Day_11_Chronal_Charge.ipynb

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        "<a href=\"https://colab.research.google.com/github/elichen/aoc2018/blob/main/Day_11_Chronal_Charge.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "import numpy as np\n",
        "\n",
        "def calculate_power_levels(serial_number):\n",
        "    # Create a 300x300 grid\n",
        "    grid_size = 300\n",
        "    grid = np.zeros((grid_size, grid_size))\n",
        "\n",
        "    # Calculate power levels\n",
        "    for x in range(1, grid_size + 1):\n",
        "        for y in range(1, grid_size + 1):\n",
        "            rack_id = x + 10\n",
        "            power_level = rack_id * y\n",
        "            power_level += serial_number\n",
        "            power_level *= rack_id\n",
        "            power_level = (power_level // 100 % 10) - 5\n",
        "            grid[y - 1][x - 1] = power_level\n",
        "\n",
        "    return grid\n",
        "\n",
        "def calculate_3x3_square_power_totals(grid):\n",
        "    grid_size = 300\n",
        "    square_power_totals = np.zeros((grid_size - 2, grid_size - 2))\n",
        "\n",
        "    # Calculate 3x3 square power totals\n",
        "    for x in range(grid_size - 2):\n",
        "        for y in range(grid_size - 2):\n",
        "            square_power_totals[y][x] = np.sum(grid[y:y+3, x:x+3])\n",
        "\n",
        "    return square_power_totals"
      ]
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      "source": [
        "x = 21\n",
        "y = 61\n",
        "serial_number = 42\n",
        "grid = calculate_power_levels(serial_number)\n",
        "square_power_totals = calculate_3x3_square_power_totals(grid)\n",
        "square_power_totals[y-1,x-1]"
      ],
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        "serial_number = 4172\n",
        "grid = calculate_power_levels(serial_number)\n",
        "square_power_totals = calculate_3x3_square_power_totals(grid)\n",
        "max_index = np.argmax(square_power_totals)\n",
        "y, x = np.unravel_index(max_index, square_power_totals.shape)\n",
        "x += 1\n",
        "y += 1\n",
        "(x, y)"
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    },
    {
      "cell_type": "code",
      "source": [
        "from tqdm.notebook import tqdm\n",
        "\n",
        "def calculate_square_power_totals(grid, square_size):\n",
        "    grid_size = grid.shape[0]\n",
        "    square_power_totals = np.zeros((grid_size - square_size + 1, grid_size - square_size + 1))\n",
        "\n",
        "    # Calculate square power totals for the specified size\n",
        "    for x in range(grid_size - square_size + 1):\n",
        "        for y in range(grid_size - square_size + 1):\n",
        "            square_power_totals[y][x] = np.sum(grid[y:y+square_size, x:x+square_size])\n",
        "\n",
        "    return square_power_totals\n",
        "\n",
        "serial_number = 4172\n",
        "grid = calculate_power_levels(serial_number)\n",
        "max_power = 0\n",
        "max_x,max_y = 0,0\n",
        "max_i = None\n",
        "for i in tqdm(range(1,301)):\n",
        "  power_totals = calculate_square_power_totals(grid, i)\n",
        "  max_index = np.argmax(power_totals)\n",
        "  y, x = np.unravel_index(max_index, power_totals.shape)\n",
        "  power = power_totals[y,x]\n",
        "  if power > max_power:\n",
        "    max_power = power\n",
        "    max_x,max_y = x+1,y+1\n",
        "    max_i = i\n",
        "max_x,max_y,max_i"
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