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https://github.com/darkrenaissance/darkfi.git
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40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
from core.lottery import *
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import os
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import numpy
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from matplotlib import pyplot as plt
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os.system("rm log/f_output.hist; rm log/f_feedback.hist")
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RUNNING_TIME = int(input("running time:"))
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ERC20DRK=2.1*10**9
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NODES=1000
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plot = []
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EXPS=10
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for nodes in numpy.concatenate((numpy.array([1,5]), numpy.linspace(10,NODES, 10))):
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accs = []
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for _ in range(EXPS):
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darkies = []
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egalitarian = ERC20DRK/NODES
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darkies += [ Darkie(random.gauss(0, 0), strategy=random_strategy(EPOCH_LENGTH)) for id in range(int(nodes)) ]
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airdrop = ERC20DRK
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dt = DarkfiTable(0, RUNNING_TIME, CONTROLLER_TYPE_DISCRETE, kp=-0.0104, ki=-0.0366, kd=0.0384, r_kp=-2.53, r_ki=29.5, r_kd=53.77)
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for darkie in darkies:
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dt.add_darkie(darkie)
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acc, apy, reward, staked_ratio, apr = dt.background(rand_running_time=False)
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accs += [acc]
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effective_airdrop = 0
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for darkie in darkies:
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effective_airdrop+=darkie.stake
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effective_airdrop*=float(staked_ratio)
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stake_portion = effective_airdrop/airdrop*100
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print("network airdrop: {}, staked token: {}/{}% on {} nodes".format(airdrop, effective_airdrop, stake_portion, len(darkies)))
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avg_acc = sum(accs)/EXPS
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plot+=[(stake_portion, avg_acc)]
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plt.plot([x[0] for x in plot], [x[1] for x in plot])
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plt.xlabel('drk staked %')
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plt.ylabel('accuracy %')
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plt.savefig('img'+os.sep+'stake_pi.png')
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plt.show()
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