def build_forest(path):
points = [
tuple(common.extract_numbers(line))
for line in common.read_file(path).splitlines()
]
direct_connections = {}
def manhattan_distance(p1, p2):
return abs(p1[0] - p2[0]) + abs(p1[1] - p2[1]) + abs(
p1[2] - p2[2]) + abs(p1[3] - p2[3])
for p in points:
if p not in direct_connections:
direct_connections[p] = []
for p2 in points:
if p == p2:
continue
if p2 not in direct_connections:
direct_connections[p2] = []
if manhattan_distance(p, p2) <= 3:
direct_connections[p].append(p2)
direct_connections[p2].append(p)
unused_points = list(points)
constellations = []
while len(unused_points) > 0:
start = unused_points[0]
seen_points = set()
q = deque([start])
while len(q) > 0:
p = q.popleft()
if p in seen_points:
continue
seen_points.add(p)
unused_points.remove(p)
for rel in direct_connections[p]:
q.append(rel)
constellations.append(list(seen_points))
return constellations
import common
year_common = common.import_year_common(2019)
tape = common.extract_numbers(common.read_file('2019/25/data.txt'))
moves = [
'south',
'take monolith',
'east',
'take asterisk',
'west',
'north',
# 'west',
# 'take coin',
# 'north',
# 'east',
# 'take astronaut ice cream',
# 'west',
# 'south',
# 'east',
'north',
'north',
# 'take mutex',
'west',
'take astrolabe',
'west',
# 'take dehydrated water',
'west',
'take wreath',
'east',
'south',
import common
import numpy as np
lines = common.read_file('2018/03/data.txt').splitlines()
parsed = [common.extract_numbers(x) for x in lines]
fabric = np.zeros((1000, 1000))
for idd, x, y, w, h in parsed:
fabric[x:x + w, y:y + h] += 1
print(np.sum(fabric > 1))
for idd, x, y, w, h in parsed:
if np.all(fabric[x:x + w, y:y + h] == 1):
print(idd)
import common
import collections as coll
data = common.read_file('2018/06/data.txt').splitlines()
parsed = [tuple(common.extract_numbers(x)) for x in data]
minx = min(map(lambda x: x[0], parsed))
miny = min(map(lambda x: x[1], parsed))
maxx = max(map(lambda x: x[0], parsed))
maxy = max(map(lambda x: x[1], parsed))
dx = maxx - minx + 1
dy = maxy - miny + 1
print(minx, maxx, miny, maxy)
def diffs(x, y):
for row in parsed:
rx, ry = row
diff = abs(rx - x) + abs(ry - y)
yield diff
def min_diff(x, y):
min_d = 50000
min_i = None
dfs = list(diffs(x, y))
for i in range(len(dfs)):
diff = dfs[i]
if diff < min_d:
min_d = diff
min_i = i
import re
from queue import PriorityQueue
import common
lines = common.read_file('2018/23/data.txt').splitlines()
rows = []
for line in lines:
nums = common.extract_numbers(line)
rows.append(tuple(nums))
X = 0
Y = 1
Z = 2
R = 3
def manhattan_dist(pos1, pos2):
return abs(pos1[X]-pos2[X])+abs(pos1[Y]-pos2[Y])+abs(pos1[Z]-pos2[Z])
def sees(bot, point):
return manhattan_dist(bot, point) <= bot[R]
# part 1
max_range_bot = max(rows, key=lambda x: x[R])
max_range_bot_pos = max_range_bot[:R]
max_range_bot_range = max_range_bot[R]
in_range_count = 0
for row in rows:
dist = manhattan_dist(max_range_bot_pos, row)
if dist <= max_range_bot_range:
in_range_count += 1
