def run():
print(datetime.datetime.now(), sys.argv[0], " begin")
path_to_input = os.path.join(path_to_trackml, "train_1")
path_to_out = "out_" + sys.argv[0].split(".")[0]
niter = 150
num_step = 5
eps0s = np.linspace(0.0010, 0.0400, num_step)
th_lens = [13, 10, 6, 3, 3]
num_exts = [0 for _ in range(num_step)]
calc_steps(niter, eps0s, th_lens, num_exts, path_to_out)
print(datetime.datetime.now(), sys.argv[0], " end")
def run():
print(datetime.datetime.now(), sys.argv[0], " begin")
path_to_input = os.path.join(path_to_trackml, "train_1")
path_to_out = "out_" + sys.argv[0].split(".")[0]
niter = 150
num_step = 5
eps0s = list(np.linspace(0.001, 0.008, num_step - 1)) + [0.030]
th_lens = [13, 10, 6, 3, 3]
num_exts = [0, 0, 0, 0, 0]
calc_steps(niter, eps0s, th_lens, num_exts, path_to_out)
print(datetime.datetime.now(), sys.argv[0], " end")
def run():
print(datetime.datetime.now(), sys.argv[0], " begin")
path_to_input = os.path.join(path_to_trackml, "train_1")
path_to_out = "out_" + sys.argv[0].split(".")[0]
niter = 150
num_step = 5
th_len_1 = 13
th_len_N = 3
eps0s = list(np.logspace(np.log10(0.001), np.log10(0.008),
num_step - 1)) + [0.0400]
th_lens = [int(x) for x in np.linspace(th_len_1, th_len_N, num_step - 1)]
th_lens.append(th_lens[-1])
num_exts = [0 for _ in range(num_step)]
calc_steps(niter, eps0s, th_lens, num_exts, path_to_out)
print(datetime.datetime.now(), sys.argv[0], " end")
def Fun4BO(eps1, eps2, eps3, eps4, eps5):
eps0s = [eps1, eps2, eps3, eps4, eps5]
th_lens = [13, 10, 6, 3, 3]
num_exts = [0, 0, 0, 0, 0]
score = calc_steps(niter, eps0s, th_lens, num_exts, path_to_out)
return score
