2042 lines
605 KiB
Plaintext
2042 lines
605 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"#import networkx as nx\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import scipy.stats as sts\n",
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"import seaborn as sns\n",
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"\n",
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"%matplotlib inline\n",
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"\n",
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"#import conviction files\n",
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"#from conviction_helpers import *\n",
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"#from conviction_system_logic3 import *\n",
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"from bonding_curve_eq import *"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"System initialization"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"hatch_raise = 100000 # fiat units\n",
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"hatch_price = .1 #fiat per tokens\n",
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"theta = .5 #share of funds going to funding pool at launch\n",
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"\n",
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"R0 = hatch_raise*(1-theta)\n",
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"F0 = hatch_raise*theta\n",
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"S0 = hatch_raise/hatch_price\n",
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"\n",
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"kappa = 2\n",
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"V0 = invariant(R0,S0,kappa)\n",
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"P0 = spot_price(R0, V0, kappa)\n",
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"\n",
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"dust = 10**-8"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"agent initialization"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"#number of agents\n",
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"n= 100\n",
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"\n",
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"#gain factors\n",
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"g = np.random.normal(2, .5, size=n)\n",
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"phat0 = g*F0/S0 #derivative, integral and proportion\n",
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"#agents as controllers, co-steering\n",
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"\n",
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"#wakeup rates\n",
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"gamma = sts.expon.rvs(loc=1,scale=5, size=n)\n",
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"\n",
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"#holdings fiat\n",
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"h = sts.expon.rvs( loc=100,scale=1000, size=n)\n",
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"\n",
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"#holdings tokens\n",
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"s_dist = sts.expon.rvs(loc=10, scale=10, size=n)\n",
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"s0 = s_dist/sum(s_dist)*S0\n",
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"\n",
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"#lambda for revenue process\n",
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"lam = 200\n",
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"\n",
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"#phi for exiting funds\n",
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"phi = .05\n",
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"\n",
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"#beta is param for armijo rule\n",
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"beta = .9"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(array([52., 17., 16., 2., 7., 3., 2., 0., 0., 1.]),\n",
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" array([ 1.01812525, 4.11562861, 7.21313198, 10.31063534, 13.40813871,\n",
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" 16.50564207, 19.60314544, 22.7006488 , 25.79815217, 28.89565553,\n",
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" 31.9931589 ]),\n",
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" <a list of 10 Patch objects>)"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": "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\n",
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"text/plain": [
|
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"<Figure size 432x288 with 1 Axes>"
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]
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},
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"metadata": {
|
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"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
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"source": [
|
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"plt.hist(gamma)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
|
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"params= {\n",
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" 'kappa': [kappa],\n",
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" 'lambda': [lam],\n",
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" 'gains': [g],\n",
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" 'rates':[1/gamma],\n",
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" 'population':[n],\n",
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" 'beta':[beta],\n",
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" 'phi': [phi],\n",
|
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" 'invariant': [V0],\n",
|
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" 'dust' : [dust]}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"initial_conditions = {'holdings': h,\n",
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" 'tokens': s0,\n",
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" 'supply': S0,\n",
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" 'prices': phat0,\n",
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" 'funds':F0,\n",
|
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" 'reserve': R0,\n",
|
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" 'spot_price': P0,\n",
|
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" 'actions': {}}"
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]
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},
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{
|
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"cell_type": "code",
|
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"execution_count": 7,
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"metadata": {},
|
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"outputs": [
|
|
{
|
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"data": {
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"text/plain": [
|
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"{'holdings': array([1491.55435956, 220.27578262, 1427.61302781, 1837.26575481,\n",
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" 213.40532294, 381.03687516, 1601.51537288, 4813.1662553 ,\n",
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" 1868.79910159, 1138.68223172, 876.96458284, 1451.66010493,\n",
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" 637.15523644, 722.52620083, 2986.72943671, 1696.36022861,\n",
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" 2248.03302654, 171.33668465, 1046.16247899, 163.91100293,\n",
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" 321.57265953, 1539.95340377, 1150.6561499 , 2017.809995 ,\n",
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" 810.22492366, 356.85382975, 255.57699567, 2735.3029003 ,\n",
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" 166.05187014, 553.87163738, 191.31958362, 245.15748154,\n",
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" 1672.53699603, 429.85070433, 1821.52869909, 1275.30989826,\n",
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" 376.89993344, 1044.730325 , 357.60647402, 1201.64973791,\n",
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" 401.07895237, 3332.56229971, 890.00829058, 218.79592259,\n",
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" 3540.38718226, 321.26611676, 102.27640047, 320.05752999,\n",
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" 422.18337838, 1937.20770684, 836.56389561, 813.00152219,\n",
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" 1595.59377871, 1802.87939861, 900.46679522, 871.38716144,\n",
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" 582.32788667, 537.83845232, 2421.924436 , 356.05091508,\n",
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" 1226.54729115, 2835.48975185, 142.97098182, 952.62666157,\n",
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" 1877.55619028, 2662.11396083, 533.57911447, 211.84197505,\n",
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" 1856.23818927, 380.63638383, 158.96055638, 935.02924472,\n",
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" 441.71092027, 936.20732242, 538.99677711, 716.97079533,\n",
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" 178.66736784, 203.97840114, 1242.86074279, 891.99953323,\n",
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" 332.74568677, 514.53219289, 2141.15779718, 282.96800403,\n",
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" 354.92725936, 324.72668179, 1030.94652897, 1023.75245337,\n",
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" 222.80730247, 2638.84311727, 1438.57356195, 834.61659702,\n",
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" 253.42363562, 798.90610804, 112.04118094, 683.04808874,\n",
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" 449.10103684, 409.16342809, 2061.1424766 , 1661.28134282]),\n",
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" 'tokens': array([12303.53806701, 10109.38039546, 10926.36469101, 8488.89090689,\n",
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" 5689.04815992, 12149.88252629, 13660.98344781, 13194.27189783,\n",
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" 7171.53282821, 6085.28915257, 7255.28317247, 4858.05227946,\n",
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" 5529.0164384 , 11496.24708729, 20547.44084098, 11074.27577223,\n",
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" 12167.87629611, 4898.18568064, 5949.05560271, 8289.65626165,\n",
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" 19272.01146512, 27046.05752105, 11693.71303987, 6400.85429817,\n",
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" 4996.43623277, 10357.56795015, 5803.61558714, 10096.77673423,\n",
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" 16462.48603272, 8473.59865226, 17688.31032579, 15470.90589254,\n",
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" 5701.23213959, 6376.32982457, 7251.5305819 , 5477.3624347 ,\n",
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" 15771.00241095, 10990.01025806, 13056.83922153, 8772.29535309,\n",
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" 8803.02801489, 11190.41242618, 7125.2937636 , 5139.62966442,\n",
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" 5601.38336516, 5819.099935 , 10637.61593258, 5534.66658128,\n",
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" 13191.67079571, 12877.36128768, 7229.77097774, 16233.8747754 ,\n",
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" 5556.49627084, 12192.45403971, 26333.94524461, 10302.14245382,\n",
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" 8132.85889666, 16421.96952054, 5647.83182678, 9387.50079862,\n",
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" 4752.80636085, 10841.11752658, 6932.59864833, 5644.00029573,\n",
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" 12937.57620221, 5267.74160796, 6246.16355859, 6766.30536371,\n",
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" 8684.51328386, 5874.03814796, 7684.72812837, 5230.11401078,\n",
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" 5422.79939888, 6739.66125901, 9680.66638856, 14161.88831625,\n",
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" 5171.77881692, 10627.45829653, 7170.62244963, 18410.55808681,\n",
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" 10500.85306901, 7691.91878301, 20426.67936269, 7200.19999212,\n",
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" 19287.03669814, 13059.1012849 , 8354.32990509, 7546.14310014,\n",
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" 7142.98095366, 6268.43443328, 11074.15688199, 16392.39076861,\n",
|
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" 4745.6742865 , 12004.03447145, 7840.53858944, 7781.80546276,\n",
|
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" 11668.27927659, 6424.49058654, 8768.32319628, 19213.27871795]),\n",
|
|
" 'supply': 1000000.0,\n",
|
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" 'prices': array([0.03668392, 0.13584553, 0.07053848, 0.07144591, 0.07455708,\n",
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" 0.10541149, 0.08256638, 0.10352117, 0.07044857, 0.11900253,\n",
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" 0.10538831, 0.11682792, 0.04871774, 0.10522783, 0.08966995,\n",
|
|
" 0.06342526, 0.10124545, 0.12728149, 0.11869192, 0.06921892,\n",
|
|
" 0.07955202, 0.1164087 , 0.12764083, 0.09522398, 0.08137281,\n",
|
|
" 0.10352062, 0.09386865, 0.0929732 , 0.06913695, 0.11679376,\n",
|
|
" 0.11174555, 0.0869627 , 0.04874983, 0.13749126, 0.09208374,\n",
|
|
" 0.09774717, 0.09822203, 0.08609091, 0.14359277, 0.10374467,\n",
|
|
" 0.10982005, 0.13749575, 0.10067457, 0.10437326, 0.05864195,\n",
|
|
" 0.05425359, 0.01838324, 0.077781 , 0.10059241, 0.10841435,\n",
|
|
" 0.06218726, 0.06592297, 0.12834567, 0.08270084, 0.11138052,\n",
|
|
" 0.09135989, 0.10528527, 0.08301035, 0.1267354 , 0.09933988,\n",
|
|
" 0.11215415, 0.07629801, 0.09257582, 0.09956197, 0.11751681,\n",
|
|
" 0.10644767, 0.14348938, 0.08617678, 0.10231833, 0.10384093,\n",
|
|
" 0.11837285, 0.10366437, 0.04744786, 0.10375815, 0.06812439,\n",
|
|
" 0.10273873, 0.10489761, 0.16678139, 0.10486019, 0.0819059 ,\n",
|
|
" 0.07080829, 0.12240588, 0.092658 , 0.06394913, 0.08888752,\n",
|
|
" 0.10281423, 0.09446 , 0.15793036, 0.12062319, 0.07484083,\n",
|
|
" 0.1150664 , 0.09466796, 0.1377474 , 0.110938 , 0.10357414,\n",
|
|
" 0.12454611, 0.12119661, 0.08180721, 0.12163599, 0.10826474]),\n",
|
|
" 'funds': 50000.0,\n",
|
|
" 'reserve': 50000.0,\n",
|
|
" 'spot_price': 0.09999999999999999,\n",
|
|
" 'actions': {}}"
|
|
]
|
|
},
|
|
"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 = 5000\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, 5000), 'M': {'kappa': 2, 'lambda': 200, 'gains': array([0.73367846, 2.71691057, 1.41076956, 1.42891825, 1.49114154,\n",
|
|
" 2.10822977, 1.65132761, 2.07042345, 1.40897136, 2.38005052,\n",
|
|
" 2.10776616, 2.3365585 , 0.97435478, 2.10455653, 1.79339891,\n",
|
|
" 1.26850517, 2.02490894, 2.54562971, 2.3738383 , 1.3843783 ,\n",
|
|
" 1.59104031, 2.32817395, 2.55281667, 1.90447954, 1.62745615,\n",
|
|
" 2.07041234, 1.8773729 , 1.85946406, 1.38273899, 2.33587529,\n",
|
|
" 2.23491101, 1.73925407, 0.97499668, 2.74982515, 1.84167486,\n",
|
|
" 1.95494333, 1.96444055, 1.72181825, 2.87185532, 2.07489349,\n",
|
|
" 2.19640108, 2.749915 , 2.01349133, 2.08746513, 1.1728389 ,\n",
|
|
" 1.08507175, 0.36766485, 1.55562008, 2.01184819, 2.16828692,\n",
|
|
" 1.24374517, 1.3184594 , 2.56691333, 1.65401685, 2.22761044,\n",
|
|
" 1.82719782, 2.10570537, 1.66020692, 2.534708 , 1.98679766,\n",
|
|
" 2.24308303, 1.52596016, 1.85151643, 1.9912393 , 2.35033616,\n",
|
|
" 2.12895337, 2.86978766, 1.72353564, 2.04636656, 2.07681855,\n",
|
|
" 2.36745698, 2.07328742, 0.94895726, 2.075163 , 1.36248778,\n",
|
|
" 2.0547746 , 2.09795219, 3.33562787, 2.09720382, 1.63811794,\n",
|
|
" 1.4161659 , 2.44811757, 1.85316006, 1.27898255, 1.77775031,\n",
|
|
" 2.05628459, 1.88920004, 3.1586071 , 2.41246388, 1.49681667,\n",
|
|
" 2.30132792, 1.89335929, 2.75494809, 2.21876008, 2.07148279,\n",
|
|
" 2.49092212, 2.42393213, 1.63614422, 2.4327197 , 2.1652949 ]), 'rates': array([0.03125668, 0.14183608, 0.21822113, 0.06359907, 0.32401442,\n",
|
|
" 0.68289966, 0.11491106, 0.44452703, 0.71193421, 0.41189494,\n",
|
|
" 0.10769661, 0.31670005, 0.12568907, 0.0990496 , 0.54318276,\n",
|
|
" 0.59410785, 0.54978918, 0.06269876, 0.3123104 , 0.50939301,\n",
|
|
" 0.79091847, 0.10103308, 0.16747244, 0.12056136, 0.64958248,\n",
|
|
" 0.45103943, 0.08176658, 0.21650152, 0.33726675, 0.38864594,\n",
|
|
" 0.10207843, 0.12241801, 0.3616399 , 0.89397711, 0.2439942 ,\n",
|
|
" 0.11757751, 0.25521799, 0.33494926, 0.36640979, 0.20082133,\n",
|
|
" 0.18855699, 0.08150525, 0.63106324, 0.05901084, 0.78906531,\n",
|
|
" 0.83885896, 0.6649887 , 0.15746301, 0.10144705, 0.49359504,\n",
|
|
" 0.27554918, 0.06776478, 0.85326199, 0.10063573, 0.11056234,\n",
|
|
" 0.05904045, 0.52637014, 0.34167326, 0.07224392, 0.2350956 ,\n",
|
|
" 0.55402776, 0.20499293, 0.1727246 , 0.07022692, 0.06785565,\n",
|
|
" 0.26307256, 0.14224596, 0.09989587, 0.14084076, 0.17091149,\n",
|
|
" 0.98219743, 0.22435375, 0.40399 , 0.52002548, 0.78328536,\n",
|
|
" 0.69675604, 0.14135151, 0.51410459, 0.04919006, 0.05680226,\n",
|
|
" 0.04742116, 0.76624676, 0.09711861, 0.31337428, 0.07028642,\n",
|
|
" 0.49380023, 0.11935541, 0.34574773, 0.50764208, 0.48373149,\n",
|
|
" 0.18922239, 0.27173928, 0.26108245, 0.63390254, 0.09871005,\n",
|
|
" 0.37966998, 0.22329211, 0.75355945, 0.4149401 , 0.66222853]), 'population': 100, 'beta': 0.9, 'phi': 0.05, 'invariant': 20000000.0, 'dust': 1e-08}}]\n"
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]
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}
|
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],
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"source": [
|
|
"from cadCAD.configuration import append_configs\n",
|
|
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #\n",
|
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"# The configurations above are then packaged into a `Configuration` object\n",
|
|
"append_configs(\n",
|
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" initial_state=initial_conditions, #dict containing variable names and initial values\n",
|
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" partial_state_update_blocks=partial_state_update_blocks, #dict containing state update functions\n",
|
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" sim_configs=simulation_parameters #dict containing simulation parameters\n",
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")"
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]
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},
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{
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"cell_type": "code",
|
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"execution_count": 18,
|
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"metadata": {},
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"outputs": [],
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"source": [
|
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"from tabulate import tabulate\n",
|
|
"from cadCAD.engine import ExecutionMode, ExecutionContext, Executor\n",
|
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"from cadCAD import configs\n",
|
|
"import pandas as pd\n",
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"\n",
|
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"exec_mode = ExecutionMode()\n",
|
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"multi_proc_ctx = ExecutionContext(context=exec_mode.multi_proc)\n",
|
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"run = Executor(exec_context=multi_proc_ctx, configs=configs)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
|
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" __________ ____ \n",
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" ________ __ _____/ ____/ | / __ \\\n",
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" / ___/ __` / __ / / / /| | / / / /\n",
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" / /__/ /_/ / /_/ / /___/ ___ |/ /_/ / \n",
|
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" \\___/\\__,_/\\__,_/\\____/_/ |_/_____/ \n",
|
|
" by BlockScience\n",
|
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" \n",
|
|
"Execution Mode: multi_proc: [<cadCAD.configuration.Configuration object at 0x1a15f4b0f0>]\n",
|
|
"Configurations: [<cadCAD.configuration.Configuration object at 0x1a15f4b0f0>]\n"
|
|
]
|
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},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"/Users/Zargham/Documents/GitHub/conviction/bonding_curve_eq.py:62: RuntimeWarning: invalid value encountered in double_scalars\n",
|
|
" realized_price = quantity_recieved/deltaS\n",
|
|
"/Users/Zargham/Documents/GitHub/conviction/bonding_curve_eq.py:62: RuntimeWarning: divide by zero encountered in double_scalars\n",
|
|
" realized_price = quantity_recieved/deltaS\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"i = 0\n",
|
|
"verbose = False\n",
|
|
"results = {}\n",
|
|
"for raw_result, tensor_field in run.execute():\n",
|
|
" result = pd.DataFrame(raw_result)\n",
|
|
" if verbose:\n",
|
|
" print()\n",
|
|
" print(f\"Tensor Field: {type(tensor_field)}\")\n",
|
|
" print(tabulate(tensor_field, headers='keys', tablefmt='psql'))\n",
|
|
" print(f\"Output: {type(result)}\")\n",
|
|
" print(tabulate(result, headers='keys', tablefmt='psql'))\n",
|
|
" print()\n",
|
|
" results[i] = {}\n",
|
|
" results[i]['result'] = result\n",
|
|
" results[i]['simulation_parameters'] = simulation_parameters[i]\n",
|
|
" i += 1\n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"experiment_index = 0\n",
|
|
"df = results[experiment_index]['result']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 21,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
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"text/html": [
|
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"<div>\n",
|
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"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
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" vertical-align: middle;\n",
|
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" }\n",
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|
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" .dataframe tbody tr th {\n",
|
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" vertical-align: top;\n",
|
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|
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|
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" .dataframe thead th {\n",
|
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" text-align: right;\n",
|
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" }\n",
|
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"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>actions</th>\n",
|
|
" <th>funds</th>\n",
|
|
" <th>holdings</th>\n",
|
|
" <th>prices</th>\n",
|
|
" <th>reserve</th>\n",
|
|
" <th>run</th>\n",
|
|
" <th>spot_price</th>\n",
|
|
" <th>substep</th>\n",
|
|
" <th>supply</th>\n",
|
|
" <th>timestep</th>\n",
|
|
" <th>tokens</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
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|
|
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|
|
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|
|
" <td>0.100000</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>1.000000e+06</td>\n",
|
|
" <td>0</td>\n",
|
|
" <td>[12303.538067007707, 10109.380395456104, 10926...</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>1</th>\n",
|
|
" <td>{}</td>\n",
|
|
" <td>49751.511718</td>\n",
|
|
" <td>[1491.554359556692, 220.2757826216507, 1427.61...</td>\n",
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" <td>[0.036683923187958434, 0.13584552866350832, 0....</td>\n",
|
|
" <td>50000.000000</td>\n",
|
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" <td>1</td>\n",
|
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" <td>0.100000</td>\n",
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" <td>1</td>\n",
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" <td>1.000000e+06</td>\n",
|
|
" <td>1</td>\n",
|
|
" <td>[12303.538067007707, 10109.380395456104, 10926...</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2</th>\n",
|
|
" <td>[{'agent': 12, 'mech': 'burn', 'amt': 5529.016...</td>\n",
|
|
" <td>49751.511718</td>\n",
|
|
" <td>[1491.554359556692, 220.2757826216507, 1427.61...</td>\n",
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|
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|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>[{'agent': 12, 'mech': 'burn', 'amt': 5529.016...</td>\n",
|
|
" <td>50431.256076</td>\n",
|
|
" <td>[1491.554359556692, 0.0, 1427.6130278081594, 1...</td>\n",
|
|
" <td>[0.036683923187958434, 0.13584552866350832, 0....</td>\n",
|
|
" <td>56392.984066</td>\n",
|
|
" <td>1</td>\n",
|
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" <td>0.106201</td>\n",
|
|
" <td>3</td>\n",
|
|
" <td>1.062007e+06</td>\n",
|
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|
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" <td>[12303.538067007703, 12185.555300491747, 10926...</td>\n",
|
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|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
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|
|
" <td>50251.729410</td>\n",
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" <td>1</td>\n",
|
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" <td>1.062007e+06</td>\n",
|
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"</div>"
|
|
],
|
|
"text/plain": [
|
|
" actions funds \\\n",
|
|
"0 {} 50000.000000 \n",
|
|
"1 {} 49751.511718 \n",
|
|
"2 [{'agent': 12, 'mech': 'burn', 'amt': 5529.016... 49751.511718 \n",
|
|
"3 [{'agent': 12, 'mech': 'burn', 'amt': 5529.016... 50431.256076 \n",
|
|
"4 [{'agent': 12, 'mech': 'burn', 'amt': 5529.016... 50251.729410 \n",
|
|
"\n",
|
|
" holdings \\\n",
|
|
"0 [1491.554359556692, 220.2757826216507, 1427.61... \n",
|
|
"1 [1491.554359556692, 220.2757826216507, 1427.61... \n",
|
|
"2 [1491.554359556692, 220.2757826216507, 1427.61... \n",
|
|
"3 [1491.554359556692, 0.0, 1427.6130278081594, 1... \n",
|
|
"4 [1491.554359556692, 0.0, 1427.6130278081594, 1... \n",
|
|
"\n",
|
|
" prices reserve run \\\n",
|
|
"0 [0.036683923187958434, 0.13584552866350832, 0.... 50000.000000 1 \n",
|
|
"1 [0.036683923187958434, 0.13584552866350832, 0.... 50000.000000 1 \n",
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"2 [0.036683923187958434, 0.13584552866350832, 0.... 50000.000000 1 \n",
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"3 [0.036683923187958434, 0.13584552866350832, 0.... 56392.984066 1 \n",
|
|
"4 [0.03483998989031369, 0.12901719429056374, 0.0... 56392.984066 1 \n",
|
|
"\n",
|
|
" spot_price substep supply timestep \\\n",
|
|
"0 0.100000 0 1.000000e+06 0 \n",
|
|
"1 0.100000 1 1.000000e+06 1 \n",
|
|
"2 0.100000 2 1.000000e+06 1 \n",
|
|
"3 0.106201 3 1.062007e+06 1 \n",
|
|
"4 0.106201 1 1.062007e+06 2 \n",
|
|
"\n",
|
|
" tokens \n",
|
|
"0 [12303.538067007707, 10109.380395456104, 10926... \n",
|
|
"1 [12303.538067007707, 10109.380395456104, 10926... \n",
|
|
"2 [12303.538067007707, 10109.380395456104, 10926... \n",
|
|
"3 [12303.538067007703, 12185.555300491747, 10926... \n",
|
|
"4 [12303.538067007703, 12185.555300491747, 10926... "
|
|
]
|
|
},
|
|
"execution_count": 21,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"df.head()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a3ea07320>"
|
|
]
|
|
},
|
|
"execution_count": 22,
|
|
"metadata": {},
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"output_type": "execute_result"
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},
|
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{
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"data": {
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kW73HEg8mTV6MC5+biR9WJdZrTRBEOMSBvCxzbMRPE4fjxKOKMaZvW8diM9ayosnCGNDWaVKQ74Ajd47qHjadeTyINJfTuEEdMLhzcwBmg3SzRrHN9bgtRsGL75Rrq0qrG64gxBsRDmEY2i3yYLsm+WZjbruifLz5u8FonKeplPTJyUh+iMjeRDBvwx6UTZzimOhvxvIdKJs4xTGj6bHtmpr2E5WAL9LXeej8Y/HmNYMBAIcMXmW1Mcy39PWy7Rj80Nf4Zvn2mF1zv9QeFxKMCAcbjOqUaOa41k1Cu3Lm20RdN8kP7eET75xFd76vGcXfnmNv/9DzQzmpv6zRx7GcbEPhjcLmkJFByMnKMAUYxjKH1eLN+wAACzbui9k1KWTWKEGIPSIcbPjEENlsrU/sBmNhoEuP7xB0XFe/3D6ym78tI8xv/+ynfox4HJGwasfBkMd1461VCDixtzq0QTtW6CuHu8/qEdF5uZkZWG+IkI6l2kaPFdlzKHb34ICsHIQEI8LBhjkG7xC3k6ERY36fPJtVQraqM21MEufxclBQlrFedaKexJ3Qc0AdsgT4ndSlGBNO6YyTupSY2jfuToyOfMte7XWywklXCwdqPCjICaj/MiM8PxT65//fX9bH7JrNXFYiFIRYIcLBhpzMwKRdn0hhwH7S0fX2RvVSndeHhRv3mvp1KG6E6x28m2LNxQNKQx4vUgbbw3U+XP5yIKNpaVEj/OnMHkHvM1GuoaP/+QOAyNV/ZcWNTE/jT0yPXWxJ0zAqwmgocBGU+PnirQnPxSU0XEQ42KAX+QHMT+/RYBdMpi9GSgoD6a09PsaFz8209OOEpdyw6rRbNDan3taT1N323kL8sCpQC2HXIXM1u96lmmHa2CcR7DjgXFXPjuzMDBw2BMEddEh5Eg12q8VoMAqvnyrM93Pxpn1YXWlWBV73xjyMT0JWXKFhIsLBhka5gR/3tVEWpl9wz+kY07ctbhreJeiYrj4yBtht3RtQw3Qq0WpIXD2kM7IzEvMRZWeZhcPoY1qbnoCrVVpua8qJWWvNAVr/uFhLw6VXXUsUizfvDd/JQHZmBmrjlFspN4qoejuMMTYfLzBn+P3Nv37EiL9/Z3ueUxp4QYgEEQ42HFQ1GD69cQjO7RddUbqiRjn459h+trriNirHksfn86uW9hpcRLu0LMS6h8/Cb4/vgKzMxHipZFjqIDRrlIP9h+vg9TH2Vdc5qtdKmzUy7esFdRKdmuKGocFCOBTZlgm8ZePYFSkKVSI2Eqx2FLfOEZURrqIEwQ4RDjboqbZjaaQ0MrizVnO5Y3EBfp44HADwniq5CQBN8gJP7IkKLLNO5k3ys8GsCco+f/7K8TyrgVpXqRyqjZ2axg1WNVg4cixCN1K1VCiMDgn1Se/ROM9su3CbymV3DL2khCMXEQ4hiJdGZ9yg9vhp4nD0bV/kX1kY1TX3nN3Tv12fySUSfrLUVG6sDKAVlaFdXM+zrKz0bK52uZfiSdMIM8G6tQu8PXsDHvliedh+v27Zh637NNWg8TOrTyU/axqWKgeB+8/pq0w1KawC+0hnX1Udjv/r9JgGJR4JiHAIQZ0nPhMzEflrSANA15aFpuPGia59c7PaJl5ssvj5694xz3672vGcvOyMoAy0eqT3qzPXJ6RewsldS9C8IActG0dWQ8IoHAZ0bGb6PIxMnLwYz367OqQrcZ3Xh7Oe/BEnPPRN0LH66P+tzhC66tEofJgZj09faeq3Xircmbj29bnYvr8GV/2nPHxnwY8IhxCUNgtffyEWOCXqA4DiJPm363UdPCHKhS645wxTZlMrP69OTHbWDlEI0OM7BVKYFORmhY1neX/uJsdj63eZJ2PjlaLJ6qtjtQPpAmrq4kCSwBH/CDZKT128NerXbIiImi06RDiEIFGBR7lZziqOXm0111A3xXdiRcWDo/1jcqqzvPwvo8KqZhKh3mAOH11uhzGXVXWtF1sNifK8Pg4y6v7pw8WO1wp6fYN0qI9wYJgF1qTJi7F40z7c8GagtOyaymD13Wk9Wrm6/uUvz0LZxCmYvrRhq1uMDgIeqf7nGlfCgYjWqXrRC4ioXLU9SkTLiWgREX1IREWqvYyIqlXfBUT0nOE6/dV1KojoSVKWOyJqTkTTiGiV+t/MfiQNk1ClSDMzCGP6tkVxYWIE1ee3nIyszAz/mFbbTD6Au4jk/Q5J+mKJjzkqx4FFhrxHs1VEvK4C+vtXKzDwwemuA/lC1a+uqfPiYI0HP1dEHvdhNVcs2LgXv/lX+DQqbtV5eizKpBCCryFg9Pg7VCNuvm6JZOUwjJn7MvMAtT8NwDHM3BvASgCTDH1Xq759mflaQ/uzACYA6Kr+Rqn2iQC+ZuauAL5W+0cM89aH9tH/eMGWINVFPGicl+UvVBRqNQMEqzzsOHDYA5+Psetg/Fwrfcwm7yC3GCfQEd1bAgg85f/n53UAgKUOGWpDXQswP/HXeHz4/X/L8duXZmFHhNH2um3hofOPjei8XyIstlR5oMYfx9IQOblrILPyP5NYZTHdiFqtxMxfMbOuN/gFQMj8C0TUBkATZp7J2rf+NQDnqsNjALyqtl81tIdkyqKt2LQntpOmXnXrxKOKY3rdULitZfzrlthl+bRCBFx5Ypl/P5QdBEBIW4POwRoPnv1uNfo/MB2b98Yn15IvSrWSMR3FKUdrk0etx4cd+w+jSk2Ut7y9wNW1goSDRa30U4U2WU+evzmiMeqXiTQdx/RlOyLqDwB3fLAofKc0xZjDbNWO+GY3bki4FQ4M4CsimktEE2yOXwXgc8N+JyKaT0TfEdHJqq0dAKNVb5NqA4BWzLwVANT/lm4GdcOb83DBsz+7fAvu0FNYxCrK1Q2dWxSEPK6rTc56Mj6ZWQ/VeMAMzN8QWMEURegaauRPZ3YHAHQsboTJ87SPfGuchAMzu1rFWDHGRej2hxqPF4P++rW/vcrl0/QbszY4Hrv+9bn+7UhrT+hCplGEtT6aR2Er+3ThlvCd0hTjfZcAQfe4nQFPYubjAIwGcAMRnaIfIKK7AHgAvKGatgLowMz9ANwK4E0iagLYJqSP6NdCRBOIqJyIyrft0PSl2/fH7sN+tzxQyyCaCSda9leHNtweFUZ41JcVqlbEjwa9uJ1r6N8v6uPqer9R1e4276n22yzcTrSRsHDjXsxZtyeqz+r84wLxGfqDgNV4vPNgDXJcPCRYPZmMK4ctBkP3US3MLsvh0S4UqdrM6IkVCmMOsYaMUTgsD1GOVzDjSjgw8xb1fweADwEMAgAiGg/gbACXKlURmLmGmXep7bkAVgM4GtpKwah6KgWgP65sV2onXf1kuy5m5heYeQAzD6isCzzZXvHKbPS93zmK1y13vB9YWidQNmBnGJ38k+P6mfb//dNaU1rx+qI/mYYz7F7QP3TmVv/1sjWVjdEjKJqiPKF4ekYFxjz9E4DoPitj2g9dOFir3I0b1AFFBpWOG0+XJZudVX+Rxn3otyzSt+dWELduGllsSLqy0aB61lWIQnjCCgciKiCixvo2gDMALCGiUQDuBHAOM1cZ+rcgoky13Rma4XmNUhcdIKLBykvpCgAfq9M+ATBebY83tLvi+5WV2FtVhzVhonlDYc1bs3J79NeKNXoiPgCYvXY3/vzpUlxkyeBaH7JUKPjfLujt2KdNBBOJbq8wPonHuh7Fo1+u8G9vqGfQlz5n11nGaPUic5Oob/7GvY7L4UiEw76qOlzywi8AIlvF5mVnuPayiqaQVTrSSNXtaNM0D61imEOroeNm5dAKwI9EtBDAbABTmPkLAP8C0BjANIvL6ikAFqn+7wO4lpn1x9zrALwEoALaikK3UzwM4HQiWgXgdLUfMRc//0s0pwEAnvm2wrRf3wknEnq2CZ3B1Og5dPHzsRMKOrpXTCgj9Izbhrq+nh7ZO2VRIBgrnmlAovXk+uymIfjspiEoUW7CdV42BT7OXL3LFBznlEzQ+DSan53p+F7DrRCNLNi0168OIQqo6ux4/erj/dvNGuW4jq2IppBVqvJ/Hy0xpRAx4vEyCnOzkJedic+XbJN63C4JKxyYeQ0z91F/vZj5QdXehZnbW11WmfkD1a8PMx/HzJ8arlXOzMcw81HMfKNBFbWLmUcwc1f1PyqdSSQ/PivW1NOJ5I5R3cL2OT/K7LBu0B8grU+oQ7sFJj094K1jcaOwqwjdk2np1oAraCoaAo9p1xTHtGvqtyvUer0mR4Tl2w6Y9NVOK4fOhpXdbe8tdHw9PduvE5e/PAt/fEfzkDJVAfT6kB1C5Teka6AKX52XTY4FobC+nXRdSUyavDhk1T2vz4fMDMLanYdwsMaD3vfVXwV9JCAR0opofOVjxdBuLbHu4bMw/dZTMP3WU2377IowBcDuQ7UY/ti3qHDhuqc/QVrnn+cu6x/U993fn4DJ158Y0VgAd66vycIvHDy+oPiO6jqvP8J2b5W7J84P5tmn2gg39/6waic+nL8Z1bVekyG8dZNgYWxMzmhEf0DaWxX++2Jd4RwII7xSlbdmO3uLAUCdj/2leQX3NDjhsG1fdGU9v0+B8opdWjZGl5b2Hi1rLVlO87IzUOvx4b3yjbZqjG9X7MCanYdw90dLwr6uLhysAtIuPUarJnn+ehSRoAdZvf7LepRNnIJV21PHa8TorWSdRA7X+fyGeqesqMxsikX48lf7dBTzNuxxNZ4vft1qcg4ozM0yFaACgKuGdMKZx7bGUxZnBeO4w2FVK1XVpZ9wsH737VY/Hq/Pb1cT3NPg7tjSrfELFEsm7ZubJ+RebZvi6RkVuP39Rfh0UXCitWaq5vOug26eILX/8XTf1aOOdWH14g9rYnbtkb3c5RJyQq8ZvnF3la0xWc/Y6qTL1wPxOhabEwCeavGMsSYiPHC4zlbg/FRhtnXkZWdiePfg0J9nLu3vaItwE+xlzfqR6NKuscCausRO9efxcsKKZjUkGpxwaKhpea871VzpzONjbFfpGNba5D/S5/lVO8J7XTmplWLJpj3VJjfPJnnRBdnVeX341zfmFAj9OtTPX19/6s/LzrT1qvpVpdFwSr/N0FJ4ZFtSbFtdY61ulMfe9xV63vNl0PWKC3JMT8R52RkY3r1VRE4Bl78cvpa0vlrW7RtvhgjmS1Ws2QUW27gSz1q7G5v2VJtqtv/utfKU0BakMg1OODRUjEZHAFi+db+/7oPdU1EkpkUng3SsOfspc4T3RxGmkwCAez5egse+MtcvmHBy53qNKy8noFY6GCKT7JX/nmPbXuvxoabOGyQcFmw0G4ZDGXyNMRRN8rNNxmJdvdeppAB/u7A3zgnhuRQNvz9Vu3+RuCunCut3mR+MnrTJnaSnbjHet2lLt+OKV8IL0COZtBYOV5zQMW7XTmSK7GhoXpDjf+Lz+hiv/LgWPxkinHWf/W6tGoe9VsDmEIeBOvDSj2vxh3cWRGx7eGv2RtP+RzecVG9jt34fa+q8thO4MZrajnfLN+FQrTfIXjGsm3mlECrWw5gy/MBhj0mtZBQ6Fw9oHxQUCcD/VGzMj7Vsq7vEgWP6apPmiV1KwvRMHUY+/j2e+261P92NTjwi8Y9U0lo43DGqu217pFkpjbxweX+c1KUYr1w5MOprxJs2TfNQ4/HhqW+02AyP14f7P1uKS1+a5d+f8F8tp4+bgCj2q5USr5c9/fHv63V+3/ZF9R4DESE3KwM1Hp9tJHf31uEFLBDszXSFYaIGgPkb9+DLX7VCPVZBMXd9wFh9sKYu4hgEXTBdPaSTv23GitAJ+Lq2LMToY1qjab5mn6pIISeBcKzYfgAPf7486D4esMQw6LE2nUsKUNI4OYWz0pW0Fg6ZDpPZ2BciD4bLycxASWEOzujVGm9cMxiDXOanSQbFhTmm6la1FqPcyz+u9W8fcvEkFQ+10ru/PyFm13LigXOPidm1ajw+fPHrtiDff0ALbHPD0ZZVmnH12aZpHuq8jN8roX2aoYIbM+MP7wQywL7+ywa/PeniAe5SluirC6NQCZfN1aeSFuquumsSXPc7Howb1MG0f/dHWq2KdbsO4Xf1VD8eaaS1cIil73LrpnmmvO+pSO9SrSrcks1mdYHXUsrTGHDmpiiPrkqx6zp2YHv/60ZCIoTr6GNiLT5RAAAgAElEQVRax/R62/cftn1iN7r0bt3nnF3WmsnXqOIwejKt2HbAFIHfadLUoGv98R0tmO7iAe1djBzo0UYTTMbhvztnY8g6Dcxa/In+/tLRW8mKNfPtHrWaa5SThezMDNxp0DaUJKiAVrqS1sIhy6CLrU+KaUBLl+Emd04yeeXKgZh8/Ym4ebjZc2nLXnNsh1E14saFT/892QUCPnxBb3xy45AoRht/igtjmyfncJ0Puw/Vonvrxlj5wGh/uzEgzRpvAmh2ndN6tArK4GoUFj0MKVJGPuFeleY2OPO+c3rh7rN6mITQwk37cOu7zjUptJWD66GkBVZ34xM6a3VZdEcD4wPlThdu3kcyaS0cAM1GAAD/ver4MD3DM8UmXiCVKCnMxXEdmgW561lXUManx427w9dRGPeinuCt/mNsCCzfdsA00ZtcWB1MAVkZFLRyMK64CnKic3BwW6GtTdN8XHNy5yBhsjSEUXrdrqqgGuHpmkJDp7rW7FRgrcNdn5reRxppKxx0PfAZvVpj3cNn4djSplG7+MWrSlm8uH2k2RBv/cJb0yC4Laoe63khJzP2X69oVFz1ZbNhZXbn5OCKaT5mZGSY1Xmz/jQCjXKysPKB0Vjz1zOjdpLY7SINhpVLDKqocAWG5lnyMNX50nvy/NeMCnT+U7CaTseYWBFwjnoX0lg42K22nVJPhGN7hLV9k41VV2oUBswclNsnVBlSY7LCSOsNhGP+PadjyZ9Hhu0XqgaClTyV++jxS9wVHooFHq8PJ6s4E7uVmF7HWhcAnUoK0ErlQ8rJykBGBrkuO2tdfbgV7Eb+aqg5HU44jBukCRLdFdYacZyKuJnQ9RWRnoakQ3NN3WZ1LnCTZuRIJX2Fg00JlHDFapxIt6V0M0sZSGMFN6Onkk4o//rJBkESa+FQkJuFwtyssOqq1RHU4fAy46QuxTivnzsvHrc8eJ6z51NVrRfnhciKy6x5et02Usuua+cE0LNt6LTsOh9ef5Jpv3EUkeTG34Hxsz/xoa9RNnEK9hyqRf+/TAMQUHfdOOwoAME1LVKRcJUTgYALt159741rNLVzvqXkaigHgyOdtBUOdtjln3FDE+Xyd9sZR8dyOHHDGolr5PVf1qOZMs7fpAzXofSs1bWBY/F6anQqtak/xd3y9gI8Pm2lbR8rXl90NaPDYVSBWdVh/ToUhXwC1w27epyDXcoSa7ZXOwaWNQsSIqf1iO47rcdmGCO+9ZKlZz/1oz/Lr34rs9VnZPeAUOvxRVz/Op4Yc+i1K8rH97cPQ1eL1kD/Lnt9jJLCHLRXKwdrrrEnpgdHVAsaaSsc7OaHHm2a4KqTOkUc3aw/XXV1EU2c6qzbVYU9VXVo3SQPLVXVq1A2FWOQXNui+KRP0Cdb66RrTNfwT5u0B3b4mKNeIYYi16Bu8Fj07uf0aev3NrJLMbFuVxXW7arCb/q0AWCu76DjJor76UuPC2qLNpV8qGSBxu+Dfn39geOZb1cH9T/67s9x8iPfRDWOeDBrTaD2ypZ91ehQ3AjTbj3VVH/kMVUpcE3lIXh89tHmADC4szt135FI2goHpxw4uapM4px1u3HbewtdVSCrVHp3N8Xk0wWPj/GZ8r666LmZ2ONQD+Ld8oBaqXdp/aON7eijopjn3H0ayu8+DZcN1gKVIk178cT0lVi0KT5Zd42xIo9dpNkzZt81AjMnDQcR4Zh2miF8q0NK+IUb96JAPZSU2JSidArYvHlEV/92y8aa4Pnf0+u/gg1V1a/YoJbURzVTZYzVs+da2RJlKvx4cNNb8/3bxp/3tysCifS+Xr4DNR4vZq7ZZYpcP/noEvRs08Tv5ZiKRahShYYzGypyszJQ52X89sVf8P7cTa5c165/fR4AYGeaflFaNQmejPYfrsMlAwNeK3epSFGr8b0+1fPc8sylx+HtCYPRND8bJYW5/khipwnTCV0FYJwEYoVeo6JnmyY4/zjNntGysX3tCrsCSmf3boM2TfPxz7F98azNCsCunMBpPVoF5V8CgN+d0hn52Zkh7SDhaG4QAFaV0Ok9DSnO1Uegr3rSmTJLyvTT/xEcT9IkLxtTbzkZxyqvt+e+W+344HSk40o4ENE6IlqsakWXq7bmRDSNiFap/81UOxHRk0RUQUSLiOg4w3XGq/6riGi8ob2/un6FOjdqvYEelarrHN3kqNG9eUJ59aQydgKw1uPDiO6BSWD1jkOYsWIHjv+rZpSc77LwTCxonJdtWr7rqT9WWHL5xLPOdDg86vsSKi5AZ4flISI/OxNtlRpnTN92tsF5pUXmiWtw5+Z4afyAIAMpoEVkL/vLKFx6fPSJJSeO7uHftj4AvD0nkLxQd+zoWBysCks37j2nl2k/VB14o4pzb7XUlLYjkpXDMFUreoDanwjga2buCuBrtQ8AowF0VX8TADwLaMIEwL0AjgcwCMC9ukBRfSYYzhsVbjBOQUXWZaLbICIgMEGkAzcO04zNR7cqdCxfWZgXuEctGudisUElc/0b80x9+3WIj0rJDmsqa51Jkxfj8pdnJWwcRiLxd7fWdfAx2/jOmelQ3Ag/TRzuj8XRK5MVF8Q2ylvHaHfzMQfVwNDRH8OMk6WbZI2pSG4EcTVGFbI1/YygUR+10hgAr6rtVwGca2h/jTV+AVBERG0AjAQwjZl3M/MeANMAjFLHmjDzTNYeHV8zXMsRp1QXVmO0mxS+esriYVF6OyWD20Z2w493DsPuQ85PPUbD7YEaj8ml1Ko7f3l84rLQOtVfeHvOxqTl9+neWjM467UNQlHUyOxKzADCSgdoRuJGaqWgpzVpnBe/1PDXD9XcUz1eDqqBoaMP21gIZ+ve5NgXZizfgbKJU/DazHVRne/WXRgwzxMSNW2PW+HAAL4iorlENEG1tWLmrQCg/uszazsAxqT7m1RbqPZNNu1BENEEIiononInn3xr2UQ3qiJ9YrAr5J7KlDZrhEMhitMYOaVriW0E9BCVw795QeKSkB3fuRi9S5vixSsGhO+cIDoUN8LCe8/ARIc08EDAV964wvx4wWbUenyu3Wsnz9MKHOmrD7s63bGim3JnDZUzTB+2Ub310+rkCOj/+Y9WTOneT34N2a+xgzdiUaMcVDw4OqjdzrvNqLmWHEv2uH1sOYmZtxBRSwDTiGh5iL52vxKOoj24kfkFAC8AQG6brrZ98ixeGm4mTz3/ShLKGdQbt3aSWq8Pb1jKQM5asws/Vux0lbk1lmRmUL2S+V0+OD5FnsKluNbdIHXX5zvfX4R3yrXnHbdCWp+oje6kC+89Iy6qnBzLeO0wyo1xgzrgrdkbcNeHS/z2jkTZgYx2kXAveXznYmzZW40/j+kVpEbOyszA2b3b+D31AOBPZ/awXsLEvR8vwbe3D4t80A0cVysHZt6i/u8A8CE0m8F2pRKC+q9XFtkEwJhnuBTAljDtpTbtUWENNnKzZNS/jMkodlNfrEXsrQws08w6CzfuNdWAAICHPtdkvCeFApzcYE2mlij0BIf6qlUXDADw2sz1EV0ry+C+1DQ/2+/GGkt0F+2VIYr4GIvj9GwTHOdj/Grsc7BtxYIBD0z3b4d7WJm+bDuWbt2PgWXNceaxwV5W1nTxizbZ27h01u1yNlwfyYQVDkRUQESN9W0AZwBYAuATALrH0XgAH6vtTwBcobyWBgPYp9ROXwI4g4iaKUP0GQC+VMcOENFg5aV0heFajnSyCTQC7HKnuCh240vflcOjF/YOefzVqwYBAH5ZszvIHpNKUa9GZtkkqTMajJOVWV03YtYntfu1p2p2ALvU37FGz+8U6kncuPLUXXiNGL8jhxKUpK6+DystLN5iHy+wf9ZMZH6udMTNyqEVgB+JaCGA2QCmMPMXAB4GcDoRrQJwutoHgKkA1gCoAPAigOsBgJl3A/gLgDnq737VBgDXAXhJnbMawOfhBuUUBV1UYFYNuEmspX8V03Hl0NJgJ7FTtzQyeHWdZXnKcltlLJ7oCdGMXPLCL5izbreprc5jSMOcJJdXXU3z3cro4ywSGWipR0nbucvqGKONC3KzcFqPluhpqD1hdAV386AVCWsqD+K7lZW4+PmZ4TtHgNt73L5Z8HdPCBDW5sDMawAEiVhm3gVghE07A7jB4VqvAHjFpr0cQExqPuZZ1EpOkdRG9B9AutczKAlT/MaoBgEQVBciGXRuUWDrj/7olyvMpUYNn82xSUjbDQRycL05awP+et6xYXrbYycM44We4TWUatWaWiUnK8O0MjKuHGLt1TP879+F7xQFboVD/46aytX60CRoNLgIaWvhm20usi6GqoSWTugpE84/rh3m3HWav/0CG3UBEEid8f618a/37MQ/x/YLqmwHALPX7sbbszfgk4WaSsC4WrjEZenMWNPSJi1GpFxwnOaIZ5d/Kdbok+R3ISLKT7HYrPZV16HCkDjQWFXQGvyXqlhzeF3U3/77T0Ro2zQv5MrqSKbBCQfrBO/qaYc5Le0NOneO6o7OJQUY1k3zJv7toA5oYZjIrPUSXr/aXDWvTVFwiohE0TQ/G0Md4ksmTl6Mm1UeHV2AX9S/1FQeNpEYv1trLGnGb1Apr91cY8rNQ/DBdSfGdGx26N5Ven2PywZ3wK2WvE1WIfVThWbv0Q3VxnT241+ZjVdsUsInmiZ5WbjyxDLH41bX1UcvcrYtNMnPlvQZDjQ44WAllBufjo9dxTClLNcNPQrf3DYU3Vo3xrqHz8KAMrO3RrGlOJDVZTPZ6rSjXWTDXbBRS/exMIznSaIwqkTuObsnbjujm+tze7VtGlSTIx4UWOxyjXKygoLuTjm6xLR/xyjtfei2OqvTwv2fLY31MCPGx6Htgy0iWOEV5mZhj021vb1VtUElVI804heemUQyKPCk6cazhBGfGgGpwsCy5vh5dcADKD8ntZ4J3KRY/2LJNgDAyu3uCwMliquGdEr2EGyxPgS0K8rHMe00Y/PfL+qDET1aBkV7l6h0HnrcxeEUjB72+hihFo9WoRiK8vXaQ8fPq3fixKMCgnL437/D7kO1WPfwWVGPM91JrVkiRvzOkJ7B7cqhIQuHGy06/XxLXqp41EeIJR6vz28fsaunILgjK5PQv2NzzPu/03FB/9IgwQAE7Fa6OtYYBxFPrHanf3y1wrafz8eorvOGTItjTEl+91mhA+B03rQEiFpjgo5EGqRwMAYkOSWlM+LjNNcrhcFY4OSkLsVBT5TxCMCKJcbPc+Jo5/QWQmj2qeyjoVKl6EGke5Wq5VBNYpLw1VqSXlqj+XVmrd0d8jhgtg1d45DHy4oxolrQaJDCYfSxrf3bM20CqoLg5OvdE8XTvz0uKFAwFbh9pLPO/rGvVvjddBPpCmpHicV+k04rmRoXMT86y7dpUdWhqgjGkue+W40/n9MLJ3fVVDu7HJ7c3cZajBvUHk9c0jdm4zsSaZDC4bQegToGbpaHWg3gI0M6+Dg11Uih7n9VrRfnKxfQPnGqVucWN7WgUxU3wYMFudr7u/ujJQDM3krxHsv4E8vwvKrQ5kSuyxiGh87vjXP72ebvNHFcmFT1yawxkmwapHCw5mbRv+AVOw7i62Xbg/qnu7eSG5699Di0K8qPa4ro+hBOXu1QFewiLS0aa662GJ9TNQWJHW7iePp10ALDmLWJ0Y3NLhp+3WIuqtRHBTaGW9Xqd/vl8bHJ6BvOs+mpbyqOWAHRIIWD9aN89rvV2L7/MMa+8AuufrUcv3utHDOW7wj0b+AGaQAYfWwb/DRxuN/+EMpPPBno0aqPXHAsvvzDKUHHrUb0ZHHVkE5485pAnIieFjsdcFMV0Tg5a2V242NzsKbc1zOnGgWY3aSsq5tilWI+J8xK8B/TVmLJ5v14aOoyXPzcTGxJkJotFWiQwuHEo4rRy1D449EvV+D8Z372pwWetnQ7/uc/c1A2cQqenlGhVfJq2LIhiD/GoIh9LBlQ1hzz/+90XDKwA45uVRh0fP/huiB9f7Iw5rN68Nzo0mgkgzoXlQ6NKscNu6viVgjH6r7cw/B7/V/13bR7bT0o0lqsKlruHBWwdTkFw13w7M94/vs1mL1uNz5bFHXC6LSjQQqHxnnZmHLzyfjTmQHPFqccSy//uBbMnPapMyKlaX423vrdYPzhtK7JHoofPTCMiHBaD3PU9P7qOlOa62RinNg6FKdP8rZLj+8QUf/VlQf9ab97G/JZxcIOoWdenTi6O+4Y1Q1N8gIedHp521AlfmOV8qK0WSMM66alEPn9f+fa9jHGSi3alPx8ZIkiNX5tceKYtuETtHm8PjCOHG8lIyccVYw/nJZaKwgd65Plvuo6f2nNZJMq43DD9FtPRdeWhfjXb/uhfYSeXlMXb8Pz360BYE6zEYvVxFJlc8jKIFw/1BzjoJdStStkdVQLbRwndykJOhYtuqDRNQsvfL/asa81y3N1rRfPfrsa367Y4XBG+tKghUOhwfi63yGYp87LR5S3Urpgzem/fleVKV4jmRSFqRiXSnRpWYhpt56Ks3u3Dd9Z8amhSt/ZvbWMpcZMp7FI3Z2trlfaLDivl25qsPM0XF2p1cGIZX6t7fs1obBG1dj461TnQpfTl23Hpj2BtBo97vkCj3yxHFf+e07MxpMqpMavLU4Y1RBOtjiPz6d5K4lsSCl0LxL/U2StN2VccLMyM7D0/pG29YobAsaU6DmZGShtlm8SzG5L04ZC95prZVO3Xa/Mpge8xZuRvVqF72RgyCMz4jSS1KJhCwcXy/86L4M5/dN1NzTO6aM96T45th8ATe9rTCWdbBrlZCUtO2wiWb+7CrlZGSb9fyyEg263sFux6/UV7AIeI0mq55ZmNmlEhAYuHIpdursx8xFpc0hl+nVohnUPn4U+7ZMb9HakM3f9HhARSg0TdSzyDunxIXarwTyV38lOfdW7XVN/8sBYMfIYLaOCHp3tBjuj/OPTVmL7/sO475Nf4xYfkkhcCwciyiSi+UT0mdr/gYgWqL8tRPSRah9KRPsMx+4xXGMUEa0gogoimmho70REs4hoFRG9Q0QxEeXFYSqj6fiYQQ0+DC49SdWgvYZOP0PksMfrM0Um/99HS1BZz8I/er4suwV7noq1sDN8e5mRGeNVfpO8bLQryo9oVWK3evrn16tw5weL8J+f1+Hou8NWOk55Ilk53AJgmb7DzCczc19m7gtgJoDJhr4/6MeY+X5AEy4AngYwGkBPAOOIqKfq/wiAx5m5K4A9AK6O+h1Fwbvlm7Btf2z8poXY4jZdghBbjHFCpc0ambyVlm87gIEPTo/62pv3VuPHip0A7FcO+me+16bOgi9OKuCqWg8mz9uM69+wd2e1Yg3i04kkf1Wq4+qXR0SlAM4C8JLNscYAhgP4KMxlBgGoYOY1zFwL4G0AY0j7pIcDeF/1exXAue6GH54Xr4hNmL2QHMQWlByMOaQyMwijjmmNJ8f1i8m1jZ+o3SpAt+U8+63ZpfT/PlqC71dWxkUFvEdlb566eJu/7bgORfhl0gjb/k42sDU7U8cuVl/cPpY9AeAOAHZi8TwAXzOzMVnKCUS0kIg+J6Jeqq0dAGOF+02qrRjAXmb2WNpjwuk9W+F8Fwm4BEEIYFyxZWUQiMjvJFBfjKsFO+Gvp5S/wFD7mZnx31/WB50fT3wMtG6ah9euGmQKqAU0R5ZFNlUJu7ZMn3Qq4QgrHIjobAA7mNlpvTUOwFuG/XkAOjJzHwBPIbCisPtEOUS73VgmEFE5EZVXVjoXTbdySwpFAQtCOmCcgENNxht3V+HvX62IKGramOPJ7tqZGYTMDDIl0DQmOExUZtwFG7XJ/5SjW2DCKeYa4WsqD+K+T37173do3gjtm+enjLt1LHCzcjgJwDlEtA6aKmg4Eb0OAERUDE1dNEXvzMz7mfmg2p4KIJuISqCtCNobrlsKYAuAnQCKiCjL0h4EM7/AzAOYeUCLFi1cv0nrl2lIDKMrBaEhYowRMhpfrRP2X6cuw1PfVPjrP7jBONE7zaU5mRkmvb7XIFDcJBCMFDelao3c+OZ87D8cSMlzQudi1HnYJBwWbkyNeufRElY4MPMkZi5l5jIAYwF8w8yXqcMXAfiMmf3WXCJqrewIIKJB6jV2AZgDoKvyTMpR1/qEtdSLMwBcqC4xHsDHMXl3Ct01DgDWPXwWnrnsuFheXhAaHG2LAsFpCwyT3LK/jEK3Vprq5MDhOmxRCfAOR5C91WdQTjtlJqiu8/qD4aznHN0q9qqbQ7XBudfuOtO5xKheVU8nPycTh2o9JnXcmKd/wscLNsdukAmmvq4gY2FWKQHaJL+EiBYCeBLAWNbwALgRwJfQvJ7eZWZ9XXYngFuJqAKaDeLleo7LhHXlkGfY79Emtj7TQuwpaqTpoHOOgKCzVMEYQHrA8IScnZmB7Czt2FuzNyJH9auLwK/fuAoIVZ9j2tJA7RXjOXlxqGTYqbggqO2ak821O5ycW8YNao+C3ExU13qDIr7/MW1l7AaZYCL6tTHzt8x8tmF/KDN/YenzL2buxcx9mHkwM/9sODaVmY9m5qOY+UFD+xpmHsTMXZj5ImaunxO1BV2ad1ZJu7INX/webRqOAamhcsXgjgCAKTcPCdNTiBWrtjt73ejanhkrdmDOuj0AAunAdx6sCVsAyXg8XMzCSz9oif+8hnTj2XFIfGgdRk5WRpCx/PSerfDRDScFnXv54DI0ysmCx8eosqxAYpVaPBkcEY9iGRmE//zPQPz3aq1ICxFh7t2nYeUDo/061L+elz55+Y80/nj60VjxwCh0jYM6QbDntyHSez90vvZbmW3IfVRd58WhGg8GPDAdR/1pashrG4v4ONXo6K6KKD0wZRmY2bRyiEdhNmu2VacIZ7u4Gx+zv0jSZ4u2mo5Zq1KmE0eEcACAod1aol1RIANkcWEucrIy/D7VXl/DCV5paBBRWtduTkeMvxWr7r1Zo+CstJ8v2Wqrt7fDONE75afKNaiOar0+02pjy77YV2N7clxfV/3shEObpnnIVXbNKksNCut+OnHECAcndF3prhjkixGEhgIR4ebhXfDBdSfgd6d0Nh3LsZkgJ8/b7DoFjT7RDyxrFqJP4GHtcK3P5KEUj+p0/Ts2x8PnB7QHTqorO3tHcWFug3x4OeKFg54moHFe+uToF4REcOsZ3dC/Y/Ogdqe6Gm/MWu/quvq8b40dMPK7kwMCqbrOa6rvsb/avjZLfSkyZGdt6lCzo8hm1QTExg5yuM6LLXurcbDGA49Deo5EcsRnNbtscEdkZmZg7MD24TsLguDXr1t5Y9YGV+fPWafZKkI5nxnjDnYerDFN1k6vX19ysgITvJ423IqTYIxFIaob35yP6cs0D62RvVrh+cuTm/rniF85ZGVm4PLBHVOmypggpDoFDgFjbjO13v/ZUgDOMQ6AOXL67Kd+NAfExaCGtR0nHlWCsQPb49Mbh+Ce3/Sy7eNkYDbaIi4bbDbmT128FTNX7wr7+rpgAIAvf90eomdiOOJXDoIgJIdQwqHEkm5/w+5AQFy86p7nZWfi4Qt6h+xjdW/Va0AM7lzsb7OqqK9/Yx4ALQA3nZDHZUEQkkKoPERWw++ug5rDyDsTBpvKmCaTdkX5eHn8QADaampwZ80+U5ATndrLya03WYhwEAQhYpq7rLIYilDxb1aX0f99byEAza01Vdi8t9rkuXVUi0IAwKY91SEF30s/rMHFz88EoNWsmL9hD7bsrU45t1dRKwmCEDF3jOyGiZMX1+sadV5n24FTigxPiHMSRZeWhba1HL5etgMA8OnCLVh83xn4qWIXfvdaeVC/B6ZoNdPK1+3G/Z8txaJN++I74CiRlYMgCBFz8YDQ3n1ujMYHDju7pDayqGYGlWkqm+M6OMdGJIp3f38CgGD31U9u0lJrzLhtKBrlZDm6w+pc+NzMlBUMgAgHQRCiwJgw74c7hgUdP2xTYxkwp87ICxE4ZhUOegbxjBSYsZoX5ODfVw7EtD+eampv2TgP6x4+Cy1V8j2r8Phw/ibsOhjw6GpXlB+yDG51ktVMKXCrBUFIZ9o3bxTU5iQcjCuKbq2dc2VZvYJ+WaPHRqRGrqJh3VuirCQ4k6sRq3v889+twYXPzfTvj+jRMmS094fzk5vuW4SDIAgx57GvVmC/jdpIz6t0+8hutkIlHKHcX1MNa5qRvVV1WLvzkH//tZmhI8pXbndfQCkeiHAQBCHmvDV7I/749oKgdn3l4GYF8M+xfXH7yG6mtnQKVrWO9WCNu8SEOi0a54bvFEfS504LgpBSTL/1FL+94ehWhUHH7cp56sLBTSrrMX3b4fITOvr3zzy2dcqoldxgtZscrPHg9J6tXJ2bnUkRC5NYI8JBEISo6NKysV819MQl/YKO2/kr6cLBrXqoMCfgbZ9ulQDt0ow0zc92tSIoyM3CIREOgiCkOz3bhi+3e6jGg8WbNdfNLJdZTDMyyP8EnpkKrkoRUGgjHDbsrkJ+dibGDXJ2BW6Uk4mCnKz0WTkQUSYRzSeiz9T+f4hoLREtUH99VTsR0ZNEVEFEi4joOMM1xhPRKvU33tDen4gWq3OeJKurgiAIKc93tw/FJzcGymhaPZaGPPINLn95NoDIDMv6E3g6VlWzGqVnr92NjXuq0Lu0KKjvoxf2xmc3DcGM24biwOE6TJ6XPt5KtwBYZmm7nZn7qj/d+jQaQFf1NwHAswBARM0B3AvgeACDANxLRHpEy7Oqr37eqCjeiyAISaRjcYFp0rNGQO+pCngvRTLRN1bCITMOtaPjTWkzraLepNHd/W3MwIX9S4P6Ht2qMY5p1xStmuRh/2Ft1VDjSV6sg6v0GURUCuAsAA8CuDVM9zEAXmMt2uUXIioiojYAhgKYxsy71TWnARhFRN8CaMLMM1X7awDOBfB55G9HEIRUYdOeKsdjGREIh3ReObx5zWDMXrcbSzabI6GNnkzf3z4MedkZ/uA5I/FKT+4GtyuHJwDcAcAasfGgUgqVVmMAABEPSURBVB09TkS6laUdgI2GPptUW6j2TTbtgiCkId/8rxY5vH2/c32HzIjUSrrNIf2EQ+umeTinT1ts3htc93r2n0Zg5qTh6FDcyFYwAJG7v8aSsMKBiM4GsIOZ51oOTQLQHcBAAM0B3KmfYnMZjqLdbiwTiKiciMorKyvDDV0QhCTQuUUh8rIzQqaGiOR5uDBXy1GUTjEOVsb0aRvU1rJJHto0zQ953uHa5GWhdXO3TwJwDhGtA/A2gOFE9Dozb2WNGgD/hmZHALQnf6MpvhTAljDtpTbtQTDzC8w8gJkHtGjRwsXQBUFIBiO6t0K7Zs4TX7ui0JOikVlrtSpqdSmUrjtSRvRwF99gxW1d7lAcrvPi3o+XYF9VZLW3wwoHZp7EzKXMXAZgLIBvmPkyZUeA8iw6F8ASdconAK5QXkuDAexj5q0AvgRwBhE1U4boMwB8qY4dIKLB6lpXAPg4onchCEJKUZCbiUM1Huw/XOfXtw/pUuI/nh9BQZwDyjg7d/2e2A4ygWRmED647kT0atvENlGhE5UHa/Be+Ub0uucLeKIUjh8v2IxXZ67HY1+tiOi8+qzT3iCixQAWAygB8IBqnwpgDYAKAC8CuB4AlCH6LwDmqL/7deM0gOsAvKTOWQ0xRgtCWlOQm4U9VXXofd9XOPupH4MmtnyHeg2hSOX01m7o37EZptx8squcUpOvPxEA0LNNE/zls6U4VOuN2v6g3/pIV14RFfth5m8BfKu2hzv0YQA3OBx7BcArNu3lAI6JZCyCIKQuhblZqDVkHK2q85rSabgNggOAAR2boXz9nqgESrqiv1e9MBAQfRU83fY/e93u0B0tpK+FRxCElGVN5SHT/rqdh0zCoVkj92VG/3Ku9tz46lWDwvRsONhFV9fURSccdLWe9TMJh5QJFQQh5kxZvNW0v/NgDeq8jAEdm+HxS/pGVIO6R5smWPfwWbEeYkpjp3raebAmqjTnb8zaENUYZOUgCELMuWZIJ9P+Vf8px9z1e5CdmRHVBCcgZGGgeCDCQRCEmDOse0vb9jTLnZdSVDtU13OLXVr1UMhHJQhCwkinSm7Jxpqi/HAUNaWNNbtXbj8Y0bkiHARBiDkiA+qPNV3IzW/PN032bnhv7ibTfiTni3AQBCHmdHCwK8jKwT1Wd986L2PnwdqIrjF7rdl9NRJ3WBEOgiDEnNJmTsIhwQNJZ2we8n9YFVlOuWyLgNmy97Drc0U4CIKQMGTl4B49xcjNI7r624oLw5cYNWL1DBv22LeuzxXhIAhCXNBrJX9w3Yno31Gr6yVFHt1TVlwAADjxqGJ/W22E7qx/+yKyfEpGRDgIghAXdLtD26I8f9K8qtrk1kVOJ37Tpw0AoLWh1sOhKPMr3T6yW8TniHAQBCEuPH95fzx2UR9TzYKfV+9K4ojSi8sGd8SCe05HWUmBv+0P7ywIcYYzw7ppcSdWG0QoRDgIghAXSgpz/bWSxw3qkOTRpB9EhCKVg+qes3tGdY2xA7USOj3bNsF5/dqhdVP7inN2iHAQBCHuDHeImBbccelg98L1b18sx0y1QsvLzkSTPC2FXp3Xh427g8uVOiHCQRCEuDOsm1RurA/WaOlQPPPtaox78RcAWtBbhvIf/mHVzoheU4SDIAhxJyuN6z+nArqXVyRxIl4fw8eAfkrXlpHlVpKU3YIgJIR7f9MTA8uaJ3sYaY0vTPYLY3qMw3VeMNgfWxJpjIlrcU5EmUQ0n4g+U/tvENEKIlpCRK8QUbZqH0pE+4hogfq7x3CNUeqcCiKaaGjvRESziGgVEb1DRO6TvQuCkBb8z0mdcEy7pskeRtoyrFsLdG1ZiF0Ha+B1kBLG9kM1Huyr9uCAcn+9dmjniF4vkrXeLQCWGfbfANAdwLEA8gFcYzj2AzP3VX/3A5pwAfA0gNEAegIYR0S6Cf4RAI8zc1cAewBcHdG7EARBaOAU5mVjT1Ud+j8wHQ9NXWbb54SHv/Fv13h8+HThFn/g3PDurTBzkm11Z1tcCQciKgVwFoCX9DZmnsoKALMBlIa5zCAAFcy8hplrAbwNYAxpyrThAN5X/V4FcK7rdyAIgnAEkJuVgZ0HawAAny/ZZtun8kCNf9uuOJAx5iQcblcOTwC4A0DQqyl10uUAvjA0n0BEC4nocyLqpdraAdho6LNJtRUD2MvMHku7IAiCoDAGsG3eG94lNdJUG1bCCgciOhvADmae69DlGQDfM/MPan8egI7M3AfAUwA+0i9lcy6HaLcbywQiKiei8srKyLITCoIgpDMHDkeWOmP/4bp6vZ6blcNJAM4honXQVEHDieh1ACCiewG0AHCr3pmZ9zPzQbU9FUA2EZVAWxG0N1y3FMAWADsBFBFRlqU9CGZ+gZkHMPOAFi3Eb1oQhCMHpzToTuyvjrNwYOZJzFzKzGUAxgL4hpkvI6JrAIwEMI6Z/esXImqt7AggokHqNXYBmAOgq/JMylHX+kTZLGYAuFBdYjyAj+v1rgRBEBoYTfIjizz486dL6/V69YlzeA7AegAzlSyYrDyTLgRwHRF5AFQDGKsEgIeIbgTwJYBMAK8w86/qWncCeJuIHgAwH8DL9RiXIAhCg+O7FcGq9IM1HuyrrsOBw3UY9cQPpmO6XWJM37ZRvV5EwoGZvwXwrdq2PZeZ/wXgXw7HpgKYatO+Bpo3kyAIgmDDOX3bYpal7OeFz/6M5dsOmAoCWcnPzozq9SSmXRAEIQ04pWuwnXX5tgMA7L16dMpVLY1IEeEgCIKQBrQrMscoeLwBV9Vdh2qs3W37RYIIB0EQhDQgw5J1zxjkdqjG69/+2wW9Tf0OGo5F9HpRnSUIgiAklZd+WIv2zbXVxJ6qWn97pkWI3BFFiVBAsrIKgiCkDS9eMQCPfLEcFTsO4vHpK/3teVkBo/Oeqlo8dlEf+HyM4T1aoqQwN6rXEuEgCIKQJpzesxWYGRP+a05YsXFPlX97X3Udrjk5sgysdohaSRAEIY3Is3FN/XXLfv92qybu60SHQoSDIAhCGmEnHHTO79cOF/YPlyDbHaJWEgRBSCNys5yf6f92Ye+YlWSVlYMgCEIaEUptFMta3SIcBEEQ0oim+dkJeR0RDoIgCGlEfk50uZIiRWwOgiAIac4do7rh2HZNY3pNWTkIgiCkGQ+ce4xp//qhXXCyTWK++iDCQRAEIc24bHDHuL+GCAdBEAQhCBEOgiAIaczRrQrjcl0RDoIgCGnI2xMGAwDqvByX67sWDkSUSUTziegztd+JiGYR0SoieoeIclR7rtqvUMfLDNeYpNpXENFIQ/so1VZBRBNj9/YEQRAaJnq21booi/mEI5KVwy0Alhn2HwHwODN3BbAHwNWq/WoAe5i5C4DHVT8QUU8AYwH0AjAKwDNK4GQCeBrAaAA9AYxTfQVBEAQH8rK16dvrS+LKgYhKAZwF4CW1TwCGA3hfdXkVwLlqe4zahzo+QvUfA+BtZq5h5rUAKgAMUn8VzLyGmWsBvK36CoIgCA7kqBxLoRLx1Qe3QXBPALgDQGO1XwxgLzN71P4mAO3UdjsAGwGAmT1EtE/1bwfgF8M1jedstLQfH8F7EARBOOJoUZiL20d2w1nHtonL9cOuHIjobAA7mNlYXYJsunKYY5G2241lAhGVE1F5ZWVliFELgiA0bIgINwzrgrKSgrhc341a6SQA5xDROmgqn+HQVhJFRKSvPEoBbFHbmwC0BwB1vCmA3cZ2yzlO7UEw8wvMPICZB7RoEdtoQEEQBCFAWOHAzJOYuZSZy6AZlL9h5ksBzABwoeo2HsDHavsTtQ91/BtmZtU+VnkzdQLQFcBsAHMAdFXeTznqNT6JybsTBEEQoqI+iffuBPA2ET0AYD6Al1X7ywD+S0QV0FYMYwGAmX8loncBLAXgAXADM3sBgIhuBPAlgEwArzDzr/UYlyAIglBPSHuoTz8GDBjA5eXlyR6GIAhCWkFEc5l5QLh+EiEtCIIgBCHCQRAEQQhChIMgCIIQhAgHQRAEIYi0NUgT0QEAK5I9jggoAbAz2YOIEBlz/Em38QIy5kQQz/F2ZOawgWLpXEN6hRuLe6pAROXpNF5AxpwI0m28gIw5EaTCeEWtJAiCIAQhwkEQBEEIIp2FwwvJHkCEpNt4ARlzIki38QIy5kSQ9PGmrUFaEARBiB/pvHIQBEEQ4kTaCYdUqjdNRO2JaAYRLSOiX4noFtXenIimqfra04iomWonInpSjX0RER1nuNZ41X8VEY13es0YjTtu9cDjNN4iInqfiJare31CGtzjP6rvxBIieouI8lLpPhPRK0S0g4iWGNpidk+JqD8RLVbnPElEdnVbYjHmR9X3YhERfUhERYZjEdWsd/p8Yj1mw7HbiIiJqETtp8R99sPMafMHLWvragCdAeQAWAigZxLH0wbAcWq7MYCV0Opg/w3ARNU+EcAjavtMAJ9DK3A0GMAs1d4cwBr1v5nabhbHcd8K4E0An6n9dwGMVdvPAbhObV8P4Dm1PRbAO2q7p7r3uQA6qc8kM47jfRXANWo7B0BRKt9jaBUO1wLIN9zfK1PpPgM4BcBxAJYY2mJ2T6Gl4z9BnfM5gNFxGvMZALLU9iOGMdveO4SYQ5w+n1iPWbW3h5aJej2AklS6z/4xxuPHEa8/dRO+NOxPAjAp2eMyjOdjAKdDC85ro9raQIvJAIDnAYwz9F+hjo8D8Lyh3dQvxmMsBfA1tKJNn6kv1U7DD8x/j9WX9wS1naX6kfW+G/vFYbxNoE20ZGlP5Xusl8ptru7bZwBGptp9BlAG80Qbk3uqji03tJv6xXLMlmPnAXhDbdveOzjMIaF+B/EYM4D3AfQBsA4B4ZAy95mZ006t5K9PrTDWoU4qShXQD8AsAK2YeSsAqP8tVTen8Sfyfen1wH1q33U9cADGeuCJGm9nAJUA/k2aKuwlIipACt9jZt4M4DEAGwBshXbf5iK17zMQu3vaTm1b2+PNVdCenhFmbHbtoX4HMYWIzgGwmZkXWg6l1H1ON+Hgut50IiGiQgAfAPgDM+8P1dWmLaI62vWB4l8PPB5kQVuWP8vM/QAcgqbycCLpY1a6+jHQ1BltARQAGB3i9ZM+5jDErS58rCCiu6AVEXtDb3IYQ7J/g40A3AXgHrvDDmNIypjTTTi4rjedKIgoG5pgeIOZJ6vm7UTURh1vA2CHaq93He16Eu964PFgE4BNzDxL7b8PTVik6j0GgNMArGXmSmauAzAZwIlI7fsMxO6eblLb1va4oAy0ZwO4lJV+JYox74Tz5xNLjoL20LBQ/Q5LAcwjotZRjDm+9zlW+qlE/EF7ilyjbq5uTOqVxPEQgNcAPGFpfxRmw97f1PZZMBucZqv25tD06s3U31oAzeM89qEIGKTfg9kQd73avgFmQ+m7arsXzMa+NYivQfoHAN3U9n3q/qbsPQZwPIBfATRS43gVwE2pdp8RbHOI2T2FVht+MAKG0jPjNOZR0EoPt7D0s713CDGHOH0+sR6z5dg6BGwOKXOfmdPMIK1uxpnQvIJWA7gryWMZAm0ZtwjAAvV3JjT95dcAVqn/+gdJAJ5WY18MYIDhWlcBqFB//5OAsQ9FQDh0hub1UKF+ILmqPU/tV6jjnQ3n36XexwrE0EPCYax9AZSr+/yR+oGk9D0G8GcAywEsAfBfNUmlzH0G8BY0e0gdtCfQq2N5TwEMUO99NYB/weJQEMMxV0DTx+u/v+fC3Ts4zCFOn0+sx2w5vg4B4ZAS91n/kwhpQRAEIYh0szkIgiAICUCEgyAIghCECAdBEAQhCBEOgiAIQhAiHARBEIQgRDgIgiAIQYhwEARBEIIQ4SAIgiAE8f8TOGH9EotprQAAAABJRU5ErkJggg==\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"df.funds.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 23,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a6b382f28>"
|
|
]
|
|
},
|
|
"execution_count": 23,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"(df.funds.diff()/df.funds).hist()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 24,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf = df[df.substep == 3].copy()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 25,
|
|
"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": 26,
|
|
"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": 27,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['wealth'] = rdf.holdings + rdf.spot_price*rdf.tokens"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"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": 29,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a375b3908>"
|
|
]
|
|
},
|
|
"execution_count": 29,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.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": 30,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a398af940>"
|
|
]
|
|
},
|
|
"execution_count": 30,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
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"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"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.spot_price.plot()\n",
|
|
"plt.legend(['median','mean','tok wt mean','hold wt mean','wealth wt mean', 'spot'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 31,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a3ba93828>"
|
|
]
|
|
},
|
|
"execution_count": 31,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.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": 32,
|
|
"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": 33,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a39c34780>"
|
|
]
|
|
},
|
|
"execution_count": 33,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"(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": 34,
|
|
"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": 35,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a400814a8>"
|
|
]
|
|
},
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.est_err.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a40bd6cc0>"
|
|
]
|
|
},
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
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"text/plain": [
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|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"rdf.est_err.apply(np.abs).plot(logy=True)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a490cecc0>"
|
|
]
|
|
},
|
|
"execution_count": 37,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
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"text/plain": [
|
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"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"#head T\n",
|
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"T = 50\n",
|
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"rdf.head(T).prices.apply(np.min).plot()\n",
|
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"rdf.head(T).prices.apply(np.median).plot()\n",
|
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"rdf.head(T).prices.apply(np.mean).plot()\n",
|
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"rdf.head(T).wt_mean_price.plot()\n",
|
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"rdf.head(T).h_wt_mean_price.plot()\n",
|
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"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": 38,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x1a49ba0c50>"
|
|
]
|
|
},
|
|
"execution_count": 38,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
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"text/plain": [
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"<Figure size 432x288 with 1 Axes>"
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]
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},
|
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"metadata": {
|
|
"needs_background": "light"
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},
|
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"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": 39,
|
|
"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": 40,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sdf = pd.DataFrame(states)\n",
|
|
"tdf = pd.DataFrame(transactions).drop('posterior', axis=1)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 41,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"ind=tdf[tdf.amt==0].index\n",
|
|
"tdf.drop(ind, inplace=True)\n",
|
|
"sdf.drop(ind, inplace=True)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 42,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"txdf = sdf.merge(tdf, right_index=True, left_index=True)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 43,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>F</th>\n",
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" <th>P</th>\n",
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" <th>R</th>\n",
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" <th>S</th>\n",
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" <th>a</th>\n",
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" <th>h_a</th>\n",
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" <th>s_a</th>\n",
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" <th>agent</th>\n",
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" <th>amt</th>\n",
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" <th>mech</th>\n",
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" <th>pbar</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <td>12</td>\n",
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" <td>5529.016438</td>\n",
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" <td>burn</td>\n",
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" <td>0.094737</td>\n",
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" </tr>\n",
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" <td>0.101683</td>\n",
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" <td>51696.659884</td>\n",
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" <td>1.016825e+06</td>\n",
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" <td>16</td>\n",
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" <td>0.000000</td>\n",
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" <td>34521.950292</td>\n",
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" <td>16</td>\n",
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" <td>2248.033027</td>\n",
|
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" <td>bond</td>\n",
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" <td>0.100565</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>49840.696699</td>\n",
|
|
" <td>0.100463</td>\n",
|
|
" <td>50464.333403</td>\n",
|
|
" <td>1.004633e+06</td>\n",
|
|
" <td>53</td>\n",
|
|
" <td>2973.589556</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>53</td>\n",
|
|
" <td>12192.454040</td>\n",
|
|
" <td>burn</td>\n",
|
|
" <td>0.096019</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>3</th>\n",
|
|
" <td>49840.696699</td>\n",
|
|
" <td>0.101391</td>\n",
|
|
" <td>51400.540725</td>\n",
|
|
" <td>1.013909e+06</td>\n",
|
|
" <td>73</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>16015.739280</td>\n",
|
|
" <td>73</td>\n",
|
|
" <td>936.207322</td>\n",
|
|
" <td>bond</td>\n",
|
|
" <td>0.100927</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>4</th>\n",
|
|
" <td>49840.696699</td>\n",
|
|
" <td>0.101548</td>\n",
|
|
" <td>51559.501281</td>\n",
|
|
" <td>1.015475e+06</td>\n",
|
|
" <td>70</td>\n",
|
|
" <td>0.000000</td>\n",
|
|
" <td>9251.317400</td>\n",
|
|
" <td>70</td>\n",
|
|
" <td>158.960556</td>\n",
|
|
" <td>bond</td>\n",
|
|
" <td>0.101469</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" F P R S a h_a \\\n",
|
|
"0 49779.080375 0.099447 49448.626857 9.944710e+05 12 1160.959722 \n",
|
|
"1 49779.080375 0.101683 51696.659884 1.016825e+06 16 0.000000 \n",
|
|
"2 49840.696699 0.100463 50464.333403 1.004633e+06 53 2973.589556 \n",
|
|
"3 49840.696699 0.101391 51400.540725 1.013909e+06 73 0.000000 \n",
|
|
"4 49840.696699 0.101548 51559.501281 1.015475e+06 70 0.000000 \n",
|
|
"\n",
|
|
" s_a agent amt mech pbar \n",
|
|
"0 0.000000 12 5529.016438 burn 0.094737 \n",
|
|
"1 34521.950292 16 2248.033027 bond 0.100565 \n",
|
|
"2 0.000000 53 12192.454040 burn 0.096019 \n",
|
|
"3 16015.739280 73 936.207322 bond 0.100927 \n",
|
|
"4 9251.317400 70 158.960556 bond 0.101469 "
|
|
]
|
|
},
|
|
"execution_count": 43,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"txdf.head()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 44,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"emas = ['P', 'pbar']\n",
|
|
"for com in [2,4,8,16]:\n",
|
|
" k = 'pbar_ewma'+str(com)\n",
|
|
" emas.append(k)\n",
|
|
" txdf[k] = txdf.pbar.ewm(com).mean()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 45,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a49cd5588>"
|
|
]
|
|
},
|
|
"execution_count": 45,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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FyqFUh5qm8eyzz0Z2eMrIXbMIMjpz74OPRmIvAJMmTWLSpEl14jHcd1fjPXBN03jooYfCk8XR3HDDDdxwww0AuFyu8EgC6nqAjR4NRB8744wz2L59e/jYA7+7qs517rvvvkbL2dqoEcPhgFqMdQSSzDNVcxOKtkGNGFIZNWl5BKKeaWM0HI/h4DpJCeMx9OrC3FlPHVR+RzpKMCgUiiOehPEYotRRiliUKumwQKmSjk7Uc1e0DUkJBiHERCHENiHETiFEHT8VQojxQojvhRCGEGJyguM5QogCIYQatzUJpXY4OlHPXdG2NCoYhBAO4GngQmAocKUQYmhcsr3AdUDidefwAPDVwRdToVAoFK1FMiOG0cBOKeUuKWUAeBuYFJ1ASpkrpVwPWPEnCyFOA7oDnzVDeY9OlFXSkUeDz1Q970T0P+08SksPtHUxmgVd17n22msZNmwYQ4YM4eGHH27rIsWQjGDoDeRFbecH9zWKEEID/gX8selFUyirpCOQJj1T9fzrcnBCM9Xcbr/77rv4/X42bNjAmjVreO6558L+lVKBZARDorcz2adzC7BQSpnXUCIhxAwhxGohxOqSkpIks1YoFEciubm5DB48mGuvvZbhw4czefJkPB4PAP/8938ZPXo0oydcwc5dewBYsGABp59+Oqecezk//cV09u/fD9hut2f8z9+44IILuOaaaxJeyzRN/vjHPzJq1CiGDx/Oc889B8Att9zC/PnzAbjsssu4/vrrAdsb61//+tdwGW+88UZOOukkrrrqKr744gvGjh3L8ccfz8qVtvfclStXMmbMGE455RTGjBnDtp22G3MhBLW1tRiGgdfrxe12k5OT00I12nSSMVfNB/pGbfcB9iWZ/xnAOCHELUAW4BZC1EgpYyawpZTPA88DjBw5Uo2jFclRuhMO7GrrUhyxrP18LxX7Pc2aZ4fu7Tjl/GMaTbdt2zZmzpzJ2LFjuf7666PcbmexcuVKXn3qH/z+nof58LMJYbfbonQbL77+Lo8++ij/+vMMANb8sImvV6yu18PqzDfeC7vd9vv9jB07lgsuuCDsdvvSSy+loKCAwsJCwHa7PW3aNMB2u/3uu+/y/PPPM2rUqLDb7fnz5/PQQw8xb968sNttp9PJF198wV8efJT3Xn6SyZMn88EHH9CzZ088Hg+PP/44nTp1ao4qbhaSEQyrgOOFEAOAAmAa8MtkMpdShtd/CyGuA0bGCwWF4qB574ZDOFn1P1KZI93t9sqVK3E4HOzbt4/y8nLGjRvHT3/6U4499thmrMWDp1HBIKU0hBC3AZ8CDuAlKeUmIcT9wGop5XwhxChgLtARuEQI8b9SyhNbtOQKhaJFSaZn31Ic6W6333zzTSZOnIjL5aJbt26MHTuW1atXp4xgSGodg5RyoZRykJTyOCnlg8F9f5NSzg/+v0pK2UdKmSml7JxIKEgpX5FSpo5f2cMK1btVHF0c6W63jznmGBYvXoyUktraWlasWMHgwYOblHdLolY+KxQtiTI1Pijqd7sdOCLcbt96663U1NRw0kknMWrUKKZPn87w4cOblHdLonwlKRStijJBTYb63W53OiLcbmdlZfHuu+82Wr62Qo0YFAqFQhGDGjEcDih1hOIoomG32weHcrvdNJRgSGXUymeFollQbrebhlIlKRSphhohKtoYJRgOC1RDcVSiRoyKNkIJhpRGNQwthuqVH1YYUrIPC0N1kloFJRgUCkXKU2V68QpJlelv66IcFSjBcDhwuPVuC9a0dQmODA63596iCM469QLKysrqTbEfi/11Q8KkJGVlZZxzzjlkZWVx222x6y0CgQAzZsxg0KBBDB48mPfee6/Vy6esklIZpWM+OlHP/aCoEbYg7Z5A3WQYBk5n6jR36enpPPDAA2zcuLGOae6DDz5It27d2L59O5ZlceBA6wcnUiMGhUKRUiSKx+D1eAH4z5PPMXr0aEZOuILNcfEYLjlnMtf84sbDIh5DZmYmZ555Junp6XXK9NJLL/HnP/8ZsFdmd+nSpVnqtSmkjghtCywLLIOw1Y8zLXE6KcHUwemO7DP89acPYRp2709zNEtx2wQpwQw0fq9RlGGxwOHnGjMdLcUm0ANIqpC0/qfWBFJEhbR6wfscKCxo1jw79ezNyEsubzRdfDyGmS/OAiA7O5uVK1fy2NMPcds9D7E4Kh7DrrLNzH5tDo8++s+Uj8dQHxUVFYDtlXXJkiUcd9xxPPXUU3Tv3j35Sm4Gju4Rw7LHYOb5MPMC+68+1r1pp/NWRPbNvKBxXfrM8+GNKYdQwINvVNcKnWcd3kO4dpAtC+x7rSpM+pTnnV4+dgTYKEJOw1q2obvKXckbDl+Daf7r9PB3Zy3/cnq41V3douVJjiTq5ChWKcXHY/huxSoALp98KQAXX34Ra1f/ANjxGCZMmMBF4y/jxadfYdPmTeF8konH8OqrrzJixAhOP/10ysrKwvEYli1bFo7H0L1793A8hjFjxgCE4zFomtZgPIYpU6Zw0kkncccdd7Bp284G79swDPLz8xk7dizff/89Z5xxBnfeeefBVeIhcHSPGLZ+lFy6nZ/bv564ia/CH6D3afWfJ6265yTBci1AF6lxQuNJ6+UfLjvy1q8PIQ8Adi2xfyvzIadnUqe0jjiIYADzHX6uaiDNV5reSqWx+V7oLHLoh3Ww82R69i1FvfEYqD8ew4ljjmPF8pW88Pgs9ggLH5Iu7do1eJ22isdQH507d6Zdu3ZcdpkdkGjKlCnMnDmzwXNagqN7xJCiPOn08jdXbeMJW4PwB9r0Zn6xI8BmkVpB2EPIFlbXPOLysLqVhdHBsk0YLNBSyww0Ph7DT34yCoB5cxcA8NG8Txgx8mQgNubB3LfteQEDiUc0/ozbKh5DfQghuOSSS1iyZAkAixYtYujQoU26ZnOgBEMypIjOt00QwVekCXUQEiUrNJ3/TRUBF4c8TMwaW4O/uWp53dmwKq61iY/HcP0N1wLg99vxGGY9/zr/7wHbKV4oHsO0i6+hY+cOTbpOW8VjANtZ4B/+8AdeeeUV+vTpw+bNmwF45JFHuO+++xg+fDivvfYa//rXv5p0zebg6FYlxbNvHfQaEdneuQgW3R/ZborOd/XLzVeuNqXpeu7DQTPe0iMGxaERH4+hoqqAr77/jPauTB55+HF+LI3MI4TiMYT2Hdd5CD+WbeH2u27lONmw4UdbxWMAwvMQ8fTr14+lS5c2WO6WRo0Yotn5Rez2xvdjt+Mbk4YalzWvNEuRUoemjxhSGdlKMyBKACkOR9SI4XAgFRqXVChDM9LmDXZbXz+FSRiP4eCnugAVj6GpKMEQQxPfupY2J0wFc8WDmHxOgVI3SquNGJCx9ZEKz/Qw5FBrTcVjaBpKlRRNY23FUflRB+/5ICafUxlLqsnn+mjz0ZSiQVrj+SjBEE3KNhZt+KEeocJQzTEkJj09nbKyssOu3EcLUkrKysoSutJoTpQq6VBo8Y8nFRrlppfhcGhSWquMrSWAmos+ffqQn59PSUlJWxclBq+vghrDywGHm5IMLyU1tj+kQEmkbxveVywoqQ3+LwWU1vMMqovs3/qOtwTNcM309HT69OnTTAVKTFKCQQgxEfg34ABelFL+I+74eOAJYDgwTUo5J7h/BPAMkIO9IPZBKeXs5it+c3N4fcStS/J1s1ZLzUVt0ciUHR22LS6XiwEDBrR1Merw6Vf38t66eYweOJIbfzaT+16+EoDZ09eF04T3/Wol9732S/v/QHu4+avEmT4X9AtQ3/GWoC2ueRA0qkoSQjiAp4ELgaHAlUKI+KV4e4HrgDfj9nuAa6SUJwITgSeEEE1bgdKaNHUE0FpqlrYc1ofuMYUb0h77Ldp5mlZHraUqObQRQyqMGFODjG3FTJ2rk7PD9lc27T2d01enfgfkcCWZEcNoYKeUcheAEOJtYBKwOZRASpkbPBbTekgpt0f9v08IUQx0BSpISRr/iD3BTz0T0fINdirp91NY53zpJwZ+N3Br8ue02oih3mpL3fpMRZwltehAerHtGDKnRnLyJlWHLUUyk8+9gbyo7fzgviYhhBgNuIEfm3puq9Fo4yeY7q7iendVqxQnJUgl4RSHF0lp0LVFWqBp51otLOjqr7XG67NGmnxzmPhZai1E0DWLtOp/bh0qJe0rlbBoDpIRDIne5CbVvhCiJ/AaMF0m6KoJIWYIIVYLIVa37aRXY7cVdzyFG83mo+n32KfAYsasAOm+lv1I/+aqbbIL7Y4VkhO3mKRyj/3fRhH/dnrY702tCeA2xdG42fQV83SmzlMCtTlIRjDkA32jtvsA+5K9gBAiB/gI+KuUckWiNFLK56WUI6WUI7t27hg5sGpmw714fw2seAZWvgDVthUCWz+Cog3JFi+uIC2kXvjsHlj1Isy6xA74k/DaEpY+BosfjOzb9jHlWJjRjdjm+bDkH7A/6CvGCNh1EPA0rUxS2v6cQnEWCn+ArQsbSB9VN7lf2/dU8H1smryVsHMRwzfZzsK6lMU9u/Xv2r6nKoIDUMuC754HzwH7vpf9q0kqq73CbDxR8D6P3W0xZJvJ5Qt0xq40Y9cxSGlfe/GDULEXvn8NSrbVdYlSsg1e/TlUBV//4q3w5UOw+YNImsp8+/xQ1uvfhvLc8HaN6edhZy2VZpTTul1LYM+34c0ybN25bsXp0A/sgh8S2G7kLrefR8AD3z0Hvkp7f8VeO5YIgK8KVjxrl61ib0M11jysfxfKopQDG+ZA6Y6Dzk7Tgk1VTSl8cV/TM9i/yf52GkP3wbf/tcu6Ln7K9OghmTmGVcDxQogBQAEwDfhlMpkLIdzAXOBVKeW7SZWouhBob////aswYDx0Ob6ekr0Im+ba/+evhsufg68etbcPZta/ZFvsdlUzRa/avRR2B//f8TkMvqhumtoSOygOcOFSg/1dBJ7Ak/zaXc35WNwYSrcs6Glx28f2PW7+AH54GzQnjL4pnF37KknXkgYEXWW+7c8pdxlMfgnm/87eH1+2RKOiT/9f5L6i63mhHX1ABk8Jez0ONfbfBt0PFK6Hq+dA3new7g3YthC85faxkyZDx371l7uplOfCmlf46dLYRtayourmwK5Io7HjM/t31YvB8kTFJHjfjgrGx3fB1Ndh7s329vZPYegk+/+P7oTqQjp4JT0LLWRgJqx/B6bbsT8+r9jCOs3go6qdkY/o83vt32Bd1jth/f7NdjS9k6fG7q/Mt59Fv7F2Y1ZTDOfdAx/cZguJEy+Db/4TubeN78E18+qvs+Yg9KxD78c3/4ndbiqh99DQ4ccvG0wqpaRzmUV1logMeOfdYv8OvbTh62ycA+tn239g152r/kA/RyqNjhiklAZwG/ApsAV4R0q5SQhxvxDiUgAhxCghRD4wBXhOCBFyfXgFMB64TgixLvg3IsFloi8Yt91A4xbd+zabwZ+8FdcDDTVWYeIayYPRU9d3P1H7+xZYjPzBxBtsIFaLBu4t1KuMG4lcMU/n3K/NBqxvgvuNZOutCfca/Ij7Flh0Kk9wnhHsLYfLHj1B0NwqnsT5yehn3dTnaDQwoRG8t8s+1Dnzu+BYz6jr0joZa6X4YDWx9RSdMPgZW3rsb/SztaK/lSZOyKQAwhH0kprko/rFhwY/+7xhq6WvtAD58aPO+kb0RxlJrWOQUi4EFsbt+1vU/6uwVUzx570OvN7UQk11V3KJmcbVZjrJ67hTTN8v6rFaqm9e4mAnQ+vJr/EYJU2s1yaUL5TypK0WJ221yD27hP7JlqWh61TmQ1oOpOckXZb67lMa0Y1G8883OIPZx09yN+0tbeI7Hb5W0/xb9dtrcUyBBdObdrnWRARVSaIJ2t6uZZIXHF5uquf4f522hVODC6ua2UhBDz4TV7Pm2vykrEuMBY5gb6fBCd6oh9YcE8HVhbZa4Lmz7L943r0udrvBa9Z3LPlyHqJDyeC5jZzd2Isvmv6KyLhb3O2rbxI1eO1kn93bV8H7wc88fn4DoCb5yVrLbE0b+Egd1xkFNHRWso1So2tN4q8Zuz3hS4Mh21N3nQoAoTmGJKok+p3/wpFao6ObXdVcfRhYNaasYEiKmA+nmUYMX9YN2JHc9eOorwHQGg4cEpNF6DLJFSbpfO1bF+K+AAAgAElEQVTMmyp2mjBiiNe4JX1mEoRcCnz0P8HMo3Lfl0BY1IM04yafW4p4Q7bgUz0oVVL9CYPXsmK3jyA0R0hdlrrWZMlQm0S40VTgMPCVdLi+5JEGYIVmMNJy4kKQ8H42zwdH3cFlOGWD71IT62frR5EJeqjbKFYVQk7PuueFknkONHqJuoKhZT6GYZtMjt9lsb/b5WTWbrdHewPPj/Quwd6XAMvU4cBuexQ46saEaZqD+tqxBmtE92Kvn6zvZBnX+DdRPXkYCg7NaXeoKoL3tK/nr2jn2dWWRTqiObxHDIfIGw4fU92V/J/Tw33OurGJ9wqTh5y1Yb0gQLpPkuFNoqELfnzbhMkTTg+POD0x+wHbhHDdm7al0ZJ/1M2iKTdTTyNQp3GJFgoQtAKL4tO/xBUibmTx+T1NKVXiMhwqviqQFmesNulyQOLNGEhpl4ugYE3dKHw/vJW4TKYB839rb4QskJqTYLX9y+lJtLt+YVm9v/E0da7ViCrpMBQE8bgcdh+2fa1dJwF3Tyo6jI0kMFtqzujw6OE3N4fBiKEhDm2OYX5wHuO74CpTO6hKJJ8XHF62aybPOL20l4JrzHSumR20WriysdztfNKCv3kh6wfda9vva5otEHYtabSch9LjjjnXl4RuM2SxUlVom3qW7wlmFMynKC6y1q4lMOAseP7syDWTfRQJBUYS9zrrkvqP+Srt+l14J5RurzeZ9FSCv2mL46LOhk0Nm3tmSUENkkqshCrPhHdpWfDmFXSotBi+TkeeZ9r7PvlTrIVR/IghNA9UZ/I5msNbOFhOF1XZp5Hm/yFxguVPtG6BjnBSf8TQnL0dKW3d9N7vEh5eoMVOVIU+s+WazkJHgLwok4hNwkiqua4zo7DsX/D1/9n/68ktSjukyWcpYe0b9mR6fQ1qtE1/qL7fmgaf3M3aA1uY6q6ksr6ybp5fp4HvUTyA3H53YWrtkit/s/ZoJVTutUcPDTT8cvHfD+0yXz8euz3/d3YdB02cHcF7csZZPzpqA1y6UMdZU/+k6GnLDfruk8j9ZVCVby8cLIxrEFe+YKsFgeYxU0htSsp7cKDTeVRlnlb34Mb3wmuAmp0U9hHWkqS+YADbAqW6yO4NBqJUPk2ZfN4831aj5K+Gz/6aMMkbzoi9uRfJDi3Wxjn6ave7allaXb+OM4BkszAoI8HwPvwSN7FBjFcDQaONqpQWrHw+vP2Ww8d2EWeR88I5kf8r8mIOfRy06tjt25/4AgVr6uyqyjkVAH9ad7sM0SuDGyP6mW7/DOb+Jvlz489PQMDVjcqc07F8SY4WEuaXoM7jGm4r2CMYuyhWMmSu30ePEknn7xNYUMWrgr580Bbq8ayfDWtfD482LSQ+ZN3zQ6O/mv0tt6q/lZCWXeeWlln34PInW7k0Rz6pr0qac739O+pGWxfsTIMbgis4m6JKKt4Ce5YnPHTh5zrtvPDepfYEcBUWf3XWMHCXhZCSHccltiQq0utvXB51VLPBERn+W8BGYXCSbLzK/e4eaJYXpOSs5Qa7TgjeZ7iHGKSm2FZNNURUw2Yi+dDy8YET3taT834eunNDmsm5FACEDAnUoOMzSLBYMOaMuruktBvGBgi4uhFwd4s/MWFj7skYiKWlU9plIqAhzW110iSkzkQvdkPbCGXHdUDP64YWiPMZqcWpfaLNbte+FpNUAmz/pG7m3z1r/wZdW7xV/B3z3VW84q8ivEZ3R9Rcy+xfNVreVEfTbMEmG1gBkN/7JkDGLl5sKnXakaNzxJCSguG4XRZlnQS0S3DQ8MPuZTBgXNMylVaUTb79sE/9wWTkushLdPEnOndOqCFPmPTNtzh3md2zPudrO431i9heV0N9sA1CD79Tg3aaFHXTeCCnlrv1dpwigy93PcKssOc1dim9L3DCTov+BRL+mCDhG1OiLvgujPgl7FsLOxdFFTLyYnul5Pq3kp0jsdFCOnFLRtxx1CFuEVewdyqFI3hU2j6GQvirwRvleT1RPSThjmRfr+sAqPYvwuUIrq+sZ8RQ3O3ymG1DJjlY9pRBVtfk0kZRJKZhdc0KjhxmRQ6EJ4qD29F+i+LMbRvVYlQXgWWyrMIWcp61r5ERUgJsaMADTX0qNsNv59mcLkkOliWP2K5Sxt8JQy7B4Qh+g4lGDEEMp+1nTX5xP9VZJ5Pu2wvURvyoxTFop0lxl8NDadLapGStnLfM4IoPdFZGux6ObjxCqqAmrWOo2/MbFSUUdGdHupekk4dB5zKLQTsz2HPMHfjdPcJp5vp8SCLftJVEbyLNLzl7ucl5QV89FSL5MkdPhFNb2ui12PyB7aRuz3J8ab0p7zA27FzvCy3AZsPA1NIwHFmN5xXEaUm6lViYsoFe2DexQ/nQiMGbMYCAqzPOygQi9NVJNNgba6RVjHdLrZv5FIQm+JOYszCNJPtEb0y2G8wm9kJNsiMb0oqY+WrBslXsg2+eii1r4Xr7tykaxh/eCq93CNeYrwJKtiZ3/uqXIv9/+SC8c03THTLGE704tKa46ecf2G0LBbAdSwKO4Pyf7khCSOd9S1nnCezrNZ3e+6y6C1ODnL3c5IoPGnGBoeYYUoQoPy7xpn6NEvIqmQgpif/iQtYzZZ3OpaD3TeT1/S1XzDP4xYcG3Ur74DP3sq/HlfjS+lLQ6wZ2IdnXazp5fX9Lx3JZvxlmlC+d4AiYrkFPozHNUWMNWPSc4uu/aDgtxFg4Ffa4isr2Ywl8NxMPkhecXv6recjrezv5fW5hr2x45e98zc9UdyVivZ+fLzSQBWX1J65joWPfdE3WyezrdQPOknoa1R2f1933/SzbdLcRz5ZPOz1Y0o9pRSytfhSm3Qgn8THrphsdSUmD474gr/8ioTlxQ4j4fF+7LHgguF9Ku1dfWXdkJAVIRHJKDG85dSSJvya5QnoOwJpZWMKF4ciJqLWsJPwF7fgiuZXmltE04RDw1G3Iv3kKbd9qADRpf1vV/sX4jM22Z9l6kMJp+0tK0sijNdBMiWbGPVnLsj35NuSDq5VJPcFQX88s1JtKwFItQLU04Iv/bTjvOLM+SxNYwk1V1ilU+xfhN34kuyaDvX1/S1HHkQTMXHzGdgq7TyPgzOG8rzqiu7piaRlMma+TtXpT3WvkrYKZ5zPwR4MZswJMez/ykV05R8cVWgPx3Fmw55uGi9tUY50o986htkL31mAB3UosMmsjYun5/LSYU9cKnQVacE6k8IfwRHx2RbCuyptg2imN2AhpUd/BUi1AeajRrNgTW1iAXV/ZnmO31XUBvj04mf+yw0unEguvvhaPvipyGUvaE+3RveA62Nc2TBf/cXq5zV1NtH2ZD8nueMdq/uqIZ9I4nnd4meqOdEgWaQGmuitxUha+9bDwMQKI/ZuQaBFfVutnU4GFJ6oMXvcg9vT7I7qRHt5XhcVUdyVrRVyjLa2Iui+0L9kX5zN7TUpRj6vI7/Pr5M4J3geLH4AFv0su/fwk0+3fBC9fWHd/lFpMElEH62Zh3XU3Kc5Vc3RueCPuGW7/BJb/G9Y12a1ci5FycwwB0wrP97WvkhD6NvLiTEyDw9VCTJ52ehle8QP/z4jSP657C7oMgm5DbDcU0R920KtnaeeJeDKGUeNfFLx2Lrt7T8WrRxpswyrCo1djyVr0DufgiuqNpu2LmlAt2mi7zi7eAhCen3BFdcyzayWuAgOOtRtlHclWYdIJQS+pxaqOiDSXh7KK3gj42GAG+PlCA1Nzs73HJgyriCHbRvP7Yz/jIT2Ldgj+4bJ7VWMCLjrP/x0dPJIzVpv03uegJnMwTn8AHPZ8QRWSe1y1DJAO7jDqTgT5qaIm8CWZ7jFoIiPcYnmQPO300lc6eEzPilhANTgxHeEeVy0aIEzJ1Z8LtneOXZTozDUo7e9C272ETmh4kTzi9LBFM7ggmEZICyk0yqUzav1KhH87PXyvGbwSyCGjEZ1OERaL4nzxzHbYAtUhduExPVh6Kfe6avmvng0/LsJr9SC/3xS68B5gj3ZuDgYbmh2w3c3XZJwBEvxWVjhNbnCk8ZEjwClG1ATsxvcR6b7Y+wi6j69BsleYDE1k8PDt0+F5nPAEfsjbbbI919okRgxvxU1mPXcW3PQlBIKjGnem3Rms2V/vYkSwnRH6jd2kJ6EGbfRzifeDtu4te2Hk5JkNn1dTAu06Rdza6F5AgCvdfofTO9idCHdW7Or7EIFaMuo62o2MaBpbV2OZtlVmk5xIHhwpJxgqo1rBqXN1Kq606NDAwCYQUtnGt54hy416T/RQmzmkjrdGr153ZGJJuwHyG9vxsx0hnFjCZb+BvirbZDMUPOSESDwDw5ENWDjNSAM2z+lnIBm0R+NNh4+FwYblJiODF4LeHs+XJtEzDNG35gnaZbiCR00kH2sBJlju8D77JECCUb6PFzUv1wKW0DAs29dQiaOAQmGxTRiRyXDgYZeHx/SssO61rNM5VGefhrNiE8WdLX4bFTFtv7BYI3ROky78SO511XKR6cYvvIAD06pGc2SENTuh2yhriotMgnX8jj0hbwHXva1T0eFnQFFMsl2V/VmYvx3DCT/rlckzmocML5AZqRefmUvA3MPW/C5kd82lV5HF1v4mJ0kHfmBr0EQ50bhVR/KKw8fFppu3nX5WRM1zWPY4IPwELMvEb+wADCpD91uwBp9luxvxMACwTVyP3W1Rk0U4DElIDRUy0Qzl3zff4seedVWAwtRBgE9IHnHUMt3IoBsajwWF4muBHALABw4/08w0HAg7RkSdGwxauL0xGaYvtBvtECXb7cav58mRhvFgTWDnXBdZODnkYntdUSNCprzWImDuQtKVqe5Kzog6tlbolIkGVLuN0WBbIe162b/JXgM1bDKMCa6Yf2mi/TvlZXh3OvzkN3bQrGFTYMxtdbN6OUEclqaw5B92B3fGkhZfzZ5ygsEvwJNxLG6jDJdRyQEh6dDQHGXwt8nV9PKFYE3CiFrcpWkdsKyKBk4KXlMa7Ol7O52tD8KLxj4RPooti2u2LcREUp01nLLO9ouTWbuZNH8h1dnDGfft2/yxWxX/SW/PfsukZ4mFw4QlPSKmrTWBJWgiC4mgtPMEMnxrw3c6PeiZcZzl4jajHYs1ndecPnymZLIZUT0IqQMu9LIiHJmC4q4/x6GXAhHz1jS/DGvXTl9t0KtIMvdiKMPC0rIp6j4Jn6sTnsBy/IU6d3aqop3HjrOwfaCGFIJHXR5mB9qzSAuwW9ijt3McmYAPgpHIQpIhJN4TNSdlWHREhNUiMQTreOJSg2MKLPZ3+wWljtI6XcOqEo3BZZPwpx3D632eZuIXBr2KHKwYaREw85EyQMDcBThwmD255BODLI/k4QE1XC/ahQUz2Gqrbxw6txoZ4eb+j64aCoXFBs1gf7Cx1yxJnwLJ+h4GI6QLdwB6lltU1ZYD9sjQABZrAc61TKo0u07Ko5Y+hoMIBTvX0jKRGFFqE/io0suFiww2D9Igbo1XqMbWaAbfawYup487jAy2BK+lA685fCxxBKgUFlcb6eQ0pkV++SK46DHoO8qeiwh5tT3uXDgnGKipgYb4fYefEy0HJyQarYSEAthzFQniVYCt1nNgd4IcwUl7w6o7ugyPdvWldrEskFInwfLShuefTMNWBcfz+b0RjcXm+XDqtfDJ3ZHja4MqoFAAoV1LEguGQ6UedWZLkHKCQTOhuPtkBNBr38v82VXJdCOdTx0BHtezGz3/GYeXPlLjEiut3jQ6kp3CxBvYhikjE1MdzU6UiQpcjmPYOmQ+x22MxBRyOnphmJGIpn5zB/lWH+7av5viLoLJH3SnXVoPfnP2DwgpObXTNfiNrbYqJXMotZlDAdjT52bGL8/ltjELGbLD4JJNdgOzYqTEPVDj7OUm1YAla/CZ7ajJOpnazOOAWPPDZZrObdgfD0Q390GCo4CKfdn0yazA024QljwGAvZkXbopufZtnW8u9VOdLTk5WI6ffarzxHEVHNPnCqATHn0lUursqbHThzjrG5Pcvhq7+mvQB+bhY9T3JmuHaZjOrmDmIYOCIejeJuxzyhfXohdhcbu7mqlmOpebkef2jsPHew4/TwayKRQmvQoz2N3vVnzGZiyz7gSr7kijjFwI5NJ5d0fSA6ew95jhjFr7HFu72OqV4EAKwygiw5eGN70bTrOQF9Jia/CRYGNzAxnhtQGFwl7XUhkl2i752KB7qcT1UxO6uhj7lU7XQoutvcPjPfrlWTzX18u50kLXQj1++9OzkOT2u8t+ZLzENHcVZ1nFBIwtFBkSL5JSYXHAb+JL60V29X7yhEkJFqcGn/HArQaTVhpUTUsLt4WLNZ2TN5qcvsbEnGphOO06/0rT2euy+IeeFb5+vSy80/7NjnKqWLo9qd7qbIcPHBH12C5h0lUKsuMFUj2jDgvJtcFO0OxAexzh0+pe+8IvDPoWWGzoYdftDHcNIwJLcWoJLJiiFrfm9ruL7OrVQDAU8IvnJb6Z6FDBZsD2wLw/an4x2jy8NUi0tqaZSbnJZ3eUg7p9vaYDMK/aS4dtOpVY1ES9yOuEzp9cNZy4xSTNKzmAxRJHgNediXsgIW71VrJtXgXCio1eVpU+nyz3ufSoLuChLh3IdEecdGnal3RkSHhbN/Mxq6sYtnEiY1fczM6O3clvJxm6ehzD116JR1+JbhbgN3ZiyQCmVUu1fxG1gWWUanmc9dVJnLCzF7n97iK3312c+kMnrntbp39e5EP5Y1rI4iaiNhJS0mO/Zc+/QPhe4z9vQ1agm4XkZrkYt0JgWGVYUULQ57AVFrk1Ok85vZR3OJM9x9xB++rBDMydjmFZ1AaWB3teILyCnX1vYmvvn5Pb7y4Crm70z7PXekgkvXeanLLBZNLHBiLY6PmNHfiNXWyUxwBwkzuxDvVAsPf9Q9yK7IUBH/3yLJ7Jq2T/7Ar29vk1tYGvMcxCoAaXaE+ac0iCHGHED+2paNeLav8S9vaMhMJ0BhfHWKZOXt/fsb/7NCYttOsVwB2Q9Cyywn3NaJVSuk9y06s6P/1M55yltnFBTk1fcvvdxcvSzfsOP5kVwZGEw23/4mLCYoMOlZJKw4Nb+vHo3+M0NYowechRi1ffhM/YyjR3Fcf/aCJ1ezL7K9Pgz64a7nTV0K2kC0U9rsZynMWdrhoecXk4EBRQJ2y0S/mh7mPgjyaaIdkmdEaudeJL680Phh4zuV0Ypcq7vp5nEkO0o8XKfCLBm6Iadd0bu6gujj+7aviLq66jykTR5PxICoJCWEjJWw4fVeEyx77pPwqTnkUZ+N3dY84HMKwSKnNGxmae+3XsrWXHHvchecXhrdN5iWHvt4n3h0yEa0tgzSx44Tx7PmPfugRpt9luTfJXQ/Fme9/G9+36feXiSCz2NiLlRgxgu3Hwm1vRRHtmzAogcWBp6cwYXI0GvBXshazU7A9u7EqT6lzJ4xMEaX6JmWAEGQi6kytHctEXg9nf+Uyw8sAsRNPak211xBy1hQFz/snyn7qZJHLoXPEdosN4LOlh0bkb6Js3jz6bT4jJt0wrhEDkIZpWJaYVazZbG1hWpzylaYKy9H7I4MR3Xo/LcWhBJXNwnwzpmoPye7mmc9OrkV772l/WNSv8SPMzx+lneOBbBG6qpI5Tc+LV676ce3tO4YLFcxAY/Nh3OKZVREGHYQTMtXUrEPDqtjmjbuZRnjMct+nDmzGQJeJ9ehdKfGm96FS+j7LMyJxFwNyNZmUB5Wim5MbXdUwNmGo/kyecHn5i2enNqI/x/5wefvm2jsBFRftR7O09Bp+xARM/gmp+NqaUvPe3YTiy2Nv7xjp1XJozGF23dfgePeK2I1SXhrDQzWJ8xmZ6ettz06tlfDvKwaCdFp3LJS9f6cJ0i2CZBBaSKfN0PBkD6FZSitO0G9SiblMxrVJyas5mtmMBU52dqGg/BF3Gdk6umKezeHouu3QPOVY5PiPA7e4ajt9phed9rn0rgO4aSn5OBshqeu+DzZ0M+nphyPZ25HXaTo6ezYxZAX7sr1H4E5NOQgubXfctsBi3wqTqBJ2a9oLiblPwp/VmVcHTFHXXmbDG5LvTHPiiBt5eQrp5CyllcjEgEq1p+foJ27ompydvOXyk+SV6XOtSnMTcko7kmuBIYcYsnaJugnkX+hkkTDpjq3Gj+Yurhgm9b0EKd/i7cUfJmvKO5wIvN35PQT52BPjYESALYatmZfTKpSYQbRm34Pa6sa5D8cPXxlkibV1oT0L/uAhOubrp120mUk4waJaL2kBQV0ch+7tejt/dDdPRjn57n8SfBrO6eLnWzEASWSeQ5gevgGvf1qnMFnBxbL43uqvDPYmzO5yIX18JQIYRoF/FYlae6mCGqz23X2sww8hATH2L9m+dT2btZjTLy+xAR7ZnB/hEZGHJumoMhxRILRtLNuzB1OXog27mAyCjGg+PvrpO2vbVFj5jC27RDR3Jfx0ebsSBP607DtPLI84azl1qMnC3xdyfWZR2slgpAkE1avBlLoOKDmOAiC25FrwHn+Yj95j/AQSewOI613dLJ2jtcToH4tFjrcLK0izSHCdjyWreqZZcVDKAoh6/IMO7o04+GX6NPcLEYYHEgRac11mnGazRDHYJiwG5Frt7S0qxqBAWOyoD9MsZw4H2p6FbJQSC74TbaXDTuAOk4eD+X7rI8PqZNvcJdvb9DV59JWnOofiNzehm4pXTppDhqvEZtorgx66n0NPj5YxVEZv4LA90LLCYMaCa0y0X32k6l2ddQGW749GEm5yaTVRnj8BvbEM38+m7qz0Bl0l5p8lAB9p5llHjCCCFw15oiAPvio0cV3gMJekgAxVMWGTQpaw/u4L9gbKOl1PhqMG0bFNX09eV877qSHbtJvK7DkI38yjTwH/MH+lW+ilVtbspy3JgOWwF2bgVdoNd5jXxShcup4bPv4jOe8/gzBWLEVj0y7co6K3ZkdgBhynxGRswrBKkFMlpKH54O/J/wAPudhHXHfNuYZ7bz4zXdfJ6a1SMtygTksxaScDdeNahMXxoBNejWPKL+ToiYFIQFGi9CiMCpk+BRcAqx5SRdTZXv6OzKbIuFbBVWfnCZLzl5ltN5wmnJ2ypFk2oc7JM01ms6TxVXYTWmNuZZAhaiunOjsiDiIrY2qScYCBuyXuxYw+Ye8CEs79uj8Py89LVAa41M3DWWPz8o0iv2RmwH2r76roSPqfURLPg0o9NNvaINF67hpSw+Fj7je0RcETMFJ0ZfHKek4mLqnn7MhfnA+5MB+3cp2NJL1LqePVVOLSu9KguoeK8DXT97FiKO5+DKasQOLDwEzDiGsq0+Th9F2JYjfvbmfi5xfau+zBECY85PVz/us6efnchpUTiZeJnH9O3yPbFc9xuixVddG6aZZLXC3xWJn7NIDvNRVFGT9AjgsHtOAafsRnd3IceNW8Sj5XhZOOJi+lY8gV9910Rcy+mVYnHWgHA+KX9KO52EX5jN0ZaZ/x67Iijxz646/Qaeu+T7On3P7gDheSJj8LDda3c4PyvDHYcq3HruGqQkpvmG/zY9wS8gdi1HiP6CdKOnwAlW/l7pcnudiazL/Vw6cJ32Nf7BnrnP8u2rsfXe09S1lUzmlY5JVnH0zHK7mBK0CprTnsn6zIDZAegst1APLp9zzVuwj1UgFqXk/HfpFHQU2A6dALuHmDuRUqdipwxWLKG9KqulKTvBSykcNHxQH+KulwIwTzLxJ6YmXmJSV6mIKPDNfZiruBrXRNYjNXxDBbrFex3FzFNSNKwreDy+/wGh/EOvfb3JC9jc/j+9neZQIfq9aT5C+hdEKVKekNnY3fbIsgwNdxaEpZG0fErPrgFLvl3zOERG2wB1bfA4teuKhwGXD9HZ08fDX2cjLWeC7JZGDzgquWfehYzZtld/prMoTjMGtx6R8qzjgH2ARoXf2awIdjwX/SFwYYesa7gdVfnOvn/2WV35sYH3DwRXDhbG/gGl6NPeB6nr4yoGoqCoxt/3oqI/6lDIThCKOgdikCd/CimXspz7cny4VNsjwfNSMoJBkvUP2m8u9tYNJHJja++xcpf6nTapOM0oSr7FHSxneOXeynpcgnuQDE7xXYypaAnDnYKg8s+MpAIdvW9JfwhDqgo5+ruAar1LLKD4/Gw7brQ2NtH4/lr3Qy1nGBAX6nRp+A5NMtAs3wE3F3ZPOgHPh8teD6jA/83YBsnb9piu80QTiwtgy1dB4XLr4lMPv+Jg8lfZOLLOA9L+vEEvo6/zTB5vaaBvh4pdTou91HU7So8+uooVVUHsjqMJcO7h+Gb8xm+OcDuY/5Auj8PQ+7FD2wOCDL0iOdPl6MPiIa7bgNL9xBI701hnw2U50BRe43zVr7Lj32vD6uTotmfkRZpJBNoGTxOmLRQp3uJJLefHWTlTlcNaX7JVXMN1p1k96CO32XRs0innddBUffJYdNh4aiib0k5wpnD6L+8BpkdYek/6V+xl/7SwayOPj68sJLLP3yUReOcdI8Kw+By9Ec3cxu8X7DnQ3L73UXXknlI4SKr1p5cnLzAwNTSCbi7s7NDYnftAIZVxp4+M9CNXQQCsaOVmoCtRgg42xPd8ud3GIAZfBcbIlGde/TVdC/MJLvGpCZ9EBU5F2BpGVjSh3RMxuuI1YOXOIvx9bgKgPaV3wK2PjzaFHqeafJRZjUzA9k4k7XzO7Db/oti9PcmNZlDcOnlXPtmES5D4EvrRa+iWq52V4UnpKOZ7/BjAXc6q7kJ8GQMoLTLxUhpEDB3EzBDPqViBdePfX8DwdF/iIKeV0KwQ6GbRWyLm7s6d6nBwN0WG3p48Rs7wmtd3g7kgJR0LbUo6SxACCyrrnlw2xN8aHN/bc/tSKvZJ8BTTjCYsv7JsJB6oCp7FC86f+BMYdE3axgHOp2PsIaQXfMW1TlDqM0cwv9z2b3WVwI5POKt4dyuk6jNOA5PIKLr+27UXi51daBLosgyDje3Gsh1HkwAACAASURBVBl84Ahwb3DhnAPBd6fVEHALKrMF3UtKmHJ8Dh2CDtlKT0vj+ZF2y+jSJTlVXgYFNUTdvdCxaiXn+NpRWDwXNDeVOV7MrKsxrVIMq67bgOg1Fem+aykXW5Bx7grKc06jIucMJDoCNzWBxXi0bDINAxyQUwa6wwI0Mlyj6V38ISaC3R0T+5zp4XXx7oXleNqV87g3k7HeDNanWbz4qwDXzP6Qgh5XRan6kqPcLelfM5zcfhOoDgqQY/IsJi62P7rhmy1qMk9CSD+1mSdS3KUftVEC87QR+Rzo4KQbB3CnBRfUOSP9uNv1DP7RycPsX6VxmeGmIHc8XmM9Gc7h6FbdEVGWlUmNVnci1G/soKSr7exPCo12nh0U9L4JU6Tj0VdCAhViNInmkqIxzWJCJqwAZiOm0dFqx0R0KExn5MZ0inqMw9IyMK0qPPoqhEjHk+YG6cOhdcQMmnh69LWkO0+kIucn6GzhG02nov1PsA1a4XPDwofEgyQnSjDUIGPXQMSz4PaYTW96P0q72CbGzkAxAVcHtGBn5KZZ/2Lu1X4uM2M7gIaUuP0SS7PduXhcmfgC3yVU2+b3vhGC82CeOKEA9kgghM/YxN+iJr0NJH0LulLY43zAXoxaWKVz0j6L7cebrM3zcdlSg+9OdRBwg3lSa/tKSnC9RQ+Av8q2RIo2tw2puFb8t9lLkXKCIRHprlPwRakn8tpZTH8jgDfjNMo6n4eUEoeZQXZNJ4ozNqGJDMZ/Y1DeXnDdiVXc+Dbs6tMVb5RQ2DNkPfuO0RCDp9n+7QEufAQ+/hP0PR2caYy33Iy3gr3rX82F1S+x2R2ZLCrpCvcEIlX4Vz2TSiy6oLFXWGzO1tktcrBkFT8MXou7l4N7XG6eudhDh6oA/v7pjFp4gJr0/tQkEAzRVFiJXYLUBur6irFkNb70vmDmoQetY4RIo3fJR6wbU8SgdZ1xaO3DI49jKn/Am3Up3nYD2TDgGWakt8PtcNAn00UfYATQ3nKwfmgxo9Y9xoYeCYKlNMK+9scSiFK9TFhsUdbpPFx6Bem+PeT1GI9hFWPJKoygUJAEGDJsF2NyssJzSTiDDcrI68OuEk6RrnAv9Edh4q14Eqd5Apm1iyjueBbFcYPQ6vb5iOqOdcoYMPeiiSxMWU1xx7E4Ol9IwNyHX98Sk66HL52i9IYt3xJhibQ6q9izrBxkul2ftYEvSXcOo4NnHyDpUPEFub2n4UtgOACgaxp7e9+AJuz1KyH3IFL6kPgAkzT3QDw+e79pHaA2sAyXozc3OapwWHBG+7EQWApYZPicOMol3kyY7fDyhSPAU4FsZjt9LNN0jpOOsKFAQ+zvPpWawPKI2i5qMnhjjxF869jAxWZkQea3mo6xM8B1K0zWnOzA5+6GJ7C03vwrrC31HkvEjFkBZl7twmHCXIefyh43Y1il4WU2kz8wkVo6Dxxfw7BK+wGd/n1woeMEu/GVSOY4/Mxx+BltufifBCv+GyMZp5sRogRwKFxt2DNvywurlBUMbufxWLIWl9aTThWzqex0c9h1BUBVzvlUZp2I//+3d97hcRVno//NadvVJatbLrg3jI0LtsEYsDEGh9BMNaQACamE5Eu+3C/JTbuJU4AvH/cGk0AAE0qITegkNCcQMN1gMDbulrtlS1bfNvePc7ZqJa3klbQW5/c8++zunPaeOXPmnXnnnXcCHxAMH0RXqzhU/BmCYfMlqjh8BkMOBRD8mx1VN9MaN7iqKLncUuqjxK/ArC/HFEMkTpNQYrM7I7gLYOz5fP/jNRQiaEBGJxABMOcbuF+5Dbfl6DhCqlSj8NeAm4BeSdFJm/lsyIGOYF6ei3UFAX4d8PDy4afIU318XDwKIQwEDsJd9JrSJRBKXHDHHfbhatvFjaWF/GxOPRPen4aUYSQC/cJP4IlnyDtWxIhJcJrm7NBwWRp28OfJbWwYpzD9JRdStqIpJYTksZR2+2RipgCTPWXLaVLqMLwTcAbGdRjcBsgxYKpTRZlxY8fZqYbbfCaRqKUWI6TKf52vULl3M7uqdC56Yh9YkU41pRSHNg73kLs5lEIxAKYtHzP/dLU85RjMlsrXqa67mjY9xxpr6thqTYVXG0KzP3Fs6Y2zX+eih94ipHoIqW5crfcikDw3X+NAieDKv/yZXVVfpXT/Q+wvXUZYttDij5mJmv2voqsVKQfbheKkVX0GKEpID4T2EAoKLnjazy73y9H0Ce8MYUTdQb51xTGCCjjb4CvOWFnsavShCclLip8lYYOw9HdZJr5wb4Crr2nAg8LvAj5uU5s5f7t59qnrw2wojSkFJdzKiLqP+aT45GhawrmFjkcZAeoQmv1Jnj8W+0qv5PJHH8DdBuvHh1CSerx7h5xPwDGK5Q/eimJ5XIUUN23OSgJ+P1tFiHvVVjYpIdwtkvWqn8scAX4c8CCA3SLMAqsBeZAwClCEgkTyghJgRljDiWCN2k4o3MDxLNULwP71UDjy+M7RDVmrGIbue4YjxUvIOfIyOyc0MfaNFewY+o1od32vcQTiuu6B0G5a9eJo6d3rbEPKIJM2VLM1L9HjprrhDSqSh5QcPqicDsPmmVPbUyEUJlkzOSuAcaG47KuaafY04mI66QiKD5uL6ywIxUw3y0JOllmzlO+7TMfR3sbUt8ajKj7c7YdoNEYm9JCSKQ5VEFTzOEqKIH5JeIwzAajZbS5FWYTCV4WT7TtX4NeL0ILHOFvm8myoEb19N6NE5wv43O73co/WhteYCSjkNvwbJdTCHl9h1FyRLkfl+xCyKiltYrT1BqCG22nP301RdTutk6+HSZelDltw9RrTKyYp8Npd4Vx+VdnCDSGd12q2kn/oMtqDm/CGdNxt73BhOdyxJbZ/ZxVrRCkcqNhB1f4z8Ye2USBH4ZuyidZX72Pk9jDvTVDxNlxHa9zzEjKA23EWkjACnZA8jCMYxn3kdZq9sVg/qnCxMuzlWXEIh7+R+y7TaXPGWuQ3Bl3ce3ELFz++gjVLdC586mE0fx3bypckOAJ05oFVnt/IJ/puctumdRhnWfS8SovrHCAWzr3NKKA+dyZa4G0++2SQ3GOS2jLB21NUlj4T5O5LJF7dG30HWpFomOX8D1orrykBhgfUlGMi8TT4JuFo/4jCQyGur2pk0fMhhhzUaciZgt8oAmLK83CFn5fPUVm4djpC6LQkOSP49FkcKLyL6e/52V51A6AQls0J789hPmZImxmttrD+ixwl0QPwqKgFfy3bK6+nav9DHMuZht8ox2+UcPjQbv633oQalFz7UAA9IJBC5+ELJT/wxUxUK2nlyqAzGnxyccigSqrcLVq4y4i1/mel8D5MSV1H775oT+HJm/tcMaTlNyWEWCSE2CSE2CKE+G6K7fOEEO8IIYJCiIuTti0XQnxifZanK9jrM5oo2/cAb5+8lfJqBxtOEtTs7HoJv/gCKWU7EGJHQcxDJUeWMKpuB/VDktzPrngYlv0ZNAPO+QnklKe+gKugY9qsm6xtebCw44pjK5cbrFze+WDvFMPA7VEorX+PvGOPUHJwDeV1sRaTxzgdl35q9H9VM7wx6SnK963CoY3p9LwRvC0baSq8iyZviEaPgMKR6F6FJ8/RaHfU8cpMs4UUcTFXVWGGPPh8x5DYpah8L+jB1fIbanauQA2+yhtTP2DYkVghdumxlp2qpLdKXMRtNMKh6k18farO0rmXM3TBDWZAMlWH6pkdDzY6duk9CH4U9DA/bDCs0kFBy348xixK69ZSeOQFdFXBY8zCrU/D51iAQx3d8bwWLa5D3Dg8THnDJnyOBQw5/ATXhpy8OE9j5XKDN6YqVB58Gp8jNmtWU/LIOfbfhJQ7qPf9hsqDz5Nf/wDhIR4rj6aiKnm4VHNBnEcv0Flznsbpeszm9Sd/DvPDBt/TvNx/mcEkt4GrbSd6uImqus4GwVVK23Mpa88nRzuVvII9DB3npvpwxwlZOQ1OZFKwvLBs4kjuNJat8eJor6C24nrK9+ssfcbU2iO2hvmZ3sxmEeQlxc+1xjG+b9nvW0NhyvaH2ayEorHFOqPWo/GZJ0MsfDFI0f4QxXWV7Kr+Bkfzz6DBVZl4R0aAXx/QKT/4JEMOPZe4TSkG/53Ujg/Q4gpQtfcBqvfcw/Dd9yGEM2Hfw/lzaXGPoqELM1RLYB21ZVfT5J1CiyZobH+R/Q1+xm4KMWddCClK2V59E1srruDSx1RmvRGkYm9ssulfwq1c+ZcAyx/0s7atnUeaWvj8qgCnrQtStj/MWS/HWj8Hw2HeEgE6rBwfCTe/tZtxvLotXW8/TrrtMQghVOAO4GygFnhTCPG4lPKjuN12AdcCtyQdWwD8EJiGaZx42zq22+bl5pNUNp+kclPQRZVUeWR2kDdmSWY+byBl+nHLIz7hh6s/YuIbb/PiHJX6oRrXxveLfaWpD46gWYXM09ENjkmXmp8IN6xNiN54U9CVMNM0mW8G3QSQ/Ne0j3AVaTQ0SM5au5lIQJyhtf+XVtcw9hfMQcoAL85bxcV5Xu66uoVLHvuAnd5YCzOfsTSr7VY8IJOiQ09SOdrF/3zW3O8z3iFU1H3CySUuHrzI8hr3w0sLNEq3hZjsEHDS2V1Ouf/b4tg1Z4Z1nszby9g3ylGEh8Ija6n15aAID1XHDrEvbyLtwTQXjQEai1vZNF6gX/Uc6HG9ui90PqsWwxuL1ukdkrD0ZlmOzhuV/2TSR+8Q1Op5+myNBYAi3FEzriOwH2nMotnfsQKdPeog1ZqPl3M+YOjOD3j+dJWFuFjlz2G3CFMlFb5z+kGW/H1FdOxlX/kuzhhtBn+oFWGeL9nHnjLBGbVefDtnogXr0fRTUKmHuTfTuO6HNPoEn/O7cCCYENai3nGjpRYdP3kBs8J9YlEtk9aNi06MAxCynYNVH3E0BHPeCVNw5Hnmza+GYAs/PeUIJTvGJEy83FY0Cplizk2z/zVajXwOFS7CH9rBzqqvUXbgIZRwK5M+dBFS9vFf40058uslh4wgaOBY3875H4ZZfV4LkaaYEG7c+jRaAq8hZQBDG4E/aLpXO9tzCGiC8587yvbqi2jxv05YtpJssLopt5mCAg+/Pns/Fz0ZhFwzj93GaVTV3sNrZwe4PZTLjec2MGpLA5tOUvDrMPeVUQnOGwcczXh9iwl3MXZh3v8riQP2Wz5i2sZKtOAxasuvijpe7Kj4PGM++TOjt6go4Ta0UBPvj1OQYgwt7mKmbFjHmM2CPeXXMHzH84zZfAgI85EVyPYbSishPciUsMYlIQcblBCLQwZG/NjCY19ODL3RCWEk+9NZV6QHpGNKOhXYIqXcBiCEeAhYCkQVg5Ryh7UtWbqFwD+klEes7f8AFgGdx9e1+J3fR0lch+YHQQ8/0ZvxhvNpFAdw6VNpC34QDdnQHZ+MDfHJWLPlXqC5oCdrd/Q0LskFvwN3ITz3PeZFAoZdeKc5cJpiNSkdwZXlPoZJle3FIX56eTNnv2QqFzX8Nt7mjXh8U/EbxRwuUjjDrzOJHP6WuwGf8nWC1ONpr+fZsx5m/t8nExkPz2E46ye9x+IqB9EbduWhILgm5GReWCff8siqK1TYXiS4zi9i97vkVnjymx3kfdifSwBzAXovgo88Bq8b5lKrbv+7aMpIDDWP/cUbMMKL0JVymlJMoEuFZij8MOBJVArdYrW6VAMW/AD+dlN0y7ywzp+nqLx9cgtgMNZyPY6n3ZDU7FrJtsrltAU/QhU5US+x0Zo5RKqUaIi9AY4UCCibjL5vPcMtv/fFxR7uuqaFuc9pBESQXHeI8Za5ZayEeaU61+nHaA8HcQIiMntXhGDcUr7zyi9ptEalrwwltnTjaXPAexNUfuXM4YmQi2PaUPwhs3z5fRrXjMrlDq2V+8aEcLbB2Rf/ER66gt2VIWr2mKEf2oM78Ie2dvne1OYNJxx8GymDtAbb2DvkYqRsozX4Pqe+c4gd1WF8TZIlfw8SUuCuK1opPeChrmAGRXUxO3/VsaNoob9xoGQpwfBB8ps3st9hlq3tQ87CoQ3H8O+nNbihQy9DET40pYjCvJ0IAbf58vjiZQ3Mfc2cmTds16384wyNzxR50cOCJq/gnSkqI6TKESRFxzZzyDcxoTca6DB3SCWVf3W8WXR/AzTlFaEqJxGKG5toCbzOzrKLEBgIoTO09i5O2lbEvpKzCYT2Urp/Oo1eP02iHn/JZwHNnFVujZNettrN38+qZ31hgPes2PxtyKiJGUhLKQD8TfXzkNpzZ4iuSMeUVAHEj2TWWmnpkNaxQojrhRBvCSGiBriSJNEmWC0nXyCI1ziTyv1PkCcmRLe79JinjMc4A0Md3qlQI4TDNPuc/h9p3kYPFUPZJMitgEvvi6WVjIGCYWbFFWFoLBbTRKnhRTDRuk8hNIQwzRXrTlEp2/8AQ3fdxi1BNwJBIQovnaVTcuhWRu6+By30GD/Hx7EiN7pagdc4g8qDT/LmVJWqpXHubHEeDTVSJdfK54hGT7jTiqlmZQumF1Cc7DpmQDSBiFaCAM+cbeDSJ+IULtZPMHt2eqger3E6hlqTkE2l/kTTnKGNYrbalHr9gHS4eg2UTkhIUhCsDOTwnwHTjKMB1MyhYs+dFNY9A4Aj3MQ9V0jKD7+A1ziNkrZYpVmWY76oOyZoPPhZnZBPgSW3JVzj7LDBbQGfGeoDOF3qcNEfzfwDHAg8UrA53xyAl5GxIasddYrUOSPc9dwSgPuWGbw/wXxmQj5FSdxyrxM9exktNW4LePkNOXzd5TUbIktu5VY1h5qdKxi681cUtCV21nXRMbZ/KHw0GnoiFG6g2f8vWgJvImU7n5Sdw7LVQc59XuNw4bm0O0aw8UAbIfUc6txDOGV9lZnPYT+5zRtwt20jp/kjDLWCtmExzzt/aDuN7S/QIA4RCh/pIINbn4ZDG45QBVScgoGgzSmo3Hs3lXvvYeVyg+1DFUqT1u7+WcDDzwMedlRtRVdL8Brzotvag5uiv53aBFz6FDzGfBzauE7zvKnFHc2TZMyFotbR7H+FXZU3cih/Fs3+V/GHtrPfpXEoZxT+0A6a/P+kOfBvmuI8CLfnD+WzTwWZ+WYIlxUfrr2Xg9Lrwn5GbM9sjyEdxZCqVkz3DtI6Vkq5Uko5TUo5LcX+CfiOvcCQQ6tZO/cwlXtjMzBLD/4dTS3HoY2nsnYlRc0Ho3bGQr+THwQ8fCfg5qcBD19RS6FmDow5zvjovWFkJxEcu2D9hJiH1PSwbppLgP/xe1l1mTmG8dp5DqqlSpVw4NTGUFD/T9YsCTI1rOHLH9btNSKh/zuGvbYe1+TLu5Xd1/gOIjonJMwPQxpDd/6Kij13oQCqYioCXziX4cea2VX5IkKYL57bmIlDrcKbiWmmS+/okDRCqnik4OKQA07/DnqwAV/TBxTWPUtO63P8UHp56uzd1OxcQX1OpHcTy3cpBI0+wTeC7pSLsJSiomumSdJpAEUjISfWBvpFwMuXp8/ntVNu5d0JZmfbHfigw3nS5fnTgxwojs31yPOZPUIFQQkKE6QGuhsMD/ko/GmZzl/PV1GDscFbnyxj87h1eIxZHc7fGYHQXmrLv8juqq9R765gX9EiFr2gcVQ5RHvwY/YWzjZ31Kp49AKdFhcU1j3PkAMPU53fUQGkmr8DIOLDRiz5LYw9n/8IuPnbuc08ubCJbwbd/DLgpUYmeg8KBAUoTDPqqdm5gppdt5HM2H3vMKT+PUrr/knRkX9QevQ9HFrHcSZdrcKlT0+SK3UBbfKvpUHG7P5h2UhbMDaeIWVbB0+tZvdoJmwUXP1IAE+zTB1yPo5VahuXGQ2s0JoJI2lHmut0vOGPrimfKdJRDLVAVdz/Ssy56enQy2M71zuvX6Lz6oydfLk0h6fOjrUsHaEGXNpYvCGF589s5ZMRr+BWalCVHD6YuIHxUuMUqXOS1HCmG6vkgt+Z30t+G0s75Vo456dw3m9gyhXpnSeZSIUhBCx/HOZ+q9NdI/blVZfoPHShZdt35sD0L5CLwsP+XP7sz+F2KyS5tArXjio4ki/4j6AHFI3rgy6+GHTB9C8kXqB0AoxaSEXYzBOtbHLi9vNvh3FLzcFfgHNXpJSzZucKCo88Hw38p4YbrfBzkmM5AilAU/Jx6zNwSQ+elo8pzNcYXl+Lz7EAVZgtel3rRcvnPLPiiC4sUzrBHCdRdfN5AV4EdwdyGCM1cMZm3vqa3keV7YyWGtf5PDxzjYsRp/nwGHPwRqLrjl3CCKsCyuvi5XUqRfgcC9Cnm1GBmXUTjJgPQCEKo33VNPoEYbWVmp0rcAe7MBXUzDGf1enfSbn5Ni2HQzOdKFa+iSoVFv0fc+OwuWbvyXBDwQgA7hd5HClQePxcPw7N9Gh58cy/85sSN+UH1pCnTMVQqzuXJ4768Nu0BTdaLebX2Vl5Y9QUFKkM631bWOpz8fI5OoIQrrad5CgKRbJzbxpNKYn9DjYgZFz043m3MFXqHClQOFSkMDKsJiiFHwU8nB2yel1xDZiPR4no/UZ4arFKTtN6dlZvJqdpPTnNH+BNirxpaCMZtv9lanb/ASPu+KL2w+hqFceLIjwcKl7KnorPEVQ9XPlogI27WhOWbj1MmBcUs9d9lXGMJ9R2RFjyLgFWqm1cYxzjG3oTI7e7qCvoeYOzS/nS2OdN4CQhxDAhhAEsAx5P8/zPAecIIfKFEPnAOVZa+iz4QSwefH4NP8TLN8tyqZEqe8pj4j97ZiOFdc+R0/AgM0tdfHlUHqVH1pEjRnL9kF6aJsommYPJJXGhnaddZ754ldNgxg29O+/MuPV1nbkw7gJzAZQ4qnfdRrXV2vlMyEGLW3Asx6qURi+GqVfDwp8DxGajXnIPufJNXK3baHN8yB1+K+qYUFkQNjgrbJgD6DesjX2W3gHz/5P/UEr4fsCD0zpnlCHjYe7NsXGH6hlmRXzRH83jy09O2D2g11F0+CkKm2JrNmsSSvevQg/UoSpeGnLhr+draFU6703YRfWu35JXb3azDbUXC7eXjIF5tySOBZ35v8wB6ylXJpjsKBrV8XiLGWGdXwe8LAgbKMKBEJYynPdtlhVO5RcBbyyezvgLze/rnul4Is06TnfBWT9K6eGVkvhzLfyZ+YzHnGeaPC83A9dNDGsw/fPkovCjoAe3Ph2PMRdx6hdh6GzIHwpCNed4QMJ8nIf9udwtcslva8TnWMCd5KAheOasAxzN+yP5fomqpHCwSEH8/I7kGd9SwKZx+xgmVRpyFR5brHE0V+DI0yg78HDK8xW1hamq34pDG4VXn0XFnpVU7+rohbjQqvzdSQp6rNT4QshqzZ/+XaS1sE+1rlHYUodDG4OuVlIYEpxU5GDlNTpHpjv5xxkaT56jUb7vfhwiNt+jsu5NVi1r5u7lCmUNm3Hpp+DST2bTmAM4tc7LULqEZTPN/jdoFa3sKL8ciUrJoTC/0FvYba05/nOliQfaW1ijthNAIsKSqx8J8IX7A7wWaGfIwTDH2kLsrvgSh12p5+X0lm4VgzSNjV/BrNA3Ao9IKT8UQvxYCHEBgBBiuhCiFrgEuFMI8aF17BHgJ5jK5U3gx5GB6K4QQjNbphMvhuHzocjyczjt6ygIhlhiD41rMUgFfE3rcQX9XBJyko/Cm6dsx9f4B6qyLZhhqpmLkV6D7obLVqFIP4rlfXV58oBkpFJKLgx5NWg0M+Tgo0yzZmADHSfrpcBHbI5Gt1SeYppKwBxkj0NIibf5Q0TcJVXA4T9IzjHTzVISpq5AIReFDeNUFBkkr+FVanauQFPTcyZIG82ART+HC615EFZvcfUSjbcnm0JKtfvZvKoQDIs3W8z5hqkYDTecfxss+gVK2PSMUrXOexW/DXi5urMB5hSut4Bp8swp4/d+H/8RdMOUWDhmIVQUYTDMHe9Z13mP25xb8zQ1O1fgtSrXL+R62TbNoOTQY1Qd24dLnxodo3N2YX/vCn9OOzqCkICDxQp/+YyOMW4hK5cbqErHSuztSRtYe1orhlqFEWpCIBEp7mN5yMmdfl8HxZBM80jz+dZP1Ck88jxl9Rsobm3C536Pz4QcIATnhs1xir1lCutOUSlqfQufYwHF8iSeXFhLSBMsCznJaXyXmr0PMmL33bQ5G6nafXuXrtg+JZZnuuWS7NRPxm3MxmM5aUDM3NQaeJed5Vcx5KCbOa8H+XFrI7tFiHGvBbjy0QBPN7dy/b1+vnh/ACmG0uwexcWPB1j6TJCrHwkQCO/BH9reQY7jIa0qU0r5tJRylJRyhJTyZ1baD6SUj1u/35RSVkopPVLKQinl+Lhj75ZSjrQ+aYUUdKonmS3T2V817bnz/9Ns2VqDeRFWBGKThY7mmQXlpXmxyu2S6hx2LHVjFCQNRPfDlPK06MzbKS+uq3qlGfbhdr+XXwa85nyJyHHFcfMYKk4x88ptdcfjTy26Vwy9JzEvPxe0Wm1CIBZ9G4CPJkdCsiUu7lkiFf7sz+GT4f2guSOLyliK4XChQm15JGAipnkwCS0Yv65GFxVR+ckwdBb5jU9QdPgJnJ7Oy1eFVKMBG3tKPooZRiLFGEexI2Ie6/7ca87T+NfMWJmYInVuD3hZO1tFDX5A9f41VNeZlaQnpOI1Tsetz8CdZG9PxtBGoipF5DKW64JOhkkloXRouRX8we8jt920tQsRe1fLC1VanYdxtm2n4OhTnV5DRXS5BnwEWTaWt6eoSE3w2nQVX9N6Co+8QFOVSpVUWeXPYUZceI/1E1TWLDlG8aFfUXrgIWbpOmeEDJZUnck/Z6nsLW3mgUtUxnsN1HA7BW1mzzYv6MSlx1Z6zJWVOAIx+YcefoPi8HBKjt7N8J2/Y9jOjmMeAAEFlPB0io4s4cKnirhFb6K81iyzy9YEqCs4i/rcmewpPoe9BacS1KZEF/lqD25Oec7jIdva0gAoyWu16q6Yt8ms1GupflvxsnK5gbss9rAnSo2bg27Er7NT/AAAHnFJREFUxEv6StTumXEjVCcN7pWfDJ4iOPnquETrFUpWFl6zoi8lYlON264ocPHd4CmOrcOrp2h1pqhIOpIZZem2Kj2JhJIaVi432DVcBQnulk/QgkeoCL3FDwMeZlXMQUXw0lzT1ADW7ffFsoWRxkDc+FJC3KJhc+Gq1aCYlVXV7tsp3/vHHl1CJYC3eWN6i90cL9YAe27DqzjbEsONdNfwOVSksHG09Y5ZPVUFwaaTVB64VOefs+t5a4o5mClFgGG7fsuxvDup2r86YVXDZAqPvkNZcyP+IY+yKOxAzP0Wk63B2muCToYXjMWHwv5i023UkGbPSQiDS1xu5kuF0gN/ASW2tkKn43iGN3V6hKrYZMjCUU7+slTnT8t06oZp4MqLxmm6OejmJ5bHWkgVrLlY5/5Ldc7XnHwp5ELPH8bHo1SePUvjN1oOw3w69y7TOVDegseYjd8rGV57L8Ma2xnRUE/tmGfYMS9mDn1uwX42j1iNd6mPP12hc9dynZJAx95GW3ADRzyVHFD3sKVwBKUHwkhRycHiz3DMdzIHnRr7PAW0Bt6hLbiRvTlVNPn/GQ1KmWmyUjH4GjtZOg9M89LnY4tiu/SpeIzZMXdL7xC4/uXEY0YnhkzIVCWYFlMuh3N/kZjmzIGr/grFcZ4QKSqulFTNSPxfOAKuejQ6+U7GNYJ7Rw+PTKqEIpWtFCKWzZoTgUANt1K55w9oHGWc1BI8T6KVdF/VqZFVx1KdP5LmKTRt+Uv/BzXcjiIz6+mRUUonwHXPkF//KqUHHup8v3gl9TlzMZ3rgk5Ghy3FMGpRdHOOFBSjckalh0q3acv362FWLjfIm+zi/fF1lB94FBEXGt9rnBH97QocJr/h31ww2uo15lbxVZnL7X4f54Ud0edd6XYihIFm+MzZ5IEiaqTKDCvETDAuhETKcbwb1prjSl0g4+47pJgWBb9DkCsFnGqdc/S5zAjrjJIa1wSd/DTg4XeBHL6ke2JmWMye7XCpUoCC2/DS7hC06x9SdPQVctxv84drFP588WZWXbqbW8pz+Eac0ropz8es4R7OCRsEDHOO0NtTEtePiNBuxekKy1YueDbIgSGX0OIexeH8eQTDhxLWcAmE9qY9h6s3ZGWsJK2rKfVCmP7Zy5+Ae89Hs+yV46TKyWGNq93DzH0cPnOJvGFzu69ss4I0ldW8W7rcHMhzogNhTz/dc8Ew2Ar/mqmyv0Tha1ZZDRoiGixMIGj0gDfyWJMq5xlhHRFZW1oApZMyL2dU8cZ6o/VWL2XH+Dibv7fY/CTTE4XVXXnzmtv3jeh87ZG0SDUm0VVvRXfBDWtZdOfpLAo7zLhgmmE2pNoauOu+pdFdPxZHedN/AGfoZWaEdS4OOXixNIzzvb2UtY1ir6Mdl34yNbt+y4ZS08S75nxJi0fnj4FYHusISpPan07hxGvMxa1uoHjbr/j4JAEUIq2FtgJGGpldONJcLzkV8Q2OMUsIb3oCMAfurwg5o+7e5A2N7ndeOPYsZiRFkP2dWgltpllxqmMIy5oaEXkBfI3v0lLo4mG/lzASP+Ak0vN1ACHGSM30hAN+HPAggbXuY3S3Jtz26puRBGlu73qmNpDgNZUpsk4xCARSSUMTOhMn5ugIvhv0gGq9LJfdbz7M/JqOx2bLGEM8STLtLRXoqbKhm4HSI1NKeSv0EXNLVDj3t+aYRC+unzZTroLyk9n4jGkWE36FdVNV5IQ8IpNSBPDEYoPZrwUYWhsmuZa9OehmtacNGkOI074Ep1zUO1m6IjrGYF57YljjA2eQlcsNRhpdVNCXrep8WxLp9nqES+EPV+mMdGVkbbBEpn+x80HsZM75iSWQ6FBOVCVA+b57aSlWuDlo9kaDRSr3XKFz2ZqXqQlMRA+s4rGrDEZa0Ur8RgCEwO0pgWZzVbiEciUUuGo14e+b4dYUtZ1Vl2q0OeArQSBk7ut3CZ46W0MJQ6dOmNO/CDVzTa++ui3w/I/ihNeYlj+WVcCcwknsFi/yKvUsDzkxFvzQdJ644HcwZELq4IzJLH8ctv8TcitR6rZx4Ys/YU0FPHRhkPkeDUKmKS7epcCjR0xuVniayZczer0Z8GGPT2efHEGbowI91MLRUEcF19RJpNhkKpoC1Bf8hcL6nofC74rsUwxKM3vmH3/YaVz5Hb12sprEMYYnF5oKYFlPz6JguvGGhOnXXzgigzKmQFGgdGL0rxCC9RNVRrvUuB4DNHsEO6oFQ2tJWXG+eboO+wVfGjYpNh8hkySZ6v5X0MNmEeS/9K4DvsUcAbpvxQYMYS7Dk0YPNayKBHNHxqjpfAygJ4RTtBOmh3X+qrez6lKD0gMbOVwg+FMol7+1atTnTOZOuQuHX6J4PKZiSHV/nkI0zNa3R+zhp5qPkqACU65E4V7enahycIKTPUZ7x2PjUbXYuGNeVaJiAMpcheYcIE8ZwytOY/qOf5meTBEzT1kXvdKItQFi9zDMmkFdbwZyKJSm+3hRMOlZz/s21O9E/FvErrPvfTj1erAUwzxp8OXZa/C0SIIaTHr/iykXHOogljaWIfUfcCh/pmVWkqxZ+jTVqoOj67uOaNtTsk4xNHoFWlll9zt2Shb2BtIh3TGG7k8EgCJjvwcCiUSxTAge656SF6mJl8/vENTWdDf383gESvRKSrx6GldNoxJ/bYEb75YQo0tSROE9kVj+BPLpO+D5+2NpN6xl2J2nR+NkrS5qZ4G12M5Lc9/G1/Q2XpEPxMXaSs5XK90lPqFiz13oI5uplLHJhlII3pyqUq0oXS/+0Au6c2+NcsNaCIfhrvkRoVPuNjes4wsIJo9YDFuseSqqASedY5rnfv8nM+2cn0HIn+AAoiO4y5kHTvAjeWnvA2wpPaPT8OkRavY9wdaaRkZv20hI9QBhvhzORYQFa6p7Mf+nC7LO+F6Iwud8Y7vf8bjIZuVxfFVjgjVDZvjtSoN46UtdRSwPOvmWVm7Ogu7rAeauSKEYIqQSZ/USMzZST2jzKHwwXu0frySLuvw+uJYzB5xmbzvBs9aaP6MjuCzkNAdoL/gdP/flcktZ3DrO3TRuFF8levAo5CZGNY6Es0u5fOhA0cmzFAhOljpKbgWMXWImXvGwqRTiceaYHoidYCB47OI2Ctqa0dVy3PqMlPvp6lBevrydf83R+MM18NjiJlYvaUFYeRXMzWxVnnU9hlwpcCvpi+Vo34OrdVv3O8ZzAowx9Po08UpvAO8zcuXFYQcIDQkcLDILcUNlZHBSxO3f525JPTr/4cLkF6374+LvJh0ycadrzovY4jP8rJPGZIDYoG28qaVsUjQQY4yIa1xyj8Haz7JTSW8hLLoJyibDu6uiaxOomVasmTxf8rlk2DQfzft2QnLR4Scw8+Hajue47hl4+tsw71ugufh/Dy7jLs8rlNVPIqzUI32TaQ2sj+7ucywgt+E1rg15+QttXBly8nefn3xiPatLuojK2xuyrscA9KhCK9v/AHkNXbi3njB0Mo+hp2eRMbt+r3pGGXqJUimoukKFP16lU1/VccJdtNruq9Z2xTQzvEQKr65MXbGnuZ2JqjysCoJ6H+TZELPHsPukuGcVcflNDqY45rzE8bwEU1L8XVoeO8FImHTFDONhjSlFnIN71k/rhONqFHWUOb19Y3ibN+Jt/ijlNgw3fOYOKBgOOWVw7goWnubmtXPfRw2+wojdsXnAha1N1Oxcwfbqf+NBcG3IhY7gvLCD2WEdJl7SZay13pJ1PQYUDaZeM9BS9D8yMy3mbDIlpVIyIVUgQh3TY3L3kWJQtQ4B6Xo0xtAj0jxfFllMOuDzsHK5waiwGquxI2U0eXJZJF8jC1RFegadKflIj0FJ3N4npqQOMmS6Z5WB81XPoBqNXyk5/GZxEzsbA4x5fxj+0HYOlubw5myNmkIj1dIR5gRaVTODLt6YXpyrdMg+xVA4otvJK12S1oPKQlNShAwNPpuKof/vM/Iayl5eeyDqymyunweKeI+yWGK6DY2uc9Sf78ABBAvjvM+kJGRdUxsoRR0nS+zQ5GP7trR8TfXQkidZe3QD+wvn0+5aQ02Rg6uDcaai074GE5Jcut2ZdXjITlNSX5OVYwyZad0nmHB6pQCPr+AnViSx60+RXS9E0+empC6umRb9KFc2kLIHFymj3QVljDclJVSy5lfD+HxWn6fRNrok4bDItB01m6ulvioHn3sWJl+OjiAXhccXbcURvJMpY1q4OeimOD5P+jT2mUkWP4FeUj4ldXp8SzzVovIDTWRS0tAUi6Z04dWQzIV5EzglrDE/bJgxlNKlZo753YOB/3jGhjVuCroosyKQLnGUxTYKwbfCOVwYMieSiUjFEvccYivI9V8FHLlTTzovWoU1gSjVhMkeEnGdLBGWskzuJcbNC+lAZSdrWfnKUqdHiDxfSAwj3ykpegyRkOVFViiXobNTHxqR0V2YeF1r8FoKweEiJVEzl4yJhjQ/TekmDlIq4q/TUyLv1xBrXkT880gO0x7J50h56CKMe4/QXWY4/qvXQMEw7nDkcub8POaKFJMvM1AGuyP7TEk94aq/woPWxJNrHoNgO3hKUu+7/AmzxRNsz86Jbw4fXPloVLZTwzqtkTfn0vuhrT6tiV+5qpPvBD1mDJzcuPkg1z7Z9YGnf8echJPsbpcmPwrGZHvYnwtGor3TQFBkLcMo8ofBgt+YA2/Vs8DwMOeBhaymGZ/ei0qhl4yUKlcHnczzpTFvZspVZmVQeFK3u3ZQbopmLnjkK4Mx51F1aBO3PPtNJuRbC+NEyiZYC+x08pyvWm2Wk1R0NZHxqr+CIy5SwJLbIJDC7335E9EWcUJvarm1/ErNaWYsqZyy1LJcvQbaj0FuNYw5H3xD4IzvmsvCttVHy2PUTBXf+h5+BqWLfsmDz34XxeFjR8iBP7lPFydfBxb8EI7tiVXy+TVmnhcMh41mSAzGX9hRKV7zN3P+QbAtlu+KYuZZoDUx0jGY+XzFw6aSa9xv5kUK6vIFSrIRoLt3EEyT0CV/wvHULVTVvmnKF2g1wwAZHmg50uk1M8mJrRjiW9LdVfaO/qtwek1cjJ5vBePCGhju9MMcRPANSfzfWYUSQdVTxwjqKyKF25LzEr2UC1oO4dL7IExEJwgESyx32m5RFHPRoi5YouRxF03kG0nrKCtKYk9WdzFd6kSXDo0vm13Zij29HFxM7nHqTvOTTHyYmYgJyF2QsOJd9LmlksVdEJM/Uv5U3Vz/PLfjMvEdqnhfaXR5yytTuV86O65PHUUzzLhdERzejtaDssmJ9wKxUCDJ71dXvXSfNf+iiwr6rxeYvlUXxyd29w7Gc96vO8rYzTUzyYmtGGxOIOJ8gFI0+hQhcGXRMPB/BjxdLuOZirPUXM7yN4LWjU/5CTBekXLwOWPnxjp3J2fP5nkMnxIGhWLYWqN0HmzLZmBIMcA/3LIhTzHSHzMZKCanu5pdPANQAf1fv4+WjrFGjpu+nG4Y7lbp2BX5QHPCK4aVy02b+PUDLEf2MdAvV2rFcJ8/B4dzSIr9B5ATuEVZiEJhHzjZDXOXoQGfNUq73bendDt/pM+eRxZ6I2YpJ7xisEkmSwu/1YNwDLjCskkHr+biAX8u6Lnd79xLlBNYIQ92Bp+7qk32Y1cIn2oqNXMQttToO6Vjc3zYPQab7CIbJx/aZJQz3VUMC3gZ7qtJvUPGGw7W+eyylTa2YhhsnKiFf0B7ERm69oma9/2MECLqiNDJHpm+YGbPlwaLQ0bK0EYnCrZiGKwMtLnm01xJDnTenzB0UkYynX81c2DrS+Y60f3E8lD/zcfpC+wxhkHHAFfI5/0mjZ0GecX5aVaKx0OGIgx3YORZ8Pl/QP7QzJ53EJOWYhBCLBJCbBJCbBFCfDfFdocQ4mFr+zohRI2Vrgsh7hVCfCCE2CiE+F5mxbfpnAGqfLsLsDaYGZQ9hQG4p77Ix16Gevm00q1iEEKowB3AucA44HIhxLik3T4PHJVSjgRuBX5ppV8COKSUE4FTgBsiSsPm04bdirZJl8GoYE8s0ukxnApskVJuk1L6gYeApUn7LAXutX4/CiwQZoQsCXiEEBrgAvzAsYxIbpOaATdjxL/UvZFloOW3GTAGvOzaREhn8LkC2B33vxZIXrE6uo+UMiiEaAAKMZXEUmAf4Aa+KaU8crxCx/O9QFKschuTATdr9PQlH2h5+5MT6V77sLLuTBEMeNm1SUcxpHpKyU+0s31OxVyQrhzIB/4lhHheSrkt4WAhrseKalFdXZ2GSDGmyIysEGvTJ8Qv8tLVqlgwKHoKdos3PTqt+PsyQpNNT0inqV0LxAclrwT2draPZTbKBY4AVwDPSikDUsqDwKtAh5VGpJQrpZTTpJTTiov7MfTzoOZEfbn6Se5zV8DoxX1z7kHV4u3He7EVa9aQjmJ4EzhJCDFMCGEAy4DHk/Z5HFhu/b4YeFGai/7uAs4UJh5gJvBxZkS3sTkOqmfAuAv65tx2BddLrHwbVIr1xKRbxSClDAJfAZ4DNgKPSCk/FEL8WAgRebP+CBQKIbYANwMRl9Y7AC+wAVPB3COlfD/D92CTtXzKKki7Qjs++moeg02PSWvms5TyaeDppLQfxP1uw3RNTT6uKVW6zaeReCXR1Yvfj8rEbtkPMPbgc7Ziu/MMNrKlsuuxHANYGdgVUT9jDz5nO7ZiGKwMVGUXvW6WKKis5ETImwGQMVsaNTa2YrDJNJ0opE/DS/9puMc+xR58zhZsxTDosCunAceu2HpHRLEKu1oaaOwnMGjJgsrJU2K+5NO/MNCSdIKtRAeUDj0se4whW7AVw2Ajm8wZuhOufwlGzE//mAGRP8MVUTY9g2yksx6VnW9Zg60YBisDbc7osVPSIGglpn0PJ8C9DkglHTElDcClbRKwFYNNZhkMFbxNjP58nvYEt6zBVgw2/UQWmgky3Sq2TSGZwW5cDDi2Yhi02C9X2mS6IrIrtl5i9xiyBVsx2NjY9DN2xZ/t2Iph0DHQ5gx75vOgoj/NY7YpLmuwFYNN/9DtQj12K9LGnvmcLdiKYbBht7p6gT2PoVP61SspetH+u6ZNSmzFMFixW139j53nPcQOu52t2IrBxiZTDKaewoBgeyVlC7ZiGHScCJVTtrz4fZRXdou3d8iw+W3n34BjK4ZBy0CHxOhtpXsiKLZMkc33OpDrMdiKYaCxFcNgY6DNGXZrb5AxAM/TLkMDjq0YBisD/nJlc2vYJiuww25nLbZisMkwJ9BLPdC9q08rdtjtrMdWDDb9T7bpjkzLY1dwvcSe4JYt2Iph0HKCvlx2pfrpxR58zhpsxTDoyJKKtacV/GBqJQ6GexnIYjQY8u8EJy3FIIRYJITYJITYIoT4bortDiHEw9b2dUKImrhtk4QQrwkhPhRCfCCEcGZOfJus44R6qbNEiWYz/fo87R5DttCtYhBCqMAdwLnAOOByIcS4pN0+DxyVUo4EbgV+aR2rAauAG6WU44EzgEDGpLc5Qcm2Fz/b5Bns2IPP2U46PYZTgS1Sym1SSj/wELA0aZ+lwL3W70eBBUIIAZwDvC+lXA8gpayTUoYyI7pNSuyXy+aExR58zhbSUQwVwO64/7VWWsp9pJRBoAEoBEYBUgjxnBDiHSHEd45fZJu0sF8umxMNaSuGbEFLY59UTym5WdrZPhowB5gOtAAvCCHellK+kHCwENcD1wNUV1enIZJNp6iG+S0GyK8gcl3NSExXDQj5zd9KimKnOazj+7FSEKr5rRpd75cuWmT4rJt7UCLX1TNz3b5AsZ6j0gcydlZGlQw/D5tek45iqAWq4v5XAns72afWGlfIBY5Y6WullIcBhBBPA1OBBMUgpVwJrASYNm1az2wh874N+TU9OuSEYNEvYhVpT5h6jfk9Zklm5emO2V+FsilQOAJOWQ5jzk/c/tmVsOs1aDsGU6/uePzC/wOf/B18Zf0jL0DJOFOWcRd23Db/++At7tn5Fv4MNj8LuZVd71c8xnxO45Itsr3g/Nuhcf/xnyeZ0slw8lUw4aLMn7uzMlo9G6ZcCZMvg5FnQTiY+Wv3Fwt/HgsKeAIiZDc2aaui3wwsAPYAbwJXSCk/jNvnJmCilPJGIcQy4LNSykuFEPmYSmAO4AeeBW6VUj7V2fWmTZsm33rrreO8LRsbG5tPF5Y1ZlomztVtj0FKGRRCfAV4DlCBu6WUHwohfgy8JaV8HPgjcL8QYgtmT2GZdexRIcRvMZWJBJ7uSinY2NjY2Aw83fYY+hu7x2BjY2PTczLZY7BnPtvY2NjYJGArBhsbGxubBGzFYGNjY2OTgK0YbGxsbGwSsBWDjY2NjU0CtmKwsbGxsUkg69xVhRCNwKaBlqMbioDDAy1EN9gyZgZbxsxgy5gZupJxqJSyh9P1U5NOSIz+ZlOmfHH7CiHEW7aMx48tY2awZcwMtowxbFOSjY2NjU0CtmKwsbGxsUkgGxXDyoEWIA1sGTODLWNmsGXMDLaMFlk3+GxjY2NjM7BkY4/BxsbGxmYgkVJmzQdYhOmqugX4bj9crwp4CdgIfAh83UovAP4BfGJ951vpAvhvS773galx51pu7f8JsDwu/RTgA+uY/8bqpfVQThV4F3jS+j8MWGdd62HAsNId1v8t1vaauHN8z0rfBCzMZJ4DeZhrfX9s5eWsLMzDb1rPeAPwIODMhnwE7gYOAhvi0vo87zq7Rg9k/JX1vN8H1gB5vc2j3jyHdGSM23YLZtj/omzLRyv9q1a+fAisGMh8jJ6rNxVBX3wwK7+twHDAANYD4/r4mmWRQgH4MBckGgesiGQ48F3gl9bvxcAzVsGaCayLKxzbrO9863fkZX4Ds6IU1rHn9kLOm4E/E1MMjwDLrN+/B75k/f4y8Hvr9zLgYev3OCs/HVbh2Wrld0byHLgX+IL128BUFFmTh5hrkm8HXHH5d2025CMwD3NVw/hKt8/zrrNr9EDGcwDN+v3LOBl7nEc9fQ7pymilV2GuJbOTmGLIpnycDzwPOKz/JQOZj1G5eloJ9NXHyvTn4v5/D/heP8vwN+BsTG1cZqWVYc6tALgTuDxu/03W9suBO+PS77TSyoCP49IT9ktTpkrMVfDOBJ60CuZhYi9lNN+sF2CW9Vuz9hPJeRnZLxN5DuRgVroiKT2b8rAC2I35wmtWPi7MlnwEakisLPo87zq7RroyJm27EHgg1b13l0e9Kc89kRGzJzsZ2EFMMWRNPmJW5mel2G/A8lFKmVVjDJGXN0KtldYvCCFqgJMxu1pDpJT7AKzvkm5k7Cq9NkV6T7gN+A4QWUC2EKiXUkYWxI0/Z1QOa3uDtX9P5e4Jw4FDwD1CiHeFEH8QQnjIojyUUu4Bfg3sAvZh5svbZFc+xtMfedfZNXrD5zBb0b2RsTflOS2EEBcAe6SU65M2ZVM+jgLmCiHWCSHWCiGm91LGjOZjNikGkSJN9suFhfACfwW+IaU81tWuKdJkL9LTlWsJcFBK+XYaMvS7fBYaZvf4/0kpTwaaMbvUndHvMlprjy/F7JKXAx7g3C7OOxD5mA5ZJ5cQ4vtAEHggktRDWXpTntORyw18H/hBqs0ZlPF40TDNVjOBbwOPCCFEhmXssfzZpBhqMe2BESqBvX19USGEjqkUHpBSrraSDwghyqztZZgDRl3J2FV6ZYr0dDkNuEAIsQN4CNOcdBuQJ4SIhDOJP2dUDmt7LuYa3D2VuyfUArVSynXW/0cxFUW25CHAWcB2KeUhKWUAWA3MJrvyMZ7+yLvOrpE2QojlwBLgSmnZKXoh42F6/hzSYQRmQ2C99f5UAu8IIUp7IWNf5mMtsFqavIFpGSjqhYyZzcd07aB9/cHUnNswH2ZkUGV8H19TAPcBtyWl/4rEAaUV1u/zSBy0esNKL8C0s+dbn+1AgbXtTWvfyKDV4l7Kegaxwee/kDjI9GXr900kDjI9Yv0eT+JA1jbMQayM5DnwL2C09ftHVv5lTR4CMzA9PtzWOe7F9ATJinyko925z/Ous2v0QMZFwEdAcdJ+Pc6jnj6HdGVM2raD2BhDNuXjjcCPrd+jME0+YiDzUUqZPYrBEnoxpmfQVuD7/XC9OZhdqveB96zPYkz72wuYbl8vxBUOAdxhyfcBMC3uXJ/DdAfbAlwXlz4N00VyK/A/9MLV0jrPGcQUw3BML4ktVmGIeDQ4rf9brO3D447/viXDJuK8ejKR58AU4C0rHx+zXqqsykPgf2O6V24A7rdeuAHPR0zX2X1AALNl9/n+yLvOrtEDGbdgVmKR9+b3vc2j3jyHdGRM2r6DRHfVbMlHA1hlnfsd4MyBzMfIx575bGNjY2OTQDaNMdjY2NjYZAG2YrCxsbGxScBWDDY2NjY2CdiKwcbGxsYmAVsx2NjY2NgkYCsGGxsbG5sEbMVgY2NjY5OArRhsbGxsbBL4/+8PVLIFEyTFAAAAAElFTkSuQmCC\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"txdf[emas].plot(alpha=.8)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 46,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[0, 3000, 0.095, 0.115]"
|
|
]
|
|
},
|
|
"execution_count": 46,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"txdf[emas].plot(alpha=.8)\n",
|
|
"plt.axis([0, 3000, .095, .115])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 47,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"txdf['dP'] = txdf.P.diff()\n",
|
|
"txdf['percent_dP'] = txdf.P.pct_change().apply(abs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 48,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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lcjNWd7m5mZ+/9rW0dndjPY/+ri4XHDDLLDAzWpU3AF8SkVZSH84A8PqpFHRi43AAq3fswBpDko1kyvk8a7dtO6DYeNZy/K5dNIQh21tb2dHePmvt8+OYy265hVW9vSgwms/ztac9jd6mphk7RxIE9C5bNmP1OQ7MQhQbVb0TOE1EWgBR1X2iYUTkNar61fHKOrFxOIDhhgaMtWPbQRwzfAAzh7GWy26/nXV796KAivCDJz+Ze2dgfs2pu3bx7IcewreWW1eu5H/WrOG0LVs4qrub/oYGEKGpXOYv/vhHvn3eedM+n2PuWYDzbPZBVQcneOvtPL668j44sXHMOEaVk7q7aalU2N7UxKNtbfPdpEn54wkncNwjj9A2mP6GKrkct5x55oTHH93dzdrubvqLRRAhiGNecM893LtixZSDC8bjmJ4eLv3jHykFAVaE5/zpT4TG0DgygjVmrO6K79M+OqUgoHnHqHJSfz/NUcTWxka2LkxfhWNqTHjzO7FxzCiiyis3buSUbKltFeE/jz2W36+oX2Lj8KKSz/Pdv/xLVu/YgbGW7UuXMnqAdCKFKEonHWSdf+R5NEQRoopOQ2xO3r0bK0Il8/+UfJ/Td+3iF6tW8dSHHsJYixWhMQy5P/tM1w0NsapUoj8I2NDWNvXzq/KMvXv58127UBF+tmwZt8xwBFpDFHHFffexdniYUWOoeB5fPfpo1j/BI92stYRhON/NmA0mnIvjxMYxoxw1OMjJ3d305fMggm8tF2/ezG3LlpEcosO5JYq4ZMsWVo+OsrWhgWtXrWJwBpzjHWHI0aOjlI3h/uZmolyOh9asmVLZbW1tJMZQDEMqvk9LucymJUvQKV6jqOKpEtcdXwqCfVKx+9ZSCgI2LVvGr48/nmds2oSosmnpUn5x0kk8c/duLtm6dexxcn1HB19Yu3ZKo6tzenq47LHHGPZ9BHj1I48wagwbOjqmdA2TUUwSPnTffZw4OEgEtKqy1Rhe8cgjrO/snNYIcKFjjKFYLM53M2YDN7JxzA2FOMbC4zPqRTCqBElySGJjrOVtDz7IilKJYd/nyf39LCuX+fAJJ+zXUR8Ma0dGuPyhh/BVMcCmxkY+dfTRU66zv7GRb5x7Lhdt2EBTucy9y5fzoymGCv9ZTw8v37kTX5UNzc1cs2oVo1lgwi2rVnHGjh20l0oAhJ7Hz9etAxF+e/zx/P644zDWEvk+vrW8bNs2hnwfTwSrypm9vdy0eDGPTiFw4Gk9PfjGgDGURchZy9l9fTMmNqf397O4UiEUITYGo8qSOGaX7+OrEk9DbApJwgt6e1kRhjxYLHJrczPtScJe32dwgYSfL0SfjYisVdVHDrDv5onKLoxvxbFg2N7cTOh5NIUhJd+nOQx5tLWV8iF2AIsrFZaVy/TmciBC6HksLpdZXKmwYxpPhq/etg2A/iAAVY4fHuas/n5uPYiOdktHB1c/61kHdd7jh4d51c6dDHgesQinDQ3xih07+I9V6fpXg4UCV597Lift3o1vLZsWLWJvjY8jMWZMtPPWEqiyrlymmE1GHRGhMUk4aXSUvxwYQIGftLaysc4kePLwMBdUKjQaQ6LKw6qE1lKqmVe0vFLhgqEhYuDG1lZ6g+CgrjWfJIRZWz1rsUBBlT81N0/rQcFX5Ypt2zimXKYiwrMGBnj7zp3syeVQY/j0kiWsn8EovdngIFfqPJz4PnBG3b7rgDMBVPWtExV0YrMA8FV5cU8P546MMOh5fKOri82Fwnw3a1yGcjn+/clP5pIHHqCjXOb+zk6+d/zxh2wyibInYiE1Bkv2OpzmU2F7FFGu/thF8IDLBgZ43fAwO4KAf+/qYtdBdq4HomAtkQhHl0pIjfls0Pc5aXiYrjgmp8pu32con+fW1as5tlLhlCiiu1zmj5lZspYRzyMQoSmOKXkeBRFW5HK8tb+fJWHIcHaO00dH+dDy5dyXibNvLe/YuZPd+TwrR0fxreVJwAbf5+dLlwJwQqnE57dsoTETsb/q7eVVRx3Fjnx+ytf8QHMzJc9jT7HIsSI0GMN2Y/jmunXT+iyPKpc5ulxmr+8TAG3lMgYY9jw84O927+bNxeLYaPFwZSGNbETkeOAkoFVEXlzzVgswpc7Iic0C4NLubp7f38+Q59EZRVy5fTvvXrWKXTM4qW8m2d7czCfOPvuAxxhVXjA0xFPKZfo9j2+2tLBjnM69J5fj1s5OzuvpIRHBs5ZbOjvprun0CtaSiBAdxI/33uZmzu3roycICFRZ4/sMJAllEU4dHeXCrVv5RFcX329qok2VigilcZ5El8Yxx0QRQ8bwx1xuH+d83lr+qr+flwwN0WAtu3yfX1avURVEKFpLowj/vnMnCjwWBHyss5MLRkZ48eAgltQI/pOmJr7Y3g4i5FU5sVLhhDCko62NrsZGfFV8Y4iA8yoVPBF2GMNDIqxMEv5p714ezedZHUW0WUtRhD8EAZubmmiJYxqShG+uXMne7CHm3bt20ahKmXRVrVZreceePfz9qlVMlZ3FIp9et46P7dxJAej1PGwQ8Pb+fv5h8WKSyb4vVV4yPMyLh4dR4AdNTfwgG7FUP+cgC1evbleMoRjHdMTxYS02qrrQAgSeRJofrQ2ozcc0BLxxKhU4sVkAPHNwkD7fJxahbAxdUcTJpdJhKzYAgSoRTDiiecXAAC8ZGmLEGPJhyKnlMm9fupTe+g5ChK+tWcP9zc2sKJXYUSxyR+ZczlvLO/v7eWqlggLXNTby9ebmKY2ivrliBYUk4bTBQTCG0WKR/iDg5CTBAjlV/qavj0uGhykYgwLfampit+/TmiQ8mMuRt5b/29uLl422bikU+JdsYmeLKm/u7eXi4WGK1pIAK6KI56nyQGMjHaOjWKCoSktjIzuzc5wahvxw1y6aVAmBjZ5HCXju8DA/b2oiNoYr+/o4o1ymNUkIjIF8ntBaxFrypOJggBVJQrvvUzCGEWt5UqmEr8qoCAVjOB/4recxIELseTxYNdepcrwqbYUCCkTWElcqPLNU4qUjI1yXzfWZCgPFIpVikbs8Ly2jypMqFZZHEVsnuX//fHSU1wwN0Z+J/GuHhuj3PH5TKLAtl+OozB/kA4PGEGfiHYvQc5j7bUSEwmFqnRgPVb0euF5EnqqqtxxKHYf3N+IA0qe1XJ1D9WCe4ueS1XHM/x0cZFWS0G0MH2lp4f5xRizPGxmhN/NbjACL4pjTymV+lXV4T4oiXlwu46vy40KB28cJlX3V0BDnVSrsMQYD/O/hYR7xfX43hRUQS77P1UcfjadKPkn46tatLFXFqFIIAvIi5FTprFS4q6EBH3h3fz8DnkfJ89CRETSOaTAGzxgGVTmvXOai0VEuqVRot5a1YUgpGxXlgFagPY45OpfjnuZm/i0IOCOKeFUYss4YIlUCoKRKTDqiOcFa1htDAbi+r4/WKEpzsKmOjXoskBMhIhWZEWNosBYljQArA2XPw0sSbHbfjBhD0VpWJwk9qnx26VJ6su/pz0ol8kGAxjEKFIwhCgL2eh6vHx6m3xhumqK/bLw4WIFxxeoZlQp/OzpKkyr/k8vRWC5TFhkzmVaAp5ZK/LKhgY+sWsWLu7tZGYZsaGzk9FKJtiQhEuETS5fu43s6HFnAkzo3i8h7gTXU6IeqTpqy5oBiIyLnANcA64B7gDeo6n3TaqrjoPlWZydv3b2bxiTBADtzOe6Yx4lx1Sf5+mgiX5UPDQzQai27RWiylqsGBnh9RwdDdSaohLoYSRGS7OVxcczHssmVCpwXhlzZ3Mz6On/BaWHIIJDLjouBk6OI3x3EtSQinG0tR7W0sCSOCVRJrCUkFYfRrN3NqrR7HsbzGPU8BpKE84CKCBZYKsKQCO8YGWHI89hrDMeSGrQTVYwIokqSfW4nJwkX5nIcLUKTCMNAXpUC0JM9XORVCVRZlCQcl5Wvdt4GxsQGEUoiWGspqNIsAp5HyRgE2OX7GGMQa9HMB6OkPo4vdHXx88ZGyjWd8wlRxNYgYIUqrUmCqpL4PlsaG2lR5fxKZcpis9v3+UOhwFmlEmVjKKjyx3yebXUjjxPimPeOjDAswqAIF1YqdJOOMKsEQF/WzmHP42tLltCiylPimM3W8pAqj+Zy45o7D0cWqNhcD/wWuAnGfrJTYrKRzWeAy4HfABcBnwT+4hAa6JgGN7e00Of7nDY6ypDn8euWlvmxR6vypjDkkjDEAD8OAj6Vz4+JTpe1tFtLT/ZjHxah3VpWJQn31XUA321p4fX9/UQieKrs9X325vOckiQ8p1zGqNKdXWOrtbykXN5PbLo9j/PDkLwqqDKqyu6az+XJScK7KhU6VbnF8/hEPs9I3Q98WZJwxegoW3yfEVKhE8+jYm0asu15FICTfJ8G0qf85dnTdrXzjgCM4ahCgQppUMOOJMEzhlw+P5ZKXkVIjCH2PAzwzEqFlZ5HQ0MD7cBoGBInCQ3GkBchnyRE1jIqggYBoQhNnpeel1T0VSQd3YhQ8n2KWZvz+TwduRwPRRHH+j6+CIV8nlK5TBhFBMCmIOBXdUIDsM338YANhQLHxDGLk4S9nodmpsu+g+kkRfj/u7q4aGiIY8KQh4OA61ta9pt4enIU4amOCUVvJkxDxrAoSfu0QWP4fk2UWZe1fK5UoisTpH4R/hYoTb1188oCFZsGVX33oRScTGyMqv539vp7InLFoZzEMX3ua2jgvgnMQ3lVTslGG/eIUBahRZWLkoQ2VW43httnQJyeF0VcFobszZ7mnx9F7BbhziDgzVFElypLfZ+hJCHM5td4QL8xeKq8IEk4QZXHRPh+YyM9xnB2uUyv59FeKPC5KCIBuoA+EXqA1caw3PNoE2GZKjurP1BVkkKBQqlEooqo0ur7PDebyX+Ktbw4jtkD7AIuiGMC4P11dvLVWcddEWHA8xhJEgJV9ngeIyKcZC0X5PMEWYdmSUdQecAag6imo5AgICQ1bxrgBN9HPI8ojomCAJMJdNkYmkmf0pfk83ieB6qoKo25HGVraU0SKkBsDDubm7m6oYGv9PXRKkJjLkdFhDAM08g8EUY8jz35PC3GkPN9mkTwMxE61vPYC+xVxROhpbGRh0ol7szl+GxrK43G8C9hyInWsl2EDwQBP2to4KmVCieGIUPG0KxK2RiWJAkDxvDdgwwrjozh+62tBzxmyJhUgLLAiYIquzyP9yxaxFmZWK/P58dGNgAvz+653ZlALbKW14UhH1kgvpAFKjY/EpHnqepPDrbgZGLTVhfmts+2qv7gYE/omCaqHEcaEvIQEAGfiSKOykwsO0S43Pf5WBSxOjPbXJok/LMqP5qm0/SMJCGEsSiiCHiNtbwrDOlXZQTI5/OcUKmwLY4xwHXFIq9T5ZVhSJsqW7Ny5xjDOxsauLmxkZOThM+EIXtJn9B9Y1gTBLSrssT3Saylyff5XBjy6lyOdap8KI45zRji1lY2xzErRGjxPC4AXhjHJECDMSwCGlQpGsPrVHkgjvl29pQOsNcYPNJRQhPgZ2IxbAyrgLzvI8ZAFvVkskmgBlBjxn5AXjZqKYhQfSTwfZ98LkeTCHEUUSqVaM3qyedyeDWjveq8i4ZikYLn0Q9szdq4ThWvoYFCGCIi5PN5crkcuXweYwwlEYpAEIY0AEGNIHuki43c5/uEIiyyls93daGex/mqvCoMWaRKD7BYlX+NIi7J5XhfezvHZiOgRhHeniQ0ifCAMbxAlZ4k4afZuWeCX+VyPL9c5tjMbBcBn25ooM/z+O8JHrI6VfcJgc8bw0VAa5JwrTHcdRh35qpKFEXz3YxD4e3Ae0UkBEJSS66qastkBaVqwx33TZEv87iPr/rNac0JprSOwQHqfw7wr4AHfEFV/7nu/TzwNdIJQz3AJar6aPbeFaRrKyTA21T1xqnUOW47zjpLWb9+OpcyIf2kH5ZHOvPptRMcN0j6xFw/pbCX9Cn448DlqsTW8rAqRdIn9ltVeYa1rMg6yRFVlgJhZmJpAjarEolw9jhzJM4Evgf8J/DObN8QqTO21iW/DWirVLgjijgje2qOPY+8pHNUSqQRaOsz5/Y5xhAZw1dEeKG1LLY27aBF+LUqzcA7cjneYgzPjWNaoghEGAR+p8paa2kToaRKuzEbQkZNAAAgAElEQVS0GwOqbPJ9+q3lbNL5ItWVNVUVq0qUOdMhvTGU9IkqytrpVZcR8Lx0RAO8rVzmX8tlikFAJQwJfB81hiSOCbJjJctllcvlxv4DhGFIEARYa8cEI7GWIBP2ekdwHMdj+zUb0dQiIni+P3ZdFWvxs6f5avtVlTiO0zrSQnjGEFsLmcmpWm9ibXr/ed7YCDAoFEhEeEyVZXHMvcZQyr7DC1Sp5HJgDDcDf6aKnyRsyL6z5cAe0vv6ARHe5HlURHgH8CGgG3gu8ACPdxx7YEyAw+z7GK9nyquyNYooqnKm7/PgJKPxC6OI91Uq9IjQIsLpnscOEXqz7/qtvs/dsyE4Ineq6lnTqWLt2rX6wQ9+cErHvuY1r5n2+Q4HJhObd9Vs1oqOAqjqJw75xCIe8CDwbNK+7A7g5bUBCCLyt8Cpqvo3InIp8CJVvURETgS+DTyF9P6/CTguK3bAOsdtyyyIzUbg+My0BZlCZ07w2tisHcDSmm0lFaSvs78TXVVRa/eZebwrilji+2MdWvWJKQiCfTq5Shji5/M0kXawACNArZu3+hRRu+3VtqPuXtHMjFP9PxH17ydJQnccs6Q6UbGuXmst3whD1opwfhDsc722OsKYwAkcxzGe5+177ZUK+RqhjeMY3/fHIqK05ns6VKqfebW+JEnSc9RcszFmrF1RFOHXfW/Vtk90bZN9zuORJElqqsuwdfdP9ZxkDxBj5yK7X5MkXSba89LrUqXHWm4jvW/f63n81Bjqg5gfBp5K+kA0UYu3A7Wzdurv9yHSII0JUeWyKOKVUcRxxhB5Hg9k19apyq+N4f2z4ducIbG56qpJV1IG4NWvfvVhIzaS3oCvANaq6j+KyCpgmarePlnZycI2mrK/M4E3k3bsy4G/AU6cVqtTodisqg+raghcC1xcd8zFPL42wnXABdnFXgxcq6qVLCfP5qy+qdQ5Jxxf14FlQ0E84LGa/UvqygnwZRgLfd0H1f06olqhgbSD8Ov2QWa2AaoJjN7HvkJTPTeZs53sKTgmnbVfLwjVc9UKzkTUt8XzvFRoHj9gn/eNMbw8n+ecOqGpvnegNB+1HXqVXN18jqoIVNs8E8++QV14t19nsvTqOr3676j6vR3o2g7Fxl9/3vr6x9pRP8KC9B7IRmtk97MnQptJlzpQUt/VeLNljiZ9kDpQi5fXvI7GObYJ+PMDlEeEb+VyPK+xke/lcuyt/Tw5QPrhw4DqiHcqf4cZnyV9jrgs2x4mDSSblAMa8VX1gwAi8nPgDFUdyrY/QGp9mQ4rgK0129uAcyY6RlVjERkAOrP9t9aVreawn6zOuSFzdNZS3Vpav28cU8q4TPHGO1CHVTWNvWi8N8cTDGtnLztvbb11HZ6XdXBTRWs7xv1OM377Z+tnPOH56sRlquUm41BGPFM993hCZCSNMiyLcPkBzjvZk2xtyfGOFdL8KDdNUg/Ad4zh6daORaYhwnWHeQj0YSgkU+EcVT1DRO4CUNU+EZnS7PKpeoxXk5pbq4Skk3qmw3ifdH3vMtExE+0f7+4at8cSkTcBbwJg9eoJGzmTVDuFcv2+/Q8cC2mtZbwfPiLjmqImaACjWZl72T+b3rhFrIUpmiIm6vTqTTdkbahv2z5lsu2Z6C4O2BnXnHe846a677BmqvfHuEUzMx+kEYCkj7KbRPik5/GApJGJZO/XMt49vM/7qixVZUBk/GNV6Qbagb7qdUzA3SK8xfd5SZbw8/vGcM9h/h0tqHvocaLMBZK5C2URPH4LHIipis3XgdtF5IfZSV7EBEt/HgTb2Ndku5J05D3eMdtExCc14fZOUnayOgFQ1WtIJ6ymPpsZpo/9nf0ANklorem8R6OIxjoTzNY4ZiQIOGG8ius6jntFOOUg2rVheJhTGhp4nefxKjITWcZ4neiOMGRlobCfk7veFAWpf0BV9zMpjSc25SiiUJsnrAZV5RVJQmwM143jYK83pVWd89ZakiTZ7/wTiUOtg94YQxzH+5Wt31f1GR1KR1H7OdT7UiZrK6R+nnqfzoHMl5CKtqnxC2mdKdZam0bbHUhAMyGIROgGLgQ21vp9VPfpSFSVWJV/EuHKbGJp9sY+1Q6PjvJN0p7qB7kcLwmCfY4Nw5A3xjF/BfzK8/hIzZyu8dggwobDPHNAlQUcjfZp4IfAYhH5MPBS4P9OpeCUxEZVPywiPwWenu16naredSgtreEO4FgRWUvqK7yUx+2AVW4AXgPcQnpRv1RVFZEbgG+JyCdITb/HAreTjngmq3NO6BJhoyrHJsnYjzgMQ35nLa2NjQxk+75tLReWyyzPOu/fxzE/8zz+GfiuKhdHESLCoOfRkuXP+icRTgC+BNwIPBO4QdKliUXT+RTVjkVEiElnsfdVKjQB/1gq8eLGRi4KQ76lSoPvo6r8tlTipEKBjqz8sLVoHDNcqVDInO6RtQTGjAlLtZOPoiiNxFIlSpI03Un22ssczdU29VYq9KjyYBRxbrFIZ5KMiZ61lp8nCZcBW4yhJ0loyXwZcZY+ZWsQcHQW1VUljuOxjtdaO9aRR3E81tl6nkelUiGXy2GMIQxDrLV0xzFLs7kZlUplrGySRXaFYZheW7ZdNdeVSiVyuRye52GtxVq7jwhXhUpEiKKIJEnI5XJjnwXs6+upVCqIyFiZ2mCH2ii2quCNjWrt+A+WpVKJXLGYmiTjeEyMq/6hKIroBa4vFPiDCB9RpYOasNOajn0TcBWpSauv7jz/USrxyjimWCxiraVULqcJQIMAr1ikAmgYjn0PAL2lEo+I0O155FXpCENWeh6PZuLUH0Xcn82TArggSXgwirj2MM4HeDAYYxZUbrQqqvpNEbkTuID0Vnmhqt4/lbJTnnihqn8A/nBoTRy3vlhE3kraX3rAl1R1o4hcBaxX1RuALwJfF5HNpCOaS7OyG0Xku8B9pL70t6hqAjBenTPV5oNChL+0lv8ol8dm1EM62llkLQNZh3a/MZwQx9wexwiwTJX7RWi0lp6BAX6RdUwjxnB5aytbxpkr82vSUNK853FVHHN+dS5HklBKEo7SNKljntQR26JKiyqvq1S4iXSUAbBUlX+zlqW+z3lJglYnzYUhrZ5HTpVBa7nV8zgaOEaVEtCUdRBJklAyBl+VjXEMIuwQYZsqJ0YRndbSkYVA9wEtYcjbRbhsZIRT4ph+z2NrQwNG0jDuoqZ5vbxsuWUD9CcJf+N5vF6Vi60dS+EiWUCDkg69kyQBESJVwkoFQyq4Hql4iO8znM2TCVS5vVKhbAxneB5BJpBG0gXJPBGSLMy6Uqk83tmTjjbyhUJq+gSiJBkLBrHWMpp9tjljSIC+KKIlGymoKmG5nIoXpE/zqpRLpTQnme9TSZI0PVAm2KVyGS+fR4AfRxFLoog1qvj5PA2eB9ZSzj6DPSL8MI75cBDw8TjmL6OI5ZnZK8rmIvUaw1XZsV8Cmklt5JUpjtzyqpyTJIyoEmXJRQ2wSJVV1fsQuL1cZoVm2Ray87QDW7JzNamySpVq2MjHk4Qnq5IXoSJCWZVTrOXaKbVqYbAQ17MRkXOBjar6mWy7WUTOUdXbJis7r4k4s1moP6nb9/6a12XgZROU/TDw4anUOV90G0MkQoOmmXaLmc17T81Ndk0QsFaVU7P5ED/1fX7k+7y4VGJtHI+lX+mwlr8aGeH9B5iJXRHh3b5PJ6lp4unAFVnalerzYAkYkDT/VEAaBi3A4jhmqbW0WcsVLS28R5W/0MfzaJWThDjLGZZ4HjuThDWAZPM3ImuJrGWn5/Go5/GVbBLhzcZwWhRxdV8frXGM+j6jhQI7RFikylsGBxnKOpTWJKE4MkJvYyNX53Iss5YzKxUC0if62FoeSxJePzzMq9vb+fso4ooowtc0JLcaRRdXTUfWsj2KaLWWyBgaMhOk6uMTM8MkoUGV5VHEds/jblVOVWUnUKzO77E29V0lCaZGaGxWz0i2noqNYwqFAmoMcZJQHh1FrcWKIMUiXhCQIw05/zbwijimmI0i46w9w6o0ZJ95mCQEmRkxjGOiSiUVUGPoTRJOiWOCzFHvl0qMBAHNxnCP5zFkDJ3Wjo1OdmVO/cSYsRGGAYasZU+23Wot52WZnY+PIlSE3+fzfLytjd0TTAgOyeYzyeMRiUoq4Pdl966vSmcckxPZp8MJat73SOfjXDQywl+USjwdWOT7lEkXhOvzPB5ZgJ3zgVigPpvPsa+7d2ScfePisj7PIsMiXJnPc1WlQmeW+vwf8nkGa26yERHelsuxRJUks4kjQmeWlr5KmXRENCmSpnkBuCEzx/x1GHKctewBBkV4X7GIFeFHuRwvr1RoimO6stT6J5ZKfLhS4VNdXTw5SViUJDSRitRgZpJbZC0BsCeOeVCVQIRj4pgisDEIuKJQYEfWMTRZy1/39rI9G4U0Vir0WktSLJKzlpg0x9mwKiutpVmVf/N9vuv7NAH/q1ymvVIhFqFPhK0itGka6ffxIOBFvb2szUKkrbXksqf7CBixluHsMymqUso6O0+V7aosr1RosBarSqsITVFEmCT0qrLB98fMUx3W0pvLcSGPBywoqQ8jp8pgkuBl5ymVSuzK51k+OopqusaMUWW0VOKOXI7Nnsc3fJ939fay1RiODgI8VWySMFqpUB4ZYSQI6GptRY1htFymlN0bhWz0ticMCbJ7p02ERNIknaG1YAxtquSspajKqf39fDtJuKdQIDYmzfycpYYJ45jfBgGIsCqK+Gh3NydF0VjG6IoxXFAu097Tw1sWLx53wToV4RP5PJ8ol8fmkFlVthrDhzOTV5u1JFGE5nJjQS5K5tfMhObzQcCp5TJ/PTRETpVcHENDA57n0aZKt7V8ewYXszscWKBiI1rjKFRVm/nTJ8WJzSxzZxDwMt+nS5VuEUbHu8FE2F23/64g4IWlUpqFmDTr8I8P9scmwvVBwPVBQKsq7dayuybFyJfyeSqqvGdoiG5gs7UMex4r45iWOOaVDQ38rzjmGVHECPAb3ycBTlBluwgVVd5eLqPW8ojn8alCgRvr7NDHRBFN1rLb8+g3hhOzuhercnMQcFI2WmgdHYUwZESEu1pbQdJMyJc3NPD5KGJU0uwCi1T5bdaJnT06SnFoiD3VDrRYpDOXI/Z9ImPYDdyQz1NQ5aIwpCkbQTwYxyzt7WXQWsTz0rQy+TyeMfQlCVEc09zQwJBJsy8b4L3FIhsqFf6/cpkcqe3WAntU6ck6/B7gVGsZjCLaVMdGLYm1REnCoj17+OCyZewh7YDvAR4slzl1ZIR8koyFWXpRxPaBAT67eDFvydpt4njM2Z+vVNjR0EAsQiETIUizDTxoLbfkcgSqnDowQKzpEgfPGBmhX7M1ajTNdRaKcG1zMwBvHBigLRtdw+PzwgJVlljLsjjmsQnuv+/kcpSAv6tUKKrya9/nn4pFRrIHjkZVHhVhZRTRmJlcd1vLG5uasMbQLelCb5/NRrlLNM0E0V0qMRAEDHgeDxuzXxLVhcwCDhB4WETeRjqaAfhb0jm8k+LEZg4YFWHLQf5Qbsvl+PfGRl47OooP/KxQ4JvTWFZgQGTMT1QlEeHafJ4XdXfTXZMvrNrp9RvD9bkc19c5ZX9V8/quIGCZtewyhl3jRAJVJE0dQtbp3ev7LEkS/q65mT8Zw9uA/93dTbFSwRrDXmN4z86dvGvVKvp9n4eCgCubm3nbyAgdqvw+l+NTTU2IKq/bu5ckjvFE8JIERkcZBl7Y3k7oeZSBXSZd6+Y3uRyLrOW44WGeMjpKLnt6F02zMpTLZZQ0Jf5gNqO+MxvZfKqxke2+zyd8n38tFnldpcLSJOH2IODoKOLiUglUaRThC42NnJutwFhd0EyzaLnmJOHK3bt57apVqCot5TLFOB4zzVXNUUYV4phv5/Pc5vt8p7c3XZ5ZhB2q7ADuSxJO9H36gcWkP+Ttvs8Hmpv5YxBw4fAwxyUJo76PUaUjighF2GUtLYBYyz82N7MhE5AlSbJPnrPa+QUGJk3bf0Muxw0TOO93eB7bPY8wSSirUlRlr+dxv+/v4xsqZ/fKaObDUlKzIknC5iMkMKDKQg0QIJ3Q/2nSCDQFfkF1CskkOLE5XBHhhw0N/LBYTJ8yZ+mpLjSGXzY2csHICCVjyFvLriDggSn+uHd73j5p/evZFAQ8agznjY4iqgwHAZ9va+NPmQ/g6qYm/nz3bsq5HKPGMGQMHVHE8eUyt2bZhW/N57k1n99nomxXFNEex5SzUYUn6ZLRv/V9HqxruyUVG4Ar+/ooSTqvIyHtdMmyDiSkAvzfDQ18ra2NxUlCX9amKokxfCFby6UrDHnK7t2UoohyLsc3Fi3iJ01NBMALR0Z4T18frZrOmRpMEhJgaZZK/w5reX5/fzqSKRRSn4c8Htbuq3LlQw9R8jyuLRY5K0nozgS0A3jq4CDbsxxs32lu5urOTnqqq2Hy+Do8aJqV2ic1xd6dJOSA5iTh9mxVUYC78nmeNzJCv6QLvQXZX48I1zc2smcaIcWRCO9ta+OdQ0Osi2Me8H0+3tKyXxDC15ua+EBf31jOujzpff9QEPDlg8w0vRBYaGa0bH7NK1T10kMp78TmcEdk1tNufK69nR2+z6mVCjt9n2tbWihPwxm7tFTinO5uPGvZ2tREw549POb75IwhLpXoz+ehJU3FaEXoN4bRLHEnmdlqPP9A7aS+UIRYhE25HEfFMbksCODTbW0HbNujuRynlkr0eR6S+ZmqHfyDuRw/bWzkK21thCJs8X2WlMucPjhIZAx3t7VRykTSqPLORx9lcRjyiO/TWCrxvK1b+Z/jjmPE9/leUxN+HHNFdzdhZgo1pEsnFKzluMFB7ikUyKmyCDiG1JcE6ePiYBa40BrHdFUqUCymzn3gqEqFbmvZ4/t0q7Kut5eu5mZ6arIj31YssimX40lRNJapenv1O80mPvbUCMiXW1potZbzy2Wi7No35nL8T7HIHTPwBL7T8/g/k3w3d+Xz/H1HB+dVKpSBe3I5hjyPbZ43lmn8SGKhiY2qJiJyMem6ZgeNExsHsQjfb2nh+zNQ1/LRUS7fuJF8ZqZqiWMoFHg4CEDTlSif0dfHjUuyrHAifKuzk9d1d2MzR/ufCgXuKRYxmi59PN7M8UHf58aWFp43MJAuC20MtzQ28sAkHeP329t5UqXCMdkaKcOex/fa27k5CHjpI49w9I4dvKalhWvXraOrUuHd99/P4lIJX5WeXI7LTz+dnkKBtjhmSRjSl5mhhn2f1jhmZaXCJt9Pgxp6e3k0ilhsDBXPYxD4WXPz2MTEERFGjKGPNBTZzybPmnKZR4CK51EBCmHIBt/nBGvxVBmyls2ZcNjsYWRJGLKpRmwiEa5cvJhzSiUarSWfJFza309bttrrZzs76a+JMKsYw0c7OsZ8hHaeOsJNuRybjjCT2XjMZN4zOcTs+SLybOCfSdPbhcD/UdVfTnK6m0XkauA7pJFowNjUmAPixMYxozxz1y4Ca+nJEm02xzFNpRJkHaGnSqVu1PSztjZ25nKcWCrR43ncVizyynvv5YSeHiqexw+PO44/LF2637m+2tXFA8UiR1Uq7Mzl+H1T06R53EaN4R+WLWNFFKHA9iAgnyR88A9/YGVfH0aVNT09rB4YYLSpiWXZ3JFIhMWVCu/auJH3nnnmmJnKt5bYpIuoeaqMeB7NYcjl995LcxTxiAih5/FYWxs3dXXx89ZWLLAtn2dVpcKA59GUJGzzff5+1SpKnseH/vQnOmomrYoqtxSL/GNnJwAfeuQRlofh2KJ0ALvG6aAjEX5XI0C/aWxkcRzT7fv0ThDKHC2wp+2FzEzMs8lMW5+hJtO9iNxQl+n+DUCfqh4jafb8jwKXkK4I8QJV3SEiJ5POT1zBgTkv+1+bslqBP5usrU5sHDNKztp9TB4DQUA+jukKw7FRyg+X1Oe6hg0NDWzIOsZX3nsvJ/b00JvPE1jLJfffT3dDA1ta6lZBEeG2piZuO0h7fiLClprOecXoKCv7+xFVomztmif19tJdnbeTmZtiEVaPjpJLEsqex7eXLuWyXbsgm8j5i44OtuXzPHXvXlrCkN5McEeTBO3v56fHHDN2zo+tWsVf7dzJulKJkSShu7eXN+/Zw03r1vHdJUt4x9atNGT19uRy3N7WNiakn1mxgndv2UJbHGNU+UFXFw9OsMBYLf2+v89oxjF/VDNMzABjme4BRKSa6b5WbC4GPpC9vg64WkSkLgvMRqAgInlVrTABqvqsQ22ou/McM8qtixZxVk8PjVlqGU+Vq9eto02VgrXc1drKQ5NE1R3X28tALpdOYPQ8TBiyanBwf7GZIRJVgiQZ81NVgzG25fMcVS4TaZosVYARzxszg93U1cXDDQ2sKJfpzeXY2NiY5hHTfb1smkVX1dIfBHxs9WrO2bKFFz72GEkQ0KTKpffcw5dPP50PrV3LaUNDlDyP37e1MVgjEjvzef5+3ToWRRHDnseAE5AFhzFmnzWWpsF0sud31xzzEuCuAwkNgIgsAT4CLFfV50q6tthTVfWLkzXU3aWOGeWB1lY+f+yx/MXOnXiq/GLpUu7s6pq8YA2D+TytlUpqqso67uFZnND3SHMzg0FAcxSN5W8byOW4ds0aFm/ezLqREaykeby+vXYttsb88XBDAw/XjCqW9/Rw1t1302Ut7b7PnuZmcqrcsGrVeKfm9F27KPs+YSYYOWs5efdufnjSSfvUW09oDNtnprNyzBMH4bPpEpHa1R2vyRIJw/Sy51fbcRKpae3CKbTlK6RLbr0v236Q1H/jxMYx99zb0cG9HePlvJ4a1x1/PG+8+25aszQwD3Z0cO+iRTPXwHqM4aNnnsnbNmwgyLJN37h6NQ+3tXH5mWdyZk8PrZUKjzU1sekAEVWNpRIv/93vgHQy77HlMgFw7Smn8LtxTIcAJd9Pl7euNsVaykfYTHnH+ByE2HQfYKXO6WTPR0RWkmZxfrWqPjSFtnSp6ndF5AoYGyklkxUCJzaOw5BHW1v52FOewuqhIcqex5/a2/cZTcwGD7a3876nPpWlo6MMBQE7Mj9QLMJtUxS6pQMDeNYynEXEbfA8WgYHuaOjY8LAhZvWrePovj7aSyUAhnM5bplgFOQ4spihaLTpZM9vA34MXKGqN0/xfCMi0snj69mcCwxMpaATG8dhSV+xSF+xfuHq2WUgn2dgGqapchCks/+zyaeetVhjiA7gU9ne2srV55zDCXv3Yo3hj0uWMLgwZ5Y7DpKZEJvpZM8H3ko6xetKEbky23ehqu5hYt5JKl5Hi8jNwCJSAZsUJzYOxwyxvaOD+1au5MStj/trf3rGGZOOyvY2NbH3CJwh7zgw1fWRpsuhZs9X1Q8BHzrI091HanYbBYaA/yT120yKExuHY6YQ4b/OPpuNq1bRXC6zu7WVndPwXTmOXERkpqLR5pqvAYOkEWkALyddyXncpWBqcWLjcBwizXv30rprF2GxyJ6jj4Ysdf9Dy5bNd9McC4CFlq4m40mqelrN9v9r735D7KjOOI5/f9l0jQqRJP5LEzWhLkJaSqTbxJfSmGT1RZOSFiNYV2pILYiUUiQibSRiiUKxlNrCqkuDL6pFX5gUJaxRX5Q2Niv1bzVssCbZJsTVTbXaJlb36Yt7Vm62c7OT3Zk7u3t/HxjunTPPzD2zC/e558w5M89LeiXPjk42ZhOw8K23+PqTT34+p+bIFVewb8MGmGEP+LJyFHm7mib7q6SrImIvgKSVQK7BBU42Zmcqgit37eK/c+bwWXs7RPDF/fu54OBBhpYurbp2Nk1M02SzErhJ0qG0finwpqTXgIiIrzba0cnG7AxpZIT2Eyf49+gjutPjAdrT8GWz8UREYQMEmqxrojs62ZidoWhrY+iyyzj/0CH+M3cus0+eJGbN4p8ZNws1yyKJL0zDybsRcXCi+7qD2WwC+jdsYGjJEs7+8EM+mz2bvddfz8ceeWZnYPS6zXjLTOGWjdkEnDz3XP50442nPD3ULK+ZlkjycLIxm4wW+8Kw4jjZmJlZ6ZxszMysVNN4NNqEVTJAQNJ8SX2SBtLrvAZx3SlmQFJ3XfnXJL0m6YCkXyr9RJB0t6R/SHo5Ldc165zMzPIaHY2WZ5kpqhqNtgXYExEdwJ60fgpJ84Gt1CYRrQC21iWl3wCbgY601I/9fiAilqfllJvTmZlNBXlHos2krraqks06YEd6vwNYnxGzFuiLiOGIOA70AV2SFgJzI+LPERHUbgyXtb+Z2ZTlZNMcF0XEUYD0emFGTNaztRelZTCjfNRtkl6V1Nuoe87MrGpONgWR9Kyk1zOWdXkPkVEWpymHWvfal4DlwFHg56ep32ZJ/ZL6GRrKWSUzM5uI0kajRcQ1jbZJOiZpYUQcTd1iWU+GGwSurltfDLyQyhePKT+SPvNY3Wc8BPzhNPXrAXoA1NkZjeLMzMowq8XuEF7V2Y4+E5v0+lRGzG5gjaR5qTtsDbA7dbv9S9JVaRTaTaP7p8Q16lvA62WdgJnZRLXiAIGq5tlsB34v6RbgEOkpb5I6gVsjYlNEDEu6B9iX9tkWEcPp/Q+A3wJnA8+kBeB+Scupdau9A3y/CediZmbjqCTZRMT7wKqM8n5gU916L9DbIO4rGeXfLbamZmblmEmtljx8BwEzswo42ZiZWelGRkaqrkJTOdmYmTXZdH142mQ42ZiZVaDVutFaa6C3mZlVwi0bM7MKuGVjZmZWMLdszMwqULtpfetwsjEzazJJzJ7dWl+/rXW2ZmZTRKtds3GyMTOrgJONmZmVzsnGzMxK59vVmJlZ6dra2qquQlM52ZiZNdlMezBaHp7UaWZmpXOyMTOrQFGPhZbUJWm/pAOStmRsP0vS42n7i5KWpPIFkp6X9JGkXxV+gmM42ZiZVaCIZCOpDXgQuBZYBtwgadmYsFuA4xFxOfAAcF8qPwH8BPhxkefViJONmfKbOvYAAAYiSURBVFkFRkZGci3jWAEciIi3I+IT4DFg3ZiYdcCO9P4JYJUkRcTHEfFHakmndB4gYGZWgYJuV7MIOFy3PgisbBQTEZ9K+gBYALxXRAXycrIxM5vazpfUX7feExE96X1WP9vYO3zmiSmdk42ZWZOd4dDn9yKis8G2QeCSuvXFwJEGMYOSZgPnAcNnUN1C+JqNmVkFChqNtg/okLRUUjuwEdg5JmYn0J3efxt4Lip4voFbNmZmFShiUme6BnMbsBtoA3oj4g1J24D+iNgJPAI8KukAtRbNxro6vAPMBdolrQfWRMTfJl2xDE42ZmYVKOreaBHxNPD0mLKf1r0/AXynwb5LCqlEDk42ZmYVaLWHp1VyzUbSfEl9kgbS67wGcd0pZkBSd135vZIOS/poTHzmTFkzs6kk7/WamXT/tKoGCGwB9kREB7AnrZ9C0nxgK7Ux4yuArXVJaVcqG6vRTFkzM6tQVcmmfkbrDmB9RsxaoC8ihiPiONAHdAFExN6IODrOcT+fKVtozc3MCuCWTXNcNJos0uuFGTFZM2MXjXPcU2bKAqMzZf+PpM2S+iX1MzR0htU3M5uciMi1zBSlXaGS9Cxwccamu/IeIqNsvL987n3SDNweAHV2zpz/qJlNC7NmtdY0x9KSTURc02ibpGOSFkbEUUkLgXczwgaBq+vWFwMvjPOxU2KmrJnZeGZSF1keVaXW+hmt3cBTGTG7gTWS5qWBAWtSWd7jVjZT1sxsPL5m0xzbgdWSBoDVaR1JnZIeBoiIYeAeardj2AdsS2VIul/SIHCOpEFJd6fjPgIsSDNlf0TGKDczM2u+SmYVRcT7wKqM8n5gU916L9CbEXcHcEdGecOZsmZmU8VMa7Xk0VpXqMzMrBKtdb8EM7MpwqPRzMysdO5GMzMzK5hbNmZmTeYBAmZmZiVwsjEzs9K5G83MrAKt1o3mZGNmVoFWSzbuRjMzs9I52ZiZWencjWZmVoFW60ZzsjEzq0CrJRt3o5mZWencsjEzazLfQcDMzKwETjZmZlY6d6OZmVWg1brRnGzMzCrQasnG3WhmZlY6t2zMzCrglo2ZmVnB3LIxM6uAWzZmZmYFc8vGzKzJfAeBJpE0X1KfpIH0Oq9BXHeKGZDUXVd+r6TDkj4aE3+zpCFJL6dlU9nnYmY2EaMJZ7xlpqiqG20LsCciOoA9af0UkuYDW4GVwApga11S2pXKsjweEcvT8nDxVTczmzokdUnaL+mApKzv0rMkPZ62vyhpSd22O1P5fklry6xnVclmHbAjvd8BrM+IWQv0RcRwRBwH+oAugIjYGxFHm1JTM7MSFNGykdQGPAhcCywDbpC0bEzYLcDxiLgceAC4L+27DNgIfJnad+uv0/FKUVWyuWg0WaTXCzNiFgGH69YHU9l4Nkh6VdITki6ZfFXNzKasFcCBiHg7Ij4BHqP2Y75e/Y/7J4BVqmWxdcBjEXEyIv4OHKBxj9GklTZAQNKzwMUZm+7Ke4iMshhnn13A7yLipKRbqf2Bv9GgfpuBzQBcemnOKpmZFaOg6zFZP8pXNoqJiE8lfQAsSOV7x+yb5wf9hJSWbCLimkbbJB2TtDAijkpaCLybETYIXF23vhh4YZzPfL9u9SFSc7FBbA/Qk+ozhHTwdMe2ae884IOqK2GVKPp/f9lkD/DSSy/tlnR+zvA5kvrr1nvS9xfk+1HeKGYiP+gnrKqhzzuBbmB7en0qI2Y38LO6QQFrgDtPd9DRBJZWvwm8macyEXFBnjibviT1RMTmquthzTcV//cR0VXQoQaB+ssFi4EjDWIGJc2mlnyHc+5bmKqu2WwHVksaAFandSR1SnoYICKGgXuAfWnZlsqQdL+kQeAcSYOS7k7HvV3SG5JeAW4Hbm7iOdnUtqvqClhlZvL/fh/QIWmppHZqF/x3jokZ/XEP8G3guYiIVL4xjVZbCnQAfymroqp9ppmZTUeSrgN+AbQBvRFxr6RtQH9E7JQ0B3gUuJJai2ZjRLyd9r0L+B7wKfDDiHimtHo62ZiZWdl8bzQzMyudk42ZmZXOycbMzErnZGNmZqVzsjEzs9I52ZiZWemcbMzMrHRONmZmVrr/ASACLXtlh+MwAAAAAElFTkSuQmCC\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"txdf.plot.scatter(x='R', y='dP', c='percent_dP', alpha=.7, logx=True)\n",
|
|
"plt.gca().set_facecolor('cyan') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 49,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"txdf.plot.scatter(x='a',y='dP', c='percent_dP', alpha=.7)\n",
|
|
"plt.gca().set_facecolor('cyan') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 50,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.axes._subplots.AxesSubplot at 0x1a4f6b3e10>"
|
|
]
|
|
},
|
|
"execution_count": 50,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
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},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"sns.scatterplot(x=\"pbar\", y=\"P\", data=txdf) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 51,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"ename": "ValueError",
|
|
"evalue": "Axis limits cannot be NaN or Inf",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
|
|
"\u001b[0;32m<ipython-input-51-0929f4931ae7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtxdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'pbar'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'P'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
|
"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, x, y, kind, ax, subplots, sharex, sharey, layout, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, secondary_y, sort_columns, **kwds)\u001b[0m\n\u001b[1;32m 2940\u001b[0m \u001b[0mfontsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfontsize\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolormap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolormap\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtable\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2941\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2942\u001b[0;31m sort_columns=sort_columns, **kwds)\n\u001b[0m\u001b[1;32m 2943\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplot_frame\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2944\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36mplot_frame\u001b[0;34m(data, x, y, kind, ax, subplots, sharex, sharey, layout, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, secondary_y, sort_columns, **kwds)\u001b[0m\n\u001b[1;32m 1971\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1972\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msort_columns\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msort_columns\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1973\u001b[0;31m **kwds)\n\u001b[0m\u001b[1;32m 1974\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1975\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m_plot\u001b[0;34m(data, x, y, subplots, ax, kind, **kwds)\u001b[0m\n\u001b[1;32m 1799\u001b[0m \u001b[0mplot_obj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mklass\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubplots\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1800\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1801\u001b[0;31m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1802\u001b[0m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1803\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36mgenerate\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 249\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compute_plot_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 250\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setup_subplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 251\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_plot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 252\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_add_table\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 253\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_legend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m_make_plot\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 999\u001b[0m \u001b[0mlines\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_all_lines\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1000\u001b[0m \u001b[0mleft\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mright\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_xlim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlines\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1001\u001b[0;31m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xlim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mleft\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mright\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1002\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1003\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0mclassmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36mset_xlim\u001b[0;34m(self, left, right, emit, auto, xmin, xmax)\u001b[0m\n\u001b[1;32m 3226\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_process_unit_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mxdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mleft\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mright\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3227\u001b[0m \u001b[0mleft\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_converted_limits\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mleft\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconvert_xunits\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3228\u001b[0;31m \u001b[0mright\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_converted_limits\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mright\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconvert_xunits\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3229\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3230\u001b[0m \u001b[0mold_left\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mold_right\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_xlim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m_validate_converted_limits\u001b[0;34m(self, limit, convert)\u001b[0m\n\u001b[1;32m 3137\u001b[0m if (isinstance(converted_limit, Real)\n\u001b[1;32m 3138\u001b[0m and not np.isfinite(converted_limit)):\n\u001b[0;32m-> 3139\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Axis limits cannot be NaN or Inf\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3140\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mconverted_limit\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3141\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mValueError\u001b[0m: Axis limits cannot be NaN or Inf"
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]
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},
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{
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"data": {
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"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"txdf.plot(x='pbar',y='P')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sns.jointplot(x=\"pbar\", y=\"P\",kind=\"reg\", data=txdf.replace([np.inf, -np.inf], np.nan).dropna(how=\"all\")) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"txdf['P_err'] = txdf.P-txdf.pbar"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sns.jointplot(x=\"agent\", y=\"P_err\",kind=\"reg\", data=txdf.replace([np.inf, -np.inf], np.nan).dropna(how=\"all\")) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sns.jointplot(x='index',y=\"P\",kind=\"reg\", data=txdf.replace([np.inf, -np.inf], np.nan).dropna(how=\"all\").reset_index()) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sns.scatterplot(x='index',y=\"P_err\", hue = \"pbar\", data=txdf.replace([np.inf, -np.inf], np.nan).dropna(how=\"all\").reset_index()) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sns.scatterplot(x='index',y=\"P\", hue = \"pbar\", data=txdf.replace([np.inf, -np.inf], np.nan).dropna(how=\"all\").reset_index()) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"txdf['P_err_factor'] = txdf.P/txdf.pbar"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sns.scatterplot(x='index',y=\"P_err_factor\", hue = \"pbar\", data=txdf.replace([np.inf, -np.inf], np.nan).dropna(how=\"all\").reset_index()) \n",
|
|
"plt.gca().set_yscale('log')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"tx_summary=tdf[['agent','mech','pbar','amt']].groupby(['agent','mech']).agg(['median','count']).T.iloc[:-1].T"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"tx_summary"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"tx_summary.pbar['median'].plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sdf['P'].plot(logx=True)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sdf['P'].plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sdf.F.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"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": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.hist(bond_amts, bins=20)\n",
|
|
"plt.yscale('log')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.hist(burn_amts, bins=20)\n",
|
|
"plt.yscale('log')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['invariant'] = rdf.supply.apply(lambda x: x**kappa)/rdf.reserve"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"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": null,
|
|
"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": null,
|
|
"metadata": {
|
|
"scrolled": false
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.hist(rdf.iloc[-1].holdings)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['gini_h'] = rdf.holdings.apply(gini)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf.gini_h.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.hist(rdf.iloc[-1].tokens)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['gini_s'] = rdf.tokens.apply(gini)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf.gini_s.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf.tokens.apply(np.count_nonzero).plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['asset_value'] = rdf.holdings + rdf.spot_price*rdf.tokens"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.hist(rdf.iloc[-1].asset_value)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['gini'] = rdf.asset_value.apply(gini)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf.gini.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"rdf['pref_gap'] = (rdf.prices - rdf.spot_price)/rdf.spot_price"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.hist(rdf.iloc[-7:].pref_gap, bins=7)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.6.8"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|