 * Useful for setting outputs.
	 * 
	 * 
	 * @return a random connection
	 */
	public Connection getRandomConnection() {
		// choose output or node
		int index = Utilities.getRandomInt(inputs.length + Parameters.getNodeCount());

		if (index < inputs.length) {
			// outputs
			return inputs[index];
		} else {
			// node	
			index -= inputs.length;
			return nodes[index / Parameters.getColumns()][index % Parameters.getColumns()];
		}
	}

	/**
	 * This causes the list of active nodes to be recomputed lazily (once it is actually requested).
	 */
	public void recomputeActiveNodes() {
		recomputeActiveNodes = true;
	}

	/**
	 * This method computes a list of active connections (if necessary) and returns it.
	 *
	 * @return
	 */
	public ArrayList<Node> getActiveNodes() {
		computeActiveNodes();
		return activeNodes;
	}

	private void computeActiveNodes() {
		// lazy recomputation has been triggered, do it
		if (recomputeActiveNodes) {
			recomputeActiveNodes = false;
			activeNodes = new ArrayList<Node>();

			for (Output output : outputs) {
				output.getActiveNodes(activeNodes);
			}
		}

	}

	public boolean compareTo(Chromosome chromosome) {
		for (int r = 0; r < Parameters.getRows(); r++) {
			for (int c = 0; c < Parameters.getColumns(); c++) {
				if (!(nodes[r][c].copyOf(chromosome.getNode(r, c)))) {
					return false;
				}
			}
		}
		
		for (int o = 0; o < Parameters.getOutputs(); o++) {
			if (!(outputs[o].copyOf(chromosome.getOutput(o)))) {
				return false;
			}
		}
		
		return true;
	}

	public boolean compareActiveTo(Chromosome chromosome) {
		// update list if it is out of date
		computeActiveNodes();
		
		if (activeNodes.size() == chromosome.getActiveNodes().size()) {
			for (int i = 0; i < activeNodes.size(); i++) {
				if (!(activeNodes.get(i).copyOf(chromosome.getActiveNodes().get(i)))){
					return false;
				}
			}
			return true;
		}
		return false;
	}
}