AOC 2023, day 11

aoc2023_day10.py

import numpy as np
from scipy.spatial.distance import cdist

def dist_calc(expansion):
    grid = np.array(list(map(list, inp.splitlines())), dtype="U1")
    cols = np.nonzero(np.all(grid == ".", axis=0))[0]
    rows = np.nonzero(np.all(grid == ".", axis=1))[0]
    locs = np.argwhere(grid == "#")
    locs[:, 0] += expansion * np.sum([locs[:, 0] > r for r in rows], axis=0)
    locs[:, 1] += expansion * np.sum([locs[:, 1] > c for c in cols], axis=0)
    return int(cdist(locs, locs, metric="cityblock").sum() / 2)

part_one = dist_calc(1)
part_two = dist_calc(999_999)


# ------------------------------------------------------------------------ #
# Initial solution to part one: (will send your RAM flying if run on part 2)
# ------------------------------------------------------------------------ #
lines = []
for line in inp.splitlines():
    lines.append(line)
    if "#" not in line:
        lines.append("."*len(line))
        
columns = []
for col in map("".join, zip(*lines)):
    columns.append(col)
    if "#" not in col:
        columns.append("." * len(col))

# There and back again
uni = np.array(list(zip(*columns)))
locs = np.argwhere(uni == "#")
int(cdist(locs, locs, metric="cityblock").sum() / 2)