def test_reward():
ac = mfg_ac2.actor_critic()
P = np.array([[1, 3, 3], [4, 5, 6], [7, 8, 9]])
print(P)
pi = np.array([0.1, 0.2, 0.7])
print(pi)
reward = ac.calc_reward(P, pi, 3)
print("Reward", reward)
def time_value(n):
d = 47
ac = mfg_ac2.actor_critic(d=d)
num_features = int((d + 1) * d / 2 + d + 1)
ac.w = np.ones(num_features)
pi = np.random.rand(d)
t_start = time.time()
for j in range(n):
value = ac.calc_value(pi)
t_end = time.time()
print("Time taken for %d runs of calc_value" % n, (t_end - t_start))
print("Value", value)
def time_reward(n):
ac = mfg_ac2.actor_critic()
# P = np.array([[1,3,3,4],[4,5,6,6],[7,8,9,10],[1,2,3,4]])
P = np.ones([47, 47])
# pi = np.array([0.1,0.2,0.6,0.1])
pi = np.zeros(47)
pi[0] = 1
t_start = time.time()
for j in range(n):
reward = ac.calc_reward(P, pi, 47)
t_end = time.time()
print("Time taken for %d runs of calc_reward" % n, (t_end - t_start))
print("Reward", reward)
def test_value():
d = 3
ac = mfg_ac2.actor_critic(d=d)
num_features = int((d + 1) * d / 2 + d + 1)
ac.w = np.ones(num_features)
print("weights")
print(ac.w)
pi = np.array([0.1, 0.2, 0.7])
print("pi")
print(pi)
value = ac.calc_value(pi)
# vec_features = ac.calc_features(pi)
# value = vec_features.dot(ac.w)
print("value", value)
def test_pi0(indir):
ac = mfg_ac2.actor_critic(d=20)
ac.init_pi0(path_to_dir='./' + indir)
print(ac.mat_pi0)
import numpy as np
import mfg_ac2
import time
import os
ac = mfg_ac2.actor_critic(theta=10, shift=0.4, d=4)
def test_pi0(indir):
ac = mfg_ac2.actor_critic(d=20)
ac.init_pi0(path_to_dir='./' + indir)
print(ac.mat_pi0)
def test_action():
pi = np.array([0.7, 0.09, 0.01, 0.2])
print("pi")
print(pi)
print("Sum of pi", np.sum(pi))
P = ac.sample_action(pi)
print("P matrix")
print(P)
print("Row 1 sum", np.sum(P[1, :]))
print("Col 3 sum", np.sum(P[:, 3]))
print("New pi")
pi_next = np.transpose(P).dot(pi)