{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "import igraph as ig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "# Load the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "G = ig.read(\"data/bitcoin/bitcoinotc.graphml\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "G.to_undirected(combine_edges=\"first\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "# Clique distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "G.clique_number()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "cl = G.cliques()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "plt.hist(list(map(len,cl)), bins=10);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "# Rescale the timestamps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "edges = pd.DataFrame([e.attributes().values() for e in G.es])\n",
    "edges.columns = G.es.attribute_names()\n",
    "edges.drop([\"Edge Label\", \"id\"], axis=1, inplace=True)\n",
    "edges.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "timerange = edges.time.max() - edges.time.min()\n",
    "timemin = edges.time.min()\n",
    "G.es[\"time\"] = (G.es[\"time\"] - timemin) / timerange"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "# Temporal subgraphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "G.subgraph_edges(G.es(lambda e: e[\"time\"] < 0.1)).summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "def temporal_subgraph(graph, tmin=None, tmax=None, delete_vertices=True):\n",
    "    if tmin==None:\n",
    "        tmin = min(graph.es[\"time\"])\n",
    "    if tmax==None:\n",
    "        tmax = max(graph.es[\"time\"])\n",
    "    return G.subgraph_edges(G.es(lambda e: (e[\"time\"] > tmin) & (e[\"time\"] < tmax)), delete_vertices=delete_vertices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "temporal_subgraph(G, tmin=0.1, tmax=0.3).summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "ti = 0\n",
    "dt = 0.01\n",
    "subg = temporal_subgraph(G, tmin=ti, tmax=ti+dt)\n",
    "layout = subg.layout(\"kk\")\n",
    "ig.plot(subg, layout=layout)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "# Export multilayer graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "dt = 0.05\n",
    "layout = []\n",
    "subg = []\n",
    "for i in range(2):\n",
    "    subg.append(temporal_subgraph(G, tmin=i*dt, tmax=i*dt+dt))\n",
    "    layout.append(subg[i].layout(\"kk\").coords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "vs_df = pd.DataFrame()\n",
    "es_df = pd.DataFrame()\n",
    "for i in range(2):\n",
    "    subg_vs = pd.DataFrame(layout[i])\n",
    "    subg_vs.columns = [\"x\",\"y\"]\n",
    "    subg_vs[\"id\"] = np.arange(len(layout[i]))\n",
    "    subg_vs[\"layer\"] = i+1\n",
    "    # subg_vs.to_csv(\"vs1.csv\", index=False)\n",
    "    vs_df = pd.concat([vs_df,subg_vs])\n",
    "    subg_es = pd.DataFrame([[e.source,e.target] for e in subg[i].es])\n",
    "    subg_es.columns = [\"u\",\"v\"]\n",
    "    # subg_es.to_csv(\"es1.csv\", index=False)\n",
    "    es_df = pd.concat([es_df,subg_es])\n",
    "    \n",
    "vs_df.to_csv(\"vs.csv\", index=False)\n",
    "es_df.to_csv(\"es.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "autoscroll": false,
    "collapsed": false,
    "ein.tags": "worksheet-0",
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "name": "bitcoin.ipynb"
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