Day 16 (with numpy)

day16/part1-v2.py

@@ -0,0 +1,33 @@
+#!/usr/bin/env python3
+
+import re
+import numpy as np
+
+lines = (x.strip() for x in open("input.txt"))
+REGEX_RANGES = re.compile(r"^([a-z ]+): (\d+)-(\d+) or (\d+)-(\d+)$")
+REGEX_TICKET = re.compile(r"^(\d+,)*\d+$")
+read_step = 0
+mtype = '|S30,i4,i4,i4,i4'
+names = np.array([], dtype=str)
+groups = []
+tickets = []
+
+for line in lines:
+    match = REGEX_RANGES.match(line)
+    if match:
+        m_groups = match.groups()
+        names = np.append(names, [m_groups[0]])
+        groups.append(list(map(int, m_groups[1:])))
+    match = REGEX_TICKET.match(line)
+    if match:
+        ticket = tuple(map(int, line.split(',')))
+        tickets.append(ticket)
+
+groups = np.array(groups)
+tickets = np.array(tickets, dtype=np.int32)
+ranges = np.concatenate((groups[:, :2], groups[:, 2:]), axis=0)
+valids = np.full(tickets.shape, False)
+for idx, elem in np.ndenumerate(tickets):
+    valids[idx] = np.any(np.logical_and(ranges[:, 0] <= elem, elem <= ranges[:, 1]))
+
+print(np.ma.array(tickets, mask=valids).sum())

day16/part2-v2.py

@@ -0,0 +1,53 @@
+#!/usr/bin/env python3
+
+import re
+import numpy as np
+
+lines = (x.strip() for x in open("input.txt"))
+REGEX_RANGES = re.compile(r"^([a-z ]+): (\d+)-(\d+) or (\d+)-(\d+)$")
+REGEX_TICKET = re.compile(r"^(\d+,)*\d+$")
+read_step = 0
+mtype = '|S30,i4,i4,i4,i4'
+names = np.array([], dtype=str)
+groups = []
+tickets = []
+
+for line in lines:
+    match = REGEX_RANGES.match(line)
+    if match:
+        m_groups = match.groups()
+        names = np.append(names, [m_groups[0]])
+        groups.append(list(map(int, m_groups[1:])))
+    match = REGEX_TICKET.match(line)
+    if match:
+        ticket = tuple(map(int, line.split(',')))
+        tickets.append(ticket)
+
+groups = np.array(groups)
+tickets = np.array(tickets, dtype=np.int32)
+ranges = np.concatenate((groups[:, :2], groups[:, 2:]), axis=0)
+valids = np.full(tickets.shape, False)
+for idx, elem in np.ndenumerate(tickets):
+    valids[idx] = np.any(np.logical_and(ranges[:, 0] <= elem, elem <= ranges[:, 1]))
+
+tickets = tickets[np.all(valids, axis=1)]
+valids = np.full(tickets.shape, False)
+matches = np.full((groups.shape[0], groups.shape[0]), False)
+for idx in np.ndindex(matches.shape):
+    a = np.logical_or(np.logical_and(
+        groups[idx[0], 0] <= tickets[:, idx[1]],
+        groups[idx[0], 1] >= tickets[:, idx[1]]
+    ), np.logical_and(
+        groups[idx[0], 2] <= tickets[:, idx[1]],
+        groups[idx[0], 3] >= tickets[:, idx[1]]
+    ))
+    matches[idx] = np.all(a)
+
+product = 1
+for idx in np.argsort(np.count_nonzero(matches, axis=0)):
+    name = names[matches[:, idx]][0]
+    matches = np.logical_and(matches.T, np.logical_not(matches[:, idx])).T
+    if name.startswith("departure"):
+        product *= tickets[0, idx]
+
+print(product)