diff --git a/src/AoC_2023/Dazbo's_Advent_of_Code_2023.ipynb b/src/AoC_2023/Dazbo's_Advent_of_Code_2023.ipynb index c78f85a..a0fce85 100644 --- a/src/AoC_2023/Dazbo's_Advent_of_Code_2023.ipynb +++ b/src/AoC_2023/Dazbo's_Advent_of_Code_2023.ipynb @@ -47,19 +47,118 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "metadata": { "id": "9Dgeww1rMrkQ", "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: jupyterlab-lsp in f:\\users\\darren\\anaconda3\\envs\\ana-aoc\\lib\\site-packages (5.0.0)\n", + "Requirement already satisfied: colorama in f:\\users\\darren\\anaconda3\\envs\\ana-aoc\\lib\\site-packages (0.4.6)\n", + "Requirement already satisfied: python-dotenv in f:\\users\\darren\\anaconda3\\envs\\ana-aoc\\lib\\site-packages (0.21.0)\n", + "Requirement already satisfied: ipykernel in f:\\users\\darren\\anaconda3\\envs\\ana-aoc\\lib\\site-packages (6.25.0)\n", + 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isoduration->jsonschema[format-nongpl]>=3.2.0->jupyter-events>=0.6.0->jupyter-server>=1.1.2->jupyter-lsp>=2.0.0->jupyterlab-lsp) (1.3.0)\n", + "Requirement already satisfied: types-python-dateutil>=2.8.10 in f:\\users\\darren\\anaconda3\\envs\\ana-aoc\\lib\\site-packages (from arrow>=0.15.0->isoduration->jsonschema[format-nongpl]>=3.2.0->jupyter-events>=0.6.0->jupyter-server>=1.1.2->jupyter-lsp>=2.0.0->jupyterlab-lsp) (2.8.19.14)\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], "source": [ "%pip install jupyterlab-lsp colorama python-dotenv ipykernel " ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "metadata": { "id": "p5Ki_HvOJUWk", "tags": [] @@ -72,6 +171,7 @@ "from functools import cache, reduce\n", "from itertools import permutations, combinations, count, cycle\n", "from collections import Counter, deque, defaultdict\n", + "from io import BytesIO\n", "import heapq\n", "import copy\n", "import operator\n", @@ -82,6 +182,7 @@ "import ast\n", "import unittest\n", "import requests\n", + "import imageio\n", "import math\n", "import matplotlib.pyplot as plt\n", "from matplotlib.patches import Rectangle\n", @@ -113,7 +214,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "metadata": { "id": "SwzjfUFCKhXe", "tags": [] @@ -209,7 +310,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ @@ -269,9 +370,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[32m17:00:47.935:__main__ - INF: Using .env at F:\\Users\\Darren\\localdev\\Python\\Advent-of-Code\\.env\u001b[39m\n" + ] + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def get_envs_from_file() -> bool:\n", " \"\"\" Look for .env files, read variables from it, and store as environment variables \"\"\"\n", @@ -293,12 +412,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "metadata": { "id": "kSem0cT_LApT", "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[32m17:00:48.176:__main__ - INF: Session cookie retrieved: 53616c...ff33e0\u001b[39m\n" + ] + } + ], "source": [ "if os.getenv('AOC_SESSION_COOKIE'):\n", " logger.info('Session cookie retrieved: %s...%s', os.environ['AOC_SESSION_COOKIE'][0:6], os.environ['AOC_SESSION_COOKIE'][-6:])\n", @@ -333,7 +460,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "metadata": { "id": "VK27bcGiK0_M", "tags": [] @@ -382,7 +509,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "metadata": { "id": "lwP0r3BAaxjt", "tags": [] @@ -451,7 +578,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "metadata": { "id": "Y6nbd6WMryWi", "tags": [] @@ -479,7 +606,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 116, "metadata": { "id": "A8sU4Ez_bBKl", "tags": [] @@ -605,13 +732,95 @@ " 'tm': (0, 1)\n", " }\n", "\n", + "class Animator():\n", + " \"\"\" Creates an animation file of specified target size. \"\"\"\n", + " \n", + " def __init__(self, file: Path, duration: int, loop=1) -> None:\n", + " \"\"\" Create an Animator. Suggest the file should be a .gif.\n", + " Set duration in ms. E.g. 10 fps = 100 ms\n", + " Set loop to 0, to loop indefinitely. Default is 1. \"\"\"\n", + " self._outputfile = file\n", + " self._frames = [] # can be in-memory BytesIO objects, or files\n", + " self._duration = duration\n", + " self._loop = loop\n", + " \n", + " dir_path = Path(self._outputfile).parent\n", + " if not Path.exists(dir_path):\n", + " Path.mkdir(dir_path)\n", + " \n", + " def save_anim(self):\n", + " \"\"\" Takes animation frames, and converts to a single animated file. \"\"\"\n", + " logger.debug(\"Saving animation...\")\n", + " with imageio.get_writer(self._outputfile, mode='I', duration=self._duration, loop=self._loop) as writer:\n", + " for frame in tqdm(self._frames):\n", + " image = imageio.imread(frame)\n", + " writer.append_data(image)\n", + " \n", + " logger.info(\"Animation saved to %s\", self._outputfile)\n", + " \n", + " def add_frame(self, frame):\n", + " \"\"\" Add a frame to the animation.\n", + " The frame can be in the form of a BytesIO object, or a file Path\n", + " \"\"\"\n", + " self._frames.append(frame)\n", + " \n", "class Grid():\n", " \"\"\" 2D grid of point values. \"\"\"\n", - " def __init__(self, grid_array: list) -> None:\n", + " def __init__(self, grid_array: list, animator: Animator=None) -> None:\n", " self.array = grid_array\n", " self._width = len(self.array[0])\n", " self._height = len(self.array)\n", + " \n", + " init_str = \"Created Grid\"\n", + " if animator:\n", + " init_str += \" with Animator\"\n", + " logger.debug(init_str)\n", + " \n", + " self._animator = animator\n", + " self._plot_info = self.setup_fig() # does no work if no Animator\n", + " self._render_frame()\n", + " \n", + " def setup_fig(self):\n", + " if not self._animator:\n", + " return\n", + " \n", + " my_dpi = 120\n", + " fig, axes = plt.subplots(figsize=(1024/my_dpi, 768/my_dpi), dpi=my_dpi, facecolor=\"black\") # set size in pixels\n", "\n", + " axes.get_xaxis().set_visible(False)\n", + " axes.get_yaxis().set_visible(False)\n", + " axes.set_aspect('equal') # set x and y to equal aspect\n", + " axes.set_facecolor('xkcd:orange')\n", + " \n", + " min_x, max_x = -0.5, self.width - 0.5\n", + " min_y, max_y = -0.5, self.height - 0.5\n", + " axes.set_xlim(min_x, max_x)\n", + " axes.set_ylim(max_y, min_y)\n", + "\n", + " # dynamically compute the marker size\n", + " fig.canvas.draw()\n", + " mkr_size = ((axes.get_window_extent().width / (max_x-min_x) * (45/fig.dpi)) ** 2)\n", + " return axes, mkr_size\n", + " \n", + " def _render_frame(self):\n", + " \"\"\" Abstract implementation: add your rendering logic when extending this class.\n", + " This only renders an animation frame if we've attached an Animator. \"\"\"\n", + " if not self._animator:\n", + " return\n", + " \n", + " # axes, mkr_size = self._plot_info\n", + " \n", + " # axes.clear()\n", + " # min_x, max_x = -0.5, self.width - 0.5\n", + " # min_y, max_y = -0.5, self.height - 0.5\n", + " # axes.set_xlim(min_x, max_x)\n", + " # axes.set_ylim(max_y, min_y)\n", + " \n", + " # # save the plot as a frame; store the frame in-memory, using a BytesIO buffer\n", + " # frame = BytesIO()\n", + " # plt.savefig(frame, format='png') # save to memory, rather than file\n", + " # self._animator.add_frame(frame) \n", + " \n", " def value_at_point(self, point: Point):\n", " \"\"\" The value at this point \"\"\"\n", " return self.array[point.y][point.x]\n", @@ -677,7 +886,8 @@ " return f\"Grid(size={self.width}*{self.height})\"\n", "\n", " def __str__(self) -> str:\n", - " return \"\\n\".join(\"\".join(map(str, row)) for row in self.array)" + " return \"\\n\".join(\"\".join(map(str, row)) for row in self.array)\n", + " " ] }, { @@ -691,7 +901,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 76, "metadata": { "id": "DT5FSYliC9wp", "tags": [] @@ -793,7 +1003,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 45, "metadata": { "id": "sbdA-geUNqAF", "tags": [] @@ -3279,9 +3489,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 46, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/markdown": [ + "#### See [Day 10](https://adventofcode.com/2023/day/10)." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "DAY = \"10\" # replace with actual number (without leading digit)\n", "logger.setLevel(logging.DEBUG)\n", @@ -3291,9 +3514,42 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 47, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m17:01:38.662:aoc2023 - DBG: input.txt already exists\u001b[39m\n", + "\u001b[34m17:01:38.662:aoc2023 - DBG: input.txt already exists\u001b[39m\n", + "\u001b[32m17:01:38.664:aoc2023 - INF: Input data:\n", + " 1: ..77LJJ7|7.|F-L77.F77FLF-L-777L7.77.F7-77-F|-7-F-FL-LF7F77FFF-7F7F7F-7F7FFF777|.FL|.F|.FFF-7|FL777FF.FFF77F--L-77--|FJFFF7FLF-|-JF7J-F--7-77\n", + " 2: 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|..LL-7J.-.LLF.L|.FJJ...J..L7.LJJLJLJ.LL-JL---J-J..F-L7LFJJJ-|.LJLJJLLLJLLJJLLJLLL-L--J.L|J---|L|JJL7LLL-7-J-|-|J.L-J.J.J.LJ-7J.LL7J..LLJJJ.\u001b[39m\n" + ] + } + ], "source": [ "d_name = \"d\" + str(DAY).zfill(2) # e.g. d01\n", "script_name = \"aoc\" + str(YEAR) + d_name # e.g. aoc2017d01\n", @@ -3391,7 +3647,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 48, "metadata": {}, "outputs": [], "source": [ @@ -3444,7 +3700,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 49, "metadata": {}, "outputs": [], "source": [ @@ -3529,9 +3785,64 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 50, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m17:01:40.792:aoc2023 - DBG: Created Grid\u001b[39m\n", + "\u001b[34m17:01:40.792:aoc2023 - DBG: Created Grid\u001b[39m\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[32m17:01:40.954:aoc2023 - INF: Tests passed!\u001b[39m\n", + "\u001b[32m17:01:40.954:aoc2023 - INF: Tests passed!\u001b[39m\n", + "\u001b[34m17:01:40.954:aoc2023 - DBG: Created Grid\u001b[39m\n", + "\u001b[34m17:01:40.954:aoc2023 - DBG: Created Grid\u001b[39m\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[32m17:01:41.309:aoc2023 - INF: Part 1: steps to farthest point=6875\u001b[39m\n", + "\u001b[32m17:01:41.309:aoc2023 - INF: Part 1: steps to farthest point=6875\u001b[39m\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: total: 344 ms\n", + "Wall time: 518 ms\n" + ] + } + ], "source": [ "%%time\n", "sample_inputs = [[\"..F7.\",\n", @@ -3652,7 +3963,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 51, "metadata": {}, "outputs": [], "source": [ @@ -3682,7 +3993,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 52, "metadata": {}, "outputs": [], "source": [ @@ -3772,7 +4083,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 53, "metadata": {}, "outputs": [], "source": [ @@ -3804,9 +4115,330 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 54, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m17:01:55.419:aoc2023 - DBG: Created Grid\u001b[39m\n", + "\u001b[34m17:01:55.419:aoc2023 - DBG: Created Grid\u001b[39m\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m17:01:55.591:aoc2023 - DBG: Loop path has length 47.\u001b[39m\n", + "\u001b[34m17:01:55.591:aoc2023 - DBG: Loop path has length 47.\u001b[39m\n", + "\u001b[34m17:01:55.592:aoc2023 - DBG: Getting non_loop_tiles..\u001b[39m\n", + "\u001b[34m17:01:55.592:aoc2023 - DBG: Getting non_loop_tiles..\u001b[39m\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "233c204c125140fca7cba207327ac4d8", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/99 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m17:01:55.720:aoc2023 - DBG: Created Grid\u001b[39m\n", + "\u001b[34m17:01:55.720:aoc2023 - DBG: Created Grid\u001b[39m\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m17:01:55.883:aoc2023 - DBG: Loop path has length 45.\u001b[39m\n", + "\u001b[34m17:01:55.883:aoc2023 - DBG: Loop path has length 45.\u001b[39m\n", + "\u001b[34m17:01:55.884:aoc2023 - DBG: Getting non_loop_tiles..\u001b[39m\n", + "\u001b[34m17:01:55.884:aoc2023 - DBG: Getting non_loop_tiles..\u001b[39m\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "8339431dfed443b6bf7b15d1260a41d8", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/90 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m17:01:56.012:aoc2023 - DBG: Created Grid\u001b[39m\n", + "\u001b[34m17:01:56.012:aoc2023 - DBG: Created Grid\u001b[39m\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m17:01:56.457:aoc2023 - DBG: Loop path has length 161.\u001b[39m\n", + "\u001b[34m17:01:56.457:aoc2023 - DBG: Loop path has length 161.\u001b[39m\n", + "\u001b[34m17:01:56.458:aoc2023 - DBG: Getting non_loop_tiles..\u001b[39m\n", + "\u001b[34m17:01:56.458:aoc2023 - DBG: Getting non_loop_tiles..\u001b[39m\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ccdf4872491546ba8a8d0944239ecba7", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/200 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[32m17:01:56.580:aoc2023 - INF: Tests passed!\u001b[39m\n", + "\u001b[32m17:01:56.580:aoc2023 - INF: Tests passed!\u001b[39m\n", + "\u001b[34m17:01:56.600:aoc2023 - DBG: Loop path has length 13751.\u001b[39m\n", + "\u001b[34m17:01:56.600:aoc2023 - DBG: Loop path has length 13751.\u001b[39m\n", + "\u001b[34m17:01:56.659:aoc2023 - DBG: Getting non_loop_tiles..\u001b[39m\n", + "\u001b[34m17:01:56.659:aoc2023 - DBG: Getting non_loop_tiles..\u001b[39m\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9109883e87b54a739969aebdf3d0ba72", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/19600 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[32m17:01:58.344:aoc2023 - INF: Part 2 soln=471\u001b[39m\n", + "\u001b[32m17:01:58.344:aoc2023 - INF: Part 2 soln=471\u001b[39m\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: total: 2.33 s\n", + "Wall time: 2.93 s\n" + ] + } + ], "source": [ "%%time\n", "\n", @@ -5344,9 +5976,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 55, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/markdown": [ + "#### See [Day 16](https://adventofcode.com/2023/day/16)." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "DAY = \"16\" # replace with actual number (without leading digit)\n", "day_link = f\"#### See [Day {DAY}](https://adventofcode.com/{YEAR}/day/{DAY}).\"\n", @@ -5357,7 +6002,40 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m17:11:08.673:aoc2023 - DBG: input.txt already exists\u001b[39m\n", + "\u001b[34m17:11:08.673:aoc2023 - DBG: input.txt already exists\u001b[39m\n", + "\u001b[32m17:11:08.675:aoc2023 - INF: Input data:\n", + " 1: \\.......\\..//-.............-/....|....../-....|..................................|........--/.................\n", + " 2: ..|/..-..\\..........\\.....|......\\...-....../...................................................|.../||\\......\n", + " 3: ....././\\..........-|....|....-..........................\\.......|.............................-/\\............\n", + " 4: ...........\\..-...\\...................|.......\\/./../...|.....-.|....|.........................|..............\n", + " 5: ............|-..............-....................-...\\.........|.............-..................\\...|.....//..\n", + "...\n", + "106: |.....|.......................././...............|.../..|.\\............-.................../............./....\n", + "107: ..-........\\............./../|..........................--....|..\\.........|/./................/...../........\n", + "108: ..........\\|.....................................--............/....../............\\.|......|.......-|......\\.\n", + "109: ..........|-........\\....|.....................\\................................-\\...|......../.........\\..|..\n", + "110: ..\\\\.........\\..|../................|.........\\.....--...-...\\................/.............................\\.\u001b[39m\n", + "\u001b[32m17:11:08.675:aoc2023 - INF: Input data:\n", + " 1: \\.......\\..//-.............-/....|....../-....|..................................|........--/.................\n", + " 2: ..|/..-..\\..........\\.....|......\\...-....../...................................................|.../||\\......\n", + " 3: ....././\\..........-|....|....-..........................\\.......|.............................-/\\............\n", + " 4: ...........\\..-...\\...................|.......\\/./../...|.....-.|....|.........................|..............\n", + " 5: ............|-..............-....................-...\\.........|.............-..................\\...|.....//..\n", + "...\n", + "106: |.....|.......................././...............|.../..|.\\............-.................../............./....\n", + "107: ..-........\\............./../|..........................--....|..\\.........|/./................/...../........\n", + "108: ..........\\|.....................................--............/....../............\\.|......|.......-|......\\.\n", + "109: ..........|-........\\....|.....................\\................................-\\...|......../.........\\..|..\n", + "110: ..\\\\.........\\..|../................|.........\\.....--...-...\\................/.............................\\.\u001b[39m\n" + ] + } + ], "source": [ "d_name = \"d\" + str(DAY).zfill(2) # e.g. d01\n", "script_name = \"aoc\" + str(YEAR) + d_name # e.g. aoc2017d01\n", @@ -5440,7 +6118,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 147, "metadata": {}, "outputs": [], "source": [ @@ -5468,14 +6146,15 @@ " Vectors.W.y_inverted_value: \"<\",\n", " }\n", " \n", - " def __init__(self, grid_array: list) -> None:\n", + " def __init__(self, *args, **kwargs) -> None:\n", " \"\"\" Creates a grid that light beams pass through. \"\"\"\n", - " super().__init__(grid_array)\n", - " \n", + " \n", " # [ (posn, dirn), ... ]\n", " # dirn is the direction we were facing when we arrived at this position\n", - " self.path_taken = []\n", + " self.path_taken: list[tuple[Point, tuple[int,int]]] = []\n", " self.energised = defaultdict(set) # { point: {dirn}, }\n", + " \n", + " super().__init__(*args, **kwargs)\n", " \n", " def reset(self):\n", " \"\"\" Clear the path_taken and energised properties \"\"\"\n", @@ -5497,6 +6176,7 @@ " posn, dirn = frontier.popleft() # point, vector value\n", " self.path_taken.append((posn, dirn))\n", " self.energised[posn].add(dirn)\n", + " self._render_frame() # if an Animator is active, this will create a frame \n", " \n", " for neighbour in self.next_move(posn, dirn):\n", " if self.valid_location(neighbour[0]): # is this next move in the grid?\n", @@ -5568,27 +6248,404 @@ " rows.append(\"\".join(repr))\n", " \n", " return \"\\n\".join(rows)\n", + " \n", + " def _render_frame(self):\n", + " \"\"\" This only renders an animation frame if we've attached an Animator. \"\"\"\n", + " if not self._animator:\n", + " return\n", + " \n", + " axes, mkr_size = self._plot_info\n", + " axes.clear()\n", + " min_x, max_x = -0.5, self.width - 0.5\n", + " min_y, max_y = -0.5, self.height - 0.5\n", + " axes.set_xlim(min_x, max_x)\n", + " axes.set_ylim(max_y, min_y)\n", + " \n", + " dir_sets = []\n", + " for _ in range(4):\n", + " dir_sets.append(set())\n", + " \n", + " vert_splitters = set()\n", + " horz_splitters = set()\n", + " forw_mirrors = set()\n", + " back_mirrors = set()\n", + " \n", + " # todo: just pull out the infra from the array, rather than the path\n", + " for point, dirn in self.path_taken:\n", + " value = self.value_at_point(point)\n", + " if value in (\"|\", \"-\", \"/\", \"\\\\\"):\n", + " if value == \"|\":\n", + " vert_splitters.add(point)\n", + " elif value == \"-\":\n", + " horz_splitters.add(point)\n", + " elif value == \"/\":\n", + " forw_mirrors.add(point)\n", + " else:\n", + " back_mirrors.add(point)\n", + " else:\n", + " for dir_set, arrow in zip(dir_sets, (\"^\", \">\", \"v\", \"<\")):\n", + " if LightGrid.VECTORS_TO_ARROWS[dirn] == arrow:\n", + " dir_set.add(point)\n", + " continue\n", + " \n", + " if vert_splitters:\n", + " x, y = zip(*((point.x, point.y) for point in vert_splitters))\n", + " axes.scatter(x, y, marker=\"|\", s=mkr_size, color=\"blue\")\n", + " \n", + " if horz_splitters:\n", + " x, y = zip(*((point.x, point.y) for point in horz_splitters))\n", + " axes.scatter(x, y, marker=\"x\", s=mkr_size, color=\"blue\")\n", + " \n", + " if forw_mirrors:\n", + " x, y = zip(*((point.x, point.y) for point in forw_mirrors))\n", + " axes.scatter(x, y, marker=\"o\", s=mkr_size, color=\"blue\")\n", + " \n", + " if back_mirrors:\n", + " x, y = zip(*((point.x, point.y) for point in back_mirrors))\n", + " axes.scatter(x, y, marker=\"*\", s=mkr_size, color=\"blue\") \n", + " \n", + " for dir_set, arrow in zip(dir_sets, (\"^\", \">\", \"v\", \"<\")):\n", + " if dir_set:\n", + " dir_set_x, dir_set_y = zip(*((point.x, point.y) for point in dir_set))\n", + " axes.scatter(dir_set_x, dir_set_y, marker=arrow, s=mkr_size, color=\"white\") \n", + " \n", + " # save the plot as a frame; store the frame in-memory, using a BytesIO buffer\n", + " frame = BytesIO()\n", + " plt.savefig(frame, format='png') # save to memory, rather than file\n", + " self._animator.add_frame(frame) \n", " " ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 148, "metadata": {}, "outputs": [], "source": [ - "def solve_part1(data):\n", - " grid = LightGrid(data)\n", + "def solve_part1(data, animate=False, out_name=\"lava_floor.gif\"):\n", + " if animate:\n", + " output_file = Path(locations.output_dir, out_name)\n", + " animator = Animator(file=output_file, duration=75)\n", + " else:\n", + " animator = None\n", + " \n", + " grid = LightGrid(data, animator=animator)\n", " grid.bfs()\n", " logger.debug(f\"\\n{grid}\")\n", + " if animate:\n", + " animator.save_anim()\n", + " \n", " return len(grid.energised)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 149, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m18:11:44.409:aoc2023 - DBG: Created Grid with Animator\u001b[39m\n", + "\u001b[34m18:11:44.409:aoc2023 - DBG: Created Grid with Animator\u001b[39m\n", + "\u001b[34m18:11:47.145:aoc2023 - DBG: \n", + "\u001b[33m>\u001b[39m\u001b[33m|\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m\\\u001b[39m....\n", + "|\u001b[33mv\u001b[39m-.\\\u001b[33m^\u001b[39m....\n", + ".\u001b[33mv\u001b[39m...\u001b[33m|\u001b[39m\u001b[33m-\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\n", + 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"\u001b[34m18:11:47.146:aoc2023 - DBG: Saving animation...\u001b[39m\n", + "\u001b[34m18:11:47.146:aoc2023 - DBG: Saving animation...\u001b[39m\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "28ebaa29e9b84bdf9893d6c89e3f0a53", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/52 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+ "\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m......\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m.\\\u001b[33mv\u001b[39m....\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m.....\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m..\\\u001b[33mv\u001b[39m..\u001b[33m/\u001b[39m\u001b[33m2\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m>\u001b[39m\u001b[33m|\u001b[39m\u001b[33m2\u001b[39m.\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m.\u001b[33m2\u001b[39m\\....|..\\...\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m.....\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m...\u001b[33m^\u001b[39m.......\u001b[33m2\u001b[39m\n", + 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+ ".\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m/.\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m..../-\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m....\u001b[33mv\u001b[39m....\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m.....\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m...\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m.\u001b[33mv\u001b[39m/\u001b[33mv\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m.\u001b[33m2\u001b[39m-|.|........\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m.....\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m|\u001b[33m^\u001b[39m..|\u001b[33m^\u001b[39m.\u001b[33m/\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m/\u001b[39m\n", + ".\u001b[33m^\u001b[39m....\u001b[33m|\u001b[39m..\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m......\u001b[33m^\u001b[39m.\u001b[33m|\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m....\u001b[33mv\u001b[39m....\u001b[33m^\u001b[39m.\u001b[33m/\u001b[39m\u001b[33m3\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m<\u001b[39m\u001b[33m2\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m2\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m-\u001b[39m\u001b[33m3\u001b[39m\u001b[33m3\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m3\u001b[39m\u001b[33m3\u001b[39m\u001b[33m>\u001b[39m\u001b[33m3\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m\\\u001b[39m|.......-\u001b[33m^\u001b[39m.\\\u001b[33mv\u001b[39m/....\u001b[33m^\u001b[39m/\u001b[33m^\u001b[39m-\u001b[33m^\u001b[39m../\u001b[33m^\u001b[39m.\u001b[33m2\u001b[39m.../..\n", 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+ 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+ 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+ ".\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m....\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m.\u001b[33m^\u001b[39m...\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m....\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m.....\u001b[33m2\u001b[39m..\u001b[33m^\u001b[39m.........\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m.....\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m.\u001b[33m2\u001b[39m..../.\n", + 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+ ".\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m..-/\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m|\u001b[33m|\u001b[39m./.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m...|\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m.|...\u001b[33m2\u001b[39m..\u001b[33m^\u001b[39m.........\u001b[33m^\u001b[39m.-\u001b[33mv\u001b[39m../..\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m.\u001b[33m2\u001b[39m.....|\n", + 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ "....|.\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m-..\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m.....\u001b[33m^\u001b[39m./.......\u001b[33m^\u001b[39m.-|...\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33m2\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m^\u001b[39m-\u001b[33mv\u001b[39m/....\\.\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m..../..\n", + 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+ 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+ 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+ ".......-.\u001b[33mv\u001b[39m...\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m|.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m....\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m.......\u001b[33mv\u001b[39m...../..\\\u001b[33mv\u001b[39m|.....\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m...\\\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m......\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m.\\\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m....\u001b[33m|\u001b[39m\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m|...|..\n", + 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+ 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+ 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+ 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+ ".....\\...\u001b[33mv\u001b[39m|..\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m|.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m|..\u001b[33mv\u001b[39m.......\u001b[33mv\u001b[39m.....\u001b[33m2\u001b[39m../\u001b[33mv\u001b[39m......\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33m\\\u001b[39m\u001b[33m2\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m|\u001b[39m\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m...|\u001b[33mv\u001b[39m...\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m..\\\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m./.\u001b[33m^\u001b[39m./.\n", + 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+ ".../.....\u001b[33mv\u001b[39m...\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m....-\u001b[33mv\u001b[39m.....\u001b[33mv\u001b[39m.....\u001b[33m2\u001b[39m...\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m\\....\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m....\u001b[33mv\u001b[39m./.\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m.-\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m......\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m./\n", + 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+ 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+ 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+ "..\\\\.....\u001b[33mv\u001b[39m...\\..\u001b[33m|\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m/\u001b[39m..\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m...\u001b[33mv\u001b[39m.....\u001b[33mv\u001b[39m|.........\\....\u001b[33mv\u001b[39m--.\u001b[33mv\u001b[39m.-...\u001b[33m\\\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m/\u001b[39m..\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m...........\u001b[33mv\u001b[39m.......\u001b[33mv\u001b[39m\\.\u001b[39m\n", + "\u001b[34m18:11:48.223:aoc2023 - DBG: \n", + 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+ 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+ 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+ 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+ 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+ "\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m......\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m\\.\u001b[33m|\u001b[39m.-\u001b[33mv\u001b[39m|\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m.....\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m-\u001b[33m^\u001b[39m...\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m.\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m..\u001b[33m2\u001b[39m............\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m.....\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m-..\u001b[33m^\u001b[39m.......\u001b[33m2\u001b[39m\n", + 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+ "\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m......\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m.\\\u001b[33mv\u001b[39m....\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m.....\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m..\\\u001b[33mv\u001b[39m..\u001b[33m/\u001b[39m\u001b[33m2\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m>\u001b[39m\u001b[33m|\u001b[39m\u001b[33m2\u001b[39m.\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m.\u001b[33m2\u001b[39m\\....|..\\...\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m.....\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m...\u001b[33m^\u001b[39m.......\u001b[33m2\u001b[39m\n", + 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+ ".\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m/.\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m..../-\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m....\u001b[33mv\u001b[39m....\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m.....\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m...\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m.\u001b[33mv\u001b[39m/\u001b[33mv\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m.\u001b[33m2\u001b[39m-|.|........\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m.....\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m|\u001b[33m^\u001b[39m..|\u001b[33m^\u001b[39m.\u001b[33m/\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m/\u001b[39m\n", + 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+ ".\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m....\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m.\u001b[33m^\u001b[39m...\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m....\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m.....\u001b[33m2\u001b[39m..\u001b[33m^\u001b[39m.........\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m.....\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m.\u001b[33m2\u001b[39m..../.\n", + 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+ ".\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m..\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m..-/\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m....\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m|\u001b[33m|\u001b[39m./.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m...|\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33m2\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m.|...\u001b[33m2\u001b[39m..\u001b[33m^\u001b[39m.........\u001b[33m^\u001b[39m.-\u001b[33mv\u001b[39m../..\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m.\u001b[33m2\u001b[39m.....|\n", + 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ 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+ "......./.\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m|\u001b[39m.\u001b[33m\\\u001b[39m\u001b[33m2\u001b[39m\u001b[33m3\u001b[39m\u001b[33m2\u001b[39m\u001b[33m|\u001b[39m...\u001b[33m^\u001b[39m.....\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m.......\u001b[33m^\u001b[39m......\u001b[33mv\u001b[39m..\u001b[33m/\u001b[39m\u001b[33m\\\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33m2\u001b[39m\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m\\.....|\u001b[33mv\u001b[39m....\u001b[33m|\u001b[39m-..\u001b[33m^\u001b[39m|.\u001b[33m^\u001b[39m...|\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m...|...\n", + 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+ 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+ "....|.\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m-..\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m\u001b[33m2\u001b[39m\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m.....\u001b[33m^\u001b[39m./.......\u001b[33m^\u001b[39m.-|...\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33m2\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m<\u001b[39m\u001b[33m\\\u001b[39m\u001b[33m^\u001b[39m-\u001b[33mv\u001b[39m/....\\.\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m..../..\n", + 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+ ".../.....\u001b[33mv\u001b[39m...\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m....-\u001b[33mv\u001b[39m.....\u001b[33mv\u001b[39m.....\u001b[33m2\u001b[39m...\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m..\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m..\u001b[33mv\u001b[39m\\....\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m....\u001b[33mv\u001b[39m./.\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m...\u001b[33m^\u001b[39m.-\u001b[33m^\u001b[39m....\u001b[33mv\u001b[39m......\u001b[33m^\u001b[39m\u001b[33mv\u001b[39m./\n", + 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"..-......\u001b[33mv\u001b[39m.\\....\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33m/\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m/\u001b[39m\u001b[33m|\u001b[39m.....\u001b[33mv\u001b[39m...........\u001b[33m2\u001b[39m...\u001b[33mv\u001b[39m...\u001b[33mv\u001b[39m--...\u001b[33mv\u001b[39m|..\u001b[33m\\\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m|\u001b[39m/.\u001b[33m/\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m2\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m>\u001b[39m\u001b[33m2\u001b[39m\u001b[33m/\u001b[39m...\u001b[33mv\u001b[39m./.....\u001b[33mv\u001b[39m..\n", + ".........\u001b[33mv\u001b[39m\\|....\u001b[33m^\u001b[39m..\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m.\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33mv\u001b[39m\u001b[33m^\u001b[39m...\u001b[33mv\u001b[39m.....\u001b[33mv\u001b[39m...........\u001b[33m2\u001b[39m.--\u001b[33mv\u001b[39m...\u001b[33mv\u001b[39m.....\u001b[33mv\u001b[39m./....\u001b[33mv\u001b[39m./....\u001b[33mv\u001b[39m..\u001b[33m^\u001b[39m.\u001b[33mv\u001b[39m..\\\u001b[33mv\u001b[39m\u001b[33m|\u001b[39m.\u001b[33mv\u001b[39m....|.\u001b[33mv\u001b[39m....\u001b[33mv\u001b[39m-|.....\u001b[33mv\u001b[39m\\.\n", + 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soln=7034\u001b[39m\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: total: 3.38 s\n", + "Wall time: 3.82 s\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "%%time\n", "sample_inputs = []\n", @@ -5605,7 +6662,7 @@ "sample_answers = [46]\n", "\n", "for curr_input, curr_ans in zip(sample_inputs, sample_answers):\n", - " validate(solve_part1(curr_input.splitlines()), curr_ans) # test with sample data\n", + " validate(solve_part1(curr_input.splitlines(), animate=True, out_name=\"lava_floor.gif\"), curr_ans) # test with sample data\n", "\n", "logger.info(\"Tests passed!\")\n", "\n", @@ -5643,7 +6700,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 60, "metadata": {}, "outputs": [], "source": [ @@ -5674,9 +6731,72 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 61, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[34m17:02:35.272:aoc2023 - DBG: Created Grid\u001b[39m\n", + "\u001b[34m17:02:35.272:aoc2023 - DBG: Created Grid\u001b[39m\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "53730357b1df4476a883ccc0dd1392e5", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/40 [00:00