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     "start_time": "2025-03-21T10:15:10.163120Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from src.models import KeypadSize\n",
    "from src.user_keypad import UserKeypad\n",
    "from src.utils import keypad_md_table\n",
    "import numpy as np\n",
    "from IPython.display import Markdown, display"
   ],
   "id": "1f073371d04d02ef",
   "outputs": [],
   "execution_count": 37
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "## Keypad Split Shuffle\n",
    "\n",
    "The split shuffle algorithm aims to increase the number of observations required to decipher an nKode.\n",
    "For more details, refer to the [Evil nKode](https://github.com/Arcanum-Technology/evil-nkode).\n",
    "\n",
    "The positions of the keypad properties are divided into two sets, with each set being shuffled collectively to form a new key."
   ],
   "id": "651d7d661f4128d"
  },
  {
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-03-21T10:15:10.177990Z",
     "start_time": "2025-03-21T10:15:10.172547Z"
    }
   },
   "cell_type": "code",
   "source": [
    "keypad_size = KeypadSize(numb_of_keys=5, props_per_key=4)\n",
    "props = [1, 10, 11, 100]\n",
    "keypad_list = []\n",
    "for key_numb in range(1,keypad_size.numb_of_keys+1):\n",
    "    keypad_list.extend([key_numb * prop for prop in props])\n",
    "\n",
    "user_keypad = UserKeypad(keypad_size=keypad_size, keypad=np.array(keypad_list))\n",
    "display(Markdown(f\"\"\"\n",
    "## Example Keypad\n",
    "{keypad_size.numb_of_keys} X {keypad_size.props_per_key} keypad ({keypad_size.numb_of_keys} keys, {keypad_size.props_per_key} properties per key).\n",
    "\"\"\"))\n",
    "keypad_mat = user_keypad.keypad_matrix()\n",
    "display(Markdown(keypad_md_table(user_keypad.keypad, keypad_size)))"
   ],
   "id": "initial_id",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ],
      "text/markdown": "\n## Example Keypad\n5 X 4 keypad (5 keys, 4 properties per key).\n"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ],
      "text/markdown": "||position 0|position 1|position 2|position 3|\n|-|-|-|-|-|\n|key 0|1|10|11|100|\n|key 1|2|20|22|200|\n|key 2|3|30|33|300|\n|key 3|4|40|44|400|\n|key 4|5|50|55|500|"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 38
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-21T10:15:10.187564Z",
     "start_time": "2025-03-21T10:15:10.184075Z"
    }
   },
   "cell_type": "code",
   "source": [
    "np.random.shuffle(keypad_mat)\n",
    "display(Markdown(\"\"\"\n",
    "### Step 1\n",
    "\n",
    "Shuffle the keys\n",
    "\"\"\"\n",
    "))\n",
    "display(Markdown(keypad_md_table(keypad_mat.reshape(-1), keypad_size)))"
   ],
   "id": "43db2b9d247f420d",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ],
      "text/markdown": "\n### Step 1\n\nShuffle the keys\n"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ],
      "text/markdown": "||position 0|position 1|position 2|position 3|\n|-|-|-|-|-|\n|key 0|1|10|11|100|\n|key 1|3|30|33|300|\n|key 2|2|20|22|200|\n|key 3|5|50|55|500|\n|key 4|4|40|44|400|"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 39
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-21T10:15:10.202941Z",
     "start_time": "2025-03-21T10:15:10.198267Z"
    }
   },
   "cell_type": "code",
   "source": [
    "display(Markdown(\"\"\"\n",
    "### Step 2\n",
    "\n",
    "Choose half of the properties and randomly assign them to a new key as a group, then shuffle this group to another new key.\"\"\"\n",
    "))\n",
    "prop_permutation = np.random.permutation(keypad_size.props_per_key)[: keypad_size.props_per_key // 2]\n",
    "print(f\"Selected Group: {prop_permutation}\")\n",
    "key_permutation = np.random.permutation(keypad_size.numb_of_keys)\n",
    "# shuffle the selected property sets to new keys as a group\n",
    "keypad_mat[:, prop_permutation] = keypad_mat[key_permutation, :][:, prop_permutation]\n",
    "display(Markdown(keypad_md_table(keypad_mat.reshape(-1), keypad_size)))"
   ],
   "id": "8c322a6c074392e6",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ],
      "text/markdown": "\n### Step 2\n\nChoose half of the properties and randomly assign them to a new key as a group, then shuffle this group to another new key."
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selected Group: [2 0]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ],
      "text/markdown": "||position 0|position 1|position 2|position 3|\n|-|-|-|-|-|\n|key 0|2|10|22|100|\n|key 1|4|30|44|300|\n|key 2|1|20|11|200|\n|key 3|5|50|55|500|\n|key 4|3|40|33|400|"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 40
  }
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