ipynb_files/059_Spiral_Matrix_II.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-26T16:10:14.675991Z",
     "start_time": "2019-06-26T16:10:14.673991Z"
    }
   },
   "outputs": [],
   "source": [
    "from IPython.display import display, Image"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Question\n",
    "(https://leetcode.com/problems/spiral-matrix-ii/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-26T16:10:14.699992Z",
     "start_time": "2019-06-26T16:10:14.694991Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(Image('../images/059_Q.PNG'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Solution 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-26T16:10:14.720991Z",
     "start_time": "2019-06-26T16:10:14.716992Z"
    }
   },
   "outputs": [],
   "source": [
    "class Solution:\n",
    "    def generateMatrix(self, n: int):\n",
    "        output = [[0]*n for _ in range(n)]\n",
    "        minRow = 0\n",
    "        maxRow = n - 1\n",
    "        minCol = 0\n",
    "        maxCol = n - 1\n",
    "        value = 0\n",
    "        maxValue = n**2\n",
    "        while True:\n",
    "            for i in range(minCol, maxCol + 1):\n",
    "                value += 1\n",
    "                output[minRow][i] = value\n",
    "            minRow += 1\n",
    "            if value == maxValue:\n",
    "                break\n",
    "            for i in range(minRow, maxRow + 1):\n",
    "                value += 1\n",
    "                output[i][maxCol] = value\n",
    "            maxCol -= 1\n",
    "            if value == maxValue:\n",
    "                break\n",
    "            for i in range(maxCol, minCol - 1, -1):\n",
    "                value += 1\n",
    "                output[maxRow][i] = value\n",
    "            maxRow -= 1\n",
    "            if value == maxValue:\n",
    "                break\n",
    "            for i in range(maxRow, minRow - 1, -1):\n",
    "                value += 1\n",
    "                output[i][minCol] = value\n",
    "            minCol += 1\n",
    "            if value == maxValue:\n",
    "                break\n",
    "        return output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-26T16:10:14.728993Z",
     "start_time": "2019-06-26T16:10:14.726992Z"
    }
   },
   "outputs": [],
   "source": [
    "s = Solution()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-26T16:10:14.736992Z",
     "start_time": "2019-06-26T16:10:14.729992Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[1, 2, 3], [8, 9, 4], [7, 6, 5]]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.generateMatrix(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### submit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-26T16:10:14.745992Z",
     "start_time": "2019-06-26T16:10:14.740992Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(Image('../images/059_S1.PNG'))"
   ]
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  },
  "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": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "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
}