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Author: EvanLi

常见算法/图 DFS BFS.ipynb renamed to 常见算法/图-深度优先搜索DFS-广度优先搜索BFS.ipynb

@@ -30,38 +30,49 @@
     "\n",
     " ## [数据结构：图的存储结构之邻接矩阵](https://blog.csdn.net/jnu_simba/article/details/8866705)\n",
     " \n",
-    " 图的邻接矩阵（Adjacency Matrix)存储方式是用两个数组来表示图。一个一维的数组存储图中顶点信息，一个二维数组（称为邻接矩阵）存储图中的边或弧的信息。\n",
+    "图的**邻接矩阵（Adjacency Matrix)**存储方式是用两个数组来表示图。一个一维的数组存储图中顶点信息，一个二维数组（称为邻接矩阵）存储图中的边或弧的信息。\n",
     " \n",
     " 设图G有n个顶点，则邻接矩阵是一个`n*n`的方阵，定义为：\n",
     " \n",
     " ![](https://raw.githubusercontent.com/hostimg/img/gh-pages/s/20190827182144.png)\n",
     " \n",
-    " 无向图:\n",
+    "### 无向图:\n",
     " \n",
     "![](https://raw.githubusercontent.com/hostimg/img/gh-pages/s/20190828160319.png)\n",
     " \n",
-    " 有向图：\n",
+    "### 有向图：\n",
     " \n",
     "![](https://raw.githubusercontent.com/hostimg/img/gh-pages/s/20190828160358.png)\n",
     " \n",
     "\n",
-    "**网：**\n",
+    "## 网\n",
     "\n",
     "在图的术语中，我们提到了网的概念，也就是每条边上都带有权的图叫做网。那些这些权值就需要保存下来。\n",
     "\n",
     "设图G是网图，有n个顶点，则邻接矩阵是一个`n*n`的方阵，定义为：\n",
     "\n",
     "![](https://raw.githubusercontent.com/hostimg/img/gh-pages/s/20190827182537.png)\n",
     "\n",
-    "有向图网：\n",
+    "### 有向图网：\n",
     "\n",
     "![](https://raw.githubusercontent.com/hostimg/img/gh-pages/s/20190828160533.png)\n",
     "\n",
     "## [数据结构：图的存储结构之邻接表](https://blog.csdn.net/jnu_simba/article/details/8866844)\n",
     "\n",
-    "# 深度优先搜索：\n",
+    "# 深度优先搜索（Depth-First-Search，DFS）\n",
     "\n",
-    "　　求连通简单图G的一棵生成树的许多方法中，深度优先搜索（depth first search）是一个十分重要的算法。\n",
+    "求连通简单图G的一棵生成树的许多方法中，深度优先搜索（depth first search）是一个十分重要的算法。\n",
+    "\n",
+    "- 1.首先将根节点放入stack中。\n",
+    "- 2.从stack中取出第一个节点，并检验它是否为目标。\n",
+    "    - 如果找到目标，则结束搜寻并回传结果。\n",
+    "    - 否则将它某一个尚未检验过的直接子节点加入stack中。\n",
+    "- 3.重复步骤2。\n",
+    "- 4.如果不存在未检测过的直接子节点。\n",
+    "    - 将上一级节点加入stack中。\n",
+    "    - 重复步骤2。\n",
+    "- 5.重复步骤4。\n",
+    "- 6.若stack为空，表示整张图都检查过了——亦即图中没有欲搜寻的目标。结束搜寻并回传“找不到目标”。\n",
     "\n",
     "基本思想：\n",
     "\n",
@@ -94,9 +105,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "tf36",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "tf36"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -108,7 +119,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,

常见算法/排序算法总结.ipynb

@@ -62,7 +62,7 @@
     "\n",
     "![](https://raw.githubusercontent.com/hostimg/img/gh-pages/s/20190824130735.png)\n",
     "\n",
-    "**下面是网上流传很广一张图，的这里的快排的空间复杂度应该为$O(logn)$，最坏情况是$O(n)$，而不是$O(nlogn)$**\n",
+    "**下面是网上流传很广一张图，的这里的快排的空间复杂度应该为$O(logn)$，而不是$O(nlogn)$（递归使用的栈空间），空间复杂度最坏情况是$O(n)$**\n",
     "\n",
     "![](https://raw.githubusercontent.com/hostimg/img/gh-pages/s/20190901010247.png)"
    ]
@@ -300,7 +300,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,