indices = np.round(indices)
indices = indices.astype(int)
return indices
free_energies_pmfs_files = [
os.path.join(args.pull_data_dir, f)
for f in args.free_energies_pmfs_files.split()
]
print("free_energies_pmfs_files", free_energies_pmfs_files)
print("us_fe_file", args.us_fe_file)
print("us_pmf_file", args.us_pmf_file)
fe_us = pickle.load(open(args.us_fe_file, "r"))
fe_us["fe"] = first_to_zero(fe_us["fe"])
if args.system_type == "asymmetric":
fe_us["lambdas"] = replicate(fe_us["lambdas"],
"as_is",
exclude_last_in_first_half=True)
fe_us["fe"] = replicate(fe_us["fe"],
"as_is",
exclude_last_in_first_half=True)
pmf_us = dict()
pmf_us["pmf"] = np.loadtxt(args.us_pmf_file)[:, 1]
pmf_us["pmf"] *= BETA # kcal/mol to KT/mol or RT
pmf_us["pmf"] = min_to_zero(pmf_us["pmf"])
data_estimator_pairs = args.data_estimator_pairs.split()
if len(data_estimator_pairs) != len(free_energies_pmfs_files):
fes_pmfs_files = {}
for label, matching in zip(data_estimator_pairs, fes_pmfs_file_matching):
fes_pmfs_files[label] = glob.glob(os.path.join(args.data_dir, matching))
number_of_files = [len(files) for files in fes_pmfs_files.values()]
if np.unique(number_of_files).shape[0] != 1:
raise ValueError("different labels do not have the same number of files")
num_fe_file = os.path.join(args.data_dir, args.num_fe_file)
print("num_fe_file", num_fe_file)
exact_pmf_file = os.path.join(args.data_dir, args.exact_pmf_file)
print("exact_pmf_file", exact_pmf_file)
fe_num = pickle.load(open(num_fe_file, "r"))
fe_num["fe"] = first_to_zero(fe_num["fe"])
pmf_exact = pickle.load(open(exact_pmf_file, "r"))
pmf_exact["pmf"] = min_to_zero(pmf_exact["pmf"])
fe_rmse = {}
pmf_rmse = {}
for label in data_estimator_pairs:
print("label", label)
fe_rmse[label] = []
pmf_rmse[label] = []
for fes_pmfs_file in fes_pmfs_files[label]:
print("processing file", fes_pmfs_file)
data = pickle.load(open(fes_pmfs_file, "r"))