def test_forest_age(forest_age_range=(3, 10, 50, 100), num_sim=50):
dfs = []
for age in forest_age_range:
series = []
for n in range(1, num_sim + 1):
P, R = forest(S=age)
vi = solve_mdp.solve_mdp_by_iteration(ValueIteration, P, R, max_iter=n)
series.append(vi)
df = pd.concat(series, axis=1).T
dfs.append(df)
return pd.concat(dfs)
def test_discount_factor(discount_factor_range=(0.1, 0.2, 0.3, 0.5, 0.7, 0.9, 0.99), num_sim=50):
dfs = []
for factor in discount_factor_range:
series = []
for n in range(1, num_sim + 1):
P, R = forest(S=50)
vi = solve_mdp.solve_mdp_by_iteration(ValueIteration, P, R, discount=factor, max_iter=n)
series.append(vi)
df = pd.concat(series, axis=1).T
dfs.append(df)
return pd.concat(dfs)
def test_discount_factor(transitions, rewards, discount_factor_range=(0.1, 0.2, 0.3, 0.5, 0.7, 0.9, 0.99), num_sim=50):
dfs = []
P, R = transitions, rewards
for factor in discount_factor_range:
series = []
for n in range(1, num_sim):
vi = solve_mdp.solve_mdp_by_iteration(ValueIteration, P, R, discount=factor, max_iter=n)
series.append(vi)
df = pd.concat(series, axis=1).T
dfs.append(df)
return pd.concat(dfs)
def test_fire_probability(fireprob_range=(0.01, 0.1, 0.2, 0.5, 0.8, 0.9, 0.99), num_sim=50):
dfs = []
for factor in fireprob_range:
series = []
for n in range(1, num_sim + 1):
P, R = forest(S=50, p=factor)
vi = solve_mdp.solve_mdp_by_iteration(ValueIteration, P, R, max_iter=n)
vi = vi.append(pd.Series(factor, index=["fire_probability"]))
series.append(vi)
df = pd.concat(series, axis=1).T
dfs.append(df)
return pd.concat(dfs)
