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| author | sangeet <sangeet.kar@gmail.com> | 2020-05-28 08:46:03 +0000 |
|---|---|---|
| committer | sangeet <sangeet.kar@gmail.com> | 2020-05-28 08:46:03 +0000 |
| commit | f5b70e89f1a919d4f013f27bba42297bc4857662 (patch) | |
| tree | e7bb205fad15e2656ef67c45858da2eb02925cb7 /challenge-062/sangeet-kar/python | |
| parent | 7be5a3f822cf1f0bd971b2dada2b9d019919102c (diff) | |
| download | perlweeklychallenge-club-f5b70e89f1a919d4f013f27bba42297bc4857662.tar.gz perlweeklychallenge-club-f5b70e89f1a919d4f013f27bba42297bc4857662.tar.bz2 perlweeklychallenge-club-f5b70e89f1a919d4f013f27bba42297bc4857662.zip | |
CH-2 with beam search
Diffstat (limited to 'challenge-062/sangeet-kar/python')
| -rwxr-xr-x | challenge-062/sangeet-kar/python/ch-2a.py | 50 |
1 files changed, 50 insertions, 0 deletions
diff --git a/challenge-062/sangeet-kar/python/ch-2a.py b/challenge-062/sangeet-kar/python/ch-2a.py new file mode 100755 index 0000000000..21ed5b6898 --- /dev/null +++ b/challenge-062/sangeet-kar/python/ch-2a.py @@ -0,0 +1,50 @@ +#!/usr/bin/env python + +import sys +import heapq + +# 1. n_queens_3d finds the solution using beam search +# 2. the higher the beam_width, the better is the solution. +# 3. with beam_width=1, it's very fast but the solution may not be optimal maximising the number of queens. +# 4. with beam-width=-1, it searches the entire search space. Ensures best solution but slow as hell for high n +# 5. I think one can find the best solution with beam-width 2-3 for n-values less than 8 + + +def n_queens_3d (n = 2, beam_width = 2): + solutions = [] + place_queen ([(i, j, k) for i in range(n) for j in range(n) for k in range(n)], + [], + solutions, + beam_width=beam_width) + best = max(solutions, key=len) + print(f"queens: {len(best)}") + return indices_to_array( best, n) + +def place_queen (indices, queens, solutions, beam_width=2): + if not indices: + solutions.append(queens) + return + if beam_width == -1: + best = ((index, [i for i in indices if is_available(index, i)]) for index in indices) + else: + best = heapq.nlargest(beam_width, + ((index, [i for i in indices if is_available(index, i)]) for index in indices), + key=lambda pair: len(pair[1])) + for pos, available in best: + place_queen (available, [*queens, pos], solutions, beam_width=beam_width) + +def is_available(ref, pos): + diff = {abs(i - j) for i, j in zip (ref, pos)} + return not ( len(diff) < 2 or (len(diff) == 2 and 0 in diff)) + +def indices_to_array (indices, n): + array = [[[0 for _ in range(n)] for _ in range(n)] for _ in range(n)] + for i, j, k in indices: + array[i][j][k] = 1 + return array + +n = int(sys.argv[1]) if len(sys.argv) > 1 else 2 +beam_width = int(sys.argv[2]) if len(sys.argv) > 2 else 2 + +print(n_queens_3d (n, beam_width)) + |
