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- import os
- import numpy
- from core.strategy import *
- from core.lottery import *
- import matplotlib.pyplot as plt
- import scipy.stats as stats
- import math
- from draw import draw
- os.system("rm log/*_feedback.hist; rm log/*_output.hist; rm log/darkie*.log")
- RUNNING_TIME = int(input("running time:"))
- if __name__ == "__main__":
- mu = PREMINT/NODES
- darkies = [Darkie(random.gauss(mu, mu/10), strategy=LinearStrategy(EPOCH_LENGTH)) for _ in range(NODES)]
- #dt = DarkfiTable(0, RUNNING_TIME, CONTROLLER_TYPE_DISCRETE, kp=-0.010399999999938556, ki=-0.0365999996461878, kd=0.03840000000000491, r_kp=-2.53, r_ki=29.5, r_kd=53.77)
- dt = DarkfiTable(PREMINT, RUNNING_TIME, CONTROLLER_TYPE_DISCRETE, kp=-0.010399999999938556, ki=-0.0365999996461878, kd=0.03840000000000491, r_kp=-0.719, r_ki=1.6, r_kd=0.1)
- for darkie in darkies:
- dt.add_darkie(darkie)
- acc, avg_apy, avg_reward, stake_ratio, avg_apr = dt.background(rand_running_time=False)
- #sum_zero_stake = sum([darkie.stake for darkie in darkies[NODES:]])
- print('acc: {}, avg(apr): {}%, avg(reward): {}, stake_ratio: {}'.format(acc, round(avg_apr*100,2), avg_reward, stake_ratio))
- #print('total stake of 0mint: {}, ratio: {}'.format(sum_zero_stake, sum_zero_stake/ERC20DRK))
- dt.write()
- aprs = []
- fortuners = 0.0
- for darkie in darkies:
- aprs += [float(darkie.apr_scaled_to_runningtime())]
- if darkie.initial_stake[-1] - darkie.initial_stake[0] > 0:
- fortuners+=1
- print('fortuners: {}'.format(str(fortuners/len(darkies))))
- # distribution of aprs
- aprs = sorted(aprs)
- mu = float(sum(aprs)/len(aprs))
- shifted_aprs = [apr - mu for apr in aprs]
- plt.plot([round(apr*100,2) for apr in aprs])
- plt.title('annual percentage return, avg: {:}'.format(mu*100))
- plt.savefig('img/apr_distribution.png')
- plt.show()
- variance = sum(shifted_aprs)/(len(aprs)-1)
- print('mu: {}, variance: {}'.format(str(mu), str(variance)))
- draw()
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