Bokeh Plotting with NetworkX http://nbviewer.ipython.org/gist/tonyfast/635714a234703d187452

NetworkX.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NetworkX"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> This notebook as been adapted from the [original notebook](https://github.com/jdwittenauer/ipython-notebooks/blob/master/NetworkX.ipynb) to plot with [Bokeh](bokeh.pydata.org) instead of matplotlib.\n",
    "\n",
    "NetworkX is a Python language software package for the creation, manipulation, and study of the structure, dynamics, and function of complex networks.\n",
    "\n",
    "With NetworkX you can load and store networks in standard and nonstandard data formats, generate many types of random and classic networks, analyze network structure, build network models, design new network algorithms, draw networks, and much more.\n",
    "\n",
    "Library documentation: <a>https://networkx.github.io/</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "G = nx.Graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# basic add nodes\n",
    "G.add_node(1)\n",
    "G.add_nodes_from([2, 3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# add a group of nodes at once\n",
    "H = nx.path_graph(10)\n",
    "G.add_nodes_from(H)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# add another graph itself as a node\n",
    "G.add_node(H)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# add edges using similar methods\n",
    "G.add_edge(1, 2)\n",
    "e = (2, 3)\n",
    "G.add_edge(*e)\n",
    "G.add_edges_from([(1, 2), (1, 3)])\n",
    "G.add_edges_from(H.edges())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# can also remove or clear\n",
    "G.remove_node(H)\n",
    "G.clear()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# repeats are ignored\n",
    "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'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8, 2)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get the number of nodes and edges\n",
    "G.number_of_nodes(), G.number_of_edges()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2: {}, 3: {}}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# access graph edges\n",
    "G[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G[1][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# set an attribute of an edge\n",
    "G.add_edge(1,3)\n",
    "G[1][3]['color'] = 'blue'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "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.adjacency_iter():\n",
    "    for nbr, eattr in nbrs.items():\n",
    "        data = eattr['weight']\n",
    "        if data < 0.5: print('(%d, %d, %.3f)' % (n, nbr, data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'day': 'Friday'}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# graph attribte\n",
    "G = nx.Graph(day='Friday')\n",
    "G.graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'day': 'Monday'}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# modifying an attribute\n",
    "G.graph['day'] = 'Monday'\n",
    "G.graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1, {'room': 714, 'time': '5pm'}), (3, {'time': '2pm'})]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# node attributes\n",
    "G.add_node(1, time='5pm')\n",
    "G.add_nodes_from([3], time='2pm')\n",
    "G.node[1]['room'] = 714\n",
    "G.nodes(data=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# edge attributes (weight is a special numeric attribute)\n",
    "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.edge[1][2]['weight'] = 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# directed graph\n",
    "DG = nx.DiGraph()\n",
    "DG.add_weighted_edges_from([(1, 2 ,0.5), (3, 1, 0.75)])\n",
    "DG.out_degree(1, weight='weight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.25"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DG.degree(1, weight='weight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DG.successors(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DG.predecessors(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# convert to undirected graph\n",
    "H = nx.Graph(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "    \n",
       "        <link rel=\"stylesheet\" href=\"http://cdn.pydata.org/bokeh/release/bokeh-0.9.1.min.css\" type=\"text/css\" />\n",
       "        <script type=\"text/javascript\" src=\"http://cdn.pydata.org/bokeh/release/bokeh-0.9.1.min.js\"></script>\n",
       "        <script type=\"text/javascript\">\n",
       "            Bokeh.set_log_level(\"info\");\n",
       "        </script>\n",
       "    <div>\n",
       "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span>BokehJS successfully loaded.</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bokeh.plotting import figure, show\n",
    "from bokeh.resources import CDN\n",
    "from bokeh.io import output_notebook\n",
    "output_notebook( resources=CDN )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Explore NetworkX Graph Layouts\n",
    "\n",
    "There are a few [layouts available in NetworkX graphs.](https://networkx.github.io/documentation/latest/reference/generated/networkx.drawing.layout.circular_layout.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Circular Layout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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\"y\": {\"field\": \"y\"}, \"tags\": []}, \"id\": \"a22464f0-430a-4347-9398-ec8688aee317\", \"type\": \"Line\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"line_color\": {\"value\": \"#1f77b4\"}, \"doc\": null, \"id\": \"db732f51-98dc-4c3a-8d50-9753bf976403\", \"x\": {\"field\": \"x\"}, \"y\": {\"field\": \"y\"}, \"tags\": []}, \"id\": \"db732f51-98dc-4c3a-8d50-9753bf976403\", \"type\": \"Line\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"line_color\": {\"value\": \"#1f77b4\"}, \"doc\": null, \"id\": \"ae929c0f-0cc6-48f6-8c6a-71765654bc59\", \"x\": {\"field\": \"x\"}, \"y\": {\"field\": \"y\"}, \"tags\": []}, \"id\": \"ae929c0f-0cc6-48f6-8c6a-71765654bc59\", \"type\": \"Line\"}, {\"attributes\": {\"doc\": null, \"selected\": {\"2d\": {\"indices\": []}, \"1d\": {\"indices\": []}, \"0d\": {\"flag\": false, \"indices\": []}}, \"callback\": null, \"id\": \"a7f6c736-e8f5-4e87-be8c-d77b7f57f32d\", \"data\": {\"x\": [0.5877853035926819], \"y\": [1.0]}, \"tags\": [], \"column_names\": [\"x\", \"y\"]}, \"id\": \"a7f6c736-e8f5-4e87-be8c-d77b7f57f32d\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"selection_glyph\": null, \"doc\": null, \"data_source\": {\"id\": \"2e8d4a24-dfb0-4580-b1cb-80197ab12b78\", \"type\": \"ColumnDataSource\"}, \"id\": \"df4fe983-b979-4767-bec9-5b24bf71e815\", \"glyph\": {\"id\": \"db732f51-98dc-4c3a-8d50-9753bf976403\", \"type\": \"Line\"}, \"nonselection_glyph\": {\"id\": \"35c17abe-d517-432f-9d6b-f28fbe2cb090\", \"type\": \"Line\"}, \"tags\": []}, \"id\": \"df4fe983-b979-4767-bec9-5b24bf71e815\", \"type\": \"GlyphRenderer\"}, {\"attributes\": {\"doc\": null, \"plot\": {\"subtype\": \"Figure\", \"id\": \"d5a571ec-20c0-452c-ab1d-e26557dbafb3\", \"type\": \"Plot\"}, \"id\": \"72311b24-efef-47e3-9aa0-48850732e38a\", \"dimensions\": [\"width\", \"height\"], \"tags\": []}, \"id\": \"72311b24-efef-47e3-9aa0-48850732e38a\", \"type\": \"WheelZoomTool\"}, {\"attributes\": {\"doc\": null, \"plot\": {\"subtype\": \"Figure\", \"id\": \"d5a571ec-20c0-452c-ab1d-e26557dbafb3\", \"type\": \"Plot\"}, \"id\": \"1da867e4-55e6-414c-a0cd-8f3da0f9dc1e\", \"tags\": []}, \"id\": \"1da867e4-55e6-414c-a0cd-8f3da0f9dc1e\", \"type\": \"PreviewSaveTool\"}, {\"attributes\": {\"dimension\": 1, \"ticker\": {\"id\": \"e7873066-6d0b-44c1-8515-3ab5356a6393\", \"type\": \"BasicTicker\"}, \"id\": \"e933aa5c-04d8-452f-8198-9e5948aa52aa\", \"plot\": {\"subtype\": \"Figure\", \"id\": \"d5a571ec-20c0-452c-ab1d-e26557dbafb3\", \"type\": \"Plot\"}, \"doc\": null, \"tags\": []}, \"id\": \"e933aa5c-04d8-452f-8198-9e5948aa52aa\", \"type\": \"Grid\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"line_color\": {\"value\": \"#1f77b4\"}, \"doc\": null, \"id\": \"0ce74cc6-7cfb-41ab-8f70-99c7165eed55\", \"x\": {\"field\": \"x\"}, \"y\": {\"field\": \"y\"}, \"tags\": []}, \"id\": \"0ce74cc6-7cfb-41ab-8f70-99c7165eed55\", \"type\": \"Line\"}, {\"attributes\": {\"ticker\": {\"id\": \"e7873066-6d0b-44c1-8515-3ab5356a6393\", \"type\": 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\"ec65efb3-7900-48d9-b33e-63326bff451c\", \"dimensions\": [\"width\", \"height\"], \"tags\": []}, \"id\": \"ec65efb3-7900-48d9-b33e-63326bff451c\", \"type\": \"BoxZoomTool\"}, {\"attributes\": {\"doc\": null, \"selected\": {\"2d\": {\"indices\": []}, \"1d\": {\"indices\": []}, \"0d\": {\"flag\": false, \"indices\": []}}, \"callback\": null, \"id\": \"e7b9b263-232b-4313-b036-54e466da8273\", \"data\": {\"x\": [6.26720364493849e-08], \"y\": [0.19098293781280518]}, \"tags\": [], \"column_names\": [\"x\", \"y\"]}, \"id\": \"e7b9b263-232b-4313-b036-54e466da8273\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 0.1}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"0a2bf01e-efc3-461a-8858-061de5aac626\", \"tags\": []}, \"id\": \"0a2bf01e-efc3-461a-8858-061de5aac626\", \"type\": \"Circle\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 1.0}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"a290ed6d-4491-406f-82b9-52c75b620bf7\", \"tags\": []}, \"id\": \"a290ed6d-4491-406f-82b9-52c75b620bf7\", \"type\": \"Circle\"}, {\"attributes\": {\"num_minor_ticks\": 5, \"doc\": null, \"id\": \"e7873066-6d0b-44c1-8515-3ab5356a6393\", \"tags\": [], \"mantissas\": [2, 5, 10]}, \"id\": \"e7873066-6d0b-44c1-8515-3ab5356a6393\", \"type\": \"BasicTicker\"}];\n",
       "            Bokeh.load_models(all_models);\n",
       "            var plots = [{'modelid': 'd5a571ec-20c0-452c-ab1d-e26557dbafb3', 'elementid': '#99616fc1-537e-45f7-a7f5-881f50deb33f', 'modeltype': 'Plot'}];\n",
       "            for (idx in plots) {\n",
       "            \tvar plot = plots[idx];\n",
       "            \tvar model = Bokeh.Collections(plot.modeltype).get(plot.modelid);\n",
       "            \tBokeh.logger.info('Realizing plot:')\n",
       "            \tBokeh.logger.info(' - modeltype: ' + plot.modeltype);\n",
       "            \tBokeh.logger.info(' - modelid: ' + plot.modelid);\n",
       "            \tBokeh.logger.info(' - elementid: ' + plot.elementid);\n",
       "            \tvar view = new model.default_view({\n",
       "            \t\tmodel: model,\n",
       "            \t\tel: plot.elementid\n",
       "            \t});\n",
       "            \tBokeh.index[plot.modelid] = view;\n",
       "            }\n",
       "        });\n",
       "    </script>\n",
       "<div class=\"plotdiv\" id=\"99616fc1-537e-45f7-a7f5-881f50deb33f\"></div>\n",
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pts = nx.circular_layout(G)\n",
    "p = figure(\n",
    "    x_range = (-.1,1.1),\n",
    "    y_range = (-.1,1.1),\n",
    "    height= 400,\n",
    "    width= 400,\n",
    ")\n",
    "for edge in G.edges():\n",
    "    p.line( \n",
    "        x= [pts[pt][0] for pt in edge],\n",
    "        y= [pts[pt][1] for pt in edge],\n",
    "    )\n",
    "\n",
    "for node in G.nodes():\n",
    "    p.circle( \n",
    "        x= [pts[node][0]],\n",
    "        y= [pts[node][1]],\n",
    "        radius=.05\n",
    "    )\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Layout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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\"3790211d-4fe5-42b3-acc0-b8a4ce1cdb36\", \"data\": {\"x\": [0.3063741624355316, 0.06526412069797516], \"y\": [0.6662241220474243, 0.3997838497161865]}, \"tags\": [], \"column_names\": [\"x\", \"y\"]}, \"id\": \"3790211d-4fe5-42b3-acc0-b8a4ce1cdb36\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"doc\": null, \"selected\": {\"2d\": {\"indices\": []}, \"1d\": {\"indices\": []}, \"0d\": {\"flag\": false, \"indices\": []}}, \"callback\": null, \"id\": \"8659d146-1158-4876-ae2a-9a8e1decab19\", \"data\": {\"x\": [0.3063741624355316], \"y\": [0.6662241220474243]}, \"tags\": [], \"column_names\": [\"x\", \"y\"]}, \"id\": \"8659d146-1158-4876-ae2a-9a8e1decab19\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"start\": -0.1, \"callback\": null, \"id\": \"85d79f98-6ef8-4e50-94b1-11fd84329f21\", \"doc\": null, \"tags\": [], \"end\": 1.1}, \"id\": \"85d79f98-6ef8-4e50-94b1-11fd84329f21\", \"type\": \"Range1d\"}];\n",
       "            Bokeh.load_models(all_models);\n",
       "            var plots = [{'modelid': '3eae7f62-9521-4629-ba73-c5cd0107ce1b', 'elementid': '#7180f043-3f3f-425c-9b0c-f4e67ed0be9a', 'modeltype': 'Plot'}];\n",
       "            for (idx in plots) {\n",
       "            \tvar plot = plots[idx];\n",
       "            \tvar model = Bokeh.Collections(plot.modeltype).get(plot.modelid);\n",
       "            \tBokeh.logger.info('Realizing plot:')\n",
       "            \tBokeh.logger.info(' - modeltype: ' + plot.modeltype);\n",
       "            \tBokeh.logger.info(' - modelid: ' + plot.modelid);\n",
       "            \tBokeh.logger.info(' - elementid: ' + plot.elementid);\n",
       "            \tvar view = new model.default_view({\n",
       "            \t\tmodel: model,\n",
       "            \t\tel: plot.elementid\n",
       "            \t});\n",
       "            \tBokeh.index[plot.modelid] = view;\n",
       "            }\n",
       "        });\n",
       "    </script>\n",
       "<div class=\"plotdiv\" id=\"7180f043-3f3f-425c-9b0c-f4e67ed0be9a\"></div>\n",
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pts = nx.random_layout(G)\n",
    "p = figure(\n",
    "    x_range = (-.1,1.1),\n",
    "    y_range = (-.1,1.1),\n",
    "    height= 400,\n",
    "    width= 400,\n",
    ")\n",
    "for edge in G.edges():\n",
    "    p.line( \n",
    "        x= [pts[pt][0] for pt in edge],\n",
    "        y= [pts[pt][1] for pt in edge],\n",
    "    )\n",
    "\n",
    "for node in G.nodes():\n",
    "    p.circle( \n",
    "        x= [pts[node][0]],\n",
    "        y= [pts[node][1]],\n",
    "        radius=.05\n",
    "    )\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Shell Layout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script type=\"text/javascript\">\n",
       "        Bokeh.$(function() {\n",
       "            var all_models = [{\"attributes\": {\"doc\": null, \"plot\": {\"subtype\": \"Figure\", \"id\": \"40b1c4e9-c389-42d6-b49a-0730dbc3fb76\", \"type\": \"Plot\"}, \"id\": \"578b64d4-f151-48b5-8a73-e26b032534c1\", \"tags\": []}, \"id\": \"578b64d4-f151-48b5-8a73-e26b032534c1\", \"type\": \"HelpTool\"}, {\"attributes\": {\"doc\": null, \"id\": \"6c67d2da-8ffc-470b-9ae0-38a500575435\", \"geometries\": [], \"tags\": []}, \"id\": \"6c67d2da-8ffc-470b-9ae0-38a500575435\", \"type\": \"ToolEvents\"}, {\"attributes\": {\"doc\": null, \"selected\": {\"2d\": {\"indices\": []}, \"1d\": {\"indices\": []}, \"0d\": {\"flag\": false, \"indices\": []}}, \"callback\": null, \"id\": \"c5fe8e1c-1abf-4f40-97a4-e2bfb612fccf\", \"data\": {\"x\": [0.3090171217918396], \"y\": [-0.9510564804077148]}, \"tags\": [], \"column_names\": [\"x\", \"y\"]}, \"id\": \"c5fe8e1c-1abf-4f40-97a4-e2bfb612fccf\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"selection_glyph\": null, \"doc\": null, 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\"e91c7929-966a-4a40-b3e4-a70c8c63cff6\", \"type\": \"GlyphRenderer\"}, {\"id\": \"de00ed24-0ea8-45ea-a834-e314438d57f5\", \"type\": \"GlyphRenderer\"}], \"extra_y_ranges\": {}, \"below\": [{\"id\": \"79918ca8-ae96-4bbe-8741-0845d3920818\", \"type\": \"LinearAxis\"}], \"tags\": [], \"tools\": [{\"id\": \"e9e5cdb5-2320-49ac-849d-3a02be598c94\", \"type\": \"PanTool\"}, {\"id\": \"213cc1f1-3740-4da9-b1ff-1e74e0b3caf4\", \"type\": \"WheelZoomTool\"}, {\"id\": \"b600f5d3-f43c-4f7b-a02a-097364b1a7c5\", \"type\": \"BoxZoomTool\"}, {\"id\": \"c6739687-ae15-4cab-bbf3-d713bbef691d\", \"type\": \"PreviewSaveTool\"}, {\"id\": \"ca797c97-dee1-4987-b0f1-c17ecc75998e\", \"type\": \"ResizeTool\"}, {\"id\": \"e5a4422d-ef25-44d2-a349-2850c36515ff\", \"type\": \"ResetTool\"}, {\"id\": \"578b64d4-f151-48b5-8a73-e26b032534c1\", \"type\": \"HelpTool\"}]}, \"subtype\": \"Figure\", \"id\": \"40b1c4e9-c389-42d6-b49a-0730dbc3fb76\", \"type\": \"Plot\"}, {\"attributes\": {\"doc\": null, \"plot\": {\"subtype\": 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\"11399360-4e4c-444e-b245-dd32501186d4\", \"data\": {\"x\": [0.30901697278022766, -0.8090170621871948], \"y\": [0.9510565400123596, 0.5877851843833923]}, \"tags\": [], \"column_names\": [\"x\", \"y\"]}, \"id\": \"11399360-4e4c-444e-b245-dd32501186d4\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 0.1}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"6b45fc68-0eea-469e-8076-1182f611a301\", \"tags\": []}, \"id\": \"6b45fc68-0eea-469e-8076-1182f611a301\", \"type\": \"Circle\"}, {\"attributes\": {\"doc\": null, \"selected\": {\"2d\": {\"indices\": []}, \"1d\": {\"indices\": []}, \"0d\": {\"flag\": false, \"indices\": []}}, \"callback\": null, \"id\": \"f317eda0-49b5-4c23-92c7-560c5728f587\", \"data\": {\"x\": [-0.8090170621871948, -0.8090169429779053], \"y\": [0.5877851843833923, -0.5877853631973267]}, \"tags\": [], \"column_names\": [\"x\", \"y\"]}, \"id\": \"f317eda0-49b5-4c23-92c7-560c5728f587\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"selection_glyph\": null, \"doc\": null, \"data_source\": {\"id\": \"c5fe8e1c-1abf-4f40-97a4-e2bfb612fccf\", \"type\": \"ColumnDataSource\"}, \"id\": \"de00ed24-0ea8-45ea-a834-e314438d57f5\", \"glyph\": {\"id\": \"8b28d7e1-3294-40e9-bd98-f81eede86c72\", \"type\": \"Circle\"}, \"nonselection_glyph\": {\"id\": \"6ca6139a-83bb-40f3-93a4-de4b1e478f87\", \"type\": \"Circle\"}, \"tags\": []}, \"id\": \"de00ed24-0ea8-45ea-a834-e314438d57f5\", \"type\": \"GlyphRenderer\"}, {\"attributes\": {\"doc\": null, \"plot\": {\"subtype\": \"Figure\", \"id\": \"40b1c4e9-c389-42d6-b49a-0730dbc3fb76\", \"type\": \"Plot\"}, \"id\": \"b600f5d3-f43c-4f7b-a02a-097364b1a7c5\", \"dimensions\": [\"width\", \"height\"], \"tags\": []}, \"id\": \"b600f5d3-f43c-4f7b-a02a-097364b1a7c5\", \"type\": \"BoxZoomTool\"}, {\"attributes\": {\"doc\": null, \"plot\": {\"subtype\": \"Figure\", \"id\": \"40b1c4e9-c389-42d6-b49a-0730dbc3fb76\", \"type\": \"Plot\"}, \"id\": \"e5a4422d-ef25-44d2-a349-2850c36515ff\", \"tags\": []}, \"id\": \"e5a4422d-ef25-44d2-a349-2850c36515ff\", \"type\": \"ResetTool\"}, {\"attributes\": {\"selection_glyph\": null, \"doc\": null, \"data_source\": {\"id\": \"d3475a74-d9fa-4a0c-ba56-32a69a4a206f\", \"type\": \"ColumnDataSource\"}, \"id\": \"35a9f438-7a0d-4625-941b-a2ffdec72337\", \"glyph\": {\"id\": \"67cd65ce-85f5-4962-8d59-88ef72794650\", \"type\": \"Circle\"}, \"nonselection_glyph\": {\"id\": \"847c0be1-e457-4d1a-ad06-b0436d3f308c\", \"type\": \"Circle\"}, \"tags\": []}, \"id\": \"35a9f438-7a0d-4625-941b-a2ffdec72337\", \"type\": \"GlyphRenderer\"}, {\"attributes\": {\"selection_glyph\": null, \"doc\": null, \"data_source\": {\"id\": \"5b939a37-3504-4713-8c4e-98b38039e686\", \"type\": \"ColumnDataSource\"}, \"id\": \"7262c9ad-7889-4815-bcd1-03f755e0bd7d\", \"glyph\": {\"id\": 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\"column_names\": [\"x\", \"y\"]}, \"id\": \"5b939a37-3504-4713-8c4e-98b38039e686\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"doc\": null, \"selected\": {\"2d\": {\"indices\": []}, \"1d\": {\"indices\": []}, \"0d\": {\"flag\": false, \"indices\": []}}, \"callback\": null, \"id\": \"285ecaf1-4d9b-4487-8d7d-783359e97b9c\", \"data\": {\"x\": [-0.8090169429779053], \"y\": [-0.5877853631973267]}, \"tags\": [], \"column_names\": [\"x\", \"y\"]}, \"id\": \"285ecaf1-4d9b-4487-8d7d-783359e97b9c\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"line_color\": {\"value\": \"#1f77b4\"}, \"doc\": null, \"id\": \"7ad26c74-ec91-4291-a37a-bb5c0e22c582\", \"x\": {\"field\": \"x\"}, \"y\": {\"field\": \"y\"}, \"tags\": []}, \"id\": \"7ad26c74-ec91-4291-a37a-bb5c0e22c582\", \"type\": \"Line\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 1.0}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"67cd65ce-85f5-4962-8d59-88ef72794650\", \"tags\": []}, \"id\": \"67cd65ce-85f5-4962-8d59-88ef72794650\", \"type\": \"Circle\"}, {\"attributes\": {\"start\": -1.1, \"callback\": null, \"id\": \"586dbf1d-5b37-497b-888b-9a9b0052b451\", \"doc\": null, \"tags\": [], \"end\": 1.1}, \"id\": \"586dbf1d-5b37-497b-888b-9a9b0052b451\", \"type\": \"Range1d\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"line_color\": {\"value\": \"#1f77b4\"}, \"doc\": null, \"id\": \"ea183012-1e67-4bf4-8bc4-7ecc54d5e4f6\", \"x\": {\"field\": \"x\"}, \"y\": {\"field\": \"y\"}, \"tags\": []}, \"id\": \"ea183012-1e67-4bf4-8bc4-7ecc54d5e4f6\", \"type\": \"Line\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"line_color\": {\"value\": \"#1f77b4\"}, \"doc\": null, \"id\": \"676b37a4-cc5c-47a2-bbda-351416dd6e1f\", \"x\": {\"field\": \"x\"}, \"y\": {\"field\": \"y\"}, \"tags\": []}, \"id\": \"676b37a4-cc5c-47a2-bbda-351416dd6e1f\", \"type\": \"Line\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 1.0}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"8b28d7e1-3294-40e9-bd98-f81eede86c72\", \"tags\": []}, \"id\": \"8b28d7e1-3294-40e9-bd98-f81eede86c72\", \"type\": \"Circle\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 1.0}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"27fd4824-0e91-4f32-bf36-70ac283e7870\", \"tags\": []}, \"id\": \"27fd4824-0e91-4f32-bf36-70ac283e7870\", \"type\": \"Circle\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"line_color\": {\"value\": \"#1f77b4\"}, \"doc\": null, \"id\": \"03aa24c4-f864-4c49-995a-306ec95a65ff\", \"x\": {\"field\": \"x\"}, \"y\": {\"field\": \"y\"}, \"tags\": []}, \"id\": \"03aa24c4-f864-4c49-995a-306ec95a65ff\", \"type\": \"Line\"}, {\"attributes\": {\"ticker\": {\"id\": \"31dc52f6-f313-4311-9448-2fca0238a907\", \"type\": \"BasicTicker\"}, \"id\": \"fcf1221a-f19f-41de-a9e1-93fb026140e1\", \"plot\": {\"subtype\": \"Figure\", \"id\": \"40b1c4e9-c389-42d6-b49a-0730dbc3fb76\", \"type\": \"Plot\"}, \"doc\": null, \"formatter\": {\"id\": \"19b7c8bc-5090-4ee5-be42-923d938796d7\", \"type\": \"BasicTickFormatter\"}, \"tags\": []}, \"id\": \"fcf1221a-f19f-41de-a9e1-93fb026140e1\", \"type\": \"LinearAxis\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 1.0}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"81b4b602-db1c-4554-827f-fc423162f335\", \"tags\": []}, \"id\": \"81b4b602-db1c-4554-827f-fc423162f335\", \"type\": \"Circle\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 1.0}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"9fc0727c-02b2-4f6c-9fb1-acb4f37cbe30\", \"tags\": []}, \"id\": \"9fc0727c-02b2-4f6c-9fb1-acb4f37cbe30\", \"type\": \"Circle\"}, {\"attributes\": {\"num_minor_ticks\": 5, \"doc\": null, \"id\": \"ef2797d3-f9cf-4023-bb21-d60d5e310724\", \"tags\": [], \"mantissas\": [2, 5, 10]}, \"id\": \"ef2797d3-f9cf-4023-bb21-d60d5e310724\", \"type\": \"BasicTicker\"}, {\"attributes\": {\"doc\": null, \"plot\": {\"subtype\": \"Figure\", \"id\": \"40b1c4e9-c389-42d6-b49a-0730dbc3fb76\", \"type\": \"Plot\"}, \"id\": \"213cc1f1-3740-4da9-b1ff-1e74e0b3caf4\", \"dimensions\": [\"width\", \"height\"], \"tags\": []}, \"id\": \"213cc1f1-3740-4da9-b1ff-1e74e0b3caf4\", \"type\": \"WheelZoomTool\"}, {\"attributes\": {\"doc\": null, \"plot\": {\"subtype\": \"Figure\", \"id\": \"40b1c4e9-c389-42d6-b49a-0730dbc3fb76\", \"type\": \"Plot\"}, \"id\": \"ca797c97-dee1-4987-b0f1-c17ecc75998e\", \"tags\": []}, \"id\": \"ca797c97-dee1-4987-b0f1-c17ecc75998e\", \"type\": \"ResizeTool\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 0.1}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"847c0be1-e457-4d1a-ad06-b0436d3f308c\", \"tags\": []}, \"id\": \"847c0be1-e457-4d1a-ad06-b0436d3f308c\", \"type\": \"Circle\"}];\n",
       "            Bokeh.load_models(all_models);\n",
       "            var plots = [{'modelid': '40b1c4e9-c389-42d6-b49a-0730dbc3fb76', 'elementid': '#770e5309-114f-45b0-9bb6-2d271a9f8bf7', 'modeltype': 'Plot'}];\n",
       "            for (idx in plots) {\n",
       "            \tvar plot = plots[idx];\n",
       "            \tvar model = Bokeh.Collections(plot.modeltype).get(plot.modelid);\n",
       "            \tBokeh.logger.info('Realizing plot:')\n",
       "            \tBokeh.logger.info(' - modeltype: ' + plot.modeltype);\n",
       "            \tBokeh.logger.info(' - modelid: ' + plot.modelid);\n",
       "            \tBokeh.logger.info(' - elementid: ' + plot.elementid);\n",
       "            \tvar view = new model.default_view({\n",
       "            \t\tmodel: model,\n",
       "            \t\tel: plot.elementid\n",
       "            \t});\n",
       "            \tBokeh.index[plot.modelid] = view;\n",
       "            }\n",
       "        });\n",
       "    </script>\n",
       "<div class=\"plotdiv\" id=\"770e5309-114f-45b0-9bb6-2d271a9f8bf7\"></div>\n",
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pts = nx.shell_layout(G)\n",
    "p = figure(\n",
    "    x_range = (-1.1,1.1),\n",
    "    y_range = (-1.1,1.1),\n",
    "    height= 400,\n",
    "    width= 400,\n",
    ")\n",
    "for edge in G.edges():\n",
    "    p.line( \n",
    "        x= [pts[pt][0] for pt in edge],\n",
    "        y= [pts[pt][1] for pt in edge],\n",
    "    )\n",
    "\n",
    "for node in G.nodes():\n",
    "    p.circle( \n",
    "        x= [pts[node][0]],\n",
    "        y= [pts[node][1]],\n",
    "        radius=.05\n",
    "    )\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spring Layout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script type=\"text/javascript\">\n",
       "        Bokeh.$(function() {\n",
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\"fb521495-928b-473f-97b3-705932ce90f0\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"doc\": null, \"selected\": {\"2d\": {\"indices\": []}, \"1d\": {\"indices\": []}, \"0d\": {\"flag\": false, \"indices\": []}}, \"callback\": null, \"id\": \"21f69f3c-c9e8-4b2c-950a-42cc1b246a98\", \"data\": {\"x\": [0.14217413065045498], \"y\": [0.1733710780091455]}, \"tags\": [], \"column_names\": [\"x\", \"y\"]}, \"id\": \"21f69f3c-c9e8-4b2c-950a-42cc1b246a98\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"doc\": null, \"plot\": {\"subtype\": \"Figure\", \"id\": \"541ef108-b0dc-4731-b9f9-151ea606246b\", \"type\": \"Plot\"}, \"id\": \"124a1c8e-70a5-4843-90f2-942ddc32eff2\", \"dimensions\": [\"width\", \"height\"], \"tags\": []}, \"id\": \"124a1c8e-70a5-4843-90f2-942ddc32eff2\", \"type\": \"WheelZoomTool\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 0.1}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"cd282e85-1203-4420-bd19-7d8d0e43418a\", \"tags\": []}, \"id\": \"cd282e85-1203-4420-bd19-7d8d0e43418a\", \"type\": \"Circle\"}, {\"attributes\": {\"doc\": null, \"plot\": {\"subtype\": \"Figure\", \"id\": \"541ef108-b0dc-4731-b9f9-151ea606246b\", \"type\": \"Plot\"}, \"id\": \"e0ee032e-e0cb-48da-a6ab-8c5b4660fdb3\", \"tags\": []}, \"id\": \"e0ee032e-e0cb-48da-a6ab-8c5b4660fdb3\", \"type\": \"ResetTool\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 1.0}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"ebe6fb07-ed8b-45fe-8c21-4a77ce265e15\", \"tags\": []}, \"id\": \"ebe6fb07-ed8b-45fe-8c21-4a77ce265e15\", \"type\": \"Circle\"}, {\"attributes\": {\"ticker\": {\"id\": \"8399b32a-dfbb-4ed2-91b8-f499b2e1a0cd\", \"type\": \"BasicTicker\"}, \"id\": \"9bfb21b3-0896-40ba-afbe-7665631797e3\", \"plot\": {\"subtype\": \"Figure\", \"id\": \"541ef108-b0dc-4731-b9f9-151ea606246b\", \"type\": \"Plot\"}, \"doc\": null, \"formatter\": {\"id\": \"da39eee7-3f76-4600-9d38-85428f663969\", \"type\": \"BasicTickFormatter\"}, \"tags\": []}, \"id\": \"9bfb21b3-0896-40ba-afbe-7665631797e3\", \"type\": \"LinearAxis\"}, {\"attributes\": {\"ticker\": {\"id\": \"b6884e76-ae54-497f-8d81-7952602f0550\", \"type\": \"BasicTicker\"}, \"id\": \"2c866a9a-28be-4e1c-9174-36bf8cf862d7\", \"plot\": {\"subtype\": \"Figure\", \"id\": \"541ef108-b0dc-4731-b9f9-151ea606246b\", \"type\": \"Plot\"}, \"doc\": null, \"formatter\": {\"id\": \"44603456-25d0-4ef8-abf7-b4e5aac21eea\", \"type\": \"BasicTickFormatter\"}, \"tags\": []}, \"id\": \"2c866a9a-28be-4e1c-9174-36bf8cf862d7\", \"type\": \"LinearAxis\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"line_color\": {\"value\": \"#1f77b4\"}, \"doc\": null, \"id\": \"d3ac986c-8438-4fb3-beb8-496cc57de50b\", \"x\": {\"field\": \"x\"}, \"y\": {\"field\": \"y\"}, \"tags\": []}, \"id\": \"d3ac986c-8438-4fb3-beb8-496cc57de50b\", \"type\": \"Line\"}, {\"attributes\": {\"line_alpha\": {\"value\": 1.0}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 1.0}, \"fill_color\": {\"value\": \"#1f77b4\"}, \"id\": \"d043ea98-a0af-4c91-aa2a-b0bf21ef3653\", \"tags\": []}, \"id\": \"d043ea98-a0af-4c91-aa2a-b0bf21ef3653\", \"type\": \"Circle\"}, {\"attributes\": {\"start\": -0.1, \"callback\": null, \"id\": \"41454110-1b59-4746-a7a6-68fc16580a2d\", \"doc\": null, \"tags\": [], \"end\": 1.1}, \"id\": \"41454110-1b59-4746-a7a6-68fc16580a2d\", \"type\": \"Range1d\"}, {\"attributes\": {\"doc\": null, \"selected\": {\"2d\": {\"indices\": []}, \"1d\": {\"indices\": []}, \"0d\": {\"flag\": false, \"indices\": []}}, \"callback\": null, \"id\": \"8d8645b7-2b3f-45f2-ba1a-9e82b316d097\", \"data\": {\"x\": [0.0], \"y\": [0.3983372746930259]}, \"tags\": [], \"column_names\": [\"x\", \"y\"]}, \"id\": \"8d8645b7-2b3f-45f2-ba1a-9e82b316d097\", \"type\": \"ColumnDataSource\"}, {\"attributes\": {\"selection_glyph\": null, \"doc\": null, \"data_source\": {\"id\": \"6004476c-07f0-41a7-8e69-13ee7ffcd4cc\", \"type\": \"ColumnDataSource\"}, \"id\": \"6c67b11a-9dc0-410a-92d5-4bb04b675917\", \"glyph\": {\"id\": \"04be11c1-6905-4ceb-bfad-a9318addb3bd\", \"type\": \"Line\"}, \"nonselection_glyph\": {\"id\": \"c558c508-ea9b-4a7c-a036-9161f6428bda\", \"type\": \"Line\"}, \"tags\": []}, \"id\": \"6c67b11a-9dc0-410a-92d5-4bb04b675917\", \"type\": \"GlyphRenderer\"}];\n",
       "            Bokeh.load_models(all_models);\n",
       "            var plots = [{'modelid': '541ef108-b0dc-4731-b9f9-151ea606246b', 'elementid': '#6fbaf3b9-4d7e-42ed-9521-28ef1047cb23', 'modeltype': 'Plot'}];\n",
       "            for (idx in plots) {\n",
       "            \tvar plot = plots[idx];\n",
       "            \tvar model = Bokeh.Collections(plot.modeltype).get(plot.modelid);\n",
       "            \tBokeh.logger.info('Realizing plot:')\n",
       "            \tBokeh.logger.info(' - modeltype: ' + plot.modeltype);\n",
       "            \tBokeh.logger.info(' - modelid: ' + plot.modelid);\n",
       "            \tBokeh.logger.info(' - elementid: ' + plot.elementid);\n",
       "            \tvar view = new model.default_view({\n",
       "            \t\tmodel: model,\n",
       "            \t\tel: plot.elementid\n",
       "            \t});\n",
       "            \tBokeh.index[plot.modelid] = view;\n",
       "            }\n",
       "        });\n",
       "    </script>\n",
       "<div class=\"plotdiv\" id=\"6fbaf3b9-4d7e-42ed-9521-28ef1047cb23\"></div>\n",
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pts = nx.spring_layout(G)\n",
    "p = figure(\n",
    "    x_range = (-.1,1.1),\n",
    "    y_range = (-.1,1.1),\n",
    "    height= 400,\n",
    "    width= 400,\n",
    ")\n",
    "for edge in G.edges():\n",
    "    p.line( \n",
    "        x= [pts[pt][0] for pt in edge],\n",
    "        y= [pts[pt][1] for pt in edge],\n",
    "    )\n",
    "\n",
    "for node in G.nodes():\n",
    "    p.circle( \n",
    "        x= [pts[node][0]],\n",
    "        y= [pts[node][1]],\n",
    "        radius=.05,\n",
    "    )\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spectral Layout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script type=\"text/javascript\">\n",
       "        Bokeh.$(function() {\n",
       "            var all_models = [{\"attributes\": {\"doc\": null, \"tags\": [], \"id\": \"8dc12ddf-a88d-48d3-ac49-7e3409094b5c\"}, \"id\": \"8dc12ddf-a88d-48d3-ac49-7e3409094b5c\", \"type\": \"BasicTickFormatter\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"line_color\": {\"value\": \"#1f77b4\"}, \"doc\": null, \"id\": \"64034369-4aec-4e7f-a4e8-922f8becc753\", \"x\": {\"field\": \"x\"}, \"y\": {\"field\": \"y\"}, \"tags\": []}, \"id\": \"64034369-4aec-4e7f-a4e8-922f8becc753\", \"type\": \"Line\"}, {\"attributes\": {\"doc\": null, \"id\": \"b2d31a0f-6492-42f9-a671-c2da33de87b7\", \"geometries\": [], \"tags\": []}, \"id\": \"b2d31a0f-6492-42f9-a671-c2da33de87b7\", \"type\": \"ToolEvents\"}, {\"attributes\": {\"line_alpha\": {\"value\": 0.1}, \"doc\": null, \"x\": {\"field\": \"x\"}, \"line_color\": {\"value\": \"#1f77b4\"}, \"y\": {\"field\": \"y\"}, \"radius\": {\"value\": 0.05, \"units\": \"data\"}, \"fill_alpha\": {\"value\": 0.1}, \"fill_color\": {\"value\": 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       "            Bokeh.load_models(all_models);\n",
       "            var plots = [{'modelid': 'bc0de009-0207-4098-9b4f-61db942afe5a', 'elementid': '#44bf5575-0ee6-4868-89f3-7ba83d0a1649', 'modeltype': 'Plot'}];\n",
       "            for (idx in plots) {\n",
       "            \tvar plot = plots[idx];\n",
       "            \tvar model = Bokeh.Collections(plot.modeltype).get(plot.modelid);\n",
       "            \tBokeh.logger.info('Realizing plot:')\n",
       "            \tBokeh.logger.info(' - modeltype: ' + plot.modeltype);\n",
       "            \tBokeh.logger.info(' - modelid: ' + plot.modelid);\n",
       "            \tBokeh.logger.info(' - elementid: ' + plot.elementid);\n",
       "            \tvar view = new model.default_view({\n",
       "            \t\tmodel: model,\n",
       "            \t\tel: plot.elementid\n",
       "            \t});\n",
       "            \tBokeh.index[plot.modelid] = view;\n",
       "            }\n",
       "        });\n",
       "    </script>\n",
       "<div class=\"plotdiv\" id=\"44bf5575-0ee6-4868-89f3-7ba83d0a1649\"></div>\n",
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pts = nx.spectral_layout(G)\n",
    "p = figure(\n",
    "    x_range = (-.1,1.1),\n",
    "    y_range = (-.1,1.1),\n",
    "    height= 400,\n",
    "    width= 400,\n",
    ")\n",
    "for edge in G.edges():\n",
    "    p.line( \n",
    "        x= [pts[pt][0] for pt in edge],\n",
    "        y= [pts[pt][1] for pt in edge],\n",
    "    )\n",
    "\n",
    "for node in G.nodes():\n",
    "    p.circle( \n",
    "        x= [pts[node][0]],\n",
    "        y= [pts[node][1]],\n",
    "        radius=.05,\n",
    "    )\n",
    "show(p)"
   ]
  }
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