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