conviction/conviction_cadCAD3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scipy.stats as sts\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "#import conviction files\n",
    "from conviction_helpers import *\n",
    "from conviction_system_logic3 import *\n",
    "from bonding_curve_eq import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook uses the differential games framework developed by BlockScience. It is currently in private beta, and building towards a full open source release.\n",
    "\n",
    "**Description:**\n",
    "\n",
    "cadCAD is a Python library that assists in the processes of designing, testing and validating complex systems through simulation. At its core, cadCAD is a differential games engine that supports parameter sweeping and Monte Carlo analyses and can be easily integrated with other scientific computing Python modules and data science workflows.\n",
    "\n",
    "To learn more about cadCAD, follow our [tutorial series](https://github.com/BlockScience/cadCAD-Tutorials/tree/master/01%20Tutorials)\n",
    "\n",
    "**Installing cadCAD:**\n",
    "\n",
    "cadCAD is in private beta. Tokens are issued to participants. Replace `<TOKEN>` in the installation URL below\n",
    "```bash\n",
    "pip3 install cadCAD --extra-index-url https://<TOKEN>@repo.fury.io/blockscience/\n",
    "```\n",
    "\n",
    "If you'd like to participate in the beta program, contact cadcad [at] block [dot] science.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#THIS policy is one of the main paramters of this system!\n",
    "\n",
    "#maximum share of funds a proposal can take\n",
    "default_beta = .2 #later we should set this to be param so we can sweep it\n",
    "# tuning param for the trigger function\n",
    "default_rho = .5*default_beta**2\n",
    "\n",
    "def trigger_threshold(requested, funds, supply, beta=default_beta , rho=default_rho):\n",
    "    \n",
    "    share = requested/funds\n",
    "    if share < beta:\n",
    "        return rho*supply/(beta-share)**2\n",
    "    else: \n",
    "        return np.inf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/Zargham/Documents/GitHub/conviction/conviction_helpers.py:189: RuntimeWarning: divide by zero encountered in log10\n",
      "  demo_data_Z0[sof_ind,ts_ind] = np.log10(trigger)\n",
      "/Users/Zargham/Documents/GitHub/conviction/conviction_helpers.py:191: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  demo_data_Z2[sof_ind,ts_ind] = trigger/tc #share of maximum possible conviction\n",
      "/Users/Zargham/Documents/GitHub/conviction/conviction_helpers.py:192: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  demo_data_Z3[sof_ind,ts_ind] = np.log10(trigger/tc)\n"
     ]
    }
   ],
   "source": [
    "dict1 = trigger_sweep('token_supply',trigger_threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.15940000000000001, 1008990000.0, 'fixed alpha = 0.5')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "trigger_plotter(dict1['share_of_funds'],\n",
    "                dict1['log10_trigger'], \n",
    "                'log10_trigger',\n",
    "                dict1['total_supply'],\n",
    "                'Token Supply')\n",
    "axis = plt.axis()\n",
    "plt.text(.2*axis[0]+.8*axis[1],axis[-1]*1.01, 'fixed alpha = 0.5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "dict2 = trigger_sweep('alpha',trigger_threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['log10_trigger', 'trigger', 'share_of_max_conv', 'log10_share_of_max_conv', 'alpha', 'share_of_funds'])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict2.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "trigger_plotter(dict2['share_of_funds'],\n",
    "                dict2['log10_share_of_max_conv'], \n",
    "                'Log10 Share of Conviction Required to Pass',\n",
    "                dict2['alpha'],\n",
    "                'alpha')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "n= 35 #initial participants\n",
    "m= 5 #initial proposals\n",
    "\n",
    "initial_sentiment = .7\n",
    "\n",
    "network, initial_funds, initial_supply, total_requested = initialize_network(n,m,total_funds_given_total_supply,trigger_threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "theta =.35\n",
    "kappa = 2\n",
    "sale_price = .1\n",
    "\n",
    "initial_reserve, invariant, initial_price= initialize_bonding_curve(initial_supply, initial_price = sale_price, kappa =kappa, theta = theta)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "proposals = get_nodes_by_type(network, 'proposal')\n",
    "participants = get_nodes_by_type(network, 'participant')\n",
    "\n",
    "supporters = get_edges_by_type(network, 'support')\n",
    "influencers = get_edges_by_type(network, 'influence')\n",
    "competitors = get_edges_by_type(network, 'conflict')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200248.2765906408"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "initial_reserve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'type': 'proposal',\n",
       " 'conviction': 0,\n",
       " 'status': 'candidate',\n",
       " 'age': 0,\n",
       " 'funds_requested': 17166.01391645285,\n",
       " 'trigger': inf}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sample proposal\n",
    "network.nodes[proposals[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'type': 'participant',\n",
       " 'holdings': 365.06034882214334,\n",
       " 'sentiment': 0.027116327731857126}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sample participant\n",
    "network.nodes[participants[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'affinity': 0.8537642133854632,\n",
       " 'tokens': 0,\n",
       " 'conviction': 0,\n",
       " 'type': 'support'}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sample relationship participant to proposal\n",
    "network.edges[supporters[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'influence': 4.7628180580485715, 'type': 'influence'}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "network.edges[influencers[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'conflict': 0.8098865280206033, 'type': 'conflict'}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "network.edges[competitors[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Participants Social Network')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nx.draw_kamada_kawai(network, nodelist = participants, edgelist=influencers)\n",
    "plt.title('Participants Social Network')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Proposals Conflict Network')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nx.draw_kamada_kawai(network, nodelist = proposals, edgelist=competitors, node_color='b')\n",
    "plt.title('Proposals Conflict Network')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Histogram of Participants Token Holdings')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([ network.nodes[i]['holdings'] for i in participants])\n",
    "plt.title('Histogram of Participants Token Holdings')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Histogram of Proposals Funds Requested')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([ network.nodes[i]['funds_requested'] for i in proposals])\n",
    "plt.title('Histogram of Proposals Funds Requested')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "affinities = np.empty((n,m))\n",
    "for i_ind in range(n):\n",
    "    for j_ind in range(m):\n",
    "        i = participants[i_ind]\n",
    "        j = proposals[j_ind]\n",
    "        affinities[i_ind][j_ind] = network.edges[(i,j)]['affinity']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 96.12857142857142, 'participant_id')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dims = (20, 5)\n",
    "fig, ax = plt.subplots(figsize=dims)\n",
    "\n",
    "sns.heatmap(affinities.T,\n",
    "            xticklabels=participants,\n",
    "            yticklabels=proposals,\n",
    "            square=True,\n",
    "            cbar=True,\n",
    "            ax=ax)\n",
    "\n",
    "plt.title('affinities between participants and proposals')\n",
    "plt.ylabel('proposal_id')\n",
    "plt.xlabel('participant_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.8]\n"
     ]
    }
   ],
   "source": [
    "#power of 1 token forever\n",
    "conviction_capactity = [5]\n",
    "alpha = [1-1/cc for cc in conviction_capactity]\n",
    "print(alpha)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "params= {\n",
    "    'sensitivity': [.75],\n",
    "    'tmin': [7], #unit days; minimum periods passed before a proposal can pass\n",
    "    'min_supp':[50], #number of tokens that must be stake for a proposal to be a candidate\n",
    "    'sentiment_decay': [.01], #termed mu in the state update function\n",
    "    'alpha': alpha,\n",
    "    'base_completion_rate': [100],\n",
    "    'base_failure_rate': [200],\n",
    "    'trigger_func': [trigger_threshold],\n",
    "    'kappa': [2], #bonding curve curvature\n",
    "    'invariant': [invariant], #set by bonding curve choices\n",
    "    'tax_rate': [.02]\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "function"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(trigger_threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
    "# Settings of general simulation parameters, unrelated to the system itself\n",
    "# `T` is a range with the number of discrete units of time the simulation will run for;\n",
    "# `N` is the number of times the simulation will be run (Monte Carlo runs)\n",
    "time_periods_per_run = 200\n",
    "monte_carlo_runs = 1\n",
    "\n",
    "from cadCAD.configuration.utils import config_sim\n",
    "simulation_parameters = config_sim({\n",
    "    'T': range(time_periods_per_run),\n",
    "    'N': monte_carlo_runs,\n",
    "    'M': params\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'N': 1,\n",
       "  'T': range(0, 200),\n",
       "  'M': {'sensitivity': 0.75,\n",
       "   'tmin': 7,\n",
       "   'min_supp': 50,\n",
       "   'sentiment_decay': 0.01,\n",
       "   'alpha': 0.8,\n",
       "   'base_completion_rate': 100,\n",
       "   'base_failure_rate': 200,\n",
       "   'trigger_func': <function __main__.trigger_threshold(requested, funds, supply, beta=0.2, rho=0.020000000000000004)>,\n",
       "   'kappa': 2,\n",
       "   'invariant': 4739.604179660138,\n",
       "   'tax_rate': 0.02}}]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulation_parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "initial_conditions = {'network':network,\n",
    "                      'supply': initial_supply,\n",
    "                      'funds':initial_funds,\n",
    "                      'reserve': initial_reserve,\n",
    "                      'spot_price': initial_price,\n",
    "                      'sentiment': initial_sentiment}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'network': <networkx.classes.digraph.DiGraph at 0x1a2322a9e8>,\n",
       " 'supply': 30807.427167790895,\n",
       " 'funds': 77018.56791947722,\n",
       " 'reserve': 200248.2765906408,\n",
       " 'spot_price': 12.999999999999998,\n",
       " 'sentiment': 0.7}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "initial_conditions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
    "# The Partial State Update Blocks\n",
    "partial_state_update_blocks = [\n",
    "    { \n",
    "        'policies': { \n",
    "            #new proposals or new participants\n",
    "            'random': driving_process\n",
    "        },\n",
    "        'variables': {\n",
    "            'network': update_network,\n",
    "            'funds':increment_funds,\n",
    "            'supply':increment_supply\n",
    "        }\n",
    "    },\n",
    "    {\n",
    "      'policies': {\n",
    "          'completion': check_progress #see if any of the funded proposals completes\n",
    "        },\n",
    "        'variables': { # The following state variables will be updated simultaneously\n",
    "            'sentiment': update_sentiment_on_completion, #note completing decays sentiment, completing bumps it\n",
    "            'network': complete_proposal #book-keeping\n",
    "        }\n",
    "    },\n",
    "        {\n",
    "      'policies': {\n",
    "          'release': trigger_function #check each proposal to see if it passes\n",
    "        },\n",
    "        'variables': { # The following state variables will be updated simultaneously\n",
    "            'funds': decrement_funds, #funds expended\n",
    "            'sentiment': update_sentiment_on_release, #releasing funds can bump sentiment\n",
    "            'network': update_proposals #reset convictions, and participants sentiments\n",
    "                                        #update based on affinities\n",
    "        }\n",
    "    },\n",
    "    { \n",
    "        'policies': { \n",
    "            #currently naive decisions; future: strategic\n",
    "            'participants_act': participants_decisions, #high sentiment, high affinity =>buy\n",
    "                                                        #low sentiment, low affinities => burn\n",
    "                                                        #assign tokens to top affinities\n",
    "        },\n",
    "        'variables': {\n",
    "            'supply': update_supply, #book-keeping from participants decisions\n",
    "            'reserve': update_reserve, #funds under the bonding curve\n",
    "            'spot_price': update_price, #new bonding curve spot price\n",
    "            'funds': update_funds, #capture taxes\n",
    "            'network': update_tokens #update everyones holdings \n",
    "                                    #and their conviction for each proposal\n",
    "        }\n",
    "    }\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cadCAD.configuration import append_configs\n",
    "# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n",
    "# The configurations above are then packaged into a `Configuration` object\n",
    "append_configs(\n",
    "    initial_state=initial_conditions, #dict containing variable names and initial values\n",
    "    partial_state_update_blocks=partial_state_update_blocks, #dict containing state update functions\n",
    "    sim_configs=simulation_parameters #dict containing simulation parameters\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tabulate import tabulate\n",
    "from cadCAD.engine import ExecutionMode, ExecutionContext, Executor\n",
    "from cadCAD import configs\n",
    "import pandas as pd\n",
    "\n",
    "exec_mode = ExecutionMode()\n",
    "multi_proc_ctx = ExecutionContext(context=exec_mode.multi_proc)\n",
    "run = Executor(exec_context=multi_proc_ctx, configs=configs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "multi_proc: [<cadCAD.configuration.Configuration object at 0x1a23d80748>]\n",
      "[<cadCAD.configuration.Configuration object at 0x1a23d80748>]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/Zargham/Documents/GitHub/conviction/bonding_curve_eq.py:56: RuntimeWarning: invalid value encountered in double_scalars\n",
      "  realized_price = quantity_recieved/deltaS\n"
     ]
    }
   ],
   "source": [
    "i = 0\n",
    "verbose = False\n",
    "results = {}\n",
    "for raw_result, tensor_field in run.execute():\n",
    "    result = pd.DataFrame(raw_result)\n",
    "    if verbose:\n",
    "        print()\n",
    "        print(f\"Tensor Field: {type(tensor_field)}\")\n",
    "        print(tabulate(tensor_field, headers='keys', tablefmt='psql'))\n",
    "        print(f\"Output: {type(result)}\")\n",
    "        print(tabulate(result, headers='keys', tablefmt='psql'))\n",
    "        print()\n",
    "    results[i] = {}\n",
    "    results[i]['result'] = result\n",
    "    results[i]['simulation_parameters'] = simulation_parameters[i]\n",
    "    i += 1\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = results[0]['result']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a251794e0>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.supply.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a23a9ce80>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.reserve.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a30a74c50>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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u07YLVUREUqlF5wCcc9c2U/468HpKIxIRkXahS0GIiASUrwnAzCaZ2bOVlZV+hiEiEki+JgDn3KvOudsKCgr8DENEJJDUBSQiElBKACIiAaUEICISUEoAIiIBpQQgIhJQSgAiIgGl3wGIiASUfgcgIhJQrbkfQMps3Lmf6557HwDnwOFi0+DdZJjY9MHXws6xe38dJV/pmjCvizxxSes4UBti0PH59CnMTZrfW6/36BXElx+MK67MHdxWbLmkdRF9valtxGKLlCW9Hr/thG0lxOIa1U1z6yI+pmbW1VT9N66b5HU7/rGnmuM659CnMM/7LJLqpak62VpVwwkFeZiBYZhBhoGZYUQejcg0ZGVkcMZJhYzs353OOWnxtRXp8NLif1LYOepCYSxyixnDYrebsehfRqQ80lgArN66l+O75VKxp8ZrLOKWt7jlMWN/bYj12/exbNOXLYrpYONjsTvfRBsr4hqm6Lai8x7cJk00ZBZbLvoG7XDrssRtN4qriW3Hz0vSdpPrKFo/lhDLId5zBhgZsXVt2VNDv6IuLN24mzXb9rJk/c7DxlpVEyI70+iUlYmRmJDCLjG5OAeh8MH7Bd09YTDfuaCkRZ+hiBxaWiSAgT27Mv9/f7XNtxNqCNPgXGLjR3ID2dSNzsRP1XUNfLa1ique/n+s2bqXv67d0egIKPHoJ/EIBxofjQzo0ZWhvbv596ZE0kBaJID2kpWZEaw3fIzIy8nkzJOOIz83m4WfVLDwk9bfeO4r+Z1Yet+FKYhOpONSeygdxmt3jGFrVU1CN1pT3WuJ3V9x3VGR6dl/+Zw/fPwPvvrvf4qtO/6m1C7uSfR8SEMYDtSF6NG1E2MH9+TBycPa9s2KtAMlAOkwTuzemRO7d271eqaO7k9WhsUa/fhOv/gewOiZEDOorm9gRXklG3fu58X3NvHXtTuAwyeO5PKmnh8sj1sm8hh2jvoGR152Jqf0ym+8TNOrarS+li7TpVMWP75iOAV52YeYq/Wcc4Rd43M/3muR53HzxXfzheO695IHWcTWmTSAIRQOY2ax18LR+cNJ641bf7fcLEq+0rjOjyVKABI4w/sW8LNvnH5Uy67eWsUzf9lAOK5xTUwg1mQ5SaeWLK4gMemQUB528OfV2ynsnM22vTVNxmTJK09aR9PLNPZJufd7nEUrtnBCQW7SCXmAgyfl99bUk2FG55zMhPMu4bhGN3k0WHwj31FkGPTM7wTQZF14UwcTUajBsa82RN/j8g47GMLMvJFvSQM29teGMIP83Cz+z0WDk0bQHdxeTlbrR/ErAYgcgVN6dePRb47wO4w2sa82xM8Wr2Z/XQMGZNjBrrNod1uGeY3c3poQPbrmxI1yizRmzQzlzbDEUWfxDV90+G/kJW/euGk4uM7YUOGE7SRtn8TXK6vrOa5LdiSGg9uOjze6zYzIaMOqmnre/HQbXTplNupSTOx6jJRHyjbu3O8ljBYM3U4+AnFAXShMRUOYddv3AXDTCx+05UeONXeY2B7MbBIwqaSk5NZ169b5FoeISDoJNYT5tKKKsHNJw8e9ZFMfDrNrXx3jT+213DlXerTb8TUBRJWWlrply5b5HYaISIdiZq1KALoYnIhIQCkBiIgElBKAiEhAKQGIiASUEoCISEApAYiIBJQSgIhIQCkBiIgElBKAiEhA6abwIiIBpZvCi4gElLqAREQCSglARCSglABERAJKCUBEJKCUAEREAkoJQEQkoJQAREQCSglARCSglABERAJKCUBEJKCUAEREAirLz42b2SRgUklJiZ9hiIikld01u3lr01vUh+tpCDcQdmEaXOJjVkbrm29fE4Bz7lXg1dLS0lv9jENEJF1U1lYydfFUPq/8vM235WsCEBE51lTVVbFyx0rMDByECeOcw+EIuzBhF8bhcC7ynDA42HZgGwCLNy5m897NPH3h0wwrGkZGRgaZlkmGJT6aGfZta1WsSgAiIkl2Vu9k3pp5VNdXxxrwaNeLc65R2Rd7vyAnI4ct+7ewee/mVm07Pzufn3ztJ4zpMyZF76Z5SgAickyK7WFH9rIbwg04vEY7FA5xoP5Ak33rK3eu5KmPnmJ3zW5ys3IxLLbHnWEZB//IwMx7DaC2oZbSXqVcPvByenftTZ+ufcgwb5xNdBkzw/DWY5i3TrzXMOjeqTsFnQq8o4d2oAQgIoDXgM1dPZcDoQMJjWesuyKy1xstB2LTdeE6dtfsprBT4cHGNJzYuJZVldEzrycNriG29xy/Fx1tqDdVbqJn554J649uPzod7U5JLq9pqAHAMByuVfUxf9J8Bncf3LpKTXNKACICwNzVc3l42cOx5432VKN7sXF7rtFyh6MmVEOmZVLYqdDrp85I7LfulNmJjZUb6detH1kZWeRYTmzPOv6xX34/dtXs4sT8E2MxRPeeo9tsqjy6F72rehcndDkhcW898pdpmd4efUYm++v3x+aL71s/EDrA2BPHkp+T7+On0T6UAESEuoY6Xvz0RUb2Gslz45+LNfJybNMPwUSERRsWsb16OzcPuzm2Vy3HPh0BiKS5TVWb2FW9K3byssE10BBuoLqhmppQDdWhavbX72f17tXsq9vX6KRmtD/+i31fUJRblDgEMfJXsb+CId2HMKr3KL/frrQjJQCRoxQ/jjvhZGWkLL6RrQ/XJ8wTGxMeGQMev0zIhaiqrWJf/T7eLHuTxWWLWxRPn6596J7bPaFPOycjx+v/zsige153dhzYwYn5JzYa1ZJpmXzzlG9qzz9glABEjsCCtQv44fs/JORC7bI9w/jn0/6Zs44/i6yMLDItk8yMTLIsi8yMTBpcA50yOtE9rzvdc7u3S0xy7FACEDkCv139W/rk9+GS/pckjIKJjo5J3rOOjlapbaglKyOLrtldG40FbzQ+3IyaUA098nowoGBAbEikSKopAYi00Jrda1j75VruHXkv1w25zu9wRFpNo4BEWmjRxkVkWRYX97/Y71BEUsLXBGBmk8zs2crKSj/DEDms+nA9r294ndF9RquvXY4Zuhy0BM6XNV/yxsY3yMvKS7xCY9xlBeLLyqrKWLp1KdsObOPekff6Hb5IyugcgATOtxd/mw2VG45omYEFA3li3BOMPXFs2wQl4gMlAAmcrtld6dO1D89PeL7RSJzkqzxGy/Oy8vwOWyTllAAkUJxzrN+znsklk+ndtbff4Yj4SqOAJFAq9ldwIHSAQccN8jsUEd8pAUigrP9yPQCDCpUARJQAJFDW7VkHQElhic+RiPhPCUACZe2Xa+ndpTddc7r6HYqI75QAJFDW71lPyXHa+xcBJQAJkPpwPRsrN6r/XyRCw0AlrTnnePD9B5m/dj7dc7sn3I8Wa3zfWsC7NyxQVVdFUW4R+Tn5GEb5vnJC4ZCOAEQilADEd1v2bWFf/T6yM7Ib3cT7mRXPMH/tfHrm9WTsiWNjd7MC7yYq0ecJjziqaqv4suZLunXqFptvYMFAhhUNY3Tv0T6/Y5H0oAQgrVbbUMsjyx5hc9Vmjss9LmFvPDod/whgZoTCIf6w/g+HXf+UQVOYNWqW7lYlkmJKANJqP1n6E+avnc9xnY6jc3ZngIS98ei09+9g2a6aXQzpPoShRUM554RzEi7CFnZhqkPV5GXlMblkshp/kTYQmASw48AOfrDkB+ys3gmQuDcat1canY4+T3g9ac82OmuzrzexnoTpgytg+4HtFHcrjl1/JtMyycjwHjMtk6q6KvJz8snNzG1yjzq+HzwaW/SaNvHvLzZfZJ7d1bs5vsvxjeorfplG7yfuteXblvP2F29z06k38f3S77f48xAR/wUiAYRdmHuX3Msn2z9hdJ/RsT7k6N5o5EmjssPOF/d67DHu9abmc+7g82hZ+d5yivKKqNhXQYNroME1EHZhGsLe9N66vdSEauiS0wXDYn3ayXvUh3yM3xNPsXNPOJc7zrwj5esVkbbVYRNAZW0lr37+KhX7K2JlyXv04O2lLvx8IbtrdjNr1CyuPPnKdo813cQnhwbX4JXFJYZGic01Thrxr3XJ7qIuGpEOKC0SwJov13D+vPOBpJOGkW6K5DKHY8v+LQDkZeXFGvzm9m6rQ9Vc1O8ipgya0j5vKM3FdxNlkul3OCLik7RIAN1yunHhSRcmdFUATXZlgNdfPu6kcVxRcgWDuw/2M3QRkQ4rLRLACV1OYOaomX6HISISKLopvIhIQPmaAJxzrzrnbisoKPAzDBGRQNLF4EREAkoJQEQkoJQAREQCSglARCSglABERAJKCUBEJKCsqeu8tHsQZnuBNX7H0QI9gJ1+B9ECHSHOjhAjKM5UU5ypNdg5l3+0C6fFL4GBNc65Ur+DOBwzW6Y4U6MjxAiKM9UUZ2qZ2bLWLK8uIBGRgFICEBEJqHRJAM/6HUALKc7U6QgxguJMNcWZWq2KMy1OAouISPtLlyMAERFpZ35fDvpiM1tjZuvNbIafscQzsxPN7G0z+8zMPjWz6ZHyWWb2DzP7OPJ3aRrEWmZmKyPxLIuUdTez/zazdZHH43yOcXBcnX1sZlVmdmc61KeZPW9m283s73FlTdafeR6PfF9XmNmZPsf5MzNbHYnl92ZWGCkvNrPquHqd7XOczX7OZnZvpD7XmNkEH2OcFxdfmZl9HCn3sy6ba4dS9/2M3qS8vf+ATOBzYACQA3wCDPUrnqTYTgDOjEznA2uBocAs4C6/40uKtQzokVT2U2BGZHoG8JDfcSZ97luBfulQn8B5wJnA3w9Xf8ClwBuAAecCf/M5zvFAVmT6obg4i+PnS4P6bPJzjvyf+gToBPSPtAeZfsSY9PojwP1pUJfNtUMp+376eQQwEljvnNvgnKsD5gKTfYwnxjm3xTn3YWR6L/AZ0MffqI7IZOA/I9P/CfwvH2NJ9nXgc+fcJr8DAXDO/RXYnVTcXP1NBl50nveBQjM7wa84nXNvOudCkafvA33bI5ZDaaY+mzMZmOucq3XObQTW47ULbepQMZqZAVcDL7V1HIdziHYoZd9PPxNAH+CLuOflpGEja2bFwBnA3yJFt0cOr573u2slwgFvmtlyM7stUna8c24LeF8i4Cu+RdfYNST+50q3+oTm6y+dv7NT8fb+ovqb2Udm9hcz+5pfQcVp6nNOx/r8GrDNObcursz3ukxqh1L2/fQzAVgTZWk1JMnMugILgDudc1XA08BAYASwBe9Q0W+jnXNnApcA3zGz8/wOqDlmlgNcDvwuUpSO9XkoafmdNbP7gBDwm0jRFuAk59wZwPeB35pZN7/io/nPOR3r81oSd1B8r8sm2qFmZ22i7JD16WcCKAdOjHveF6jwKZZGzCwbr9J/45x7BcA5t8051+CcCwPP0Q6Hq4fjnKuIPG4Hfo8X07booV/kcbt/ESa4BPjQObcN0rM+I5qrv7T7zprZt4DLgOtdpCM40qWyKzK9HK9v/WS/YjzE55xW9WlmWcAUYF60zO+6bKodIoXfTz8TwAfAIDPrH9kzvAZY6GM8MZF+wP8APnPO/TyuPL4/7Qrg78nLticz62Jm+dFpvJOCf8erx29FZvsW8Ed/ImwkYe8q3eozTnP1txD4p8hoi3OByuihuB/M7GLgHuBy59yBuPKeZpYZmR4ADAI2+BPlIT/nhcA1ZtbJzPrjxbm0veOLcyGw2jlXHi3wsy6ba4dI5ffTj7PbcWe5L8U7s/05cJ+fsSTFNQbv0GkF8HHk71Lg/wIrI+ULgRN8jnMA3iiKT4BPo3UIFAF/AtZFHrunQZ12BnYBBXFlvtcnXkLaAtTj7UHd3Fz94R1iPxX5vq4ESn2Ocz1en2/0Ozo7Mu+Vke/DJ8CHwCSf42z2cwbui9TnGuASv2KMlL8ATEua18+6bK4dStn3U78EFhEJKP0SWEQkoJQAREQCSglARCSglABERAJKCUBEJKCUAOSYYGaFZvYvkeneZja/Dbc1wtLgSrAiraUEIMeKQuBfwPt1tHPuqjbc1gi88dgiHZp+ByDHBDOLXk12Dd4PZIY454aZ2bfxrpaYCQzDuw5NDnAjUAtc6pzbbWYD8X5E0xM4ANzqnFttZt8A/hVoACrxfi26HsgD/gH8O/Aa8AQwHMgCZjnn/hjZ9hUcvNzxb51zD7RxVYi0WJbfAYgLw7PHAAABsklEQVSkyAxgmHNuROTKia/FvTYM70qKuXiN9z3OuTPM7FHgn4DH8O6tOs05t87MzgF+CYwD7gcmOOf+YWaFzrk6M7sf71eWtwOY2Y+BPzvnppp3U5alZvZWZNsjI9s/AHxgZoucc8vasiJEWkoJQILgbeddT32vmVUCr0bKVwKnRa62+FXgd97lVwBvrx3gXeAFM3sZeIWmjQcuN7O7Is9zgZMi0//tIhcTM7NX8H7erwQgaUEJQIKgNm46HPc8jPd/IAPY45wbkbygc25a5IhgIvCxmTWaB+8aLFc659YkFHrLJfexqs9V0oZOAsuxYi/ebfOOmPOusb4x0t8fvbfq6ZHpgc65vznn7gd24l1uN3lb/wXcEbl6I2Z2RtxrF5l3D9c8vHMR7x5NjCJtQQlAjgmRbpZ3zbvR98+OYhXXAzebWfTKqtHbk/7MzFZG1vtXvKtCvg0MNe8m4d8E/g3IBlZE5vu3uPUuwbsa5sfAAvX/SzrRKCCRNhIZBRQ7WSySbnQEICISUDoCEBEJKB0BiIgElBKAiEhAKQGIiASUEoCISEApAYiIBJQSgIhIQP1/KalXgZ1a1acAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(x='timestep', y=['funds', 'reserve','supply'], logy=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a31087ac8>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.sentiment.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a3709a6d8>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(x='timestep', y='funds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pad(vec, length,fill=True):\n",
    "    \n",
    "    if fill:\n",
    "        padded = np.zeros(length,)\n",
    "    else:\n",
    "        padded = np.empty(length,)\n",
    "        padded[:] = np.nan\n",
    "        \n",
    "    for i in range(len(vec)):\n",
    "        padded[i]= vec[i]\n",
    "        \n",
    "    return padded\n",
    "\n",
    "def make2D(key, data, fill=False):\n",
    "    maxL = data[key].apply(len).max()\n",
    "    newkey = 'padded_'+key\n",
    "    data[newkey] = data[key].apply(lambda x: pad(x,maxL,fill))\n",
    "    reshaped = np.array([a for a in data[newkey].values])\n",
    "    \n",
    "    return reshaped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['conviction'] = df.network.apply(lambda g: np.array([g.nodes[j]['conviction'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate']))\n",
    "df['candidate_count'] = df.network.apply(lambda g: len([j for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate']))\n",
    "df['candidate_funds'] = df.network.apply(lambda g: np.sum([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate']))\n",
    "df['killed_count'] = df.network.apply(lambda g: len([j for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='killed']))\n",
    "df['killed_funds'] = df.network.apply(lambda g: np.sum([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='killed']))\n",
    "df['candidate_funds_requested'] = df.network.apply(lambda g: np.array([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate']))\n",
    "df['active_count'] = df.network.apply(lambda g: len([j for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='active']))\n",
    "df['active_funds'] = df.network.apply(lambda g: np.sum([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='active']))\n",
    "df['failed_count'] = df.network.apply(lambda g: len([j for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='failed']))\n",
    "df['failed_funds'] = df.network.apply(lambda g: np.sum([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='failed']))\n",
    "df['completed_count'] = df.network.apply(lambda g: len([j for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='completed']))\n",
    "df['completed_funds'] = df.network.apply(lambda g: np.sum([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='completed']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['funds_requested'] = df.network.apply(lambda g: np.array([g.nodes[j]['funds_requested'] for j in get_nodes_by_type(g, 'proposal')]))\n",
    "df['share_of_funds_requested'] = df.candidate_funds_requested/df.funds\n",
    "\n",
    "df['share_of_funds_requested_all'] = df.funds_requested/df.funds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['triggers'] = df.network.apply(lambda g: np.array([g.nodes[j]['trigger'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate' ]))\n",
    "df['conviction_share_of_trigger'] = df.conviction/df.triggers\n",
    "df['age'] = df.network.apply(lambda g: np.array([g.nodes[j]['age'] for j in get_nodes_by_type(g, 'proposal') if g.nodes[j]['status']=='candidate' ]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['age_all'] = df.network.apply(lambda g: np.array([g.nodes[j]['age'] for j in get_nodes_by_type(g, 'proposal') ]))\n",
    "df['conviction_all'] = df.network.apply(lambda g: np.array([g.nodes[j]['conviction'] for j in get_nodes_by_type(g, 'proposal') ]))\n",
    "df['triggers_all'] = df.network.apply(lambda g: np.array([g.nodes[j]['trigger'] for j in get_nodes_by_type(g, 'proposal')  ]))\n",
    "\n",
    "df['conviction_share_of_trigger_all'] = df.conviction_all/df.triggers_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "rdf= df[df.substep==4].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "last_net= df.network.values[-1]\n",
    "last_props=get_nodes_by_type(last_net, 'proposal')\n",
    "M = len(last_props)\n",
    "last_parts=get_nodes_by_type(last_net, 'participant')\n",
    "N = len(last_parts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1a3316aa20>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rdf.plot(x='reserve', y='supply', kind='scatter', alpha=.5)\n",
    "axis = plt.axis()\n",
    "xrange = np.arange(axis[0], axis[1], (axis[1]-axis[0])/100)\n",
    "yrange = np.array([supply(x, invariant, kappa) for x in xrange ])\n",
    "plt.plot(xrange, yrange, 'y')\n",
    "plt.title('Bonding Curve Invariant')\n",
    "plt.legend(['Invariant', 'Observed Data'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "affinities = np.empty((N,M))\n",
    "for i_ind in range(N):\n",
    "    for j_ind in range(M):\n",
    "        i = last_parts[i_ind]\n",
    "        j = last_props[j_ind]\n",
    "        affinities[i_ind][j_ind] = last_net.edges[(i,j)]['affinity']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 204.0, 'participant_id')"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 7200x1800 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dims = (100, 25)\n",
    "fig, ax = plt.subplots(figsize=dims)\n",
    "\n",
    "sns.heatmap(affinities.T,\n",
    "            xticklabels=last_parts,\n",
    "            yticklabels=last_props,\n",
    "            square=True,\n",
    "            cbar=True,\n",
    "            ax=ax)\n",
    "\n",
    "plt.title('affinities between participants and proposals')\n",
    "plt.ylabel('proposal_id')\n",
    "plt.xlabel('participant_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "#working on deduplicating colors\n",
    "#\n",
    "#last_props=get_nodes_by_type(last_net, 'proposal')\n",
    "#M = len(last_props)\n",
    "\n",
    "#cm = plt.get_cmap('gist_rainbow')\n",
    "#c= [cm(1.*j/M) for j in range(M)] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  1.,   1.,   1., ...,  nan,  nan,  nan],\n",
       "       [  2.,   2.,   2., ...,  nan,  nan,  nan],\n",
       "       [  3.,   3.,   3., ...,  nan,  nan,  nan],\n",
       "       ...,\n",
       "       [198., 198., 198., ...,  29.,  13.,   8.],\n",
       "       [199., 199., 199., ...,  30.,  14.,   9.],\n",
       "       [200., 200., 200., ...,  31.,  15.,  10.]])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "make2D('age_all', rdf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Proposal Status')"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rdf.plot(x='timestep',y=['candidate_count','active_count','completed_count', 'killed_count', 'failed_count'])\n",
    "plt.title('Proposal Status')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Proposal Status weighted by funds requested')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rdf.plot(x='timestep',y=['candidate_funds','active_funds','completed_funds', 'killed_funds', 'failed_funds'])\n",
    "plt.title('Proposal Status weighted by funds requested')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'share_of_funds_requested')"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(rdf.timestep,make2D('share_of_funds_requested_all', rdf))\n",
    "plt.title('share_of_funds_requested by proposal')\n",
    "plt.xlabel('time $t$')\n",
    "plt.ylabel('share_of_funds_requested')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'share_of_funds_requested')"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.loglog(make2D('share_of_funds_requested_all', rdf), make2D('conviction_all', rdf), '.')\n",
    "plt.ylabel('conviction')\n",
    "plt.xlabel('share_of_funds_requested')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'proposal_age')"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(make2D('age_all', rdf), make2D('triggers_all', rdf))\n",
    "plt.ylabel('triggers')\n",
    "plt.xlabel('proposal_age')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'phase: Triggers & Conviction')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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k1KhRdevdNR62/e5TknrHMSNzZBgj7XwsyRhjTBPOnTtHdnY2xcXFdRNaxsbG3lXn8IZLFN4sZ8VrU4jtYV+r/uy3YYwxAVRUVLBhwwaOHj1aN6HlkCFDGtS7fb2UwxsuM3Z6P4ZNSgtDpJ2bJRljjKnn1KlTrF27loqKCh566CEeeuihgBNaejzKtt9+SmyPaOY8NSYMkXZ+XTbJiEgisBN4XVXXhDseY0znV1JSwrp16/jkk08YMGAAL774Iv3792+0/okd17h1sZhFL08gPjm20XrdWUiTjIj0An4JTAIUeEVV97ainTeBFUCuqk6qt24p8CMgCvilqv7At+obwLttCN8Y002oKkeOHGHjxo24XC4WL17MzJkzcTgcjW5TUlDJvv86z5CJqYyd0Xgi6u5CPZL5EbBBVZ8UkVjgrodXi0hfoEJVS/zKRqvquXrtvAX8BPhNve2jgJ8Ci4Ec4KCIOIGBwCmgR/vujjGmqyksLCQ7O5sLFy4wbNgwMjMzSUsLfG5FVSm7U03elWKObL6KqjL/uXERfy9LKIUsyYhICvAQ8DKAqlYD1fWqzQO+KiLLVLVSRF4FngCW+VdS1Z0iMjxAN9OBc6p6wdfnO8BjQBKQCEwEKkRknapG3iPljDEh4/F46ia0FBGWL19ORkZGXcLwJpQqci+XkHfF+8q9UkJFsfdrTATmPTeOlPT4cO5GpxfKkcxIIA/4NxGZAhwGvq6qZbUVVPU9ERkBvCMi7wGv4B2VBGsQcNVvOQeYoaqvAYjIy0B+oARjT8Y03VnBjTIOZF/wLuhdPxosqDZ8hkmAorrCxtsJVBiob228j+baCbBNoPiLSgs5eHIHt+/con/6UB4YP4cr2xxc2Xa4rp3i/AoqSmoAb0LpPSCRoRNT6TM0mb5Dk0kfkkxMXOefoDLcQplkooH7ga+p6n4R+RHwP4G/9q+kqj/0jUDeAEapamkL+gg0Rv3sI6j6VmMb2pMxTXfmqnZTcKO8bjnQ0Z67y+SuH41v07Aw4JEkv8Km+26kXgv6risXcHvcfHrxKCfPf0R0VAyzpj7MsAFj7tq29u2wSWn0GZpC32HJpA1OIiYCZjzujEKZZHKAHFXd71t+H2+SuYuIzMV7YcAfgdeB11rYh/+F64OB662K1phupO+wFJ57fUa4w+hQ169fJysri5r0WzwxbwHLli0jMTEx3GF1eSFLMqp6U0Suisg4VT0NPIz3ZHwdEZkK/AJYDlwEfici31fVbwfZzUFgjO+Q2zXgWeC5dtsJY0zEq6mpYfv27ezdu5fExESeffZZxo8fH+6wuo1QX132NeD3vivLLgCr661PAJ5S1fMAIvISvgsF/InI28B8IF1EcvDe+/IrVXWJyGvARryXML+pqidDtTPGmMhy+fJlnE4nt2/f5v777+eRRx6hRw+76LQjSaCTYt1JRkaGHjp0KNxhGGPaUVVVFZs3b+bgwYP07t2blStXMnKkTVzZnkTksKpmNFevy97xb4zpns6ePcuaNWsoLi5m5syZLFiwoMGElqbjWJIxxnQJ5eXlbNiwgWPHjtGnTx+++MUvMnjw4HCH1e1ZkjHGRDRV5eTJk6xfv56KigrmzZvH3LlzA05oaTqe/SsYYyJWSUkJa9as4fTp0wwcOJAvfOEL9OvXL9xhGT+WZIwxEUdV+fjjj9m0aRMul4tHHnmEBx98sMkJLU14WJIxxkSUwsJCnE4nFy9eZPjw4WRmZpKamhrusEwjLMkYYyKCx+Nh//79bN26FYfDwcqVK7n//vttBuROzpKMMabTy83Nxel0kpOTw9ixY1mxYgUpKSnhDssEwZKMMabTcrvd7N69m507dxIXF8fnP/95Jk2aZKOXCGJJxhjTKV27do2srCxyc3O59957Wbp0qU1oGYEsyRhjOpWamhq2bdvG3r17SU5OZtWqVYwbNy7cYZlWsiRjjOk0Ll26hNPppKCggIyMDBYtWmQTWkY4SzLGmLCrrKzkgw8+4PDhw6SmpvLSSy8xYsSIcIdl2oElGWNMWJ05c4Y1a9ZQUlLCrFmzWLBgATExMeEOy7QTSzLGmLAoKytjw4YNHD9+nH79+vHMM88waNCgcIdl2lm3TTIishJYOXr06HCHYky3oqqcOHGC9evXU1VVxYIFC5gzZw5RUVHhDs2EQLdNMqqaDWRnZGS8Gu5YjOkuiouLWbNmDWfOnGHw4MFkZmbSt2/fcIdlQqjbJhljTMdRVQ4fPswHH3yAx+NhyZIlzJgxwya07AYsyRhjQqqgoACn08mlS5cYMWIEmZmZ9O7dO9xhmQ5iScYYExIej4d9+/axdetWoqKiyMzMZOrUqTYlTDdjScYY0+5u3bpFVlYW169fZ9y4cSxfvtwmtOymLMkYY9qNy+Vi165d7Nq1i/j4eJ566ikmTpxoo5duzJKMMaZd5OTkkJWVRV5eHpMnT2bp0qUkJCSEOywTZpZkjDFtUl1dzbZt29i3bx/Jyck8//zzjBkzJtxhmU7CkowxptUuXLhAdnY2hYWFTJs2jUWLFhEXFxfusEwnYknGGNNilZWVbNq0iY8++oi0tDRWr17NsGHDwh2W6YQsyRhjWuTTTz9l7dq1lJWVMWfOHObNm2cTWppGWZIxxgSltLSU9evXc/LkSfr378+qVasYOHBguMMynZwlGWNMk1SV48ePs379eqqrq1m4cCGzZ8+2CS1NUCzJGGMaVVRUxJo1azh79ixDhgwhMzOTPn36hDssE0EsyRhjGlBVDh06xAcffICq8uijjzJt2jSb0NK0mCUZY8xdbt++jdPp5PLly4waNYoVK1bYhJam1SzJGGMA74SWe/bsYfv27URHR/P4448zZcoUmxLGtIklGWMMN2/eJCsrixs3bjBhwgSWLVtGcnJyuMMyXYAlGWO6MZfLxc6dO9m9ezcJCQk8/fTTTJw4MdxhmS6k2SQjIrOBI6paJiIvAPcDP1LVyyGPzhgTMlevXiUrK4v8/Hzuu+8+lixZQnx8fLjDMl1MMCOZN4ApIjIF+EvgV8BvgHmhDMwYExrV1dVs2bKFAwcOkJKSwgsvvMDo0aPDHZbpooJJMi5VVRF5DO8I5lci8lKoA2srEUkEdgKvq+qacMdjTGdw/vx5srOzKSoqYtq0aTz88MM2oaUJqWCSTImIfBN4AXhIRKKAoCcq8tU/BFxT1RWtCVJE3gRWALmqOqneuqXAj4Ao4Jeq+gPfqm8A77amP2O6moqKCjZu3MiRI0dIT09n9erVDB06NNxhmW4gmCTzDPAc8EVVvSkiQ4F/aEEfXwc+ARo8e1VE+gIVqlriVzZaVc/Vq/oW8BO8h+n8t48CfgosBnKAgyLiBAYCp4AeLYjTmC7pk08+Ye3atZSXlzN37lzmzZtHdLRd82M6RpOfNN+X+O9UdVFtmapeod6XfRPbDwaWA38L/HmAKvOAr4rIMlWtFJFXgSeAZf6VVHWniAwPsP104JyqXvD19w7wGJAEJAITgQoRWaeqnnqxrQRW2rFo01WVlpaybt06Tp06Rf/+/Xn++ecZMGBAuMMy3UyTSUZV3SJSLiI9VbWoFe3/M96LBQJecK+q74nICOAdEXkPeAXvqCRYg4Crfss5wAxVfQ1ARF4G8usnGF/f2UB2RkbGqy3oz5hOT1U5evQoGzdupKamhocffphZs2bZhJYmLIIZM1cCx0XkA6CstlBV/6ypjUSk9hzKYRGZ31g9Vf2hbwTyBjBKVUuDitzXTaAm/dp+qwVtGRPx7ty5Q3Z2NufPn2fo0KFkZmaSnp4e7rBMNxZMklnre7XUbCBTRJbhPTeSIiK/U9UX/CuJyFxgEvBH4HXgtRb0kQMM8VseDFxvRazGRDRV5cCBA2zZsgWAZcuWMW3aNJsSxoRds0lGVX8tIvHAUFU9HWzDqvpN4JsAvpHMfw+QYKYCv8B73uYi8DsR+b6qfjvIbg4CY3yH3K4Bz+K9SMGYbiM/Px+n08mVK1cYPXo0K1asoFevXuEOyxgguDv+VwL/C4gFRojIfcD3VDWzHfpPAJ5S1fO+vl4CXg4Qw9vAfCBdRHLw3vvyK1V1ichrwEa8lzC/qaon2yEuYzo9t9tdN6FlbGwsTzzxBJMnT7bRi+lURFWbriByGFgIbFfVqb6y46p6bwfEF3IZGRl66NChcIdhTIvcuHGDrKwsbt68ycSJE1m2bBlJSUnhDst0IyJyWFUzmqsX7B3/RfX+Omo6MxljQqKmpoYdO3awZ88eEhISeOaZZ5gwYUK4wzKmUcEkmRMi8hwQJSJjgD8D9oQ2LGNMfVeuXCErK4vbt28zdepUHnnkEZvQ0nR6wSSZrwF/BVQBb+M9//E3oQzKGPOZqqqqugkte/XqxYsvvsioUaPCHZYxQQnm6rJyvEnmr0IfjjHG37lz58jOzqa4uJgHH3yQhQsXEhsbG+6wjAlaMFeXZdPwHEwR3kkv/1VVK0MRmDHdWXl5ORs3buTo0aP06dOHV155hSFDhjS/oTGdTDCHyy4AffAeKgPvhJm3gLF473F5MTShGdP9qGrdhJYVFRU89NBDPPTQQzahpYlYwXxyp6rqQ37L2SKyU1UfEhG7J8WYdlJSUsK6dev45JNPGDhwIC+++CL9+/cPd1jGtEkwSaaPiAz1zb6Mb6r/2smQqkMWmTHdhKpy5MgRNm7ciMvlYvHixcycOROHwxHu0Ixps2CSzF8Au0XkPN4JKUcAf+J78uSvQxmcMV1dYWEh2dnZXLhwgWHDhpGZmUlaWlq4wzKm3QRzddk63/0x4/EmmU/9Tvb/cyiDM6ar8ng8dRNaOhwOVqxYwQMPPGBTwpguJ5iryz5Xr2ikiBQBx1U1NzRhGdN15eXl4XQ6uXr1KmPGjGHFihX07Nkz3GEZExLBHC77IjAT2Ip3JDMf2AeMFZHvqepvQxeeMV2H2+3mww8/ZMeOHcTFxfG5z32Oe++910YvpksLJsl4gAmqegtARPrhfcDYDGAnYEnGmGZcv36drKwsbt26xaRJk3j00UdJTEwMd1gRS9XD5cs/R8TBsGFfDnc4pgnBJJnhtQnGJxcYq6oFIlIToriM6RJqamrYvn07e/bsISkpiWeffZbx48eHO6yIV1Z2jvMX/oGU5MmWZDq5YJLMLhFZA7znW/48sNN3ddmdkEVmTIS7dOkSTqeTgoICHnjgARYvXkyPHj3CHVZAqsqe937PuAfnkD50eLjDaZbLVQzAyJF/HuZITHOCSTJ/ijexzMZ7TuY3wH+o90E0C0IYmzERqaqqig8++IBDhw7Ru3dvXnrpJUaMGBHusJpUnHeLff/xDmf2fcjqf3wj3OE0y+UqASA6OjnMkZjmBHMJswLv+17GmCacPXuW7OxsSkpKmDlzJgsWLIiICS179u3PvQsf4dzBfeEOpVGqHq5cfZP8/K2Ulp4CICbGHjPd2TWaZERkt6rOEZES7p4gU/DmnpSQR2dMhCgvL2fDhg0cO3aMPn368PTTTzN48OBwh9UiCT17UVlWiqqG9Iq36uoCbt3Kxu0uQ9WNqgfF+xN1e8vw+Na58Lir8HiqKC45QUXFJZKTJ9G790x69cwgPn5YyOI07aPRJKOqc3w/bTxqTCNUlZMnT7Ju3ToqKyuZP38+c+bMicgJLXskJaMeD+//7V+Td/kiFcVFLP/6XzJ+1kPNbxwEl6uUK1ff5MqVX+F2l9ZbK4hEIeIAourei0QT5eiBIyqO+B6DGDni6/Trt9Iu+44gTf6fIN5/8WOqOqmD4jEmYhQXF7N27VpOnz7NoEGDyMzMpF+/fh0eh/eIdu3BBm20DBStOybRcP3QyRNxxLjJ+fQwAI4Y2Pab/0NSeiL9RowJuE39fj5r3r/MQ+6ttVy6/DNqagro02cJI0d8nfj44b5kEmVJowsT1fqPiqlXQeT3wDdrJ8jsajIyMvTQoUPhDsO00ZEjqymvuOxb0rofeteXYm257wvyri/N+uV3b6P+X5qqnDlTzsGDRXg8ytSpyUycmIDDIY1s4xeTb/v6ZZ9tQ4OyxreJLKm95zBq1F+QkjI53KGYdiAih1U1o7l6wYzpBwAnReQAUFZbqKqZbYjPmHaVmDiG6JieeE8ZglD7l7FQ9xa5uxxAJMCbdApcAAAfNklEQVQ2teX1thHhzp0Ktm87S07OHUYMH8PChePp1Sve10TgbRr2fXf5Z30H2uaz2Nuyzd37ffc2/v/1eDx43G48bg/q8XD15DGufXqK+V941a+PQH0H+r1/Vj8pcSy9ejX7fWS6oGCSTBKwwm9ZgP8/NOEY0zpjxnwrpO17PB7279/P1q1bcTgeZPXqR7j//vu79GGemuoqPn73dW6f7sfQoa+EOxwToYJJMtGqusO/QETiQxRPu/HdLLoTeF1V14Q7HhO5cnNzycrK4tq1a4wdO5YVK1aQktL1L67c8+7vyTl1gplPrgp3KCaCNXUJ81eBP8E76/Ixv1XJwIfNNSwiPfB+ycf5+nlfVV9vTZAi8ibe0VRu/YsQRGQp8CMgCvilqv7At+obwLut6c8Y8E5ouWvXLnbt2kVcXByf//znmTRpUpcevfgruZ1Pz779mPXU8+EOxUSwpkYyfwDWA38P/E+/8hJVLQii7SpgoaqWikgM3gefrVfVuru9RKQvUKGqJX5lo1X1XL223gJ+gne2AfzqRgE/BRYDOcBBEXECA4FTQOecw8N0eteuXSMrK4vc3Fzuvfdeli5d2u0mtFS3m+jYuHCHYSJcU/fJFAFFQKvGyr6ZAmovho/xvepfEjMP+KqILFPVShF5FXgCWFavrZ0iMjxAN9OBc6p6AUBE3gEew3seKRGYCFSIyDpV9bRmP0z3UlNTw7Zt29i7dy/Jyck899xzjB07NtxhhYXH47ZHQJs2C+kdY76RxmFgNPBTVd3vv15V3xOREcA7IvIe8AreUUmwBgFX/ZZzgBmq+pqv/5eB/EAJRkRWAitHjx7dgu5MV3bx4kWcTieFhYVkZGSwaNGiTjuhZUfwuN1IVFS4wzARLqRJRlXdwH0i0gv4o4hMUtUT9er80DcCeQMYpar1bwVuSqCD4373g+lbTcSWDWRnZGS82oL+TBdUWVnJBx98wOHDh0lNTeXll19m+PDh4Q4r7DweDw5LMqaNOmTuC1W9IyLbgaXAXUlGROYCk4A/Aq8Dr7Wg6RxgiN/yYOB6m4I13crp06dZs2YNpaWlzJo1iwULFhATExPusMKu4HoOl4547/xXjwexw2amlUKWZESkD1DjSzDxwCLq3V8jIlOBXwDLgYvA70Tk+6r67SC7OQiM8R1yuwY8CzzXXvtguq6ysjLWr1/PiRMn6NevH88++yyDBg0Kd1hhUXD9Gvv+8x0qS0uoriinqryc/CuX6tZXV1YQl9B9LnqoPH+HqgtFpCwa2m2uJAylUI5kBgC/9p2XcQDvBrhfJQF4SlXPA4jIS8DL9RsSkbeB+UC6iOTgvfflV6rqEpHXgI14L2F+U1VPhmqHTORTVU6cOMH69eupqqpiwYIFzJkzh6hufFho8y9+wo3zZ0gbNITYHvH07NuPMdNnce/Dj5DYqzcOR/f53bhLqsn/xXEAEh/oR3Rq9z0n115ClmRU9RgwtZk6H9ZbrsE7sqlfr9Er3FR1HbCulWGabqSoqIi1a9dy5swZBg8eTGZmJn379g13WGFTnJ/HL/50dd2yIzoaj8dDdUUF106f4sa50zgcDhxRUYjDgcMR9dn7qCgcjs/eR8fGcv+jmSSlpoVxj9qu5pZ35qy0lyZagmknkTcfuTEtpKocPnyYDz74AI/Hw9KlS5k+fXq3vzw3PiWFgeMmcv30KYZOmgziQN1u79xlNdXe9x5P3c/P3vuV+15V5WX07NufKYsfDfdutUnNrXIAYgclhTmSrsOSjOnSbt++TXZ2NpcuXWLkyJGsXLmS3r17hzusTiEmNo5V3/thm9spvHmdN7/+ZWLiIvvGTVdRFUXZF7wLkTfJdadlScZ0SR6Ph71797Jt2zaio6PJzMxk6tSpdiI3BKorKgCIie/0Uxo2SRyffTburLlAdJ944kb0pMcY+6OkLSzJmC7n1q1bZGVlcf36dcaPH8/y5ctJTrYHvIZKjS/JxPYIT5IpqnFxqqwStyoeBQ+1P8Gj3qcDeVR9y9716re+7qdbKb4/hercCqKLi8k8kU/p7usM+OZ0HPH2Vdla9pszXYbL5aqb0DI+Pp6nnnqKiRMn2uglxKorOzbJuFU5WlLO9oIStheUcLi4DHd7Hd7qA/TpQXKUgy9l3kPu//mYku1XiZ/cB4kScHhf4hCIEqKSY+8aAZmGLMmYLiEnJ4esrCzy8vKYMmUKS5YsISEhIdxhdQvVFb6T5SE8XHazqobtBcVsKyhhZ0EJhS43AkxOjudrQ/sxvWci8VEOHIBDBAfeZ6Y5EG9e8JWL33qH3/q7y70/Y+NiiBvVk5IdOZTsyAkYV9KsgfTKHBWy/e4KLMmYiFZdXc3WrVvZv38/KSkpPP/884wZMybcYXUrtSOZmBaMZFQVt4JLFbcqLlVcit975XJFNdsKSthWUMwnZZUA9ImNZlF6CgtSU3iodzLpsaH9CktdNZ7qqyXgAfUoeBT1KKUfXqMmp5Qe41ND2n9XYEnGRJRvn80ht9qFKhRfvcLl7R9QXVJM+qTJDHxwNieqouHERdR3+KT2KIr6XS5UV9agTv1yvaucBuv9yurVbbTt2nr1GtUA7xuLo/E+AsQbZBwN1weOIVDMFaRR/uzXef9MLnIuH6VhwgiUUIIRI8L0non81cgBLExLYWJijw49/BmVFEv8hIb3/rjvVFKTU0rcyJ4dFkuksiRjIsq5siquFpdQuH83pac/IaZnL9IeyaRywCAuugBX1V1Ps7/rp993k9z1ZHu/mVal3jb16zVYH6DNJurUrhdpIoYGbUijcdQLu0EMgdpvGF9wbQdqX4AbN69SWpDH6FEjEBwgEC1CtEO8P+veO+rKomrriBAlQrRAlAgx8tn69NgYZvZMJDG6E844UHsSyM7HNMuSjIko3+lRw9otWyirKGPWs08wb948m9AyzH7+0+9ScjsPNr0d3AbiS5oCbnHgEXCJozbzIuJABPIQPnXU1hXvCMb3s6aqihrfYTp/n/vmdxlx3wPtvIcNqUe9sVqSaZYlGRMRSktLWb9+PSdPnqR///6sWrWKgQMHhjssAyx+9U/Jz7kCqqjvhf9PvOcx8F06jHp8h+EU9Xi8h93u2ta33r/srjaUUzu3BYwluaOmtfGojWKCZEnGdGqqyrFjx9iwYQPV1dU8/PDDzJo1q1tPaNnZjJiawYipGR3aZ2nBbfIuX+LVn/wqLI8hUI/aKCZIlmRMp1VUVER2djbnzp1jyJAhZGZm0qdPn3CHZcKsorSES0c/5v5lmeF7zo2n4cUbJjBLMqbTUVUOHjzI5s2bAXj00UeZNm1at5/Q0nidO7AXj9vFuJlzwxaDIzEGXB4qzxXSY7RNO9MUSzKmU8nPz8fpdHLlyhVGjRrFypUr6dWrV7jDMp3I6b276NVvAP1Gjg5bDEkPDqB44yXKDt5Coh2gIDEOYgfb9EX1WZIxnYLH42HPnj1s376d6OhoHn/8caZMmWJTwpi7lBfd4crxo0x//KmwfjYc8dHEDE6i4mgeFUfz6srTvzjJJtSsx5KMCbubN2+SlZXFjRs3mDBhAsuXLycpyZ7nYRo6s+9DVD2MmxW+Q2W1+n5lCsXbrlKy5QrRaT3oMT7Vbs4MwJKMCRuXy8WOHTv48MMPSUhI4Omnn2bixInhDst0Yqf37iJt8FDShwwLdyjew2QAAn2/fj+OWLviMRBLMiYsrly5gtPpJD8/n/vuu48lS5YQH+HPIzGhVVKQT86nJ5n15HOd5jCq62YZ0WnxlmCaYEnGdKjq6mq2bNnCgQMHSElJ4YUXXmD06PCdwDWR48zeD0G1Uxwqq1Vzq5yY/jbbd1MsyZgOc/78ebKzsykqKmL69OksXLiQuAh/ZK/pOKf37KTv8FGkDhwc7lAA8FS7cd2uIOE+u3erKZZkTMhVVFSwceNGjhw5Qnp6OqtXr2bo0KHhDstEkKLcm9w4d5q5z70c7lDquG6Vg0JM/8Rwh9KpWZIxIXXq1CnWrVtHeXk5c+fOZd68eURH28fOtMzpvbsBwnoDZn01N8sASzLNsf/bTUiUlpaybt06Tp06xYABA3jhhRfo379/uMMyEerTPTsZMGYcPfv2C3coALiLqynddwOJiyIqtUe4w+nULMmYdqWqHD16lA0bNuByuVi0aBEzZ860CS1NqxVczyHv0gXmf+HVsMZRdaWYvH85eldZdHo8xRsv4al2U7b3BgDJC4fQ85HhYYiwc7IkY9rNnTt3yM7O5vz58wwdOpTMzEzS09PDHZbpRDxuNzmfnODM/j1c+/Qk6vEQ2yOeAWPHE+U7jKr1Zp7Mu3wRRBg7c3Y4Qq5TdaGoQZnrTiUlu6999hAzoGTrVUsyfizJmDZTVQ4cOMCWLVsAWL58ORkZGZ3mXgYTXq6aGq6cOMLZ/Xs4d2g/lSXFRMfFMWTCJGLielBSeJtjH6xvuKHf52fcg3NITg3vHywp84eQMn9IwHXFmy9TvOUKg/5m9mc3abZSdXUBACJRvge4Rdf9BAciwqXL/8rVq28SFeWdGaN//8cZOeJrbeo3VCzJmDbJy8vD6XRy9epVRo8ezYoVK2xCS0NNVSWXjnzE2QN7OH/4ANUV5cTGJzDqgemMmTGL4VPuJyau65zLqMmvIKpXXJsTzIULP+LipR83WUckClU3AP36zQRVesQNaFO/oWRJxrSK2+2um9AyNjaWJ554gsmTJ9vopRurKi/nwscHObv/Qy4eOYyrqooeySmMfXA2Y2bMYuik+4juoo/KduVXEJ3ethkryssvc+nyG6SlzSctbZ43kagHVRda7ycoAwY8SULC8HaJP5QsyZgWu3HjBllZWdy8eZN77rmHRx991Ca07GRUFY/bjTjEd6ilbcnf43Zz9sAePt6QTXF+HlFR0TiiooiKjsYRHY2IkHf5Im6Xi8TeqdwzbxFjZ8xi8IRJOLr4RR+qiiuvgoT7+7apnXPnf4jDEcOE8X9PXFzb2upMLMl0sGvX/507hQfuLgz4/7/UW6pfKcBGDb5ImmsjULeB6njLamrcHDx4hSMfXyM+PoZ580YzapSLnGvHGt2mRbE0KGo8lkbbaSL+JvtusEnzv+9m/02CiqXp9S2NRVXJv3qZKyeOUl1eXrde/WuJ+JoUb5n/e4fvvYj3GSkiIN4k466uoUffZIZP7IvHU4F6FPV4UPX+HDCtN2mDh5GS3hcR8LCHK1f3BPV7abakVf+uwfwuA7Xasn9XT6Wb4r6XqOidTmlOr1bFUlNTSF7eBkaO+G9dKsGAJZkOV1F+maKij+qWlUDPcK1fVm85wHNfG7YTxLNh67XTVCw3b1bx4e5CioprGDMmkenTexIX9zG5ecHEH7DzeqEEE3/TdRq20Xy/oYrF207Lt2mfWCA1ZJNZ5wEXCDQ2USC/xPvqdiYALuBM65tISBjF0KFfbK+IOg1LMh1s9Oi/ZPTovwx3GEGrqqpi8+bNnDxxkOHDe5GZmcnIkSPDHVabeNxuKkqKG5TXHVKq95dq/fK7/kqVenV8BZ8t1tum0fJ629W1U2+7ANuU5Oex8/f/xum9u0jqncqcVS8xce4CxO9x1c0nq0BJsuXbNEySAao02057xdJcG+0TS/nHt7iz5gJ9vzaV6F5xAbdr+PdGw3ZjYnricMQGiDGyWZIxjTp79ixr1qyhuLiYBx98kIULFxIb27n/J6iuKKek4Dalfq+7lgtvU37nDqqecIcaEqWFBWz4l39iw7/8U5P1nv3uDxk0vunhjl3DEZzygiKiPT2JTx+AOOyXVp8lGdNAeXk5Gzdu5OjRo/Tp04dXXnmFIUMC3x/QUTweN+VFRb6kkX9XEvFPINUVFQ22jUtMJKl3Gslp6fQZNpyk1DQSevbC4XB89gel703dIcPa5bo/OO8uD7Su7i/curbqtV3/8KQ2bLO2/KN1WQFHW+3l+tlPm00yJjiuvAqi0+ItwTTCkoypo6p1E1pWVFQwb9485s6dG/IJLWsqKz8bbRQ2TB4lhbcpKyxAPXePPhxRUST2SiUpNZW0IUMZNmWqN5mkppHk94rE+zFmPPE0l44cxlVT7T1R7zsZ7384TUSITUggOTW97gS9/zrEe2gtKiYGR1QUDkcUEhWFw+Ho8ld8daT2uHy5K7MkYwAoKSlh7dq1fPrppwwcOJAXX3yx3Sa0LLh+jcIbOY0evqoqK2uwTWx8Ql2SGDZoivd977uTR0LPnjgcXfPLUkQYMTUj3GGYZqhHcd2uoMeE1HCH0ml12SQjIonATuB1VV0T7ng6K1Xl448/ZtOmTbhcLhYvXszMmTNxONp257K/ve//gU8/3AGAiIPEXr1ISk2j94CBDLnn3rrkkZyWXpdAYnvYX4am83PfqQK3EmMjmUaFLMmIyBDgN0B/wAP8XFV/1Mq23gRWALmqOqneuqXAj4Ao4Jeq+gPfqm8A77Yy/G6hsLCQ7OxsLly4wLBhw8jMzCQtLa3d+5nx+FPcvyyTpNQ0Env2tkM1pstw5XvPAdrhssaFciTjAv5CVT8SkWTgsIh8oKqnaiuISF+gQlVL/MpGq+q5em29BfwEb9LCr24U8FNgMZADHBQRJzAQOAVE3sH4DuDxeOomtHQ4HKxYsYIHHnggZFPCpA8dHpJ2jQk3V573hldLMo0LWZJR1RvADd/7EhH5BBiE98u/1jzgqyKyTFUrReRV4AlgWb22dorI8ADdTAfOqeoFABF5B3gMSAISgYlAhYis03rXrIrISmDl6NGj27yvkSQ3Nxen00lOTg5jxoxhxYoV9OzZM9xhGdPpqctD0aZL1OSUEtM/EYlxUHWhCImLwpHUNedkaw8dck7GlyCmAvv9y1X1PREZAbwjIu8Br+AdlQRrEHDVbzkHmKGqr/n6fRnIr59gfH1nA9kZGRnhfRJSB3G73ezevZudO3cSFxfH5z73Oe69916b0NKYILiLq7j9+0+pvlyMIzmGqsu+y8sF4iem2f9HTQh5khGRJOA/gP9XVRtc+K+qP/SNQN4ARqlqaUuaD1Dmd3uCvtXCcLuka9eu4XQ6uXXrFpMmTeLRRx8lMdGeS25MMKouFXH795+gVW5SnxtPwuQ+4Q4pooQ0yYhIDN4E83tV/c9G6swFJgF/BF4HXmtBFzmA/12Cg4HrrYu266mpqWH79u3s2bOHpKQkVq1axbhx48IdljERofp6KRUn8inZnkN07zjSvngvMf3tj7OWCuXVZQL8CvhEVf+xkTpTgV8Ay4GLwO9E5Puq+u0guzkIjPEdcrsGPAs81+bgu4BLly7hdDopKCjggQceYPHixfToYddBGBOMmltl5P74YwB6jE8l9ZlxOOK77B0fIRXK39ps4EXguIgc8ZV9S1XX+dVJAJ5S1fMAIvIS8HL9hkTkbWA+kC4iOXjvffmVqrpE5DVgI95LmN9U1ZOh2qFIUFlZyebNmzl06BC9e/fmpZdeYsSIEeEOy5iIUrLzGgAJGf3o/bkxNmVMG4Ty6rLdNPKkFL86H9ZbrsE7sqlfb1UTbawD1jW2vjs5c+YMa9asoaSkhJkzZ7Jw4UJiuuiTCI0JJa12E5Xag9Qnx4Y7lIhn478uoKysjA0bNnD8+HH69u3L008/zeDBg8MdVlCqb5RRdabws4Km/iyRRhca367hrPx+BU2tbHSj5rdpUK3l27SmH//9Cer5b0312eQ2vjnUxNen38+75lDzL3MEKKu3vQhojQdPtRt1eYjuFUd0ekKA/axtKnSjC0+VG0eCfT22B/stRjBV5eTJk6xbt46qqirmz5/P3LlziYqgO+qrrxZTtP5iuMMwkS5AEvosGwVeF/iBo96kpzUe4oantHuY3ZElmQhVXFzM2rVrOX36NIMGDSIzM5N+/fqFO6wWS3ygHwn3+R4329STJBt7JlWDZ0wFrtjkQzMbW9nkNk1UbCzsILdput/mYw3mAVlt7Uc9+tmyKqjv0QV+ywHL8Cura8O77Kl0U/j+Z4+WdCREkzR7UMB47lrUJnZe/YNuWHRXod9jH9TlIX5i+0+x1B1ZkokwqspHH33Epk2b8Hg8LFmyhBkzZrTrhJYdSaIcSOQMvEyIJWZE3h9KpmmWZCJIQUEB2dnZXLx4kREjRrBy5UpSU22KcWNM52VJJgJ4PB727dvHtm3bcDgcrFy5kvvvv9+msjDGdHqWZDq53NxcsrKyuHbtGuPGjWP58uWkpNgJSWNMZLAk00m53W527drFrl27iIuL48knn+See+6x0YsxJqJYkumErl27RlZWFrm5uUyePJmlS5eSkJAQ7rCMMabFLMl0ItXV1Wzbto19+/aRnJzMc889x9ixdsexMSZyWZLpJC5evIjT6aSwsJCMjAwWL15MXFxcuMMyxpg2sSQTZpWVlWzatImPPvqI1NRUXn75ZYYPHx7usIwxpl1Ykgmj06dPs2bNGkpLS5k9ezbz58+3CS2NMV2KJZkwKCsrY/369Zw4cYJ+/fqxatUqBg4cGO6wjDGm3VmS6UCqyvHjx9mwYQNVVVUsXLiQ2bNnR9SElsYY0xKWZDpIUVERa9as4ezZswwePJjHHnuMPn3sWeHGmK7NkkyIqSqHDh1i8+bNeDweli5dyvTp0yN2QktjjGkJSzIhdPv2bZxOJ5cvX2bkyJGsXLmS3r17hzssY4zpMJZkQsDj8bB37162bdtGdHQ0jz32GPfdd59NCWOM6XYsybSzmzdv4nQ6uX79OuPHj2f58uUkJyeHOyxjjAkLSzLtxOVysXPnTnbv3k18fDxPPfUUEydOtNGLMaZbsyTTDq5evYrT6SQvL48pU6awZMkSm9DSGGOwJNMm1dXVbN26lf3795OSksLzzz/PmDFjwh2WMcZ0GpZkWunixYtkZWVx584dpk+fzsMPP2wTWhpjTD2WZFqptLSUqKgoVq9ezbBhw8IdjjHGdEqWZFpp0qRJTJgwgeho+xUaY0xj7LbzVhIRSzDGGNMMSzLGGGNCxpKMMcaYkLEkY4wxJmQsyRhjjAkZSzLGGGNCxpKMMcaYkLEkY4wxJmREVcMdQ1iJSB5wuYWb9QSKQhBOe/fR2jZasl2wdZur19T6ptalA/lB9N8ZRMrnprXttHSbYOq35XPT1Hr73LS9j2Gq2vwz5FXVXi18AT+PhD5a20ZLtgu2bnP1mlrfzLpD4f48dOS/aUf10Zp2WrpNMPXb8rlpar19bjquDztc1jrZEdJHa9toyXbB1m2uXlPrO+L33REi5XPT2nZauk0w9dvyuQm2j84ukj43DXT7w2UmsonIIVXNCHccJrLY56bj2EjGRLqfhzsAE5Hsc9NBbCRjjDEmZGwkY4wxJmQsyRhjjAkZSzLGGGNCxpKM6VJEZIKI/ExE3heRr4Y7HhM5RCRRRA6LyIpwx9KVWJIxnZ6IvCkiuSJyol75UhE5LSLnROR/AqjqJ6r6FeBpwC5R7cZa8rnx+QbwbsdG2fVZkjGR4C1gqX+BiEQBPwUeBSYCq0Rkom9dJrAb2NKxYZpO5i2C/NyIyCLgFHCro4Ps6uwh9abTU9WdIjK8XvF04JyqXgAQkXeAx4BTquoEnCKyFvhDR8ZqOo8Wfm6SgES8iadCRNapqqcDw+2yLMmYSDUIuOq3nAPMEJH5wOeAOGBdGOIynVvAz42qvgYgIi8D+ZZg2o8lGROpJECZqup2YHvHhmIiSMDPTd0b1bc6LpTuwc7JmEiVAwzxWx4MXA9TLCZy2Oemg1mSMZHqIDBGREaISCzwLOAMc0ym87PPTQezJGM6PRF5G9gLjBORHBH5oqq6gNeAjcAnwLuqejKccZrOxT43nYNNkGmMMSZkbCRjjDEmZCzJGGOMCRlLMsYYY0LGkowxxpiQsSRjjDEmZCzJGGOMCRlLMsZ0MiKSISI/bqbOt+ot7wltVMa0jt0nY0wEEpFSVU0KdxzGNMdGMsa0koh8QUSOichREfmtiAwTkS2+si0iMtRX7y0R+bGI7BGRCyLypK/830VkmV97b4nI50Vkvois8ZUlici/ichxX7ufF5EfAPEickREfu+rV+r7KSLyDyJywrfNM77y+SKy3ffE0E9F5PciEmiySGPalc3CbEwriMg9wF8Bs1U1X0RSgV8Dv1HVX4vIK8CPgcd9mwwA5gDj8c6V9T7wDvAMsM43j9bDwFeBGX5d/TVQpKr3+vrtrar/ISKvqep9AUL7HHAfMAVIBw6KyE7fuqnAPXgnhPwQmI334W7GhIyNZIxpnYXA+6qaD6CqBcBMPntI2m/xJpVa/6WqHlU9BfTzla0HFopIHN4nNe5U1Yp6/SzC+yRHfP0UNhPXHOBtVXWr6i1gBzDNt+6Aqub4npVyBBge9N4a00qWZIxpHcHvOSSN8F9fVW9bVLUS77NvluAd0bzTyn7q12+Mfwxu7EiG6QCWZIxpnS3A0yKSBuA7XLYH79TxAM8T3KGod4DVwFy8MwPXtwnvrMH4+unte1sjIjEB6u8EnhGRKBHpAzwEHAgiDmNCwpKMMa3gmx7+b4EdInIU+Efgz4DVInIMeBH4ehBNbcKbCDaranWA9d8HevtO5B8FFvjKfw4cqz3x7+ePwDHgKLAV+EtVvdmyvTOm/dglzMYYY0LGRjLGGGNCxpKMMcaYkLEkY4wxJmQsyRhjjAkZSzLGGGNCxpKMMcaYkLEkY4wxJmQsyRhjjAmZ/wvvhTGuvaqU9gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.loglog(make2D('conviction_all', rdf), make2D('triggers_all', rdf))\n",
    "a = plt.axis()\n",
    "plt.loglog(a[:2],a[2:], 'k',alpha=.5 )\n",
    "plt.ylabel('triggers')\n",
    "plt.xlabel('conviction')\n",
    "plt.title('phase: Triggers & Conviction')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.LineCollection at 0x1a2c47c208>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "T = time_periods_per_run\n",
    "plt.semilogy(rdf.timestep,make2D('conviction_share_of_trigger_all', rdf))\n",
    "plt.title('conviction_share_of_trigger')\n",
    "plt.xlabel('time $t$')\n",
    "plt.ylabel('conviction_share_of_trigger')\n",
    "plt.hlines(1,0,T, linestyle='--')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.LineCollection at 0x1a2add67f0>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.semilogy(make2D('age_all', rdf), make2D('conviction_share_of_trigger_all', rdf))\n",
    "plt.ylabel('triggers')\n",
    "plt.xlabel('proposal_age')\n",
    "plt.hlines(1,0,T, linestyle='--')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "nets = rdf.network.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snap_plot(nets[:1], size_scale = 1/1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}