afvanwoudenberg/word_search_clock.ipynb

## word_search_clock.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "da4f8e1d-20be-41ad-abf6-cd02103f9f84",
   "metadata": {},
   "source": [
    "# Word Search Clock\n",
    "\n",
    "Aswin van Woudenberg (https://www.aswinvanwoudenberg.com | https://github.com/afvanwoudenberg)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40559a4a-7831-4643-a606-e6776b852dc7",
   "metadata": {},
   "source": [
    "## Importing libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f8fde0fa-36d1-4753-9fdb-4901873e57bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import string\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9e0e3db-2489-4682-ba9b-60f31d3a69be",
   "metadata": {},
   "source": [
    "## Specifying the word order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "850e02ef-16a5-4eab-980b-191d5aaa3a59",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Words to fill. Each tuple is (ID, word, preceding)\n",
    "words = [\n",
    "    (0, \"it\", []), \n",
    "    (1, \"is\", [0]),\n",
    "    (2, \"twenty\", [1]),\n",
    "    (3, \"half\", [1]),\n",
    "    (4, \"ten\", [1]),\n",
    "    (5, \"eleven\", [1]),\n",
    "    (6, \"twelve\", [1]),\n",
    "    (7, \"thirteen\", [1]),\n",
    "    (8, \"fourteen\", [2]),\n",
    "    (9, \"sixteen\", [2]),\n",
    "    (10, \"seventeen\", [2]),\n",
    "    (11, \"eighteen\", [2]),\n",
    "    (12, \"nineteen\", [2]),\n",
    "    (13, \"a\", [1]),\n",
    "    (14, \"quarter\", [13]),\n",
    "    (15, \"one\", [2]),\n",
    "    (16, \"two\", [2]),\n",
    "    (17, \"three\", [2]),\n",
    "    (18, \"five\", [2]),\n",
    "    (19, \"minutes\", [15, 16, 17, 8, 9, 10, 11, 12, 5, 6, 7]),\n",
    "    (20, \"past\", [19, 18, 4, 14, 2, 3]),\n",
    "    (21, \"to\", [19, 18, 4, 14, 2]),\n",
    "    (22, \"one\", [20, 21]),\n",
    "    (23, \"two\", [20, 21]),\n",
    "    (24, \"three\", [20, 21]),\n",
    "    (25, \"four\", [20, 21]),\n",
    "    (26, \"five\", [20, 21]),\n",
    "    (27, \"six\", [20, 21]),\n",
    "    (28, \"seven\", [20, 21]),\n",
    "    (29, \"eight\", [20, 21]),\n",
    "    (30, \"nine\", [20, 21]),\n",
    "    (31, \"ten\", [20, 21]),\n",
    "    (32, \"eleven\", [20, 21]),\n",
    "    (33, \"twelve\", [20, 21]),\n",
    "    (34, \"oclock\", [22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33])\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df652e15-3810-44f3-9b57-1ee7f926a33d",
   "metadata": {},
   "source": [
    "## Filling the grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "89fdd587-3616-42e9-9674-48da0d6845a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "directions = [(1, 0), (0, 1), (1, 1), (1, -1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "749369aa-09df-4ac4-9c86-726c84016397",
   "metadata": {},
   "outputs": [],
   "source": [
    "def placeable_word_ids(words):\n",
    "    unplaced_word_ids = [id for (id, _, loc, _, _) in words if loc is None]\n",
    "    return [id for (id, _, loc, _, prec) in words if not any(prec_id in unplaced_word_ids for prec_id in prec) and loc is None]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "701e8818-9cdb-487b-811c-7b5a3b33c595",
   "metadata": {},
   "outputs": [],
   "source": [
    "def can_place_word(word, grid, dir, r, c):\n",
    "    height = len(grid)\n",
    "    width = len(grid[0])\n",
    "    d_x, d_y = dir\n",
    "    if c + len(word) * d_x > width or r + len(word) * d_y > height or c + len(word) * d_x < 0 or r + len(word) * d_y < 0:\n",
    "        return False\n",
    "    for i, ch in enumerate(word):\n",
    "        if grid[r + i * d_y][c + i * d_x] not in ['?', ch]: \n",
    "            return False\n",
    "    return True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "40161d4d-94c0-401c-a1e0-c035edbf65dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "def replace_characters(word, grid, dir, r, c):\n",
    "    height = len(grid)\n",
    "    width = len(grid[0])\n",
    "    previous = \"\"\n",
    "    d_x, d_y = dir\n",
    "    for i, ch in enumerate(word):\n",
    "        previous += grid[r + i * d_y][c + i * d_x]\n",
    "        grid[r + i * d_y][c + i * d_x] = ch\n",
    "    return previous"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "81cb242a-69db-48b5-8af0-5fb265082819",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fill_grid_(grid, words, i=0):\n",
    "    height = len(grid)\n",
    "    width = len(grid[0])\n",
    "    ids = placeable_word_ids(words)\n",
    "    \n",
    "    if not ids:\n",
    "        yield grid, words\n",
    "    elif i < height * width:\n",
    "        row = i // width\n",
    "        col = i % width\n",
    "        for id in ids:\n",
    "            dir_length = len(directions)\n",
    "            for d in range(dir_length):\n",
    "                dir = directions[(i + d) % dir_length]\n",
    "                if can_place_word(words[id][1], grid, dir, row, col):\n",
    "                    previous = replace_characters(words[id][1], grid, dir, row, col)\n",
    "                    words[id] = (id, words[id][1], (col, row), dir, words[id][4])\n",
    "                    yield from fill_grid_(grid, words, i+1)\n",
    "                    words[id] = (id, words[id][1], None, None, words[id][4])\n",
    "                    replace_characters(previous, grid, dir, row, col)\n",
    "        else:\n",
    "            yield from fill_grid_(grid, words, i+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c4569ec6-01ba-46f4-9a33-3bc1da2c16cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fill_grid(width, height):\n",
    "    loc_dir_words = [(id, word, None, None, prec) for (id, word, prec) in words]\n",
    "    grid = [['?' for c in range(width)] for r in range(height)]\n",
    "    yield from fill_grid_(grid, loc_dir_words, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c4d25be6-4567-4241-a6ea-889e5af19ee9",
   "metadata": {},
   "outputs": [],
   "source": [
    "gen = fill_grid(15, 11)\n",
    "(g, w) = next(gen)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "409b841f-42fc-4da3-b521-5d8538e05467",
   "metadata": {},
   "source": [
    "## Occupying vacant spaces in grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "97adbe36-6fe5-4f57-a9a0-7bf16043d067",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(row.count('?') for row in g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3a8c27c5-f52c-4411-a53f-625a7249491a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def remove_spaces_and_punctuation(input_string):\n",
    "    # Remove spaces\n",
    "    no_spaces = input_string.replace(\" \", \"\")\n",
    "    \n",
    "    # Remove punctuation\n",
    "    translator = str.maketrans(\"\", \"\", string.punctuation)\n",
    "    no_punctuation = no_spaces.translate(translator)\n",
    "    \n",
    "    return no_punctuation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "06d48b62-bd05-47a8-a127-8103e42a612a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def replace_question_marks(grid, phrase):\n",
    "    chars = remove_spaces_and_punctuation(phrase)\n",
    "    i = 0\n",
    "    for row in range(len(grid)):\n",
    "        for col in range(len(grid[row])):\n",
    "            if grid[row][col] == '?' and i < len(chars):\n",
    "                grid[row][col] = chars[i]\n",
    "                i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4569e747-f972-4c25-877c-6aedc7c78712",
   "metadata": {},
   "outputs": [],
   "source": [
    "replace_question_marks(g, \"Time keeps moving\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6b3e015-e780-4430-8e6e-59a5f72afaa2",
   "metadata": {},
   "source": [
    "## Plotting the grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fc6cc643-c86f-4dd1-b3a3-1649f712f1df",
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_to_sentence(hours, minutes):\n",
    "    # Define words for numbers\n",
    "    time_words = [\"twelve\", \"one\", \"two\", \"three\", \"four\", \"five\", \"six\", \"seven\", \"eight\", \"nine\", \"ten\", \n",
    "             \"eleven\", \"twelve\", \"thirteen\", \"fourteen\", \"a quarter\", \"sixteen\", \"seventeen\", \"eighteen\", \"nineteen\", \"twenty\",\n",
    "             \"twenty-one\", \"twenty-two\", \"twenty-three\", \"twenty-four\", \"twenty-five\", \"twenty-six\", \"twenty-seven\", \"twenty-eight\", \"twenty-nine\", \"half\"]\n",
    "\n",
    "    # Convert hours and minutes to words\n",
    "    if minutes <= 30:\n",
    "        hour_word = time_words[hours % 12]\n",
    "        minute_word = time_words[minutes]\n",
    "    else:\n",
    "        hour_word = time_words[(hours+1) % 12]\n",
    "        minute_word = time_words[60 - minutes]\n",
    "        \n",
    "    # Determine whether it's past or to\n",
    "    if minutes == 0:\n",
    "        time_phrase = f\"it is {hour_word} o'clock\"\n",
    "    elif minutes in [5, 10, 15, 20, 25, 30]:\n",
    "        time_phrase = f\"it is {minute_word} past {hour_word}\"\n",
    "    elif minutes in [35, 40, 45, 50, 55]:\n",
    "        time_phrase = f\"it is {minute_word} to {hour_word}\"\n",
    "    elif minutes == 1:\n",
    "        time_phrase = f\"it is {minute_word} minute past {hour_word}\"\n",
    "    elif minutes == 59:\n",
    "        time_phrase = f\"it is {minute_word} minute to {hour_word}\"\n",
    "    elif minutes < 30:\n",
    "        time_phrase = f\"it is {minute_word} minutes past {hour_word}\"\n",
    "    else:\n",
    "        time_phrase = f\"it is {minute_word} minutes to {hour_word}\"\n",
    "\n",
    "    return time_phrase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e3d6cda1-40db-4f99-acc2-7acd87543d7c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "it is twenty-three minutes past ten\n",
      "it is eight minutes past twelve\n"
     ]
    }
   ],
   "source": [
    "print(time_to_sentence(10, 23))\n",
    "print(time_to_sentence(0, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7b5122b0-bdd4-4578-9c84-ccbc3bc5064d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def word_at_location(words, r, c):\n",
    "    for (id, word, (x, y), dir, prec) in words:\n",
    "        if x == c and y == r:\n",
    "            return (id, word, (x, y), dir, prec)\n",
    "    return None        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "74363d7c-5f16-437e-bc13-b37046180c6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_grid(grid, words=None, hours=None, minutes=None, ax=None):\n",
    "    if not ax:\n",
    "        # Create a figure and axes\n",
    "        fig, ax = plt.subplots(figsize=(12,9))\n",
    "    else:\n",
    "        fig = None\n",
    "    \n",
    "    # Give all cells the same value/color\n",
    "    ax.imshow([[0 for cell in row] for row in grid], cmap='gray')\n",
    "\n",
    "    ax.patch.set_edgecolor('black')\n",
    "    ax.patch.set_linewidth(2)\n",
    "    \n",
    "    # Display the letters\n",
    "    for i in range(len(grid)):\n",
    "        for j in range(len(grid[0])):\n",
    "            ax.text(j, i, grid[i][j].upper(), ha='center', va='center', fontsize=32, color='white')\n",
    "\n",
    "    # Highlight the time\n",
    "    if not None in [hours, minutes, words]:\n",
    "        # Highlight the time\n",
    "        time_sentence = time_to_sentence(hours, minutes)\n",
    "        time_sentence = time_sentence.replace(\"-\", \" \")\n",
    "        time_sentence = time_sentence.replace(\"'\", \"\")\n",
    "\n",
    "        time_words = time_sentence.split()\n",
    "        i = 0\n",
    "        for r in range(len(grid)):\n",
    "            for c in range(len(grid[0])):\n",
    "                word_at_loc = word_at_location(words, r, c)\n",
    "                if word_at_loc:\n",
    "                    (_, word, (x, y), (d_x, d_y), _) = word_at_loc\n",
    "                    if i < len(time_words) and time_words[i] == word[:len(time_words[i])]:\n",
    "                        x_values = [x, x + d_x * (len(time_words[i])-1) + 0.01]\n",
    "                        y_values = [y - 0.05, y + d_y * (len(time_words[i])-1) - 0.05]\n",
    "                        ax.plot(x_values, y_values, linewidth=35, solid_capstyle='round', alpha=0.5)\n",
    "                        i += 1\n",
    "    \n",
    "    # Remove the axes ticks\n",
    "    ax.set_xticks([])\n",
    "    ax.set_yticks([])\n",
    "\n",
    "    if fig:\n",
    "        fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "488e1c88-e6f3-4c09-baba-c96d49e58772",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_grid(g, w, 4, 14)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b44be42c-8d43-4306-a72f-91aa5bff2e1e",
   "metadata": {},
   "source": [
    "## Saving images to file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e11e036e-b0d0-4db2-8769-32e41c96decb",
   "metadata": {},
   "outputs": [],
   "source": [
    "output_directory = 'images'\n",
    "os.makedirs(output_directory, exist_ok=True)\n",
    "\n",
    "for h in range(12):\n",
    "    for m in range(60):\n",
    "        plot_grid(g, w, h, m)\n",
    "        file_name = f\"time_{h:02d}_{m:02d}.jpg\"\n",
    "        file_path = os.path.join(output_directory, file_name)\n",
    "        plt.savefig(file_path, bbox_inches='tight')\n",
    "        plt.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cbb1e5f7-21ca-428f-8e5c-96828818c5d4",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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