def general_test():
# Levels and repetitions
levels = 4
repetitions = [1000, 500, 1000, 1000]
MLMCprob = MLMC_Problem(binProblem, samp, lvl_maker)
MLMCsolv = MLMC_Solver(MLMCprob, levels, repetitions)
estimate = MLMCsolv.solve()
print(estimate)
def general_test_serial():
# Levels and repetitions
s = time.time()
levels = 2
repetitions = [100, 100]
MLMCprob = MLMC_Problem(problemClass, samp, lvl_maker)
MLMCsolv = MLMC_Solver(MLMCprob, levels, repetitions)
estimate, lvls = MLMCsolv.solve()
print("Total Time Taken: ", time.time() - s)
print(estimate)
print(lvls)
def general_test_para():
# Levels and repetitions
s = time.time()
levels = 2
repetitions = [64, 64]
limits = [1, 1]
MLMCprob = MLMC_Problem(problemClass, samp, lvl_maker)
MLMCsolv = MLMC_Solver(MLMCprob,
levels,
repetitions,
comm=MPI.COMM_WORLD,
comm_limits=limits)
estimate, lvls = MLMCsolv.solve()
if MPI.COMM_WORLD.Get_rank() == 0:
print("Total Time Taken: ", time.time() - s)
print(estimate)
print(list(lvls))
def plotting():
import matplotlib.pyplot as plt
xs = np.linspace(0, 1, 1001)
g, _ = sampler(None)
plt.plot(xs, g(xs), linewidth=0.5)
xf, xc = level_maker(0, 1)
plt.plot(xc, g(xc), 'x-')
plt.plot(xf, g(xf), '+-')
plt.show()
# Levels and repetitions
levels = 3
repetitions = [100, 14, 2]
MLMCprob = MLMC_Problem(SimpleProblem, sampler, level_maker)
MLMCsolv = MLMC_Solver(MLMCprob, levels, repetitions)
estimate = MLMCsolv.solve()
print(estimate)
reps = levels * repetitions[-1]
xf, _ = level_maker(2, -1)
prob = SimpleProblem(xf)
total = 0
for _ in range(reps):
total += prob.solve(sampler(None)[0])
print(total / reps)