1692 lines
461 KiB
Plaintext
1692 lines
461 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 1,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#import networkx as nx\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"import numpy as np\n",
|
|
"import scipy.stats as sts\n",
|
|
"import seaborn as sns\n",
|
|
"\n",
|
|
"%matplotlib inline\n",
|
|
"\n",
|
|
"#import conviction files\n",
|
|
"#from conviction_helpers import *\n",
|
|
"#from conviction_system_logic3 import *\n",
|
|
"from bonding_curve_eq import *"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"System initialization"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"hatch_raise = 100000 # fiat units\n",
|
|
"hatch_price = .1 #fiat per tokens\n",
|
|
"theta = .5 #share of funds going to funding pool at launch\n",
|
|
"\n",
|
|
"R0 = hatch_raise*(1-theta)\n",
|
|
"F0 = hatch_raise*theta\n",
|
|
"S0 = hatch_raise/hatch_price\n",
|
|
"\n",
|
|
"kappa = 2\n",
|
|
"V0 = invariant(R0,S0,kappa)\n",
|
|
"P0 = spot_price(R0, V0, kappa)\n",
|
|
"\n",
|
|
"dust = 10**-8"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"agent initialization"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#number of agents\n",
|
|
"n= 100\n",
|
|
"\n",
|
|
"#gain factors\n",
|
|
"g = np.random.normal(1, .1, size=n)\n",
|
|
"phat0 = g*F0/S0 #derivative, integral and proportion\n",
|
|
"#agents as controllers, co-steering\n",
|
|
"\n",
|
|
"#wakeup rates\n",
|
|
"gamma = sts.expon.rvs(loc=1,scale=5, size=n)\n",
|
|
"\n",
|
|
"#holdings fiat\n",
|
|
"h = sts.expon.rvs( loc=10,scale=10, size=n)\n",
|
|
"\n",
|
|
"#holdings tokens\n",
|
|
"s_dist = sts.expon.rvs(loc=10, scale=10, size=n)\n",
|
|
"s0 = s_dist/sum(s_dist)*S0\n",
|
|
"\n",
|
|
"#lambda for revenue process\n",
|
|
"lam = 200\n",
|
|
"\n",
|
|
"#phi for exiting funds\n",
|
|
"phi = .05\n",
|
|
"\n",
|
|
"#beta is param for armijo rule\n",
|
|
"beta = .9"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(array([36., 17., 14., 12., 6., 3., 7., 2., 2., 1.]),\n",
|
|
" array([ 1.0319341 , 2.96150724, 4.89108039, 6.82065354, 8.75022669,\n",
|
|
" 10.67979984, 12.60937299, 14.53894614, 16.46851929, 18.39809244,\n",
|
|
" 20.32766559]),\n",
|
|
" <a list of 10 Patch objects>)"
|
|
]
|
|
},
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a17af2a20>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist(gamma)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"params= {\n",
|
|
" 'kappa': [kappa],\n",
|
|
" 'lambda': [lam],\n",
|
|
" 'gains': [g],\n",
|
|
" 'rates':[1/gamma],\n",
|
|
" 'population':[n],\n",
|
|
" 'beta':[beta],\n",
|
|
" 'phi': [phi],\n",
|
|
" 'invariant': [V0],\n",
|
|
" 'dust' : [dust]}"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"initial_conditions = {'holdings': h,\n",
|
|
" 'tokens': s0,\n",
|
|
" 'supply': S0,\n",
|
|
" 'prices': phat0,\n",
|
|
" 'funds':F0,\n",
|
|
" 'reserve': R0,\n",
|
|
" 'spot_price': P0,\n",
|
|
" 'actions': {}}"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"{'actions': {},\n",
|
|
" 'funds': 50000.0,\n",
|
|
" 'holdings': array([11.05986715, 14.94218419, 15.48820511, 12.92408422, 16.44058258,\n",
|
|
" 10.04330453, 10.1363183 , 11.25295092, 23.30880776, 15.84820996,\n",
|
|
" 19.32519009, 30.84642311, 28.6472968 , 22.62088499, 55.7532467 ,\n",
|
|
" 14.53069067, 19.69148971, 16.03173292, 14.26035724, 12.50119405,\n",
|
|
" 17.18948811, 25.17606952, 34.37364318, 11.21207026, 10.85120593,\n",
|
|
" 16.83190876, 11.02032996, 28.55606449, 15.97294022, 18.35775853,\n",
|
|
" 10.20455263, 14.9005508 , 10.14350217, 32.71292419, 28.66446322,\n",
|
|
" 52.09840552, 31.14302571, 24.96256575, 16.82618473, 12.08821128,\n",
|
|
" 19.80327803, 17.56324532, 18.97653665, 26.4598746 , 13.95149808,\n",
|
|
" 34.51432315, 18.72391548, 16.71876591, 18.13080429, 14.53424435,\n",
|
|
" 15.379136 , 12.53012723, 10.30743761, 19.41545118, 23.93423996,\n",
|
|
" 26.64819375, 25.59097769, 26.9389408 , 68.286046 , 13.37039963,\n",
|
|
" 22.98591204, 21.70571029, 15.73671593, 19.62997574, 19.69963393,\n",
|
|
" 79.93447614, 12.43392123, 23.12653646, 21.79068931, 41.41622162,\n",
|
|
" 27.78373519, 30.10005663, 11.14577993, 38.59169558, 27.85753894,\n",
|
|
" 13.00716943, 17.14991691, 13.95504795, 17.17385954, 39.04715026,\n",
|
|
" 23.02779838, 22.63655923, 10.74827678, 29.14395308, 11.74968571,\n",
|
|
" 13.90609155, 65.13775398, 11.83838557, 39.33694545, 20.3951349 ,\n",
|
|
" 18.95801552, 15.01178109, 22.91174026, 15.97094429, 22.32785709,\n",
|
|
" 16.38798609, 17.07670376, 13.87833571, 23.16142931, 14.42884 ]),\n",
|
|
" 'prices': array([0.06502486, 0.04923535, 0.05266082, 0.04846955, 0.04627227,\n",
|
|
" 0.05071279, 0.05114012, 0.03935161, 0.04708958, 0.04819298,\n",
|
|
" 0.04360423, 0.04712211, 0.05453592, 0.05064768, 0.04538688,\n",
|
|
" 0.04487122, 0.05027221, 0.05392449, 0.0576688 , 0.04664043,\n",
|
|
" 0.04306378, 0.05062993, 0.04847401, 0.04243136, 0.05431824,\n",
|
|
" 0.05346246, 0.05105484, 0.04605105, 0.04707876, 0.05092108,\n",
|
|
" 0.04461997, 0.04903719, 0.04597559, 0.0574774 , 0.04797139,\n",
|
|
" 0.05195119, 0.04889758, 0.05751687, 0.04967615, 0.04798664,\n",
|
|
" 0.05340409, 0.04259232, 0.04341358, 0.05365862, 0.05240502,\n",
|
|
" 0.05966367, 0.04701776, 0.04193448, 0.04320229, 0.04795019,\n",
|
|
" 0.042168 , 0.05908844, 0.05058276, 0.04873113, 0.04768983,\n",
|
|
" 0.04912654, 0.04242245, 0.0490861 , 0.05203078, 0.05442437,\n",
|
|
" 0.05375595, 0.0511511 , 0.05398197, 0.03790224, 0.05684956,\n",
|
|
" 0.04608418, 0.05594797, 0.0453356 , 0.0465136 , 0.05622394,\n",
|
|
" 0.05178035, 0.04580008, 0.04096692, 0.05152421, 0.04097554,\n",
|
|
" 0.05889381, 0.05525055, 0.0441924 , 0.05235828, 0.05043502,\n",
|
|
" 0.04779179, 0.05268808, 0.05053905, 0.0521754 , 0.04950957,\n",
|
|
" 0.06201351, 0.04747159, 0.04411191, 0.04594882, 0.04805512,\n",
|
|
" 0.04307883, 0.04324429, 0.05196991, 0.05546813, 0.04199149,\n",
|
|
" 0.04487411, 0.04963048, 0.04862837, 0.04331553, 0.05608939]),\n",
|
|
" 'reserve': 50000.0,\n",
|
|
" 'spot_price': 0.09999999999999999,\n",
|
|
" 'supply': 1000000.0,\n",
|
|
" 'tokens': array([ 6421.39455145, 7840.15473045, 9720.46904127, 11672.6794578 ,\n",
|
|
" 7185.25576082, 5839.88988335, 7019.35970211, 5622.55645721,\n",
|
|
" 5671.1202087 , 6849.00929359, 6929.25894956, 9177.00415389,\n",
|
|
" 5880.60928089, 12502.45024432, 9054.64788843, 15466.88728729,\n",
|
|
" 14101.18383759, 10007.786193 , 11289.99874112, 5365.69438147,\n",
|
|
" 17604.03491337, 15885.50525694, 6722.10966317, 12989.23732282,\n",
|
|
" 10132.32858181, 17440.80003924, 19813.15686909, 6402.7736831 ,\n",
|
|
" 6537.04613587, 25027.55449448, 11169.81695748, 7858.58197433,\n",
|
|
" 7051.31847487, 5944.06595745, 6642.22698186, 10239.13928023,\n",
|
|
" 12837.47277006, 10813.19044289, 5438.17292633, 12490.27294377,\n",
|
|
" 6399.10194006, 6203.82907288, 15977.80302183, 32401.23023703,\n",
|
|
" 11884.92321748, 12709.57068791, 5922.14556825, 6324.76834414,\n",
|
|
" 6928.93710102, 5546.3434079 , 7904.75897255, 14346.29800155,\n",
|
|
" 6155.04347334, 6325.7501625 , 5831.82724859, 12483.04458524,\n",
|
|
" 6014.32119935, 5579.31027479, 17819.61856925, 5730.96343168,\n",
|
|
" 14310.0238682 , 9635.01378123, 8456.45208595, 10370.86589303,\n",
|
|
" 15772.14191643, 5788.08486562, 8929.54069272, 5944.11871272,\n",
|
|
" 6110.84465206, 5550.66560662, 9292.06922321, 9828.11455175,\n",
|
|
" 18106.24208788, 5816.75811006, 6533.85244344, 6232.82844659,\n",
|
|
" 10260.02071087, 7170.34250095, 15767.71480793, 11592.10478427,\n",
|
|
" 6192.04141453, 5496.12846049, 8855.8095317 , 8491.17044356,\n",
|
|
" 8572.09493024, 19829.20993057, 5566.0629069 , 8292.89964942,\n",
|
|
" 9387.89973201, 7140.57044842, 26768.64030166, 22139.96802228,\n",
|
|
" 7091.82087941, 15409.26327718, 5385.77025081, 9032.18948441,\n",
|
|
" 7844.00284339, 9989.76066683, 9158.19038671, 6742.90246714])}"
|
|
]
|
|
},
|
|
"execution_count": 7,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"initial_conditions"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#change in F (revenue and spending accounted for)\n",
|
|
"def revenue_process(params, step, sL, s):\n",
|
|
" lam = params['lambda']\n",
|
|
" rv = sts.expon.rvs(loc = 0, scale=1/lam)\n",
|
|
" delF= 1-1/lam+rv\n",
|
|
" \n",
|
|
" #avoid the crash (temporary hacks, tune martingale process better)\n",
|
|
" if delF <1:\n",
|
|
" if s['funds'] <1000:\n",
|
|
" delF =100\n",
|
|
" \n",
|
|
" return({'delF':delF})"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def update_funds(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" funds = s['funds']*_input['delF']\n",
|
|
" \n",
|
|
" key = 'funds'\n",
|
|
" value = funds\n",
|
|
" \n",
|
|
" return (key, value)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def update_prices(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" g = params['gains']\n",
|
|
" phat = g*s['funds']/s['supply']\n",
|
|
" \n",
|
|
" key = 'prices'\n",
|
|
" value = phat\n",
|
|
" \n",
|
|
" return (key, value)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#change in F (revenue and spending accounted for)\n",
|
|
"def choose_agents(params, step, sL, s):\n",
|
|
" n = params['population']\n",
|
|
" rates = params['rates']\n",
|
|
" \n",
|
|
" agents = []\n",
|
|
" for a in range(n):\n",
|
|
" sq_gap = (s['spot_price']-s['prices'][a])**2\n",
|
|
" pr = (rates[a]+sq_gap)/(1+sq_gap) #rates when sq_gap =0, 1 when sq_gap -> infty\n",
|
|
" rv = np.random.rand()\n",
|
|
" if rv < pr:\n",
|
|
" agents.append(a)\n",
|
|
" \n",
|
|
" #shuffle\n",
|
|
" shuffled_agents =np.random.choice(agents,len(agents), False) \n",
|
|
" \n",
|
|
" return({'agents':shuffled_agents})"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def agent_actions(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" R = s['reserve']\n",
|
|
" S = s['supply']\n",
|
|
" F = s['funds']\n",
|
|
" V0 = params['invariant']\n",
|
|
" P=s['spot_price']\n",
|
|
" \n",
|
|
" actions = []\n",
|
|
" for a in _input['agents']:\n",
|
|
" h_a = s['holdings'][a]\n",
|
|
" phat_a = s['prices'][a]\n",
|
|
" s_a = s['tokens'][a]\n",
|
|
" beta = params['beta']\n",
|
|
"\n",
|
|
" if P>phat_a: #equiv: pbar(0)>phat_a\n",
|
|
" mech = 'burn'\n",
|
|
" \n",
|
|
" #approx for burn s.t. p=phat\n",
|
|
" #armijo style\n",
|
|
" amt = s_a\n",
|
|
" \n",
|
|
" def pbar(amt):\n",
|
|
" output = withdraw_with_tax(amt, R,S, V0, params['phi'], params['kappa'])\n",
|
|
"\n",
|
|
" if not(output[2])>0:\n",
|
|
" return np.Infinity\n",
|
|
" else:\n",
|
|
" return output[2]\n",
|
|
"\n",
|
|
" if amt > 10**-8:\n",
|
|
" while pbar(amt)< phat_a:\n",
|
|
" amt = amt*beta\n",
|
|
"\n",
|
|
" else: # P<phat_a; #equiv pbar(0)<phat_a\n",
|
|
" mech = 'bond'\n",
|
|
" #approx for buy s.t. p=phat\n",
|
|
" #armijo style\n",
|
|
" amt = h_a\n",
|
|
" \n",
|
|
" def pbar(amt):\n",
|
|
" output = mint(amt, R,S, V0, params['kappa'])\n",
|
|
"\n",
|
|
" if not(output[1])>0:\n",
|
|
" return 0\n",
|
|
" else:\n",
|
|
" return output[1]\n",
|
|
" \n",
|
|
" if amt > params['dust']:\n",
|
|
" while pbar(amt)> phat_a:\n",
|
|
" amt = amt*beta\n",
|
|
" \n",
|
|
" action = {'agent':a, 'mech':mech, 'amt':amt, 'pbar':pbar(amt),'posterior':{}}\n",
|
|
" \n",
|
|
" if action['mech'] == 'bond':\n",
|
|
" h_a = h_a-amt\n",
|
|
" dS, pbar = mint(amt, R,S, V0, params['kappa'])\n",
|
|
" R = R+amt\n",
|
|
" S = S+dS\n",
|
|
" s_a = s_a+dS\n",
|
|
" P = spot_price(R, V0, kappa)\n",
|
|
" \n",
|
|
" elif action['mech'] == 'burn':\n",
|
|
" s_a = s_a-amt\n",
|
|
" dR, pbar = withdraw(amt, R,S, V0, params['kappa'])\n",
|
|
" R = R-dR\n",
|
|
" F = F + params['phi']*dR\n",
|
|
" S = S-amt\n",
|
|
" h_a = h_a + (1-params['phi'])*dR\n",
|
|
" P = spot_price(R, V0, kappa)\n",
|
|
" \n",
|
|
" action['posterior'] = {'F':F, 'S':S, 'R':R,'P':P, 'a':a,'s_a':s_a, 'h_a':h_a}\n",
|
|
" actions.append(action)\n",
|
|
" \n",
|
|
" key = 'actions'\n",
|
|
" value = actions\n",
|
|
" \n",
|
|
" return (key, value)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def resolve_actions(params, step, sL, s):\n",
|
|
" \n",
|
|
" H_a = s['holdings']\n",
|
|
" S_a = s['tokens']\n",
|
|
" \n",
|
|
" actions = s['actions']\n",
|
|
" \n",
|
|
" for action in actions:\n",
|
|
" a= action['agent']\n",
|
|
" H_a[a] = action['posterior']['h_a']\n",
|
|
" S_a[a] = action['posterior']['s_a']\n",
|
|
" \n",
|
|
" #last action only\n",
|
|
" F = action['posterior']['F']\n",
|
|
" R = action['posterior']['R']\n",
|
|
" P = action['posterior']['P']\n",
|
|
" S = action['posterior']['S']\n",
|
|
" \n",
|
|
" return({'F':F, 'S':S, 'R':R,'P':P, 'S_a':S_a, 'H_a':H_a})"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def update_F(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" F = _input['F']\n",
|
|
" \n",
|
|
" key = 'funds'\n",
|
|
" value = F\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def update_S(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" S = _input['S']\n",
|
|
" \n",
|
|
" key = 'supply'\n",
|
|
" value = S\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def update_R(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" R = _input['R']\n",
|
|
" \n",
|
|
" key = 'reserve'\n",
|
|
" value = R\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def update_P(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" P = _input['P']\n",
|
|
" \n",
|
|
" key = 'spot_price'\n",
|
|
" value = P\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def update_holdings(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" H_a = _input['H_a']\n",
|
|
" \n",
|
|
" key = 'holdings'\n",
|
|
" value = H_a\n",
|
|
" \n",
|
|
" return (key, value)\n",
|
|
"\n",
|
|
"def update_tokens(params, step, sL, s, _input):\n",
|
|
" \n",
|
|
" S_a = _input['S_a']\n",
|
|
" \n",
|
|
" sumS = np.sum(S_a)\n",
|
|
" S = _input['S']\n",
|
|
" \n",
|
|
" tokens = S_a*S/sumS\n",
|
|
" \n",
|
|
" key = 'tokens'\n",
|
|
" value = tokens\n",
|
|
" \n",
|
|
" return (key, value)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
|
|
"# The Partial State Update Blocks\n",
|
|
"partial_state_update_blocks = [\n",
|
|
" { \n",
|
|
" 'policies': { \n",
|
|
" #new proposals or new participants\n",
|
|
" 'random': revenue_process\n",
|
|
" },\n",
|
|
" 'variables': {\n",
|
|
" 'funds': update_funds,\n",
|
|
" 'prices': update_prices\n",
|
|
" }\n",
|
|
" },\n",
|
|
" {\n",
|
|
" 'policies': {\n",
|
|
" 'random': choose_agents\n",
|
|
" },\n",
|
|
" 'variables': { \n",
|
|
" 'actions': agent_actions, \n",
|
|
" }\n",
|
|
" },\n",
|
|
" {\n",
|
|
" 'policies': {\n",
|
|
" 'act': resolve_actions,\n",
|
|
" },\n",
|
|
" 'variables': {\n",
|
|
" 'funds': update_F, #\n",
|
|
" 'supply': update_S, \n",
|
|
" 'reserve': update_R,\n",
|
|
" 'spot_price': update_P,\n",
|
|
" 'holdings': update_holdings,\n",
|
|
" 'tokens': update_tokens\n",
|
|
" }\n",
|
|
" }\n",
|
|
"]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"time_periods_per_run = 500\n",
|
|
"monte_carlo_runs = 1\n",
|
|
"\n",
|
|
"from cadCAD.configuration.utils import config_sim\n",
|
|
"simulation_parameters = config_sim({\n",
|
|
" 'T': range(time_periods_per_run),\n",
|
|
" 'N': monte_carlo_runs,\n",
|
|
" 'M': params\n",
|
|
"})"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"[{'N': 1, 'T': range(0, 500), 'M': {'kappa': 2, 'lambda': 200, 'gains': array([1.30049726, 0.98470691, 1.05321633, 0.96939095, 0.92544539,\n",
|
|
" 1.01425588, 1.0228024 , 0.78703228, 0.94179167, 0.96385964,\n",
|
|
" 0.87208454, 0.94244219, 1.09071831, 1.0129536 , 0.90773756,\n",
|
|
" 0.89742438, 1.00544415, 1.07848972, 1.15337594, 0.93280853,\n",
|
|
" 0.86127553, 1.01259862, 0.96948019, 0.84862713, 1.08636476,\n",
|
|
" 1.06924922, 1.02109687, 0.92102105, 0.94157513, 1.01842161,\n",
|
|
" 0.89239949, 0.98074385, 0.91951177, 1.14954805, 0.95942784,\n",
|
|
" 1.03902388, 0.97795167, 1.15033743, 0.99352293, 0.95973281,\n",
|
|
" 1.06808185, 0.85184633, 0.86827154, 1.07317232, 1.04810033,\n",
|
|
" 1.1932734 , 0.9403552 , 0.83868956, 0.86404574, 0.95900389,\n",
|
|
" 0.84336007, 1.18176877, 1.01165514, 0.97462265, 0.95379659,\n",
|
|
" 0.98253086, 0.84844908, 0.98172198, 1.04061565, 1.08848738,\n",
|
|
" 1.07511908, 1.02302204, 1.07963931, 0.75804473, 1.13699112,\n",
|
|
" 0.92168365, 1.11895939, 0.90671204, 0.930272 , 1.12447877,\n",
|
|
" 1.035607 , 0.91600151, 0.8193384 , 1.0304841 , 0.81951079,\n",
|
|
" 1.17787616, 1.10501107, 0.88384803, 1.04716558, 1.00870046,\n",
|
|
" 0.95583572, 1.05376157, 1.01078107, 1.04350802, 0.99019131,\n",
|
|
" 1.24027027, 0.94943171, 0.88223827, 0.91897646, 0.96110246,\n",
|
|
" 0.86157656, 0.86488572, 1.03939814, 1.10936254, 0.83982981,\n",
|
|
" 0.89748225, 0.99260967, 0.97256749, 0.86631052, 1.12178784]), 'rates': array([0.11751444, 0.09959177, 0.11188741, 0.49641392, 0.67278733,\n",
|
|
" 0.06208673, 0.14887222, 0.05631604, 0.80037254, 0.14804573,\n",
|
|
" 0.72964424, 0.54145524, 0.34563681, 0.20412908, 0.12745886,\n",
|
|
" 0.92166074, 0.46745089, 0.13303627, 0.17095796, 0.22697734,\n",
|
|
" 0.07385743, 0.28831065, 0.38474022, 0.89280815, 0.12736936,\n",
|
|
" 0.38503026, 0.16210463, 0.14500682, 0.51382846, 0.69029809,\n",
|
|
" 0.33881205, 0.34937485, 0.05474289, 0.27157435, 0.13064763,\n",
|
|
" 0.7085255 , 0.07073383, 0.483336 , 0.96905413, 0.10916525,\n",
|
|
" 0.10770227, 0.35048731, 0.38933273, 0.3250805 , 0.33260263,\n",
|
|
" 0.07793718, 0.43629884, 0.57181774, 0.59195072, 0.10062208,\n",
|
|
" 0.76558002, 0.20720555, 0.11732356, 0.18774591, 0.18605133,\n",
|
|
" 0.29656868, 0.16853935, 0.07181874, 0.14191967, 0.25616456,\n",
|
|
" 0.39910766, 0.09920216, 0.12709577, 0.21351378, 0.5526183 ,\n",
|
|
" 0.17254546, 0.27002083, 0.34259554, 0.76904748, 0.23426641,\n",
|
|
" 0.95433403, 0.22574721, 0.16127948, 0.44403813, 0.07014266,\n",
|
|
" 0.11560727, 0.61385516, 0.06546837, 0.07199142, 0.04919404,\n",
|
|
" 0.23367889, 0.09286221, 0.7741666 , 0.2414841 , 0.76040473,\n",
|
|
" 0.41186495, 0.58434905, 0.20082187, 0.22899022, 0.13698614,\n",
|
|
" 0.14822741, 0.07933781, 0.17801904, 0.09043008, 0.29028465,\n",
|
|
" 0.07392798, 0.14244575, 0.20565926, 0.38622728, 0.16001222]), 'population': 100, 'beta': 0.9, 'phi': 0.05, 'invariant': 20000000.0, 'dust': 1e-08}}]\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"from cadCAD.configuration import append_configs\n",
|
|
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n",
|
|
"# The configurations above are then packaged into a `Configuration` object\n",
|
|
"append_configs(\n",
|
|
" initial_state=initial_conditions, #dict containing variable names and initial values\n",
|
|
" partial_state_update_blocks=partial_state_update_blocks, #dict containing state update functions\n",
|
|
" sim_configs=simulation_parameters #dict containing simulation parameters\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 18,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from tabulate import tabulate\n",
|
|
"from cadCAD.engine import ExecutionMode, ExecutionContext, Executor\n",
|
|
"from cadCAD import configs\n",
|
|
"import pandas as pd\n",
|
|
"\n",
|
|
"exec_mode = ExecutionMode()\n",
|
|
"multi_proc_ctx = ExecutionContext(context=exec_mode.multi_proc)\n",
|
|
"run = Executor(exec_context=multi_proc_ctx, configs=configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 19,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"\n",
|
|
" __________ ____ \n",
|
|
" ________ __ _____/ ____/ | / __ \\\n",
|
|
" / ___/ __` / __ / / / /| | / / / /\n",
|
|
" / /__/ /_/ / /_/ / /___/ ___ |/ /_/ / \n",
|
|
" \\___/\\__,_/\\__,_/\\____/_/ |_/_____/ \n",
|
|
" by BlockScience\n",
|
|
" \n",
|
|
"Execution Mode: multi_proc: [<cadCAD.configuration.Configuration object at 0x1a19c50240>]\n",
|
|
"Configurations: [<cadCAD.configuration.Configuration object at 0x1a19c50240>]\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"/Users/zargham/Documents/GitHub/conviction/bonding_curve_eq.py:56: RuntimeWarning: divide by zero encountered in double_scalars\n",
|
|
" realized_price = quantity_recieved/deltaS\n",
|
|
"/Users/zargham/Documents/GitHub/conviction/bonding_curve_eq.py:47: RuntimeWarning: divide by zero encountered in double_scalars\n",
|
|
" realized_price = deltaR/deltaS\n",
|
|
"/Users/zargham/Documents/GitHub/conviction/bonding_curve_eq.py:56: RuntimeWarning: invalid value encountered in double_scalars\n",
|
|
" realized_price = quantity_recieved/deltaS\n",
|
|
"/Users/zargham/Documents/GitHub/conviction/bonding_curve_eq.py:47: RuntimeWarning: invalid value encountered in double_scalars\n",
|
|
" realized_price = deltaR/deltaS\n",
|
|
"/Users/zargham/Documents/GitHub/conviction/bonding_curve_eq.py:37: RuntimeWarning: invalid value encountered in double_scalars\n",
|
|
" realized_price = deltaR/deltaS\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"i = 0\n",
|
|
"verbose = False\n",
|
|
"results = {}\n",
|
|
"for raw_result, tensor_field in run.execute():\n",
|
|
" result = pd.DataFrame(raw_result)\n",
|
|
" if verbose:\n",
|
|
" print()\n",
|
|
" print(f\"Tensor Field: {type(tensor_field)}\")\n",
|
|
" print(tabulate(tensor_field, headers='keys', tablefmt='psql'))\n",
|
|
" print(f\"Output: {type(result)}\")\n",
|
|
" print(tabulate(result, headers='keys', tablefmt='psql'))\n",
|
|
" print()\n",
|
|
" results[i] = {}\n",
|
|
" results[i]['result'] = result\n",
|
|
" results[i]['simulation_parameters'] = simulation_parameters[i]\n",
|
|
" i += 1\n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"experiment_index = 0\n",
|
|
"df = results[experiment_index]['result']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 21,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a19c4a5f8>"
|
|
]
|
|
},
|
|
"execution_count": 21,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAD8CAYAAACcjGjIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJztnXd4XNW16H9rZtQtW7IlV7kXsDHuuODQm+mEQEJCglMJhOSR5OYm8MgNCaSHlMdNIYRACKGHZoopoRd33LvcZbnITbLVZ2a/P06ZM5qRNJJG0tizft+nT2f2KbPmSLPXWWWvJcYYFEVRFMWLr7sFUBRFUVIPVQ6KoihKDKocFEVRlBhUOSiKoigxqHJQFEVRYlDloCiKosSgykFRFEWJQZWDoiiKEoMqB0VRFCWGQHcL0F6KiorMsGHDulsMRVGU44ply5YdMMYUt3bccaschg0bxtKlS7tbDEVRlOMKEdmRyHHqVlIURVFiUOWgKIqixKDKQVEURYlBlYOiKIoSgyoHRVEUJQZVDoqiKEoMqhwURVGUGFQ5KIqitIN/LdzBB5sPdLcYncZxuwhOURSlu6g4Ws8Pn18DwPZfXtrN0nQOajkoiqK0kcZQ2N2uD4a6UZLOQ5WDoihKGwmFjbv9/PLd3ShJ56HKQVEUpY0EPcrhUHVjN0rSeahyUBRFaSNey6G28cR0K2lAWlEUpQ18/oFFLN5+yH1dp8pBURQlfalrDDH3wcUs2nYoanz9nqpukqhzUbeSoihKApQfqY1RDADvbz5wQmYsqXJQFEVJAE+YweXUQb0AqKxpf1D6j29t5pbHPo6KY6QCqhwURVESIGxiJ+9TBvYEYOO+owD85Z0tjP2fV9m492jC173n9U28vGoPjy7aQdBeP1FV18jf3tvKS6vKMXHetytQ5aAoipIAzpP9X66f4o4NL8oD4InFuwCYt7Kc2sYQm/e3rBz2V9Vx3f0LeGFFZI3Ej15YywelVjmOdzZW8LNX1vPNx5az9UB1Uj9HomhAWlEUJQEc5eDziTs2aXAB/XpmEQxbT/wZfmvf0bpgi9dav/coC7ceouxwbdT4/qp6ABqDkRXYlbXds45CLQdFUZQEcNxKfokoh4BfGNArh9pGazL324rjuY9bXjUdthVNdX20Ern3rc1R7xXvmK5ClYOiKEoCOPFin2fW9ImQk+GnriHkvgbY1IpbybFCDjcJZFfZVoJXOSzZfrhDcrcXVQ6KoigJ4LqVRPjUlBIA+vbMJifTz/aD1eyrqmPZDmsib/C4heJeq0mQ+YunD+OKiQNpsAPS3sSlN9fvS9ZHaBOqHBRFURLAdSv5hHuuncCGu+cwqCAHAfYfrWf+6j3usbWNITfL6OVVe7jjudVRCiPsmf2fvmkWP77iFIYX5VHXGMYY4yqik/vnd1uKqyoHRVGUBHAmab8IIkJ2hh+A66YPAaC8sg6As08qxhiot5XBd55awaOLdkaltzqWw91XjWfa0EIAcjKt69UHw65iKeqRRU1D9yywS0g5iMh2EVktIitEZKk9NklEFjpjIjLdHhcRuVdESkVklYhM8Vxnrohstn/mesan2tcvtc+VWCkURVE6n3DY8NKqcnYcrI4Zh+hsJYCSwhwAjtZZ8YKe2RkArNldCURcTFsPHHPPcRTNrBF9cKa77IA1Ha8tr3L398gKpLZysDnHGDPJGDPNfv1r4CfGmEnAj+zXABcDo+2fG4G/AIhIb+BOYAYwHbhTRArtc/5iH+ucN6fdn0hRFKUDrCmv5JuPLees37wTlUbqBqSbPLvm2BaEk746ZUgBAG9u2A9E0lv//PYW1yLwuqgcTrFXW7+xbp/7XnlZAQ4cq2fXoZqkfb5E6YhbyQA97e1eQLm9fSXwT2OxECgQkQHARcAbxphDxpjDwBvAHHtfT2PMAmPduX8CV3VALkVRlHZT74kNLNx60N0OuRN69PGOO8hRDtOH9yE/K0BtQ4jahhCNIeu8jfuOct7v3rWuZb+FNy32tGG96ZkdoK4x5CqP6cOt5+enl5Ul6+MlTKLKwQCvi8gyEbnRHvs28BsR2QXcA9xujw8CdnnOLbPHWhovizMeg4jcaLuwllZUVCQouqIoSuJ4E4mO2RN+QzAccSs1sRyc2MO7m6w5KcMv5GT6qW0I8eaG6EyjrRXV1AdDHhdV9HvnZgaoaQi6yuHSCQPJ8Av3vrm5y8toJKocZhtjpmC5jG4RkTOBm4HvGGMGA98B/m4fGy9eYNoxHjtozP3GmGnGmGnFxcUJiq4oipI43jUGlbWN/OntUsb8cD5L7B4O/iYxh57ZAde1BBDw+8jN9FPbGHLjBXNnDXX319SHPFZI9LVys/zUNISiLIsrJlrPylW1XbsYLiHlYIwpt3/vB57DihnMBZ61D3naHgPryX+w5/QSLJdTS+MlccYVRVG6HK9y+MX89Xy0xap3tGmfFVBuajmICNfPGOK+DviEnMyAVWfJVg43nz2KH102DoDqhmBU5pOXTL+Pl1btcYPbPh+cMboIgOdXdG2v6laVg4jkiUi+sw1cCKzBmsDPsg87F9hsb88DbrCzlmYClcaYPcBrwIUiUmgHoi8EXrP3HRWRmXaW0g3AC8n7iIqiKInj9d6ICH7b91NZ2wDEKgeAfDtDCSDD72NAr2wAdhyssceE/vbYz19Zz/6jVg2lpplPU+201r12WqxPhBkjegNw57y13P7sqo59uDaQiOXQD/hARFYCi4GXjTGvAl8DfmuP/xwr2wjgFWArUAr8DfgGgDHmEHA3sMT+ucseA8tF9YB9zhZgfsc/mqIoSttxLIezTyqmIRimwW7k45SxaOoKAhjdr4e7HfAL10y1nCGOBRDw+5g90rIAXlm9l3vftJ6lm1oOZ46x3OVH7XpKfrFqN2XZaa6PL95FV9FqVVZjzFZgYpzxD4CpccYNcEsz13oQeDDO+FJgfALyKoqidCqO5dAv33rSX7g1uvtbj+zYafOSUwfwf84bTdnhGnrnZsakt2b4hdzMAIMKcth9JFKJtanlkGtnPjnF9hzd4VVIa3ZXMt5Oe+1MdIW0oiiKB8dyuHLywJh9JYU5DCrIiXvedy8Yw+8+PQmfL7J6+mi9bTnYrqlffurUqHNiAtK2cti8/xg+wV0gd/vFJ7vHLNhykK5AlYOiKIoHx3LIzYxYCHdePo6T++fzfy8Zm9A1nLUPH5ZaE7mzEO6M0cV88fRh7nFN3Up9bWul4mh9VPG9L8waxtafXwLAsS4q4a3NfhRFUTw4loN32p46tJAvzR6e8DWG9s51twM+wVsRyLEqemYHyM6Ifj4f3DuXL54+jH98tD3mmj6fkJvp77L+Dmo5KIqieHAsB29WkteKSITCvEwun2i5pZomNxXmWplNt18ylnhl5G49b3Sz183J8PPAB9taLQmeDFQ5KIqieHAtB4HTR/YBoDg/q83XmVhiBY3HDegZNf6l2cN54ZbZXDu1JN5p9MzJiDsOcP3MoUwf3hsTf51wUlG3kqIoigdvgb1/fnk69cEweVltnyq/esYI5p4+jECToHNmwMfEwQXNnuf3CV+ePdyNU3j57gVj2ixHe1HloCiK4sF4LIeA30egaaW9NpDRznN/dPm4dr9nslC3kqIoac+Og9WsK68CIoXd4q2ETifUclAUJe254Pfv0RAMs/Gnc9yYQ5yF0GmFWg6KoqQ9TvbPsbqgG3NI94aUqhwURVFsqutDbsxBLQdFURQFgM37j3pSWdNbO6hyUBQPobDhjXX72H+0rrtFUbqBe98q9SyC615ZuhtVDori4T/r9/G1fy7lR8+v7W5RlC4iGIqsNl656whrdltZS+meraTKQVE83P7sagCq7Dr8yolPg60cnNXQa8orgdiyF+mGKgdF8eCLUz+/MRRmyfZDbstH5cRi2Q6ric/04VbHtcXbrP4NGnNQFMXF8Td7FcFLq8q59r4FfP1fy7pJKqUzcfojnD+2H6P7Rjq6acxBURSXkK0dlu44TL3dHrKq1iqR/N6mCv65YHs3SaZ0FlV1jfTOy2T8oF7Msl1LoDEHVQ6K4iEUilS7XL7zCABBT9eV+av3drlMSudhjOFfC3eSb7f+dNp7gsYcVDkoiodg2DBzhOV7/rD0AI2hsJvNMm1oITWNGnc4kag4Wg9AdsBSClke5ZDuloPWVlIUDyFj6GXX0//ft0op6pHlWg49czIoO1zTneIpScb5235p9jCgieXQHQKlEGo5KIqHUNjQMzvSbOVQdQMhRzlkB9i075hbXkE5/nH+tj47+vyJUUXuvoxAek+Pajkoio0xhlDY0KdHFgW5GRypaaSmIeg+TTpN49/dVMHZJ/XtTlGVJOGUyvDbLqRTS3rx7DdOp+JofdRDQjqS3qpRUTw4cefcTD9L7zifntkB/v7BNjbsPUrAJ9wwaxgQ8VMrxx9bK45x3f0LeHdTBRCxHLzrWqYMKeSiU/p3i3yphCoHRbHZWnEMsCaKgN9HlV2++fV1+wj4hb52H+Hq+mBS33f/0Tre31yh7qouYNmOwyzceohHFuwAIpaDL90XNcRBlYOiAJU1jVzw+/eAyFPk184Y7u4P+HxuH+H739vK3sr4hfkqjtbz13e3tKlw37efWMEX/r6Yj+3UWaXzqLf7NoTCzm9r3J/mmUnxUOWgKMChmgZ322kIf8el47hswgAAjtUHybIDlOWVdTz04ba413n24zJ+MX8Djy/alfB7r99jFXo7cEzdVZ2N09THcSFG3ErdJVHqordEUYh2FXnz27/8iYj1ICL85fopAFTVRY6vawyxeNshGoJhNzWypiFx15NjqZQdro3Zt6+qjv/73GrW7K5M+HrHO4u3HeLa+z5idVnyP3O9qxxM1O90X9MQD1UOigLUeGopZfgjE8UpA3tGjV186gCG9M6l1jP5//2DbXz6rwt4bnkZjbafwpmEHFaXVTL7l2/xwordUeO1DSEOHLOslj++tTlGrnc27uexRTu5790tHfl4SWPXoRp+8uJadhys7rT3eHvjfpZsP8y7m/Yn/dqO5fCxXWwvXkBasUhIOYjIdhFZLSIrRGSpZ/xbIrJRRNaKyK8947eLSKm97yLP+Bx7rFREbvOMDxeRRSKyWUSeFJHMZH1ARUmEp5dabqAZw3tzoSdTJSvg56VvfYL5t57pjuVm+qOUiWN17Kmsc5XD9iaT54qyI+w+UsutT6zg7x9EXFJLth9yt+M9vR6sthRHQxNl0128uKqchz7cztNLyzrtPRz//z2vb+KpJYm75xLBqZdV3RBi24Fqt5aWBqRjaYvlcI4xZpIxZhqAiJwDXAlMMMacAtxjj48DrgNOAeYAfxYRv4j4gT8BFwPjgM/axwL8Cvi9MWY0cBj4Ssc/mqIkxuHqBp5eZk12D37xNPr1zI7aP35QL0Z5qnXmZPp5fd0+13XkzOkPfrCNoF2b6Z2NFRyqbuCtDfs4WtdIVW2kP8TdL61zJyln0p89qg9H64JRGUt/e28rv351I2C5l1IB5/PVdWIZkcZwRBG+k2Tr4c/vRCywwzUNhMPR6xyUCB1xK90M/NIYUw9gjHH+ilcCTxhj6o0x24BSYLr9U2qM2WqMaQCeAK4Uq2j6ucC/7fMfBq7qgFyK0iaeW265en4w52Q3I6klTh3UC4DHFu0EIsHNqrogR2oiSuChD7fx5X8s5c/vbOHPb5dGXePVNVYBPydGUdQji4ZQmG89vhxjDA+8v5WfvbLePX5lWWWzGVJdiaPMklljav7qPdz5whrX6gqFDHmZfiaW9OJYffLep2mqcHV90P3bacwhlkSVgwFeF5FlInKjPTYGOMN2B70rIqfZ44MAry1YZo81N94HOGKMCTYZV5Qu4ef2JPxVT+pqS9x63mgAXl69B8B9+oTorKe3N1rPS7sO1VDdpFGQo0SC9lPytVMHk5fp56VVe5i/Zi8/fTmiGO64ZCzQ/YvvHlmwnT/aSu6xRTuT5ur61uPLeXjBDrZWWK64YNgQ8Fupw8lcU9JoWz2X2hloS7cf9pTPSNrbnDAkektmG2OmYLmEbhGRM7FKbxQCM4H/Bp6yrYB4Kti0YzwGEblRRJaKyNKKiooERVeU5jHGEAwbzhxTTEaC+Yx9emRx/th+7sQV8iiHw9UR5eD0Il6xy1q/EPAJA3pZLqtq2yXluGkGFmRzz7UTAfjGox+71ygpzGGcHRRvSwZUZ3Dfu1ujXh/2KMKO4FhPtbY10hgKk+EX8rICLNtxOGkWU53tyhvWJxeA//fmZvczqFsploS+DcaYcvv3fuA5LBdRGfCssVgMhIEie3yw5/QSoLyF8QNAgYgEmozHk+N+Y8w0Y8y04uLixD6horRAXaP19OuU6U6UXjkZVNsuj5DHXbF0x2EGFeS4WU4QSVH9+SdP5aPbzsUnkSC2MzFm+H307ZkV9R7fOX8M9352Mrl2Taeabm5TmtWkEF2y5XHiGKGwwe8TpgwpBGD93qqkXL/e/lv375XDt8+3rL8XV1pTjWYrxdKqchCRPBHJd7aBC4E1wPNYsQJEZAyQiTXRzwOuE5EsERkOjAYWA0uA0XZmUiZW0HqesRyBbwPX2G85F3gheR9RUZpn+S4rpTG/jUXWemT52X2klvc3VxAOG3cCB8saKcyNTbgbVJiDiJCd4edPb2+xrBbbz+73CZMHF/K9C8e4x99yzkimDCkkN9N6bnrm487LEEqE3Cx/1OvyI7VU1TU2c3TbiVgOhoDPxwXj+gFEBfM7gpMEkBXwccs5owArcQA0WykeiVgO/YAPRGQl1iT/sjHmVeBBYISIrMEKLs+1rYi1wFPAOuBV4BZjTMiOKXwTeA1YDzxlHwvwA+C7IlKKFYP4e/I+oqI0z1vrrbiA90k/EaYMtZ5qv/TQEhpCYbIz/G7tpQvG9XMruHqZbZeDPvdkq6LrPz7aTqNtOQT8gs8nXD2lxD0+YLu5hvS23CAvrdrDFrv+U3eQnxWtQK9/YBHn3vNu0q6/82CN7eYLE/CL21fj1idW8LOX13W49tQrdowoO8PvuhAdhZShQYcYWr0jdnbRRPvnFGPMz+zxBmPM540x440xU4wxb3nO+ZkxZqQx5iRjzHzP+CvGmDH2vp81eY/pxphRxphrnQwoRelsGkJheuVkuC6MRLly0iB+fPk4gmHDsx/vxieR1bYzR/SJsiSa8uMrTgHgw9KDhGzLIWBPTtkZseflZPp54IZpANz+7Oo2yZlMMgI+BvbK5okbZ7pjB47V8/BH21m5q/11oZx7dee8tby2dq8VkPYJffIyybP3/e39bR0OyO86ZLn3Zo2w+kR/69xR7r6xA/I7dO0TEVWXSlrTEAzH+NIT5byxltujPhjGJ+K6pvKzMzhtWPMxjKIeWUwbWsh/1u9jpz1hBewV2DlxlAPA+eP64ROrtIQ3O6orCYcN/XtlM2N49Ge7c95avvLwknZftzA3k9H2OpJdh2p5edUeAj4fPp/wq2smuMcd7WDmUtgYinpkUmxbeEP75AFWanJAiyvFoHdESWsagmEy26kcBvfOZWSxNcH4fcLdV47n8zOHMHlIgesvd5jeZEKdM95ahf3+ZsvnneFaDj7OGF3EpzzuJYfbLj4ZSO4ag7bgBIpFxM34cThwrMHNykqURxftYPJdr7P7SK1rub24ygoQO3+TyyYM5L7PTwWgsoOxh7AxiCcraYT9t/vE6KLmTklrtBOcktbUh9qvHAB62NaCT4RPjC5yJ5qApz7Tf757Fv2aZCJNHlIAwOb9VgzBqd0kIjzylRlx38tZoFddH6SHvV1Z08hra/dy4Sn9KIgTBE8mIWPcxWLxFo09smAHH5Ye4OazRroB3iM1Ddz14jpG98vna2cMj3pCf2nlHg7b6z0yAtbxq+xiezfMGuoe52Rx3fvmZv7xpekx7/vJP3/IkZpG3v7e2S3LHzZRKatThhSy9icXtegCTGfUclDSmoZgmMwOuBR62Bk8x5q4PLICfp65eRbzbz2DUX17xGRD5WREnssuOqVfQm4NRyG8uzGyxuexxTv5/jOreHxxcmsQxSMcjigHZ+3FrBF9OLm/5a9/5uMyfvPaxqig+cc7D/Ps8t386tUNLG9iWXgVaMDn46ueCrhehT2pxFKkzgrqpizfeYRtB6pbXZQXCsemrOZlBaKsCSWCKgclrVmy/VC7Yw4Ao/taE2M8l8fUob0ZOyB+FpT3aXVEcY+4xzRlgj1JLth60B07Yi/iSnZ3uniEjXEn119+agLPfeN0Hv3qDJ79xulRx3nXP9Q2RCbsqtpGN3UXiJqUBxZkM6Agx33tXZDo8wnnntyXytpG6oMh9zM3pbV7EDZGV0K3Ab1VStqy+0gtR2oaO7SY6+Lx7es13KdHxAWU20wQuinDi/KYMqSA55bvprYhhDGGf3y0HeiaBXIhE1kP0CMrwOQhhfh8QnYgWv5aT0zEu6r7Kw8vZdQd8zl4rJ7ahhDv2X2cr5o0kBvPHBmlMANNnvB7ZAVYs7uK03/xFpPueiOugmhqvcXI38StpLSMKgclbXGeNG86a2S7rxFvPUMi5GdncMmp/dt8DSfDZv3eKqrqgm7fiNrGjlsOobCh/EhswyGHcNjgjzO3+nzCHE+Zc69yiFe99Y7n1riupysmDuQP100GojO1MppYc2fYsRynhHn5kdiSGv9csL1Z2cGxHFQ5JIoqByVtcXzYiVRibY6OBDO/MHMY04f1Zqadd58InznNqkBT1xCKctE8vnhX1Ov28OvXNnD6L99yn+ib4mQrxeO+L0zl+VtmA0SteXh4wY6YY2saQzTYsl49JVJjs6hHJGjfNA7U9B45mVHehXFPLS1rMc037AmoK62jykFJW0JuXaP2TxjxFq0lyqyRfXjqplmMt0uAJ4LzdF3bGIoq+Aewv4OLxHbbNaB+OX9D3P2tTa7OSu7X1u6LyBSnD0VtQ5BG2+LxKoHZoyIKoKlbKT87WoE/b5dZ996DytpG7ni++UWC6lZqG6oclLTDGENVXaNbwrkjRdf69czm/LH9+O+LTkqWeC3iuKBqG0Nu0b5zTrKKUB481r4qqYu2HmRV2RFX8azbU+WWG/fSkuUA0DsvkwvG9XNrIR2qbqCqLsi3zx/N5RMHusfVNITce+/N0vIGqJu6lZpad06pc+ceOGXUl2w/3Kx8obDWUGoLqhyUtOPeN0uZ8OPXeXmVVWsn0VLd8cjw+3hg7jS3kFtn40zg33xsOdfetwDAzfL5w382tfl6obDhM/cv5Io/fsim/ZEU1Oc+3h17bAI++0EFOew+UstHpQf410LLpTS8KI8vzx7GacMKGVSQw9ryKjdQ3dRqu37GEDIDPgb2yokaz/D7OHNMpBKzE4B3lENelp+rpwyitoXAvJVt1aL4ige9VUraseOQ1VTmwQ+tXs5NXRipjFP6AaxsK4BpdhHAYDvKanjXDqzcdYQRxXmcMrAn81aWs/9oxCUUDhu2VlS36pa5arIVQ9hyoNrtWXHlpEFMHlLI0zed7gaW39pgWSZNFfPPPnkqG+6aQ/9e0a1aAS63m/RApB9GyLFAfD5yMvwtti9Vt1LbUOWgpB1NlcHxVFcnO8MfFcQFa4KdNaJPi82A3t9cwc9ejvSudmiqUDJ8PtcF5BSqA6tPBRAT52iK02u7tiFIfWOYnk1iBd+5wCpJ/tRSa9FevNXpzVknn5w8iGduPp3PTBvMrkO1vLpmj+teCviF3Ex/iym9TctnKC1z/HwrFCVJON3XHI4nywFii/NZXdNanhi/8+RK/vb+NtaVRzfOCTW9F35xM4PW7K50x/dUWoqitVaqjmw1DSFqG0IxabpORpKjY9ri0gv4fUwdWsgX7NIa//XUSldZ+X1CToaf2sYQdzy3mp0Ha2LO9y7iU1pHlYOSdgTDhuFFee7rQAeylbqDphlDfp+PnMwAa8urWFteGfccZ9GYswbhueVlfFh6gMZwdPrroeoGBtounSeXWE/3jy/eya1PrABweyw0h98nBHzCgi0HqW0MxSgyv0/4+lkj3NftUczjB/Xi0gkDqG4IUW63EA34xK2S++iindw5b03UObc9s4oPSw+26HZSolHloKQdwXA46gmyIwHp7qBphdeAT5hqF/L76sNL457juG9qG0Icqw/ynSdXcv0Di9wnb6cMd2VtI317ZjNlSIHrstm496h7nUQW7IWMYdG2Q8xbWR733vbJi6wOjxdbSISJJVb67yP2Oor+vXKYOLiA88dajZTe3lgRte7jCVvR7UlSP+p04Pj6VihKEgiGrGYykwZbE2prT8OpxuUTB7LiRxe4r/0+4Yuzh/Pl2cPZU1nHm+v3xZzjKIeahpC7xgAiMYdBdsaT45oaVpTn9sj2Bq2b6zfh5QdzTna3x8XpsDexpIC++Vnc+9nJ7VbMTiHDZz4uozg/i7PsTKYH5p7GNVOtcufX3Lcgxr3UXF0mJRZVDkraEQwbAn7h0a/O4IMfnEO/nu17eu1OCnIzcYwfxy3mlLmOl+vvLDZ79uOyqCC083RdYi9gcyyI/KwAu4/Ucri6gVJPimsilsOYfpFCgo6rx8uMEX1YfMf5XOFZ+9BWHMUOUNBEuf/i6lOZMbw3K3Yd4Tl7sZxT0fbyDrxnuqHKQUk7rDaUPvKyApQU5rZ+Qopy8XgrtbNPnhXkHVaUR6+cDGo9WUvGGA4eq6ePHQguO1wblXHk9E8YWZzHf757Jg/MtdqROllHD320nUXbDgHw75tmkRVoXTmcNaavu92Rirct4a12+18XRi9AzPD7ePLrs8jPDrhpy0U9rAV6v//0pE6R50RElYOSdgRD4eMuQykef7huEgtvP4+T+kf6HzdN5/zzO1uY+tP/sH6PlaVU0xByYwkAb6yzXFABn49RffNdd83nZw5FxGqwA/CbayYwrYXWp1688ZyOlBdJlMLc+G7BHlkBnv3YqmAbDBvyswK6QroNqHJQ0g7HrXS8k+H3xQR0czL9bNwXCSA39blXNwSjLId5K622nE3vh4hw2tCIMrg6TtvSRMjuJMvBS4/s+IUTnVatVXWNhE6Qv3lXospBSSsagmEWbztE4ATt+hIOG1aVVfKvhTt4dc1esjKiP+eRmka3Naeh1yN/AAAgAElEQVSXeJaUM7lOHlLQ5vUBfe2V3J1pOdx28cmcNqyQYX3y4u53+lI7loP/BP2bdxbaQ1pJKzbZT9Xt7cOQ6nxuxhB+/soGfvi8lef/2emDY47597LYlqLxutE596g9z9t//NwUPtpyIG62UrK46ayRLfbiyPZUsD1RXIldiSoHJa0I2/X/rzstdtI8EWj6FP3iyj3u9vlj+/Kf9ft5e0N0v4YPbzvXTWX1kkjaanNMH947Zj1GV9O0gq26ldqG2llKWuH420/Upi9NLSJv68xg2NDDTlF1KM7PosjTstSL48vv42nCczzhKLd/LdxhxRzUcmgTqhyUtMKJxZ6oWSstdaZrCIb5/WciqZwPffE0ltxxfrPpqWeMLuLOy8fxw0vHJl3OrmCCvYr6wLEGgiGNObQVdSspaYXjVjpBdUNUq838rABHPZZDz+wMN8gMrTc5ys0M8KXZLRfaS2WyM/ycMbqIRVsP0qAxhzajykFJK5wewydqXf+hffL4z3fPom/PLJ5ZVsZPXlwHwE+uOIVzTrIWp2UGfDQEw2lRoTQ/O0C9XS7k9JGJ9+pWVDkoaUbIthxO5Lr+zurmGcMjk+Hc04e520N651K6/9hxV3CwPfTwtBdNdBGfYpHQf4eIbBeR1SKyQkSWNtn3PRExIlJkvxYRuVdESkVklYhM8Rw7V0Q22z9zPeNT7euX2ueeuN9cpVuxdUNaPDWP6tuDqycP4tefmhA1/rtPT+S/Lhjj+uRPZL517mh3O15jIaV52mI5nGOMOeAdEJHBwAXATs/wxcBo+2cG8Bdghoj0Bu4EpgEGWCYi84wxh+1jbgQWAq8Ac4D57fpEitICkWylbhakC8gM+PjdZ2JrCU0oKWBCSUGcM048io7TTKtUoKNupd8D3wde8IxdCfzTGGOAhSJSICIDgLOBN4wxhwBE5A1gjoi8A/Q0xiywx/8JXIUqB6UTCKeBW0mJkJPp5ydXnELPHPWgt5VE75gBXhcRA/zVGHO/iFwB7DbGrGzyRRsEeJdgltljLY2XxRlXlKSTTm4lxcIbb1ESJ1HlMNsYUy4ifYE3RGQDcAdwYZxj433rTDvGYy8sciOW+4khQ4YkIreiRJFObiVF6QgJRWiMMeX27/3Ac8BZwHBgpYhsB0qAj0WkP9aTv7c2QQlQ3sp4SZzxeHLcb4yZZoyZVlxcnIjoihJFZJ2DagdFaYlWlYOI5IlIvrONZS0sMcb0NcYMM8YMw5rgpxhj9gLzgBvsrKWZQKUxZg/wGnChiBSKSKF9ndfsfUdFZKadpXQD0TEMRUkaqhwUJTEScSv1A56z4woB4DFjzKstHP8KcAlQCtQAXwIwxhwSkbuBJfZxdznBaeBm4B9ADlYgWoPRSqcQ1piDoiREq8rBGLMVmNjKMcM82wa4pZnjHgQejDO+FBjfmiyK0lE05qAoiaGrQpS04b1NFXzr8eXAiVt4T1GShSqHFOK+d7cw+5dvUe4pqawkj+0Hq91tjTkoSsuockgh/vHhdnYfqWXD3qruFuWEJBiKZEifqIX3FCVZqHJIIZzmKq+v3dfNkpyYOJlKAKobFKVlVDmkEL3zrI5cTyzZxVsbVEEkm2DYYzlozEFRWkSVQwoR8Am9cjIAWLtbXUvJxslUmjKkgD7NtMZUFMVClUMKEQwbxg7IJ+ATahtD3S3OCYejHJ76+qxmW2MqimKhyiFF2H+0jh0Hqwn4fORk+qlpCBEMhbtbrBMKRzmoS0lRWkeVQ4pw/m/fZV9VPSJW79t/fLSdUXfM18ylJBIKG3yi5boVJRFUOaQIVXVWI/iGYJhMT/vG7QdqukukE46QMWo1KEqCqHJIMYJhw8wRkd6/1fXBbpTmxCIcVuWgKImiyiHFaAyFOWN0kfu6pkGVQzIoP1LLs8t3E47bKURRlKaockgxGoJh8rIi9RD/+HZpN0pz4vA/z6+h4mg9DUEN8itKIqhySAGMZ+XusD555GVF0ixrGjSlNRnsP1rf3SIoynGFdt1OARrtmj+nj+zDL64+lewMP1/5xHBW7jrC8l1HMMZohk0HycnUdQ2K0hbUckgBGu31DGeNKaYwL5OcTD//c9k4LhjXj1DY8PTSsm6W8Phkze5K7n9vi+WqU+WgKG1CLYcUwFEOGf5oXT12QE8y/ML3n1nFGWOKGNArpzvEOy6pawxx2f9+AMDEkgIC9r397bUt9q1SFMVGLYcU4IkluwCiYg0AZ44p5t7rJgNwpKaxy+U6nlmy/ZC7faw+SChsOHVQLz41taQbpVKU4wdVDilAjb2W4fKJA2P29bQL8bU1oBoOm7TOzKlvjHz2moYQQV3joChtQpVDCuCs3M3NjPXyFfXIAuB/39zcpmvOfWgxE3/yOsfSdBGdtzx3TUOQUDhMQJWDoiSMKocUIBRuvjPZmH496JOXSaNnsttacYxL/t/7zFtZHvec2oYQ728+QG1jiANpmsIZDEcsh3te30QwpJaDorQFVQ4pQNgYfM38JUSEM0YXsXLXESprrbjDuj1VrNtTxcMfbY97zryVu93tdC393bQlaChsCPhVOShKoqhySAFCYdNiT+MhvXMB+GDzASCS3VQfjD/xexfOpesiOsetdO7JfaltdGIO+u+uKImi35YUIBQ2+FpweXxm+hAgUoSvMWiifse7nsPBY2nqVrIVaM/sgB1zMBpzUJQ2oMohBQi3UkraWcDlBJcbbX/6xn1Ho0pvOHiDsX9K09pMToymV04GjSHD6t2VGnNQlDagyiFBnl66i6l3v8Gw217mM39d0KxLpz2ETctuJSeL6eXVe1izu5JGT4rq2vLYZkCO5TCkdy4ryypZVXYkabKmOvXBEF98aDG/f2MTANOG9Xb3hbQkq6IkjCqHBPmg9AAHqxsAWLTtEPsq2+eu2XWohpv/tYyXVkUyjULhlruTZQZ8FPXIYtmOw1z2vx/wgidLqSKO28iZBH946VgAtlQci3vdTfuO8siC7W4M40Tggfe38c7GCg7Zf6uzTip2991yzqjuEktRjjtUOSRI0wVl1e3ss7Bw60Hmr9nLNx9bzu4jtYDThKbl81799hn8/JOnArB8Z8QS+Ou7W2KOddxKE0oKgOaD0t97eiX/88LaqOsd7yzcejDqdYYnCN0rR6vFKEqiqHKIQ1VdI0dqGqLGmj5df/2RZSz1lGhIFK9r464X11pjrbiVwFoM97kZQ/jcjCFR45v2xVoFzoKvXLscR20zymFfVR2AmyJ7IuBNYS3MzSAzEPkX9/bJUBSlZVQ5NMEYw4Qfv86Uu9+IGjvcpLbRzkM13PSvj9t8fW+weG+lNTmHW8lW8nLHJWPd7ZvPHsmh6gZeXbMn5j38PiE3w1IO79spsE3JznAC3SeOcgiFDTNH9Oaj287l/R+ci98nTBtaSHaGj8LczO4WT1GOGxJSDiKyXURWi8gKEVlqj/1GRDaIyCoReU5ECjzH3y4ipSKyUUQu8ozPscdKReQ2z/hwEVkkIptF5EkR6bZvsVPDyJnD64Mhzvj12yzbcTjm2APH6vnHh9vaZEE4lsP04b2paQixdPshnl2+u5WzIuRlBbh+xhCunVrC3FnDACjdH209hEJW2qZTifTD0maUQ8BSDn99d2vC75/qNIbDZPh9DCzIoYdtKTz59VmsvPNCVxkqitI6bbEczjHGTDLGTLNfvwGMN8ZMADYBtwOIyDjgOuAUYA7wZxHxi4gf+BNwMTAO+Kx9LMCvgN8bY0YDh4GvdPBztZn6YIi15ZUx/vknl+yi7LAVGxhRlMc73zubbb+4hO9dOAaAH7+4jmvuW8AVf/wgofdxLIee2RnUNIT4xqOW9eG8RyL87JOn8ptrJ9K/VzaZfh/3vL6JRxZsj3oPxxK5+eyRBMPGzfv3kp9tTZ5H606c+kvBUOx6Br9PyAqoYlCUttBut5Ix5nVjjDOrLAScWshXAk8YY+qNMduAUmC6/VNqjNlqjGkAngCuFCtN51zg3/b5DwNXtVeu9vK7NzZx6b0f8MrqaBeNt1R2fTDMsKI8RGKL5K0qq4w7ATclFI4sztp9pLbD7SudGMSCrQc5eKyez/1tIU8t3eVOkH3zrcJ9u+IoH2ctQF1jiPpgKO6aieMNXQmtKMkh0W+RAV4XkWUicmOc/V8G5tvbg4Bdnn1l9lhz432AIx5F44zHICI3ishSEVlaUVGRoOiJseeI5f/fdajGHRt228v85Z1INlC9J2PJcVlcNmEA/3OZZQBV17e+9sGxHPr1yu640MCPrziFyUMKOFoX5Iklu/hoy0FqGkLuBOmU3nh04Y5YWWxldrC6gZN++Co/fH5NUmTqToKhMBlaQ0lROkyiymG2MWYKlkvoFhE509khIncAQeBRZyjO+aYd47GDxtxvjJlmjJlWXFwc75A2U9cY4sWV5a47yWm84+AtXHfJqf3d7fPH9eOb54zi2+ePId9WFBXH6lp9v5CdTXPreaPJSZIPPD87g/c3H+BfHgXgeFbOG9sPEaizF+3NX72H7/97JXWNoZgMrEcX7Wzze4fDhiv++AFff2Rp+z9AEgmGjRtrURSl/ST0LTLGlNu/9wPPYbmIEJG5wGXA9SbikygDBntOLwHKWxg/ABSISKDJeJfw2tq9fOvx5fxn/b4Wj9tw9xx+csUp7uveeZl876KTGNW3B8W26+b+91oP7DqWQ1bAx91Xje+A5BGK7Z4Pe+zsp7EDevLNcyMLvgYV5LjK7wfPrOKppWWsLa+Mm8K6fk/siuuWqDhWz6qySl5b2/L96yqC2rdBUZJCq8pBRPJEJN/ZBi4E1ojIHOAHwBXGmBrPKfOA60QkS0SGA6OBxcASYLSdmZSJFbSeZyuVt4Fr7PPnAi8k5+O1TlUzOf7nnFTM9Z41BdkZ/mZXMZ81ppicDD8vrtxDuJUSDaGwwSfWiuhzTirmhllDOeekYu77/JR2f4bbLznZ3b5+xhDm33oGN9iZTAC5mX53rcNRuz7TR6UH2VdVz6UTBkRda8fBGtrCH/6zyd1eF6eUR1cTLyCtKErbScRy6Ad8ICIrsSb5l40xrwJ/BPKBN+wU1/sAjDFrgaeAdcCrwC3GmJAdU/gm8BqwHnjKPhYsJfNdESnFikH8PWmfsBWa63fwjXNGRT19t4TPJ5xa0ovaxhDr97Y8QYaMIWDHA/r0yOKuK8fz0JemM2f8gBbPa4miHlmMKM4DiJuVk5MZYP6avbY/3nrv39q1h66eHB3eqWnjym+v9XHjI0u7NahdVdfInso6dSspShJodcmoMWYrMDHOeLMzpzHmZ8DP4oy/ArzSzHtMb02WzqC2IX6GUYbfR5+8LEYW53HKwF6tXufW80Zz/QOLmk0LDYcNz3xcxtryqk6pDnrm6GK2VlSTnRE7MRblWctGLvz9ezFlQEoKc7l6yiDe33yAiqP1be7/UF0fYmJJL+oaw2zcd5Syw7UMtoPgXc2H9mK/Pnm62E1ROkraP2I1Zzn0yrFKL7z5X2dz72cnt3odpzRDcwvONu47yn//exXvbaog3AlP184CL2+5CIebzh4JwNYD1TH7MgM+fvfpSbz9vbMBeHnVnphjWqKmIUhuZoDvzzkJwC1419Xsr6rjIbsz3rXTSlo+WFGUVkl75fD+5khKbEFuBv/n3FE89rUZDC/Ka9N1cu2eC//7Vvz+CV4l1BlP1k7mU0Ycl8rgwsj7XT9jCJ+dHskLcJRJboafDL+wYOtB3t3UcpqwMYaGYJjKmkaWbD9MXpafQvtp/a/vxRYC7ArufWszi7dZK9V1JbSidJy0rkRmjGFteRXjBvTkzDHFXHrqAE4tad2FFI8erRR1c8pm/PULUzlrTHLScL1cM62EhlCIqybHLhHp3yubsQN6sn5PFSWFuRzwlPnOtJWJzye8/p2zOOeed1i09WBcGesaQ6zcdYQXV5Xz6KKd3H2llW01tE8e423X28pdlfz9g21cdEo/Sgq7zr3kdQ9m62poRekwaWs5zFtZ7pasuHh8f267+OR2KwaAAb2y3fUOpfuPYYxhf1Vk3UOj27Yyo1OebAcV5PDfF53MoIKcuPv797TSXXMyfK6VA9FuqOFFefTKyWg27nD/e1v5zP0L+dfCnRgDK3dZpb6vmjSIzICPqycPYveRWu5+aR1/+M/mZH20hPDGWrLixF0URWkbafktqmsM8X8eX8619y0A4vvp24qI8LvPTAIsV9WTS3Yx/edvcu5v36ExFHZLSXfX6l3nM+Zk+rlyUsS6yGry2fMy/W6vagcnDbZpP+qnl5W51wS4ZmrE19+05HlX0vQzKYrSdtLSreSsbdhrP9nH89O3hzPHFAFwrC7I3S+tA2BrRTV7K+tct1J3pVl+YeYwjtUHmTasNyOLe3Dt1BIqjtXHTKQ5mf6oBYEPfbiNn7y4jj55me5iv6Y4lsiY/vnuWHOB/s7Cub83zBraYlc9RVESIy2Vw+YmJa6TYTmA5b8P+ITVuyvxroX74fNr3NIb3bVA6xOji/jE6CL39W+ujclOBqwV3IdrGtlXVUe/ntms2W2t2zhY3eC2SQW4atJAnl9hLWR3qrt64y4fllqFAPv0iK9Qkk0wbBhUkMNdVyZn1bmipDtpaX+vLItui5ks5SAi5GT4eX2d9eT9txumMWtEH97dVMHibVY/iECKF4X77gVWKfKjdZZ15Y1PeDl9lKVorp8xhPzsDCDWnfO397dR10UWRMhucKQoSnJIS8thd5Py1ZlJdPUMKMjm6L5jjB/Uk/PH9mVYn1wu+P17bre1QIqXk86zS5Fv2neMkcU9MHFqID7ylemcMbqYyycMdOMNYCnHf980ixW7jvDTl9dz37tbOKl/D/ZV1TOmXw/OPblfp8ndGNKaSoqSTNJSObyzMTqPP1mWA8DTXz+dXYdrGFncAxFxM5OcldOpPoE5lsI3Hv2Yc0/uSz87y2nWiD4s2HqQX159KmeMttJcc+JYFdOG9aZ/r2x++vJ6AFaXVfHgh9sA2P7LSztNbrUcFCW5pJ1yqG0IsftItOWQzHILvXIz6JUbSYl1JltngVaqu5W8E/5bG/ZzzdQSBvbK5tGvzqC2MeSuBG+JksJcnv3G6Vz954/4x0fbOlNcFy3VrSjJJe2+TYfsFMurp0TSOYf2adtq6LbgTLZOqe5eORmd9l7JYOyAnnxm2mAmDbZagu+rqsPvF3w+SUgxOEwZUkhhbgatFKlNGqGwVmNVlGSSdsrhsJ1xM2VIIZkBH1/9xHD6J6krWzxyMvxuNs9lEwa4wdtUJTvDz6+umcDXzhgBwPubD7Q7TvKLqydEvXYqtn77ieWce8871AeTF6wOqltJUZJK2ikHJ3tmaJ9cNv30Yn5ot/jsLESEb55jFbDtm995SijZzBkf6XrX3ify88f2jXr9kl3U7/kV5Ww9UE35kdY75yVCVV0j77VSD0pRlLaRdsrBcXP4unCh1KUTBvD5mdEF71Idv08YP6gnAA2h+GXNW6NpDGDnoehGQve8trF9wjVhf5W1cvuUgT2Tcj1FUdJSOVjaoSsX0ZYU5vLTq05ldL/81g9OIcbY8pY1Sf1tC6cOigTnnZIaTgZUdRsbCzWHszp69qiiVo5UFCVR0lY5dKXlcLxyzRSrVlKoA1Hlv39xGk/fNIs+eZn87f1tBD1WSNMaTu0lGLauqX9TRUkeaaccTDe4lY5XeiYhs6pvfjanDevNWSdZayMWbj3kKptj9ckJSNu6QbOVFCWJpJ1yiFgO3SzIcUBJYQ65mX6undrxzmpfnj0cgCeX7nLTetfvqWJLxbGWTksIx3LQbCVFSR5ptwjO8ZBo5c7WKcjNZN1dc5JyrfGDejG6bw+q64OEQoY+eZkcrG5g2Y7DjCzu0aFrO5aIKgdFSR7pZzmE1XLoLvr0yOTAsXpCxripsj+Zt7bD13XLoesfVVGSRvopBw1Idxs5GX5WlVVS0xAiPzuDiSW9aAwZd3Fce3GUg0+Vg6IkjTRUDtZvdUF0PZdNGOhuB3zCZRMG0hAK8+b6/R26bsio5aAoySYNlUPXr3NQLCba9ZrAeso/f5xVwnvZzsMdum5QYw6KknTSTjkYdSt1Gz2zI/kPAZ8wvCiPntkBt0d1e9i07yhfemgJoMpBUZJJ2imH7iifoVh4W4Y6E3luZqBDi+FW7Ix09VPloCjJIw2Vg2YrdRd+n3DLOSOBSPe93Ew/q3dXtvua3squqd5lT1GOJ3Sdg9KlXHfaEMIGrp1mLawzwIa9R6k4Wk9xflbLJ8ehPhgpx6G9fhQleaTd18mo5dCtDO6dyw/mnExBrtV978Yzrb4R+6raXr47GAqzad9RAGYM782ggtzkCaooaU5CykFEtovIahFZISJL7bHeIvKGiGy2fxfa4yIi94pIqYisEpEpnuvMtY/fLCJzPeNT7euX2ud22tTt5sSr5ZASjOprrY5+8IO2txP9+SsbeGppGQBP3Dgzbk9rRVHaR1ssh3OMMZOMMdPs17cBbxpjRgNv2q8BLgZG2z83An8BS5kAdwIzgOnAnY5CsY+50XNecmo2xEED0qmF04OhaV/vRNh2IFKXSd2EipJcOuJWuhJ42N5+GLjKM/5PY7EQKBCRAcBFwBvGmEPGmMPAG8Ace19PY8wCY/l8/um5VtJxA9Jp51BLTXIzA5x3ct929XbIzUy7kJmidBmJTpEGeF1ElonIjfZYP2PMHgD7t9MTchCwy3NumT3W0nhZnPFO4fv/XgWo5ZBK5GUFKN1/rM1lNJxMpWduntUZYilKWpOocphtjJmC5TK6RUTObOHYeLOuacd47IVFbhSRpSKytKKiYz2DVTmkDrmZfuoaw7zbxj7QdY1hpg4tZOrQ3p0kmaKkLwkpB2NMuf17P/AcVsxgn+0Swv7tFMgpA7zNkkuA8lbGS+KMx5PjfmPMNGPMtOLi4kREbxbNVkodbjrLWvtw07+WJXzO4eoGPig9QHaG+gcVpTNo9ZslInkiku9sAxcCa4B5gJNxNBd4wd6eB9xgZy3NBCptt9NrwIUiUmgHoi8EXrP3HRWRmXaW0g2ea3UaGsBMHYYV5TFpcAF1jeGEWpLuPFjDlX/6EIAJJQWtHK0oSntIJKLXD3jOnkwDwGPGmFdFZAnwlIh8BdgJXGsf/wpwCVAK1ABfAjDGHBKRu4El9nF3GWMO2ds3A/8AcoD59k+nopZDanHlpIGs2HWEteWVrU74727az85DNQBcMn5AV4inKGlHq8rBGLMVmBhn/CBwXpxxA9zSzLUeBB6MM74UGJ+AvB1m2tBClu44TGZA3RGpxEn98wF4aumuVpVDYyhiXRTkdrzPtaIosaTdDPmXz0/l6ZtmkZ+tk0oqcfrIIob0zuWxRTtbzVpyekZ//awRlBTmdIV4ipJ2pJ1yKM7P4rRhmt2SiuRlBQgb2LTvWIvHOZbDd84fo7EjRekk0k45KKnLXVeeAsDLq+Imq7k4QesMrbSnKJ2GfruUlGG0XWfJu97hl/M38N0nV0S5moIhy62kSQWK0nmoclBShoLcTC6fOJCqukgpjfve3cKzy3dzzNMQqDFsyPCLupQUpRNR5aCkFAU5GWw7UM1HWw5ElfE+6lEYobDRrm+K0smoclBSinNPtkp0fe5vi3hs0U53fG15lbvdGAqToZUTFaVT0W+YklKcc3JftyTG3sqI5fDc8khtxlDYEPCr5aAonYkqByXl+P2nJwHw5NJd9MwOcHL//Ci30kdbDmrhREXpZFQ5KCnHuWP7uttZGX4GFuTw/uYDbKk4RmMoTOn+Y1TWNnajhIpy4qPKQUk5sgJ+Zgy3FipW1we5YuJAAM777bu8snoPALeeN7rb5FOUdECVg5KSnDnGKsle0xDiqsmD+Ptcqzvtil1HAMjN0i5witKZqHJQUpLrZwwBYOpQq834eWP7kZPhp7LGcidlaEBaUToVffxSUpKC3Ew+/p8LyM30u2PZGT6eXb4b0NIZitLZ6DdMSVl652WSnRFRDoV5me52QBfBKUqnospBOW748/VT3G3tx6EonYt+w5TjhpP796Q4PwuAgK6QVpRORb9hynFFph1r0BXSitK5qHJQjit65Vgd/DRbSVE6F81WUo4rfnjpWJ5dvpvJgwu7WxRFOaFR5aAcV5w+qojTRxV1txiKcsKjbiVFURQlBlUOiqIoSgyqHBRFUZQYVDkoiqIoMahyUBRFUWJQ5aAoiqLEoMpBURRFiUGVg6IoihKDGGO6W4Z2ISIVwI52nl4EHEiiOJ1BqsuY6vJB6suY6vJB6suY6vJB6sk41BhT3NpBx61y6AgistQYM6275WiJVJcx1eWD1Jcx1eWD1Jcx1eWD40PGeKhbSVEURYlBlYOiKIoSQ7oqh/u7W4AESHUZU10+SH0ZU10+SH0ZU10+OD5kjCEtYw6KoihKy6Sr5aAoiqK0QFopBxGZIyIbRaRURG7rRjkGi8jbIrJeRNaKyK32eG8ReUNENtu/C+1xEZF7bblXiciULpLTLyLLReQl+/VwEVlky/ekiGTa41n261J7/7Aukq9ARP4tIhvsezkrle6hiHzH/vuuEZHHRSS7u++hiDwoIvtFZI1nrM33TETm2sdvFpG5XSDjb+y/8yoReU5ECjz7brdl3CgiF3nGO+37Hk9Gz77viYgRkSL7dbfcxw5jjEmLH8APbAFGAJnASmBcN8kyAJhib+cDm4BxwK+B2+zx24Bf2duXAPMBAWYCi7pIzu8CjwEv2a+fAq6zt+8Dbra3vwHcZ29fBzzZRfI9DHzV3s4EClLlHgKDgG1AjufefbG77yFwJjAFWOMZa9M9A3oDW+3fhfZ2YSfLeCEQsLd/5ZFxnP1dzgKG299xf2d/3+PJaI8PBl7DWoNV1J33scOfsbsF6LIPCrOA1zyvbwdu7265bFleAC4ANgID7LEBwEZ7+6/AZz3Hu8d1okwlwJvAucBL9j/2Ac8X1Oj3W8UAAANUSURBVL2f9pdhlr0dsI+TTpavpz35SpPxlLiHWMphl/3FD9j38KJUuIfAsCYTb5vuGfBZ4K+e8ajjOkPGJvs+CTxqb0d9j5372BXf93gyAv8GJgLbiSiHbruPHflJJ7eS82V1KLPHuhXbfTAZWAT0M8bsAbB/97UP6w7Z/wB8Hwjbr/sAR4wxwTgyuPLZ+yvt4zuTEUAF8JDt+npARPJIkXtojNkN3APsBPZg3ZNlpNY9dGjrPevu79KXsZ7EaUGWLpdRRK4AdhtjVjbZlTIytoV0Ug4SZ6xbU7VEpAfwDPBtY0xVS4fGGes02UXkMmC/MWZZgjJ0x70NYJn1fzHGTAaqsVwizdHV97AQuBLL1TEQyAMubkGGlPv/pHmZuk1WEbkDCAKPOkPNyNLVf+9c4A7gR/F2NyNLKv7NXdJJOZRh+QMdSoDybpIFEcnAUgyPGmOetYf3icgAe/8AYL893tWyzwauEJHtwBNYrqU/AAUiEogjgyufvb8XcKgT5XPes8wYs8h+/W8sZZEq9/B8YJsxpsIY0wg8C5xOat1Dh7bes275LtkB28uA643th0khGUdiPQistL83JcDHItI/hWRsE+mkHJYAo+1skUysoN+87hBERAT4O7DeGPM7z655gJOxMBcrFuGM32BnPcwEKh03QGdgjLndGFNijBmGdZ/eMsZcD7wNXNOMfI7c19jHd+oTkDFmL7BLRE6yh84D1pEi9xDLnTRTRHLtv7cjX8rcQw9tvWevAReKSKFtIV1oj3UaIjIH+AFwhTGmpons19nZXsOB0cBiuvj7boxZbYzpa4wZZn9vyrCSTvaSQvexTXR30KMrf7CyBjZhZTHc0Y1yfALLfFwFrLB/LsHyMb8JbLZ/97aPF+BPttyrgWldKOvZRLKVRmB98UqBp4Esezzbfl1q7x/RRbJNApba9/F5rIyPlLmHwE+ADcAa4BGsjJpuvYfA41gxkEasCewr7blnWH7/UvvnS10gYymWf975vtznOf4OW8aNwMWe8U77vseTscn+7UQC0t1yHzv6oyukFUVRlBjSya2kKIqiJIgqB0VRFCUGVQ6KoihKDKocFEVRlBhUOSiKoigxqHJQFEVRYlDloCiKosSgykFRFEWJ4f8DUYbi6ehPE84AAAAASUVORK5CYII=\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a19e22d30>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"df.funds.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a22ae2da0>"
|
|
]
|
|
},
|
|
"execution_count": 22,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a19e22908>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"(df.funds.diff()/df.funds).hist()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 23,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf = df[df.substep == 3].copy()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 24,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['token_wts'] = (rdf.tokens/rdf.supply)\n",
|
|
"rdf['wt_mean_price'] = (rdf.token_wts*rdf.prices).apply(sum)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 25,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['holding_wts'] = (rdf.holdings/rdf.holdings.apply(sum))\n",
|
|
"rdf['h_wt_mean_price'] = (rdf.holding_wts*rdf.prices).apply(sum)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 26,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['wealth'] = rdf.holdings + rdf.spot_price*rdf.tokens"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 27,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['wealth_wts'] = rdf.wealth/rdf.wealth.apply(sum)\n",
|
|
"rdf['w_wt_mean_price'] = (rdf.wealth_wts*rdf.prices).apply(sum)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a1d19c860>"
|
|
]
|
|
},
|
|
"execution_count": 28,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1dc03ef0>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.prices.apply(np.min).plot()\n",
|
|
"rdf.prices.apply(np.median).plot()\n",
|
|
"rdf.prices.apply(np.mean).plot()\n",
|
|
"rdf.wt_mean_price.plot()\n",
|
|
"rdf.h_wt_mean_price.plot()\n",
|
|
"rdf.w_wt_mean_price.plot()\n",
|
|
"rdf.prices.apply(np.max).plot()\n",
|
|
"rdf.spot_price.plot()\n",
|
|
"plt.legend(['min', 'median','mean','tok wt mean','hold wt mean','wealth wt mean','max', 'spot'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a20477630>"
|
|
]
|
|
},
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1ea29208>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.prices.apply(np.min).plot(logy=True)\n",
|
|
"rdf.prices.apply(np.median).plot(logy=True)\n",
|
|
"rdf.prices.apply(np.mean).plot(logy=True)\n",
|
|
"rdf.wt_mean_price.plot(logy=True)\n",
|
|
"rdf.h_wt_mean_price.plot(logy=True)\n",
|
|
"rdf.w_wt_mean_price.plot(logy=True)\n",
|
|
"rdf.prices.apply(np.max).plot(logy=True)\n",
|
|
"rdf.spot_price.plot(logy=True)\n",
|
|
"plt.legend(['min', 'median','mean','tok wt mean','hold wt mean','wealth wt mean','max', 'spot'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 30,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['median_price']=rdf.prices.apply(np.median)\n",
|
|
"rdf['mean_price']=rdf.prices.apply(np.mean)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 31,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a21346b38>"
|
|
]
|
|
},
|
|
"execution_count": 31,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a213464e0>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"(np.sign(rdf['mean_price']-rdf['spot_price'])*(rdf['mean_price']-rdf['spot_price'])**2).apply(np.log10).plot(alpha=1)\n",
|
|
"(-np.sign(rdf['mean_price']-rdf['spot_price'])*(rdf['mean_price']-rdf['spot_price'])**2).apply(np.log10).plot(alpha=.5)\n",
|
|
"plt.legend(['over','under'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 32,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['est_err'] = rdf.spot_price - rdf.wt_mean_price\n",
|
|
"rdf['sq_est_err'] = rdf['est_err']**2"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 33,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a225ec940>"
|
|
]
|
|
},
|
|
"execution_count": 33,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1d19cba8>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.est_err.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 34,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a2284fc88>"
|
|
]
|
|
},
|
|
"execution_count": 34,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a225ecc18>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.est_err.apply(np.abs).plot(logy=True)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a1d0cc5f8>"
|
|
]
|
|
},
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1c9d1e48>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"#head T\n",
|
|
"T = 50\n",
|
|
"rdf.head(T).prices.apply(np.min).plot()\n",
|
|
"rdf.head(T).prices.apply(np.median).plot()\n",
|
|
"rdf.head(T).prices.apply(np.mean).plot()\n",
|
|
"rdf.head(T).wt_mean_price.plot()\n",
|
|
"rdf.head(T).h_wt_mean_price.plot()\n",
|
|
"rdf.head(T).w_wt_mean_price.plot()\n",
|
|
"rdf.head(T).prices.apply(np.max).plot()\n",
|
|
"rdf.head(T).spot_price.plot()\n",
|
|
"plt.legend(['min', 'median','mean','tok wt mean','hold wt mean','wealth wt mean','max', 'spot'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a1db5aba8>"
|
|
]
|
|
},
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1d0cc320>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"T = 50\n",
|
|
"rdf.tail(T).prices.apply(np.min).plot()\n",
|
|
"rdf.tail(T).prices.apply(np.median).plot()\n",
|
|
"rdf.tail(T).prices.apply(np.mean).plot()\n",
|
|
"rdf.tail(T).wt_mean_price.plot()\n",
|
|
"rdf.tail(T).h_wt_mean_price.plot()\n",
|
|
"rdf.tail(T).w_wt_mean_price.plot()\n",
|
|
"rdf.tail(T).prices.apply(np.max).plot()\n",
|
|
"rdf.tail(T).spot_price.plot()\n",
|
|
"plt.legend(['min', 'median','mean','tok wt mean','hold wt mean','wealth wt mean','max', 'spot'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"tx_data = rdf.actions.values\n",
|
|
"transactions = []\n",
|
|
"states = []\n",
|
|
"for t in range(time_periods_per_run):\n",
|
|
" for tx in range(len(tx_data[t])):\n",
|
|
" states.append(tx_data[t][tx]['posterior'])\n",
|
|
" transactions.append(tx_data[t][tx])\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 38,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sdf = pd.DataFrame(states)\n",
|
|
"tdf = pd.DataFrame(transactions).drop('posterior', axis=1)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 39,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>agent</th>\n",
|
|
" <th>amt</th>\n",
|
|
" <th>mech</th>\n",
|
|
" <th>pbar</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>0</th>\n",
|
|
" <td>67</td>\n",
|
|
" <td>5944.118713</td>\n",
|
|
" <td>burn</td>\n",
|
|
" <td>0.094718</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>94</td>\n",
|
|
" <td>5385.770251</td>\n",
|
|
" <td>burn</td>\n",
|
|
" <td>0.094179</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>98</td>\n",
|
|
" <td>9158.190387</td>\n",
|
|
" <td>burn</td>\n",
|
|
" <td>0.093489</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>50</td>\n",
|
|
" <td>7904.758973</td>\n",
|
|
" <td>burn</td>\n",
|
|
" <td>0.092678</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>70</td>\n",
|
|
" <td>9292.069223</td>\n",
|
|
" <td>burn</td>\n",
|
|
" <td>0.091861</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" agent amt mech pbar\n",
|
|
"0 67 5944.118713 burn 0.094718\n",
|
|
"1 94 5385.770251 burn 0.094179\n",
|
|
"2 98 9158.190387 burn 0.093489\n",
|
|
"3 50 7904.758973 burn 0.092678\n",
|
|
"4 70 9292.069223 burn 0.091861"
|
|
]
|
|
},
|
|
"execution_count": 39,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"tdf.head()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 40,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a22798e80>"
|
|
]
|
|
},
|
|
"execution_count": 40,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a22c8ea90>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"sdf['P'].head(100).plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 41,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"bond_amts = [tdf.iloc[k].amt for k in range(time_periods_per_run) if tdf.iloc[k].mech=='bond']\n",
|
|
"burn_amts = [tdf.iloc[k].amt for k in range(time_periods_per_run) if tdf.iloc[k].mech=='burn']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 42,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(array([197., 6., 7., 5., 3., 0., 1., 0., 1., 1.]),\n",
|
|
" array([ 0. , 222.28881809, 444.57763618, 666.86645427,\n",
|
|
" 889.15527236, 1111.44409045, 1333.73290854, 1556.02172663,\n",
|
|
" 1778.31054472, 2000.59936281, 2222.8881809 ]),\n",
|
|
" <a list of 10 Patch objects>)"
|
|
]
|
|
},
|
|
"execution_count": 42,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a226402e8>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist(bond_amts)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 43,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(array([219., 24., 19., 8., 4., 2., 0., 1., 1., 1.]),\n",
|
|
" array([ 0. , 3240.1230237 , 6480.24604741, 9720.36907111,\n",
|
|
" 12960.49209481, 16200.61511851, 19440.73814222, 22680.86116592,\n",
|
|
" 25920.98418962, 29161.10721333, 32401.23023703]),\n",
|
|
" <a list of 10 Patch objects>)"
|
|
]
|
|
},
|
|
"execution_count": 43,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1e1aecc0>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist(burn_amts)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 44,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['invariant'] = rdf.supply.apply(lambda x: x**kappa)/rdf.reserve"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 45,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a1e7ca8d0>"
|
|
]
|
|
},
|
|
"execution_count": 45,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1e3f4438>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.plot(x='reserve', y='supply', kind='scatter', alpha=.5)\n",
|
|
"axis = plt.axis()\n",
|
|
"xrange = np.arange(axis[0], axis[1], (axis[1]-axis[0])/100)\n",
|
|
"yrange = np.array([supply(x, V0, kappa) for x in xrange ])\n",
|
|
"plt.plot(xrange, yrange, 'y')\n",
|
|
"plt.title('Bonding Curve Invariant')\n",
|
|
"plt.legend(['Invariant', 'Observed Data'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 46,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a1e7ca438>"
|
|
]
|
|
},
|
|
"execution_count": 46,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1e344518>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"(rdf.tokens.apply(sum)-rdf.supply).plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 47,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def gini(x):\n",
|
|
"\n",
|
|
" # Mean absolute difference\n",
|
|
" mad = np.abs(np.subtract.outer(x, x)).mean()\n",
|
|
" # Relative mean absolute difference\n",
|
|
" rmad = mad/np.mean(x)\n",
|
|
" # Gini coefficient\n",
|
|
" g = 0.5 * rmad\n",
|
|
" return g"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 48,
|
|
"metadata": {
|
|
"scrolled": false
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(array([71., 5., 9., 8., 1., 4., 1., 0., 0., 1.]),\n",
|
|
" array([ 0. , 225.91666347, 451.83332693, 677.7499904 ,\n",
|
|
" 903.66665387, 1129.58331733, 1355.4999808 , 1581.41664427,\n",
|
|
" 1807.33330773, 2033.2499712 , 2259.16663466]),\n",
|
|
" <a list of 10 Patch objects>)"
|
|
]
|
|
},
|
|
"execution_count": 48,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1f2ca048>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist(rdf.iloc[-1].holdings)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 49,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['gini_h'] = rdf.holdings.apply(gini)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 50,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a1f2caf60>"
|
|
]
|
|
},
|
|
"execution_count": 50,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1f3ee0f0>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.gini_h.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 51,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(array([29., 12., 26., 14., 9., 4., 4., 0., 1., 1.]),\n",
|
|
" array([ 0. , 3129.07337115, 6258.1467423 , 9387.22011346,\n",
|
|
" 12516.29348461, 15645.36685576, 18774.44022691, 21903.51359807,\n",
|
|
" 25032.58696922, 28161.66034037, 31290.73371152]),\n",
|
|
" <a list of 10 Patch objects>)"
|
|
]
|
|
},
|
|
"execution_count": 51,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1f743630>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist(rdf.iloc[-1].tokens)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 52,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['gini_s'] = rdf.tokens.apply(gini)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 53,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a1ff54160>"
|
|
]
|
|
},
|
|
"execution_count": 53,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a212a7f98>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.gini_s.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 54,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a1f9039e8>"
|
|
]
|
|
},
|
|
"execution_count": 54,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1ffde128>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.tokens.apply(np.count_nonzero).plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 55,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['asset_value'] = rdf.holdings + rdf.spot_price*rdf.tokens"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 56,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(array([42., 22., 13., 7., 8., 5., 0., 0., 1., 2.]),\n",
|
|
" array([ 374.03166522, 568.24101061, 762.450356 , 956.65970138,\n",
|
|
" 1150.86904677, 1345.07839216, 1539.28773755, 1733.49708293,\n",
|
|
" 1927.70642832, 2121.91577371, 2316.1251191 ]),\n",
|
|
" <a list of 10 Patch objects>)"
|
|
]
|
|
},
|
|
"execution_count": 56,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a1f894e10>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.hist(rdf.iloc[-1].asset_value)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 57,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['gini'] = rdf.asset_value.apply(gini)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 58,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a202729e8>"
|
|
]
|
|
},
|
|
"execution_count": 58,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<matplotlib.figure.Figure at 0x1a207bb7b8>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.gini.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.6.4"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|