Samuel Enocsson
549f0c4382
🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
import numpy as np
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filename = "13-input.txt"
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def main():
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with open(filename, "r") as file:
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arr = []
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nr_reflections = 0
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pattern = 0
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for i, line in enumerate(file):
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if line == "\n":
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if arr:
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pattern += 1
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print(f"Pattern {pattern}")
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matrix = np.array(arr)
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r = get_reflections(matrix)
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print(f"Found {r} reflections")
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if r <= 0:
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print("Rotating 90 degrees")
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r = get_reflections(np.rot90(matrix)) * 100
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print(f"Found {r} reflections")
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nr_reflections += r
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arr = []
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continue
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char_array = []
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for char in line.strip():
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char_array.append(char)
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arr.append(char_array)
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print(nr_reflections)
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def get_reflections(matrix: []):
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f = {}
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for i in range(0, matrix.shape[0] - 1):
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for ii in range(i, matrix.shape[1] + 1, 2):
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part_matrix = matrix[:, i:ii]
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first, second = fold_matrix(part_matrix)
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if first.size > 0 and second.size > 0 and np.all(first == second):
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#if np.all(np.any(part_matrix == '#', axis=1)):
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print(f"Found reflection at {i}, {ii}")
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f[part_matrix.size] = ((ii - i) // 2) + i
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if not f:
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return 0
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# Sort the dictionary in descending order of keys
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sorted_f = dict(sorted(f.items(), key=lambda item: item[0], reverse=True))
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# Return the value of the first item in the sorted dictionary
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return sorted_f.popitem()[1]
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def fold_matrix(matrix: []):
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if matrix.shape[1] % 2 != 0:
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return np.empty(0), np.empty(0)
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half = matrix.shape[1] // 2
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first_half = matrix[:, :half]
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second_half = np.flip(matrix[:, half:], axis=1)
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# if len(matrix) % 2 != 0:
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# second_half = np.vstack([second_half, np.zeros_like(first_half[0])])
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return first_half, second_half
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if __name__ == "__main__":
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main()
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