Rating:
A \\(m\times n\\) board yields a system of linear equations in \\(mn\\) variables. Each variable \\(a_\{ij\}\\) represents the number of mines at row \\(i\\), column \\(j\\). Each equation sets a constraint on how many mines can be at a location's neighbors based on the number in its tile. For example, if there are \\(b_\{23\}\\) mines adjacent to a non-edge tile at row \\(2\\), column \\(3\\), the correpsonding equation is
\\[a_\{13\} + a_\{22\} + a_\{33\} + a_\{24\} = b_\{23\}.\\]
Normally, such systems are solved using Gaussian elimination in \\(O((mn)^3)\\). Luckily, our system of equations is very sparse, so `scipy.sparse` can solve the system more quickly.
Flag: `BITSCTF{D0_u_y34rn_f0R_th3_m1n3s?}`
The final solve script can be found [here](https://gopherhack.com/_astro/solve.pfXOrQYr.py).
