Not Defined Variable In Numpy
i'm trying to run the code below but i get the same when running the code. The issue is that q seems to not be defined but this should not be true.
#Question 1 #i) #Defining the parameters using SimpleNameSpace. par = Parameters par = SimpleNamespace() par.y = 1 #assets par.p = 0.2 #probability par.theta = -2 #elasticity #Defining utility function for agent def utility(z,par): return (z**(1+par.theta))/(1+par.theta) #Defining premium def premium(q,par): return par.p*q #Defining expected value #Note that z_1, z_2 represents first and second part of the objective function - just in a compressed version def exp_value (i,q,par): z_1 = par.y-i+q-premium(q,par) z_2 = par.y-premium(q,par) return par.p*utility(z_1,par)+(1-par.p)*utility(z_2,par) def opt_q(i,q,par): obj = lambda q: -exp_value(i,q,par) #defining the objective function solution = optimize.minimize_scalar(obj, bounds=(0,0.9), method="bounded") #bounded solution within [0.01, 0.9] q = solution.x return q for i in np.linspace(0.01,0.9,num=100): res = opt_q(i,q,par) print(res)
You are getting the
NameError because you are not passing the
opt_q in the last for-loop. Since it is already defined inside
opt_q just remove
q from its arguments and don't pass it in the for-loop as well as follows:
def opt_q(i,par): obj = lambda q: -exp_value(i,q,par) #defining the objective function solution = minimize_scalar(obj, bounds=(0,0.9), method="bounded") #bounded solution within [0.01, 0.9] q = solution.x return q for i in np.linspace(0.01,0.9,num=100): res = opt_q(i,par) print(res)
This resolves your issue.
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