mrkwse / Game-Of-Life

A GoL solution for that thing where a person wanted me to make a solution for GoL

Solution

Life.py gains setCell() method for clearer iteration through 2D array in evolve(). Both evolve() and setCell() function correctly regardless of dimensions of array (whether square or not).

Tests

It is assumed that Scenario 0 and 5 are identical in terms of input and expected output and as such, the predefined test_no_interaction test is assumed to be valid for both.

For the remainder of tests in testlife.py:

• test_underpopulation checks that for scenario 1, if a live cell has too few live neighbouring cells it dies.
• test_overcrowding checks that for scenario 2, if a live cell has too many live neighbouring cells it dies.
• test_survival checks that for scenario 3, if a live cell has 2 or 3 live neighbouring cells the cell survives (with [0,1],[1,0], and [2,2] having 2 neighbours and [1,2] and [2,1] having 3 neighbours).
• test_creation checks that for scenario 4, if an empty position has exactly 3 neighbouring cells a new live cell is created.
  • Note that test_survival checks that for 2 or 4 neighbouring live cells an empty cell doesn't create a live cell.
• test_seeded_outcome checks that for scenario 6, and with an array of a higher dimension (5x5), the example outcomes defined are correctly adhered to.
• test_non_square checks scenario 6 again, but with a [3x5] array.

Assumptions

The most substantial assumption is that the evaluation of neighbouring cells is according to their intial value, and is not affected by evolutions that may precede the evaluation of a later cell.

Another assumption is that an array will be rectangular, i.e., there will be an equal number of cells in each row. It is also assumed that a live cell will only be defined as 1. The final assumption is that an output 2D array should retain the same dimensions as the input state array.