Advent of Code 2018.ipynb

{
  "cells": [
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# Advent of Code 2018"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2018-12-07T07:19:20.684792Z",
          "start_time": "2018-12-07T07:19:20.681078Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "import os\nimport re\nimport string\n\nfrom collections import Counter, defaultdict, deque\nfrom datetime import datetime\nfrom itertools import accumulate, chain, combinations, cycle, zip_longest\nimport operator as op\n\nimport matplotlib.pyplot as plt\nimport networkx as nx\nimport numpy as np\nimport pandas as pd\nimport requests\n\nfrom scipy.spatial.distance import cdist\nfrom scipy.signal import convolve2d\nfrom scipy.ndimage import convolve\n\n%load_ext blackcellmagic\n%matplotlib inline",
      "execution_count": 1,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2018-12-07T07:14:44.789656Z",
          "start_time": "2018-12-07T07:14:44.783592Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "def input_for_day(day):\n    file_name = f\"day{day:0>2}_input\"\n    if os.path.exists(file_name):\n        return os.path.abspath(file_name)\n    with open(\"session\", \"r\") as session_file:\n        response = requests.get(\n            f\"https://adventofcode.com/2018/day/{day}/input\",\n            cookies={\"session\": session_file.read()},\n        )\n    with open(file_name, \"w\") as input_file:\n        print(response.text.strip(), file=input_file)\n    return os.path.abspath(file_name)",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Day 1\n### Part One\nStarting with a frequency of zero, what is the resulting frequency after all of the changes in frequency have been applied?"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2018-12-07T07:15:06.606814Z",
          "start_time": "2018-12-07T07:15:06.601101Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(1), \"r\") as input_file:\n    print(f\"Answer: {sum(map(int, input_file))}\")",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 538\nCPU times: user 2.36 ms, sys: 659 µs, total: 3.02 ms\nWall time: 239 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nWhat is the first frequency your device reaches twice?"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2018-12-07T07:16:21.654873Z",
          "start_time": "2018-12-07T07:16:21.622404Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nfreq_set = {0}\nwith open(input_for_day(1), \"r\") as input_file:\n    for freq in accumulate(cycle(int(line) for line in input_file)):\n        if freq in freq_set or freq_set.add(freq):\n            print(f\"Answer: {freq}\")\n            break",
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 77271\nCPU times: user 40.2 ms, sys: 0 ns, total: 40.2 ms\nWall time: 61.9 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Day 2\n### Part One\nWhat is the checksum for your list of box IDs?"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2018-12-07T08:29:17.221428Z",
          "start_time": "2018-12-07T08:29:17.211589Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(2), \"r\") as input_file:\n    counters = [Counter(n.strip()).values() for n in input_file]\nchecksum = sum(2 in c for c in counters) * sum(3 in c for c in counters)\nprint(f\"Answer: {checksum}\")",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 5976\nCPU times: user 7.96 ms, sys: 0 ns, total: 7.96 ms\nWall time: 193 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nWhat letters are common between the two correct box IDs?"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2018-12-07T08:33:07.567351Z",
          "start_time": "2018-12-07T08:33:07.5611Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(2), \"r\") as input_file:\n    counters = {x: Counter(x).values() for x in (n.strip() for n in input_file)}\nfor x, y in combinations(\n    (n for n, c in counters.items() if any(s in c for s in (2, 3))), 2\n):\n    if sum(a != b for a, b in zip(x, y)) == 1:\n        print(f\"Answer: {''.join(a for a, b in zip(x, y) if a == b)}\")\n        break",
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: xretqmmonskvzupalfiwhcfdb\nCPU times: user 14.8 ms, sys: 5.82 ms, total: 20.6 ms\nWall time: 43.7 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Day 3\n### Part One\nHow many square inches of fabric are within two or more claims?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nexpr = re.compile(r\"#(\\d+)\\s@\\s(\\d+),(\\d+):\\s(\\d+)x(\\d+)\")\nfabric = np.zeros((1000, 1000), dtype=np.uint32)\nwith open(input_for_day(3), \"r\") as input_file:\n    for claim in input_file:\n        _, x, y, w, h = map(int, expr.match(claim).groups())\n        fabric[y : y + h, x : x + w] += 1\n    print(f\"Answer: {np.sum(fabric > 1)}\")",
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 117948\nCPU times: user 26.1 ms, sys: 1.64 ms, total: 27.7 ms\nWall time: 262 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nWhat is the ID of the only claim that doesn't overlap?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nexpr = re.compile(r\"#(\\d+)\\s@\\s(\\d+),(\\d+):\\s(\\d+)x(\\d+)\")\nfabric = np.zeros((1000, 1000), dtype=np.uint32)\nwith open(input_for_day(3), \"r\") as input_file:\n    claims = [list(map(int, expr.match(claim).groups())) for claim in input_file]\nfor claim in claims:\n    _, x, y, w, h = claim\n    fabric[y : y + h, x : x + w] += 1\nfor claim in claims:\n    claim_id, x, y, w, h = claim\n    if np.all(fabric[y : y + h, x : x + w] == 1):\n        print(f\"Answer: {claim_id}\")\n        break",
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 567\nCPU times: user 16.2 ms, sys: 9.02 ms, total: 25.3 ms\nWall time: 63 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Day 4\n### Part One\nWhat is the ID of the guard you chose multiplied by the minute you chose?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nentry_expr = re.compile(r\"\\[(.+)\\]\\s(.*)\")\nguard_expr = re.compile(\"Guard\\s#(\\d+)\")\n\nguards = defaultdict(Counter)\nwith open(input_for_day(4), \"r\") as input_file:\n    lines = (entry_expr.match(entry).groups() for entry in sorted(input_file))\nfor timestamp, event in ((datetime.strptime(t, \"%Y-%m-%d %H:%M\"), e) for t, e in lines):\n    if event.startswith(\"Guard\"):\n        guard = int(guard_expr.match(event).group(1))\n    elif event.startswith(\"falls\"):\n        start = timestamp\n    elif event.startswith(\"wakes\"):\n        duration = int((timestamp - start).total_seconds()) // 60\n        guards[guard].update(Counter(start.minute + i for i in range(duration)))\n\n_, guard = max((sum(c.values()), g) for g, c in guards.items())\n\nprint(f\"Answer: {guard * guards[guard].most_common()[0][0]}\")",
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 4716\nCPU times: user 22.5 ms, sys: 7.96 ms, total: 30.5 ms\nWall time: 85.9 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nWhat is the ID of the guard you chose multiplied by the minute you chose? "
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nentry_expr = re.compile(r\"\\[(.+)\\]\\s(.*)\")\nguard_expr = re.compile(\"Guard\\s#(\\d+)\")\n\nguards = defaultdict(Counter)\nwith open(input_for_day(4), \"r\") as input_file:\n    lines = (entry_expr.match(entry).groups() for entry in sorted(input_file))\nfor timestamp, event in ((datetime.strptime(t, \"%Y-%m-%d %H:%M\"), e) for t, e in lines):\n    if event.startswith(\"Guard\"):\n        guard = int(guard_expr.match(event).group(1))\n    elif event.startswith(\"falls\"):\n        start = timestamp\n    elif event.startswith(\"wakes\"):\n        duration = int((timestamp - start).total_seconds()) // 60\n        guards[guard].update(Counter(start.minute + i for i in range(duration)))\n\n(_, minute), guard = max((c.most_common()[0][::-1], g) for g, c in guards.items())\n\nprint(f\"Answer: {guard * minute}\")",
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 117061\nCPU times: user 31 ms, sys: 173 µs, total: 31.1 ms\nWall time: 64.6 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Day 5\n### Part One\nHow many units remain after fully reacting the polymer you scanned?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\ndef collapse(s):\n    p = [\"_\"]\n    for u in s:\n        v = p[-1]\n        p.pop() if v != u and v.lower() == u.lower() else p.append(u)\n\n    return len(p) - 1\n\n\nwith open(input_for_day(5), \"r\") as input_file:\n    print(f\"Answer: {collapse(input_file.read().strip())}\")",
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 11252\nCPU times: user 22.5 ms, sys: 0 ns, total: 22.5 ms\nWall time: 195 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nWhat is the length of the shortest polymer you can produce by removing all units of exactly one type and fully reacting the result?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\ndef collapse(s):\n    p = [\"_\"]\n    for u in s:\n        v = p[-1]\n        p.pop() if v != u and v.lower() == u.lower() else p.append(u)\n\n    return len(p) - 1\n\n\nwith open(input_for_day(5), \"r\") as input_file:\n    data = input_file.read().strip()\nmin_length = min(\n    collapse(s)\n    for s in (\n        data.replace(l, \"\").replace(l.swapcase(), \"\") for l in string.ascii_lowercase\n    )\n)\nprint(f\"Answer: {min_length}\")",
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 6118\nCPU times: user 568 ms, sys: 8.25 ms, total: 576 ms\nWall time: 597 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Day 6\n### Part One\nWhat is the size of the largest area that isn't infinite?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(6), \"r\") as input_file:\n    points = np.fromiter(\n        chain.from_iterable(map(int, l.strip().split(\",\")) for l in input_file), np.uint\n    ).reshape(50, 2)\n\n# Boundaries\ntl = np.min(points, axis=0)\nbr = np.max(points, axis=0) + 1\n\n# Index grid\nxx, yy = np.mgrid[tl[0] : br[0], tl[1] : br[1]]\npositions = np.vstack([xx.ravel(), yy.ravel()]).T\n\n# Manhatten distances\ndists = cdist(positions, points, metric=\"cityblock\")\nmin_dists = np.min(dists, axis=1)\n\n# Mapping to pointts\nindex_array = min_dists[..., np.newaxis] == dists\n\n# Non ambigious distances\nnon_ambigious_index = np.sum(index_array, axis=1) == 1\nindex_array = index_array[non_ambigious_index]\n\n# Borders to filter infinit regions\nborder_index = np.any(np.vstack([tl, br - 1])[:, np.newaxis] == positions, axis=(0, 2))\nborder_index = border_index[non_ambigious_index]\nborder_index = np.any(index_array[border_index], axis=0)\n\n# Compute arrea for all points\narea = np.sum(index_array, axis=0)\n\n# Remove points that areas touch the borders\narea[border_index] = -1\n\nprint(f\"Answer: {np.max(area)}\")",
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 4754\nCPU times: user 171 ms, sys: 31.9 ms, total: 203 ms\nWall time: 350 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nWhat is the size of the region containing all locations which have a total distance to all given coordinates of less than 10000?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(6), \"r\") as input_file:\n    points = np.fromiter(\n        chain.from_iterable(map(int, l.strip().split(\",\")) for l in input_file), np.uint\n    ).reshape(50, 2)\n\n# Boundaries\ntl = np.min(points, axis=0)\nbr = np.max(points, axis=0) + 1\n\n# Index grid\nxx, yy = np.mgrid[tl[0] : br[0], tl[1] : br[1]]\npositions = np.vstack([xx.ravel(), yy.ravel()]).T\n\n# Manhatten distances\ndists = cdist(positions, points, metric=\"cityblock\")\n\nprint(f\"Answer: {np.sum(np.sum(dists, axis=1) < 10000)}\")",
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 42344\nCPU times: user 35.1 ms, sys: 0 ns, total: 35.1 ms\nWall time: 67.1 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Day 7\n### Part One\nIn what order should the steps in your instructions be completed?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nG = nx.DiGraph()\nwith open(input_for_day(7), \"r\") as input_file:\n    G.add_edges_from(re.findall(\"\\s(\\w)\\s\", edge) for edge in input_file)\n\nresult = []\nwhile G.nodes:\n    result.append(min(G.in_degree(G.nodes), key=lambda x: (x[1], x[0]))[0])\n    G.remove_node(result[-1])\n\nprint(f\"Answer: {''.join(result)}\")",
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: JNOIKSYABEQRUVWXGTZFDMHLPC\nCPU times: user 4.41 ms, sys: 0 ns, total: 4.41 ms\nWall time: 165 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nWith 5 workers and the 60+ second step durations described above, how long will it take to complete all of the steps?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nG = nx.DiGraph()\nwith open(input_for_day(7), \"r\") as input_file:\n    G.add_edges_from(re.findall(\"\\s(\\w)\\s\", edge) for edge in input_file)\n\ntick = 0\ntime_left = Counter({n: ord(n) - 4 for n in G.nodes})\nwhile G.nodes:\n    ready_nodes = [\n        x[0]\n        for x in sorted(G.in_degree(G.nodes), key=lambda x: (x[1], x[0]))\n        if x[1] == 0\n    ]\n    nodes_changed = False\n    while not nodes_changed:\n        tick = tick + 1\n        for node in ready_nodes[:5]:\n            time_left.subtract(node)\n            if time_left[node] == 0:\n                G.remove_node(node)\n                nodes_changed = True\n\nprint(f\"Answer: {tick}\")",
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 1099\nCPU times: user 10.4 ms, sys: 0 ns, total: 10.4 ms\nWall time: 39.1 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Day 8\n### Part One\nWhat is the sum of all metadata entries?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\ndef sum_meta(tree):\n    child_count = next(tree)\n    metadata_count = next(tree)\n    return sum(sum_meta(tree) for _ in range(child_count)) + sum(\n        next(tree) for _ in range(metadata_count)\n    )\n\n\nwith open(input_for_day(8), \"r\") as input_file:\n    print(f\"Answer: {sum_meta(map(int, input_file.read().split()))}\")",
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 42798\nCPU times: user 12.6 ms, sys: 445 µs, total: 13 ms\nWall time: 117 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nWhat is the value of the root node?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\ndef sum_childs(tree):\n    child_count = next(tree)\n    metadata_count = next(tree)\n    child_values = [sum_childs(tree) for _ in range(child_count)]\n    metadata_values = (next(tree) for _ in range(metadata_count))\n    return (\n        sum(child_values[i - 1] for i in metadata_values if 0 < i <= child_count)\n        if child_count\n        else sum(metadata_values)\n    )\n\n\nwith open(input_for_day(8), \"r\") as input_file:\n    print(f\"Answer: {sum_childs(map(int, input_file.read().split()))}\")",
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 23798\nCPU times: user 12.5 ms, sys: 275 µs, total: 12.8 ms\nWall time: 40.6 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Day 9\n### Part One\nWhat is the winning Elf's score?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(9), \"r\") as input_file:\n    players, marbles = map(int, re.findall(r\"\\d+\", input_file.read()))\n\nmarble_circle = deque([0])\nscores = Counter({i: 0 for i in range(players)})\nfor current_count in range(1, marbles + 1):\n    if current_count % 23 == 0:\n        marble_circle.rotate(7)\n        scores[current_count % players] += current_count + marble_circle.pop()\n        marble_circle.rotate(-1)\n    else:\n        marble_circle.rotate(-1)\n        marble_circle.append(current_count)\n\nprint(f\"Answer: {max(scores.values())}\")",
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 404502\nCPU times: user 34.7 ms, sys: 0 ns, total: 34.7 ms\nWall time: 74.4 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nWhat would the new winning Elf's score be if the number of the last marble were 100 times larger?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(9), \"r\") as input_file:\n    players, marbles = map(int, re.findall(r\"\\d+\", input_file.read()))\nmarbles *= 100\n\nmarble_circle = deque([0])\nscores = Counter({i: 0 for i in range(players)})\nfor current_count in range(1, marbles + 1):\n    if current_count % 23 == 0:\n        marble_circle.rotate(7)\n        scores[current_count % players] += current_count + marble_circle.pop()\n        marble_circle.rotate(-1)\n    else:\n        marble_circle.rotate(-1)\n        marble_circle.append(current_count)\n\nprint(f\"Answer: {max(scores.values())}\")",
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 3243916887\nCPU times: user 2.99 s, sys: 261 ms, total: 3.25 s\nWall time: 3.27 s\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Day 10\n### Part One\nWhat message will eventually appear in the sky?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(10), \"r\") as input_file:\n    positions, velocity = np.hsplit(\n        np.array([list(map(int, re.findall(r\"-?\\d+\", l))) for l in input_file]), 2\n    )\n\n\ndef bbox_area(positions):\n    return np.prod(np.max(positions, axis=0) - np.min(positions, axis=0))\n\n\nlast_area = np.iinfo(np.uint64).max\narea = bbox_area(positions)\nwhile area < last_area:\n    positions += velocity\n    last_area = area\n    area = bbox_area(positions)\n\npositions -= velocity\nplt.figure(figsize=(25, 5))\nplt.scatter(*np.hsplit(positions, 2), s=1500, marker=\"s\")\nplt.ylim(121, 110)\nprint(\"Answer:\")",
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer:\nCPU times: user 495 ms, sys: 0 ns, total: 495 ms\nWall time: 534 ms\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": "<Figure size 1800x360 with 1 Axes>"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nImpressed by your sub-hour communication capabilities, the Elves are curious: exactly how many seconds would they have needed to wait for that message to appear?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(10), \"r\") as input_file:\n    positions, velocity = np.hsplit(\n        np.array([list(map(int, re.findall(r\"-?\\d+\", l))) for l in input_file]), 2\n    )\n\n\ndef bbox_area(positions):\n    return np.prod(np.max(positions, axis=0) - np.min(positions, axis=0))\n\n\nlast_area = np.iinfo(np.uint64).max\narea = bbox_area(positions)\ncounter = -1\nwhile area < last_area:\n    counter += 1\n    positions += velocity\n    last_area = area\n    area = bbox_area(positions)\n\nprint(f\"Answer: {counter}\")",
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 10886\nCPU times: user 466 ms, sys: 0 ns, total: 466 ms\nWall time: 493 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "markdown",
      "source": "## Day 11\n### Part One\nWhat is the X,Y coordinate of the top-left fuel cell of the 3x3 square with the largest total power?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(11), \"r\") as input_file:\n    serial = int(input_file.read())\n\n\ndef fuel_level(x, y, serial):\n    rack_id = x + 10\n    return (((rack_id * y + serial) * rack_id) // 100) % 10 - 5\n\n\nx, y = np.mgrid[0:300, 0:300]\nlevels = fuel_level(x, y, serial).reshape((300, 300))\n\nres = convolve2d(levels, np.ones((3, 3)), mode=\"valid\")\nx, y = np.unravel_index(np.argmax(res), res.shape)\n\nprint(f\"Answer: {x},{y}\")",
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 21,34\nCPU times: user 12 ms, sys: 0 ns, total: 12 ms\nWall time: 45.7 ms\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Part Two\nWhat is the X,Y,size identifier of the square with the largest total power?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(11), \"r\") as input_file:\n    serial = int(input_file.read())\n\n\ndef fuel_level(x, y, serial):\n    rack_id = x + 10\n    return (((rack_id * y + serial) * rack_id) // 100) % 10 - 5\n\n\ndef max_square(levels, size):\n    kernel = np.ones((size, 1))\n    result = convolve2d(\n        convolve2d(levels, kernel, mode=\"valid\"), kernel.T, mode=\"valid\"\n    )\n    return np.max(result), np.unravel_index(np.argmax(result), result.shape), size\n\n\nx, y = np.mgrid[0:300, 0:300]\nlevels = fuel_level(x, y, serial).reshape((300, 300))\n\n_, (x, y), s = max(max_square(levels, s) for s in range(1, 301))\n\nprint(f\"Answer: {x},{y},{s}\")",
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 90,244,16\nCPU times: user 14.6 s, sys: 0 ns, total: 14.6 s\nWall time: 14.7 s\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "Really fast version using integral images."
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "%%time\nwith open(input_for_day(11), \"r\") as input_file:\n    serial = int(input_file.read())\n\ndisplay_size = 300\n\n\ndef fuel_level(x, y, serial):\n    rack_id = x + 10\n    return (((rack_id * y + serial) * rack_id) // 100) % 10 - 5\n\n\ndef max_square(integral, size):\n    x, y = np.mgrid[size:display_size, size:display_size]\n    result = (\n        integral[x, y]\n        - integral[x, y - size]\n        - integral[x - size, y]\n        + integral[x - size, y - size]\n    )\n    max_index = np.unravel_index(np.argmax(result), result.shape)\n    return result[max_index], max_index, size\n\n\nx, y = np.mgrid[0:display_size, 0:display_size]\nintegral = np.zeros((display_size + 1, display_size + 1), dtype=np.int64)\nintegral[1:, 1:] = np.cumsum(\n    fuel_level(x, y, serial).reshape((display_size, display_size)), axis=0\n).cumsum(axis=1)\n\n_, (x, y), s = max(max_square(integral, s) for s in range(1, display_size))\n\nprint(f\"Answer: {x},{y},{s}\")",
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Answer: 90,244,16\nCPU times: user 413 ms, sys: 480 µs, total: 413 ms\nWall time: 460 ms\n",
          "name": "stdout"
        }
      ]
    }
  ],
  "metadata": {
    "hide_input": false,
    "kernelspec": {
      "name": "python36",
      "display_name": "Python 3.6",
      "language": "python"
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    "language_info": {
      "mimetype": "text/x-python",
      "nbconvert_exporter": "python",
      "name": "python",
      "pygments_lexer": "ipython3",
      "version": "3.6.6",
      "file_extension": ".py",
      "codemirror_mode": {
        "version": 3,
        "name": "ipython"
      }
    },
    "toc": {
      "base_numbering": 1,
      "nav_menu": {},
      "number_sections": true,
      "sideBar": true,
      "skip_h1_title": false,
      "title_cell": "Table of Contents",
      "title_sidebar": "Contents",
      "toc_cell": false,
      "toc_position": {},
      "toc_section_display": true,
      "toc_window_display": false
    },
    "varInspector": {
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        "lenVar": 40
      },
      "kernels_config": {
        "python": {
          "delete_cmd_postfix": "",
          "delete_cmd_prefix": "del ",
          "library": "var_list.py",
          "varRefreshCmd": "print(var_dic_list())"
        },
        "r": {
          "delete_cmd_postfix": ") ",
          "delete_cmd_prefix": "rm(",
          "library": "var_list.r",
          "varRefreshCmd": "cat(var_dic_list()) "
        }
      },
      "types_to_exclude": [
        "module",
        "function",
        "builtin_function_or_method",
        "instance",
        "_Feature"
      ],
      "window_display": false
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}