42 lines
1.4 KiB
Python
42 lines
1.4 KiB
Python
with open('day12-input', 'r') as file:
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data = [l.strip('\n') for l in file]
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import numpy as np
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initial_state = np.array([False if s=='.' else True for s in data[0].split()[-1]], dtype=np.bool)
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rules_list = [(sum([0 if s=='.' else 2**i for i, s in enumerate(d.split()[0])]), False if d.split()[-1] == '.' else True)
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for d in data[2:]]
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rules = np.array([v for k, v in sorted(rules_list)], dtype=np.bool)
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r_transform = np.array([1, 2, 4, 8, 16], dtype=np.int64)
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state = set(*initial_state.nonzero())
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def perform_generation(input_state):
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working_state = set()
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adj = np.array([-2, -1, 0, 1, 2], dtype=np.int64)
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check_set = {i+j for i in input_state for j in adj}
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for pot in check_set:
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if rules[(r_transform * [p in input_state for p in pot+adj]).sum()]:
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working_state.add(pot)
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return working_state
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for gen in range(20):
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state = perform_generation(state)
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val = sum(state)
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print(val) # Part 1
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state_2 = state.copy()
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last_val = val
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last_deltas = [None, None, None, None]
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LAST_GEN = 50000000000
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for gen in range(20, LAST_GEN):
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if gen % 20 == 0:
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val = sum(state_2)
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last_deltas.append(val-last_val)
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last_val = val
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if len(set(last_deltas)) == 1: # If all the last few deltas are identical, give up
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print(val + (last_deltas[0]*(LAST_GEN-gen)//20)) # Part 2
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break
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last_deltas.pop(0)
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state_2 = perform_generation(state_2)
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