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Question of the day: https://www.careercup.com/question?id=5642834636963840

Given a 2D array of digits, try to find the occurence of a given 2D pattern of digits. For example, consider the following 2D matrix:

7283455864  
6731158619  
8988242643  
3839505324  
9509505813  
3843845384  
6473530293  
7053106601  
0834282956  
4607924137

Assume we need to look for the following 2D pattern:

950  
384  
353

Return a list of the top left indices of an occurence of the pattern in the 2D matrix. If there are multiple occurences, return all of the possible indices.

Ideas

I'm going to make some assumptions to get myself started. I can explore these assumptions more in the follow-up section later on.

  1. We don't care about finding rotations of the 2D pattern inside the matrix.
  2. We don't care about finding parts of the 2D patten inside the matrix
  3. The dimensions of the 2D pattern are always less than or equal to the respective dimensions of the matrix.

A brute force solution would be to iterate through all possible locations in the matrix and check if the 2D pattern matches starting at that location. Let's define width and height to be the width and height of the matrix. It would take O(width*height) time just to go through all the possible starting locations. Let's define pWidth and pHeight to be the width and height of the 2D pattern. So then if the pattern matches, there would be an additional O(pWidth*pHeight) per location with a possible start point, which excludes parts of the matrix. In the worst case, the runtime to this brute force solution is O((width - pWidth + 1) * (height - pHeight + 1) * pWidth * pHeight). I do a subtraction which is key, because in a matrix like this:

11111  
11111  
11111  
11111  
11111

with a 2D pattern like this:

1111  
1111  
1111  
1111

there are only 4 possible starting locations: (0, 0), (0, 1), (1,0), (1,1).

I don't think it's possible to do this problem and faster. So it's not a very complex problem, now I just have to write the code.

Code

Python

Follow up

@jjwon0 made a great observation that the Knuth-Morris-Pratt linear time string matching algorithm may be applied to 2D pattern matching to make this more efficient.

Read the wikipedia article on the algorithm, and then read this guy's blog post on what's going on with the preprocessing step.