Finding matches in two columns and replace - c

I have two columns with an int inside for each field like that:
1 2
2 3
4 1
5 6
And I also have a larger grid, like that:
1 1 1 1 2 2 1
1 2 3 4 2 1 1
1 3 2 3 1 3 2
1 3 6 5 6 1 3
The two columns let me know that I have to replace every 2 with 1, every 3 with 2 and every 1 with 4 in the larger grid, so the result can be
1 1 1 1 1 1 1
1 1 1 1 1 1 1
1 1 1 1 1 1 1
1 1 5 5 5 1 1
If I proceed directly replacing in the second table with the first entry, I won't be able to proceed with the second, since there are no more "2".
How can I solve that?
If the problem is not that clear, I give you this article that explains the problem, without showing any concrete solution.
http://www.labbookpages.co.uk/software/imgProc/blobDetection.html#table
EDIT: I have an input like that:
Table of exchanges
3 2
4 1
Table to correct
1111111111111111111111111111
1122111111111111111111113311
1122211111111111111111133311
1112221111111111111111333111
1111222111111111111113331111
1111122211111111111133311111
1111112221111111111333111111
1111111222111111113331111111
1111111122211111133311111111
1111111111222113331111111111
1111111111122222211111111111
1111111111112222111111111111
1111111111112222111111111111
1111111111122222211111111111
1111111111222442221111111111
1111111112224444222111111111
1111111122244444422211111111
1111111222444444442221111111
1111112224444444444222111111
1111122244444444444422211111
1111222444444444444442221111
1112224444444444444444222111
1122244444444444444444422211
1122444444444444444444442211
1111111111111111111111111111
(this is an X)
In this case was pretty easy to make the replacement, since I don't have another reference to 2 except than 3 and 1 for 4, but most of cases do.
What I did was to directly go and replace the 3's with 2 and the 1's with 4.

As you have found out, you can't apply the transformations one after another to your whole grid. Instead, you should find the correct transformation for each grid cell.
A rule that assigns a unique value based on the input is called a map. The identity map just maps each value to itself; these are the elements you don't change. Start with an identity map and then adjust it according to your replacement pairs.
Here's a simple program based on your first example. Make sure that each input value is a valid index in the map array.
#include <stdlib.h>
#include <stdio.h>
int main()
{
int grid[4][7] = {
{1, 1, 1, 1, 2, 2, 1},
{1, 2, 3, 4, 2, 1, 1},
{1, 3, 2, 3, 1, 3, 2},
{1, 3, 6, 5, 6, 1, 3},
};
int map[10] = {
0, 1, 2, 3, 4, 5, 6, 7, 8, 9 // identity
};
int i, j;
map[2] = 1; // adjust map to
map[3] = 2; // replacement pairs
map[1] = 4;
map[6] = 5;
// apply mapping rule
for (j = 0; j < 4; j++) {
for (i = 0; i < 7; i++) {
grid[j][i] = map[grid[j][i]];
}
}
// print grid
for (j = 0; j < 4; j++) {
for (i = 0; i < 7; i++) {
printf("%d ", grid[j][i]);
}
puts("");
}
return 0;
}

Check for Dependencies, In changer column values <2 3 1 6>. <1 6> can easily change and not depends. Afterward you need to save the states for every Integer.
Take array for store index position, i.e. if(grid==1) then one[]=grid.value; if(grid==2) then two[]=grid,value; respectively.
Now, change grid[one[]]=2; and grid[two[]]=1; Simply.

1- Duplicate the matrix (d). This will not be modified, just an aux.
2- For each cell in (d), compare (d)[cell] with every cell in 2nd row of your 2 columns.
2.1- On match, set in your result matrix (wich has been duplicated before), the value of the cell in the first column at the same (d) position.
3- Return the matrix modified.

Related

renumbering values to be consecutive

I am working with bioinformatics data. I have a sequence of repetitive numbers that are nonconsecutive in nature. I am trying to find a simple way to renumber them so that they are consecutive.
Ex:
old: 1 1 1 2 2 3 3 5 5 7 7 7 9 9
Desire change
new: 1 1 1 2 2 3 3 4 4 5 5 5 6 6
I'm using R.
One way you can solve this is by using a for loop and keeping track of the current number you are inserting and the value you are replacing.
vec <- c(1, 1, 1, 2, 2, 3, 3, 5, 5, 7, 7, 7, 9, 9)
curr <- vec[1]
rep <- vec[1]
for(i in 1:length(vec)) {
if(vec[i] > rep) {
rep <- vec[i]
curr <- curr + 1
}
if(vec[i] > curr) {
vec[i] <- curr
}
}
# Print the results
for(val in vec) {
print(val)
}
This solution assumes that the numbers are already sorted. If not, you can use the sort method.

Randoming Numbers is Way too Long [duplicate]

How do you generate a Sudoku board with a unique solution? What I thought was to initialize a random board and then remove some numbers. But my question is how do I maintain the uniqueness of a solution?
Here is the way my own SuDoKu program does it:
Start with a complete, valid board (filled with 81 numbers).
Make a list of all 81 cell positions and shuffle it randomly.
As long as the list is not empty, take the next position from the list and remove the number from the related cell.
Test uniqueness using a fast backtracking solver. My solver is - in theory - able to count all solutions, but for testing uniqueness, it will stop immediately when it finds more than one solution.
If the current board has still just one solution, goto step 3) and repeat.
If the current board has more than one solution, undo the last removal (step 3), and continue step 3 with the next position from the list
Stop when you have tested all 81 positions.
This gives you not only unique boards, but boards where you cannot remove any more numbers without destroying the uniqueness of the solution.
Of course, this is only the second half of the algorithm. The first half is to find a complete valid board first (randomly filled!) It works very similar, but "in the other direction":
Start with an empty board.
Add a random number at one of the free cells (the cell is chosen randomly, and the number is chosen randomly from the list of numbers valid for this cell according to the SuDoKu rules).
Use the backtracking solver to check if the current board has at least one valid solution. If not, undo step 2 and repeat with another number and cell. Note that this step might produce full valid boards on its own, but those are in no way random.
Repeat until the board is completely filled with numbers.
Easy:
Find all solutions with an efficient backtracking algorithm.
If there is just one solution, you are done. Otherwise if you have more than one solution, find a position at which most of the solutions differ. Add the number at this position.
Go to 1.
I doubt you can find a solution that would be much faster than this.
You can cheat. Start with an existing Sudoku board that can be solved then fiddle with it.
You can swap any row of three 3x3 blocks with any other row. You can swap any column of three 3x3 blocks with another column. Within each block row or block column you can swap single rows and single columns. Finally you can permute the numbers so there are different numbers in the filled positions as long as the permutation is consistent across the whole board.
None of these changes will make a solvable board unsolvable.
Unless P = NP, there is no polynomial-time algorithm for generating general Sudoku problems with exactly one solution.
In his master's thesis, Takayuki Yato defined The Another Solution Problem (ASP), where the goal is, given a problem and some solution, to find a different solution to that problem or to show that none exists. Yato then defined ASP-completeness, problems for which it is difficult to find another solution, and showed that Sudoku is ASP-complete. Since he also proves that ASP-completeness implies NP-hardness, this means that if you allow for arbitrary-sized Sudoku boards, there is no polynomial-time algorithm to check if the puzzle you've generated has a unique solution (unless P = NP).
Sorry to spoil your hopes for a fast algorithm!
The solution is divide in to 2 parts:
A. Generating the number pattern 600 billion
B. Generating the masking pattern ~ 7e23 combinations
A ) For Number pattern the fastest way which can generate unique combinations with NO time spent on backtracing or testing
Step 1. Choose an already exiting matrix, I chose the below one as it can be made easily by human without any help from a computing device or solver:
First row is numbers in ascending order
Second row is also in ascending order but start from 4 & roll around
Third row is also in ascending order but start from 7 & roll around
Row 4,5,6: Replace the three cell column with the top right column - 2 5 8 and roll within the 3x3 cell for last column
Row 7,8,9: Replace the three cell column with the top right column - 3 6 9 and roll within the 3x3 cell for last column
1 2 3 4 5 6 7 8 9
4 5 6 7 8 9 1 2 3
7 8 9 1 2 3 4 5 6
2 3 1 5 6 4 8 9 7
5 6 4 8 9 7 2 3 1
8 9 7 2 3 1 5 6 4
3 1 2 6 4 5 9 7 8
6 4 5 9 7 8 3 1 2
9 7 8 3 1 2 6 4 5
Step 2. Shuffle the the digits and replace in all other cells
Step 3. Randomly rearrange columns 1,2 and 3 within themselves
Step 4. Randomly rearrange columns 4,5 and 6 within themselves
Step 5. Randomly rearrange columns 7,8 and 9 within themselves
Step 6. Randomly rearrange rows 1,2 and 3 within themselves
Step 7. Randomly rearrange rows 4,5 and 6 within themselves
Step 8. Randomly rearrange rows 7,8 and 9 within themselves
Step 9. Randomly rearrange in 3 column groups of size 9x3
Step 10. Randomly rearrange in 3 row groups of size 3x9
voila...
5 8 3 1 6 4 9 7 2
7 2 9 3 5 8 1 4 6
1 4 6 2 7 9 3 8 5
8 5 2 6 9 1 4 3 7
3 1 7 4 2 5 8 6 9
6 9 4 8 3 7 2 5 1
4 6 5 9 1 3 7 2 8
2 3 1 7 8 6 5 9 4
9 7 8 5 4 2 6 1 3
B ) For Masking Pattern we need to have a solver algorithm. As we already have a quite unique number grid (which is also solved!) this gives us faster performance for using solver
Step 1: Start with selecting 15 random locations out of the 81.
Step 2: Check with solver whether it has unique solution
Step 3: If solution not unique select additional location. iterate Steps 2 and 3 until unique solution found
This should give you the very unique and fast Sudoku board.
This way you can generate any possible sudoku board as well as any other nxn sudoku board
as for how efficient this algorithm is , it took 3.6 secs to generate a million boards in java & 3.5 sec in golang
Find any filled board of sudoku. (use trivial ones will not affect final result)
int[][] board = new int[][] {
{1,2,3, 4,5,6, 7,8,9},
{4,5,6, 7,8,9, 1,2,3},
{7,8,9, 1,2,3, 4,5,6},
{2,3,1, 5,6,4, 8,9,7},
{5,6,4, 8,9,7, 2,3,1},
{8,9,7, 2,3,1, 5,6,4},
{3,1,2, 6,4,5, 9,7,8},
{6,4,5, 9,7,8, 3,1,2},
{9,7,8, 3,1,2, 6,4,5}
};
for each number from 1 to 9 (say num), (i.e 1, 2, 3, 5, 6, 7, 8, 9) take a random number from range [1 to 9], traverse the board, swap num with your random number.
void shuffleNumbers() {
for (int i = 0; i < 9; i++) {
int ranNum = random.nextInt(9);
swapNumbers(i, ranNum);
}
}
private void swapNumbers(int n1, int n2) {
for (int y = 0; y<9; y++) {
for (int x = 0; x<9; x++) {
if (board[x][y] == n1) {
board[x][y] = n2;
} else if (board[x][y] == n2) {
board[x][y] = n1;
}
}
}
}
Now shuffle rows. Take the first group of 3 rows , shuffle them , and do it for all rows. (in 9 X 9 sudoku), do it for second group and as well as third.
void shuffleRows() {
int blockNumber;
for (int i = 0; i < 9; i++) {
int ranNum = random.nextInt(3);
blockNumber = i / 3;
swapRows(i, blockNumber * 3 + ranNum);
}
}
void swapRows(int r1, int r2) {
int[] row = board[r1];
board[r1] = board[r2];
board[r2] = row;
}
Swap columns, again take block of 3 columns , shuffle them, and do it for all 3 blocks
void shuffleCols() {
int blockNumber;
for (int i = 0; i < 9; i++) {
int ranNum = random.nextInt(3);
blockNumber = i / 3;
swapCols(i, blockNumber * 3 + ranNum);
}
}
void swapCols(int c1, int c2) {
int colVal;
for (int i = 0; i < 9; i++){
colVal = board[i][c1];
board[i][c1] = board[i][c2];
board[i][c2] = colVal;
}
}
swap the row blocks itself (ie 3X9 blocks)
void shuffle3X3Rows() {
for (int i = 0; i < 3; i++) {
int ranNum = random.nextInt(3);
swap3X3Rows(i, ranNum);
}
}
void swap3X3Rows(int r1, int r2) {
for (int i = 0; i < 3; i++) {
swapRows(r1 * 3 + i, r2 * 3 + i);
}
}
do the same for columns, swap blockwise
void shuffle3X3Cols() {
for (int i = 0; i < 3; i++) {
int ranNum = random.nextInt(3);
swap3X3Cols(i, ranNum);
}
}
private void swap3X3Cols(int c1, int c2) {
for (int i = 0; i < 3; i++) {
swapCols(c1 * 3 + i, c2 * 3 + i);
}
}
Now you are done, your board should be a valid sudoku board
To generate a board with hidden values, this can be done using backtracking sudoku algorithm with it try to remove one element from the board until you have a board that is solvable, remove until it will become unsolvable even if you remove only one more element.
if you want to categorised final generated board by difficulty, just count how many numbers are left in board while removing element one by one. The less the number harder it will be to solve
least possible hints in sudoku can be 17, but all possible sudoku board not necessarily reducible to 17 hint sudoku
SWIFT 5 version
The simply way, here my code:
First, create the function into [[Int]] array
func getNumberSudoku() -> [[Int]] {
// Original number
let originalNum = [1,2,3,4,5,6,7,8,9]
// Create line 1 to 9 and shuffle from original
let line1 = originalNum.shuffled()
let line2 = line1.shift(withDistance: 3)
let line3 = line2.shift(withDistance: 3)
let line4 = line3.shift(withDistance: 1)
let line5 = line4.shift(withDistance: 3)
let line6 = line5.shift(withDistance: 3)
let line7 = line6.shift(withDistance: 1)
let line8 = line7.shift(withDistance: 3)
let line9 = line8.shift(withDistance: 3)
// Final array
let renewRow = [line1,line2,line3,line4,line5,line6,line7,line8,line9]
// Pre-shuffle for column
let colSh1 = [0,1,2].shuffled()
let colSh2 = [3,4,5].shuffled()
let colSh3 = [6,7,8].shuffled()
let rowSh1 = [0,1,2].shuffled()
let rowSh2 = [3,4,5].shuffled()
let rowSh3 = [6,7,8].shuffled()
// Create the let and var
let colResult = colSh1 + colSh2 + colSh3
let rowResult = rowSh1 + rowSh2 + rowSh3
var preCol: [Int] = []
var finalCol: [[Int]] = []
var prerow: [Int] = []
var finalRow: [[Int]] = []
// Shuffle the columns
for x in 0...8 {
preCol.removeAll()
for i in 0...8 {
preCol.append(renewRow[x][colResult[i]])
}
finalCol.append(preCol)
}
// Shuffle the rows
for x in 0...8 {
prerow.removeAll()
for i in 0...8 {
prerow.append(finalCol[x][rowResult[i]])
}
finalRow.append(prerow)
}
// Final, create the array into the [[Int]].
return finalRow
}
Then usage:
var finalArray = [[Int]]
finalArray = getNumberSudoku()
It's not easy to give a generic solution. You need to know a few things to generate a specific kind of Sudoku... for example, you cannot build a Sudoku with more than nine empty 9-number groups (rows, 3x3 blocks or columns). Minimum given numbers (i.e. "clues") in a single-solution Sudoku is believed to be 17, but number positions for this Sudoku are very specific if I'm not wrong. The average number of clues for a Sudoku is about 26, and I'm not sure but if you quit numbers of a completed grid until having 26 and leave those in a symmetric way, you may have a valid Sudoku.
On the other hand, you can just randomly quit numbers from completed grids and testing them with CHECKER or other tools until it comes up with an OK.
Here is a way to make a classic sudoku puzzle (sudoku puzzle with one and only solution; pre-filled squares are symmetrical around the center square R5C5).
1) start with a complete grid (using group filling plus circular shift to get it easily)
2) remove number(s) from two symmetrical squares if the cleared squares can be inferred using the remaining clues.
3) repeat (2) until all the numbers are checked.
Using this method you can create a very easy sudoku puzzle with or without programming. You can also use this method to craft harder Sudoku puzzles. You may want to search "create classic sudoku" on YouTube to have a step by step example.
You can start with any valid (filled) puzzle and modify it to produce a completely different one (again, filled). Instead of permutating groups of numbers, you can swap single cells - there will be no similarity whatsoever between the seed puzzle and the resulting puzzle. I have written a simple program long ago in VB, you can find it here: https://www.charalampakis.com/blog/programming-vb-net/a-simple-algorithm-for-creating-sudoku-puzzles-using-visual-basic. It can be translated to any language easily.
Then, randomly and gradually remove cells and check if the puzzle is solvable and has a unique solution. You can also rate the puzzle in terms of difficulty depending on the rules needed for the solution. Continue until removing any known cell leads to an unsolvable puzzle.
HTH
I also think that you will have to explicitly check uniqueness. If you have less than 17 givens, a unique solution is very unlikely, though: None has yet been found, although it is not clear yet whether it might exist.)
But you can also use a SAT-solver, as opposed to writing an own backtracking algorithm. That way, you can to some extent regulate how difficult it will be to find a solution: If you restrict the inference rules that the SAT-solver uses, you can check whether you can solve the puzzle easily. Just google for "SAT solving sudoku".
One way to generate sudoku faster.
find an exist sudoku.
exchange the value with a random group.
exchange the cell or the column or the row-grid or the column-grid.
You exchange the value will make the value different, if not exchange the rows or the column, the sudoku isn't changed in the essential.
You can flag the sudoku with 9 grids, the rows and column exchanged must do in the same grid. Like you can exchange row1-3, row4-6, row7-9, don't exchange row1-4 or row1-7. You can also exchange the row-grid(exchange row1~3 with the row4~6 or row7~9).
Solve the sudoku: record the empty with all the possible value, then check the value from 1 to 9. If one value is unique, remove it from the loop.
You may need code like this:
#pz is a 9x9 numpy array
def PossibleValueAtPosition(pz:[], row:int, col:int):
r=row//3*3
c=col//3*3
return {1,2,3,4,5,6,7,8,9}.difference(set(pz[r:r+3,c:c+3].flat)).difference(set(pz[row,:])).difference(set(pz[:,col]))
def SolvePuzzle(pz:[], n:int, Nof_solution:int):# init Nof_solution = 0
if Nof_solution>1:
return Nof_solution # no need to further check
if n>=81:
Nof_solution+=1
return Nof_solution
(row,col) = divmod(n,9)
if pz[row][col]>0: # location filled, try next location
Nof_solution = SolvePuzzle(pz, n+1, Nof_solution)
else:
l = PossibleValueAtPosition(pz, row,col)
for v in l: # if l = empty set, bypass all
pz[row][col] = v # try to fill a possible value v
Nof_solution = SolvePuzzle(pz, n+1, Nof_solution)
pz[row][col] = 0
return Nof_solution # resume the value, blacktrack
Quick and Dirty, but works:
import numpy as np
import math
N = 3
# rewrite of https://www.tutorialspoint.com/valid-sudoku-in-python
def isValidSudoku(M):
'''
Check a sudoku matrix:
A 9x9 sudoku matrix is valid iff every:
row contains 1 - 9 and
col contains 1 - 9 and
3x3 contains 1 - 9
0 is used for blank entry
'''
for i in range(9):
row = {}
col = {}
block = {}
row_cube = N * (i//N)
col_cube = N * (i%N)
for j in range(N*N):
if M[i][j] != 0 and M[i][j] in row:
return False
row[M[i][j]] = 1
if M[j][i] != 0 and M[j][i] in col:
return False
col[M[j][i]] = 1
rc = row_cube + j//N
cc = col_cube + j%N
if M[rc][cc] in block and M[rc][cc] != 0:
return False
block[M[rc][cc]]=1
return True
def generate_sudoku_puzzles(run_size, seed):
order = int(math.sqrt(run_size))
count = 0
valid = 0
empty = []
np.random.seed(seed) # for reproducible results
for k in range(order):
for l in range(order):
A = np.fromfunction(lambda i, j: ((k*i + l+j) % (N*N)) + 1, (N*N, N*N), dtype=int)
B = np.random.randint(2, size=(N*N, N*N))
empty.append(np.count_nonzero(B))
C = A*B
count += 1
if isValidSudoku(C):
valid += 1
last = C
# print('C(',k,l,') is valid sudoku:')
# print(C) # Uncomment for puzzle
print('Tried', count, 'valid', valid, 'yield', round(valid/count, 3)*100, '%', 'Average Clues', round(sum(empty)/len(empty)))
return(last)
posTest = np.array([(0, 7, 0, 0, 4, 0, 0, 6, 0), \
(3, 0, 0, 5, 0, 7, 0, 0, 2), \
(0, 0, 5, 0, 0, 0, 3, 0, 0), \
(0, 4, 0, 3, 0, 6, 0, 5, 0), \
(6, 0, 0, 0, 0, 0, 0, 0, 8), \
(0, 1, 0, 2, 0, 8, 0, 3, 0), \
(0, 0, 7, 0, 0, 0, 4, 0, 0), \
(1, 0, 0, 8, 0, 2, 0, 0, 9), \
(0, 6, 0, 0, 9, 0, 0, 1, 0), \
])
negTest = np.array([(0, 7, 0, 0, 4, 0, 0, 6, 2), \
(3, 0, 0, 5, 0, 7, 0, 0, 2), \
(0, 0, 5, 0, 0, 0, 3, 0, 0), \
(0, 4, 0, 3, 0, 6, 0, 5, 0), \
(6, 0, 0, 0, 0, 0, 0, 0, 8), \
(0, 1, 0, 2, 0, 8, 0, 3, 0), \
(0, 0, 7, 0, 0, 0, 4, 0, 0), \
(1, 0, 0, 8, 0, 2, 0, 0, 9), \
(0, 6, 0, 0, 9, 0, 0, 1, 0), \
])
print('Positive Quality Control Test:', isValidSudoku(posTest))
print('Negative Quality Control Test:', isValidSudoku(negTest))
print(generate_sudoku_puzzles(10000, 0))
Output:
Positive Quality Control Test: True
Negative Quality Control Test: False
Tried 10000 valid 31 yield 0.3 % Average Clues 40
[[0 0 2 3 0 0 0 7 8]
[7 8 9 1 2 0 0 0 0]
[5 0 0 0 9 0 0 3 0]
[0 0 0 6 7 8 0 0 2]
[0 2 0 0 0 0 7 8 9]
[8 0 0 2 3 0 0 0 0]
[0 0 0 0 0 2 3 0 5]
[0 5 6 0 8 9 1 2 0]
[0 3 0 5 0 0 0 9 0]]
Uncomment the two lines for puzzle source.
Here is a SQL Server stored procedure to generate Sudoku puzzles. I still need to remove values from the completed grid.
CREATE PROC dbo.sp_sudoku
AS
DROP TABLE IF EXISTS #cg
;
WITH cg
AS ( SELECT 1 AS g, 1 AS c, RAND() AS rnd
UNION ALL SELECT 1 AS g, 2 AS c, RAND() AS rnd
UNION ALL SELECT 1 AS g, 3 AS c, RAND() AS rnd
UNION ALL SELECT 2 AS g, 1 AS c, RAND() AS rnd
UNION ALL SELECT 2 AS g, 2 AS c, RAND() AS rnd
UNION ALL SELECT 2 AS g, 3 AS c, RAND() AS rnd
UNION ALL SELECT 3 AS g, 1 AS c, RAND() AS rnd
UNION ALL SELECT 3 AS g, 2 AS c, RAND() AS rnd
UNION ALL SELECT 3 AS g, 3 AS c, RAND() AS rnd)
, cg_seq
AS (SELECT g
, c
, row_number() over (partition by g
order by rnd) AS n
FROM cg)
SELECT g
, c + ((g - 1) * 3) AS c
, n + ((g - 1) * 3) AS n
INTO #cg
FROM cg_seq
--SELECT *
-- FROM #cg
-- ORDER BY g, c
DROP TABLE IF EXISTS #rg
;
WITH rg
AS ( SELECT 1 AS g, 1 AS r, RAND() AS rnd
UNION ALL SELECT 1 AS g, 2 AS r, RAND() AS rnd
UNION ALL SELECT 1 AS g, 3 AS r, RAND() AS rnd
UNION ALL SELECT 2 AS g, 1 AS r, RAND() AS rnd
UNION ALL SELECT 2 AS g, 2 AS r, RAND() AS rnd
UNION ALL SELECT 2 AS g, 3 AS r, RAND() AS rnd
UNION ALL SELECT 3 AS g, 1 AS r, RAND() AS rnd
UNION ALL SELECT 3 AS g, 2 AS r, RAND() AS rnd
UNION ALL SELECT 3 AS g, 3 AS r, RAND() AS rnd)
, rg_seq
AS (SELECT g
, r
, row_number() over (partition by g
order by rnd) AS n
FROM rg)
SELECT g
, r + ((g - 1) * 3) AS r
, n + ((g - 1) * 3) AS n
INTO #rg
FROM rg_seq
--SELECT *
-- FROM #rg
-- ORDER BY g, r
DROP TABLE IF EXISTS #r1
;
WITH r1
AS ( SELECT 1 AS r, 1 AS c, RAND() AS rnd
UNION ALL SELECT 1 AS r, 2 AS c, RAND() AS rnd
UNION ALL SELECT 1 AS r, 3 AS c, RAND() AS rnd
UNION ALL SELECT 1 AS r, 4 AS c, RAND() AS rnd
UNION ALL SELECT 1 AS r, 5 AS c, RAND() AS rnd
UNION ALL SELECT 1 AS r, 6 AS c, RAND() AS rnd
UNION ALL SELECT 1 AS r, 7 AS c, RAND() AS rnd
UNION ALL SELECT 1 AS r, 8 AS c, RAND() AS rnd
UNION ALL SELECT 1 AS r, 9 AS c, RAND() AS rnd)
, r1_seq
AS (SELECT r
, c
, row_number() over (order by rnd) AS n
FROM r1)
SELECT *
INTO #r1
FROM r1_seq
DROP TABLE IF EXISTS #r_tot
;
WITH r2
AS (SELECT r + 1 AS r
, CASE WHEN c > 6 THEN c - 6
ELSE c + 3
END AS c
, n
FROM #r1)
, r3
AS (SELECT r + 1 AS r
, CASE WHEN c > 6 THEN c - 6
ELSE c + 3
END AS c
, n
FROM r2)
, r4
AS (SELECT r + 3 AS r
, CASE WHEN c = 1 THEN c + 8
ELSE c - 1
END AS c
, n
FROM #r1)
, r5
AS (SELECT r + 1 AS r
, CASE WHEN c > 6 THEN c - 6
ELSE c + 3
END AS c
, n
FROM r4)
, r6
AS (SELECT r + 1 AS r
, CASE WHEN c > 6 THEN c - 6
ELSE c + 3
END AS c
, n
FROM r5)
, r7
AS (SELECT r + 6 AS r
, CASE WHEN c = 1 THEN c + 7
WHEN c = 2 THEN c + 7
ELSE c - 2
END AS c
, n
FROM #r1)
, r8
AS (SELECT r + 1 AS r
, CASE WHEN c > 6 THEN c - 6
ELSE c + 3
END AS c
, n
FROM r7)
, r9
AS (SELECT r + 1 AS r
, CASE WHEN c > 6 THEN c - 6
ELSE c + 3
END AS c
, n
FROM r8)
, r_tot
AS (
SELECT * FROM #r1
UNION ALL SELECT * FROM r2
UNION ALL SELECT * FROM r3
UNION ALL SELECT * FROM r4
UNION ALL SELECT * FROM r5
UNION ALL SELECT * FROM r6
UNION ALL SELECT * FROM r7
UNION ALL SELECT * FROM r8
UNION ALL SELECT * FROM r9
)
SELECT *
INTO #r_tot
FROM r_tot
DROP TABLE IF EXISTS #r_tot2
;
SELECT g.n AS r
, r.c
, r.n
INTO #r_tot2
FROM #r_tot r
, #rg g
WHERE r.r = g.r
DROP TABLE IF EXISTS #c_tot2
;
SELECT r.r
, g.n AS c
, r.n
INTO #c_tot2
FROM #r_tot2 r
, #cg g
WHERE r.c = g.c
;
WITH c1 AS (SELECT r, n FROM #c_tot2 WHERE c = 1)
, c2 AS (SELECT r, n FROM #c_tot2 WHERE c = 2)
, c3 AS (SELECT r, n FROM #c_tot2 WHERE c = 3)
, c4 AS (SELECT r, n FROM #c_tot2 WHERE c = 4)
, c5 AS (SELECT r, n FROM #c_tot2 WHERE c = 5)
, c6 AS (SELECT r, n FROM #c_tot2 WHERE c = 6)
, c7 AS (SELECT r, n FROM #c_tot2 WHERE c = 7)
, c8 AS (SELECT r, n FROM #c_tot2 WHERE c = 8)
, c9 AS (SELECT r, n FROM #c_tot2 WHERE c = 9)
SELECT c1.r
, CAST(c1.n AS CHAR(2))
+ CAST(c2.n AS CHAR(2))
+ CAST(c3.n AS CHAR(2))
+ CAST(c4.n AS CHAR(2))
+ CAST(c5.n AS CHAR(2))
+ CAST(c6.n AS CHAR(2))
+ CAST(c7.n AS CHAR(2))
+ CAST(c8.n AS CHAR(2))
+ CAST(c9.n AS CHAR(2)) AS puzzle
FROM c1, c2, c3, c4, c5, c6, c7, c8, c9 WHERE c1.r = c2.r AND c3.r = c2.r AND c4.r = c3.r AND c5.r = c4.r AND c6.r = c5.r AND c7.r = c6.r AND c8.r = c7.r AND c9.r = c8.r
ORDER BY r

Generate an array with specific duplicate elements in MATLAB

I have one array, for example B = [2,5,7], and also have a number C = 10, where C is always larger than or equal to the largest number in B.
and I want to generate an array A according to B and C. In this specific example, I have
A = [1, 2, 2, 2, 3, 4, 5, 5, 5, 6, 7, 7, 7, 8, 9, 10]
that is, I generate an array [1:C], but with each element in B are duplicated 3 times. Is there any good way that does not use for loop to generate array A?
Thank you!
You can use repelem (introduced in Matlab R2015a):
B = [2 5 7]
C = 10;
n = 3;
r = ones(1,C);
r(B) = n;
A = repelem(1:C, r)
How about...
B = [2,5,7];
C = 10;
A = sort([1:C,B,B])
I think the answer of #RPM could be faster. But because you specifically asked for a solution without sort:
B = [2,5,7];
C = 10;
D = setdiff(1:C,B)-1;
A = reshape(repmat(1:C,3,1),1,3*C);
A([3*D+1,3*D+2]) = [];
which will also return the correct result. I'm not to sure about the order setdiff() has. It might be worse than sort() in all cases. Especially with
A = sort([1:C,B,B]) as the input is already almost in order.
Following the same philosophy as this solution to Repeat copies of array elements: Run-length decoding in MATLAB, you can do something similar here, like this -
%// Get increment array (increments used after each index being repeated in B)
inc = zeros(1,C);
inc(B+1) = N-1
%// Calculate ID array (places in output array where shifts occur)
id = zeros(1,C+(N-1)*numel(B));
id(cumsum(inc) + (1:C)) = 1
%// Finally get cumulative summation for final output
A = cumsum(id)
Sample run -
B =
2 5 7
C =
10
N =
3
inc =
0 0 2 0 0 2 0 2 0 0
id =
1 1 0 0 1 1 1 0 0 1 1 0 0 1 1 1
A =
1 2 2 2 3 4 5 5 5 6 7 7 7 8 9 10

Matlab, averaging y values based on x =1

I am having trouble averaging y values based on their x counter parts.
For example
1 5
3 4
1 6
How do I get 5 and 6 to average based on being paired with an x value of 1? For my specific issue I will have 98 values between repeating 1's, and there will be a total of 99 1's in the array.
This is not extremely complicated, but it has been over a year since I have used matlab so being rusty has me scratching my head.
Here's what I got:
x = [1, 5;
3, 4;
1, 6]
col1 = x(:, 1) % extract first row
col1 =
1
3
1
ri = find(col1 == 1) % get row indices where 1 appears
ri =
1
3
mean(x(ri, 2)) % index into the second column of rows with a 1, and take average
ans = 5.5000

Formula needed: Sort array to array-"zig-zag"

I have the following array:
a = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]
I use it for some visual stuff like this:
1 2 3 4
5 6 7 8
9 10 11 12
13 14 15 16
Now I want to sort the array like this to have a "zig-zag" when rendering later.
// rearrange the array according to this schema
1 3 6 10
2 5 9 13
4 8 12 15
7 11 14 16
// the original array should look like this:
a = [1,5,2,9,6,3,13,10,7,4,14,11,8,15,12,16]
// the second index to draw should be the first index in the second row,
// which is represent by 5 in the original 1D Array
Yeah, now I'm looking for a smart formula to do that
ticker = 0;
rows = 4; // can be n
cols = 4; // can be n
originalArray = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16];
newArray = [];
while(ticker < originalArray.length)
{
//do the magic here
ticker++;
}
You can leave it sorted in the original order, you just have to step through it differently. EDIT: Turns out that my naive implementation didn't account for the differing step size based on the diagonal. The code below does and has been tested in C#.
var diagonals = new [] { 1, 2, 3, 4, 4, 3, 2, 1 };
for (int i = 0, m = 0; m < 4; i = i + m, ++m) {
for (int j = m, k = 0; k < 4; j = j + diagonals[m+k+1], ++k) {
Console.Write( i+j+1 );
Console.Write( " " );
}
Console.WriteLine();
}
Obviously, you could use this algorithm to fill a new array if you needed to keep that ordering around. It should also scale -- you just need to change the termination conditions to the square root of the array size and automate the generation of the diagonals.
Look at the structure of your matrix:
1 3
| / /
| / /
|/ / ...
2 / 5
/ /
/ /
4
The 1st row starts at 1
The 2nd row starts at 2 = 1 + 1 (# elements in 1st zig)
The 3rd row starts at 4 = 1
+ 1 (# elements in 1st zig)
+ 2 (# elements in 2nd zig)
...
The 3rd row ends at 6 = start of 3rd row + row num
= 4 + 3 = 7
You can derive a closed form formula for the ith row and go ahead.

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