[research/lotterysim/reports] added cascade control report WIP

script/research/lotterysim/acc_vs_staked_ratio.py

@@ -10,24 +10,25 @@ ERC20DRK=2.1*10**9
 NODES=100
 plot = []
 EXPS=10
-for portion in range(1,11):
+for nodes in numpy.linspace(1,NODES, 5):
     accs = []
     for _ in range(EXPS):
         darkies = []
         egalitarian = ERC20DRK/NODES
-        darkies += [ Darkie(random.gauss(egalitarian, egalitarian*0.1), commit=False, strategy=Hodler(EPOCH_LENGTH)) for id in range(int(NODES/portion)) ]
+        darkies += [ Darkie(random.gauss(egalitarian, egalitarian*0.1), strategy=random_strategy(EPOCH_LENGTH)) for id in range(int(nodes)) ]
         #darkies += [Darkie() for _ in range(NODES*2)]
         airdrop = ERC20DRK
+        dt = DarkfiTable(airdrop, RUNNING_TIME, CONTROLLER_TYPE_DISCRETE, kp=0.005999999999989028, ki=-0.005999999985257798, kd=0.01299999999999478, r_kp=0.47, r_ki=7.2, r_kd=21.33)
+        for darkie in darkies:
+            dt.add_darkie(darkie)
+        acc, apy, reward, staked_ratio, apr = dt.background(rand_running_time=False)
+        accs += [acc]
         effective_airdrop  = 0
         for darkie in darkies:
             effective_airdrop+=darkie.stake
+        effective_airdrop*=float(staked_ratio)
         stake_portion = effective_airdrop/airdrop*100
         print("network airdrop: {}, staked token: {}/{}% on {} nodes".format(airdrop, effective_airdrop, stake_portion, len(darkies)))
-        dt = DarkfiTable(airdrop, RUNNING_TIME, CONTROLLER_TYPE_DISCRETE, kp=0.005999999999989028, ki=-0.005999999985257798, kd=0.01299999999999478, r_kp=0.051, r_ki=-0.3229, r_kd=-0.008)
-        for darkie in darkies:
-            dt.add_darkie(darkie)
-        acc, apy, reward, staked_ratio, apr = dt.background(rand_running_time=False)
-        accs += [acc]
     avg_acc = sum(accs)/EXPS*100
     plot+=[(stake_portion, avg_acc)]
 

script/research/lotterysim/core/constants.py

@@ -19,7 +19,7 @@ ONE_YEAR = Num(365.25*24*60*60/SLOT)
 
 TARGET_APR = Num(0.12)
 
-PRIMARY_REWARD_TARGET = 0.8 # staked ratio
+PRIMARY_REWARD_TARGET = 0.5 # staked ratio
 SECONDARY_LEAD_TARGET = 1 #number of lead per slot
 
 EPSILON = 1

script/research/lotterysim/core/darkie.py

@@ -11,7 +11,6 @@ class Darkie():
         self.f = None
         self.epoch_len=epoch_len # epoch length during which the stake is static
         self.strategy = strategy
-        print('strategy type: {}'.format(strategy.type))
         self.slot = 0
         self.won_hist = [] # winning history boolean
 

script/research/lotterysim/discrete_instance.py

@@ -9,7 +9,7 @@ import math
 os.system("rm log/*_feedback.hist; rm log/*_output.hist")
 
 RUNNING_TIME = int(input("running time:"))
-NODES=100
+NODES=1000
 
 if __name__ == "__main__":
     egalitarian = ERC20DRK/NODES
@@ -25,7 +25,7 @@ if __name__ == "__main__":
     for darkie in darkies:
         effective_airdrop+=darkie.stake
     print("network airdrop: {}, staked token: {}/{}% on {} nodes".format(airdrop, effective_airdrop, effective_airdrop/airdrop*100, len(darkies)))
-    dt = DarkfiTable(airdrop, RUNNING_TIME, CONTROLLER_TYPE_DISCRETE, kp=-0.010399999999938556, ki=-0.0365999996461878, kd=0.03840000000000491,  r_kp=0.13, r_ki=-0.5, r_kd=-0.5)
+    dt = DarkfiTable(airdrop, RUNNING_TIME, CONTROLLER_TYPE_DISCRETE, kp=-0.010399999999938556, ki=-0.0365999996461878, kd=0.03840000000000491,  r_kp=0.41, r_ki=5.65, r_kd=89.23)
     for darkie in darkies:
         dt.add_darkie(darkie)
     acc, avg_apy, avg_reward, stake_ratio, avg_apr = dt.background(rand_running_time=False)
@@ -47,8 +47,8 @@ if __name__ == "__main__":
     shifted_aprs = [apr - mu for apr in aprs]
     plt.plot([apr*100 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)
-    sigma = math.sqrt(float(variance))
     print('mu: {}, variance: {}'.format(str(mu), str(variance)))