import numpy as np
import ostracism
if __name__ == "__main__":
# mu, sigma case analysis
mu = np.float64(sys.argv[1])
s = np.float64(sys.argv[2])
# N case analysis
#s = np.float64(sys.argv[1])
#N = int(sys.argv[2])
#case = sys.argv[3]
model = ostracism.SocialLearningSim(N=5,
M=100,
c=1.,
r=3.,
G=.7,
B=.7,
gamma=.7,
beta=.7,
sigma=1.,
omega=0,
mu=mu,
s=s,
compulsory=False,
SOP=False,
case="competition")
model.runAnalyticalSim()
import sys
import numpy as np
import ostracism
if __name__ == "__main__":
# mu, sigma case analysis
mu = np.float64(sys.argv[1])
s = np.float64(sys.argv[2])
# N case analysis
#s = np.float64(sys.argv[1])
#N = int(sys.argv[2])
#case = sys.argv[3]
model = ostracism.SocialLearningSim(N = 5, M = 100, c = 1., r = 3., G = .7, B = .7, gamma = .7, beta = .7, sigma = 1., omega = 0, mu = mu, s = s, compulsory = True, SOP=True, case="pool")
model.runAnalyticalSim()