def prep_graph(graph_files, walker_path):
# copy graph files
cwd = os.getcwd()
for ii in graph_files:
file_name = os.path.basename(ii)
abs_path = os.path.abspath(ii)
rel_path = os.path.relpath(abs_path, os.path.abspath(walker_path))
checkfile(walker_path + file_name)
os.chdir(walker_path)
os.symlink(rel_path, walker_path + file_name)
os.chdir(cwd)
def make_conf(nconf,
res_path,
walker_idx,
walker_path,
sel_idx,
jdata,
mol_path,
conf_start=0,
conf_every=1,
custom_mdp=None):
mol_path = os.path.abspath(mol_path) + "/"
mol_files = ["topol.top"]
nsteps = jdata["res_nsteps"]
frame_freq = jdata["res_frame_freq"]
dt = jdata["res_dt"]
temperature = jdata["res_temperature"]
itp_files = glob.glob(mol_path + "*.itp")
for ii in range(conf_start, nconf, conf_every):
work_path = res_path + ((walker_format + ".%06d") %
(walker_idx, sel_idx[ii])) + "/"
os.makedirs(work_path)
make_grompp(work_path + "grompp.mdp",
"res",
nsteps,
frame_freq,
temperature=temperature,
dt=dt,
define="",
custom_mdp=custom_mdp)
for jj in mol_files:
checkfile(work_path + jj)
shutil.copy(mol_path + jj, work_path)
for itp_ in itp_files:
shutil.copy(itp_, work_path)
conf_file = walker_path + enhc_out_conf + \
("conf%d.gro" % sel_idx[int(ii)])
checkfile(work_path + "conf.gro")
tmp_cwd = os.getcwd()
os.chdir(work_path)
os.symlink(os.path.relpath(conf_file), "conf.gro")
os.chdir(tmp_cwd)
def make_enhc(iter_index,
json_file,
graph_files,
mol_dir,
cv_file,
base_dir='./',
custom_mdp=None):
base_dir = os.path.abspath(base_dir) + "/"
json_file = os.path.abspath(json_file)
cv_file = os.path.abspath(cv_file)
graph_files.sort()
fp = open(json_file, 'r')
jdata = json.load(fp)
fp.close()
numb_walkers = jdata["numb_walkers"]
enhc_trust_lvl_1 = jdata["bias_trust_lvl_1"]
enhc_trust_lvl_2 = jdata["bias_trust_lvl_2"]
nsteps = jdata["bias_nsteps"]
frame_freq = jdata["bias_frame_freq"]
num_of_cluster_threshold = jdata["num_of_cluster_threshold"]
dt = jdata["bias_dt"]
temperature = jdata["bias_temperature"]
iter_name = make_iter_name(iter_index)
work_path = base_dir + iter_name + "/" + enhc_name + "/"
mol_path = os.path.abspath(mol_dir) + "/"
conf_list = glob.glob(mol_path + "*gro")
conf_list.sort()
assert (len(conf_list) >=
numb_walkers), "not enough conf files in mol dir %s" % mol_path
create_path(work_path)
mol_files = ["topol.top"]
for walker_idx in range(numb_walkers):
walker_path = work_path + make_walker_name(walker_idx) + "/"
create_path(walker_path)
make_grompp(walker_path + "grompp.mdp", "bias", nsteps,
frame_freq, temperature=temperature, dt=dt, define='', custom_mdp=custom_mdp)
# make_grompp(walker_path + "grompp_restraint.mdp", "res", nsteps, frame_freq, temperature=temperature, dt=dt, define='-DPOSRE')
for ii in mol_files:
checkfile(walker_path + ii)
shutil.copy(mol_path + ii, walker_path)
# copy conf file
conf_file = conf_list[walker_idx]
checkfile(walker_path + "conf.gro")
shutil.copy(conf_file, walker_path + "conf.gro")
checkfile(walker_path + "conf_init.gro")
shutil.copy(conf_file, walker_path + "conf_init.gro")
# if have prev confout.gro, use as init conf
if iter_index > 0:
prev_enhc_path = base_dir + \
make_iter_name(iter_index-1) + "/" + enhc_name + \
"/" + make_walker_name(walker_idx) + "/"
prev_enhc_path = os.path.abspath(prev_enhc_path) + "/"
if os.path.isfile(prev_enhc_path + "confout.gro"):
os.remove(walker_path + "conf.gro")
rel_prev_enhc_path = os.path.relpath(
prev_enhc_path + "confout.gro", walker_path)
os.symlink(rel_prev_enhc_path, walker_path + "conf.gro")
else:
raise RuntimeError(
"cannot find prev output conf file " + prev_enhc_path + 'confout.gro')
log_task("use conf of iter " + make_iter_name(iter_index -
1) + " walker " + make_walker_name(walker_idx))
enhc_trust_lvl_1, enhc_trust_lvl_2 = adjust_lvl(
prev_enhc_path, num_of_cluster_threshold, jdata)
np.savetxt(walker_path+'trust_lvl1.dat',
[enhc_trust_lvl_1], fmt='%.6f')
make_plumed(walker_path, "dpbias", conf_file, cv_file)
make_plumed(walker_path, "bf", conf_file, cv_file)
prep_graph(graph_files, walker_path)
# config plumed
graph_list = get_graph_list(graph_files)
conf_enhc_plumed(walker_path + enhc_plm, "enhc", graph_list, enhc_trust_lvl_1=enhc_trust_lvl_1,
enhc_trust_lvl_2=enhc_trust_lvl_2, frame_freq=frame_freq, enhc_out_plm=enhc_out_plm)
conf_enhc_plumed(walker_path + enhc_bf_plm, "bf", graph_list,
frame_freq=frame_freq, enhc_out_plm=enhc_out_plm)
if len(graph_list) == 0:
log_task("brute force MD without NN acc")
else:
log_task("use NN model(s): " + graph_list)
log_task("set trust l1 and l2: %f %f" %
(enhc_trust_lvl_1, enhc_trust_lvl_2))
print("Enhanced sampling has prepared.")