Null Pointer Exception
Hi,
I've been trying to figure out for the last few hours why I got this error but to no avail. I can't see which part of my code is pointing to null. If anyone can point out what's wrong and how to correct it please let me know. Here is the whole code, with the /*** ***/ highlighting the lines of code which the compiler is showing as part of the null pointer exception - It's highlighted 4 errors. I do know it has something to do with the line of code (highlighted) Collections.sort(modifiedOffSpring); and not anything to do with Collections.sort(populatn); .
publicclass Population{
public Database d =new Database();
public Random rand =new Random();
publicstatic ArrayList population =new ArrayList();
publicstatic ArrayList parents =new ArrayList();
publicstatic ArrayList children =new ArrayList();
publicvoid initialPopulation(){
double[] reuters ={
8.0, 9.0, 12.5, 11.5, 6, 7, 4, 2, 3, 4, 3, 5, 5.5};
Share s1 =new Share(reuters);
d.addShare(s1);
for (int i = 0; i < 12; i++){
Chromosome chr =new Chromosome(rand);
chr.setDatabase(d);
population.add(chr);
System.out.println("Chromosome Weights are: " + chr);
System.out.println("Chromosome Fitness Value is: " + chr.fitness(0));
System.out.println();
}
}
public ArrayList tournamentSelection(int tournamentSize){
ArrayList contenders =new ArrayList();
for (int n = 0; n < (population.size()); n = (n + tournamentSize)){
int j = 0;// pointer variable to keep contender's indexes 0-4 fixed for adding population elements
// Check that sample of 5 can be taken from population
if ( (n + tournamentSize) < population.size() ||
(n + tournamentSize) == population.size()){
for (int i = n; i < n + tournamentSize; i++){// Get as many chromosomes as specified by tournament size (which is 5)
contenders.add(j, population.get(i));
j++;
}
// Sort the sub-population in order of fitness (ascending order)
Collections.sort(contenders);
// Return the best two Chromosomes with the lowest fitness
parents.add(contenders.get(0));
parents.add(contenders.get(1));
for (int k = tournamentSize; k > 0; k--){
contenders.remove(k - 1);// remove all elements from contenders to start over and receive the next sample of tournamentSize
}
}
else{//If sample of 5 cannot be taken from population, break to terminate from first/outter for loop
break;
}
}
//for(int i=0; i<parents.size(); i++){
// System.out.println("parents "+ i+ " " + parents.get(i));}
// System.out.println("contenders"+contenders.toString());
return parents;
}
public ArrayList crossOver(ArrayList intermediateGen,double crossOverRate){//crossOverRate between 0.7 and 0.95, intermediateGen are the parents
//Shuffle parents to exclude any chance of bias
Collections.shuffle(intermediateGen,new Random());
for (int i = 0; i >< parents.size(); i++){
System.out.println("parents " + i +" " + parents.get(i));
}
for (int p = 0; p < parents.size() - 1; p = p + 2){
double random = rand.nextDouble();//Get a value between 0.0 and 1.0
if (random < crossOverRate || random == crossOverRate){// If value generated is less than or equal to crossOverRate, apply cross-over
int crossOverPoint = (rand.nextInt(11) + 1);//The cross over point is generated randomly, and must occur between bit index 1 and bit index 11 of the parent Chromosomes so that an actual cross-over will always occur.
System.out.println("Crossover Point " + crossOverPoint);
int[] childStart =newint[12];
int[] childFinish =newint[12];
int[] childStart2 =newint[12];
int[] childFinish2 =newint[12];
// Child one
//Copying bits before cross-over point from first parent
for (int j = 0; j < crossOverPoint; j++){
childStart[j] = ( (Chromosome) intermediateGen.get(p)).bit[j];
}
// Copying bits after cross-over point from second parent
for (int k = crossOverPoint; k < childFinish.length; k++){
childFinish[k] = ( (Chromosome) intermediateGen.get(p + 1)).bit[k];
}
children.add(new Chromosome(childStart, childFinish));//Creation of new child Chromosome
System.out.println("children list c1" + children.toString());
//Child two
//Copying bits before cross-over point from second parent
for (int m = 0; m < crossOverPoint; m++){
childStart2[m] = ( (Chromosome) intermediateGen.get(p + 1)).bit[m];
}
//Copying bits after cross-over point from first parent
for (int n = crossOverPoint; n < childFinish2.length; n++){
childFinish2[n] = ( (Chromosome) intermediateGen.get(p)).bit[n];
}
children.add(new Chromosome(childStart2, childFinish2));//Creation of new child Chromosome
System.out.println("children list c2" + children.toString());
}
else{//If no cross-over, then children are exact copies of their parents
System.out.println("No crossover this time");
children.add(parents.get(p));
children.add(parents.get(p + 1));
}
}
System.out.println("Children list in total " + children);
return children;
}
public ArrayList mutation(ArrayList offSpring,double mutationRate){//Mutation rate between 1% and 5%
int[] bitMutate =newint[1];
for (int i = 0; i < (offSpring.size()); i++){//Iterate through each Chromosome
System.out.println("Traversing through new Chromosome");
for (int k = 0; k < 12; k++){//Iterate through each bit of Chromosome
double random = rand.nextDouble();//Get a value between 0.0 and 1.0 for each bit
System.out.println("Random value as a % is " + (random * 100) +"%");
if (random < mutationRate || random == mutationRate){//If value generated is less than or equal to mutation rate, apply mutation
System.out.println("Mutation needed here");
bitMutate[0] = ( (Chromosome) offSpring.get(i)).bit[k];//Get bit and store its weight value temporarily into bitMutate
System.out.println("bit " + (k + 1) +" is of weight value " +
bitMutate[0]);
bitMutate[0] = rand.nextInt(6);//Mutate bit by generating a new weight value between 0 and 5
if (bitMutate[0] == ( (Chromosome) offSpring.get(i)).bit[k]){
System.out.println("New mutated weight is the same as original weight, therefore mutation will be applied again.");
bitMutate[0] = rand.nextInt(6);
}//If mutated value generated is the same as the weight value already in the chromosome, then generate a new mutated weight value
System.out.println("mutated weight value is now " + bitMutate[0]);
( (Chromosome) offSpring.get(i)).bit[k] = bitMutate[0];//Replace the corresponding bit value with the mutated bit value
System.out.println(
"Corresponding Chromosome bit value has been mutated to " +
( (Chromosome) offSpring.get(i)).bit[k]);
}
else{
System.out.println("No Mutation needed here.");
}
}
}
return offSpring;//Arraylist returned with new mutated values in the genes
}
publicvoid reinsertion(ArrayList populatn, ArrayList modifiedOffSpring){
Collections.sort(populatn);
System.out.println(populatn.toString());
Collections.sort(modifiedOffSpring);/****** ERROR *****/
//System.out.println(modifiedOffSpring.toString());
}
publicstaticvoid main(String args[]){
// Population p = new Population();
// p.initialPopulation();
// p.tournamentSelection(5);
}
}
publicclass Chromosome
implements Comparable{
int[] bit =newint[12];
Database db;
public Chromosome(Random rand){
for (int i = 0; i < 12; i++){
bit[i] = rand.nextInt(6);
}
}
public Chromosome(int[] cs,int[] cf){
for (int i = 0; i < cs.length; i++){
if (cs[i] == 0){}
else{
bit[i] = cs[i];
}
}
for (int j = 0; j < cf.length; j++){
if (cf[j] == 0){}
else{
bit[j] = cf[j];
}
}
}
public String toString(){
String result ="";
for (int i = 0; i < 12; i++){
result = result + bit[i] +",";
}
return result;
}
publicvoid setDatabase(Database d){
db = d;
}
publicdouble fitness(int share){
double prediction = 0;
int divisor = 0;
Share sh = db.getShare(share);/****ERROR****/
for (int i = 0; i < 12; i++){
prediction = prediction + bit[i] * sh.getPrice(i);
divisor = divisor + bit[i];
}
if (divisor != 0){
prediction = prediction / divisor;
}
else{
prediction = 0;
}
// System.out.println("Prediction Value is: " + prediction);
double actualPrice = sh.getPrice(12);
return Math.abs(prediction - actualPrice);
}
//Used for comparing the fitness values of each Chromosome object in the contender ArrayList for tournament selection in the Population class
publicint compareTo(Object otherChromosomeObject)throws ClassCastException{
if (! (otherChromosomeObjectinstanceof Chromosome)){
thrownew ClassCastException("A Chromosome object expected.");// Throws exception if objects being compared are not both of type Chromosome
}
Chromosome otherChromosome = (Chromosome) otherChromosomeObject;
if (this.fitness(0) < otherChromosome.fitness(0)){/****** ERROR ****/
return -1;
}
if (this.fitness(0) > otherChromosome.fitness(0)){
return 1;
}
return 0;
}
}
publicclass GenAlg{
publicstaticvoid main(String[] args){
/* Database d = new Database();
double[] dd = {
8.0, 9.0, 12.5, 11.5, 6, 7, 4, 2, 3, 4, 3, 5, 5.5};
Share s1 = new Share(dd);
d.addShare(s1);
ArrayList population = new ArrayList(); */
Population p =new Population();
p.initialPopulation();
p.tournamentSelection(5);
p.crossOver(p.parents, 0.9);
p.mutation(p.children, 0.05);//5 is the tournament selection size
p.reinsertion(p.population, p.children);/***** ERROR *****
// Random rand = new Random();
/* for (int i = 0; i < 10; i++) {
Chromosome c = new Chromosome(rand);
c.setDatabase(d);
population.add(c);
System.out.println("Chromosome Weights are: " + c);
System.out.println("Chromosome Fitness Value is: " + c.fitness(0));
System.out.println();
System.out.println(population.size());
System.out.println(population.toString());
}
*/
}
}
publicclass Share{
double[] prices =newdouble[13];
public Share(double[] pr){
prices = pr;
}
double getPrice(int i){
return prices[i];
}
}
import java.util.ArrayList;
import java.util.Random;
publicclass Database{
ArrayList sharedatavalues =new ArrayList();
publicvoid addShare(Share s){
sharedatavalues.add(s);
}
public Share getShare(int i){
return (Share) sharedatavalues.get(i);
}
}
