Day 12 (minified)
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30
day12/part1.min.py
Normal file
30
day12/part1.min.py
Normal file
@@ -0,0 +1,30 @@
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#!/usr/bin/env python3
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import numpy as np
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lines = np.array([np.array([ord(y) for y in x.strip()]) for x in open("input.txt")])
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start = tuple(np.array(np.where(lines == ord('S'))).T[0])
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end = tuple(np.array(np.where(lines == ord('E'))).T[0])
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lines[start] = ord('a')
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lines[end] = ord('z')
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lines = lines-ord('a')
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open = [(0, start, None)]
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closed = dict()
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while open:
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prio, n, prev = open.pop(0)
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if n in closed:
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continue
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closed[n] = (prio, prev)
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if n == end:
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path = [n]
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while path[-1] is not None:
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path.append(closed[path[-1]][1])
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print(len(path)-2)
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break
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for dx, dy in [(-1, 0), (0, -1), (1, 0), (0, 1)]:
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xn, yn = n[0]+dx, n[1]+dy
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if 0 <= xn < len(lines) and 0 <= yn < len(lines[0]) and lines[n] + 1 >= lines[xn, yn]:
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open.append((prio+1, (xn, yn), n))
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@@ -53,8 +53,6 @@ def find_path(start, end_fnct, neighbors_fnct, heuristic_cost_estimate_fnct, dis
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return None
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path = list(find_path(
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start,
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end_fnct=is_end,
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30
day12/part2.min.py
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30
day12/part2.min.py
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@@ -0,0 +1,30 @@
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#!/usr/bin/env python3
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import numpy as np
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lines = np.array([np.array([ord(y) for y in x.strip()]) for x in open("input.txt")])
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start = tuple(np.array(np.where(lines == ord('S'))).T[0])
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end = tuple(np.array(np.where(lines == ord('E'))).T[0])
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lines[start] = ord('a')
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lines[end] = ord('z')
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lines = lines-ord('a')
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open = [(0, end, None)]
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closed = dict()
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while open:
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prio, n, prev = open.pop(0)
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if n in closed:
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continue
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closed[n] = (prio, prev)
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if lines[n] == 0:
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path = [n]
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while path[-1] is not None:
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path.append(closed[path[-1]][1])
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print(len(path)-2)
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break
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for dx, dy in [(-1, 0), (0, -1), (1, 0), (0, 1)]:
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xn, yn = n[0]+dx, n[1]+dy
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if 0 <= xn < len(lines) and 0 <= yn < len(lines[0]) and lines[n] - 1 <= lines[xn, yn]:
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open.append((prio+1, (xn, yn), n))
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@@ -53,8 +53,6 @@ def find_path(start, end_fnct, neighbors_fnct, heuristic_cost_estimate_fnct, dis
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return None
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path = list(find_path(
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end,
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end_fnct=is_end,
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