Develop Reference

How to find most common/rare bits in a set of BitSets?

I'm working on a file sync app similar to p2p, where files are mapped by BitSets. And trying to find most rare file pieces among peers to be sent first to the receiver.
package asd;
import java.util.Arrays;
import java.util.BitSet;
import java.util.Random;
public class ChoosePiece
{
static Random rand = new Random();
public static BitSet rand_bit_set(int size)
{
int n_long = (size + 64 -1)/64;
long a[] = new long[n_long];
for (int i = 0; i < a.length; i++) a[i] = rand.nextLong();
// clear unused bits of the last long
int m = size % 64;
a[n_long-1] <<= (64-m);
a[n_long-1] >>>= (64-m);
return BitSet.valueOf(a);
}
public static void main(String args[])
{
int n_sets = 5;
int size = 20;
System.out.println("======== receiver map ==========================");
BitSet reciever_map = rand_bit_set(size);
print(reciever_map, size);
System.out.println("======== peers maps ============================");
BitSet bs[] = new BitSet[n_sets];
for (int i = 0; i < bs.length; i++) bs[i] = rand_bit_set(size);
for (int i = 0; i < bs.length; i++) print(bs[i], size);
IdxCnt cnt[] = new IdxCnt[size];
for (int i = 0; i < cnt.length; i++) cnt[i] = new IdxCnt(i, 0);
for (int i = reciever_map.nextSetBit(0); i >= 0; i = reciever_map.nextSetBit(i+1))
{
for (int j = 0; j < bs.length; j++)
{
if (reciever_map.get(i) && bs[j].get(i)) cnt[i].cnt++;
}
if (i == Integer.MAX_VALUE) break; // or (i+1) would overflow
}
System.out.println("========== count ====================================");
System.out.println(Arrays.toString(cnt));
Arrays.sort(cnt);
System.out.println(Arrays.toString(cnt));
}
public static void print(BitSet bs, int size)
{
System.out.println(bs);
StringBuffer b = new StringBuffer();
for (int i = 0; i < size; i++)
{
char c = bs.get(i) ? '1' : '0';
b.append(c);
}
System.out.println(b.toString());
}
public static class IdxCnt implements Comparable<IdxCnt>
{
public int idx;
public int cnt;
public IdxCnt(int idx, int cnt)
{
this.idx = idx;
this.cnt = cnt;
}
#Override
public String toString()
{
return String.valueOf(cnt);
}
#Override
public int compareTo(IdxCnt o)
{
return -Integer.compare(cnt, o.cnt);
}
}
}
The above code basically counts the bits set, I wander if there is a better way to find most common/rate bits using logical operations over BitSet? Feel like there should be, could be wrong.

How to write PI calculation program in Java using multi-thread?

I need to create a program that can calculate approximation to the constant PI, using Java multi-thread.
I'm intent to use Gregory-Leibniz Series to calculate the result for PI / 4, and then multiply by 4 to get the PI approximation.
But I have some concern about the program:
How can I seperate the calculation process so that I can implement a multi-thread processing for the program? Because the formula is for the total sum, I don't know how to split them into parts and then in the end I will collect them all.
I'm thinking about the fact that the program will execute the formula to infinite so user will need to provide some means of configuring the execution in order to determine when it should stop and return a result. Is it possible and how can I do that?
This is so far the most I can do by now.
public class PICalculate {
public static void main(String[] args) {
System.out.println(calculatePI(5000000) * 4);
}
static double calculatePI(int n) {
double result = 0.0;
if (n < 0) {
return 0.0;
}
for (int i = 0; i <= n; i++) {
result += Math.pow(-1, i) / ((2 * i) + 1);
}
return result;
}
}

The most straightforward, but not the most optimal, approach is to distribute the sequence elements between threads you have. Ie, if you have 4 threads, thread one will work with n%4 == 0 elements, thread2 with n%4 == 1 elements and so on
public static void main(String ... args) throws InterruptedException {
int threadCount = 4;
int N = 100_000;
PiThread[] threads = new PiThread[threadCount];
for (int i = 0; i < threadCount; i++) {
threads[i] = new PiThread(threadCount, i, N);
threads[i].start();
}
for (int i = 0; i < threadCount; i++) {
threads[i].join();
}
double pi = 0;
for (int i = 0; i < threadCount; i++) {
pi += threads[i].getSum();
}
System.out.print("PI/4 = " + pi);
}
static class PiThread extends Thread {
private final int threadCount;
private final int threadRemainder;
private final int N;
private double sum = 0;
public PiThread(int threadCount, int threadRemainder, int n) {
this.threadCount = threadCount;
this.threadRemainder = threadRemainder;
N = n;
}
#Override
public void run() {
for (int i = 0; i <= N; i++) {
if (i % threadCount == threadRemainder) {
sum += Math.pow(-1, i) / (2 * i + 1);
}
}
}
public double getSum() {
return sum;
}
}
PiThread is more efficient, but arguably harder to read, if the loop is shorter:
public void run() {
for (int i = threadRemainder; i <= N; i += threadCount) {
sum += Math.pow(-1, i) / (2 * i + 1);
}
}
In case you don't want to limit yourself with number of elements in sequence and just by time, you may follow an approach below. But note, that it is still limited with Long.MAX_VALUE and you'll have to use BigIntegers, BigDecimals or any other reasonable approach to improve it
public static volatile boolean running = true;
public static void main(String ... args) throws InterruptedException {
int threadCount = 4;
long timeoutMs = 5_000;
final AtomicLong counter = new AtomicLong(0);
PiThread[] threads = new PiThread[threadCount];
for (int i = 0; i < threadCount; i++) {
threads[i] = new PiThread(counter);
threads[i].start();
}
Thread.sleep(timeoutMs);
running = false;
for (int i = 0; i < threadCount; i++) {
threads[i].join();
}
double sum = 0;
for (int i = 0; i < threadCount; i++) {
sum += threads[i].getSum();
}
System.out.print("counter = " + counter.get());
System.out.print("PI = " + 4*sum);
}
static class PiThread extends Thread {
private AtomicLong counter;
private double sum = 0;
public PiThread(AtomicLong counter) {
this.counter = counter;
}
#Override
public void run() {
long i;
while (running && isValidCounter(i = counter.getAndAdd(1))) {
sum += Math.pow(-1, i) / (2 * i + 1);
}
}
private boolean isValidCounter(long value) {
return value >= 0 && value < Long.MAX_VALUE;
}
public double getSum() {
return sum;
}
}

Code compiles and executes, but does not print anything

The time-limit-extended is the status when executing the successfully compiled class file of the following code.
import java.io.*;
public class CandidateCode {
public static int ThirstyCrowProblem(int[] input1, int input2, int input3) {
int[] arrK = new int[input3];
int minstones = 0;
for (int i = 0; i < input3; i++) //create an array of k Os.
{
int smallest = input1[0], place = 0;
for (int j = 0; j < input2; j++) {
if ((smallest >= input1[j]) && (input1[j] >= 0)) {
smallest = input1[j];
place = j;
}
}
input1[place] = -1;
arrK[i] = smallest;
}
int n = input2, i = 0;
while (i < input3)
minstones = minstones + arrK[i] * (n - i);
return minstones;
}
public static void main(String[] args) {
int[] arr = new int[] {
5, 58
};
int stones_min = CandidateCode.ThirstyCrowProblem(arr, 2, 1);
System.out.println("The result is" + stones_min);
}
}
The cursor is waiting and waiting, but I don't think there is an error in the code!??

Option A :
Change your while into an if statement :
if(i<input3) {
minstones= minstones + arrK[i]*(n-i);
}
Option B : or increment i (i++) but I don't this that's what you want
while(i<input3) {
minstones = minstones + arrK[i]*(n-i);
i++;
}

You need to increment i in your while loop.Since you are not incrementing,its going in infinite loop.
while(i<input3)
{
minstones= minstones + arrK[i]*(n-i);
i++;
}
After making this change,I got
The result is10

Program with threads for matrix multiplication

I'm trying to create a Java program with threads for matrix multiplication. This is the source code:
import java.util.Random;
public class MatrixTest {
//Creating the matrix
static int[][] mat = new int[3][3];
static int[][] mat2 = new int[3][3];
static int[][] result = new int[3][3];
public static void main(String[] args) {
//Creating the object of random class
Random rand = new Random();
//Filling first matrix with random values
for (int i = 0; i < mat.length; i++) {
for (int j = 0; j < mat[i].length; j++) {
mat[i][j] = rand.nextInt(10);
}
}
//Filling second matrix with random values
for (int i = 0; i < mat2.length; i++) {
for (int j = 0; j < mat2[i].length; j++) {
mat2[i][j] = rand.nextInt(10);
}
}
try {
//Object of multiply Class
Multiply multiply = new Multiply(3, 3);
//Threads
MatrixMultiplier thread1 = new MatrixMultiplier(multiply);
MatrixMultiplier thread2 = new MatrixMultiplier(multiply);
MatrixMultiplier thread3 = new MatrixMultiplier(multiply);
//Implementing threads
Thread th1 = new Thread(thread1);
Thread th2 = new Thread(thread2);
Thread th3 = new Thread(thread3);
//Starting threads
th1.start();
th2.start();
th3.start();
th1.join();
th2.join();
th3.join();
} catch (Exception e) {
e.printStackTrace();
}
//Printing the result
System.out.println("\n\nResult:");
for (int i = 0; i < result.length; i++) {
for (int j = 0; j < result[i].length; j++) {
System.out.print(result[i][j] + " ");
}
System.out.println();
}
}//End main
}//End Class
//Multiply Class
class Multiply extends MatrixTest {
private int i;
private int j;
private int chance;
public Multiply(int i, int j) {
this.i = i;
this.j = j;
chance = 0;
}
//Matrix Multiplication Function
public synchronized void multiplyMatrix() {
int sum = 0;
int a = 0;
for (a = 0; a < i; a++) {
sum = 0;
for (int b = 0; b < j; b++) {
sum = sum + mat[chance][b] * mat2[b][a];
}
result[chance][a] = sum;
}
if (chance >= i)
return;
chance++;
}
}//End multiply class
//Thread Class
class MatrixMultiplier implements Runnable {
private final Multiply mul;
public MatrixMultiplier(Multiply mul) {
this.mul = mul;
}
#Override
public void run() {
mul.multiplyMatrix();
}
}
I just tried on Eclipse and it works, but now I want to create another version of that program in which, I use one thread for each cell that I'll have on the result matrix. For example I've got two 3x3 matrices. So the result matrix will be 3x3. Then, I want to use 9 threads to calculate each one of the 9 cells of the result matrix.
Can anyone help me?

You can create n Threads as follows (Note: numberOfThreads is the number of threads that you want to create. This will be the number of cells):
List<Thread> threads = new ArrayList<>(numberOfThreads);
for (int x = 0; x < numberOfThreads; x++) {
Thread t = new Thread(new MatrixMultiplier(multiply));
t.start();
threads.add(t);
}
for (Thread t : threads) {
t.join();
}

Please use the new Executor framework to create Threads, instead of manually doing the plumbing.
ExecutorService executor = Executors.newFixedThreadPool(numberOfThreadsInPool);
for (int i = 0; i < numberOfThreads; i++) {
Runnable worker = new Thread(new MatrixMultiplier(multiply));;
executor.execute(worker);
}
executor.shutdown();
while (!executor.isTerminated()) {
}

With this code i think that i resolve my problem. I don't use synchronized in the methods but i think that is not necessary in that case.
import java.util.Scanner;
class MatrixProduct extends Thread {
private int[][] A;
private int[][] B;
private int[][] C;
private int rig, col;
private int dim;
public MatrixProduct(int[][] A, int[][] B, int[][] C, int rig, int col, int dim_com) {
this.A = A;
this.B = B;
this.C = C;
this.rig = rig;
this.col = col;
this.dim = dim_com;
}
public void run() {
for (int i = 0; i < dim; i++) {
C[rig][col] += A[rig][i] * B[i][col];
}
System.out.println("Thread " + rig + "," + col + " complete.");
}
}
public class MatrixMultiplication {
public static void main(String[] args) {
Scanner In = new Scanner(System.in);
System.out.print("Row of Matrix A: ");
int rA = In.nextInt();
System.out.print("Column of Matrix A: ");
int cA = In.nextInt();
System.out.print("Row of Matrix B: ");
int rB = In.nextInt();
System.out.print("Column of Matrix B: ");
int cB = In.nextInt();
System.out.println();
if (cA != rB) {
System.out.println("We can't do the matrix product!");
System.exit(-1);
}
System.out.println("The matrix result from product will be " + rA + " x " + cB);
System.out.println();
int[][] A = new int[rA][cA];
int[][] B = new int[rB][cB];
int[][] C = new int[rA][cB];
MatrixProduct[][] thrd = new MatrixProduct[rA][cB];
System.out.println("Insert A:");
System.out.println();
for (int i = 0; i < rA; i++) {
for (int j = 0; j < cA; j++) {
System.out.print(i + "," + j + " = ");
A[i][j] = In.nextInt();
}
}
System.out.println();
System.out.println("Insert B:");
System.out.println();
for (int i = 0; i < rB; i++) {
for (int j = 0; j < cB; j++) {
System.out.print(i + "," + j + " = ");
B[i][j] = In.nextInt();
}
}
System.out.println();
for (int i = 0; i < rA; i++) {
for (int j = 0; j < cB; j++) {
thrd[i][j] = new MatrixProduct(A, B, C, i, j, cA);
thrd[i][j].start();
}
}
for (int i = 0; i < rA; i++) {
for (int j = 0; j < cB; j++) {
try {
thrd[i][j].join();
} catch (InterruptedException e) {
}
}
}
System.out.println();
System.out.println("Result");
System.out.println();
for (int i = 0; i < rA; i++) {
for (int j = 0; j < cB; j++) {
System.out.print(C[i][j] + " ");
}
System.out.println();
}
}
}

Consider Matrix.java and Main.java as follows.
public class Matrix extends Thread {
private static int[][] a;
private static int[][] b;
private static int[][] c;
/* You might need other variables as well */
private int i;
private int j;
private int z1;
private int s;
private int k;
public Matrix(int[][] A, final int[][] B, final int[][] C, int i, int j, int z1) { // need to change this, might
// need some information
a = A;
b = B;
c = C;
this.i = i;
this.j = j;
this.z1 = z1; // a[0].length
}
public void run() {
synchronized (c) {
// 3. How to allocate work for each thread (recall it is the run function which
// all the threads execute)
// Here this code implements the allocated work for perticular thread
// Each element of the resulting matrix will generate by a perticular thread
for (s = 0, k = 0; k < z1; k++)
s += a[i][k] * b[k][j];
c[i][j] = s;
}
}
public static int[][] returnC() {
return c;
}
public static int[][] multiply(final int[][] a, final int[][] b) {
/*
* check if multipication can be done, if not return null allocate required
* memory return a * b
*/
final int x = a.length;
final int y = b[0].length;
final int z1 = a[0].length;
final int z2 = b.length;
if (z1 != z2) {
System.out.println("Cannnot multiply");
return null;
}
final int[][] c = new int[x][y];
int i, j;
// 1. How to use threads to parallelize the operation?
// Every element in the resulting matrix will be determined by a different
// thread
// 2. How may threads to use?
// x * y threads are used to generate the result.
for (i = 0; i < x; i++)
for (j = 0; j < y; j++) {
try {
Matrix temp_thread = new Matrix(a, b, c, i, j, z1);
temp_thread.start();
// 4. How to synchronize?
// synchronized() is used with join() to guarantee that the perticular thread
// will be accessed first
temp_thread.join();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
return Matrix.returnC();
}
}
You can use Main.java to give 2 matrices that need to be multiplied.
class Main {
public static int[][] a = {
{1, 1, 1},
{1, 1, 1},
{1, 1, 1}};
public static int[][] b = {
{1},
{1},
{1}};
public static void print_matrix(int[][] a) {
for (int i = 0; i < a.length; i++) {
for (int j = 0; j < a[i].length; j++)
System.out.print(a[i][j] + " ");
System.out.println();
}
}
public static void main(String[] args) {
int[][] x = Matrix.multiply(a, b);
print_matrix(x); // see if the multipication is correct
}
}

In simple terms, what you all need to do is,
1) Create n (no of cells in resultant matrix) threads. Assign their roles. (Ex: Consider M X N, where M and N are matrices. 'thread1' is responsible for the multiplication of M's row_1 elements with N's column_1 elements and storing the result. This is the value for the resultant matrix's cell_1.)
2) Start each thread's process. (by start() method)
3) Wait until all the threads finish their processes and store the resultant value of each cell. Because those processes should be finished before displaying the resultant matrix. (You can do this by join() methods, and other possibilities too)
4) Now, you can display the resultant matrix.
Note:
1) Since, in this example, the shared resources (M and N) are only used to read only purpose, you don't need to use 'synchronized' methods to access them.
2) You can see, in this program, there are a group of threads running and all of them needs to achieve a specific status by their own, before continuing the next step of the whole program. This multi-threaded programming model is known as a Barrier.

Tried below code in eclipse as per thread for each cell. It works fine, you can check it.
class ResMatrix {
static int[][] arrres = new int[2][2];
}
class Matrix {
int[][] arr = new int[2][2];
void setV(int v) {
//int tmp = v;
for (int i = 0; i < 2; i++) {
for (int j = 0; j < 2; j++) {
arr[i][j] = v;
v = v + 1;
}
}
}
int[][] getV() {
return arr;
}
}
class Mul extends Thread {
public int row;
public int col;
Matrix m;
Matrix m1;
Mul(int row, int col, Matrix m, Matrix m1) {
this.row = row;
this.col = col;
this.m = m;
this.m1 = m1;
}
public void run() {
//System.out.println("Started Thread: " + Thread.currentThread().getName());
int tmp = 0;
for (int i = 0; i < 2; i++) {
tmp = tmp + this.m.getV()[row][i] * this.m1.getV()[i][col];
}
ResMatrix.arrres[row][col] = tmp;
System.out.println("Started Thread END: " + Thread.currentThread().getName());
}
}
public class Test {
//static int[][] arrres =new int[2][2];
public static void main(String[] args) throws InterruptedException {
Matrix mm = new Matrix();
mm.setV(1);
Matrix mm1 = new Matrix();
mm1.setV(2);
for (int i = 0; i < 2; i++) {
for (int j = 0; j < 2; j++) {
Mul mul = new Mul(i, j, mm, mm1);
mul.start();
// mul.join();
}
}
for (int i = 0; i < 2; i++) {
for (int j = 0; j < 2; j++) {
System.out.println("VALUE: " + ResMatrix.arrres[i][j]);
}
}
}
}

In my solution I assigned to each worker a number of rows numRowForThread equals to: (number of rows of matA) / (number of threads).
public class MatMulConcur {
private final static int NUM_OF_THREAD = 1;
private static Mat matC;
public static Mat matmul(Mat matA, Mat matB) {
matC = new Mat(matA.getNRows(), matB.getNColumns());
return mul(matA, matB);
}
private static Mat mul(Mat matA, Mat matB) {
int numRowForThread;
int numRowA = matA.getNRows();
int startRow = 0;
Worker[] myWorker = new Worker[NUM_OF_THREAD];
for (int j = 0; j < NUM_OF_THREAD; j++) {
if (j < NUM_OF_THREAD - 1) {
numRowForThread = (numRowA / NUM_OF_THREAD);
} else {
numRowForThread = (numRowA / NUM_OF_THREAD) + (numRowA % NUM_OF_THREAD);
}
myWorker[j] = new Worker(startRow, startRow + numRowForThread, matA, matB);
myWorker[j].start();
startRow += numRowForThread;
}
for (Worker worker : myWorker) {
try {
worker.join();
} catch (InterruptedException e) {
}
}
return matC;
}
private static class Worker extends Thread {
private int startRow, stopRow;
private Mat matA, matB;
public Worker(int startRow, int stopRow, Mat matA, Mat matB) {
super();
this.startRow = startRow;
this.stopRow = stopRow;
this.matA = matA;
this.matB = matB;
}
#Override
public void run() {
for (int i = startRow; i < stopRow; i++) {
for (int j = 0; j < matB.getNColumns(); j++) {
double sum = 0;
for (int k = 0; k < matA.getNColumns(); k++) {
sum += matA.get(i, k) * matB.get(k, j);
}
matC.set(i, j, sum);
}
}
}
}
}
where for the class Mat, I used this implementation:
public class Mat {
private double[][] mat;
public Mat(int n, int m) {
mat = new double[n][m];
}
public void set(int i, int j, double v) {
mat[i][j] = v;
}
public double get(int i, int j) {
return mat[i][j];
}
public int getNRows() {
return mat.length;
}
public int getNColumns() {
return mat[0].length;
}
}

java version of bat algorithm in matlab

I have a Matlab code of bat algorithm and I write java version of this algorithm
Bat algorithm is a simple optimization algorithm for finding the minimum of any function
here is the matlab code and my java version of this code
My java version of this algorithm can't find the optimum result like matlab version
and I can't find where is my mistake in converting the code from matlab to java
Can anyone help me where is my mistake?
import java.util.Random;
public class Bat
{
private int n;
private float A, r;
private float Qmin, Qmax;
private int d;
private int NofGen;
private float fmin;
private int fminIndex;
private float Fnew;
private int loopCounter;
private float Q[], V[][], Sol[][], UL_bound[][], fitness[], S[][], Best[];
private Random myRand;
public Bat(
int NBats,
float loudness,
float pulseRate,
float minFreq,
float maxFreq,
int NofGeneration,
int dimension
)
{
n = NBats;
A = loudness;
r = pulseRate;
Qmin = minFreq;
Qmax = maxFreq;
NofGen = NofGeneration;
d = dimension;
S = new float[n][d];
Best = new float[d];
UL_bound = new float[2][d];
//default bounds
for(int i = 0 ; i < d ; i++)
{
UL_bound[0][i] = -10000;
UL_bound[1][i] = 10000;
}
loopCounter = 0;
myRand = new Random();
Q = new float[n];
for(int i = 0 ; i < n ; i++)
Q[i] = 0;
V = new float[n][d];
for(int i = 0 ; i < n ; i++)
for(int j = 0 ; j < d ; j++)
V[i][j] = 0;
}
public void intial()
{
Sol = new float[n][d];
for(int i = 0 ; i < n ; i++)
for(int j = 0 ; j < d ; j++)
{
float t = myRand.nextFloat();
//(upper -lower)*rand + lower
Sol[i][j] = t * (UL_bound[1][j] - UL_bound[0][j]) + UL_bound[0][j];
}
fitness = new float[n];
for(int i = 0 ; i < n ; i++)
fitness[i] = function(Sol[i]);
//finding fmin
fmin = fitness[0];
fminIndex = 0;
for(int i = 0 ; i < n ; i++)
{
if (fitness[i] < fmin)
{
fmin = fitness[i];
fminIndex = i;
}
}
//setting best
for(int j = 0 ; j < d ; j++)
Best[j] = Sol[fminIndex][j];
}
public void start()
{
while(loopCounter < NofGen)
{
for(int i = 0 ; i < n ; i++)
{
Q[i] = Qmin + (Qmin - Qmax)* myRand.nextFloat();
for(int j = 0 ; j < d ; j++)
V[i][j] = V[i][j] + (Sol[i][j]-Best[j])*Q[i];
for(int j = 0 ; j < d ; j++)
S[i][j] = Sol[i][j] + V[i][j];
Sol[i] = simpleBounds(Sol[i]);
if(myRand.nextFloat() > r)
for(int j = 0 ; j < d ; j++)
S[i][j] = (float) (Best[j] + (.001 * myRand.nextFloat()) );
Fnew = function(S[i]);
if(Fnew <= fitness[i] && myRand.nextFloat() < A)
{
for(int j = 0 ; j < d ; j++)
Sol[i][j] = S[i][j];
fitness[i] = Fnew;
}
if(Fnew <= fmin)
{
fmin = Fnew;
for(int j = 0 ; j < d ; j++)
Best[j] = S[i][j];
}
}
loopCounter++;
}
}
public float[] simpleBounds(float p[])
{
for(int i = 0 ; i < d ; i++)
{
if(p[i] < UL_bound[0][i])
p[i] = UL_bound[0][i];
if(p[i] > UL_bound[1][i])
p[i] = UL_bound[1][i];
}
return p;
}
float function(float p[])
{
// Sphere function with fmin=0 at (0,0,...,0)
float sum = 0;
for(int i = 0 ; i < p.length ; i++)
sum = sum + p[i]*p[i];
return sum;
}
public float printResult()
{
System.out.println("After " + loopCounter + "Repeats :");
for(int i = 0 ; i < d ; i++)
System.out.print(Best[i] + ", ");
System.out.println ( "F(x) = " + fmin);
return fmin;
}
public void set_UL_Bound(int n, float L, float U)
{
if( n < d && n >= 0)
{
UL_bound[0][n] = L;
UL_bound[1][n] = U;
}
}
}
and this is the matlab versian
function [best,fmin,N_iter]=bat_algorithm(para)
% Display help
help bat_algorithm.m
% Default parameters
if nargin<1, para=[20 1000 0.5 0.5]; end
n=para(1); % Population size, typically 10 to 40
N_gen=para(2); % Number of generations
A=para(3); % Loudness (constant or decreasing)
r=para(4); % Pulse rate (constant or decreasing)
% This frequency range determines the scalings
% You should change these values if necessary
Qmin=0; % Frequency minimum
Qmax=2; % Frequency maximum
% Iteration parameters
N_iter=0; % Total number of function evaluations
% Dimension of the search variables
d=5; % Number of dimensions
% Lower limit/bounds/ a vector
Lb=-3*ones(1,d);
% Upper limit/bounds/ a vector
Ub=6*ones(1,d);
% Initializing arrays
Q=zeros(n,1); % Frequency
v=zeros(n,d); % Velocities
% Initialize the population/solutions
for i=1:n,
Sol(i,:)=Lb+(Ub-Lb).*rand(1,d);
Fitness(i)=Fun(Sol(i,:));
end
% Find the initial best solution
[fmin,I]=min(Fitness);
best=Sol(I,:);
for t=1:N_gen,
% Loop over all bats/solutions
for i=1:n,
Q(i)=Qmin+(Qmin-Qmax)*rand;
v(i,:)=v(i,:)+(Sol(i,:)-best)*Q(i);
S(i,:)=Sol(i,:)+v(i,:);
% Apply simple bounds/limits
Sol(i,:)=simplebounds(Sol(i,:),Lb,Ub);
% Pulse rate
if rand>r
% The factor 0.001 limits the step sizes of random walks
S(i,:)=best+0.001*randn(1,d);
end
% Evaluate new solutions
Fnew=Fun(S(i,:));
% Update if the solution improves, or not too loud
if (Fnew<=Fitness(i)) & (rand<A) ,
Sol(i,:)=S(i,:);
Fitness(i)=Fnew;
end
% Update the current best solution
if Fnew<=fmin,
best=S(i,:);
fmin=Fnew;
end
end
N_iter=N_iter+n;
end
% Output/display
disp(['Number of evaluations: ',num2str(N_iter)]);
disp(['Best =',num2str(best),' fmin=',num2str(fmin)]);
% Application of simple limits/bounds
function s=simplebounds(s,Lb,Ub)
% Apply the lower bound vector
ns_tmp=s;
I=ns_tmp<Lb;
ns_tmp(I)=Lb(I);
% Apply the upper bound vector
J=ns_tmp>Ub;
ns_tmp(J)=Ub(J);
% Update this new move
s=ns_tmp;
function z=Fun(u)
% Sphere function with fmin=0 at (0,0,...,0)
z=sum(u.^2);
%%%%% ============ end ====================================

The diff between two codes
In Matlab code:
S(i,:)=best+0.001*randn(1,d);
randn=>standard normal distribution.
While in Java code:
S[i][j] = (float) (Best[j] + (.001 * myRand.nextFloat()) );
java.util.Random.nextFloat()=>uniformly distributed float value between 0.0 and 1.0.

I was looking for the solution in C# and stumbled up on this. It was enough to get the job done. Here is the solution in C# translated from the java with variables renamed and an additional fitness function for finding the solution of two x,y equations xy=6 and x+y = 5. Also included is finding the square root of .3 :
using System;
namespace BatAlgorithmC
namespace BatAlgorithmC
{
class Program
{
static void Main(string[] args)
{
// Mybat x = new Mybat(100, 1000, 0.5, 0.5, 5, Mybat.sphere);
// Mybat x = new Mybat(1000, 1000, 0.5, 0.5, 1, Mybat.squareRoot);
Mybat x = new Mybat(1000, 1000, 0.5, 0.5, 2, Mybat.RootOfXYEquations);
Console.WriteLine("Hit any key to continue.");
Console.ReadLine();
}
}
public class Mybat
{
/**
* #param args the command line arguments
*/
public int _numberOfBats, _generations, Qmin, Qmax, N_iter, _dimension;
public double _volume, _pulseRate, min, max, fnew, fmin;
public double[][] _lowerBound, _upperBound, _velocity, _solution, S;
public double[] _fitness, _tempSolution, _bestSolution, Q;
public Random random;
//public static void main(String[] args) {
// Mybat x = new Mybat(20,1000,0.5,0.5,5, Mybat.sphere);
//}
public static void initJagged(double[][] array, int n, int d)
{
for (int i = 0; i < n; i++) array[i] = new double[d];
}
public Mybat(
int bats,
int generations,
double loud,
double pulse,
int dimension,
Func<double[], int, double> function
)
{
//initialization of variables
_numberOfBats = bats;
_generations = generations;
_volume = loud;
_pulseRate = pulse;
_dimension = dimension;
Random random = new Random();
//plan to change later and added as parameter
min = -15;
max = 15;
fmin = 0;
//decleration for the bounds
_lowerBound = new double[1][];
_upperBound = new double[1][];
Q = new double[_numberOfBats]; // frequency
_velocity = new double[_numberOfBats][]; //velocity
initJagged(_velocity, _numberOfBats, _dimension);
initJagged(_lowerBound, 1, _dimension);
initJagged(_upperBound, 1, _dimension);
//initialize solution array
_solution = new double[_numberOfBats][];
S = new double[_numberOfBats][];
_fitness = new double[_numberOfBats]; // fitness container
_bestSolution = new double[_dimension];
_tempSolution = new double[_dimension]; //temporary holder for a row in array _solution
initJagged(_solution, _numberOfBats, _dimension);
initJagged(S, _numberOfBats, _dimension);
for (int i = 0; i < _numberOfBats; i++)
{
// for minimal coding : added initialize Q[]array with '0' as element
Q[i] = 0;
for (int x = 0; x < _dimension; x++)
{
// for minimal coding : added initialize _velocity[][] array with '0' as element
_velocity[i][x] = 0;
//find random double values from LB to UB
_solution[i][x] = (random.NextDouble()*(max - min)) + min;
_tempSolution[x] = _solution[i][x];
//Console.WriteLine("sol["+i+"]["+x+"] = "+_solution[i][x]); //test line
//Console.WriteLine(rand.nextDouble()); //test line
}
_fitness[i] = function(_tempSolution, _dimension);
//initialize best and the fmin
if (i == 0 || fmin > _fitness[i])
{
fmin = _fitness[i];
for (int x = 0; x < _dimension; x++)
{
_bestSolution[x] = _solution[i][x];
}
}
Console.WriteLine("fitness[" + i + "]" + _fitness[i]); //test
}
Console.WriteLine("fmin = " + fmin); //test
// special note to these variables (below)
// change if required for maximum effectivity
Qmin = 0;
Qmax = 2;
N_iter = 1; //number of function evaluation
// bat proper
for (int loop = 0; loop < N_iter; loop++)
{
// loop over all bats/solutions
for (int nextBat = 0; nextBat < _numberOfBats; nextBat++)
{
Q[nextBat] = Qmin + ((Qmin - Qmax)*random.NextDouble());
// loop for velocity
for (int vel = 0; vel < _dimension; vel++)
{
_velocity[nextBat][vel] = _velocity[nextBat][vel] +
((_solution[nextBat][vel] - _bestSolution[vel])*Q[nextBat]);
}
//new solutions
for (int nextDimension = 0; nextDimension < _dimension; nextDimension++)
{
S[nextBat][nextDimension] = _solution[nextBat][nextDimension] +
_velocity[nextBat][nextDimension];
}
/**
* RESERVED SPOT for the QUESTIONABLE AREA ON THE
* MATLAB CODE (i think it is not needed for the java equivalent)
*/
// pulse rate
if (random.NextDouble() > _pulseRate)
{
for (int nextDimension = 0; nextDimension < _dimension; nextDimension++)
{
S[nextBat][nextDimension] = _bestSolution[nextDimension] + (0.001*random.NextGaussian());
}
}
//putting current row of _solution to a temp array
for (int nextDimension = 0; nextDimension < _dimension; nextDimension++)
{
_tempSolution[nextDimension] = S[nextBat][nextDimension];
}
fnew = function(_tempSolution, _dimension);
// update if solution is improved, and not too loud
if ((fnew <= _fitness[nextBat]) && (random.NextDouble() < _volume))
{
for (int x = 0; x < _dimension; x++)
{
_solution[nextBat][x] = S[nextBat][x];
_fitness[nextBat] = fnew;
}
}
//update current best solution
if (fnew <= fmin)
{
for (int nextDimension = 0; nextDimension < _dimension; nextDimension++)
{
_bestSolution[nextDimension] = S[nextBat][nextDimension];
fmin = fnew;
}
}
}
}
Console.WriteLine(" ");
Console.WriteLine("new fitness");
for (int i = 0; i < _numberOfBats; i++)
{
Console.WriteLine("fitness[" + i + "]" + _fitness[i]);
}
for (int nextDimension = 0; nextDimension < _dimension; nextDimension++)
{
Console.WriteLine("best[" + nextDimension + "]" + _bestSolution[nextDimension]);
}
Console.WriteLine("Fmin = " + fmin);
}
//possible that this function is not needed in java
public void set_bounds(int x, double L, double U)
{
//double temp_Lb[x];
//double temp_Ub[x];
for (int i = 0; i < x; i++)
{
_lowerBound[0][i] = L;
_upperBound[0][i] = U;
}
}
public static double sphere(double[] value, int d)
{
// sphere function where fmin is at 0
double result = 0;
for (int i = 0; i < d; i++)
{
result += (value[i]*value[i]);
}
return result;
}
public static double squareRoot(double[] value, int d)
{
// find the square root of .3
double result = 0;
for (int i = 0; i < d; i++)
{
result += Math.Abs(.3 - (value[i]*value[i]));
}
return result;
}
public static double RootOfXYEquations(double[] value, int d)
{
// solve for x and y xy = 6 and x+y = 5
double result = 0;
result += Math.Abs(5 - (value[0] + value[1]));
result += Math.Abs(6 - (value[0] * value[1]));
return result;
}
}
static class MathExtensiionns
{
public static double NextGaussian(this Random rand)
{
double u1 = rand.NextDouble(); //these are uniform(0,1) random doubles
double u2 = rand.NextDouble();
double mean = 0, stdDev = 1;
double randStdNormal = Math.Sqrt(-2.0 * Math.Log(u1)) *
Math.Sin(2.0 * Math.PI * u2); //random normal(0,1)
double randNormal =
mean + stdDev * randStdNormal; //random normal(mean,stdDev^2)
return randNormal;
}
}
}

this will be my first time here at stack overflow so i will say sorry beforehand if my response will be a bit ambiguous and has many problems. i just hope that this answer of mine will help future visitors on this thread who wants to study bat algo via java.
anyway, i did look at your code since i am studying bat algorithm at the moment.
tried running it and it does gives far off results compared to the matlab version.
what i noticed is that you just "literally" tried to convert the matlab code without fully understanding each matlab lines. i wanted to point out all of the stuff you missed but i am feeling lazy right now so i will just leave my version of bat algorithm in java.
NOTE: i just made a running bat algorithm in java. not an efficient, fully debugged, matlab's java-equivalent bat algorithm.
import java.util.Random;
public class Mybat {
/**
* #param args the command line arguments
*/
public int n, N_gen, Qmin, Qmax, N_iter, d;
public double A,r,min,max,fnew,fmin;
public double Lb[][],Ub[][],Q[],v[][],Sol[][],S[][],fitness[],temp[],best[];
public Random random;
public static void main(String[] args) {
Mybat x = new Mybat(20,1000,0.5,0.5,5);
}
public Mybat(
int bats,
int generations,
double loud,
double pulse,
int dimension
){
//initialization of variables
n=bats;
N_gen = generations;
A = loud;
r = pulse;
d = dimension;
Random rand = new Random();
//plan to change later and added as parameter
min = -15;
max = 15;
fmin = 0;
//decleration for the bounds
Lb = new double[1][d];
Ub = new double[1][d];
Q = new double[n]; // frequency
v = new double[n][d]; //velocity
//initialize solution array
Sol = new double[n][d];
S = new double[n][d];
fitness = new double[n]; // fitness container
best =new double[d];
temp = new double[d]; //temporary holder for a row in array Sol
for(int i=0;i<n;i++){
// for minimal coding : added initialize Q[]array with '0' as element
Q[i] = 0;
for(int x=0;x<d;x++){
// for minimal coding : added initialize v[][] array with '0' as element
v[i][x] = 0;
//find random double values from LB to UB
Sol[i][x]= (rand.nextDouble()*(max - min)) + min;
temp[x] = Sol[i][x];
//System.out.println("sol["+i+"]["+x+"] = "+Sol[i][x]); //test line
//System.out.println(rand.nextDouble()); //test line
}
fitness[i] = function(temp);
//initialize best and the fmin
if(i==0 || fmin > fitness[i]){
fmin = fitness[i];
for(int x=0;x<d;x++){
best[x] = Sol[i][x];
}
}
System.out.println("fitness["+i+"]"+fitness[i]); //test
}
System.out.println("fmin = "+fmin); //test
// special note to these variables (below)
// change if required for maximum effectivity
Qmin = 0;
Qmax = 2;
N_iter = 1; //number of function evaluation
// bat proper
for(int loop=0;loop<N_iter;loop++){
// loop over all bats/solutions
for(int i=0;i<n;i++){
Q[i] = Qmin+((Qmin-Qmax)*rand.nextDouble());
// loop for velocity
for(int vel=0;vel<d;vel++){
v[i][vel] = v[i][vel]+((Sol[i][vel]-best[vel])*Q[i]);
}
//new solutions
for(int x=0;x<d;x++){
S[i][x] = Sol[i][x] + v[i][x];
}
/**
* RESERVED SPOT for the QUESTIONABLE AREA ON THE
* MATLAB CODE (i think it is not needed for the java equivalent)
*/
// pulse rate
if(rand.nextDouble()>r){
for(int x=0;x<d;x++){
S[i][x] = best[x]+(0.001*rand.nextGaussian());
}
}
//putting current row of Sol to a temp array
for(int x=0;x<d;x++){
temp[x] = S[i][x];
}
fnew = function(temp);
// update if solution is improved, and not too loud
if((fnew<=fitness[i]) && (rand.nextDouble()<A)){
for(int x=0;x<d;x++){
Sol[i][x] = S[i][x];
fitness[i] = fnew;
}
}
//update current best solution
if(fnew<=fmin){
for(int x=0;x<d;x++){
best[x] = S[i][x];
fmin = fnew;
}
}
}
}
System.out.println(" ");
System.out.println("new fitness");
for(int i=0;i<n;i++){
System.out.println("fitness["+i+"]"+fitness[i]);
}
System.out.println("Fmin = "+fmin);
}
//possible that this function is not needed in java
public void set_bounds(int x, double L, double U){
//double temp_Lb[x];
//double temp_Ub[x];
for(int i=0; i<x; i++){
Lb[0][i] = L;
Ub[0][i] = U;
}
}
public double function(double value[]){
// sphere function where fmin is at 0
double result = 0;
for(int i=0;i<d;i++){
result += (value[i]*value[i]);
}
return result;
}
}