Hey algorithms first reddit post.
Floor tile algorithm.
I have a rather odd game project i m working on.
N 2 m 3 output.
I link a video showing the floor tile puzzle from those games here.
An important parameter for tiling is the size of the tiles.
We need 3 tiles to tile the board of size 2 x 3.
Example 2 here is one possible way of filling a 3 x 8 board.
Given a 2 x n board and tiles of size 2 x 1 count the number of ways to tile the given board using the 2 x 1 tiles.
To tile a floor with alternating black and white tiles develop an algorithm that yields the color 0 for black and 1 for white given the row and column number.
Example 1 following are all the 3 possible ways to fill up a 3 x 2 board.
A tile can either be placed horizontally or vertically.
Algorithms for tile size selection problem description.
The 4 bit example from earlier resulted in 2 4 16 tiles so this 8 bit example should surely result in 2 8 256 tiles yet there are clearly fewer than that there.
It involves my favourite gbc games of all time namely the legend of zelda.
Both n and m are positive integers and 2 m.
The correct shading will be generated only for the border tiles and there will be some inaccuracies in the remaining shading.
Below is the recursive algorithm.
N is size of given square p is location of missing cell tile int n point p 1 base case.
Input n 3 output.
A tile can either be placed horizontally i e as a 1 x 2 tile or vertically i e as 2 x 1 tile.
You have to find all the possible ways to do so.
2 is the correct shading.
Given a 3 x n board find the number of ways to fill it with 2 x 1 dominoes.
N 2 a 2 x 2 square with one cell missing is nothing but a tile and can be filled with a single tile.
1 shows the system without shading.
3 is the shading generated by the above algorithm.
The problem is to count the number of ways to tile the given floor using 1 x m tiles.
While it s true that this 8 bit bitmasking procedure results in 256 possible binary values not every combination requires an entirely unique tile.
Tiling is one of the most important locality enhancement techniques for loop nests since it permits the exploitation of data reuse in multiple loops in a loop nest.