FIP36_simulation-mild_growth_assumption.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "558b2589",
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "from tqdm import tqdm\n",
    "import datetime\n",
    "from datetime import timedelta\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.pyplot import figure\n",
    "from functools import lru_cache\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f90e5e30",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = (35,25)\n",
    "font = {'family' : 'normal',\n",
    "        'weight' : 'bold',\n",
    "        'size'   : 22}\n",
    "\n",
    "matplotlib.rc('font', **font)\n",
    "\n",
    "def closest_value(input_list, input_value):\n",
    " \n",
    "    arr = np.asarray(input_list)\n",
    " \n",
    "    i = (np.abs(arr - input_value)).argmin()\n",
    " \n",
    "    return arr[i], i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8fb626b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "epochsInYear = 2880*365\n",
    "LAM = math.log(2)/(6*epochsInYear)\n",
    "EXP_LAM_SUB_ONE = ((math.e)**LAM)-1\n",
    "SIMPLE_TOTAL = 330000000\n",
    "BASELINE_TOTAL = 770000000\n",
    "BASELINE_INITIAL_VALUE = 2888888880000000000\n",
    "BASELINE_EXPONENT = ((math.e)**(math.log(2)/epochsInYear))\n",
    "PB_MULTIPLIER=1024*1024*1024*1024*1024\n",
    "\n",
    "SECTOR = 32*1024*1024*1024\n",
    "\n",
    "#START_EPOCH = 2053894\n",
    "#START_THETA = 1423894\n",
    "#START_EPOCH_RB_POWER = 17274.2*PB_MULTIPLIER\n",
    "#START_EPOCH_QAP = 18463*PB_MULTIPLIER\n",
    "#START_EPOCH_CIRCULATION = 335204823\n",
    "\n",
    "START_EPOCH = 1903090\n",
    "def epoch_2_idx(epoch):\n",
    "    if epoch < START_EPOCH:\n",
    "        print(\"This epoch \" + str(epoch) + \" is too small!!\")\n",
    "        return 0\n",
    "    return int(epoch - START_EPOCH)\n",
    "\n",
    "START_EPOCH_RB_POWER = 16793.6*PB_MULTIPLIER\n",
    "START_EPOCH_QAP = 17704.96*PB_MULTIPLIER\n",
    "START_EPOCH_CIRCULATION = 310160000\n",
    "\n",
    "START_EPOCH_EFFECTIVE_TIME = 1782511\n",
    "START_THETA = 1782510.7077148725421923\n",
    "START_EPOCH_CUM_REAL = 9810862042507329709495504\n",
    "START_EPOCH_CUM_BASELINE = 9810864777723068410860243\n",
    "\n",
    "\n",
    "ICO_2Y_RELEASE_PER_EPOCH = 7223364 / epochsInYear / 2\n",
    "ICO_2Y_END_EPOCH = 2 * epochsInYear\n",
    "ICO_3Y_RELEASE_PER_EPOCH = (87637883 + 898958) / epochsInYear / 3\n",
    "ICO_3Y_END_EPOCH = 3 * epochsInYear\n",
    "PL_RELEASE_PER_EPOCH = 400000000 / epochsInYear / 6\n",
    "PL_END_EPOCH = 6 * epochsInYear #Didn't use in this simulation\n",
    "\n",
    "def get_baseline_power(epoch):\n",
    "    return BASELINE_INITIAL_VALUE * (BASELINE_EXPONENT**epoch)\n",
    "\n",
    "def get_start_epoch_cumsum_baseline_power(start_epoch):\n",
    "    start_epoch_cumsum_baseline_power = 0\n",
    "    for epoch in range(1, start_epoch+1):\n",
    "        start_epoch_cumsum_baseline_power += get_baseline_power(epoch)\n",
    "    return start_epoch_cumsum_baseline_power\n",
    "\n",
    "START_EPOCH_CUMSUM_BASELINE_POWER = get_start_epoch_cumsum_baseline_power(START_EPOCH)\n",
    "\n",
    "def get_date_by_epoch(epoch):\n",
    "    genesis_time = datetime.datetime(2020,8,25, 6, 0, 30)\n",
    "    td = timedelta(seconds=(epoch-1)*30)\n",
    "    return (genesis_time+td).date().isoformat()\n",
    "\n",
    "def sigmoid(epoch, start_epoch):\n",
    "    x = epoch-start_epoch\n",
    "    return 2*(1-1/(1+expneg((1/365/2880)*x)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "65fc8718",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2022-06-17'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_date_by_epoch(1903090)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "365e7c66",
   "metadata": {},
   "outputs": [],
   "source": [
    "## Assumptions we can modify\n",
    "HIGH_SPEED_INC_EPOCH = 1943280 #Power increase was high before 7/1/2022\n",
    "FIP36_EPOCH = HIGH_SPEED_INC_EPOCH + 4 * 31 * 2880 #assume start the FIP in about early of Nov\n",
    "FIP36_POST_1M_EPOCH = FIP36_EPOCH + 1 * 30 *2880\n",
    "FIP36_POST_6M_EPOCH = FIP36_EPOCH + 6 * 30 *2880\n",
    "FIP36_POST_12M_EPOCH = FIP36_EPOCH + 12 * 30 *2880\n",
    "FIP36_POST_36M_EPOCH = FIP36_EPOCH + 36 * 30 *2880\n",
    "\n",
    "TURNING_POINTS = [HIGH_SPEED_INC_EPOCH, FIP36_EPOCH, FIP36_POST_1M_EPOCH, FIP36_POST_6M_EPOCH, FIP36_POST_12M_EPOCH, FIP36_POST_36M_EPOCH]\n",
    "\n",
    "\n",
    "RB_POWER_INC_ASSUMPTIONS = [20*PB_MULTIPLIER/2880, 14*PB_MULTIPLIER/2880, 1*PB_MULTIPLIER/2880, 0.5*PB_MULTIPLIER/2880, 0.5*PB_MULTIPLIER/2880, 0.5*PB_MULTIPLIER/2880, 0.5*PB_MULTIPLIER/2880]\n",
    "if len(TURNING_POINTS)+1 != len(RB_POWER_INC_ASSUMPTIONS):\n",
    "    print(\"Assumptions for RB power increase doesn't match\")\n",
    "\n",
    "RB_POWER_EXP_ASSUMPTIONS = [10*PB_MULTIPLIER/2880, 10*PB_MULTIPLIER/2880, 40*PB_MULTIPLIER/2880, 30*PB_MULTIPLIER/2880, 15*PB_MULTIPLIER/2880, 5*PB_MULTIPLIER/2880, 2*PB_MULTIPLIER/2880]\n",
    "if len(TURNING_POINTS)+1 != len(RB_POWER_EXP_ASSUMPTIONS):\n",
    "    print(\"Assumptions for RB power expire doesn't match\")\n",
    "    \n",
    "QAP_INC_ASSUMPTIONS = [RB_POWER_INC_ASSUMPTIONS[0]*1.1, 20*PB_MULTIPLIER/2880, 40*PB_MULTIPLIER/2880, 80*PB_MULTIPLIER/2880, 80*PB_MULTIPLIER/2880, 60*PB_MULTIPLIER/2880, 80*PB_MULTIPLIER/2880]\n",
    "if len(TURNING_POINTS)+1 != len(QAP_INC_ASSUMPTIONS):\n",
    "    print(\"Assumptions for qap increase doesn't match\")\n",
    "    \n",
    "QAP_EXP_ASSUMPTIONS = [RB_POWER_EXP_ASSUMPTIONS[0], RB_POWER_EXP_ASSUMPTIONS[1]*1.1, RB_POWER_EXP_ASSUMPTIONS[2]*1.1, RB_POWER_EXP_ASSUMPTIONS[3]*1.2, RB_POWER_EXP_ASSUMPTIONS[4]*2, RB_POWER_EXP_ASSUMPTIONS[5]*5, RB_POWER_EXP_ASSUMPTIONS[6]*10]\n",
    "#QAP_EXP_ASSUMPTIONS = [RB_POWER_EXP_ASSUMPTIONS[0], RB_POWER_EXP_ASSUMPTIONS[1]*1.1, RB_POWER_EXP_ASSUMPTIONS[2]*1.1, RB_POWER_EXP_ASSUMPTIONS[3]*1.2, RB_POWER_EXP_ASSUMPTIONS[4]*2, RB_POWER_EXP_ASSUMPTIONS[5]*2, RB_POWER_EXP_ASSUMPTIONS[6]*5]\n",
    "if len(TURNING_POINTS)+1 != len(QAP_EXP_ASSUMPTIONS):\n",
    "    print(\"Assumptions for qap expire doesn't match\")\n",
    "                       \n",
    "def get_assumption(epoch, assumptions):\n",
    "    turning_point_idx = 0\n",
    "    for turning_point in TURNING_POINTS:\n",
    "        if epoch < turning_point:\n",
    "            return assumptions[turning_point_idx]\n",
    "        turning_point_idx += 1\n",
    "    if assumptions[-1] != assumptions[turning_point_idx]:\n",
    "        print(\"SOMETHING IS WRONG WHNE YOU DEFINE YOUR ASSUMPTIONS\")\n",
    "    return assumptions[-1]\n",
    "                       \n",
    "\n",
    "#QAP_EXP_AFTER_FIP =  RB_POWER_EXP_AFTER_FIP * 1.1\n",
    "\n",
    "BURN_PER_EPOCH = 18000/2880 #burn rate now is 15000 ~ 20000\n",
    "SECTOR_LIFE = 365*2880\n",
    "\n",
    "DEBUG = 0\n",
    "\n",
    "CROSS_EPOCH_REACH = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0a5b032c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_assumption(FIP36_POST_12M_EPOCH-100, RB_POWER_EXP_ASSUMPTIONS)*2880/PB_MULTIPLIER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5acb4645",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_assumption(FIP36_POST_36M_EPOCH*2, RB_POWER_EXP_ASSUMPTIONS)*2880/PB_MULTIPLIER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "60b45d81",
   "metadata": {},
   "outputs": [],
   "source": [
    "current_epoch=START_EPOCH\n",
    "current_theta=START_THETA\n",
    "thetas = [START_THETA]\n",
    "\n",
    "current_epoch_rb_power = START_EPOCH_RB_POWER\n",
    "epoch_rb_powers = [current_epoch_rb_power]\n",
    "\n",
    "current_epoch_qap = START_EPOCH_QAP\n",
    "epoch_qaps = [current_epoch_qap]\n",
    "\n",
    "epoch_circulations = [START_EPOCH_CIRCULATION]\n",
    "\n",
    "eff_net_times = [START_EPOCH_EFFECTIVE_TIME]\n",
    "cumsum_reals = [START_EPOCH_CUM_REAL]\n",
    "cumsum_bases = [START_EPOCH_CUM_BASELINE]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "450e8304",
   "metadata": {},
   "outputs": [],
   "source": [
    "def expneg(x):\n",
    "    return (math.e)**(-1*x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1e388927",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_qap_inc(epoch):\n",
    "    return get_assumption(epoch, QAP_INC_ASSUMPTIONS)\n",
    "    \n",
    "def get_qap_exp(epoch):\n",
    "    return get_assumption(epoch, QAP_EXP_ASSUMPTIONS)\n",
    "    \n",
    "def get_rb_inc(epoch):\n",
    "    return get_assumption(epoch, RB_POWER_INC_ASSUMPTIONS)\n",
    "    \n",
    "def get_rb_exp(epoch):\n",
    "    return get_assumption(epoch, RB_POWER_EXP_ASSUMPTIONS)\n",
    "    \n",
    "def get_qap_change(epoch):\n",
    "    return get_qap_inc(epoch) - get_qap_exp(epoch)\n",
    "\n",
    "def get_rb_change(epoch):\n",
    "    return get_rb_inc(epoch) - get_rb_exp(epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bf0a1eb1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_rb_power(epoch):\n",
    "    latest_epoch = len(epoch_rb_powers) + START_EPOCH - 1\n",
    "    while latest_epoch < epoch:\n",
    "        latest_epoch += 1\n",
    "        latest_rb_power = epoch_rb_powers[-1]\n",
    "        latest_rb_power = latest_rb_power + get_rb_change(latest_epoch)\n",
    "        epoch_rb_powers.append(latest_rb_power)\n",
    "    return epoch_rb_powers[epoch_2_idx(epoch)]\n",
    "\n",
    "def get_qap(epoch):\n",
    "    latest_epoch = len(epoch_qaps) + START_EPOCH - 1\n",
    "    while latest_epoch < epoch:\n",
    "        latest_epoch += 1\n",
    "        latest_qap = epoch_qaps[-1]\n",
    "        latest_qap = latest_qap + get_qap_change(latest_epoch)\n",
    "        epoch_qaps.append(latest_qap)        \n",
    "    return epoch_qaps[epoch_2_idx(epoch)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f7e19100",
   "metadata": {},
   "outputs": [],
   "source": [
    "def computeBaselineSupply(theta):\n",
    "    theta_lam = LAM * theta\n",
    "    eTL = expneg(theta_lam)\n",
    "    oneSub = 1 - eTL\n",
    "    return BASELINE_TOTAL * oneSub\n",
    "\n",
    "def get_eff_net_time(epoch):\n",
    "    update_buddle(epoch)\n",
    "    return eff_net_times[epoch_2_idx(epoch)]\n",
    "\n",
    "def get_cum_base(epoch):\n",
    "    update_buddle(epoch)\n",
    "    return cumsum_bases[epoch_2_idx(epoch)]\n",
    "\n",
    "def get_cum_real(epoch):\n",
    "    update_buddle(epoch)\n",
    "    return cumsum_reals[epoch_2_idx(epoch)]\n",
    "\n",
    "    \n",
    "def update_buddle(epoch):\n",
    "    global CROSS_EPOCH_REACH\n",
    "    last_epoch = len(cumsum_reals) + START_EPOCH - 1\n",
    "    while last_epoch < epoch:\n",
    "        last_epoch += 1\n",
    "        baseline_power = get_baseline_power(last_epoch)\n",
    "        if (get_rb_power(last_epoch) < baseline_power) and (CROSS_EPOCH_REACH)==0:\n",
    "            #print(\"Major event occur!! Baseline over take rb power now at epoch: \"+str(last_epoch))\n",
    "            #print(\"date is: \", get_date_by_epoch(last_epoch))\n",
    "            #print(\"baseline_power: \"+str(baseline_power/PB_MULTIPLIER))\n",
    "            #print(\"raw bytes power: \"+str(get_rb_power(last_epoch)/PB_MULTIPLIER))\n",
    "            CROSS_EPOCH_REACH=1\n",
    "        capped_real_power = min(get_rb_power(last_epoch), baseline_power)\n",
    "        cumsum_real = cumsum_reals[-1] + capped_real_power\n",
    "        cumsum_base = cumsum_bases[-1]\n",
    "        eff_net_time = eff_net_times[-1]\n",
    "        while cumsum_real > cumsum_base:\n",
    "            eff_net_time += 1\n",
    "            effective_baseline_power = get_baseline_power(eff_net_time)\n",
    "            cumsum_base += effective_baseline_power\n",
    "        cumsum_reals.append(cumsum_real)\n",
    "        cumsum_bases.append(cumsum_base)\n",
    "        eff_net_times.append(eff_net_time)\n",
    "        #print(\"for epoch: \"+str(last_epoch)+\" cumsum_real: \"+str(cumsum_real)+\" cusum_base:\"+str(cumsum_base)+\" eff_net_time \"+str(eff_net_time)+\" baseline: \"+str(get_baseline_power(last_epoch)) )\n",
    "            \n",
    "    \n",
    "def get_theta(epoch):\n",
    "    eff_net_time = get_eff_net_time(epoch)\n",
    "    diff = (get_cum_base(epoch) - get_cum_real(epoch)) / get_baseline_power(eff_net_time)\n",
    "    return eff_net_time - diff\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "5c1e57f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "def baseline_rewawrd(epoch):\n",
    "    return computeBaselineSupply(get_theta(epoch)) - computeBaselineSupply(get_theta(epoch-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f3ee5669",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.787439227582243"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def simple_reward(epoch):\n",
    "    simple_reward = SIMPLE_TOTAL*EXP_LAM_SUB_ONE\n",
    "    epoch_lam=LAM*epoch\n",
    "    simple_reward = simple_reward*expneg(epoch_lam)\n",
    "    return simple_reward\n",
    "simple_reward(2054274)/5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9d11f05a",
   "metadata": {},
   "outputs": [],
   "source": [
    "@lru_cache\n",
    "def block_reward(epoch):\n",
    "    return simple_reward(epoch)+baseline_rewawrd(epoch)\n",
    "\n",
    "@lru_cache\n",
    "def block_reward_by_power(epoch, power=SECTOR):\n",
    "    total_reward = block_reward(epoch)\n",
    "    return power / get_qap(epoch-1) * total_reward"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "40c53d21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20.370252455404767"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "block_reward(2086567)/5 #0.03 fil gap between with reality 20.338"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "80b937d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "@lru_cache\n",
    "def get_total_br(epoch): #the epoch is the time to \"ESTIMATIE\"\n",
    "    epoch_ = (2 * epoch + 2880) / 2\n",
    "    return block_reward(epoch_) * 2880\n",
    "\n",
    "@lru_cache\n",
    "def get_total_20_br(epoch): #the epoch is the time to \"ESTIMATIE\"\n",
    "    epoch_ = (2 * epoch + 20 * 2880) / 2\n",
    "    return block_reward(epoch_) * 20 * 2880"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e02f77ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_pledge(epoch):\n",
    "    pledge = 0\n",
    "    if epoch < FIP36_EPOCH:\n",
    "        pledge = get_total_20_br(epoch) * get_qap_inc(epoch) / get_qap(epoch-1) \n",
    "        #print(\"IP is: \"+str(pledge))\n",
    "        pledge = pledge + 3.0 / 10.0 * get_qap_inc(epoch) / max(get_qap(epoch-1), get_baseline_power(epoch-1)) * get_circulation(epoch-1)\n",
    "        #print(\"last epoch circulation is: \"+str(get_circulation(epoch-1)))\n",
    "        #print(\"all is: \"+str(pledge))\n",
    "    else:\n",
    "        pledge = get_total_20_br(epoch) * get_qap_inc(epoch) / get_qap(epoch-1)\n",
    "        pledge = pledge + 5 / 10 * get_qap_inc(epoch) / max(get_qap(epoch-1), get_baseline_power(epoch-1)) * get_circulation(epoch-1)\n",
    "    return pledge\n",
    "\n",
    "def get_pledge_by_power(epoch, power=SECTOR):\n",
    "    pledge = 0\n",
    "    if epoch < FIP36_EPOCH:\n",
    "        pledge = get_total_20_br(epoch) * power / get_qap(epoch-1) \n",
    "        #print(\"IP is: \"+str(pledge))\n",
    "        pledge = pledge + 3.0 / 10.0 * power / max(get_qap(epoch-1), get_baseline_power(epoch-1)) * get_circulation(epoch-1)\n",
    "        #print(\"last epoch circulation is: \"+str(get_circulation(epoch-1)))\n",
    "        #print(\"all is: \"+str(pledge))\n",
    "    else:\n",
    "        pledge = get_total_20_br(epoch) * power / get_qap(epoch-1)\n",
    "        pledge = pledge + 5.0 / 10.0 * power / max(get_qap(epoch-1), get_baseline_power(epoch-1)) * get_circulation(epoch-1)\n",
    "    return pledge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b050bfa5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_expire_pledge(epoch):\n",
    "    if epoch > START_EPOCH + epochsInYear:\n",
    "        return get_qap_exp(epoch) / get_qap_inc(epoch-epochsInYear) * get_pledge(epoch-epochsInYear)\n",
    "    else:\n",
    "        return get_qap_exp(epoch) / get_qap_inc(epoch) * get_pledge(epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "56a816c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_circulation(epoch):\n",
    "    latest_epoch = len(epoch_circulations) + START_EPOCH - 1\n",
    "    \n",
    "    while latest_epoch < epoch:\n",
    "        latest_epoch += 1\n",
    "        latest_circ = epoch_circulations[-1]\n",
    "        vesting = 0\n",
    "        if latest_epoch < ICO_2Y_END_EPOCH:\n",
    "            vesting += ICO_2Y_RELEASE_PER_EPOCH\n",
    "        if latest_epoch < ICO_3Y_END_EPOCH:\n",
    "            vesting += ICO_3Y_RELEASE_PER_EPOCH\n",
    "        if latest_epoch < PL_END_EPOCH:\n",
    "            vesting += PL_RELEASE_PER_EPOCH\n",
    "        if DEBUG and (latest_epoch % 2880 == 0):\n",
    "            print(\"The vesting is: \" + str(vesting) + \" in epoch \" + str(latest_epoch))\n",
    "        \n",
    "        pledge = get_pledge(latest_epoch)\n",
    "        if DEBUG and (latest_epoch % 2880 == 0):\n",
    "            print(\"The pledge is: \" + str(pledge) + \" in epoch \" + str(latest_epoch))\n",
    "            print(\"Wile the total qap is: \" + str(get_qap(latest_epoch-1))  + \" in epoch \" + str(latest_epoch))\n",
    "\n",
    "            \n",
    "        reward = block_reward(latest_epoch)\n",
    "        if DEBUG and (latest_epoch % 2880 == 0):\n",
    "            print(\"The block_reward is: \" + str(reward/5) + \" in epoch \" + str(latest_epoch))\n",
    "            \n",
    "        expire_pledge = get_expire_pledge(latest_epoch)\n",
    "        if DEBUG and (latest_epoch % 2880 == 0):\n",
    "            print(\"The expire_pledge is: \" + str(expire_pledge) + \" in epoch \" + str(latest_epoch))\n",
    "            \n",
    "        latest_circ = latest_circ + vesting - pledge + reward + expire_pledge - BURN_PER_EPOCH\n",
    "        epoch_circulations.append(latest_circ)\n",
    "        \n",
    "        if DEBUG and (latest_epoch % 2880 == 0):\n",
    "            print(\"The latest_circ is: \" + str(latest_circ) + \" in epoch \" + str(latest_epoch))\n",
    "        \n",
    "        \n",
    "        \n",
    "    return epoch_circulations[epoch_2_idx(epoch)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d085a942",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "343214027.92824167"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_circulation(2094514) # actual 343,106,924 at 8/22 noon, the gap is a bit over 1000 fil a day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "76badaf0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████| 79/79 [00:06<00:00, 12.63it/s]\n",
      "findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2520x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot rb trend in next 6 years\n",
    "a = []\n",
    "b = []\n",
    "for epoch in tqdm(range(START_EPOCH+10, START_EPOCH+6*epochsInYear, 28*2880)):\n",
    "    a.append(get_date_by_epoch(epoch))\n",
    "    b.append(get_rb_power(epoch))\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(a, b)\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "458c0c86",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████| 79/79 [00:06<00:00, 12.37it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2520x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot qap trend in next 6 years\n",
    "\n",
    "a = []\n",
    "b = []\n",
    "for epoch in tqdm(range(START_EPOCH+10, START_EPOCH+6*epochsInYear, 28*2880)):\n",
    "    a.append(get_date_by_epoch(epoch))\n",
    "    b.append(get_qap(epoch))\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(a, b)\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ae642f8d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████| 79/79 [01:54<00:00,  1.45s/it]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2520x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot pledge trend in next 6 years\n",
    "\n",
    "a = []\n",
    "b = []\n",
    "for epoch in tqdm(range(START_EPOCH+10, START_EPOCH+6*epochsInYear, 28*2880)):\n",
    "    a.append(get_date_by_epoch(epoch))\n",
    "    b.append(get_pledge(epoch))\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(a, b)\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4fbaddb8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████| 79/79 [00:00<00:00, 46754.62it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2520x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot exp pledge trend in next 6 years\n",
    "\n",
    "a = []\n",
    "b = []\n",
    "for epoch in tqdm(range(START_EPOCH+10, START_EPOCH+6*epochsInYear, 28*2880)):\n",
    "    a.append(get_date_by_epoch(epoch))\n",
    "    b.append(get_expire_pledge(epoch))\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(a, b)\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "65494418",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████| 79/79 [00:00<00:00, 71705.26it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2520x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot reward trend in next 6 years\n",
    "\n",
    "a = []\n",
    "b = []\n",
    "for epoch in tqdm(range(START_EPOCH+10, START_EPOCH+6*epochsInYear, 28*2880)):\n",
    "    a.append(get_date_by_epoch(epoch))\n",
    "    b.append(block_reward(epoch))\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(a, b)\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "685ae43e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████| 79/79 [00:00<00:00, 208527.39it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2520x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot circulation trend in next 6 years\n",
    "\n",
    "a = []\n",
    "b = []\n",
    "for epoch in tqdm(range(START_EPOCH+10, START_EPOCH+6*epochsInYear, 28*2880)):\n",
    "    a.append(get_date_by_epoch(epoch))\n",
    "    b.append(get_circulation(epoch))\n",
    "import matplotlib.pyplot as plt\n",
    "plt.plot(a, b)\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e54d328d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████| 131/131 [10:48<00:00,  4.95s/it]\n"
     ]
    }
   ],
   "source": [
    "rois = []\n",
    "start_dates = []\n",
    "start_epochs = []\n",
    "\n",
    "rbp_cross_x = 0\n",
    "rbp_cross_y = 0\n",
    "rbp_crossed = 0\n",
    "\n",
    "qap_cross_x = 0\n",
    "qap_cross_y = 0\n",
    "qap_crossed = 0\n",
    "\n",
    "for epoch in tqdm(range(START_EPOCH+10, START_EPOCH+5*epochsInYear, 14*2880)):\n",
    "    start_epochs.append(epoch)\n",
    "    start_dates.append(get_date_by_epoch(epoch))\n",
    "    cost = get_pledge_by_power(epoch)\n",
    "    reward_epoch = epoch\n",
    "    reward=0\n",
    "    for reward_epoch in range(epoch, epoch+SECTOR_LIFE):\n",
    "        epoch_reward = block_reward_by_power(reward_epoch)\n",
    "        reward += epoch_reward\n",
    "        if epoch_reward < 0:\n",
    "            print(\"reward_epoch: \"+str(reward_epoch)+\" epoch_reward: \"+str(epoch_reward))\n",
    "        \n",
    "    rois.append(reward/cost)\n",
    "    \n",
    "    if not rbp_crossed and get_baseline_power(epoch) > get_rb_power(epoch):\n",
    "        rbp_cross_x = get_date_by_epoch(epoch)\n",
    "        rbp_cross_y = reward/cost\n",
    "        rbp_crossed = 1\n",
    "        \n",
    "    if not qap_crossed and get_baseline_power(epoch) > get_qap(epoch):\n",
    "        qap_cross_x = get_date_by_epoch(epoch)\n",
    "        qap_cross_y = reward/cost\n",
    "        qap_crossed = 1\n",
    "    \n",
    "    #print(\"epoch: \"+str(epoch)+\" cost: \"+str(cost)+\" reward: \"+str(reward))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c23ed391",
   "metadata": {},
   "outputs": [],
   "source": [
    "turning_points_x=[]\n",
    "turning_points_y=[]\n",
    "for turning_point in TURNING_POINTS:\n",
    "    x, idx = closest_value(start_epochs, turning_point)\n",
    "    x = start_dates[idx]\n",
    "    y = rois[idx]\n",
    "    turning_points_x.append(x)\n",
    "    turning_points_y.append(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "42125d24",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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ypuOVX3f3DR5+X1N9JWe1jc9Z7S1Z2D4hZ7W1ZH5bS85qG5+ZgjwAAAAAjFllWebpjXvy7ee25tvPbc2qHfuTJBfPnZw3D4f2xdMnVHlKzlQnHN2LoqhP8pkkH/gpb3siyVvKstx+nMP9cZLf+BlvG0zy78qy/I/H8pmiOwBwyOBgmW37uocj/P6sHf55dcf+bNh5IH0Dr/y3UGN9JfOmjsuCtvGZ39qSBW2HfgwdWd9U754nAAAAADiV+gcG8/CanUMb7c9vy5Y93amrFLlqYWtuOX9m3nTejMyeMq7aY1IDflp0rz/Gz/gveXVw70zyYJKlSRYPP3dpkjuKoriuLMvBjMy2JE8laU5yRZJD/x9SSfIfiqJ4vCzLb47wswGAGlSpFJk1eVxmTR6Xaxe1v+q1/oHBbNnTnXWdB7Ju5/6s7zyQtZ37s67zQB5c3ZkDvQOH31sUyezJ4w7H+HmtLZk7dVzmtbZk3tSWtE9oTFFUYUt+cDCpuIsKAAAAgDPHwd6B3PPyjnz7ua35wYrt2X2gL031ldx4zrT8zpuX5g3Lpmfq+MZqjwmH/czoXhTFkiSfOOKpDUkuK8uyoyiKuiRfS/K24deuTvJLSf7qOOf4bpL/K8kPy+HV+6IoFiT5YZKFR7zvI0lEdwBgVNTXVYaieWtLrs+rg3xZluno6s36nUMRfl3ngazfeSDrOvfney9sS0dX76ve39xQydypLZl3RIif1zpu+LmWTG5pGP0/QFdXMn168r73JZ/8ZLJgwej/HgAAAABwCuw50Jfvr9iWbz+3NXe/tCPdfYOZ1FyfN547I28+f2ZuPKc9LY3Huk8Mp9bPPF6+KIr/mOTfHPHUvz3ymPeiKG5Ics8Rr/+4LMsbj3mAophdluXmn/Daryb51BFPrSjL8tyf9ZmOlwcATrYDvf3ZuOtgNuw8cPjnDbsOZMPOg9mw60D2dfe/6v0Tm+szb2pLZk8Zl7lTx2XOlHGZPWVc5gz/ekSb8jt3JjNnDv26ri65/XbxHQAAAIDTxpY9B/O957fl289ty4OrO9M/WGbGpKa8+byh+9mvOrs1DXVOeWRsONHj5W846vEjr/G4THLou8RXFUXRWJZlb47BTwruw7Yc9XjPsXwmAMDJ1tJYn3NmTMw5Mya+5ut7DvRlw64D2XhEiD8U5x9c3ZmunldH+cb6SuZMORTjmzNnSkvmTB369dIZE9M2oem1B6lUkp6epK8v+dznki98QXwHAAAAYEwqyzLPb9mb7z2/Pd99YWue3bQ3SXJ2+/j86g1n55bzZ+TiuVNSqVThGkc4AccS3Zcd9fhVkbwsy+6iKHYnmTr8VGOGjoR/8YSnS2496vGPRuEzAQBOusktDZncMjkXzJn8mq/vOdiXTbsOZvPug9l05I9dB/PDF3dkx76eV71/QVtLLp03JZfMm5JL50/NubMm5R/dWtXXJ74DAAAAMKb09g/moTWd+e7z2/K957dl857uFEVy2fyp+ZdvWZY3nTc9i6e/9mILnC6O5Xj5nuRV39NdVJbl6qPesyHJ3COeuqYsywdPaLCieHOG7m+vG35qd5Lzf8pR9B/J0J3vmT9//uXr1q07kd8eAKCqevoHsmV3dzbuOpjnNu/JE+t35/H1u7J9OMY31ldy4YzxufTrf5tLNzyXSze/mFn7OvKqfwPc0ODYeQAAAABOuT0H+vLDF7fnuy9sy90v7khXT3+aGyq5Ycm0vOncGXndsumZNvEnnOwIY9RPO15+JNF9cVmWq456z8Ykc4546uqyLB8a4bwpiuLtSb6QZNzwUz1JbivL8vvH8vXudAcAzkRlWWbLnu48sX53nli/K0+s6cgz6zrTWz/0n2oz9nXm0s0rcunmF3P5phdy2aYVqaQU3wEAAAA46dZ3Hsh3XxjaZn947c4MDJZpn9CUN547PW88d0auX9Ke5oa6n/1BMEadaHTflmT6EU9dVJblM0e9Z2deOV4+SZaVZTmi4+WLovhwkj/PKxvuB5K8pyzLbx3rZ4juAEBN2LkzvXPn54XJs/PE7KV5YvayPDF7adZPnZUkWbBrc/7JE3fl55/5bqZ0d4nvAAAAAIyawcEyT23cne+9sC3fe357Xty2L0lyzowJeeO5M/Km89zPzpnlRKP7PUluOOKpW48M4EVRtCTZf8TrvUkmlmXZO4JB/88k/+GIpzqTvO14j6oX3QGAmrBzZzJ7dtLz6vvfO1om574Fl+RvLn1rHpl3fpr6evKOF+7JBx+/MxduW5VUKklra7J161CEBwAAAIBj0N03kPtWdgyF9he2Z8e+ntRVilxx1tS86byZeeO507OgbXy1x4ST4qdF9/pj+Pqjo/uVSY7cOr/iqPc/dLzBvSiKSpI/SvLRI55em+SWsixfOp7PAgCode0H9uSdL9ydd75wd16YdlY+e+lt+dr5N+eLF70pF299OR8ctyu3/e6vpFlwBwAAAOBn6OjqyQ9WbM93n9+WH7+8I919g5nQVJ+blg7dz37z0mmZ0tL4sz8IzmDHsum+JMmKJJXhpzYmuawsyx1FUdQn+XqSW4/4kg+VZflXR3z97yX5d0e8/itlWX7miNebkvxtkvcc8Z4nkry1LMutx/sHSmy6AwA14idsuv8jDQ3ZO25ivvyB385n51+V1bt70jq+Me9bPi8fuGp+5rW2nJp5AQAAABjzyrLMqh37893nt+V7L2zL4+t3pSyT2ZOb88bzZuSN587IVWe3pqneQge15YQ23cuyfLkoij9M8lvDT81N8kJRFA8mWZpk8RFvfyjJZ49zvv87rw7uSbI9yR8XxT++46Esy/ce5+cDANSmQ3e4/8IvZNInP5lfmT8/HyrL3L+qM599YF0+9ePV+fN7VuX1S6fnn1yzIDctmeaOLQAAAIAa1Ns/mEfW7sz3X9ieH6zYlrWdB5IkF8yZlE+8YUnedN6MnDdrUl6r3QHHdrx8kvyLJDOSvH/4cVuS2456z5NJ3lmW5eBxzjDlNZ675Tg/AwCAQ46I7fnkJ5P58w+/VBRFrlvcnusWt2fLnoP53EPr83cPb8j3P/1IFrS15J9ctSA/v3yuI8EAAAAAznA79vXkRy9uzw9WbM+PX+5IV09/GusruXZRWz58/cK84dwZmT1lXLXHhNPCMUX3siz7k3ygKIq/S/KrSa7KUHjfl+TZJF9I8qmyLPtO1qAAAPwMh2L77bcPxfYFC37q22dNHpffefPS/Obrl+Rbz23NZx9Ym9//5gv5r995Me+4eHY+eM1ZuXDu5FM0PAAAAAAnU1mWeW7z3vxgxfZ8f8X2PL1xd8oymTGpKW+/eHbesGx6rl3clpbGY93ZBQ75mXe6n47c6Q4A1ISdO5OZM4d+fRyx/ad5fvPe/M1D6/K1JzblQO9ALpk3Jb909YLcdtGsNDe4pwsAAADgdHKgtz/3rezMD1Zsyw9WbM+2vT0piuTiuVPy+mXT8/pl03P+bMfGw7H4aXe6i+4AAKerrq5k+vTkfe874dh+tL3dffnyYxvz2QfXZfWO/Wkd35j3LZ+XD1w1P/NaW0bt9wEAAABgdG3cdSA/WDF0bPz9qzrT2z+YCU31uWFJe16/bHpuXjo90yY2VXtMOO2I7gAAZ6rBwaRSOWkfX5Zl7l/Vmb9+YG2++/y2lElev3R6fumaBblxybRUKv4VNAAAAEA19Q8M5okNu4dC+wvb8+K2fUmSs9pa8vplM/KGc6fnirNa01h/8r6HBLVAdAcA4IRt3n0wf/fw+vzdwxvS0dWTBW0t+SdXLcjPL5+bKS2N1R4PAAAAoGbsOdCXu1/ekR+8sC0/emlHdh/oS32lyBVnteYN5w4dG3/2tAnVHhPOKKI7AACjprd/MN96bms++8DaPLJ2V5rqK3n7xbPzgavm55J5U9wBBgAAADDKyrLMqh1d+f4L2/P9Fdvz2LpdGRgs0zq+MTcvnZY3LJuRG85pz6TmhmqPCmcs0R0AgJPi+c178zcPrcvXntiUA70DOW/WpLz/qvn5uUvnZEJTfbXHAwAAADhtHewdyAOrO/KjF3fkRy/uyPqdB5Ik586alNcvm5bXL5uRS+ZNSZ3r/+CUEN0BADip9nX35Y4nN+dvH1qfF7bszfjGurzjkjn5wFXzc8GcydUeDwAAAGDMK8syazr2D0X2l3bkwdWd6e0fzLiGuly7qC2vWzZ0bPzsKeOqPSrUJNEdAIBToizLPLlhdz730Pr8w9Ob0903mIvnTs4HrlqQt108Ky2Ntt8BAAAADjnYO5AHV3fmRy9uz49e2pF1nUPb7GdPG5+bz5me1y2blivOak1zQ12VJwVEdwAATrk9B/vy1cc35m8fWp+Xt3dlYlN93n3ZnLz/qgVZOnNitccDAAAAqIqhbfbt+dGLQ9vsPf2DaW6o5NpF7bl56bTcfM70zG9rqfaYwFFEdwAAqqYsyzy6blf+9sF1+eYzW9M7MJjlC6bm/VfNz1svnOVfagMAAABntO6+gTywujN3v7gjP3pxe9Ye2mZvH5+blk7LzUun56qFttlhrBPdAQAYE3bu782XH9uYzz28Pms69mdic31+7pI5uf2Kee5+BwAAAM4Y6zr354crho6Mf2DVK9vs15zdlpuXTs/NS6dlQdv4ao8JHAfRHQCAMaUsyzywqjNfeHRD7np2a3r7B3PBnEm5ffm8vOOSOZk8rqHaIwIAAAAcs+6+gTy0Zmd+uGJ77n5pR9Z07E+SLGwfn5vOmZabl07L1We32WaH05joDgDAmLXnQF++9uSmfP6RDXlhy9401Vfy1gtn5fYr5uWqha0piqLaIwIAAAD8I+s7D+RHL23PD1dszwOrO9PdN5im+kquWdSWm88ZOjb+rHbb7HCmEN0BABjzyrLMs5v25vOPrM/Xn9ycfT39Wdg+Pj+/fG7ee9ncTJ/UXO0RAQAAgBq2v6c/D6zqzD0v78g9L+04fDf7graWvG7p9Ny0dFqusc0OZyzRHQCA08rB3oF885kt+cKjG/Lwmp2pqxR53dLp+YUr5uXmpdNSX1ep9ogAAADAGW5wsMzzW/YejuyPrduVvoEy4xrqcvXZrblxeJt9oW12qAmiOwAAp63VO7ry949uzJce25iOrp5Mm9iUd186J++9fG6WzJhY7fEAAACAM0hHV09+/PKO3PNSR3788o50dPUmSZbNnJibzpmWG8+ZluVnTU1TvW12qDWiOwAAp72+gcH8YMX2fPHRjfnhi9szMFjm4rmT897L5+btF8/OlJbGao8IAAAAnGZ6+wfz2Lpdh7fZn9u8N0nSOr4x1y9uz43nTMuNS9pdeweI7gAAnFl27OvJHU9uypce25gVW/elsa6SN503I++9fG5uWNLu+HkAAADgJ1rbsf9wZH9gVWf29w6kvlLksgVTh7bZl0zL+bMnpVIpqj0qMIaI7gAAnJHKssxzm/fmS49tzB1PbsquA32Hj59/z+Vzc47j5wEAAKDm7evuywOrOodDe0fW7zyQJJnf2pIbz2nPjUum5ZpFbZnY3FDlSYGxTHQHAOCM19s/mB++uD1femxjfrhie/oHy1w0fPz8Oxw/DwAAADVjcHDoH+nf8/KO3P3Sjjy+blf6B8u0NNbl2kVtw0fGT8tZ7eOrPSpwGhHdAQCoKR1dPbnjyc354qMbDh8///pl0/Ouy+bkdUunp7He8fMAAABwJtm6pzv3ruzIj1/ekXtf7kjn/t4kyfmzJx2O7JcvmOp7AsCIie4AANSs5zbvyZce25h/eGpzOrp6M6WlIbddOCvvvmxOLps/NUXhfjYAAAA43XT19OfBVZ25d2VH7l3ZkZXbu5Ik7RMac8OSabnxnPZcv3hapk1sqvKkwJlCdAcAoOb1DQzm3pc78tUnNuU7z29Nd99g5re25OcunZN3XTonCx0pBwAAAGNW/8Bgntq4Oz9+uSP3rezIE+t3p3+wTHNDJVcubMsNi9tz/ZL2LJ0xMZWKf2APjD7RHQAAjrCvuy/ffm5bvvrExty/qjNlmVwyb0refdmcvO2i2Wkd7/53AAAAqKayLLO6Y3/ufbkjP365Iw+t7sy+nv4URXLRnMm5bjiyX75gaprq66o9LlADRHcAAPgJtu7pzh1PbspXn9iUFVv3pb5S5Oal0/KuS+fmDedOT3OD/+EOAAAAp0JHV0/uW9mRe4e32Tfv6U6SzG9tyfVL2nP94vZcu6gtU1r8Y3ng1BPdAQDgGLywZW+++sSm3PHkpmzb25OJTfW55YKZeecls3PN2W2pr6tUe0QAAAA4YxzsHcjDa3fmvpVD2+wvbNmbJJk8riHXLW7L9Yun5frF7Znf1lLlSQFEdwAAOC4Dg2UeWNWZrz6xKd9+bmu6evrTPqEpb7toVt5xyexcOm9KisL9cAAAAHA8BgbLPLd5z+F72R9duyu9A4NprKvk8gVTc/2S9tywpD3nz56cOveyA2OM6A4AACPU3TeQH67Ynq8/tTnfX7E9vf2Dmdc6Lu+4eHbecfGcLJ05sdojAgAAwJi1vvNA7l3ZkXtX7sj9qzqz+0BfkuTcWZNy/eK2XL9kWq48qzXjGl3vBoxtojsAAIyCvd19+c5z2/L1pzbnvpUdGRgss2zmxLz94tl5x8WzM6/VcXcAAADUtu17u/PA6s7ct7Ij96/qzMZdB5MksyY35/rF7bl+SXuuXdSeaRObqjwpwPER3QEAYJR1dPXkm89syR1Pbs5j63YlSS6bPyXvvGRO3nrhLN88AAAAoCbsOdCXB1Z35oFVQ5H95e1dSZJJzfW5ZlFbrl3UnusWt2fRtPGuagNOa6I7AACcRBt2Hsg/PL05X39yc1Zs3ZdKkVx9dlvedtHsvOWCmWkd31jtEQEAAGBUHOjtzyNrd+X+VR25f2Vnnt28J2WZjGuoy5ULW3PtcGg/b/Yk97IDZxTRHQAATpGXtu3LnU9tzp1Pb8nqjv2pqxS5dlFb3nbRrNxy/sxMaRHgAQAAOH309g/myQ27c9/KjjywqjNPbNiVvoEyDXVFLp0/Ndcuast1i9tz8dwpaayvVHtcgJNGdAcAgFOsLMu8sGVf7nx6KMCv33kg9ZUiNyxpz20Xzc6bzpuRyeMaqj0mAAAAvMrAYJnnNu/J/as6c/+qzjyyZmcO9g2kKJIL50zOtYvac+2itiw/a2paGuurPS7AKSO6AwBAFZVlmWc37c2dz2zOnU9tyabdB9NYV8mN57Tntotm5Y3nzsjEZgEeAACAU68sy6zc3pX7V3XmvpUdeXB1Z/Z29ydJlkyfkOsWt+eaRW25emFbJrf4365A7RLdAQBgjCjLMk9t3JM7n9qcbzyzJVv2dKexvpKbz5mW2y6aldcvmy7AAwAAcFJt2HkgD6zqzH2rOnL/qs7s2NeTJJnXOi7Xnt2eaxe35ZpFbZk+sbnKkwKMHaI7AACMQYODZZ7YsCt3Pr0l33xmS7bt7Tm8AX/rBbPyRkfQAwAAMAo27T6YB1Z15sHVQz827jqYJGmf0DR8J3tbrl3UnnmtLVWeFGDsEt0BAGCMGxws8/j6Xbnr2a2565kt2bynOw11Ra5b3J63XjArbzpvRqaOb6z2mAAAAJwGNu8+mAdXdw6F9jWd2bBzKLJPbWnIVQvbcvXZrbl2cXuWTJ+QoiiqPC3A6UF0BwCA08ihI+jvemZLvvnslmzYeTB1lSLXnN2WWy+cmTefNzPTJjZVe0wAAADGiC17hiL7g6t25sE1nVnXeSBJMqWlIVctbM3VZ7fl6rPbsnTGxFQqIjvASIjuAABwmirLMs9t3pu7nt2Sbz6zNWs69qdSJFec1Zq3Xjgrb7lgZmZMcsceAABALdm2t/uVTfbVnVk7HNknNdfnqrPbcs1wZF82U2QHGC2iOwAAnAHKssyL2/blm89szbee3ZKXtnUlSS6dPyVvOX9mbjl/Zs5qH1/lKQEAABht2/d254HVnXlw9c48uLozazr2JxmK7FcubMs1i4aOjF82c1LqRHaAk0J0BwCAM9DK7fty1zNb8+3nt+bZTXuTJEtnTMwtF8zMLefPyHmzJrmbDwAA4DS0fV/34cD+4OrOrN4xFNknNte/6rj4c2eJ7ACniugOAABnuI27DuQ7z23Lt5/bmkfW7sxgmcydOi63DG/AX75gqm/EAAAAjFHb93bn4bU7Dx8Xv+pQZG+qzxULWw8fF3/ebJEdoFpEdwAAqCGdXT353gvb8u3ntuXelzvSOzCY9gmNedN5M/Lm82fm2kVtaaqvq/aYAAAANalvYDAvbNmbx9ftyuPrd+exdbuyaffBJMmEpvpccdbU4ePi23LerEmpr6tUeWIAEtEdAABqVldPf3704vZ869mt+dGLO9LV05+JTfW5edn0vOm8Gbl56bRMam6o9pgAAABnrM6unjy+fnceX78rj63blac37k5332CSZNbk5lw2f2ouWzA1ly+Ymgtmi+wAY5XoDgAApKd/IPev7My3nt2a76/Ylo6u3jTUFbn67La88dwZeeN5MzJnyrhqjwkAAHDa6u4byKodXXli/e7hTfZdWdt5IEnSUFfkvNmTc/n8qblswZRcNn9qZvvfYACnDdEdAAB4lYHBMk9u2JXvPL8t331+W1YP3xd4/uxJedN5M/LGc2fk/NmTUhTuCgQAADjSwGCZTbsOZnVHV9Z07D/8Y/WO/dm852AOZZf2CU25fDiuX75gai6YMznNDa76Ajhdie4AAMBPtWpHV743HOAfW78rZZnMmTIubzx3et543oxctbAtjfWOOAQAAGpDWZbZ0dWTNTuOiOrDP6/vPJDegcHD753YVJ+zp43PwvbxWdg+IWdPG59L5k3J3Knj/ENmgDOI6A4AAByzjq6e/OCF7fnO89ty78od6e4bzMTm+ty8dHreeO703HTOtExpaaz2mAAAACdsb3df1h6xqX7k5npXT//h9zXWV3JWW8srYb19fBYOh/a28Y3iOkANEN0BAIAROdg7kHtXduS7z2/N91/Yns79vakUyeULpuZ1y6bnDctm5JwZE3yDCQAAGLO6+wayYeeBw5vqh7bXV3fsT0dXz+H3FUUyd+q4V6L6ET9mTxmXuor/3QNQy0R3AADghA0Olnlq4+78YMX2/GDF9jy3eW+SoWPoX79sel6/bHquWdTmjkIAAOCU6+kfCutrOg5kXedQVF/buT9rOw686p71ZOiu9cNRfXhb/ez28ZnX2uJ/zwDwE4nuAADAqNu6pzs/fHF7vv/C9ty3siMH+wbS3FDJdYva8/pzhyL8rMnjqj0mAABwhjgU1td2HMja4bC+rvNA1nTs/0dhffK4hpzVPj4L21qyoO2VjfWz2sdn8riG6v0hADhtie4AAMBJ1d03kAdXd+aHK7bn+yu2Z+Oug0mSc2dNyuuXTcvrl83IJfOmOI4RAAD4qYbC+sGsPbSpPryt/tPC+lltLTlrOKwvGL53fUpLY/X+EACckUR3AADglCnLMiu3d+UHwwH+sXW7MjBYpnV8Y24+Z1pet2x6bjxnmu0SAACoUd19A9m465WN9UNhfW3n/mzefTCDPyWsn9X+SmAX1gE4lUR3AACgavYc6MvdL+/ID1dszw9f3J7dB/pSVymyfMHUvGH4GPpF0yakKGzBAwDAmWL3gd6s6zyQdTsPZH3n0DHw63cO/di6t/tVG+uTmusPH/1+ZFg/q218po4X1gEYG0R3AABgTBgYLPPkhl35/gvb84MV27Ni674kyfzWlrx+2VCAv+rs1jTV11V5UgAA4KcZGCyzZc/BoZB+OK4fyLqd+7O+80D2dve/6v3TJjZlQWtL5re1ZEHr+MxvGyesA3BaEd0BAIAxadPug0Mb8Cu2596VHenpH0xLY12uW9ye1w8fQz9nyrhqjwkAADWpu28g63ceGNpY79yfDTtfiesbdx1M78Dg4fc21BWZO7Ul81pbsqC1JQvaWjK/tSUL2sZnXuu4tDTWV/FPAgAnTnQHAADGvO6+gTywqjPfX7EtP1yxI5t2H0ySLJo2PjedMz03ntOeq89uS3ODLXg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      "text/plain": [
       "<Figure size 2520x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(start_dates, rois)\n",
    "plt.scatter(turning_points_x, turning_points_y, s=200, marker='>', c='red')\n",
    "plt.scatter([rbp_cross_x, qap_cross_x], [rbp_cross_y, qap_cross_y], s=200, marker='>', c='green')\n",
    "\n",
    "\n",
    "plt.xticks(rotation = 90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "847929d5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8cae6673",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2149ef4f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18dc79ed",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ac999eb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d70057b4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8d454743",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "935e8ded",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "faa11be0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bc6a1036",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}