Solved 2024/10 P1+P2 and added BFS to helper file
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@ -100,7 +100,86 @@ The reindeer gleefully carries over a protractor and adds it to the
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pile. *What is the sum of the scores of all trailheads on your
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pile. *What is the sum of the scores of all trailheads on your
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topographic map?*
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topographic map?*
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To begin, [get your puzzle input](10/input).
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Your puzzle answer was `754`.
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Answer:
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## \-\-- Part Two \-\-- {#part2}
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The reindeer spends a few minutes reviewing your hiking trail map before
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realizing something, disappearing for a few minutes, and finally
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returning with yet another slightly-charred piece of paper.
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The paper describes a second way to measure a trailhead called its
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*rating*. A trailhead\'s rating is the *number of distinct hiking
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trails* which begin at that trailhead. For example:
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.....0.
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..4321.
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..5..2.
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..6543.
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..7..4.
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..8765.
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..9....
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The above map has a single trailhead; its rating is `3` because there
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are exactly three distinct hiking trails which begin at that position:
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.....0. .....0. .....0.
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..4321. .....1. .....1.
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..5.... .....2. .....2.
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..6.... ..6543. .....3.
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..7.... ..7.... .....4.
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..8.... ..8.... ..8765.
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..9.... ..9.... ..9....
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Here is a map containing a single trailhead with rating `13`:
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..90..9
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...1.98
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...2..7
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6543456
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765.987
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876....
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987....
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This map contains a single trailhead with rating `227` (because there
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are `121` distinct hiking trails that lead to the `9` on the right edge
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and `106` that lead to the `9` on the bottom edge):
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012345
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123456
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234567
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345678
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4.6789
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56789.
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Here\'s the larger example from before:
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89010123
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78121874
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87430965
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96549874
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45678903
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32019012
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01329801
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10456732
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Considering its trailheads in reading order, they have ratings of `20`,
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`24`, `10`, `4`, `1`, `4`, `5`, `8`, and `5`. The sum of all trailhead
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ratings in this larger example topographic map is `81`.
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You\'re not sure how, but the reindeer seems to have crafted some tiny
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flags out of toothpicks and bits of paper and is using them to mark
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trailheads on your topographic map. *What is the sum of the ratings of
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all trailheads?*
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Your puzzle answer was `1609`.
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Both parts of this puzzle are complete! They provide two gold stars:
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\*\*
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At this point, you should [return to your Advent calendar](/2024) and
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try another puzzle.
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If you still want to see it, you can [get your puzzle
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input](10/input).
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16
2024/10/README.md
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16
2024/10/README.md
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@ -0,0 +1,16 @@
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This calls for some explanations.
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solutions_P1.py solves the first part and solutions_P2.py solves the second part.
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I first started out writing the code in solutions_P2.py but i kept getting the wrong answers.
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Basically I find a zero in the grid, then check up, down, left and right if any of them are
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a one. If any are, call find_path, which looks for two, then three and so on.
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Returns 1 each time a nine is found. This means all valid paths are returned.
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I decided to read the problem again and started from a fresh solutions_P1.py file.
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The problem can be solved using BFS (Breadth First Search). I implemented a standard BFS
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function in my fred.py helper file.
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Then used that to corrently find the solution.
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Reading part 2 i realized my first code would be useful and without modifying it, it gave me
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the right answer.
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@ -1,31 +0,0 @@
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#!/bin/python3
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import sys,time,re
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from pprint import pprint
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sys.path.insert(0, '../../')
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from fred import list2int,get_re,nprint,lprint,loadFile,toGrid,TSP,dijkstra
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start_time = time.time()
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input_f = 'test'
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part = 1
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#########################################
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# #
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# Part 1 #
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# #
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#########################################
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if part == 1:
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grid = toGrid(input_f,True)
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nprint(grid)
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print(dijkstra(grid,0,9))
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#########################################
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# #
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# Part 2 #
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# #
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#########################################
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if part == 2:
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exit()
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print("--- %s seconds ---" % (time.time() - start_time))
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67
2024/10/solution_P1.py
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2024/10/solution_P1.py
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#!/bin/python3
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import sys,time,re
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from pprint import pprint
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sys.path.insert(0, '../../')
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from fred import list2int,get_re,nprint,lprint,loadFile,toGrid,TSP,dijkstra,bfs,get_value_in_direction,addTuples
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start_time = time.time()
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input_f = 'input'
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grid = toGrid(input_f,list2int)
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directions = [(-1,0),(1,0),(0,1),(0,-1)]
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starts = []
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ends = []
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# Get coordinates of all start points (0) and all end points (9)
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for row in range(len(grid)):
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for col in range(len(grid[row])):
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if grid[row][col] == 0:
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starts.append((row,col))
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elif grid[row][col] == 9:
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ends.append((row,col))
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# If the current node is in the list of end nodes, return it.
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def is_goal(node):
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return node in ends
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# Get the neighbors of the current node.
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def get_neighbors(node):
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directions = ['up','down','left','right']
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offsets = {
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'up': (-1, 0),
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'down': (1, 0),
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'left': (0, -1),
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'right': (0, 1),
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}
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neighbors = []
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# Loop through all the directions
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for d in directions:
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t = get_value_in_direction(grid,node)
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# If the direction is 1 more than the current nodes value,
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# add it to the list of valid neighbors.
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if get_value_in_direction(grid,node,d) == t+1:
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neighbors.append(addTuples(offsets[d],node))
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# Return the list of valid neighbors
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return neighbors
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result = 0
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# Loop through all the starting points.
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for s in starts:
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# Call a standard BFS (Breadth First Search).
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# Takes the following inputs:
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# s: Starting node
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# is_goal: function that returns true if the current node is the goal
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# get_neighbors: returns a list of valid neighbors
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# Returns a list of all visited goals and the path to the goals.
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goal_nodes, paths_to_goal = bfs(s,is_goal,get_neighbors)
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# We onlu care about how many goals each starting position reached.
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result += len(goal_nodes)
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print(result)
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print("--- %s seconds ---" % (time.time() - start_time))
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44
2024/10/solution_P2.py
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2024/10/solution_P2.py
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#!/bin/python3
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import sys,time,re
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from pprint import pprint
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sys.path.insert(0, '../../')
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from fred import list2int,get_re,nprint,lprint,loadFile,toGrid, get_value_in_direction,addTuples,grid_valid
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start_time = time.time()
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input_f = 'input'
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result = 0
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dir = {
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'up': (-1, 0),
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'down': (1, 0),
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'left': (0, -1),
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'right': (0, 1)
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}
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grid = toGrid(input_f,list2int)
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def find_path(grid:list,pos:set,cur:set):
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path = 0
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if cur == 9:
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return 1
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cur+=1
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for direction in ['up', 'down', 'left', 'right']:
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next_pos = addTuples(pos, dir[direction])
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if get_value_in_direction(grid,pos,direction)== cur:
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path += find_path(grid, next_pos, cur)
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return path
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for r, row in enumerate(grid):
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for c, col in enumerate(row):
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if grid[r][c] == 0:
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for direction in ['up', 'down', 'left', 'right']:
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next_pos = addTuples((r,c), dir[direction])
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if get_value_in_direction(grid,(r,c),direction) == 1:
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result += find_path(grid,next_pos,1)
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print(result)
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print("--- %s seconds ---" % (time.time() - start_time))
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@ -1,162 +0,0 @@
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#!/bin/python3
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import sys,time,re
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from pprint import pprint
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sys.path.insert(0, '../../')
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from fred import list2int,get_re,nprint,lprint,loadFile,toGrid, get_value_in_direction,addTuples
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start_time = time.time()
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input_f = 'test2'
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part = 1
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#########################################
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# #
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# Part 1 #
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# #
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#########################################
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if part == 1:
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def get_value_in_direction(grid, position, direction=None, length=1, type: str = None):
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"""
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Get the value(s) in a specified direction from a given position in a grid.
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If no direction is provided, returns the value at the current position.
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Args:
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grid (list of list of int/float/str): The 2D grid.
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position (set): A set containing x (row index) and y (column index) as integers.
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direction (str, optional): The direction to check. Defaults to None.
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length (int, optional): The number of steps to check in the given direction. Default is 1.
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type (str, optional): The type of result to return ('list' or 'str'). Defaults to None.
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Returns:
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list or str: A list or string of values in the specified direction, or a single value.
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Raises:
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ValueError: If direction is invalid or position is not a set of two integers.
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TypeError: If grid is not a list of lists.
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"""
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if not all(isinstance(row, list) for row in grid):
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raise TypeError("Grid must be a list of lists.")
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# Ensure position is a set of two integers
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if len(position) != 2 or not all(isinstance(coord, int) for coord in position):
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raise ValueError("Position must be a set containing two integers (x, y).")
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x, y = position
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offsets = {
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'up': (-1, 0),
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'down': (1, 0),
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'left': (0, -1),
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'right': (0, 1),
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'up-left': (-1, -1),
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'up-right': (-1, 1),
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'down-left': (1, -1),
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'down-right': (1, 1)
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}
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# If no direction is given, return the value at the current position
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if direction is None:
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if 0 <= x < len(grid) and 0 <= y < len(grid[x]):
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return grid[x][y]
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else:
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return None
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# Validate direction
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if direction not in offsets:
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raise ValueError(f"Invalid direction: {direction}. Choose from {list(offsets.keys())}")
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dx, dy = offsets[direction]
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new_x, new_y = x + dx, y + dy
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values = []
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if length == 1:
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# Check for out-of-bounds
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if 0 <= new_x < len(grid) and 0 <= new_y < len(grid[new_x]):
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return grid[new_x][new_y]
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else:
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return None
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else:
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for step in range(length):
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new_x, new_y = x + step * dx, y + step * dy
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# Check for out-of-bounds
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if 0 <= new_x < len(grid) and 0 <= new_y < len(grid[new_x]):
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values.append(grid[new_x][new_y])
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else:
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return [] # Return empty list if any position is out of bounds
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if type == 'list':
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return values
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elif type == 'str':
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return ''.join(values)
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else:
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return values
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grid = toGrid(input_f,True)
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def extract_tuples(nested_list):
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result = []
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for item in nested_list:
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if isinstance(item, tuple): # Check if the item is a tuple
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result.append(item)
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elif isinstance(item, list): # If it's a list, recurse into it
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result.extend(extract_tuples(item))
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return result
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def find_path(grid,pos:set,cur):
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path = 0
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if cur == 9:
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return 1
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cur+=1
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if get_value_in_direction(grid,pos,'up') == cur:
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path += find_path(grid,addTuples(pos,(-1,0)),cur)
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if get_value_in_direction(grid,pos,'down') == cur:
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path += find_path(grid,addTuples(pos,(1,0)),cur)
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if get_value_in_direction(grid,pos,'left') == cur:
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path += find_path(grid,addTuples(pos,(0,-1)),cur)
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if get_value_in_direction(grid,pos,'right') == cur:
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path += find_path(grid,addTuples(pos,(0,1)),cur)
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return path
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result = 0
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for r, row in enumerate(grid):
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for c, col in enumerate(row):
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#get_value_in_direction(grid, position, direction=None, length=1, type: str = None):
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if grid[r][c] == 0:
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if get_value_in_direction(grid,(r,c),'up') == 1:
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#print(find_path(grid,(r-1,c),1))
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result += find_path(grid,(r-1,c),1)
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if get_value_in_direction(grid,(r,c),'down') == 1:
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result += find_path(grid,(r+1,c),1)
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#print(find_path(grid,(r+1,c),1,0))
|
|
||||||
|
|
||||||
if get_value_in_direction(grid,(r,c),'left') == 1:
|
|
||||||
result += find_path(grid,(r,c-1),1)
|
|
||||||
#print(find_path(grid,(r,c-1),1,0))
|
|
||||||
|
|
||||||
if get_value_in_direction(grid,(r,c),'right') == 1:
|
|
||||||
result += find_path(grid,(r,c+1),1)
|
|
||||||
#print(find_path(grid,(r,c+1),1,0))
|
|
||||||
|
|
||||||
print(result)
|
|
||||||
|
|
||||||
|
|
||||||
#########################################
|
|
||||||
# #
|
|
||||||
# Part 2 #
|
|
||||||
# #
|
|
||||||
#########################################
|
|
||||||
if part == 2:
|
|
||||||
exit()
|
|
||||||
|
|
||||||
print("--- %s seconds ---" % (time.time() - start_time))
|
|
@ -1,7 +1,7 @@
|
|||||||
# AdventOfCode
|
# AdventOfCode
|
||||||
|
|
||||||
## 2024
|
## 2024
|
||||||
|
.-----. .------------------.
|
||||||
.--'~ ~ ~| .-' * \ / '-. 1 **
|
.--'~ ~ ~| .-' * \ / '-. 1 **
|
||||||
.--'~ ,* ~ | | >o< \_\_\|_/__/ | 2 **
|
.--'~ ,* ~ | | >o< \_\_\|_/__/ | 2 **
|
||||||
.---': ~ '(~), ~| | >@>O< o-_/.()__------| 3 **
|
.---': ~ '(~), ~| | >@>O< o-_/.()__------| 3 **
|
||||||
@ -11,6 +11,7 @@
|
|||||||
|#~~~@@@@ @ | |/\ ''. | | -/ :| 7 **
|
|#~~~@@@@ @ | |/\ ''. | | -/ :| 7 **
|
||||||
|~~..--. _____ | |* /~\ '.| | - / .'| 8 **
|
|~~..--. _____ | |* /~\ '.| | - / .'| 8 **
|
||||||
'---' ||[][]_\-| |~/ * \ :| | *..' | 9 **
|
'---' ||[][]_\-| |~/ * \ :| | *..' | 9 **
|
||||||
|
|------- | | /\ .'| |'''~~~~~| 10 **
|
||||||
|
|
||||||
## 2023
|
## 2023
|
||||||
|
|
||||||
|
Binary file not shown.
51
fred.py
51
fred.py
@ -71,7 +71,7 @@ def toGrid(input, parser=None):
|
|||||||
try:
|
try:
|
||||||
with open(input) as file:
|
with open(input) as file:
|
||||||
for line in file:
|
for line in file:
|
||||||
grid.append(list2int(list(line.rstrip())) if parser else list(line.rstrip())) # Use parser or default processing
|
grid.append(parser(list(line.rstrip())) if parser else list(line.rstrip())) # Use parser or default processing
|
||||||
except FileNotFoundError:
|
except FileNotFoundError:
|
||||||
raise FileNotFoundError(f"The file '{input}' was not found.")
|
raise FileNotFoundError(f"The file '{input}' was not found.")
|
||||||
except IOError as e:
|
except IOError as e:
|
||||||
@ -539,4 +539,51 @@ def TSP(graph, start, path_type='shortest'):
|
|||||||
if not best_path:
|
if not best_path:
|
||||||
print(f"No valid path found starting at '{start}'. Ensure all cities are connected.")
|
print(f"No valid path found starting at '{start}'. Ensure all cities are connected.")
|
||||||
|
|
||||||
return best_path, best_distance if best_path else None
|
return best_path, best_distance if best_path else None
|
||||||
|
|
||||||
|
def bfs(start, is_goal, get_neighbors, max_depth=float('inf')):
|
||||||
|
"""
|
||||||
|
Generic Breadth-First Search (BFS) function.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
start: The starting node/state
|
||||||
|
is_goal: A function that checks if the current node is a goal state
|
||||||
|
get_neighbors: A function that returns valid neighboring nodes/states
|
||||||
|
max_depth: Maximum search depth to prevent infinite loops (default: no limit)
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
tuple: (goal_nodes, paths_to_goal)
|
||||||
|
- goal_nodes: List of nodes that satisfy the goal condition
|
||||||
|
- paths_to_goal: Dictionary mapping goal nodes to their paths from start
|
||||||
|
"""
|
||||||
|
# Queue for BFS: each element is (current_node, path_to_node, depth)
|
||||||
|
queue = [(start, [start], 0)]
|
||||||
|
|
||||||
|
# Track visited nodes to prevent cycles
|
||||||
|
visited = set([start])
|
||||||
|
|
||||||
|
# Store goal nodes and their paths
|
||||||
|
goal_nodes = []
|
||||||
|
paths_to_goal = {}
|
||||||
|
|
||||||
|
while queue:
|
||||||
|
current, path, depth = queue.pop(0)
|
||||||
|
|
||||||
|
# Check if current node is a goal
|
||||||
|
if is_goal(current):
|
||||||
|
goal_nodes.append(current)
|
||||||
|
paths_to_goal[current] = path
|
||||||
|
|
||||||
|
# Stop if max depth reached
|
||||||
|
if depth >= max_depth:
|
||||||
|
continue
|
||||||
|
|
||||||
|
# Explore neighbors
|
||||||
|
for neighbor in get_neighbors(current):
|
||||||
|
# Prevent revisiting nodes
|
||||||
|
if neighbor not in visited:
|
||||||
|
visited.add(neighbor)
|
||||||
|
new_path = path + [neighbor]
|
||||||
|
queue.append((neighbor, new_path, depth + 1))
|
||||||
|
|
||||||
|
return goal_nodes, paths_to_goal
|
Loading…
Reference in New Issue
Block a user