/usr/share/doc/python3-networkx/html/tutorial_full.ipynb.gz

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   "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."
   ]
  },
  {
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   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "G = nx.Graph()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b73b74bd",
   "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 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,"
   ]
  },
  {
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   "id": "7dbf94a4",
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   "source": [
    "G.add_node(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2ce24bb",
   "metadata": {},
   "source": [
    "or add nodes from any iterable container, such as a list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "acbeaf93",
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "G.add_nodes_from([2, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0862caf4",
   "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:"
   ]
  },
  {
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   "id": "a635f070",
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   "source": [
    "H = nx.path_graph(10)\n",
    "G.add_nodes_from(H)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5188a6ed",
   "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`."
   ]
  },
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   "source": [
    "G.add_node(H)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abcf8198",
   "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,"
   ]
  },
  {
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   "execution_count": 6,
   "id": "79a3d7dc",
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   "source": [
    "G.add_edge(1, 2)\n",
    "e = (2, 3)\n",
    "G.add_edge(*e)  # unpack edge tuple*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d0ec428",
   "metadata": {},
   "source": [
    "by adding a list of edges,"
   ]
  },
  {
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   "id": "8854e22a",
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   },
   "outputs": [],
   "source": [
    "G.add_edges_from([(1, 2), (1, 3)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "788f57ea",
   "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": "7d57a88e",
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   },
   "outputs": [],
   "source": [
    "G.add_edges_from(H.edges)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f44c213c",
   "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": "4d806769",
   "metadata": {
    "execution": {
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   },
   "outputs": [],
   "source": [
    "G.clear()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fb6da17",
   "metadata": {},
   "source": [
    "we add new nodes/edges and NetworkX quietly ignores any that are\n",
    "already present."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "02181689",
   "metadata": {
    "execution": {
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   "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": "b1142338",
   "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": "5eb98f8f",
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   "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": "16a013ad",
   "metadata": {
    "execution": {
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   },
   "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": "70430150",
   "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": "9987935d",
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    {
     "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": "f1c31b85",
   "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": "9ef00098",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:41.500671Z",
     "iopub.status.busy": "2024-11-26T10:05:41.500292Z",
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     "shell.execute_reply": "2024-11-26T10:05:41.506531Z"
    }
   },
   "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": "55fe73b0",
   "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": "086ff36c",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2024-11-26T10:05:41.514216Z"
    }
   },
   "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": "12647ab7",
   "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": "58589b99",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2024-11-26T10:05:41.983813Z"
    }
   },
   "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": "efdb58e9",
   "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": "e3a435ab",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2024-11-26T10:05:41.994922Z"
    }
   },
   "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": "c91a3192",
   "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": "ab952229",
   "metadata": {
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   "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": "9836089c",
   "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": "31b36edb",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2024-11-26T10:05:42.015150Z"
    }
   },
   "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": "fdddd508",
   "metadata": {},
   "source": [
    "Convenient access to all edges is achieved with the edges property."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f283bec4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.019392Z",
     "iopub.status.busy": "2024-11-26T10:05:42.019028Z",
     "iopub.status.idle": "2024-11-26T10:05:42.024911Z",
     "shell.execute_reply": "2024-11-26T10:05:42.023917Z"
    }
   },
   "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": "a5efdae6",
   "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": "ee7ed819",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.028077Z",
     "iopub.status.busy": "2024-11-26T10:05:42.027730Z",
     "iopub.status.idle": "2024-11-26T10:05:42.034020Z",
     "shell.execute_reply": "2024-11-26T10:05:42.033077Z"
    }
   },
   "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": "af7749e7",
   "metadata": {},
   "source": [
    "Or you can modify attributes later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b3fbfa6c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.037333Z",
     "iopub.status.busy": "2024-11-26T10:05:42.036998Z",
     "iopub.status.idle": "2024-11-26T10:05:42.043582Z",
     "shell.execute_reply": "2024-11-26T10:05:42.042471Z"
    }
   },
   "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": "03bf207c",
   "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": "0c5055f4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.046617Z",
     "iopub.status.busy": "2024-11-26T10:05:42.046282Z",
     "iopub.status.idle": "2024-11-26T10:05:42.052978Z",
     "shell.execute_reply": "2024-11-26T10:05:42.051952Z"
    }
   },
   "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": "dc1dcba1",
   "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": "64f19e7d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.056153Z",
     "iopub.status.busy": "2024-11-26T10:05:42.055819Z",
     "iopub.status.idle": "2024-11-26T10:05:42.061235Z",
     "shell.execute_reply": "2024-11-26T10:05:42.060227Z"
    }
   },
   "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": "22bba0e7",
   "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": "60769aee",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.064165Z",
     "iopub.status.busy": "2024-11-26T10:05:42.063833Z",
     "iopub.status.idle": "2024-11-26T10:05:42.070740Z",
     "shell.execute_reply": "2024-11-26T10:05:42.069745Z"
    }
   },
   "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": "49e9401b",
   "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": "cca93f3b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.073765Z",
     "iopub.status.busy": "2024-11-26T10:05:42.073411Z",
     "iopub.status.idle": "2024-11-26T10:05:42.077556Z",
     "shell.execute_reply": "2024-11-26T10:05:42.076580Z"
    }
   },
   "outputs": [],
   "source": [
    "H = nx.Graph(G)  # create an undirected graph H from a directed graph G"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d396325a",
   "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": "24a87765",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.080598Z",
     "iopub.status.busy": "2024-11-26T10:05:42.080267Z",
     "iopub.status.idle": "2024-11-26T10:05:42.088533Z",
     "shell.execute_reply": "2024-11-26T10:05:42.087505Z"
    }
   },
   "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": "93cae681",
   "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": "8c9af136",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.091534Z",
     "iopub.status.busy": "2024-11-26T10:05:42.091198Z",
     "iopub.status.idle": "2024-11-26T10:05:42.097457Z",
     "shell.execute_reply": "2024-11-26T10:05:42.096454Z"
    }
   },
   "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": "9aabdcc7",
   "metadata": {},
   "source": [
    "# 4. Using a stochastic graph generator, e.g,\n",
    "\n",
    "like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "42c2c71c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.100695Z",
     "iopub.status.busy": "2024-11-26T10:05:42.100364Z",
     "iopub.status.idle": "2024-11-26T10:05:42.121540Z",
     "shell.execute_reply": "2024-11-26T10:05:42.120554Z"
    }
   },
   "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": "0c0821bd",
   "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": "dab5fd95",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.124861Z",
     "iopub.status.busy": "2024-11-26T10:05:42.124529Z",
     "iopub.status.idle": "2024-11-26T10:05:42.490685Z",
     "shell.execute_reply": "2024-11-26T10:05:42.489585Z"
    }
   },
   "outputs": [],
   "source": [
    "nx.write_gml(red, \"path.to.file\")\n",
    "mygraph = nx.read_gml(\"path.to.file\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41f61a35",
   "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": "668f22fd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.494338Z",
     "iopub.status.busy": "2024-11-26T10:05:42.494051Z",
     "iopub.status.idle": "2024-11-26T10:05:42.501546Z",
     "shell.execute_reply": "2024-11-26T10:05:42.500505Z"
    }
   },
   "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": "6417b71f",
   "metadata": {},
   "source": [
    "Some functions with large output iterate over (node, value) 2-tuples.\n",
    "These are easily stored in a `dict` structure if you desire."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "9247b774",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.504835Z",
     "iopub.status.busy": "2024-11-26T10:05:42.504553Z",
     "iopub.status.idle": "2024-11-26T10:05:42.510287Z",
     "shell.execute_reply": "2024-11-26T10:05:42.509300Z"
    }
   },
   "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": "e8b62c84",
   "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": "8929bed2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:42.513509Z",
     "iopub.status.busy": "2024-11-26T10:05:42.513227Z",
     "iopub.status.idle": "2024-11-26T10:05:43.039782Z",
     "shell.execute_reply": "2024-11-26T10:05:43.038562Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d0480c5",
   "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": "9f2458e8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:43.043954Z",
     "iopub.status.busy": "2024-11-26T10:05:43.043277Z",
     "iopub.status.idle": "2024-11-26T10:05:43.312267Z",
     "shell.execute_reply": "2024-11-26T10:05:43.311124Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "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": "b5ac7b3b",
   "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": "0f92392c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:43.316105Z",
     "iopub.status.busy": "2024-11-26T10:05:43.315803Z",
     "iopub.status.idle": "2024-11-26T10:05:43.320030Z",
     "shell.execute_reply": "2024-11-26T10:05:43.318982Z"
    }
   },
   "outputs": [],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea9ff7b0",
   "metadata": {},
   "source": [
    "command if you are not using matplotlib in interactive mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "d7884809",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:43.323694Z",
     "iopub.status.busy": "2024-11-26T10:05:43.323410Z",
     "iopub.status.idle": "2024-11-26T10:05:43.656083Z",
     "shell.execute_reply": "2024-11-26T10:05:43.655000Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "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": "8f09239d",
   "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": "21d88e2c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:43.659263Z",
     "iopub.status.busy": "2024-11-26T10:05:43.659013Z",
     "iopub.status.idle": "2024-11-26T10:05:43.770923Z",
     "shell.execute_reply": "2024-11-26T10:05:43.770017Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "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": "57f1a4c7",
   "metadata": {},
   "source": [
    "To save drawings to a file, use, for example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "763a320c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:43.774014Z",
     "iopub.status.busy": "2024-11-26T10:05:43.773778Z",
     "iopub.status.idle": "2024-11-26T10:05:43.905241Z",
     "shell.execute_reply": "2024-11-26T10:05:43.904221Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "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": "b852e82e",
   "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": "63ecba4b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-26T10:05:43.908519Z",
     "iopub.status.busy": "2024-11-26T10:05:43.908295Z",
     "iopub.status.idle": "2024-11-26T10:05:44.097474Z",
     "shell.execute_reply": "2024-11-26T10:05:44.096444Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "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": "181d8056",
   "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. 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": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}

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