Solution to problem 6 in Python

src/Year_2018/P6.py

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+# --- Day 6: Chronal Coordinates ---
+
+# The device on your wrist beeps several times, and once again you feel like
+# you're falling.
+
+# "Situation critical," the device announces. "Destination indeterminate.
+# Chronal interference detected. Please specify new target coordinates."
+
+# The device then produces a list of coordinates (your puzzle input). Are they
+# places it thinks are safe or dangerous? It recommends you check manual page
+# 729. The Elves did not give you a manual.
+
+# If they're dangerous, maybe you can minimize the danger by finding the
+# coordinate that gives the largest distance from the other points.
+
+# Using only the Manhattan distance, determine the area around each coordinate
+# by counting the number of integer X,Y locations that are closest to that
+# coordinate (and aren't tied in distance to any other coordinate).
+
+# Your goal is to find the size of the largest area that isn't infinite. For
+# example, consider the following list of coordinates:
+
+# 1, 1
+# 1, 6
+# 8, 3
+# 3, 4
+# 5, 5
+# 8, 9
+
+# If we name these coordinates A through F, we can draw them on a grid, putting
+# 0,0 at the top left:
+
+# ..........
+# .A........
+# ..........
+# ........C.
+# ...D......
+# .....E....
+# .B........
+# ..........
+# ..........
+# ........F.
+
+# This view is partial - the actual grid extends infinitely in all directions.
+# Using the Manhattan distance, each location's closest coordinate can be
+# determined, shown here in lowercase:
+
+# aaaaa.cccc
+# aAaaa.cccc
+# aaaddecccc
+# aadddeccCc
+# ..dDdeeccc
+# bb.deEeecc
+# bBb.eeee..
+# bbb.eeefff
+# bbb.eeffff
+# bbb.ffffFf
+
+# Locations shown as . are equally far from two or more coordinates, and so
+# they don't count as being closest to any.
+
+# In this example, the areas of coordinates A, B, C, and F are infinite - while
+# not shown here, their areas extend forever outside the visible grid. However,
+# the areas of coordinates D and E are finite: D is closest to 9 locations, and
+# E is closest to 17 (both including the coordinate's location itself).
+# Therefore, in this example, the size of the largest area is 17.
+
+# What is the size of the largest area that isn't infinite?
+
+from collections import defaultdict
+from copy import copy
+
+with open("files/P6.txt") as f:
+    puzzle = [
+        tuple(map(int, line.split(", ")))
+        for line in f.read().strip().split("\n")
+    ]
+
+
+def manhattan_dist(coordinate, x, y):
+    return abs(coordinate[0] - x) + abs(coordinate[1] - y)
+
+
+def part_1():
+    coordinates = copy(puzzle)
+
+    # Max/min coordinates
+    max_first = max(coordinates, key=lambda e: (e[0], e[0]))[0]
+    max_second = max(coordinates, key=lambda e: (e[1], e[1]))[1]
+    min_first = min(coordinates, key=lambda e: (e[0], e[0]))[0]
+    min_second = min(coordinates, key=lambda e: (e[1], e[1]))[1]
+
+    # Holds total area per coordinate region
+    areas = defaultdict(int)
+
+    # Holds disqualified (infinite) regions
+    infiniteCoordinates = set()
+
+    for x in range(min_first, max_first + 1):
+        for y in range(min_second, max_second + 1):
+            # Holds distances mapped to coordinates
+            distances = defaultdict(list)
+
+            for coordinate in coordinates:
+                distances[manhattan_dist(coordinate, x, y)].append(coordinate)
+
+            shortestDistance = min(distances.keys())
+
+            if len(distances[shortestDistance]) == 1:
+                areas[distances[shortestDistance][0]] += 1
+
+                # Borders also indicate infinite regions
+                if (
+                    y == min_second
+                    or y == max_second
+                    or x == min_first
+                    or x == max_first
+                ):
+                    infiniteCoordinates |= set(distances[shortestDistance])
+
+    # Remove disqualified (infinite) regions
+    for coordinate in infiniteCoordinates:
+        del areas[coordinate]
+
+    print(f"The size of the largest area is {max(areas.values())}")
+
+
+# --- Part Two ---
+
+# On the other hand, if the coordinates are safe, maybe the best you can do is
+# try to find a region near as many coordinates as possible.
+
+# For example, suppose you want the sum of the Manhattan distance to all of the
+# coordinates to be less than 32. For each location, add up the distances to all
+# of the given coordinates; if the total of those distances is less than 32,
+# that location is within the desired region. Using the same coordinates as
+# above, the resulting region looks like this:
+
+# ..........
+# .A........
+# ..........
+# ...###..C.
+# ..#D###...
+# ..###E#...
+# .B.###....
+# ..........
+# ..........
+# ........F.
+
+# In particular, consider the highlighted location 4,3 located at the top middle
+# of the region. Its calculation is as follows, where abs() is the absolute
+# value function:
+
+#     Distance to coordinate A: abs(4-1) + abs(3-1) =  5
+#     Distance to coordinate B: abs(4-1) + abs(3-6) =  6
+#     Distance to coordinate C: abs(4-8) + abs(3-3) =  4
+#     Distance to coordinate D: abs(4-3) + abs(3-4) =  2
+#     Distance to coordinate E: abs(4-5) + abs(3-5) =  3
+#     Distance to coordinate F: abs(4-8) + abs(3-9) = 10
+#     Total distance: 5 + 6 + 4 + 2 + 3 + 10 = 30
+
+# Because the total distance to all coordinates (30) is less than 32, the
+# location is within the region.
+
+# This region, which also includes coordinates D and E, has a total size of 16.
+
+# Your actual region will need to be much larger than this example, though,
+# instead including all locations with a total distance of less than 10000.
+
+# What is the size of the region containing all locations which have a total
+# distance to all given coordinates of less than 10000?
+
+
+def part_2():
+    coordinates = copy(puzzle)
+
+    # Max coordinates
+    max_x = max(coordinates, key=lambda e: (e[0], e[0]))[0]
+    max_y = max(coordinates, key=lambda e: (e[1], e[1]))[1]
+
+    size = 0
+    for x in range(max_x + 1):
+        for y in range(max_y + 1):
+            total_dist = 0
+            for coordinate in coordinates:
+                distance = manhattan_dist(coordinate, x, y)
+                total_dist += distance
+            if total_dist < 10_000:
+                size += 1
+
+    print(f"The size of the region is {size}")
+
+
+if __name__ == "__main__":
+    part_1()
+    part_2()

src/Year_2018/files/P6.txt

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+300, 90
+300, 60
+176, 327
+108, 204
+297, 303
+101, 236
+70, 102
+336, 153
+260, 265
+228, 221
+119, 267
+310, 302
+291, 164
+190, 202
+298, 228
+292, 262
+53, 251
+176, 64
+170, 160
+71, 42
+314, 51
+71, 88
+319, 150
+192, 322
+270, 88
+165, 203
+262, 340
+301, 327
+135, 324
+97, 250
+161, 231
+305, 344
+295, 213
+320, 219
+172, 269
+151, 150
+215, 128
+167, 102
+158, 138
+307, 353
+358, 335
+163, 329
+234, 147
+58, 298
+228, 50
+151, 334
+108, 176
+335, 235
+296, 263
+80, 233