{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "34932fcf",
   "metadata": {},
   "source": [
    "## Tutorial\n",
    "\n",
    "This guide can help you start working with NetworkX.\n",
    "\n",
    "### Creating a graph\n",
    "\n",
    "Create an empty graph with no nodes and no edges."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cd473e7d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.528300Z",
     "iopub.status.busy": "2023-02-27T20:27:40.528094Z",
     "iopub.status.idle": "2023-02-27T20:27:40.596239Z",
     "shell.execute_reply": "2023-02-27T20:27:40.595599Z"
    }
   },
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "G = nx.Graph()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ec0c903",
   "metadata": {},
   "source": [
    "By definition, a `Graph` is a collection of nodes (vertices) along with\n",
    "identified pairs of nodes (called edges, links, etc).  In NetworkX, nodes can\n",
    "be any [hashable](https://docs.python.org/3/glossary.html#term-hashable) object e.g., a text string, an image, an XML object,\n",
    "another Graph, a customized node object, etc.\n",
    "\n",
    "# Nodes\n",
    "\n",
    "The graph `G` can be grown in several ways.  NetworkX includes many\n",
    "graph generator functions and\n",
    "facilities to read and write graphs in many formats.\n",
    "To get started though we’ll look at simple manipulations.  You can add one node\n",
    "at a time,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e41d4029",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.599589Z",
     "iopub.status.busy": "2023-02-27T20:27:40.599053Z",
     "iopub.status.idle": "2023-02-27T20:27:40.602634Z",
     "shell.execute_reply": "2023-02-27T20:27:40.602047Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_node(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66c6ec7a",
   "metadata": {},
   "source": [
    "or add nodes from any [iterable](https://docs.python.org/3/glossary.html#term-iterable) container, such as a list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "69712d73",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.605279Z",
     "iopub.status.busy": "2023-02-27T20:27:40.604967Z",
     "iopub.status.idle": "2023-02-27T20:27:40.608511Z",
     "shell.execute_reply": "2023-02-27T20:27:40.607962Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_nodes_from([2, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb7b2f97",
   "metadata": {},
   "source": [
    "You can also add nodes along with node\n",
    "attributes if your container yields 2-tuples of the form\n",
    "`(node, node_attribute_dict)`:\n",
    "\n",
    "```\n",
    ">>> G.add_nodes_from([\n",
    "...     (4, {\"color\": \"red\"}),\n",
    "...     (5, {\"color\": \"green\"}),\n",
    "... ])\n",
    "```\n",
    "\n",
    "Node attributes are discussed further below.\n",
    "\n",
    "Nodes from one graph can be incorporated into another:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1c7f7b4d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.611052Z",
     "iopub.status.busy": "2023-02-27T20:27:40.610595Z",
     "iopub.status.idle": "2023-02-27T20:27:40.615441Z",
     "shell.execute_reply": "2023-02-27T20:27:40.614890Z"
    }
   },
   "outputs": [],
   "source": [
    "H = nx.path_graph(10)\n",
    "G.add_nodes_from(H)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5cdb5f87",
   "metadata": {},
   "source": [
    "`G` now contains the nodes of `H` as nodes of `G`.\n",
    "In contrast, you could use the graph `H` as a node in `G`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "13fe2579",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.617703Z",
     "iopub.status.busy": "2023-02-27T20:27:40.617382Z",
     "iopub.status.idle": "2023-02-27T20:27:40.620969Z",
     "shell.execute_reply": "2023-02-27T20:27:40.620415Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_node(H)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "667e7ee1",
   "metadata": {},
   "source": [
    "The graph `G` now contains `H` as a node.  This flexibility is very powerful as\n",
    "it allows graphs of graphs, graphs of files, graphs of functions and much more.\n",
    "It is worth thinking about how to structure your application so that the nodes\n",
    "are useful entities.  Of course you can always use a unique identifier in `G`\n",
    "and have a separate dictionary keyed by identifier to the node information if\n",
    "you prefer.\n",
    "\n",
    "# Edges\n",
    "\n",
    "`G` can also be grown by adding one edge at a time,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8f1ea633",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.623172Z",
     "iopub.status.busy": "2023-02-27T20:27:40.622861Z",
     "iopub.status.idle": "2023-02-27T20:27:40.626764Z",
     "shell.execute_reply": "2023-02-27T20:27:40.626180Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_edge(1, 2)\n",
    "e = (2, 3)\n",
    "G.add_edge(*e)  # unpack edge tuple*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afd13aa3",
   "metadata": {},
   "source": [
    "by adding a list of edges,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b255bc0a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.629297Z",
     "iopub.status.busy": "2023-02-27T20:27:40.628978Z",
     "iopub.status.idle": "2023-02-27T20:27:40.632067Z",
     "shell.execute_reply": "2023-02-27T20:27:40.631473Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_edges_from([(1, 2), (1, 3)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f7607ce",
   "metadata": {},
   "source": [
    "or by adding any ebunch of edges.  An *ebunch* is any iterable\n",
    "container of edge-tuples.  An edge-tuple can be a 2-tuple of nodes or a 3-tuple\n",
    "with 2 nodes followed by an edge attribute dictionary, e.g.,\n",
    "`(2, 3, {'weight': 3.1415})`.  Edge attributes are discussed further\n",
    "below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e8759a73",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.634273Z",
     "iopub.status.busy": "2023-02-27T20:27:40.633938Z",
     "iopub.status.idle": "2023-02-27T20:27:40.636894Z",
     "shell.execute_reply": "2023-02-27T20:27:40.636314Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_edges_from(H.edges)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e55e991c",
   "metadata": {},
   "source": [
    "There are no complaints when adding existing nodes or edges. For example,\n",
    "after removing all nodes and edges,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "721e72aa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.639281Z",
     "iopub.status.busy": "2023-02-27T20:27:40.638778Z",
     "iopub.status.idle": "2023-02-27T20:27:40.641711Z",
     "shell.execute_reply": "2023-02-27T20:27:40.641149Z"
    }
   },
   "outputs": [],
   "source": [
    "G.clear()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "785468a4",
   "metadata": {},
   "source": [
    "we add new nodes/edges and NetworkX quietly ignores any that are\n",
    "already present."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bbd2a149",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.644442Z",
     "iopub.status.busy": "2023-02-27T20:27:40.643992Z",
     "iopub.status.idle": "2023-02-27T20:27:40.648254Z",
     "shell.execute_reply": "2023-02-27T20:27:40.647710Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_edges_from([(1, 2), (1, 3)])\n",
    "G.add_node(1)\n",
    "G.add_edge(1, 2)\n",
    "G.add_node(\"spam\")        # adds node \"spam\"\n",
    "G.add_nodes_from(\"spam\")  # adds 4 nodes: 's', 'p', 'a', 'm'\n",
    "G.add_edge(3, 'm')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7ab412e",
   "metadata": {},
   "source": [
    "At this stage the graph `G` consists of 8 nodes and 3 edges, as can be seen by:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "cca6ffec",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.650870Z",
     "iopub.status.busy": "2023-02-27T20:27:40.650444Z",
     "iopub.status.idle": "2023-02-27T20:27:40.658394Z",
     "shell.execute_reply": "2023-02-27T20:27:40.657842Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.number_of_nodes()\n",
    "G.number_of_edges()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "eb8820e7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.660970Z",
     "iopub.status.busy": "2023-02-27T20:27:40.660543Z",
     "iopub.status.idle": "2023-02-27T20:27:40.665296Z",
     "shell.execute_reply": "2023-02-27T20:27:40.664752Z"
    }
   },
   "outputs": [],
   "source": [
    "DG = nx.DiGraph()\n",
    "DG.add_edge(2, 1)   # adds the nodes in order 2, 1\n",
    "DG.add_edge(1, 3)\n",
    "DG.add_edge(2, 4)\n",
    "DG.add_edge(1, 2)\n",
    "assert list(DG.successors(2)) == [1, 4]\n",
    "assert list(DG.edges) == [(2, 1), (2, 4), (1, 3), (1, 2)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5eece4bf",
   "metadata": {},
   "source": [
    "# Examining elements of a graph\n",
    "\n",
    "We can examine the nodes and edges. Four basic graph properties facilitate\n",
    "reporting: `G.nodes`, `G.edges`, `G.adj` and `G.degree`.  These\n",
    "are set-like views of the nodes, edges, neighbors (adjacencies), and degrees\n",
    "of nodes in a graph. They offer a continually updated read-only view into\n",
    "the graph structure. They are also dict-like in that you can look up node\n",
    "and edge data attributes via the views and iterate with data attributes\n",
    "using methods `.items()`, `.data()`.\n",
    "If you want a specific container type instead of a view, you can specify one.\n",
    "Here we use lists, though sets, dicts, tuples and other containers may be\n",
    "better in other contexts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "600d36b9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.667912Z",
     "iopub.status.busy": "2023-02-27T20:27:40.667490Z",
     "iopub.status.idle": "2023-02-27T20:27:40.672152Z",
     "shell.execute_reply": "2023-02-27T20:27:40.671547Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(G.nodes)\n",
    "list(G.edges)\n",
    "list(G.adj[1])  # or list(G.neighbors(1))\n",
    "G.degree[1]  # the number of edges incident to 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb62ccb2",
   "metadata": {},
   "source": [
    "One can specify to report the edges and degree from a subset of all nodes\n",
    "using an nbunch. An *nbunch* is any of: `None` (meaning all nodes),\n",
    "a node, or an iterable container of nodes that is not itself a node in the\n",
    "graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "02948235",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.674518Z",
     "iopub.status.busy": "2023-02-27T20:27:40.674209Z",
     "iopub.status.idle": "2023-02-27T20:27:40.680311Z",
     "shell.execute_reply": "2023-02-27T20:27:40.679397Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DegreeView({2: 1, 3: 2})"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.edges([2, 'm'])\n",
    "G.degree([2, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0da2d03",
   "metadata": {},
   "source": [
    "# Removing elements from a graph\n",
    "\n",
    "One can remove nodes and edges from the graph in a similar fashion to adding.\n",
    "Use methods\n",
    "`Graph.remove_node()`,\n",
    "`Graph.remove_nodes_from()`,\n",
    "`Graph.remove_edge()`\n",
    "and\n",
    "`Graph.remove_edges_from()`, e.g."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "16a7ac54",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.682683Z",
     "iopub.status.busy": "2023-02-27T20:27:40.682380Z",
     "iopub.status.idle": "2023-02-27T20:27:40.686391Z",
     "shell.execute_reply": "2023-02-27T20:27:40.685850Z"
    }
   },
   "outputs": [],
   "source": [
    "G.remove_node(2)\n",
    "G.remove_nodes_from(\"spam\")\n",
    "list(G.nodes)\n",
    "G.remove_edge(1, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ad77ea0",
   "metadata": {},
   "source": [
    "# Using the graph constructors\n",
    "\n",
    "Graph objects do not have to be built up incrementally - data specifying\n",
    "graph structure can be passed directly to the constructors of the various\n",
    "graph classes.\n",
    "When creating a graph structure by instantiating one of the graph\n",
    "classes you can specify data in several formats."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3a4f5043",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.688803Z",
     "iopub.status.busy": "2023-02-27T20:27:40.688587Z",
     "iopub.status.idle": "2023-02-27T20:27:40.932822Z",
     "shell.execute_reply": "2023-02-27T20:27:40.931861Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 1), (0, 2), (1, 2)]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.add_edge(1, 2)\n",
    "H = nx.DiGraph(G)  # create a DiGraph using the connections from G\n",
    "list(H.edges())\n",
    "edgelist = [(0, 1), (1, 2), (2, 3)]\n",
    "H = nx.Graph(edgelist)  # create a graph from an edge list\n",
    "list(H.edges())\n",
    "adjacency_dict = {0: (1, 2), 1: (0, 2), 2: (0, 1)}\n",
    "H = nx.Graph(adjacency_dict)  # create a Graph dict mapping nodes to nbrs\n",
    "list(H.edges())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d561f022",
   "metadata": {},
   "source": [
    "# What to use as nodes and edges\n",
    "\n",
    "You might notice that nodes and edges are not specified as NetworkX\n",
    "objects.  This leaves you free to use meaningful items as nodes and\n",
    "edges. The most common choices are numbers or strings, but a node can\n",
    "be any hashable object (except `None`), and an edge can be associated\n",
    "with any object `x` using `G.add_edge(n1, n2, object=x)`.\n",
    "\n",
    "As an example, `n1` and `n2` could be protein objects from the RCSB Protein\n",
    "Data Bank, and `x` could refer to an XML record of publications detailing\n",
    "experimental observations of their interaction.\n",
    "\n",
    "We have found this power quite useful, but its abuse\n",
    "can lead to surprising behavior unless one is familiar with Python.\n",
    "If in doubt, consider using `convert_node_labels_to_integers()` to obtain\n",
    "a more traditional graph with integer labels.\n",
    "\n",
    "# Accessing edges and neighbors\n",
    "\n",
    "In addition to the views `Graph.edges`, and `Graph.adj`,\n",
    "access to edges and neighbors is possible using subscript notation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "258013e9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.935659Z",
     "iopub.status.busy": "2023-02-27T20:27:40.935133Z",
     "iopub.status.idle": "2023-02-27T20:27:40.941431Z",
     "shell.execute_reply": "2023-02-27T20:27:40.940892Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'color': 'yellow'}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G = nx.Graph([(1, 2, {\"color\": \"yellow\"})])\n",
    "G[1]  # same as G.adj[1]\n",
    "G[1][2]\n",
    "G.edges[1, 2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de58f6ba",
   "metadata": {},
   "source": [
    "You can get/set the attributes of an edge using subscript notation\n",
    "if the edge already exists."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b8ca122e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.943951Z",
     "iopub.status.busy": "2023-02-27T20:27:40.943626Z",
     "iopub.status.idle": "2023-02-27T20:27:40.948291Z",
     "shell.execute_reply": "2023-02-27T20:27:40.947682Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'color': 'red'}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.add_edge(1, 3)\n",
    "G[1][3]['color'] = \"blue\"\n",
    "G.edges[1, 2]['color'] = \"red\"\n",
    "G.edges[1, 2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d44fd70",
   "metadata": {},
   "source": [
    "Fast examination of all (node, adjacency) pairs is achieved using\n",
    "`G.adjacency()`, or `G.adj.items()`.\n",
    "Note that for undirected graphs, adjacency iteration sees each edge twice."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "edf3809c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.950906Z",
     "iopub.status.busy": "2023-02-27T20:27:40.950585Z",
     "iopub.status.idle": "2023-02-27T20:27:40.955410Z",
     "shell.execute_reply": "2023-02-27T20:27:40.954775Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 2, 0.125)\n",
      "(2, 1, 0.125)\n",
      "(3, 4, 0.375)\n",
      "(4, 3, 0.375)\n"
     ]
    }
   ],
   "source": [
    "FG = nx.Graph()\n",
    "FG.add_weighted_edges_from([(1, 2, 0.125), (1, 3, 0.75), (2, 4, 1.2), (3, 4, 0.375)])\n",
    "for n, nbrs in FG.adj.items():\n",
    "   for nbr, eattr in nbrs.items():\n",
    "       wt = eattr['weight']\n",
    "       if wt < 0.5: print(f\"({n}, {nbr}, {wt:.3})\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4de66c10",
   "metadata": {},
   "source": [
    "Convenient access to all edges is achieved with the edges property."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4cd1760c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.958302Z",
     "iopub.status.busy": "2023-02-27T20:27:40.957799Z",
     "iopub.status.idle": "2023-02-27T20:27:40.961577Z",
     "shell.execute_reply": "2023-02-27T20:27:40.960948Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 2, 0.125)\n",
      "(3, 4, 0.375)\n"
     ]
    }
   ],
   "source": [
    "for (u, v, wt) in FG.edges.data('weight'):\n",
    "    if wt < 0.5:\n",
    "        print(f\"({u}, {v}, {wt:.3})\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eba6152a",
   "metadata": {},
   "source": [
    "# Adding attributes to graphs, nodes, and edges\n",
    "\n",
    "Attributes such as weights, labels, colors, or whatever Python object you like,\n",
    "can be attached to graphs, nodes, or edges.\n",
    "\n",
    "Each graph, node, and edge can hold key/value attribute pairs in an associated\n",
    "attribute dictionary (the keys must be hashable).  By default these are empty,\n",
    "but attributes can be added or changed using `add_edge`, `add_node` or direct\n",
    "manipulation of the attribute dictionaries named `G.graph`, `G.nodes`, and\n",
    "`G.edges` for a graph `G`.\n",
    "\n",
    "## Graph attributes\n",
    "\n",
    "Assign graph attributes when creating a new graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "65e41d33",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.964233Z",
     "iopub.status.busy": "2023-02-27T20:27:40.963907Z",
     "iopub.status.idle": "2023-02-27T20:27:40.968043Z",
     "shell.execute_reply": "2023-02-27T20:27:40.967444Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'day': 'Friday'}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G = nx.Graph(day=\"Friday\")\n",
    "G.graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8900dcd",
   "metadata": {},
   "source": [
    "Or you can modify attributes later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4aed51f0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.970602Z",
     "iopub.status.busy": "2023-02-27T20:27:40.970274Z",
     "iopub.status.idle": "2023-02-27T20:27:40.974394Z",
     "shell.execute_reply": "2023-02-27T20:27:40.973773Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'day': 'Monday'}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.graph['day'] = \"Monday\"\n",
    "G.graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1ae5957",
   "metadata": {},
   "source": [
    "# Node attributes\n",
    "\n",
    "Add node attributes using `add_node()`, `add_nodes_from()`, or `G.nodes`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "41e0f958",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.977128Z",
     "iopub.status.busy": "2023-02-27T20:27:40.976662Z",
     "iopub.status.idle": "2023-02-27T20:27:40.981552Z",
     "shell.execute_reply": "2023-02-27T20:27:40.980937Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NodeDataView({1: {'time': '5pm', 'room': 714}, 3: {'time': '2pm'}})"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.add_node(1, time='5pm')\n",
    "G.add_nodes_from([3], time='2pm')\n",
    "G.nodes[1]\n",
    "G.nodes[1]['room'] = 714\n",
    "G.nodes.data()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d1541aa",
   "metadata": {},
   "source": [
    "Note that adding a node to `G.nodes` does not add it to the graph, use\n",
    "`G.add_node()` to add new nodes. Similarly for edges.\n",
    "\n",
    "# Edge Attributes\n",
    "\n",
    "Add/change edge attributes using `add_edge()`, `add_edges_from()`,\n",
    "or subscript notation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "405ad7d8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.984007Z",
     "iopub.status.busy": "2023-02-27T20:27:40.983681Z",
     "iopub.status.idle": "2023-02-27T20:27:40.988411Z",
     "shell.execute_reply": "2023-02-27T20:27:40.987852Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_edge(1, 2, weight=4.7 )\n",
    "G.add_edges_from([(3, 4), (4, 5)], color='red')\n",
    "G.add_edges_from([(1, 2, {'color': 'blue'}), (2, 3, {'weight': 8})])\n",
    "G[1][2]['weight'] = 4.7\n",
    "G.edges[3, 4]['weight'] = 4.2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89ae6128",
   "metadata": {},
   "source": [
    "The special attribute `weight` should be numeric as it is used by\n",
    "algorithms requiring weighted edges.\n",
    "\n",
    " Directed graphs\n",
    "\n",
    "The `DiGraph` class provides additional methods and properties specific\n",
    "to directed edges, e.g.,\n",
    "`DiGraph.out_edges`, `DiGraph.in_degree`,\n",
    "`DiGraph.predecessors`, `DiGraph.successors` etc.\n",
    "To allow algorithms to work with both classes easily, the directed versions of\n",
    "`neighbors` is equivalent to\n",
    "`successors` while `degree` reports the sum\n",
    "of `in_degree` and `out_degree` even though that may feel inconsistent at times."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f1a70f53",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.991045Z",
     "iopub.status.busy": "2023-02-27T20:27:40.990608Z",
     "iopub.status.idle": "2023-02-27T20:27:40.995950Z",
     "shell.execute_reply": "2023-02-27T20:27:40.995337Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DG = nx.DiGraph()\n",
    "DG.add_weighted_edges_from([(1, 2, 0.5), (3, 1, 0.75)])\n",
    "DG.out_degree(1, weight='weight')\n",
    "DG.degree(1, weight='weight')\n",
    "list(DG.successors(1))\n",
    "list(DG.neighbors(1))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31d5f5b3",
   "metadata": {},
   "source": [
    "Some algorithms work only for directed graphs and others are not well\n",
    "defined for directed graphs.  Indeed the tendency to lump directed\n",
    "and undirected graphs together is dangerous.  If you want to treat\n",
    "a directed graph as undirected for some measurement you should probably\n",
    "convert it using `Graph.to_undirected()` or with"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a917af82",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:40.998446Z",
     "iopub.status.busy": "2023-02-27T20:27:40.998241Z",
     "iopub.status.idle": "2023-02-27T20:27:41.001360Z",
     "shell.execute_reply": "2023-02-27T20:27:41.000754Z"
    }
   },
   "outputs": [],
   "source": [
    "H = nx.Graph(G)  # create an undirected graph H from a directed graph G"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88026fea",
   "metadata": {},
   "source": [
    "# Multigraphs\n",
    "\n",
    "NetworkX provides classes for graphs which allow multiple edges\n",
    "between any pair of nodes.  The `MultiGraph` and\n",
    "`MultiDiGraph`\n",
    "classes allow you to add the same edge twice, possibly with different\n",
    "edge data.  This can be powerful for some applications, but many\n",
    "algorithms are not well defined on such graphs.\n",
    "Where results are well defined,\n",
    "e.g., `MultiGraph.degree()` we provide the function.  Otherwise you\n",
    "should convert to a standard graph in a way that makes the measurement\n",
    "well defined."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "057492be",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:41.003642Z",
     "iopub.status.busy": "2023-02-27T20:27:41.003329Z",
     "iopub.status.idle": "2023-02-27T20:27:41.009737Z",
     "shell.execute_reply": "2023-02-27T20:27:41.009124Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MG = nx.MultiGraph()\n",
    "MG.add_weighted_edges_from([(1, 2, 0.5), (1, 2, 0.75), (2, 3, 0.5)])\n",
    "dict(MG.degree(weight='weight'))\n",
    "GG = nx.Graph()\n",
    "for n, nbrs in MG.adjacency():\n",
    "   for nbr, edict in nbrs.items():\n",
    "       minvalue = min([d['weight'] for d in edict.values()])\n",
    "       GG.add_edge(n, nbr, weight = minvalue)\n",
    "\n",
    "nx.shortest_path(GG, 1, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a884bc8b",
   "metadata": {},
   "source": [
    "# Graph generators and graph operations\n",
    "\n",
    "In addition to constructing graphs node-by-node or edge-by-edge, they\n",
    "can also be generated by\n",
    "\n",
    "## 1. Applying classic graph operations, such as:\n",
    "\n",
    "## 2. Using a call to one of the classic small graphs, e.g.,\n",
    "\n",
    "## 3. Using a (constructive) generator for a classic graph, e.g.,\n",
    "\n",
    "like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7d6536ed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:41.012449Z",
     "iopub.status.busy": "2023-02-27T20:27:41.011965Z",
     "iopub.status.idle": "2023-02-27T20:27:41.016263Z",
     "shell.execute_reply": "2023-02-27T20:27:41.015647Z"
    }
   },
   "outputs": [],
   "source": [
    "K_5 = nx.complete_graph(5)\n",
    "K_3_5 = nx.complete_bipartite_graph(3, 5)\n",
    "barbell = nx.barbell_graph(10, 10)\n",
    "lollipop = nx.lollipop_graph(10, 20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae1c1e80",
   "metadata": {},
   "source": [
    "# 4. Using a stochastic graph generator, e.g,\n",
    "\n",
    "like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e79c3dcf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:41.018707Z",
     "iopub.status.busy": "2023-02-27T20:27:41.018379Z",
     "iopub.status.idle": "2023-02-27T20:27:41.040762Z",
     "shell.execute_reply": "2023-02-27T20:27:41.040170Z"
    }
   },
   "outputs": [],
   "source": [
    "er = nx.erdos_renyi_graph(100, 0.15)\n",
    "ws = nx.watts_strogatz_graph(30, 3, 0.1)\n",
    "ba = nx.barabasi_albert_graph(100, 5)\n",
    "red = nx.random_lobster(100, 0.9, 0.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae0d8913",
   "metadata": {},
   "source": [
    "# 5. Reading a graph stored in a file using common graph formats\n",
    "\n",
    "NetworkX supports many popular formats, such as edge lists, adjacency lists,\n",
    "GML, GraphML, LEDA and others."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "1e573388",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:41.043148Z",
     "iopub.status.busy": "2023-02-27T20:27:41.042833Z",
     "iopub.status.idle": "2023-02-27T20:27:41.854636Z",
     "shell.execute_reply": "2023-02-27T20:27:41.854019Z"
    }
   },
   "outputs": [],
   "source": [
    "nx.write_gml(red, \"path.to.file\")\n",
    "mygraph = nx.read_gml(\"path.to.file\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "408a62d1",
   "metadata": {},
   "source": [
    "For details on graph formats see Reading and writing graphs\n",
    "and for graph generator functions see Graph generators\n",
    "\n",
    " Analyzing graphs\n",
    "\n",
    "The structure of `G` can be analyzed using various graph-theoretic\n",
    "functions such as:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e34295a8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:41.857733Z",
     "iopub.status.busy": "2023-02-27T20:27:41.857489Z",
     "iopub.status.idle": "2023-02-27T20:27:41.864641Z",
     "shell.execute_reply": "2023-02-27T20:27:41.864067Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: 0, 2: 0, 3: 0, 'spam': 0}"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G = nx.Graph()\n",
    "G.add_edges_from([(1, 2), (1, 3)])\n",
    "G.add_node(\"spam\")       # adds node \"spam\"\n",
    "list(nx.connected_components(G))\n",
    "sorted(d for n, d in G.degree())\n",
    "nx.clustering(G)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a61c4b28",
   "metadata": {},
   "source": [
    "Some functions with large output iterate over (node, value) 2-tuples.\n",
    "These are easily stored in a [dict](https://docs.python.org/3/library/stdtypes.html#dict) structure if you desire."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "3a801a03",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:41.867044Z",
     "iopub.status.busy": "2023-02-27T20:27:41.866709Z",
     "iopub.status.idle": "2023-02-27T20:27:41.871794Z",
     "shell.execute_reply": "2023-02-27T20:27:41.871210Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{3: [3], 1: [3, 1], 2: [3, 1, 2]}"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sp = dict(nx.all_pairs_shortest_path(G))\n",
    "sp[3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffc65f46",
   "metadata": {},
   "source": [
    "See Algorithms for details on graph algorithms\n",
    "supported.\n",
    "\n",
    "# Drawing graphs\n",
    "\n",
    "NetworkX is not primarily a graph drawing package but basic drawing with\n",
    "Matplotlib as well as an interface to use the open source Graphviz software\n",
    "package are included.  These are part of the networkx.drawing\n",
    "module and will be imported if possible.\n",
    "\n",
    "First import Matplotlib’s plot interface (pylab works too)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e9d65ba2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:41.874033Z",
     "iopub.status.busy": "2023-02-27T20:27:41.873712Z",
     "iopub.status.idle": "2023-02-27T20:27:42.227907Z",
     "shell.execute_reply": "2023-02-27T20:27:42.227231Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7785478f",
   "metadata": {},
   "source": [
    "To test if the import of `nx_pylab` was successful draw `G`\n",
    "using one of"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "96c82e83",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:42.231373Z",
     "iopub.status.busy": "2023-02-27T20:27:42.230727Z",
     "iopub.status.idle": "2023-02-27T20:27:42.454194Z",
     "shell.execute_reply": "2023-02-27T20:27:42.453572Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G = nx.petersen_graph()\n",
    "subax1 = plt.subplot(121)\n",
    "nx.draw(G, with_labels=True, font_weight='bold')\n",
    "subax2 = plt.subplot(122)\n",
    "nx.draw_shell(G, nlist=[range(5, 10), range(5)], with_labels=True, font_weight='bold')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9852dd9d",
   "metadata": {},
   "source": [
    "when drawing to an interactive display.  Note that you may need to issue a\n",
    "Matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a9969348",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:42.457029Z",
     "iopub.status.busy": "2023-02-27T20:27:42.456673Z",
     "iopub.status.idle": "2023-02-27T20:27:42.459812Z",
     "shell.execute_reply": "2023-02-27T20:27:42.459197Z"
    }
   },
   "outputs": [],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c87db54f",
   "metadata": {},
   "source": [
    "command if you are not using matplotlib in interactive mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0f6044ed",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:42.462361Z",
     "iopub.status.busy": "2023-02-27T20:27:42.461903Z",
     "iopub.status.idle": "2023-02-27T20:27:42.785906Z",
     "shell.execute_reply": "2023-02-27T20:27:42.785191Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "options = {\n",
    "    'node_color': 'black',\n",
    "    'node_size': 100,\n",
    "    'width': 3,\n",
    "}\n",
    "subax1 = plt.subplot(221)\n",
    "nx.draw_random(G, **options)\n",
    "subax2 = plt.subplot(222)\n",
    "nx.draw_circular(G, **options)\n",
    "subax3 = plt.subplot(223)\n",
    "nx.draw_spectral(G, **options)\n",
    "subax4 = plt.subplot(224)\n",
    "nx.draw_shell(G, nlist=[range(5,10), range(5)], **options)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9538900",
   "metadata": {},
   "source": [
    "You can find additional options via `draw_networkx()` and\n",
    "layouts via the `layout module`.\n",
    "You can use multiple shells with `draw_shell()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "3d0ed48a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:42.789077Z",
     "iopub.status.busy": "2023-02-27T20:27:42.788559Z",
     "iopub.status.idle": "2023-02-27T20:27:42.905981Z",
     "shell.execute_reply": "2023-02-27T20:27:42.905345Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G = nx.dodecahedral_graph()\n",
    "shells = [[2, 3, 4, 5, 6], [8, 1, 0, 19, 18, 17, 16, 15, 14, 7], [9, 10, 11, 12, 13]]\n",
    "nx.draw_shell(G, nlist=shells, **options)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71d93c4e",
   "metadata": {},
   "source": [
    "To save drawings to a file, use, for example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "61c0860c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:42.908903Z",
     "iopub.status.busy": "2023-02-27T20:27:42.908462Z",
     "iopub.status.idle": "2023-02-27T20:27:43.055706Z",
     "shell.execute_reply": "2023-02-27T20:27:43.055067Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nx.draw(G)\n",
    "plt.savefig(\"path.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b386763c",
   "metadata": {},
   "source": [
    "This function writes to the file `path.png` in the local directory. If Graphviz and\n",
    "PyGraphviz or pydot, are available on your system, you can also use\n",
    "`networkx.drawing.nx_agraph.graphviz_layout` or\n",
    "`networkx.drawing.nx_pydot.graphviz_layout` to get the node positions, or write\n",
    "the graph in dot format for further processing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "03e31283",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-27T20:27:43.058591Z",
     "iopub.status.busy": "2023-02-27T20:27:43.058255Z",
     "iopub.status.idle": "2023-02-27T20:27:43.204812Z",
     "shell.execute_reply": "2023-02-27T20:27:43.204169Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from networkx.drawing.nx_pydot import write_dot\n",
    "pos = nx.nx_agraph.graphviz_layout(G)\n",
    "nx.draw(G, pos=pos)\n",
    "write_dot(G, 'file.dot')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8d17590",
   "metadata": {},
   "source": [
    "See Drawing for additional details.\n",
    "\n",
    "# NX-Guides\n",
    "\n",
    "If you are interested in learning more about NetworkX, graph theory and network analysis\n",
    "then you should check out [nx-guides](https://networkx.org/nx-guides/index.html). There you can find tutorials,\n",
    "real-world applications and in-depth examinations of graphs and network algorithms.\n",
    "All the material is official and was developed and curated by the NetworkX community."
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}