Rotate a matrix by one element: is there an easier/simpler implementation? - arrays

I was written this code to rotate the matrix elements one by one.
I wanted to do this on my own but I am stuck in this position someone please find what is the problem in my code and suggest me there is any easy implementation other than this.
#include<iostream>
using namespace std;
void rotate(int a[][10],int r,int c)
{
int b[10][10];
// Copying the input matrix 2d array to temp array
for (int x = 0; x < r; x++)
{
for (int y = 0; y < c; y++)
{
b[x][y] = a[x][y];
}
}
//Rotation process
int i = 0;
int j = 0;
int flag = 0;
while (flag == 0)
{
if (i == 0 && j < c-1)
{
b[i][j+1] = a[i][j];
j++;
}
else if (j == c-1 && i < r-1)
{
b[i+1][j] = a[i][j];
i++;
}
else if (i == r-1 && j <= c-1 && j > 0)
{
b[i][j-1]=a[i][j];
j--;
}
else if (j == 0 && i <= r-1)
{
if (i==0 && j==0)
{
//to break the loop
flag = 1;
}
b[i-1][j] = a[i][j];
i--;
}
}
for (int k = 0; k < r; k++)
{
for (int l = 0; l < c; l++)
{
cout<<"\t"<<b[k][l];
}
cout<<endl;
}
}
int main()
{
int a[10][10],row,col;
cout<<"Enter no of rows : ";
cin>>row;
cout<<"Enter no of columns : ";
cin>>col;
// Getting array elements
cout<<"Enter "<<row<<"X"<<col<<" matrix elements : ";
for (int i = 0; i < row; i++)
{
for (int j = 0; j < col; j++)
{
cin>>a[i][j];
}
}
rotate(a,row,col);
cout<<endl;
system("pause");
return 0;
}
This code is not working. Someone help me to find what wrong with this code or suggest me another way.
Thank you.

If I were solving this, I might use 4 independent loops and a single variable to hold the value to carry forward (can be read from the original or matrix copy). While perhaps more repetitive than some approaches, it also removes needing to track 'which direction' state or delta movement variables.
In pseudo-code, it might look like this:
carry = m[0][0]
x, y = 1, 0 # start at (1,0) so we end on (0,0)
# go right from (1,0) to (cols-1,0)
while x < cols:
temp = m[x][y] # hold value of this cell
m[x][y] = carry # replace it with the carried-over value
carry = temp # and forward the previous value as the next carry
x += 1 # update position
# reset back to valid index (avoid additional check in loop)
x -= 1
# do same for other directions around
# the movement is thus:
# (1,0) -> (cols-1,0) NW -> NE
# (cols-1,0) -> (cols-1,rows-1) NE -> SE
# (cols-1,rows-1) -> (0,rows-1) SE -> SW
# (0,rows-1) -> (0,0) SW -> NW
A 1xN or Nx1 matrix might need additional consideration depending on expectations.
Another approach is to use delta variables to move. Think of a little turtle that walks straight and turns right when walking into a wall. The terminal condition is once again set as (0,0) which can be checked at the end of the logic - in this case when the turtle attempts to walk North into a wall, we know it was from (0,0) and the path is completed.
This approach feels less repetitive while maintaining simple state transitions.
carry = m[0][0]
x, y = 1, 0 # start at (1,0)
dx, dy = 1, 0 # and facing East
while true:
# could also use prev_x and prev_y instead of a carry
temp = m[x][y]
m[x][y] = carry
carry = temp
# move / walk
x += dx
y += dy
# turn right when running into a wall
# at most one bound can be violated at a time
if x >= cols:
dx, dy = 0, 1 # face South (was facing East)
x = cols - 1
else if y >= rows:
dx, dy = -1, 0 # face West (was facing South)
y = rows - 1
else if x < 0:
dx, dy = 0, -1 # face North (was facing West)
x = 0
else if y < 0:
# at (0,0) walking North - finished!
break

Related

cache speed related issue

just wondering if I have a matrix like this:
so for the entry in the red position, I just want to know if the green entry is 1 or 0. If it is 0, I just have the value 0 in the same red position of a new matrix. So
if the current position of the red entry is at Matrix[4,3], then the input to the position Matrix[4,3] will be 1 since the green entry (the top-left entry of red) is 1. If the green entry is 0, then Matrix[4,3] will be 0.
So I have to do it pretty much for every entry in this matrix (except the entries that don't have the top-left neighbour for example all entries in first column would not have the top-left neighbour so this don't have to be done for those). I am just wondering will it makes a difference in terms of speed (cache access,reading, writing...etc) if I do the following in C (note that C is row-major):
Code 1:
for (i = 0; i < N; i++) {
for (j = 0; j < N; j++) {
if (i > 0 && j > 0) {
row = j - 1;
col = i - 1; // oldMatrix here is the matrix in the attached image here
*** newMatrix[j][i] += oldMatrix[row][col]; // new Matrix is the matrix to put the //left-top corner value
}
}
}
Code 2:
for (i = 0; i < N; i++) {
for (j = 0; j < N; j++) {
if (i > 0 && j > 0) {
row = j - 1;
col = i - 1; // oldMatrix here is the matrix in the attached image here
if(oldMatrix[row][col] == 1) {
newMatrix[j][i] = 1;
} else {newMatrix[j][i] = 0};
}
}
}
is it better to have this:
*** newMatrix[j][i] += oldMatrix[row][col]
or have this instead:
if(oldMatrix[row][col] == 1) {
newMatrix[j][i] = 1;
} else {newMatrix[j][i] = 0};
So the first one (the line with ***) will first have to read the value of oldMatrix[row][col] and then write to newMatrix[j][i] no matters what.
But the second code will read oldMatrix[row][col] during the "if" check. Then we just assign (assign means "write" 1 or 0 to the newMatrix[j][i] without having to copy oldMatrix[row][col] to the newMatrix[j][i]).
So which one will be better in terms of speed if we talking about cache performance (C is row-major) and why the option would be faster or better?
thank you

Longest K Sequential Increasing Subsequences

Why I created a duplicate thread
I created this thread after reading Longest increasing subsequence with K exceptions allowed. I realised that the person who was asking the question hadn't really understood the problem, because he was referring to a link which solves the "Longest Increasing sub-array with one change allowed" problem. So the answers he got were actually irrelevant to LIS problem.
Description of the problem
Suppose that an array A is given with length N.
Find the longest increasing sub-sequence with K exceptions allowed.
Example
1)
N=9 , K=1
A=[3,9,4,5,8,6,1,3,7]
Answer: 7
Explanation:
Longest increasing subsequence is : 3,4,5,8(or 6),1(exception),3,7 -> total=7
N=11 , K=2
A=[5,6,4,7,3,9,2,5,1,8,7]
answer: 8
What I have done so far...
If K=1 then only one exception is allowed. If the known algorithm for computing the Longest Increasing Subsequence in O(NlogN) is used (click here to see this algorithm), then we can compute the LIS starting from A[0] to A[N-1] for each element of array A. We save the results in a new array L with size N. Looking into example n.1 the L array would be:
L=[1,2,2,3,4,4,4,4,5].
Using the reverse logic, we compute array R, each element of which contains the current Longest Decreasing Sequence from N-1 to 0.
The LIS with one exception is just sol=max(sol,L[i]+R[i+1]),
where sol is initialized as sol=L[N-1].
So we compute LIS from 0 until an index i (exception), then stop and start a new LIS until N-1.
A=[3,9,4,5,8,6,1,3,7]
L=[1,2,2,3,4,4,4,4,5]
R=[5,4,4,3,3,3,3,2,1]
Sol = 7
-> step by step explanation:
init: sol = L[N]= 5
i=0 : sol = max(sol,1+4) = 5
i=1 : sol = max(sol,2+4) = 6
i=2 : sol = max(sol,2+3) = 6
i=3 : sol = max(sol,3+3) = 6
i=4 : sol = max(sol,4+3) = 7
i=4 : sol = max(sol,4+3) = 7
i=4 : sol = max(sol,4+2) = 7
i=5 : sol = max(sol,4+1) = 7
Complexity :
O( NlogN + NlogN + N ) = O(NlogN)
because arrays R, L need NlogN time to compute and we also need Θ(N) in order to find sol.
Code for k=1 problem
#include <stdio.h>
#include <vector>
std::vector<int> ends;
int index_search(int value, int asc) {
int l = -1;
int r = ends.size() - 1;
while (r - l > 1) {
int m = (r + l) / 2;
if (asc && ends[m] >= value)
r = m;
else if (asc && ends[m] < value)
l = m;
else if (!asc && ends[m] <= value)
r = m;
else
l = m;
}
return r;
}
int main(void) {
int n, *S, *A, *B, i, length, idx, max;
scanf("%d",&n);
S = new int[n];
L = new int[n];
R = new int[n];
for (i=0; i<n; i++) {
scanf("%d",&S[i]);
}
ends.push_back(S[0]);
length = 1;
L[0] = length;
for (i=1; i<n; i++) {
if (S[i] < ends[0]) {
ends[0] = S[i];
}
else if (S[i] > ends[length-1]) {
length++;
ends.push_back(S[i]);
}
else {
idx = index_search(S[i],1);
ends[idx] = S[i];
}
L[i] = length;
}
ends.clear();
ends.push_back(S[n-1]);
length = 1;
R[n-1] = length;
for (i=n-2; i>=0; i--) {
if (S[i] > ends[0]) {
ends[0] = S[i];
}
else if (S[i] < ends[length-1]) {
length++;
ends.push_back(S[i]);
}
else {
idx = index_search(S[i],0);
ends[idx] = S[i];
}
R[i] = length;
}
max = A[n-1];
for (i=0; i<n-1; i++) {
max = std::max(max,(L[i]+R[i+1]));
}
printf("%d\n",max);
return 0;
}
Generalization to K exceptions
I have provided an algorithm for K=1. I have no clue how to change the above algorithm to work for K exceptions. I would be glad if someone could help me.
This answer is modified from my answer to a similar question at Computer Science Stackexchange.
The LIS problem with at most k exceptions admits a O(n log² n) algorithm using Lagrangian relaxation. When k is larger than log n this improves asymptotically on the O(nk log n) DP, which we will also briefly explain.
Let DP[a][b] denote the length of the longest increasing subsequence with at most b exceptions (positions where the previous integer is larger than the next one) ending at element b a. This DP is not involved in the algorithm, but defining it makes proving the algorithm easier.
For convenience we will assume that all elements are distinct and that the last element in the array is its maximum. Note that this does not limit us, as we can just add m / 2n to the mth appearance of every number, and append infinity to the array and subtract one from the answer. Let V be the permutation for which 1 <= V[i] <= n is the value of the ith element.
To solve the problem in O(nk log n), we maintain the invariant that DP[a][b] has been calculated for b < j. Loop j from 0 to k, at the jth iteration calculating DP[a][j] for all a. To do this, loop i from 1 to n. We maintain the maximum of DP[x][j-1] over x < i and a prefix maximum data structure that at index i will have DP[x][j] at position V[x] for x < i, and 0 at every other position.
We have DP[i][j] = 1 + max(DP[i'][j], DP[x][j-1]) where we go over i', x < i, V[i'] < V[i]. The prefix maximum of DP[x][j-1] gives us the maximum of terms of the second type, and querying the prefix maximum data structure for prefix [0, V[i]] gives us the maximum of terms of the first type. Then update the prefix maximum and prefix maximum data structure.
Here is a C++ implementation of the algorithm. Note that this implementation does not assume that the last element of the array is its maximum, or that the array contains no duplicates.
#include <iostream>
#include <vector>
#include <algorithm>
using namespace std;
// Fenwick tree for prefix maximum queries
class Fenwick {
private:
vector<int> val;
public:
Fenwick(int n) : val(n+1, 0) {}
// Sets value at position i to maximum of its current value and
void inc(int i, int v) {
for (++i; i < val.size(); i += i & -i) val[i] = max(val[i], v);
}
// Calculates prefix maximum up to index i
int get(int i) {
int res = 0;
for (++i; i > 0; i -= i & -i) res = max(res, val[i]);
return res;
}
};
// Binary searches index of v from sorted vector
int bins(const vector<int>& vec, int v) {
int low = 0;
int high = (int)vec.size() - 1;
while(low != high) {
int mid = (low + high) / 2;
if (vec[mid] < v) low = mid + 1;
else high = mid;
}
return low;
}
// Compresses the range of values to [0, m), and returns m
int compress(vector<int>& vec) {
vector<int> ord = vec;
sort(ord.begin(), ord.end());
ord.erase(unique(ord.begin(), ord.end()), ord.end());
for (int& v : vec) v = bins(ord, v);
return ord.size();
}
// Returns length of longest strictly increasing subsequence with at most k exceptions
int lisExc(int k, vector<int> vec) {
int n = vec.size();
int m = compress(vec);
vector<int> dp(n, 0);
for (int j = 0;; ++j) {
Fenwick fenw(m+1); // longest subsequence with at most j exceptions ending at this value
int max_exc = 0; // longest subsequence with at most j-1 exceptions ending before this
for (int i = 0; i < n; ++i) {
int off = 1 + max(max_exc, fenw.get(vec[i]));
max_exc = max(max_exc, dp[i]);
dp[i] = off;
fenw.inc(vec[i]+1, off);
}
if (j == k) return fenw.get(m);
}
}
int main() {
int n, k;
cin >> n >> k;
vector<int> vec(n);
for (int i = 0; i < n; ++i) cin >> vec[i];
int res = lisExc(k, vec);
cout << res << '\n';
}
Now we will return to the O(n log² n) algorithm. Select some integer 0 <= r <= n. Define DP'[a][r] = max(DP[a][b] - rb), where the maximum is taken over b, MAXB[a][r] as the maximum b such that DP'[a][r] = DP[a][b] - rb, and MINB[a][r] similarly as the minimum such b. We will show that DP[a][k] = DP'[a][r] + rk if and only if MINB[a][r] <= k <= MAXB[a][r]. Further, we will show that for any k exists an r for which this inequality holds.
Note that MINB[a][r] >= MINB[a][r'] and MAXB[a][r] >= MAXB[a][r'] if r < r', hence if we assume the two claimed results, we can do binary search for the r, trying O(log n) values. Hence we achieve complexity O(n log² n) if we can calculate DP', MINB and MAXB in O(n log n) time.
To do this, we will need a segment tree that stores tuples P[i] = (v_i, low_i, high_i), and supports the following operations:
Given a range [a, b], find the maximum value in that range (maximum v_i, a <= i <= b), and the minimum low and maximum high paired with that value in the range.
Set the value of the tuple P[i]
This is easy to implement with complexity O(log n) time per operation assuming some familiarity with segment trees. You can refer to the implementation of the algorithm below for details.
We will now show how to compute DP', MINB and MAXB in O(n log n). Fix r. Build the segment tree initially containing n+1 null values (-INF, INF, -INF). We maintain that P[V[j]] = (DP'[j], MINB[j], MAXB[j]) for j less than the current position i. Set DP'[0] = 0, MINB[0] = 0 and MAXB[0] to 0 if r > 0, otherwise to INF and P[0] = (DP'[0], MINB[0], MAXB[0]).
Loop i from 1 to n. There are two types of subsequences ending at i: those where the previous element is greater than V[i], and those where it is less than V[i]. To account for the second kind, query the segment tree in the range [0, V[i]]. Let the result be (v_1, low_1, high_1). Set off1 = (v_1 + 1, low_1, high_1). For the first kind, query the segment tree in the range [V[i], n]. Let the result be (v_2, low_2, high_2). Set off2 = (v_2 + 1 - r, low_2 + 1, high_2 + 1), where we incur the penalty of r for creating an exception.
Then we combine off1 and off2 into off. If off1.v > off2.v set off = off1, and if off2.v > off1.v set off = off2. Otherwise, set off = (off1.v, min(off1.low, off2.low), max(off1.high, off2.high)). Then set DP'[i] = off.v, MINB[i] = off.low, MAXB[i] = off.high and P[i] = off.
Since we make two segment tree queries at every i, this takes O(n log n) time in total. It is easy to prove by induction that we compute the correct values DP', MINB and MAXB.
So in short, the algorithm is:
Preprocess, modifying values so that they form a permutation, and the last value is the largest value.
Binary search for the correct r, with initial bounds 0 <= r <= n
Initialise the segment tree with null values, set DP'[0], MINB[0] and MAXB[0].
Loop from i = 1 to n, at step i
Querying ranges [0, V[i]] and [V[i], n] of the segment tree,
calculating DP'[i], MINB[i] and MAXB[i] based on those queries, and
setting the value at position V[i] in the segment tree to the tuple (DP'[i], MINB[i], MAXB[i]).
If MINB[n][r] <= k <= MAXB[n][r], return DP'[n][r] + kr - 1.
Otherwise, if MAXB[n][r] < k, the correct r is less than the current r. If MINB[n][r] > k, the correct r is greater than the current r. Update the bounds on r and return to step 1.
Here is a C++ implementation for this algorithm. It also finds the optimal subsequence.
#include <iostream>
#include <vector>
#include <algorithm>
using namespace std;
using ll = long long;
const int INF = 2 * (int)1e9;
pair<ll, pair<int, int>> combine(pair<ll, pair<int, int>> le, pair<ll, pair<int, int>> ri) {
if (le.first < ri.first) swap(le, ri);
if (ri.first == le.first) {
le.second.first = min(le.second.first, ri.second.first);
le.second.second = max(le.second.second, ri.second.second);
}
return le;
}
// Specialised range maximum segment tree
class SegTree {
private:
vector<pair<ll, pair<int, int>>> seg;
int h = 1;
pair<ll, pair<int, int>> recGet(int a, int b, int i, int le, int ri) const {
if (ri <= a || b <= le) return {-INF, {INF, -INF}};
else if (a <= le && ri <= b) return seg[i];
else return combine(recGet(a, b, 2*i, le, (le+ri)/2), recGet(a, b, 2*i+1, (le+ri)/2, ri));
}
public:
SegTree(int n) {
while(h < n) h *= 2;
seg.resize(2*h, {-INF, {INF, -INF}});
}
void set(int i, pair<ll, pair<int, int>> off) {
seg[i+h] = combine(seg[i+h], off);
for (i += h; i > 1; i /= 2) seg[i/2] = combine(seg[i], seg[i^1]);
}
pair<ll, pair<int, int>> get(int a, int b) const {
return recGet(a, b+1, 1, 0, h);
}
};
// Binary searches index of v from sorted vector
int bins(const vector<int>& vec, int v) {
int low = 0;
int high = (int)vec.size() - 1;
while(low != high) {
int mid = (low + high) / 2;
if (vec[mid] < v) low = mid + 1;
else high = mid;
}
return low;
}
// Finds longest strictly increasing subsequence with at most k exceptions in O(n log^2 n)
vector<int> lisExc(int k, vector<int> vec) {
// Compress values
vector<int> ord = vec;
sort(ord.begin(), ord.end());
ord.erase(unique(ord.begin(), ord.end()), ord.end());
for (auto& v : vec) v = bins(ord, v) + 1;
// Binary search lambda
int n = vec.size();
int m = ord.size() + 1;
int lambda_0 = 0;
int lambda_1 = n;
while(true) {
int lambda = (lambda_0 + lambda_1) / 2;
SegTree seg(m);
if (lambda > 0) seg.set(0, {0, {0, 0}});
else seg.set(0, {0, {0, INF}});
// Calculate DP
vector<pair<ll, pair<int, int>>> dp(n);
for (int i = 0; i < n; ++i) {
auto off0 = seg.get(0, vec[i]-1); // previous < this
off0.first += 1;
auto off1 = seg.get(vec[i], m-1); // previous >= this
off1.first += 1 - lambda;
off1.second.first += 1;
off1.second.second += 1;
dp[i] = combine(off0, off1);
seg.set(vec[i], dp[i]);
}
// Is min_b <= k <= max_b?
auto off = seg.get(0, m-1);
if (off.second.second < k) {
lambda_1 = lambda - 1;
} else if (off.second.first > k) {
lambda_0 = lambda + 1;
} else {
// Construct solution
ll r = off.first + 1;
int v = m;
int b = k;
vector<int> res;
for (int i = n-1; i >= 0; --i) {
if (vec[i] < v) {
if (r == dp[i].first + 1 && dp[i].second.first <= b && b <= dp[i].second.second) {
res.push_back(i);
r -= 1;
v = vec[i];
}
} else {
if (r == dp[i].first + 1 - lambda && dp[i].second.first <= b-1 && b-1 <= dp[i].second.second) {
res.push_back(i);
r -= 1 - lambda;
v = vec[i];
--b;
}
}
}
reverse(res.begin(), res.end());
return res;
}
}
}
int main() {
int n, k;
cin >> n >> k;
vector<int> vec(n);
for (int i = 0; i < n; ++i) cin >> vec[i];
vector<int> ans = lisExc(k, vec);
for (auto i : ans) cout << i+1 << ' ';
cout << '\n';
}
We will now prove the two claims. We wish to prove that
DP'[a][r] = DP[a][b] - rb if and only if MINB[a][r] <= b <= MAXB[a][r]
For all a, k there exists an integer r, 0 <= r <= n, such that MINB[a][r] <= k <= MAXB[a][r]
Both of these follow from the concavity of the problem. Concavity means that DP[a][k+2] - DP[a][k+1] <= DP[a][k+1] - DP[a][k] for all a, k. This is intuitive: the more exceptions we are allowed to make, the less allowing one more helps us.
Fix a and r. Set f(b) = DP[a][b] - rb, and d(b) = f(b+1) - f(b). We have d(k+1) <= d(k) from the concavity of the problem. Assume x < y and f(x) = f(y) >= f(i) for all i. Hence d(x) <= 0, thus d(i) <= 0 for i in [x, y). But f(y) = f(x) + d(x) + d(x + 1) + ... + d(y - 1), hence d(i) = 0 for i in [x, y). Hence f(y) = f(x) = f(i) for i in [x, y]. This proves the first claim.
To prove the second, set r = DP[a][k+1] - DP[a][k] and define f, d as previously. Then d(k) = 0, hence d(i) >= 0 for i < k and d(i) <= 0 for i > k, hence f(k) is maximal as desired.
Proving concavity is more difficult. For a proof, see my answer at cs.stackexchange.

maze generation algorithm in c with DFS

recently i read this topic about generating mazes in c . see here https://www.algosome.com/articles/maze-generation-depth-first.html
and i want to write it in c . here is my code and it's not working right .
#include <stdio.h>
#include <time.h>
#include <stdlib.h>
int check[5][5];
int v[5][5];
int border(int x , int y ){
if(x> -1 && x< 6 && y > -1 && y<6)
return 1;
else
return 0 ;
}
int wall[6][6][6][6];
void dfs ( int x , int y){
srand(time(NULL));
int s = 1/*rand() % 4 ;*/ ;
if(s=1 ){
if(border(x ,y-1)&& check[x][y-1]==0){
check[x][y]=1;
wall[x][y][x+1][y]=1;
dfs(x , y-1);
}
else
return ;
}
else if(s=2){
if(border(x+1 ,y)&&check[x+1][y]==0){
check[x][y]=1;
wall[x+1][y][x+1][y+1]=1;
dfs(x+1 , y);
}
else return ;
}
else if(s=3){
if(border(x ,y+1)&&check[x][y+1]==0){
check[x][y]=1;
wall[x][y+1][x+1][y+1]=1;
dfs(x , y+1);
}
else return ;
}
else if(s=0){
if(border(x-1 ,y)&&check[x-1][y]==0){
check[x][y]=1;
wall[x][y][x][y+1]=1;
dfs(x-1 , y);
}
else return ;
}
return ;
}
int main(){
dfs( 4, 4);
for(int i =0 ; i < 6 ; i++)
for (int j =0 ; j < 6 ; j++)
for ( int h =0 ; h <6 ; h++)
for (int k =0 ; k < 6 ; k ++)
printf("%d \n" , wall[i][j][h][k]);
return 0 ;
}
i invert my table to graph , and i want to show me the coordinates of my walls .
what's the problem ?
You have several errors – programming errors and logic errors – in your code:
When you distiguish between the directions the s=1 and so on should be s == 1. You want a comparison, not an assignment. (Your code is legal C, so there is no error.)
You call srand at the beginning of dfs, which you call recursively. This will make your single (commented) rand call always create the same random number. You should seed the pseudo random number generator only once at the beginning of main.
You can store the paths the way you do, but it is wasteful. There are only four possible paths from each cell, so you don't need an array that allows to create a path between (0,0) and (3,4), for example.
Your code would benefit from using constants or enumerated values instead of the hard-coded 5's and 6's. This will allow you to change the dimensions later easily.
But your principal error is in how you implement the algorithm. You pick one of the for directions at random, then test whether that direction leads to a valid unvisited cell. If so, you recurse. If not, you stop. This will create a single unbranched path through the cells. Note that if you start in a corner cell, you have already a 50% chance of stopping the recursion short.
But you want something else: You want a maze with many branches that leads to every cell in the maze. Therefore, when the first recursion returns, you must try to branch to other cells. The algorithm goes like this:
Make a list of all possible exits.
If there are possible exits:
Pick one exit, create a path to that exit and recurse.
Update the list of possible exits.
Note that you cannot re-use the old list of exits, because the recursion may have rendered some possible exits invalid by visiting the destination cells.
Below is code that creates a maze with the described algorithm. I've used two distinct arrays to describe horizontal and vertical paths:
#include <stdlib.h>
#include <stdio.h>
#include <time.h>
enum {
W = 36, // width of maze
H = 25 // height of maze
};
enum {
North,
East,
South,
West,
NDir
};
char visited[H][W];
char horz[H][W - 1]; // horizontal E-W paths in the maze
char vert[H - 1][W]; // veritcal N-S paths in the maze
/*
* Fill dir with directions to unvisited cells, return count
*/
int adjacent(int dir[], int x, int y)
{
int ndir = 0;
if (y > 0 && visited[y - 1][x] == 0) dir[ndir++] = North;
if (x < W - 1 && visited[y][x + 1] == 0) dir[ndir++] = East;
if (y < H - 1 && visited[y + 1][x] == 0) dir[ndir++] = South;
if (x > 0 && visited[y][x - 1] == 0) dir[ndir++] = West;
return ndir;
}
/*
* Traverse cells depth first and create paths as you go
*/
void dfs(int x, int y)
{
int dir[NDir];
int ndir;
visited[y][x] = 1;
ndir = adjacent(dir, x, y);
while (ndir) {
int pick = rand() % ndir;
switch (dir[pick]) {
case North: vert[y - 1][x] = 1; dfs(x, y - 1); break;
case East: horz[y][x] = 1; dfs(x + 1, y); break;
case South: vert[y][x] = 1; dfs(x, y + 1); break;
case West: horz[y][x - 1] = 1; dfs(x - 1, y); break;
}
ndir = adjacent(dir, x, y);
}
}
/*
* Print a map of the maze
*/
void map(void)
{
int i, j;
for (i = 0; i < W; i++) {
putchar('_');
putchar('_');
}
putchar('\n');
for (j = 0; j < H; j++) {
putchar('|');
for (i = 0; i < W; i++) {
putchar(j < H - 1 && vert[j][i] ? ' ' : '_');
putchar(i < W - 1 && horz[j][i] ? '_' : '|');
}
putchar('\n');
}
}
int main()
{
srand(time(NULL));
dfs(0, 0);
map();
return 0;
}
You can test it here. If you replace the while in dsf with a simple if, you get more or less what you implemented. Note that this creates only a single, usually short path.

2D convolution with a with a kernel which is not center originated

I want to do 2D convolution of an image with a Gaussian kernel which is not centre originated given by equation:
h(x-x', y-y') = exp(-((x-x')^2+(y-y'))/2*sigma)
Lets say the centre of kernel is (1,1) instead of (0,0). How should I change my following code for generation of kernel and for the convolution?
int krowhalf=krow/2, kcolhalf=kcol/2;
int sigma=1
// sum is for normalization
float sum = 0.0;
// generate kernel
for (int x = -krowhalf; x <= krowhalf; x++)
{
for(int y = -kcolhalf; y <= kcolhalf; y++)
{
r = sqrtl((x-1)*(x-1) + (y-1)*(y-1));
gKernel[x + krowhalf][y + kcolhalf] = exp(-(r*r)/(2*sigma));
sum += gKernel[x + krowhalf][y + kcolhalf];
}
}
//normalize the Kernel
for(int i = 0; i < krow; ++i)
for(int j = 0; j < kcol; ++j)
gKernel[i][j] /= sum;
float **convolve2D(float** in, float** out, int h, int v, float **kernel, int kCols, int kRows)
{
int kCenterX = kCols / 2;
int kCenterY = kRows / 2;
int i,j,m,mm,n,nn,ii,jj;
for(i=0; i < h; ++i) // rows
{
for(j=0; j < v; ++j) // columns
{
for(m=0; m < kRows; ++m) // kernel rows
{
mm = kRows - 1 - m; // row index of flipped kernel
for(n=0; n < kCols; ++n) // kernel columns
{
nn = kCols - 1 - n; // column index of flipped kernel
//index of input signal, used for checking boundary
ii = i + (m - kCenterY);
jj = j + (n - kCenterX);
// ignore input samples which are out of bound
if( ii >= 0 && ii < h && jj >= 0 && jj < v )
//out[i][j] += in[ii][jj] * (kernel[mm+nn*29]);
out[i][j] += in[ii][jj] * (kernel[mm][nn]);
}
}
}
}
}
Since you're using the convolution operator you have 2 choices:
Using it Spatial Invariant property.
To so so, just calculate the image using regular convolution filter (Better done using either conv2 or imfilter) and then shift the result.
You should mind the boundary condition you'd to employ (See imfilter properties).
Calculate the shifted result specifically.
You can do this by loops as you suggested or more easily create non symmetric kernel and still use imfilter or conv2.
Sample Code (MATLAB)
clear();
mInputImage = imread('3.png');
mInputImage = double(mInputImage) / 255;
mConvolutionKernel = zeros(3, 3);
mConvolutionKernel(2, 2) = 1;
mOutputImage01 = conv2(mConvolutionKernel, mInputImage);
mConvolutionKernelShifted = [mConvolutionKernel, zeros(3, 150)];
mOutputImage02 = conv2(mConvolutionKernelShifted, mInputImage);
figure();
imshow(mOutputImage01);
figure();
imshow(mOutputImage02);
The tricky part is to know to "Crop" the second image in the same axis as the first.
Then you'll have a shifted image.
You can use any Kernel and any function which applies convolution.
Enjoy.

C Language - General algorithm to read a square matrix, based on the square number of it's side?

So we're reading a matrix and saving it in an array sequentially. We read the matrix from a starting [x,y] point which is provided. Here's an example of some code I wrote to get the values of [x-1,y] [x+1,y] [x,y-1] [x,y+1], which is a cross.
for(i = 0, n = -1, m = 0, array_pos = 0; i < 4; i++, n++, array_pos++) {
if(x+n < filter_matrix.src.columns && x+n >= 0 )
if(y+m < filter_matrix.src.lines && y+m >= 0){
for(k = 0; k < numpixels; k++) {
arrayToProcess[array_pos].rgb[h] = filter_matrix.src.points[x+n][y+m].rgb[h];
}
}
m = n;
m++;
}
(The if's are meant to avoid reading null positions, since it's an image we're reading the origin pixel can be located in a corner. Not relevant to the issue here.)
Now is there a similar generic algorithm which can read ALL the elements around as a square (not just a cross) based on a single parameter, which is the size of the square's side squared?
If it helps, the only values we're dealing with are 9, 25 and 49 (a 3x3 5x5 and 7x7 square).
Here is a generalized code for reading the square centered at (x,y) of size n
int startx = x-n/2;
int starty = y-n/2;
for(int u=0;u<n;u++) {
for(int v=0;v<n;v++) {
int i = startx + u;
int j = starty + v;
if(i>=0 && j>=0 && i<N && j<M) {
printf(Matrix[i][j]);
}
}
}
Explanation: Start from top left value which is (x - n/2, y-n/2) now consider that you are read a normal square matrix from where i and j are indices of Matrix[i][j]. So we just added startx & starty to shift the matrix at (0,0) to (x-n/2,y-n/2).
Given:
static inline int min(int x, int y) { return (x < y) ? x : y; }
static inline int max(int x, int y) { return (x > y) ? x : y; }
or equivalent macros, and given that:
the x-coordinates range from 0 to x_max (inclusive),
the y-coordinates range from 0 to y_max (inclusive),
the centre of the square (x,y) is within the bounds,
the square you are creating has sides of (2 * size + 1) (so size is 1, 2, or 3 for the 3x3, 5x5, and 7x7 cases; or if you prefer to have sq_side = one of 3, 5, 7, then size = sq_side / 2),
the integer types are all signed (so x - size can produce a negative value; if they're unsigned, you will get the wrong result using the expressions shown),
then you can ensure that you are within bounds by setting:
x_lo = max(x - size, 0);
x_hi = min(x + size, x_max);
y_lo = max(y - size, 0);
y_hi = min(y + size, y_max);
for (x_pos = x_lo; x_pos <= x_hi; x_pos++)
{
for (y_pos = y_lo; y_pos <= y_hi; y_pos++)
{
// Process the data at array[x_pos][y_pos]
}
}
Basically, the initial assignments determine the bounds of the the array from [x-size][y-size] to [x+size][y+size], but bounded by 0 on the low side and the maximum sizes on the high end. Then scan over the relevant rectangular (usually square) sub-section of the matrix. Note that this determines the valid ranges once, outside the loops, rather than repeatedly within the loops.
If the integer types are signed, you have ensure you never try to create a negative number during subtraction. The expressions could be rewritten as:
x_lo = x - min(x, size);
x_hi = min(x + size, x_max);
y_lo = y - min(y, size);
y_hi = min(y + size, y_max);
which isn't as symmetric but only uses the min function.
Given the coordinates (x,y), you first need to find the surrounding elements. You can do that with a double for loop, like this:
for (int i = x-1; i <= x+1; i++) {
for (int j = y-1; j <= y+1; j++) {
int elem = square[i][j];
}
}
Now you just need to do a bit of work to make sure that 0 <= i,j < n, where n is the length of a side;
I don't know whether the (X,Y) in your code is the center of the square. I assume it is.
If the side of the square is odd. generate the coordinates of the points on the square. I assume the center is (0,0). Then the points on the squares are
(-side/2, [-side/2,side/2 - 1]); ([-side/2 + 1,side/2], -side/2); (side/2,[side/2 - 1,-side/2]);([side/2 - 1, side/2],-side/2);
side is the length of the square
make use of this:
while(int i<=0 && int j<=0)
for (i = x-1; i <= x+1; i++) {
for (j = y-1; j <= y+1; j++) {
int elem = square[i][j];
}
}
}

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