111 lines
2.4 KiB
Python
111 lines
2.4 KiB
Python
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import pprint
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import pandas as pd
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import numpy as np
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mas_patterns = [
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pd.DataFrame(
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[
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["M", ".", "M"],
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[".", "A", "."],
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["S", ".", "S"],
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]
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),
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pd.DataFrame(
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[
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["M", ".", "S"],
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[".", "A", "."],
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["M", ".", "S"],
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]
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),
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pd.DataFrame(
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[
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["S", ".", "M"],
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[".", "A", "."],
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["S", ".", "M"],
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]
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),
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pd.DataFrame(
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[
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["S", ".", "S"],
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[".", "A", "."],
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["M", ".", "M"],
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]
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),
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]
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def get_diagonals(input_df: pd.DataFrame):
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n_cols = len(input_df.columns)
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n_rows = len(input_df)
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diagonals = []
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for i in range(-1 * n_rows + 1, n_cols):
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diagonals.append("".join(np.diag(input_df, i)))
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return diagonals
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def get_sub_arrays(input_df: pd.DataFrame):
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n_cols = len(input_df.columns)
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n_rows = len(input_df)
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sub_arrays = []
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for i in range(n_rows - 2):
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for j in range(n_cols - 2):
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sub = input_df.iloc[i : i + 3, j : j + 3].copy()
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sub.iloc[0, 1] = "."
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sub.iloc[1, 0] = "."
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sub.iloc[1, 2] = "."
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sub.iloc[2, 1] = "."
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sub_arrays.append(sub)
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return sub_arrays
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with open("./four.txt") as f:
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wordsearch_input = f.readlines()
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lines = [list(s.strip()) for s in wordsearch_input if s]
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lines = pd.DataFrame(lines)
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possible_strings = []
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# Rows
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possible_strings.extend("".join(line.to_list()) for _, line in lines.iterrows())
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possible_strings.extend("".join(line.to_list()) for _, line in lines.items())
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# Diagonals tl - br
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possible_strings.extend(get_diagonals(lines))
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# Diagonals bl - tr
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possible_strings.extend(get_diagonals(pd.DataFrame(np.rot90(lines))))
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# Find xmas
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occurences = 0
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for string in possible_strings:
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occurences += string.upper().count("XMAS")
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occurences += string.upper().count("SAMX")
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print(occurences)
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sub_arrays = get_sub_arrays(lines)
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better_occurences = 0
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for i, sub_array in enumerate(sub_arrays):
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for j, pattern in enumerate(mas_patterns):
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try:
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equality = (sub_array.values == pattern.values).all()
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if equality:
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better_occurences += 1
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break
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except Exception:
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print(i, j)
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print(sub_array)
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print(pattern)
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raise
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print(better_occurences)
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