experiment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# cadCAD Experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "\n",
      "                  ___________    ____\n",
      "  ________ __ ___/ / ____/   |  / __ \\\n",
      " / ___/ __` / __  / /   / /| | / / / /\n",
      "/ /__/ /_/ / /_/ / /___/ ___ |/ /_/ /\n",
      "\\___/\\__,_/\\__,_/\\____/_/  |_/_____/\n",
      "by cadCAD\n",
      "\n",
      "Execution Mode: local_proc\n",
      "Configuration Count: 1\n",
      "Dimensions of the first simulation: (Timesteps, Params, Runs, Vars) = (90, 7, 1, 5)\n",
      "Execution Method: local_simulations\n",
      "SimIDs   : [0]\n",
      "SubsetIDs: [0]\n",
      "Ns       : [0]\n",
      "ExpIDs   : [0]\n",
      "Execution Mode: single_threaded\n",
      "Total execution time: 0.33s\n",
      "     allocated_funds                                            brokers  \\\n",
      "8         155.308736  {25: <model.model.broker.Broker object at 0x10...   \n",
      "16        150.498483  {25: <model.model.broker.Broker object at 0x10...   \n",
      "24        155.106669  {25: <model.model.broker.Broker object at 0x10...   \n",
      "32        159.044489  {25: <model.model.broker.Broker object at 0x10...   \n",
      "40        131.772521  {25: <model.model.broker.Broker object at 0x10...   \n",
      "48        174.077822  {25: <model.model.broker.Broker object at 0x10...   \n",
      "56        170.372018  {25: <model.model.broker.Broker object at 0x10...   \n",
      "64        170.697515  {25: <model.model.broker.Broker object at 0x10...   \n",
      "72        162.074928  {25: <model.model.broker.Broker object at 0x10...   \n",
      "80        154.253794  {25: <model.model.broker.Broker object at 0x10...   \n",
      "88        110.541875  {25: <model.model.broker.Broker object at 0x10...   \n",
      "96        161.348560  {25: <model.model.broker.Broker object at 0x10...   \n",
      "104       142.625021  {25: <model.model.broker.Broker object at 0x10...   \n",
      "112       157.835505  {25: <model.model.broker.Broker object at 0x10...   \n",
      "120       166.234695  {25: <model.model.broker.Broker object at 0x10...   \n",
      "128       168.519228  {25: <model.model.broker.Broker object at 0x10...   \n",
      "136       142.381814  {25: <model.model.broker.Broker object at 0x10...   \n",
      "144       167.338325  {25: <model.model.broker.Broker object at 0x10...   \n",
      "152       152.776092  {25: <model.model.broker.Broker object at 0x10...   \n",
      "160       161.195061  {25: <model.model.broker.Broker object at 0x10...   \n",
      "168       184.005263  {25: <model.model.broker.Broker object at 0x10...   \n",
      "176       166.916965  {25: <model.model.broker.Broker object at 0x10...   \n",
      "184       170.802461  {25: <model.model.broker.Broker object at 0x10...   \n",
      "192       192.591073  {25: <model.model.broker.Broker object at 0x10...   \n",
      "200       174.639842  {25: <model.model.broker.Broker object at 0x10...   \n",
      "208       178.097705  {25: <model.model.broker.Broker object at 0x10...   \n",
      "216       170.265700  {25: <model.model.broker.Broker object at 0x10...   \n",
      "224       143.406504  {25: <model.model.broker.Broker object at 0x10...   \n",
      "232       138.664057  {25: <model.model.broker.Broker object at 0x10...   \n",
      "240       150.984073  {25: <model.model.broker.Broker object at 0x10...   \n",
      "..               ...                                                ...   \n",
      "488       220.993404  {25: <model.model.broker.Broker object at 0x10...   \n",
      "496       229.433520  {25: <model.model.broker.Broker object at 0x10...   \n",
      "504       209.536975  {25: <model.model.broker.Broker object at 0x10...   \n",
      "512       218.050433  {25: <model.model.broker.Broker object at 0x10...   \n",
      "520       205.381419  {25: <model.model.broker.Broker object at 0x10...   \n",
      "528       220.565134  {25: <model.model.broker.Broker object at 0x10...   \n",
      "536       245.209222  {25: <model.model.broker.Broker object at 0x10...   \n",
      "544       224.317369  {25: <model.model.broker.Broker object at 0x10...   \n",
      "552       218.091478  {25: <model.model.broker.Broker object at 0x10...   \n",
      "560       219.823631  {25: <model.model.broker.Broker object at 0x10...   \n",
      "568       233.395308  {25: <model.model.broker.Broker object at 0x10...   \n",
      "576       212.304246  {25: <model.model.broker.Broker object at 0x10...   \n",
      "584       202.290792  {25: <model.model.broker.Broker object at 0x10...   \n",
      "592       205.925299  {25: <model.model.broker.Broker object at 0x10...   \n",
      "600       239.369939  {25: <model.model.broker.Broker object at 0x10...   \n",
      "608       249.171245  {25: <model.model.broker.Broker object at 0x10...   \n",
      "616       242.466436  {25: <model.model.broker.Broker object at 0x10...   \n",
      "624       228.172545  {25: <model.model.broker.Broker object at 0x10...   \n",
      "632       240.376377  {25: <model.model.broker.Broker object at 0x10...   \n",
      "640       246.163651  {25: <model.model.broker.Broker object at 0x10...   \n",
      "648       248.982073  {25: <model.model.broker.Broker object at 0x10...   \n",
      "656       256.681424  {25: <model.model.broker.Broker object at 0x10...   \n",
      "664       215.685219  {25: <model.model.broker.Broker object at 0x10...   \n",
      "672       245.840994  {25: <model.model.broker.Broker object at 0x10...   \n",
      "680       259.794421  {25: <model.model.broker.Broker object at 0x10...   \n",
      "688       257.635266  {25: <model.model.broker.Broker object at 0x10...   \n",
      "696       263.264295  {25: <model.model.broker.Broker object at 0x10...   \n",
      "704       270.638687  {25: <model.model.broker.Broker object at 0x10...   \n",
      "712       227.209157  {25: <model.model.broker.Broker object at 0x10...   \n",
      "720       253.736065  {25: <model.model.broker.Broker object at 0x10...   \n",
      "\n",
      "                                           make_claims  num_member_brokers  \\\n",
      "8    {25: <model.model.broker.Broker object at 0x10...                   1   \n",
      "16   {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "24   {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "32   {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "40   {25: <model.model.broker.Broker object at 0x10...                   4   \n",
      "48   {25: <model.model.broker.Broker object at 0x10...                   4   \n",
      "56   {25: <model.model.broker.Broker object at 0x10...                   4   \n",
      "64   {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "72   {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "80   {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "88   {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "96   {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "104  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "112  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "120  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "128  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "136  {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "144  {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "152  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "160  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "168  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "176  {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "184  {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "192  {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "200  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "208  {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "216  {25: <model.model.broker.Broker object at 0x10...                   4   \n",
      "224  {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "232  {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "240  {25: <model.model.broker.Broker object at 0x10...                   4   \n",
      "..                                                 ...                 ...   \n",
      "488  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "496  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "504  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "512  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "520  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "528  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "536  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "544  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "552  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "560  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "568  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "576  {25: <model.model.broker.Broker object at 0x10...                   1   \n",
      "584  {25: <model.model.broker.Broker object at 0x10...                   1   \n",
      "592  {25: <model.model.broker.Broker object at 0x10...                   0   \n",
      "600  {25: <model.model.broker.Broker object at 0x10...                   1   \n",
      "608  {25: <model.model.broker.Broker object at 0x10...                   2   \n",
      "616  {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "624  {25: <model.model.broker.Broker object at 0x10...                   3   \n",
      "632  {25: <model.model.broker.Broker object at 0x10...                   4   \n",
      "640  {25: <model.model.broker.Broker object at 0x10...                   4   \n",
      "648  {25: <model.model.broker.Broker object at 0x10...                   4   \n",
      "656  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "664  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "672  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "680  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "688  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "696  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "704  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "712  {25: <model.model.broker.Broker object at 0x10...                   5   \n",
      "720  {25: <model.model.broker.Broker object at 0x10...                   4   \n",
      "\n",
      "     run  simulation  subset  substep  timestep  total_broker_stake  \\\n",
      "8      1           0       0        8         1                   5   \n",
      "16     1           0       0        8         2                  10   \n",
      "24     1           0       0        8         3                  10   \n",
      "32     1           0       0        8         4                  15   \n",
      "40     1           0       0        8         5                  20   \n",
      "48     1           0       0        8         6                  20   \n",
      "56     1           0       0        8         7                  20   \n",
      "64     1           0       0        8         8                  25   \n",
      "72     1           0       0        8         9                  25   \n",
      "80     1           0       0        8        10                  25   \n",
      "88     1           0       0        8        11                  25   \n",
      "96     1           0       0        8        12                  25   \n",
      "104    1           0       0        8        13                  25   \n",
      "112    1           0       0        8        14                  25   \n",
      "120    1           0       0        8        15                  25   \n",
      "128    1           0       0        8        16                  25   \n",
      "136    1           0       0        8        17                  15   \n",
      "144    1           0       0        8        18                  15   \n",
      "152    1           0       0        8        19                  10   \n",
      "160    1           0       0        8        20                  10   \n",
      "168    1           0       0        8        21                  10   \n",
      "176    1           0       0        8        22                  15   \n",
      "184    1           0       0        8        23                  15   \n",
      "192    1           0       0        8        24                  15   \n",
      "200    1           0       0        8        25                  10   \n",
      "208    1           0       0        8        26                  15   \n",
      "216    1           0       0        8        27                  20   \n",
      "224    1           0       0        8        28                  15   \n",
      "232    1           0       0        8        29                  15   \n",
      "240    1           0       0        8        30                  20   \n",
      "..   ...         ...     ...      ...       ...                 ...   \n",
      "488    1           0       0        8        61                  25   \n",
      "496    1           0       0        8        62                  25   \n",
      "504    1           0       0        8        63                  25   \n",
      "512    1           0       0        8        64                  25   \n",
      "520    1           0       0        8        65                  25   \n",
      "528    1           0       0        8        66                  10   \n",
      "536    1           0       0        8        67                  10   \n",
      "544    1           0       0        8        68                  10   \n",
      "552    1           0       0        8        69                  10   \n",
      "560    1           0       0        8        70                  10   \n",
      "568    1           0       0        8        71                  10   \n",
      "576    1           0       0        8        72                   5   \n",
      "584    1           0       0        8        73                   5   \n",
      "592    1           0       0        8        74                   0   \n",
      "600    1           0       0        8        75                   5   \n",
      "608    1           0       0        8        76                  10   \n",
      "616    1           0       0        8        77                  15   \n",
      "624    1           0       0        8        78                  15   \n",
      "632    1           0       0        8        79                  20   \n",
      "640    1           0       0        8        80                  20   \n",
      "648    1           0       0        8        81                  20   \n",
      "656    1           0       0        8        82                  25   \n",
      "664    1           0       0        8        83                  25   \n",
      "672    1           0       0        8        84                  25   \n",
      "680    1           0       0        8        85                  25   \n",
      "688    1           0       0        8        86                  25   \n",
      "696    1           0       0        8        87                  25   \n",
      "704    1           0       0        8        88                  25   \n",
      "712    1           0       0        8        89                  25   \n",
      "720    1           0       0        8        90                  20   \n",
      "\n",
      "     unallocated_funds  \n",
      "8           155.308736  \n",
      "16          150.498483  \n",
      "24          155.106669  \n",
      "32          159.044489  \n",
      "40          168.439188  \n",
      "48          174.077822  \n",
      "56          170.372018  \n",
      "64          170.697515  \n",
      "72          162.074928  \n",
      "80          154.253794  \n",
      "88          154.375208  \n",
      "96          161.348560  \n",
      "104         160.125021  \n",
      "112         169.835505  \n",
      "120         166.234695  \n",
      "128         168.519228  \n",
      "136         174.381814  \n",
      "144         167.338325  \n",
      "152         171.442758  \n",
      "160         178.861728  \n",
      "168         184.005263  \n",
      "176         188.583632  \n",
      "184         184.135795  \n",
      "192         192.591073  \n",
      "200         184.639842  \n",
      "208         178.097705  \n",
      "216         170.265700  \n",
      "224         160.906504  \n",
      "232         162.830724  \n",
      "240         163.484073  \n",
      "..                 ...  \n",
      "488         220.993404  \n",
      "496         229.433520  \n",
      "504         229.536975  \n",
      "512         234.050433  \n",
      "520         237.381419  \n",
      "528         244.565134  \n",
      "536         245.209222  \n",
      "544         238.317369  \n",
      "552         235.091478  \n",
      "560         229.823631  \n",
      "568         233.395308  \n",
      "576         227.304246  \n",
      "584         222.290792  \n",
      "592         220.925299  \n",
      "600         239.369939  \n",
      "608         249.171245  \n",
      "616         242.466436  \n",
      "624         246.505878  \n",
      "632         240.376377  \n",
      "640         246.163651  \n",
      "648         248.982073  \n",
      "656         256.681424  \n",
      "664         253.018552  \n",
      "672         260.674327  \n",
      "680         259.794421  \n",
      "688         257.635266  \n",
      "696         263.264295  \n",
      "704         270.638687  \n",
      "712         274.709157  \n",
      "720         279.736065  \n",
      "\n",
      "[90 rows x 11 columns]\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from model.run import run\n",
    "\n",
    "df = run()\n",
    "\n",
    "print(df)"
   ]
  },
  {
   "source": [
    "![title](agreement.png)"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "# Cumulative Claimed Rewards\n",
    "This shows that the cumulative rewards continues to rise even though each broker eventually leaves the system and their rewards become fixed.  They are of similar heights (ie. same rewards) because they all use the same policies to join and leave."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "df1 = df.reset_index().brokers\n",
    "\n",
    "broker_holdings = {}\n",
    "broker_claimable = {}\n",
    "broker_holdings_plus_claimable = {}\n",
    "timestep = 0\n",
    "for broker_dict in df1:\n",
    "    for broker_id, broker in broker_dict.items():\n",
    "        if broker_id not in broker_holdings:\n",
    "            broker_holdings[broker_id] = {}\n",
    "            broker_claimable[broker_id] = {}\n",
    "            broker_holdings_plus_claimable[broker_id] = {}\n",
    "        broker_holdings[broker_id][timestep] = broker.holdings\n",
    "        broker_claimable[broker_id][timestep] = broker.claimable_funds\n",
    "        broker_holdings_plus_claimable[broker_id][timestep] = broker.holdings + broker.claimable_funds\n",
    "        \n",
    "    timestep += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Text(0,0.5,'Broker Holdings')"
      ]
     },
     "metadata": {},
     "execution_count": 6
    },
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {}
    }
   ],
   "source": [
    "\n",
    "\n",
    "df_plot = pd.DataFrame(broker_holdings)\n",
    "df_plot.plot(kind='area')\n",
    "plt.gca().legend(loc=9, bbox_to_anchor=(1.3, 1), ncol=3)\n",
    "plt.title('Cumulative Claimed Rewards')\n",
    "plt.xlabel('Epoch Number')\n",
    "plt.ylabel('Broker Holdings')"
   ]
  },
  {
   "source": [
    "# Cumulative Unclaimed Rewards\n",
    "\n",
    "This shows that the rewards are all claimed eventually, and the unclaimed rewards do not grow unbounded which would represent a leak in the system.\n"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Text(0,0.5,'Broker Claimable Funds')"
      ]
     },
     "metadata": {},
     "execution_count": 8
    },
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {}
    }
   ],
   "source": [
    "df_plot = pd.DataFrame(broker_claimable)\n",
    "df_plot.plot(kind='area')\n",
    "plt.gca().legend(loc=9, bbox_to_anchor=(1.3, 1), ncol=3)\n",
    "plt.title('Cumulative Unclaimed Rewards')\n",
    "plt.xlabel('Epoch Number')\n",
    "plt.ylabel('Broker Claimable Funds')"
   ]
  },
  {
   "source": [
    "# Plot to show Claimed Rewards + Unclaimed Rewards\n",
    "This shows a straight line is monotonically increasing rewards, as a sanity check that the amount of rewards per epoch is a constant."
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Text(0,0.5,'Broker Claimable Funds')"
      ]
     },
     "metadata": {},
     "execution_count": 10
    },
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {}
    }
   ],
   "source": [
    "df_plot = pd.DataFrame(broker_holdings_plus_claimable)\n",
    "df_plot.plot(kind='area')\n",
    "plt.gca().legend(loc=9, bbox_to_anchor=(1.3, 1), ncol=3)\n",
    "plt.title('Cumulative Claimed + Unclaimed Rewards')\n",
    "plt.xlabel('Epoch Number')\n",
    "plt.ylabel('Broker Claimable Funds')\n"
   ]
  },
  {
   "source": [
    "# Twinned x axis, Number of Member Brokers vs Total Broker Stake.  \n",
    "\n",
    "This plot shows that each broker has exactly $5 staked on average.\n",
    "\n",
    "\n"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "Text(0,0.5,'Total Broker Stake')"
      ]
     },
     "metadata": {},
     "execution_count": 12
    },
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots()\n",
    "\n",
    "ax1.plot(df.timestep, df.num_member_brokers, label='test1')\n",
    "ax1.set_ylabel('Num Member Brokers')\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(df.timestep, df.total_broker_stake, 'ro', label='test2')\n",
    "ax2.set_ylabel('Total Broker Stake', color = 'tab:red')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['members'] = df.brokers.apply(lambda x: [v.id for v in x.values() if v.member])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "8                      [25]\n",
       "16                 [25, 26]\n",
       "24                 [25, 26]\n",
       "32             [25, 26, 27]\n",
       "40         [25, 26, 27, 28]\n",
       "48         [25, 26, 27, 28]\n",
       "56         [25, 26, 27, 28]\n",
       "64     [25, 26, 27, 28, 29]\n",
       "72     [25, 26, 27, 28, 29]\n",
       "80     [25, 26, 27, 28, 29]\n",
       "88     [25, 26, 27, 28, 29]\n",
       "96     [25, 26, 27, 28, 29]\n",
       "104    [25, 26, 27, 28, 29]\n",
       "112    [25, 26, 27, 28, 29]\n",
       "120    [25, 26, 27, 28, 29]\n",
       "128    [25, 26, 27, 28, 29]\n",
       "136            [27, 28, 29]\n",
       "144            [27, 28, 29]\n",
       "152                [28, 29]\n",
       "160                [28, 29]\n",
       "168                [28, 29]\n",
       "176            [28, 29, 30]\n",
       "184            [28, 29, 30]\n",
       "192            [28, 29, 30]\n",
       "200                [29, 30]\n",
       "208            [29, 30, 31]\n",
       "216        [29, 30, 31, 32]\n",
       "224            [30, 31, 32]\n",
       "232            [30, 31, 32]\n",
       "240        [30, 31, 32, 33]\n",
       "               ...         \n",
       "488    [31, 36, 37, 38, 39]\n",
       "496    [31, 36, 37, 38, 39]\n",
       "504    [31, 36, 37, 38, 39]\n",
       "512    [31, 36, 37, 38, 39]\n",
       "520    [31, 36, 37, 38, 39]\n",
       "528                [37, 39]\n",
       "536                [37, 39]\n",
       "544                [37, 39]\n",
       "552                [37, 39]\n",
       "560                [37, 40]\n",
       "568                [37, 40]\n",
       "576                    [40]\n",
       "584                    [40]\n",
       "592                      []\n",
       "600                    [41]\n",
       "608                [41, 42]\n",
       "616            [41, 42, 43]\n",
       "624            [41, 42, 43]\n",
       "632        [41, 42, 43, 44]\n",
       "640        [41, 42, 43, 44]\n",
       "648        [41, 42, 43, 44]\n",
       "656    [41, 42, 43, 44, 45]\n",
       "664    [41, 42, 43, 44, 45]\n",
       "672    [41, 42, 43, 44, 45]\n",
       "680    [41, 42, 43, 44, 45]\n",
       "688    [41, 42, 43, 44, 45]\n",
       "696    [41, 42, 43, 44, 45]\n",
       "704    [41, 42, 43, 44, 45]\n",
       "712    [41, 42, 43, 44, 45]\n",
       "720        [42, 43, 44, 45]\n",
       "Name: members, Length: 90, dtype: object"
      ]
     },
     "metadata": {},
     "execution_count": 16
    }
   ],
   "source": [
    "df.members"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "broker_ids = [v.id for v in df.brokers.values[-1].values()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['broker_stakes'] = df.brokers.apply(lambda x: [(v.member, v.stake) for v in x.values()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def check(x):\n",
    "    if x[0]:\n",
    "        if x[1]==5:\n",
    "            #return \"member with correct stake\"\n",
    "            return True\n",
    "        else:\n",
    "            #return \"member with incorrect stake\"\n",
    "            return False\n",
    "    else:\n",
    "        if x[1]==0:\n",
    "            #return \"nonmember with correct stake\"\n",
    "            return True\n",
    "        else:\n",
    "            #return \"nonmember with incorrect stake\"\n",
    "            return False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "8                                                 [True]\n",
       "16                                          [True, True]\n",
       "24                                          [True, True]\n",
       "32                                    [True, True, True]\n",
       "40                              [True, True, True, True]\n",
       "48                              [True, True, True, True]\n",
       "56                              [True, True, True, True]\n",
       "64                        [True, True, True, True, True]\n",
       "72                        [True, True, True, True, True]\n",
       "80                        [True, True, True, True, True]\n",
       "88                        [True, True, True, True, True]\n",
       "96                        [True, True, True, True, True]\n",
       "104                       [True, True, True, True, True]\n",
       "112                       [True, True, True, True, True]\n",
       "120                       [True, True, True, True, True]\n",
       "128                       [True, True, True, True, True]\n",
       "136                       [True, True, True, True, True]\n",
       "144                       [True, True, True, True, True]\n",
       "152                       [True, True, True, True, True]\n",
       "160                       [True, True, True, True, True]\n",
       "168                       [True, True, True, True, True]\n",
       "176                 [True, True, True, True, True, True]\n",
       "184                 [True, True, True, True, True, True]\n",
       "192                 [True, True, True, True, True, True]\n",
       "200                 [True, True, True, True, True, True]\n",
       "208           [True, True, True, True, True, True, True]\n",
       "216     [True, True, True, True, True, True, True, True]\n",
       "224     [True, True, True, True, True, True, True, True]\n",
       "232     [True, True, True, True, True, True, True, True]\n",
       "240    [True, True, True, True, True, True, True, Tru...\n",
       "                             ...                        \n",
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       "504    [True, True, True, True, True, True, True, Tru...\n",
       "512    [True, True, True, True, True, True, True, Tru...\n",
       "520    [True, True, True, True, True, True, True, Tru...\n",
       "528    [True, True, True, True, True, True, True, Tru...\n",
       "536    [True, True, True, True, True, True, True, Tru...\n",
       "544    [True, True, True, True, True, True, True, Tru...\n",
       "552    [True, True, True, True, True, True, True, Tru...\n",
       "560    [True, True, True, True, True, True, True, Tru...\n",
       "568    [True, True, True, True, True, True, True, Tru...\n",
       "576    [True, True, True, True, True, True, True, Tru...\n",
       "584    [True, True, True, True, True, True, True, Tru...\n",
       "592    [True, True, True, True, True, True, True, Tru...\n",
       "600    [True, True, True, True, True, True, True, Tru...\n",
       "608    [True, True, True, True, True, True, True, Tru...\n",
       "616    [True, True, True, True, True, True, True, Tru...\n",
       "624    [True, True, True, True, True, True, True, Tru...\n",
       "632    [True, True, True, True, True, True, True, Tru...\n",
       "640    [True, True, True, True, True, True, True, Tru...\n",
       "648    [True, True, True, True, True, True, True, Tru...\n",
       "656    [True, True, True, True, True, True, True, Tru...\n",
       "664    [True, True, True, True, True, True, True, Tru...\n",
       "672    [True, True, True, True, True, True, True, Tru...\n",
       "680    [True, True, True, True, True, True, True, Tru...\n",
       "688    [True, True, True, True, True, True, True, Tru...\n",
       "696    [True, True, True, True, True, True, True, Tru...\n",
       "704    [True, True, True, True, True, True, True, Tru...\n",
       "712    [True, True, True, True, True, True, True, Tru...\n",
       "720    [True, True, True, True, True, True, True, Tru...\n",
       "Name: broker_stakes, Length: 90, dtype: object"
      ]
     },
     "metadata": {},
     "execution_count": 24
    }
   ],
   "source": [
    "df.broker_stakes.apply(lambda z: [check(x) for x in z])  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['broker_based_total_stake'] = df.broker_stakes.apply(lambda z: sum([x[1] for x in z if x[0]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "8       5\n",
       "16     10\n",
       "24     10\n",
       "32     15\n",
       "40     20\n",
       "48     20\n",
       "56     20\n",
       "64     25\n",
       "72     25\n",
       "80     25\n",
       "88     25\n",
       "96     25\n",
       "104    25\n",
       "112    25\n",
       "120    25\n",
       "128    25\n",
       "136    15\n",
       "144    15\n",
       "152    10\n",
       "160    10\n",
       "168    10\n",
       "176    15\n",
       "184    15\n",
       "192    15\n",
       "200    10\n",
       "208    15\n",
       "216    20\n",
       "224    15\n",
       "232    15\n",
       "240    20\n",
       "       ..\n",
       "488    25\n",
       "496    25\n",
       "504    25\n",
       "512    25\n",
       "520    25\n",
       "528    10\n",
       "536    10\n",
       "544    10\n",
       "552    10\n",
       "560    10\n",
       "568    10\n",
       "576     5\n",
       "584     5\n",
       "592     0\n",
       "600     5\n",
       "608    10\n",
       "616    15\n",
       "624    15\n",
       "632    20\n",
       "640    20\n",
       "648    20\n",
       "656    25\n",
       "664    25\n",
       "672    25\n",
       "680    25\n",
       "688    25\n",
       "696    25\n",
       "704    25\n",
       "712    25\n",
       "720    20\n",
       "Name: broker_based_total_stake, Length: 90, dtype: int64"
      ]
     },
     "metadata": {},
     "execution_count": 28
    }
   ],
   "source": [
    "df['broker_based_total_stake']"
   ]
  }
 ],
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