analysis/GobblersSimulation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import random\n",
    "from VRGDA_lib import *\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "multiple distribution:  [611, 524, 458, 407]\n",
      "from 1st day to 10st day one Golbers produced GOO\n",
      "M=6 1st day 1.5000 final day 150.0000\n",
      "M=7 1st day 1.7500 final day 175.0000\n",
      "M=8 1st day 2.0000 final day 200.0000\n",
      "M=9 1st day 2.2500 final day 225.0000\n",
      "\n",
      "from 1st day to 10st day all Golbers produced GOO\n",
      "M=6 1st day 916.5000 final day 91650.0000\n",
      "M=7 1st day 917.0000 final day 91700.0000\n",
      "M=8 1st day 916.0000 final day 91600.0000\n",
      "M=9 1st day 915.7500 final day 91575.0000\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\"\"\"\n",
    "Multiple    Rarity\n",
    "6           30.55%\n",
    "7           26.18%\n",
    "8           22.91%\n",
    "9           20.36%\n",
    "\"\"\"\n",
    "\n",
    "rarities = [0.3055, 0.2618, 0.2291, 0.2036]\n",
    "multiples = [6, 7, 8, 9]\n",
    "white_list_num = 2000\n",
    "\n",
    "# total 2000 mint whitelist\n",
    "# print([2000 * rarities[i] for i in range(4)])\n",
    "# [611.0, 523.5999999999999, 458.2, 407.2]\n",
    "# after Round\n",
    "# m_distribution = [611, 523, 458, 407]\n",
    "m_distribution = [round(white_list_num * rarities[i]) for i in range(len(multiples))]\n",
    "print(\"multiple distribution: \", m_distribution)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "def single_goo(time_elasped):\n",
    "\n",
    "    m_goo = []\n",
    "    for i in range(len(multiples)):\n",
    "        m_goo.append(compute_goo_balance(multiples[i], 0, time_elasped))\n",
    "\n",
    "    return m_goo\n",
    "\n",
    "\n",
    "def sum_goo(time_elasped):\n",
    "\n",
    "    one_goo = single_goo(time_elasped)\n",
    "    total_goo = []\n",
    "    for i in range(len(m_distribution)):\n",
    "        total_goo.append(one_goo[i] * m_distribution[i])\n",
    "\n",
    "    return sum(total_goo), total_goo\n",
    "\n",
    "\n",
    "final_day = 10\n",
    "\n",
    "begin_goo = single_goo(1)\n",
    "end_goo = single_goo(final_day)\n",
    "\n",
    "print(\"from 1st day to {}st day one Golbers produced GOO\".format(final_day))\n",
    "print(\"M=6 1st day {:.4f} final day {:.4f}\".format(begin_goo[0], end_goo[0]))\n",
    "print(\"M=7 1st day {:.4f} final day {:.4f}\".format(begin_goo[1], end_goo[1]))\n",
    "print(\"M=8 1st day {:.4f} final day {:.4f}\".format(begin_goo[2], end_goo[2]))\n",
    "print(\"M=9 1st day {:.4f} final day {:.4f}\".format(begin_goo[3], end_goo[3]))\n",
    "print(\"\")\n",
    "\n",
    "(_, begin_goo) = sum_goo(1)\n",
    "(_, end_goo) = sum_goo(final_day)\n",
    "\n",
    "print(\"from 1st day to {}st day all Golbers produced GOO\".format(final_day))\n",
    "print(\"M=6 1st day {:.4f} final day {:.4f}\".format(begin_goo[0], end_goo[0]))\n",
    "print(\"M=7 1st day {:.4f} final day {:.4f}\".format(begin_goo[1], end_goo[1]))\n",
    "print(\"M=8 1st day {:.4f} final day {:.4f}\".format(begin_goo[2], end_goo[2]))\n",
    "print(\"M=9 1st day {:.4f} final day {:.4f}\".format(begin_goo[3], end_goo[3]))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4 holders\n",
      "day 3.17 mint_from_goo price 22.5528 buyer m0 9 m 16.33 gobblers 2 balance 0.0002 total cost 22.5528\n",
      "day 3.34 mint_from_goo price 22.2619 buyer m0 8 m 15.33 gobblers 2 balance 0.0092 total cost 22.2619\n",
      "day 3.53 mint_from_goo price 21.7962 buyer m0 7 m 14.33 gobblers 2 balance 0.0104 total cost 21.7962\n",
      "day 3.75 mint_from_goo price 21.1118 buyer m0 6 m 13.33 gobblers 2 balance 0.0045 total cost 21.1118\n",
      "day 5.01 mint_from_goo price 13.9380 buyer m0 9 m 23.659999999999997 gobblers 3 balance 0.0066 total cost 36.4908\n",
      "day 5.18 mint_from_goo price 13.7378 buyer m0 8 m 22.66 gobblers 3 balance 0.0102 total cost 35.9997\n",
      "day 5.40 mint_from_goo price 13.3064 buyer m0 7 m 21.66 gobblers 3 balance 0.0086 total cost 35.1026\n",
      "day 5.67 mint_from_goo price 12.6940 buyer m0 6 m 20.66 gobblers 3 balance 0.0006 total cost 33.8057\n",
      "day 6.31 mint_from_goo price 10.5250 buyer m0 9 m 30.989999999999995 gobblers 4 balance 0.0077 total cost 47.0157\n",
      "day 6.49 mint_from_goo price 10.3431 buyer m0 8 m 29.990000000000002 gobblers 4 balance 0.0024 total cost 46.3428\n",
      "day 6.72 mint_from_goo price 9.9812 buyer m0 7 m 28.990000000000002 gobblers 4 balance 0.0183 total cost 45.0838\n",
      "day 7.01 mint_from_goo price 9.4409 buyer m0 6 m 27.990000000000002 gobblers 4 balance 0.0162 total cost 43.2466\n",
      "day 7.34 mint_from_goo price 8.7787 buyer m0 9 m 38.31999999999999 gobblers 5 balance 0.0017 total cost 55.7944\n",
      "day 7.54 mint_from_goo price 8.5664 buyer m0 8 m 37.32 gobblers 5 balance 0.0187 total cost 54.9092\n",
      "day 7.75 mint_from_goo price 8.3530 buyer m0 7 m 36.32 gobblers 5 balance 0.0102 total cost 53.4368\n",
      "day 8.03 mint_from_goo price 7.9214 buyer m0 6 m 35.32 gobblers 5 balance 0.0176 total cost 51.1680\n",
      "day 8.23 mint_from_goo price 7.7326 buyer m0 9 m 45.64999999999999 gobblers 6 balance 0.0137 total cost 63.5270\n",
      "day 8.40 mint_from_goo price 7.6188 buyer m0 8 m 44.65 gobblers 6 balance 0.0190 total cost 62.5279\n",
      "day 8.62 mint_from_goo price 7.4015 buyer m0 7 m 43.65 gobblers 6 balance 0.0119 total cost 60.8382\n",
      "day 8.88 mint_from_goo price 7.0687 buyer m0 6 m 42.65 gobblers 6 balance 0.0150 total cost 58.2367\n",
      "day 8.98 mint_from_goo price 7.1452 buyer m0 9 m 52.97999999999999 gobblers 7 balance 0.0060 total cost 70.6723\n",
      "day 9.16 mint_from_goo price 7.0478 buyer m0 8 m 51.98 gobblers 7 balance 0.0108 total cost 69.5758\n",
      "day 9.38 mint_from_goo price 6.8341 buyer m0 7 m 50.98 gobblers 7 balance 0.0120 total cost 67.6724\n",
      "day 9.62 mint_from_goo price 6.5560 buyer m0 6 m 49.98 gobblers 7 balance 0.0062 total cost 64.7927\n",
      "day 9.68 mint_from_goo price 6.7586 buyer m0 9 m 60.30999999999999 gobblers 8 balance 0.0164 total cost 77.4308\n",
      "day 9.85 mint_from_goo price 6.6789 buyer m0 8 m 59.309999999999995 gobblers 8 balance 0.0174 total cost 76.2546\n",
      "gobblers last_price 6.634450413220582\n",
      "gobblers last_price 26\n",
      "final gobblers hold num:  [7, 8, 7, 8]\n",
      "\n",
      "2000 holders\n",
      "day 3.17 mint_from_goo price 22.5528 buyer m0 9 m 16.33 gobblers 2 balance 0.0002 total cost 22.5528\n",
      "day 3.22 mint_from_goo price 23.2756 buyer m0 9 m 16.33 gobblers 2 balance 0.0098 total cost 23.2756\n",
      "day 3.27 mint_from_goo price 24.0216 buyer m0 9 m 16.33 gobblers 2 balance 0.0080 total cost 24.0216\n",
      "day 3.32 mint_from_goo price 24.7823 buyer m0 9 m 16.33 gobblers 2 balance 0.0181 total cost 24.7823\n",
      "day 3.37 mint_from_goo price 25.5671 buyer m0 9 m 16.33 gobblers 2 balance 0.0163 total cost 25.5671\n",
      "day 3.42 mint_from_goo price 26.3767 buyer m0 9 m 16.33 gobblers 2 balance 0.0018 total cost 26.3767\n",
      "day 3.48 mint_from_goo price 27.1918 buyer m0 9 m 16.33 gobblers 2 balance 0.0253 total cost 27.1918\n",
      "day 3.53 mint_from_goo price 28.0425 buyer m0 9 m 16.33 gobblers 2 balance 0.0104 total cost 28.0425\n",
      "day 3.58 mint_from_goo price 28.9091 buyer m0 9 m 16.33 gobblers 2 balance 0.0084 total cost 28.9091\n",
      "day 3.64 mint_from_goo price 29.7914 buyer m0 9 m 16.33 gobblers 2 balance 0.0202 total cost 29.7914\n",
      "day 3.69 mint_from_goo price 30.7006 buyer m0 9 m 16.33 gobblers 2 balance 0.0187 total cost 30.7006\n",
      "day 3.75 mint_from_goo price 31.6375 buyer m0 9 m 16.33 gobblers 2 balance 0.0031 total cost 31.6375\n",
      "day 3.81 mint_from_goo price 32.5910 buyer m0 9 m 16.33 gobblers 2 balance 0.0017 total cost 32.5910\n",
      "day 3.86 mint_from_goo price 33.5608 buyer m0 9 m 16.33 gobblers 2 balance 0.0155 total cost 33.5608\n",
      "day 3.92 mint_from_goo price 34.5594 buyer m0 9 m 16.33 gobblers 2 balance 0.0150 total cost 34.5594\n",
      "day 3.98 mint_from_goo price 35.5745 buyer m0 9 m 16.33 gobblers 2 balance 0.0306 total cost 35.5745\n",
      "day 4.04 mint_from_goo price 36.6194 buyer m0 9 m 16.33 gobblers 2 balance 0.0315 total cost 36.6194\n",
      "day 4.09 mint_from_goo price 37.6951 buyer m0 9 m 16.33 gobblers 2 balance 0.0168 total cost 37.6951\n",
      "day 4.15 mint_from_goo price 38.7879 buyer m0 9 m 16.33 gobblers 2 balance 0.0188 total cost 38.7879\n",
      "day 4.21 mint_from_goo price 39.9124 buyer m0 9 m 16.33 gobblers 2 balance 0.0047 total cost 39.9124\n",
      "day 4.27 mint_from_goo price 41.0543 buyer m0 9 m 16.33 gobblers 2 balance 0.0082 total cost 41.0543\n",
      "day 4.33 mint_from_goo price 42.2132 buyer m0 9 m 16.33 gobblers 2 balance 0.0303 total cost 42.2132\n",
      "day 4.39 mint_from_goo price 43.4209 buyer m0 9 m 16.33 gobblers 2 balance 0.0006 total cost 43.4209\n",
      "day 4.45 mint_from_goo price 44.6300 buyer m0 9 m 16.33 gobblers 2 balance 0.0258 total cost 44.6300\n",
      "day 4.52 mint_from_goo price 45.8728 buyer m0 9 m 16.33 gobblers 2 balance 0.0346 total cost 45.8728\n",
      "day 4.58 mint_from_goo price 47.1503 buyer m0 9 m 16.33 gobblers 2 balance 0.0260 total cost 47.1503\n",
      "day 4.64 mint_from_goo price 48.4453 buyer m0 9 m 16.33 gobblers 2 balance 0.0381 total cost 48.4453\n",
      "day 4.70 mint_from_goo price 49.7759 buyer m0 9 m 16.33 gobblers 2 balance 0.0324 total cost 49.7759\n",
      "day 4.77 mint_from_goo price 51.1430 buyer m0 9 m 16.33 gobblers 2 balance 0.0081 total cost 51.1430\n",
      "day 4.83 mint_from_goo price 52.5282 buyer m0 9 m 16.33 gobblers 2 balance 0.0053 total cost 52.5282\n",
      "day 4.90 mint_from_goo price 53.9309 buyer m0 9 m 16.33 gobblers 2 balance 0.0255 total cost 53.9309\n",
      "day 4.96 mint_from_goo price 55.3711 buyer m0 9 m 16.33 gobblers 2 balance 0.0272 total cost 55.3711\n",
      "day 5.03 mint_from_goo price 56.8497 buyer m0 9 m 16.33 gobblers 2 balance 0.0094 total cost 56.8497\n",
      "day 5.09 mint_from_goo price 58.3462 buyer m0 9 m 16.33 gobblers 2 balance 0.0158 total cost 58.3462\n",
      "day 5.16 mint_from_goo price 59.8820 buyer m0 9 m 16.33 gobblers 2 balance 0.0024 total cost 59.8820\n",
      "day 5.23 mint_from_goo price 61.4355 buyer m0 9 m 16.33 gobblers 2 balance 0.0144 total cost 61.4355\n",
      "day 5.29 mint_from_goo price 63.0293 buyer m0 9 m 16.33 gobblers 2 balance 0.0063 total cost 63.0293\n",
      "day 5.36 mint_from_goo price 64.6405 buyer m0 9 m 16.33 gobblers 2 balance 0.0252 total cost 64.6405\n",
      "day 5.43 mint_from_goo price 66.2928 buyer m0 9 m 16.33 gobblers 2 balance 0.0238 total cost 66.2928\n",
      "day 5.50 mint_from_goo price 67.9874 buyer m0 9 m 16.33 gobblers 2 balance 0.0008 total cost 67.9874\n",
      "day 5.57 mint_from_goo price 69.6995 buyer m0 9 m 16.33 gobblers 2 balance 0.0063 total cost 69.6995\n",
      "day 5.64 mint_from_goo price 71.4282 buyer m0 9 m 16.33 gobblers 2 balance 0.0420 total cost 71.4282\n",
      "day 5.71 mint_from_goo price 73.2269 buyer m0 9 m 16.33 gobblers 2 balance 0.0039 total cost 73.2269\n",
      "day 5.78 mint_from_goo price 75.0152 buyer m0 9 m 16.33 gobblers 2 balance 0.0497 total cost 75.0152\n",
      "day 5.85 mint_from_goo price 76.8757 buyer m0 9 m 16.33 gobblers 2 balance 0.0196 total cost 76.8757\n",
      "day 5.92 mint_from_goo price 78.7532 buyer m0 9 m 16.33 gobblers 2 balance 0.0213 total cost 78.7532\n",
      "day 5.99 mint_from_goo price 80.6466 buyer m0 9 m 16.33 gobblers 2 balance 0.0567 total cost 80.6466\n",
      "day 6.06 mint_from_goo price 82.6161 buyer m0 9 m 16.33 gobblers 2 balance 0.0120 total cost 82.6161\n",
      "day 6.13 mint_from_goo price 84.6024 buyer m0 9 m 16.33 gobblers 2 balance 0.0008 total cost 84.6024\n",
      "day 6.21 mint_from_goo price 86.6043 buyer m0 9 m 16.33 gobblers 2 balance 0.0253 total cost 86.6043\n",
      "day 6.28 mint_from_goo price 88.6536 buyer m0 9 m 16.33 gobblers 2 balance 0.0263 total cost 88.6536\n",
      "day 6.35 mint_from_goo price 90.7514 buyer m0 9 m 16.33 gobblers 2 balance 0.0028 total cost 90.7514\n",
      "day 6.43 mint_from_goo price 92.8643 buyer m0 9 m 16.33 gobblers 2 balance 0.0171 total cost 92.8643\n",
      "day 6.50 mint_from_goo price 95.0265 buyer m0 9 m 16.33 gobblers 2 balance 0.0067 total cost 95.0265\n",
      "day 6.57 mint_from_goo price 97.2030 buyer m0 9 m 16.33 gobblers 2 balance 0.0363 total cost 97.2030\n",
      "day 6.65 mint_from_goo price 99.4293 buyer m0 9 m 16.33 gobblers 2 balance 0.0414 total cost 99.4293\n",
      "day 6.72 mint_from_goo price 101.7066 buyer m0 9 m 16.33 gobblers 2 balance 0.0208 total cost 101.7066\n",
      "day 6.80 mint_from_goo price 103.9975 buyer m0 9 m 16.33 gobblers 2 balance 0.0425 total cost 103.9975\n",
      "day 6.88 mint_from_goo price 106.3401 buyer m0 9 m 16.33 gobblers 2 balance 0.0385 total cost 106.3401\n",
      "day 6.95 mint_from_goo price 108.7354 buyer m0 9 m 16.33 gobblers 2 balance 0.0078 total cost 108.7354\n",
      "day 7.03 mint_from_goo price 111.1434 buyer m0 9 m 16.33 gobblers 2 balance 0.0220 total cost 111.1434\n",
      "day 7.11 mint_from_goo price 113.6048 buyer m0 9 m 16.33 gobblers 2 balance 0.0095 total cost 113.6048\n",
      "day 7.18 mint_from_goo price 116.0776 buyer m0 9 m 16.33 gobblers 2 balance 0.0446 total cost 116.0776\n",
      "day 7.26 mint_from_goo price 118.6042 buyer m0 9 m 16.33 gobblers 2 balance 0.0532 total cost 118.6042\n",
      "day 7.34 mint_from_goo price 121.1859 buyer m0 9 m 16.33 gobblers 2 balance 0.0342 total cost 121.1859\n",
      "day 7.42 mint_from_goo price 123.7779 buyer m0 9 m 16.33 gobblers 2 balance 0.0656 total cost 123.7779\n",
      "day 7.50 mint_from_goo price 126.4253 buyer m0 9 m 16.33 gobblers 2 balance 0.0697 total cost 126.4253\n",
      "day 7.58 mint_from_goo price 129.1293 buyer m0 9 m 16.33 gobblers 2 balance 0.0453 total cost 129.1293\n",
      "day 7.66 mint_from_goo price 131.8423 buyer m0 9 m 16.33 gobblers 2 balance 0.0744 total cost 131.8423\n",
      "day 7.74 mint_from_goo price 134.6123 buyer m0 9 m 16.33 gobblers 2 balance 0.0753 total cost 134.6123\n",
      "day 7.82 mint_from_goo price 137.4406 buyer m0 9 m 16.33 gobblers 2 balance 0.0468 total cost 137.4406\n",
      "day 7.90 mint_from_goo price 140.2762 buyer m0 9 m 16.33 gobblers 2 balance 0.0752 total cost 140.2762\n",
      "day 7.98 mint_from_goo price 143.1703 buyer m0 9 m 16.33 gobblers 2 balance 0.0747 total cost 143.1703\n",
      "day 8.06 mint_from_goo price 146.1242 buyer m0 9 m 16.33 gobblers 2 balance 0.0439 total cost 146.1242\n",
      "day 8.14 mint_from_goo price 149.0837 buyer m0 9 m 16.33 gobblers 2 balance 0.0737 total cost 149.0837\n",
      "day 8.22 mint_from_goo price 152.1032 buyer m0 9 m 16.33 gobblers 2 balance 0.0737 total cost 152.1032\n",
      "day 8.31 mint_from_goo price 155.1839 buyer m0 9 m 16.33 gobblers 2 balance 0.0428 total cost 155.1839\n",
      "day 8.39 mint_from_goo price 158.2682 buyer m0 9 m 16.33 gobblers 2 balance 0.0762 total cost 158.2682\n",
      "day 8.47 mint_from_goo price 161.4139 buyer m0 9 m 16.33 gobblers 2 balance 0.0793 total cost 161.4139\n",
      "day 8.56 mint_from_goo price 164.6222 buyer m0 9 m 16.33 gobblers 2 balance 0.0509 total cost 164.6222\n",
      "day 8.64 mint_from_goo price 167.8320 buyer m0 9 m 16.33 gobblers 2 balance 0.0908 total cost 167.8320\n",
      "day 8.72 mint_from_goo price 171.1043 buyer m0 9 m 16.33 gobblers 2 balance 0.0998 total cost 171.1043\n",
      "day 8.81 mint_from_goo price 174.4406 buyer m0 9 m 16.33 gobblers 2 balance 0.0767 total cost 174.4406\n",
      "day 8.89 mint_from_goo price 177.8419 buyer m0 9 m 16.33 gobblers 2 balance 0.0204 total cost 177.8419\n",
      "day 8.98 mint_from_goo price 181.2423 buyer m0 9 m 16.33 gobblers 2 balance 0.0370 total cost 181.2423\n",
      "day 9.06 mint_from_goo price 184.7077 buyer m0 9 m 16.33 gobblers 2 balance 0.0211 total cost 184.7077\n",
      "day 9.15 mint_from_goo price 188.1697 buyer m0 9 m 16.33 gobblers 2 balance 0.0825 total cost 188.1697\n",
      "day 9.23 mint_from_goo price 191.6965 buyer m0 9 m 16.33 gobblers 2 balance 0.1121 total cost 191.6965\n",
      "day 9.32 mint_from_goo price 195.2895 buyer m0 9 m 16.33 gobblers 2 balance 0.1090 total cost 195.2895\n",
      "day 9.41 mint_from_goo price 198.9499 buyer m0 9 m 16.33 gobblers 2 balance 0.0717 total cost 198.9499\n",
      "day 9.49 mint_from_goo price 202.6037 buyer m0 9 m 16.33 gobblers 2 balance 0.1169 total cost 202.6037\n",
      "day 9.58 mint_from_goo price 206.4013 buyer m0 9 m 16.33 gobblers 2 balance 0.0094 total cost 206.4013\n",
      "day 9.67 mint_from_goo price 210.1141 buyer m0 9 m 16.33 gobblers 2 balance 0.1069 total cost 210.1141\n",
      "day 9.75 mint_from_goo price 213.9731 buyer m0 9 m 16.33 gobblers 2 balance 0.0491 total cost 213.9731\n",
      "day 9.84 mint_from_goo price 217.8223 buyer m0 9 m 16.33 gobblers 2 balance 0.0796 total cost 217.8223\n",
      "day 9.93 mint_from_goo price 221.7407 buyer m0 9 m 16.33 gobblers 2 balance 0.0757 total cost 221.7407\n",
      "gobblers last_price 227.1580359156627\n",
      "gobblers num_sold 96\n",
      "\n"
     ]
    }
   ],
   "source": [
    "\n",
    "time_step = 0.001\n",
    "\n",
    "\"\"\"\n",
    "4 whitelist holders\n",
    "\"\"\"\n",
    "print(\"4 holders\")\n",
    "\n",
    "gobblers = ArtGobblers()\n",
    "holders = [Holder(6), Holder(7), Holder(8), Holder(9)]\n",
    "random.shuffle(holders)\n",
    "\n",
    "cur_t = 0\n",
    "while cur_t < final_day:\n",
    "    gobblers.update(cur_t)\n",
    "    gobblers_price = gobblers.last_price\n",
    "    for _holder in holders:\n",
    "        _holder.update_balance(cur_t)\n",
    "        if _holder.balance >= gobblers_price:\n",
    "            gobblers.mint_from_goo(_holder, cur_t)\n",
    "    cur_t += time_step\n",
    "\n",
    "print(\"gobblers last_price\", gobblers.last_price)\n",
    "print(\"gobblers last_price\", gobblers.num_sold)\n",
    "print(\"final gobblers hold num: \", [_holder.gobblers for _holder in holders])\n",
    "print(\"\")\n",
    "\n",
    "\n",
    "\"\"\"\n",
    "many whitelist holders\n",
    "\"\"\"\n",
    "print(\"2000 holders\")\n",
    "\n",
    "gobblers = ArtGobblers()\n",
    "holders = []\n",
    "\n",
    "for i in range(len(multiples)):\n",
    "    for j in range(m_distribution[i]):\n",
    "        holders.append(Holder(multiples[i]))\n",
    "\n",
    "random.shuffle(holders)\n",
    "\n",
    "cur_t = 0\n",
    "x_labels_gobblers = []\n",
    "y_data_gobblers = []\n",
    "# compare hold group\n",
    "ydata_m6 = []\n",
    "ydata_m7 = []\n",
    "ydata_m8 = []\n",
    "ydata_m9 = []\n",
    "\n",
    "while cur_t < final_day:\n",
    "    gobblers.update(cur_t)\n",
    "    gobblers_price = gobblers.last_price\n",
    "    for _holder in holders:\n",
    "        _holder.update_balance(cur_t)\n",
    "        if _holder.balance >= gobblers.last_price:\n",
    "            gobblers.mint_from_goo(_holder, cur_t)\n",
    "\n",
    "    x_labels_gobblers.append(cur_t)\n",
    "    y_data_gobblers.append(gobblers_price)\n",
    "\n",
    "    m_goo = single_goo(cur_t)\n",
    "    ydata_m6.append(m_goo[0])     # multiple 6\n",
    "    ydata_m7.append(m_goo[1])     # multiple 7\n",
    "    ydata_m8.append(m_goo[2])     # multiple 8\n",
    "    ydata_m9.append(m_goo[3])     # multiple 9\n",
    "\n",
    "    cur_t += time_step\n",
    "\n",
    "print(\"gobblers last_price\", gobblers.last_price)\n",
    "print(\"gobblers num_sold\", gobblers.num_sold)\n",
    "# print(\"final gobblers hold num: \", [_holder.gobblers for _holder in holders])\n",
    "print(\"\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.lines import Line2D\n",
    "\n",
    "fig = plt.figure(figsize=(16, 8))\n",
    "ax = fig.add_subplot(1, 1, 1)\n",
    "ax.set_title('Price never falls bellow M9 holders\\' balance, untill they all have minted', {'fontsize': 20})\n",
    "ax.set_xlabel('days', {'fontsize': 14})\n",
    "ax.set_ylabel('gobbler price', {'fontsize': 14})\n",
    "ax.tick_params(axis='both', which='major', labelsize=12)\n",
    "ax.tick_params(axis='both', which='minor', labelsize=12)\n",
    "ax.plot(x_labels_gobblers, y_data_gobblers)\n",
    "ax.plot(x_labels_gobblers, ydata_m6)\n",
    "ax.plot(x_labels_gobblers, ydata_m7)\n",
    "ax.plot(x_labels_gobblers, ydata_m8)\n",
    "ax.plot(x_labels_gobblers, ydata_m9)\n",
    "custom_lines = [\n",
    "    Line2D(x_labels_gobblers, y_data_gobblers, color='tab:blue'),\n",
    "    Line2D(x_labels_gobblers, ydata_m6, color='tab:orange'),\n",
    "    Line2D(x_labels_gobblers, ydata_m7, color='tab:green'),\n",
    "    Line2D(x_labels_gobblers, ydata_m8, color='tab:red'),\n",
    "    Line2D(x_labels_gobblers, ydata_m9, color='tab:purple'),\n",
    "]\n",
    "ax.legend(custom_lines, ['gobblers price', 'hold M=6',\n",
    "          'hold M=7', 'hold M=8', 'hold M=9'])\n",
    "\n",
    "fig.savefig('gobblers-price.png', transparent=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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