Related
The goal of this BFS is to find a solution to a 3x2 puzzle game(0 is blank space and you can only move pieces to that space)
start:
1 4 2
5 3 0
Goal:
0 1 2
3 4 5
The problem is that my queue becomes empty before a solution is found, how is that possible? One of the paths in the search tree must return a solution here. Please let me know if I can clarify anything.
Node Class (represents a state of the game):
mport java.lang.reflect.Array;
import java.util.*;
public class Node {
public int[] state = new int[6];
private Node parent;
public Node(int[] initialState, Node parent){
this.parent = parent;
this.state = initialState;
}
public boolean isGoal(){
int[] goal = {0,1,2,3,4,5};
return Arrays.equals(state, goal);
}
public ArrayList<Node> getChildren(){
ArrayList<Node> children = new ArrayList<>();
Integer[] newInt = new Integer[getState().length];
for (int i = 0; i < getState().length; i++) {
newInt[i] = Integer.valueOf(getState()[i]);
}
int position = Arrays.asList(newInt).indexOf(0);
switch(position){
case 0:
children.add(right());
children.add(down());
break;
case 1:
children.add(down());
children.add(left());
children.add(right());
break;
case 2:
children.add(down());
children.add(left());
break;
case 3:
children.add(up());
children.add(right());
break;
case 4:
children.add(up());
children.add(left());
children.add(right());
break;
case 5:
children.add(up());
children.add(left());
break;
}
return children;
}
public int[] getState(){
return this.state;
}
public int getBlankIndex() {
for (int i = 0; i < state.length; i++)
if (state[i] == 0) return i;
return -1;
}
public Node up(){
int[] newer = state.clone();
int blankIndex = getBlankIndex();
int temp = newer[blankIndex - 3];
newer[blankIndex] = temp;
newer[blankIndex - 3] = 0;
return new Node(newer, this);
}
public Node down(){
int[] newer = state.clone();
int blankIndex = getBlankIndex();
int temp = newer[blankIndex + 3];
newer[blankIndex] = temp;
newer[blankIndex + 3] = 0;
return new Node(newer, this);
}
public Node left(){
int[] newer = state.clone();
int blankIndex = getBlankIndex();
int temp = newer[blankIndex - 1];
newer[blankIndex] = temp;
newer[blankIndex - 1] = 0;
return new Node(newer, this);
}
public Node right(){
int[] newer = state.clone();
int blankIndex = getBlankIndex();
int temp = newer[blankIndex + 1];
newer[blankIndex] = temp;
newer[blankIndex + 1] = 0;
return new Node(newer, this);
}
public void print(){
System.out.println("---------");
System.out.println(Arrays.toString(Arrays.copyOfRange(getState(), 0, 3)));
System.out.println(Arrays.toString(Arrays.copyOfRange(getState(), 3, 6)));
System.out.println("---------");
}
public void printTrace(){
Stack<Node> stack = new Stack<>();
Node current = this;
while (current.parent != null){
stack.push(current);
current = current.parent;
}
while (!stack.isEmpty()){
stack.pop().print();
}
}
#Override
public boolean equals(Object object){
if (object instanceof Node) {
Node node2 = (Node) object;
return (Arrays.equals(node2.getState(), this.getState()));
}
return false;
}
#Override
public int hashCode() {
return this.hashCode();
}
}
Driver Class:
import java.util.*;
public class Driver {
public static void main(String[] args){
Node test = new Node(new int[]{1, 4, 2, 5, 3, 0}, null);
BFS(test);
System.out.println("done");
}
public static void BFS(Node initial){
Queue<Node> queue = new LinkedList<>();
ArrayList<Node> explored = new ArrayList<>();
queue.add(initial);
Node current = initial;
while (!queue.isEmpty() && !current.isGoal()){
current = queue.remove();
for (Node child: current.getChildren()){
if (!explored.contains(child)) {
queue.add(child);
explored.add(current);
}
}
}
System.out.println("DONEDONEDONE");
current.printTrace();
}
}
This is a very surprising problem!
I haven't looked at the code yet, it seemed more or less ok.
I'll instead address the question:
The problem is that my queue becomes empty before a solution is found, how is that possible?
The code is not the problem.
The problem is that your puzzle is unsolvable.
The funny thing is that
parity(permutation) * (-1)^{manhattanMetric(positionOfZeroTile)}
is an invariant that is preserved during the entire game.
Let me briefly explain what it means.
(It's essentially the same argument as here: https://en.wikipedia.org/wiki/15_puzzle )
The parity of a permutation is (-1)^{numberOfTranspositions}.
The number of transpositions is essentially just the number of swaps that
the bubble-sort would need to sort the sequence.
The manhattan metric of the zero-tile position is x-coordinate of the zero-tile
added with the y-coordinate of the zero-tile.
Each time you swap a tile with zero, the parity of the permutation changes
the sign.
At the same time, the manhattan metric between the upper left corner and
the position of the zero-tile changes by +1 or -1. In both cases,
(-1)^{manhattanDist} also changes the sign.
Thus, the product of the parity and (-1)^{manhattanDist} is constant.
If you now look at the solved game
0 1 2
3 4 5
then the number of transpositions is 0, parity is 1, the manhattan distance is 0.
Thus, the invariant is (+1).
However, if you look at this:
1 4 2
5 3 0
then you can calculate that the number of transpositions is even (bubble-sort it!),
parity is (+1), and the manhattan distance is 2 + 1 = 3, and thus uneven.
Thus, the invariant is (+1) * (-1)^3 = (-1).
But (-1) is not (+1). Therefore, your game is unsolvable in principle, no matter
how good your BFS is.
Another (more intuitive but less rigorous) way to see quickly that your puzzle is "broken"
is to swap two non-zero tiles in the beginning.
1 4 2
3 5
This is almost immediately solvable:
1 4 2 1 2 1 2
3 5 3 4 5 3 4 5
So, if you don't want to waste any time searching for bugs that aren't there,
don't skip the Group Theory lectures next time ;)
An error I can find is that you only add current to the explored list if it doesn‘t contain child. Additionally, you do this within the loop through the children, so it might also be that you add it multiple times. (Though, this shouldn‘t affect your result)
Problem 31
In England the currency is made up of pound, £, and pence, p, and
there are eight coins in general circulation: 1p, 2p, 5p, 10p, 20p,
50p, £1 (100p) and £2 (200p). It is possible to make £2 in the
following way: 1×£1 + 1×50p + 2×20p + 1×5p + 1×2p + 3×1p How many
different ways can £2 be made using any number of coins?
static int[] nums = {200,100,50,20,10,5,2,1};
static int size = nums.length;
static HashMap<Integer,Integer> pivots = new HashMap<>();
public static int checkSum(HashMap<Integer,Integer> pivots){
int target = 200;
int sum = 0;
for(Integer key: pivots.keySet()){
int pivot = pivots.get(key);
sum += nums[pivot];
if(sum > target) return 1;
}
if(sum < target) return -1;
return 0;
}
public static void shift(HashMap<Integer,Integer> pivots, int pivot_node){
if(pivots.size() + nums[pivots.get(1)] == 201 && pivots.get(1) != 0){
int p_1_value = pivots.get(1); //this part checks whether the current node(which is the first node)
//has reached children of all 1.
//Which means it's time to shift the root node.
pivots.clear();
pivots.put(1 , p_1_value);
shift(pivots, 1);
return;
}
if(pivots.get(pivot_node) != size - 1) {
pivots.put(pivot_node, pivots.get(pivot_node) + 1);
}
else{
shift(pivots , pivot_node - 1);
}
}
public static void branch(HashMap<Integer,Integer> pivots){
pivots.put(pivots.size() + 1, pivots.get(pivots.size()));
}
public static int search(){
int bool = checkSum(pivots);
int n = 0;
int count = 0;
while(n < 25) {
count++;
if (bool == 0) {
n++; // if the sum is equal to 200, we shift the last
//pivot to the next lower number.
shift(pivots, pivots.size());
}else if (bool == -1) {
branch(pivots); //if the sum is less than 200, we make a new pivot with value of the last pivot.
}else if (bool == 1) {
shift(pivots, pivots.size()); //if the sum is greater than 200,
//we shift to the last pivot to the next lower number.
}
bool = checkSum(pivots);
}
return n;
}
public static void main(String[] args){
pivots.put(1,0);
int n = search();
System.out.print("\n\n------------\n\n"+ "n: " + n);
}
This is an algorithm that searches for combinations of a set that add up to a target. It's kind of like a depth first tree search without using a tree. Each pivot represents node on the "tree". The shift() method changes the value of the node to the next lower value. The branch() method creates a new node with the same value of the last node. The checkSum() method checks whether the sum of the pivots are <,= or > the target, 200.
The correct answer for the number of ways is supposed to be around 73000. But my algorithm only returns about 300 ways.
I have no idea why this happens because my algorithm should reach every single possible combination that equals 200.
This is a visualization of how my algorithm works:
Your search algorithm doesn't find all possible combinations of coins that make up £2 because you are only shifting the "last pivot" to the next lower number, when you should be considering the items before that last one too.
Your algorithm will find this combination:
100, 50, 20, 20, 5, 2, 2, 1
but not this:
100, 20, 20, 20, 10, 5, 2, 2, 1
The second combination does not have the value 50 in it, but your algorithm breaks down the coin values backwards to forwards only -i.e. it will never break down 50 until all the following "pivots" are 1. You can easily see that if you print your HashMap<Integer,Integer> pivots every time the counter n is incremented.
You could try to fix your code by amending it to shift() using not only the last pivot but all the distinct previous pivots too. However, doing so you will create a lot of duplicates, so you'll need to keep a list of the distinct found combinations.
Another way to solve problem 31 is by using Dynamic Programming. Dynamic programming is best when it comes to problems that can be broken down in smaller bits. For example the solution of the same problem but where
target = 2 can be used to solve the problem where target = 5, which can be used to solve the problem where target = 10 and so on.
Good luck!
I'm trying to implement a code that returns the sum of all prime numbers under 2 million. I have an isPrime(int x) method that returns true if the the number is prime. Here it is:
public static boolean isPrime(int x) {
for (int i = 2; i < x; i++) {
if (x % i == 0) {
return false;
}
}
return true;
}
And the other method, which I'm trying to implement recursively, only works until a certain number, over that number and I get a stack overflow error. The highest I got the code to work was for 10,000.
Here it is:
public static int sumOfPrimes(int a) {
if (a < 2000000) { //this is the limit
if (isPrime(a)) {
return a + sumOfPrimes(a + 1);
} else {
return sumOfPrimes(a + 1);
}
}
return -1;
}
So why do I get a stack overflow error when the number gets bigger and how can I deal with this?
Also, how do you normally deal with writing code for such big numbers? IE: normal number operations like this but for larger numbers? I wrote this recursively because I thought it would be more efficient but it still wont work.
Your isPrime function is inefficient, it doesn't have to go to x, it's enough to go to the square root of x.
But that is not the reason why your solution doesn't work. You cannot have a recursion depth of 1 million.
I would solve this problem iteratively, using the sieve of eratosthenes and for loop over the resulting boolean array.
In general if you would still like to use recursion, you can use tail recursion.
In recursion each function call will push some data to the stack, which is limited, thus generating a stackoverflow error. In tail recursion you won't be pushing anything to the stack, thus not throwing the exception.
Basically all you need is sending the data of the previous computation as parameter instead of having it on the stack.
So:
function(int x) {
// end condition
return function(x - 1) + x;
}
with tail recursion would be
function (int max, int curr, int prev, int sum) {
if (curr > max)
return sum;
return function (max, curr + 1, curr, sum + curr)
}
Keep in mind this is just pseudo code not real java code, but is close enough to the java code.
For more info check
What is tail recursion?
Use Sieve of Eratosthenes:-
Following is the algorithm to find all the prime numbers less than or equal to a given integer n by Eratosthenes’ method:
1) Create a list of consecutive integers from 2 to n: (2, 3, 4, …, n).
2) Initially, let p equal 2, the first prime number.
3) Starting from p, count up in increments of p and mark each of these numbers greater than p itself in the list. These numbers will be 2p, 3p, 4p, etc.; note that some of them may have already been marked.
4) Find the first number greater than p in the list that is not marked. If there was no such number, stop. Otherwise, let p now equal this number (which is the next prime), and repeat from step 3.
public static void main(String[] args) {
int n = 30;
System.out.printf("Following are the prime numbers below %d\n", n);
SieveOfEratosthenes(n);
}
static void markMultiples(boolean arr[], int a, int n)
{
int i = 2, num;
while ( (num = i*a) <= n )
{
arr[ num-1 ] = true; // minus 1 because index starts from 0.
++i;
}
}
// A function to print all prime numbers smaller than n
static void SieveOfEratosthenes(int n)
{
// There are no prime numbers smaller than 2
if (n >= 2)
{
// Create an array of size n and initialize all elements as 0
boolean[] arr=new boolean[n];
for(int index=0;index<arr.length-1;index++){
arr[index]=false;
}
for (int i=1; i<n; ++i)
{
if ( arr[i] == false )
{
//(i+1) is prime, print it and mark its multiples
System.out.printf("%d ", i+1);
markMultiples(arr, i+1, n);
}
}
}
}
Output:-
Following are the prime numbers below 30
2 3 5 7 11 13 17 19 23 29
In an attempt to write a brute force maze solving C program, I've written this java program first to test an idea. I'm very new to C and intend to convert it after getting this right in java. As a result, I'm trying stick away from arraylists, fancy libraries, and such to make it easier to convert to C. The program needs to generate a single width path of shortest steps to solve a maze. I think my problem may be in fragmenting a path-storing array passed through each recursion. Thanks for looking at this. -Joe
maze:
1 3 3 3 3
3 3 3 3 3
3 0 0 0 3
3 0 3 3 3
0 3 3 3 2
Same maze solved by this program:
4 4 4 4 4
4 4 4 4 4
4 0 0 0 4
3 0 3 3 4
0 3 3 3 2
number notation are explained in code
public class javamaze {
static storage[] best_path;
static int best_count;
static storage[] path;
//the maze - 1 = start; 2 = finish; 3 = open path
static int maze[][] = {{1, 3, 3, 3, 3},
{3, 3, 3, 3, 3},
{0, 0, 0, 0, 3},
{0, 0, 3, 3, 3},
{3, 3, 3, 3, 2}};
public static void main(String[] args) {
int count1;
int count2;
//declares variables used in the solve method
best_count = 0;
storage[] path = new storage[10000];
best_path = new storage[10000];
int path_count = 0;
System.out.println("Here is the maze:");
for(count1 = 0; count1 < 5; count1++) {
for(count2 = 0; count2 < 5; count2++) {
System.out.print(maze[count1][count2] + " ");
}
System.out.println("");
}
//solves the maze
solve(findStart()/5, findStart()%5, path, path_count);
//assigns an int 4 path to the maze to visually represent the shortest path
for(int count = 0; count <= best_path.length - 1; count++)
if (best_path[count] != null)
maze[best_path[count].getx()][best_path[count].gety()] = 4;
System.out.print("Here is the solved maze\n");
//prints the solved maze
for(count1 = 0; count1 < 5; count1++) {
for(count2 = 0; count2 < 5; count2++){
System.out.print(maze[count1][count2] + " ");
}
System.out.print("\n");
}
}
//finds maze start marked by int 1 - this works perfectly and isn't related to the problem
public static int findStart() {
int count1, count2;
for(count1 = 0; count1 < 5; count1++) {
for(count2 = 0; count2 < 5; count2++) {
if (maze[count1][count2] == 1)
return (count1 * 5 + count2);
}
}
return -1;
}
//saves path coordinate values into a new array
public static void save_storage(storage[] old_storage) {
int count;
for(count = 0; count < old_storage.length; count++) {
best_path[count] = old_storage[count];
}
}
//solves the maze
public static Boolean solve(int x, int y, storage[] path, int path_count) {
//checks to see if grid squares are valid (3 = open path; 0 = wall
if (x < 0 || x > 4) { //array grid is a 5 by 5
//System.out.println("found row end returning false");
return false;
}
if (y < 0 || y > 4) {
//System.out.println("Found col end returning false");
return false;
}
//when finding finish - records the number of moves in static int best_count
if (maze[x][y] == 2) {
if (best_count == 0 || best_count > path_count) {
System.out.println("Found end with this many moves: " + path_count);
best_count = path_count;
save_storage(path); //copies path counting array into a new static array
}
}
//returns false if it hits a wall
if (maze[x][y] == 0)
return false;
//checks with previously crossed paths to prevent an unnecessary repeat in steps
for(storage i: path)
if (i != null)
if (i.getx() == x && i.gety() == y)
return false;
//saves current recursive x, y (row, col) coordinates into a storage object which is then added to an array.
//this array is supposed to fragment per each recursion which doesn't seem to - this may be the issue
storage storespoints = new storage(x, y);
path[path_count] = storespoints;
//recurses up, down, right, left
if (solve((x-1), y, path, path_count++) == true || solve((x+1), y, path, path_count++) == true ||
solve(x, (y+1), path, path_count++) == true || solve(x, (y-1), path, path_count++) == true) {
return true;
}
return false;
}
}
//stores (x, y) aka row, col coordinate points
class storage {
private int x;
private int y;
public storage(int x, int y) {
this.x = x;
this.y = y;
}
public int getx() {
return x;
}
public int gety() {
return y;
}
public String toString() {
return ("storage coordinate: " + x + ", " + y + "-------");
}
}
This wasn't originally intended to be an answer but it sort of evolved into one. Honestly, I think starting in Java and moving to C is a bad idea because the two languages are really nothing alike, and you won't be doing yourself any favors because you will run into serious issues porting it if you rely on any features java has that C doesn't (i.e. most of them)
That said, I'll sketch out some algorithmic C stuff.
Support Structures
typedef
struct Node
{
int x, y;
// x and y are array indices
}
Node;
typedef
struct Path
{
int maxlen, head;
Node * path;
// maxlen is size of path, head is the index of the current node
// path is the pointer to the node array
}
Path;
int node_compare(Node * n1, Node * n2); // returns true if nodes are equal, else false
void path_setup(Path * p, Node * n); // allocates Path.path and sets first node
void path_embiggen(Path * p); // use realloc to make path bigger in case it fills up
int path_toosmall(Path * p); // returns true if the path needs to be reallocated to add more nodes
Node * path_head(Path * p); // returns the head node of the path
void path_push(Path * p, Node * n); // pushes a new head node onto the path
void path_pop(Path * p); // pops a node from path
You might to change your maze format into an adjacency list sort of thing. You could store each node as a mask detailing which nodes you can travel to from the node.
Maze Format
const int // these constants indicate which directions of travel are possible from a node
N = (1 << 0), // travel NORTH from node is possible
S = (1 << 1), // travel SOUTH from node is possible
E = (1 << 2), // travel EAST from node is possible
W = (1 << 3), // travel WEST from node is possible
NUM_DIRECTIONS = 4; // number of directions (might not be 4. no reason it has to be)
const int
START = (1 << 4), // starting node
FINISH = (1 << 5); // finishing node
const int
MAZE_X = 4, // maze dimensions
MAZE_Y = 4;
int maze[MAZE_X][MAZE_Y] =
{
{E, S|E|W, S|E|W, S|W },
{S|FINISH, N|S, N|START, N|S },
{N|S, N|E, S|E|W, N|S|W },
{N|E, E|W, N|W, N }
};
Node start = {1, 2}; // position of start node
Node finish = {1, 0}; // position of end node
My maze is different from yours: the two formats don't quite map to each other 1:1. For example, your format allows finer movement, but mine allows one-way paths.
Note that your format explicitly positions walls. With my format, walls are conceptually located anywhere where a path is not possible. The maze I created has 3 horizontal walls and 5 vertical ones (and is also enclosed, i.e. there is a continuous wall surrounding the whole maze)
For your brute force traversal, I would use a depth first search. You can map flags to directions in a number of ways, like maybe the following. Since you are looping over each one anyway, access times are irrelevant so an array and not some sort of faster associative container will be sufficient.
Data Format to Offset Mappings
// map directions to array offsets
// format is [flag], [x offset], [y offset]
int mappings[][] =
{
{N, -1, 0},
{S, 1, 0},
{E, 0, 1},
{W, 0, -1}
}
Finally, your search. You could implement it iteratively or recursively. My example uses recursion.
Search Algorithm Pseudocode
int search_for_path(int ** maze, char ** visited, Path * path)
{
Node * head = path_head(path);
Node temp;
int i;
if (node_compare(head, &finish)) return 1; // found finish
if (visited[head->x][head->y]) return 0; // don't traverse again, that's pointless
visited[head->x][head->y] = 1;
if (path_toosmall(path)) path_embiggen(path);
for (i = 0; i < NUM_DIRECTIONS; ++i)
{
if (maze[head->x][head->y] & mappings[i][0]) // path in this direction
{
temp = {head->x + mappings[i][1], head->y + mappings[i][2]};
path_push(path, &temp);
if (search_for_path(maze, visited, path)) return 1; // something found end
path_pop(path);
}
}
return 0; // unable to find path from any unvisited neighbor
}
To call this function, you should set everything up like this:
Calling The Solver
// we already have the maze
// int maze[MAZE_X][MAZE_Y] = {...};
// make a visited list, set to all 0 (unvisited)
int visited[MAZE_X][MAZE_Y] =
{
{0,0,0,0},
{0,0,0,0},
{0,0,0,0},
{0,0,0,0}
};
// setup the path
Path p;
path_setup(&p, &start);
if (search_for_path(maze, visited, &path))
{
// succeeded, path contains the list of nodes containing coordinates from start to end
}
else
{
// maze was impossible
}
It's worth noting that because I wrote this all in the edit box, I haven't tested any of it. It probably won't work on the first try and might take a little fiddling. For example, unless start and finish are declared globally, there will be a few issues. It would be better to pass the target node to the search function instead of using a global variable.
I have to generate all variations without repetitions made of digits 0 - 9.
Length of them could be from 1 to 10. I really don't know how to solve it, especially how to avoid repetitions.
Example:
length of variations: 4
random variations: 9856, 8753, 1243, 1234 etc. (but not 9985 - contains repetition)
Can you please help me? Or can you give me the code?
The keyword to look for is permutation. There is an abundance of source code freely available that performs them.
As for keeping it repetition free I suggest a simple recursive approach: for each digit you have a choice of taking it into your variation or not, so your recursion counts through the digits and forks into two recursive calls, one in which the digit is included, one in which it is excluded. Then, after you reached the last digit each recursion essentially gives you a (unique, sorted) list of repetition-free digits. You can then create all possible permutations of this list and combine all of those permutations to achieve your final result.
(Same as duffymo said: I won't supply code for that)
Advanced note: the recursion is based on 0/1 (exclusion, inclusion) which can directly be translated to bits, hence, integer numbers. Therefore, in order to get all possible digit combinations without actually performing the recursion itself you could simply use all 10-bit integer numbers and iterate through them. Then interpret the numbers such that a set bit corresponds to including the digit in the list that needs to be permuted.
Here is my Java code. Feel free to ask if you don't understand. The main point here is:
sort again character array. for example: a1 a2 a3 b1 b2 b3 .... (a1 = a2 = a3)
generate permutation and always keep condition: index of a1 < index of a2 < index of a3 ...
import java.util.Arrays;
public class PermutationDup {
public void permutation(String s) {
char[] original = s.toCharArray();
Arrays.sort(original);
char[] clone = new char[s.length()];
boolean[] mark = new boolean[s.length()];
Arrays.fill(mark, false);
permute(original, clone, mark, 0, s.length());
}
private void permute(char[] original, char[] clone, boolean[] mark, int length, int n) {
if (length == n) {
System.out.println(clone);
return;
}
for (int i = 0; i < n; i++) {
if (mark[i] == true) continue;
// dont use this state. to keep order of duplicate character
if (i > 0 && original[i] == original[i-1] && mark[i-1] == false) continue;
mark[i] = true;
clone[length] = original[i];
permute(original, clone, mark, length+1, n);
mark[i] = false;
}
}
public static void main(String[] args) {
PermutationDup p = new PermutationDup();
p.permutation("abcab");
}
}
I have created the following code for generating permutations where ordering is important and with no repetition. It makes use of generics for permuting any type of object:
import java.util.ArrayList;
import java.util.Collection;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
public class Permutations {
public static <T> Collection<List<T>> generatePermutationsNoRepetition(Set<T> availableNumbers) {
Collection<List<T>> permutations = new HashSet<>();
for (T number : availableNumbers) {
Set<T> numbers = new HashSet<>(availableNumbers);
numbers.remove(number);
if (!numbers.isEmpty()) {
Collection<List<T>> childPermutations = generatePermutationsNoRepetition(numbers);
for (List<T> childPermutation : childPermutations) {
List<T> permutation = new ArrayList<>();
permutation.add(number);
permutation.addAll(childPermutation);
permutations.add(permutation);
}
} else {
List<T> permutation = new ArrayList<>();
permutation.add(number);
permutations.add(permutation);
}
}
return permutations;
}
}
Imagine you had a magical function - given an array of digits, it will return you the correct permutations.
How can you use that function to produce a new list of permutations with just one extra digit?
e.g.,
if i gave you a function called permute_three(char[3] digits), and i tell you that it only works for digits 0, 1, 2, how can you write a function that can permute 0, 1, 2, 3, using the given permute_three function?
...
once you solved that, what do you notice? can you generalize it?
using Dollar it is simple:
#Test
public void generatePermutations() {
// digits is the string "0123456789"
String digits = $('0', '9').join();
// then generate 10 permutations
for (int i : $(10)) {
// shuffle, the cut (0, 4) in order to get a 4-char permutation
System.out.println($(digits).shuffle().slice(4));
}
}
The code for this is similar to the one without duplicates, with the addition of an if-else statement.Check this code
In the above code,Edit the for loop as follows
for (j = i; j <= n; j++)
{
if(a[i]!=a[j] && !is_duplicate(a,i,j))
{
swap((a+i), (a+j));
permute(a, i+1, n);
swap((a+i), (a+j));
}
else if(i!=j) {} // if no duplicate is present , do nothing
else permute(a,i+1,n); // skip the ith character
}
bool is_duplicate(int *a,int i,int j)
{
if a[i] is present between a[j]...a[i]
return 1;
otherwise
return 0;
}
worked for me
Permutation without repetition is based on theorem, that amount of results is factorial of count of elements (in this case numbers). In your case 10! is 10*9*8*7*6*5*4*3*2*1 = 3628800. The proof why it is exactly right is right solution for generation also.
Well so how. On first position i.e. from left you can have 10 numbers, on the second position you can have only 9 numbers, because one number is on the position on the left and we cannot repeat the same number etc. (the proof is done by mathematical induction).
So how to generate first ten results? According my knowledges, he simplest way is to use cyclic shift. It means the order of number shift to the left on one position (or right if you want) and the number which overflow to put on the empty place.
It means for first ten results:
10 9 8 7 6 5 4 3 2 1
9 8 7 6 5 4 3 2 1 10
8 7 6 5 4 3 2 1 10 9
7 6 5 4 3 2 1 10 9 8
6 5 4 3 2 1 10 9 8 7
5 4 3 2 1 10 9 8 7 6
...
The first line is basic sample, so it is the good idea to put it into set before generation. Advantage is, that in the next step you will have to solve the same problem to avoid undesirable duplicities.
In next step recursively rotate only 10-1 numbers 10-1 times etc.
It means for first 9 results in step two:
10 9 8 7 6 5 4 3 2 1
10 8 7 6 5 4 3 2 1 9
10 7 6 5 4 3 2 1 9 8
10 6 5 4 3 2 1 9 8 7
10 5 4 3 2 1 9 8 7 6
...
etc, notice, that first line is present from previous step, so it must not be added to generated set again.
Algorithm recursively doing exactly that, what is explained above. It is possible to generate all the 3628800 combinations for 10!, because number of nesting is the same as number of elements in array (it means in your case for 10 numbers it lingers about 5min. on my computer) and you need have enough memory if you want to keep all combinations in array.
There is solution.
package permutation;
/** Class for generation amount of combinations (factorial)
* !!! this is generate proper permutations without repeating and proper amount (počet) of rows !!!
*
* #author hariprasad
*/
public class TestForPermutationII {
private static final String BUMPER = "*";
private static int counter = 0;
private static int sumsum = 0;
// definitoin of array for generation
//int[] testsimple = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
int[] testsimple = {1, 2, 3, 4, 5};
private int ELEMNUM = testsimple.length;
int[][] shuff;
private String gaps(int len) {
String addGap = "";
for(int i=0; i <len; i++)
addGap += " ";
return addGap;
}
/** Factorial computing */
private int fact(int num) {
if (num > 1) {
return num * fact(num - 1);
} else {
return 1;
}
}
/** Cyclic shift position to the left */
private int[] lShiftPos(int[] arr, int pos) {
int[] work = new int[ELEMNUM];
int offset = -1;
for (int jj = 0; jj < arr.length; jj++) {
if (jj < pos) {
work[jj] = arr[jj];
} else if (jj <= arr.length - 1) {
if (jj == pos) {
offset = arr[pos]; // last element
}
if (jj != (arr.length - 1)) {
work[jj] = arr[jj + 1];
} else {
work[jj] = offset;
}
}
}
return work;
}
private String printBuff(int[] buffer) {
String res = "";
for (int i= 0; i < buffer.length; i++) {
if (i == 0)
res += buffer[i];
else
res += ", " + buffer[i];
}
return res;
};
/** Recursive generator for arbitrary length of array */
private String permutationGenerator(int pos, int level) {
String ret = BUMPER;
int templen = counter;
int[] work = new int[ELEMNUM];
int locsumread = 0;
int locsumnew = 0;
//System.out.println("\nCalled level: " + level);
for (int i = 0; i <= templen; i++) {
work = shuff[i];
sumsum++;
locsumread++;
for (int ii = 0; ii < pos; ii++) {
counter++;
sumsum++;
locsumnew++;
work = lShiftPos(work, level); // deep copy
shuff[counter] = work;
}
}
System.out.println("locsumread, locsumnew: " + locsumread + ", " + locsumnew);
// if level == ELEMNUM-2, it means no another shift
if (level < ELEMNUM-2) {
ret = permutationGenerator(pos-1, level+1);
ret = "Level " + level + " end.";
//System.out.println(ret);
}
return ret;
}
public static void main(String[] argv) {
TestForPermutationII test = new TestForPermutationII();
counter = 0;
int len = test.testsimple.length;
int[] work = new int[len];
test.shuff = new int[test.fact(len)][];
//initial
test.shuff[counter] = test.testsimple;
work = test.testsimple; // shalow copy
test.shuff = new int[test.fact(len)][];
counter = 0;
test.shuff[counter] = test.testsimple;
test.permutationGenerator(len-1, 0);
for (int i = 0; i <= counter; i++) {
System.out.println(test.printBuff(test.shuff[i]));
}
System.out.println("Counter, cycles: " + counter + ", " + sumsum);
}
}
Intensity (number of cycles) of algorithm is sum of incomplete factorials of number of members. So there is overhang when partial set is again read to generate next subset, so intensity is:
n! + n!/2! + n!/3! + ... + n!/(n-2)! + n!(n-1)!
There is one solution which is not from mine, but it is very nice and sophisticated.
package permutations;
import java.util.HashSet;
import java.util.LinkedList;
import java.util.List;
import java.util.Set;
/**
* #author Vladimir Hajek
*
*/
public class PermutationSimple {
private static final int MAX_NUMBER = 3;
Set<String> results = new HashSet<>(0);
/**
*
*/
public PermutationSimple() {
// TODO Auto-generated constructor stub
}
/**
* #param availableNumbers
* #return
*/
public static List<String> generatePermutations(Set<Integer> availableNumbers) {
List<String> permutations = new LinkedList<>();
for (Integer number : availableNumbers) {
Set<Integer> numbers = new HashSet<>(availableNumbers);
numbers.remove(number);
if (!numbers.isEmpty()) {
List<String> childPermutations = generatePermutations(numbers);
for (String childPermutation : childPermutations) {
String permutation = number + childPermutation;
permutations.add(permutation);
}
} else {
permutations.add(number.toString());
}
}
return permutations;
}
/**
* #param args
*/
public static void main(String[] args) {
Set<Integer> availableNumbers = new HashSet<>(0);
for (int i = 1; i <= MAX_NUMBER; i++) {
availableNumbers.add(i);
}
List<String> permutations = generatePermutations(availableNumbers);
for (String permutation : permutations) {
System.out.println(permutation);
}
}
}
I think, this is the excellent solution.
Brief helpful permutation indexing Knowledge
Create a method that generates the correct permutation, given an index value between {0 and N! -1} for "zero indexed" or {1 and N!} for "one indexed".
Create a second method containing a "for loop" where the lower bound is 1 and the upper bound is N!. eg.. "for (i; i <= N!; i++)" for every instance of the loop call the first method, passing i as the argument.
def find(alphabet, alpha_current, str, str_current, max_length, acc):
if (str_current == max_length):
acc.append(''.join(str))
return
for i in range(alpha_current, len(alphabet)):
str[str_current] = alphabet[i]
alphabet[i], alphabet[alpha_current] = alphabet[alpha_current], alphabet[i]
find(alphabet, alpha_current+1, str, str_current+1, max_length, acc)
alphabet[i], alphabet[alpha_current] = alphabet[alpha_current], alphabet[i]
return
max_length = 4
str = [' ' for i in range(max_length)]
acc = list()
find(list('absdef'), 0, str, 0, max_length, acc)
for i in range(len(acc)):
print(acc[i])
print(len(acc))