def npt_equi_conf(npt_name):
thermo_file = os.path.join(npt_name, 'log.lammps')
dump_file = os.path.join(npt_name, 'dump.equi')
j_file = os.path.join(npt_name, 'in.json')
jdata = json.load(open(j_file))
stat_skip = jdata['stat_skip']
stat_bsize = jdata['stat_bsize']
data = get_thermo(thermo_file)
lx, lxe = block_avg(data[:, 8], skip=stat_skip, block_size=stat_bsize)
ly, lye = block_avg(data[:, 9], skip=stat_skip, block_size=stat_bsize)
lz, lze = block_avg(data[:, 10], skip=stat_skip, block_size=stat_bsize)
xy, xye = block_avg(data[:, 11], skip=stat_skip, block_size=stat_bsize)
xz, xze = block_avg(data[:, 12], skip=stat_skip, block_size=stat_bsize)
yz, yze = block_avg(data[:, 13], skip=stat_skip, block_size=stat_bsize)
print('~~~', lx, ly, lz, xy, xz, yz)
last_dump = get_last_dump(dump_file).split('\n')
sys_data = system_data(last_dump)
sys_data['cell'][0][0] = lx
sys_data['cell'][1][1] = ly
sys_data['cell'][2][2] = lz
sys_data['cell'][1][0] = xy
sys_data['cell'][2][0] = xz
sys_data['cell'][2][1] = yz
conf_lmp = from_system_data(sys_data)
return conf_lmp
def _compute_thermo(lmplog, natoms, stat_skip, stat_bsize):
# print(3939, natoms)
data = get_thermo(lmplog)
ea, ee = block_avg(data[:, 3], skip=stat_skip, block_size=stat_bsize)
ha, he = block_avg(data[:, 4], skip=stat_skip, block_size=stat_bsize)
ta, te = block_avg(data[:, 5], skip=stat_skip, block_size=stat_bsize)
pa, pe = block_avg(data[:, 6], skip=stat_skip, block_size=stat_bsize)
va, ve = block_avg(data[:, 7], skip=stat_skip, block_size=stat_bsize)
lxx, lxxe = block_avg(data[:, 8], skip=stat_skip, block_size=stat_bsize)
lyy, lyye = block_avg(data[:, 9], skip=stat_skip, block_size=stat_bsize)
lzz, lzze = block_avg(data[:, 10], skip=stat_skip, block_size=stat_bsize)
lxy, lxye = block_avg(data[:, 11], skip=stat_skip, block_size=stat_bsize)
lxz, lxze = block_avg(data[:, 12], skip=stat_skip, block_size=stat_bsize)
lyz, lyze = block_avg(data[:, 13], skip=stat_skip, block_size=stat_bsize)
pxx, pxxe = block_avg(data[:, 14], skip=stat_skip, block_size=stat_bsize)
pyy, pyye = block_avg(data[:, 15], skip=stat_skip, block_size=stat_bsize)
pzz, pzze = block_avg(data[:, 16], skip=stat_skip, block_size=stat_bsize)
pxy, pxye = block_avg(data[:, 17], skip=stat_skip, block_size=stat_bsize)
pxz, pxze = block_avg(data[:, 18], skip=stat_skip, block_size=stat_bsize)
pyz, pyze = block_avg(data[:, 19], skip=stat_skip, block_size=stat_bsize)
thermo_info = {}
thermo_info['p'] = pa
thermo_info['p_err'] = pe
thermo_info['v'] = va / natoms
thermo_info['v_err'] = ve / np.sqrt(natoms)
thermo_info['e'] = ea / natoms
thermo_info['e_err'] = ee / np.sqrt(natoms)
thermo_info['t'] = ta
thermo_info['t_err'] = te
thermo_info['h'] = ha / natoms
thermo_info['h_err'] = he / np.sqrt(natoms)
unit_cvt = 1e5 * (1e-10**3) / pc.electron_volt
thermo_info['pv'] = pa * va * unit_cvt / natoms
thermo_info['pv_err'] = pe * va * unit_cvt / np.sqrt(natoms)
thermo_info['lxx'] = lxx
thermo_info['lxx_err'] = lxxe
thermo_info['lyy'] = lyy
thermo_info['lyy_err'] = lyye
thermo_info['lzz'] = lzz
thermo_info['lzz_err'] = lzze
thermo_info['lxy'] = lxy
thermo_info['lxy_err'] = lxye
thermo_info['lxz'] = lxz
thermo_info['lxz_err'] = lxze
thermo_info['lyz'] = lyz
thermo_info['lyz_err'] = lyze
thermo_info['pxx'] = pxx
thermo_info['pxx_err'] = pxxe
thermo_info['pyy'] = pyy
thermo_info['pyy_err'] = pyye
thermo_info['pzz'] = pzz
thermo_info['pzz_err'] = pzze
thermo_info['pxy'] = pxy
thermo_info['pxy_err'] = pxye
thermo_info['pxz'] = pxz
thermo_info['pxz_err'] = pxze
thermo_info['pyz'] = pyz
thermo_info['pyz_err'] = pyze
return thermo_info
def _post_tasks(iter_name, step, natoms):
jdata = json.load(open(os.path.join(iter_name, 'in.json')))
stat_skip = jdata['stat_skip']
stat_bsize = jdata['stat_bsize']
all_tasks = glob.glob(os.path.join(iter_name, 'task.[0-9]*'))
all_tasks.sort()
ntasks = len(all_tasks)
all_lambda = []
all_dp_a = []
all_dp_e = []
all_msd_xyz = []
for ii in all_tasks:
log_name = os.path.join(ii, 'log.lammps')
data = get_thermo(log_name)
np.savetxt(os.path.join(ii, 'data'), data, fmt='%.6e')
dp_a, dp_e = block_avg(data[:, 8],
skip=stat_skip,
block_size=stat_bsize)
msd_xyz = data[-1, 12]
dp_a /= natoms
dp_e /= np.sqrt(natoms)
lmda_name = os.path.join(ii, 'lambda.out')
ll = float(open(lmda_name).read())
all_lambda.append(ll)
all_dp_a.append(dp_a)
all_dp_e.append(dp_e)
all_msd_xyz.append(msd_xyz)
all_lambda = np.array(all_lambda)
all_dp_a = np.array(all_dp_a)
all_dp_e = np.array(all_dp_e)
all_msd_xyz = np.array(all_msd_xyz)
de = all_dp_a
all_err = all_dp_e
all_print = []
# all_print.append(np.arange(len(all_lambda)))
all_print.append(all_lambda)
all_print.append(de)
all_print.append(all_err)
all_print.append(all_msd_xyz)
all_print = np.array(all_print)
np.savetxt(os.path.join(iter_name, 'hti.out'),
all_print.T,
fmt='%.8e',
header='lmbda dU dU_err msd_xyz')
diff_e, err = integrate(all_lambda, de, all_err)
sys_err = integrate_sys_err(all_lambda, de)
thermo_info = _compute_thermo(os.path.join(all_tasks[-1], 'log.lammps'),
natoms, stat_skip, stat_bsize)
return diff_e, [err, sys_err], thermo_info
def _compute_thermo(fname, natoms, stat_skip, stat_bsize):
data = get_thermo(fname)
ea, ee = block_avg(data[:, 3], skip=stat_skip, block_size=stat_bsize)
ha, he = block_avg(data[:, 4], skip=stat_skip, block_size=stat_bsize)
ta, te = block_avg(data[:, 5], skip=stat_skip, block_size=stat_bsize)
pa, pe = block_avg(data[:, 6], skip=stat_skip, block_size=stat_bsize)
va, ve = block_avg(data[:, 7], skip=stat_skip, block_size=stat_bsize)
thermo_info = {}
thermo_info['p'] = pa
thermo_info['p_err'] = pe
thermo_info['v'] = va / natoms
thermo_info['v_err'] = ve / np.sqrt(natoms)
thermo_info['e'] = ea / natoms
thermo_info['e_err'] = ee / np.sqrt(natoms)
thermo_info['h'] = ha / natoms
thermo_info['h_err'] = he / np.sqrt(natoms)
thermo_info['t'] = ta
thermo_info['t_err'] = te
unit_cvt = 1e5 * (1e-10**3) / pc.electron_volt
thermo_info['pv'] = pa * va * unit_cvt / natoms
thermo_info['pv_err'] = pe * va * unit_cvt / np.sqrt(natoms)
return thermo_info
def test_raise_err(self):
data1 = get_thermo(self.log_file)
data2 = np.loadtxt(self.data_file)
with self.assertRaises(AssertionError):
assert_almost_equal(data1, data2, decimal=10)
def test_normal(self):
data1 = get_thermo(self.log_file)
data2 = np.loadtxt(self.data_file)
assert_almost_equal(data1, data2, decimal=8)
def post_tasks_mbar(iter_name, jdata, Eo, natoms = None) :
equi_conf = jdata['equi_conf']
if natoms == None :
natoms = get_natoms(equi_conf)
if 'copies' in jdata :
natoms *= np.prod(jdata['copies'])
stat_skip = jdata['stat_skip']
stat_bsize = jdata['stat_bsize']
ens = jdata['ens']
path = jdata['path']
all_tasks = glob.glob(os.path.join(iter_name, 'task.[0-9]*'))
all_tasks.sort()
ntasks = len(all_tasks)
if 'nvt' in ens and path == 't' :
# TotEng
stat_col = 3
print('# TI in NVT along T path')
elif 'npt' in ens and (path == 't' or path == 't-ginv') :
# Enthalpy
stat_col = 4
print('# TI in NPT along T path')
elif 'npt' in ens and path == 'p' :
# volume
stat_col = 7
print('# TI in NPT along P path')
else:
raise RuntimeError('invalid ens or path setting' )
print('# natoms: %d' % natoms)
all_t = []
for ii in all_tasks :
thermo_name = os.path.join(ii, 'thermo.out')
tt = float(open(thermo_name).read())
all_t.append(tt)
all_t = np.array(all_t)
nt = all_t.size
ukn = None
nk = []
for ii in all_tasks :
log_name = os.path.join(ii, 'log.lammps')
data = get_thermo(log_name)
np.savetxt(os.path.join(ii, 'data'), data, fmt = '%.6e')
block_u = []
if path == 't' or path == 't-ginv':
this_e = data[stat_skip::1, stat_col]
nk.append(this_e.size)
for tt in all_t :
kt_in_ev = pc.Boltzmann * tt / pc.electron_volt
block_u.append(this_e / kt_in_ev)
elif path == 'p' :
this_e = data[stat_skip::1, 3]
this_v = data[stat_skip::1, 7]
nk.append(this_e.size)
# # cvt from barA^3 to eV
unit_cvt = 1e5 * (1e-10**3) / pc.electron_volt
temp = jdata['temps']
kt_in_ev = temp * pc.Boltzmann / pc.electron_volt
for tt in all_t :
block_u.append((this_e + tt * this_v * unit_cvt) / kt_in_ev)
else:
raise RuntimeError('invalid path setting' )
block_u = np.reshape(block_u, [nt, -1])
if ukn is None :
ukn = block_u
else :
ukn = np.concatenate((ukn, block_u), axis = 1)
nk = np.array(nk)
info0 = _compute_thermo(os.path.join(all_tasks[ 0], 'log.lammps'), natoms, stat_skip, stat_bsize)
info1 = _compute_thermo(os.path.join(all_tasks[-1], 'log.lammps'), natoms, stat_skip, stat_bsize)
_print_thermo_info(info0, 'at start point')
_print_thermo_info(info1, 'at end point')
mbar = pymbar.MBAR(ukn, nk)
Deltaf_ij, dDeltaf_ij, Theta_ij = mbar.getFreeEnergyDifferences()
Deltaf_ij = Deltaf_ij / natoms
dDeltaf_ij = dDeltaf_ij / np.sqrt(natoms)
all_temps = []
all_press = []
all_fe = []
all_fe_err = []
all_fe_sys_err = []
for ii in range(0, nt) :
if path == 't' or path == 't-ginv':
kt_in_ev = all_t[ii] * pc.Boltzmann / pc.electron_volt
e1 = (Eo / (all_t[0])) * all_t[ii] + Deltaf_ij[0,ii] * kt_in_ev
err = dDeltaf_ij[0,ii] * kt_in_ev
sys_err = 0
all_temps.append(all_t[ii])
if 'npt' in ens :
all_press.append(jdata['pres'])
elif path == 'p':
kt_in_ev = jdata['temps'] * pc.Boltzmann / pc.electron_volt
e1 = Eo + Deltaf_ij[0,ii] * kt_in_ev
err = dDeltaf_ij[0,ii] * kt_in_ev
sys_err = 0
all_temps.append(jdata['temp'])
all_press.append(all_t[ii])
else :
pass
all_fe.append(e1)
all_fe_err.append(err)
all_fe_sys_err.append(sys_err)
if 'nvt' == ens :
print('#%8s %15s %9s %9s' % ('T(ctrl)', 'F', 'stat_err', 'inte_err'))
for ii in range(len(all_temps)) :
print ('%9.2f %20.12f %9.2e %9.2e'
% (all_temps[ii], all_fe[ii], all_fe_err[ii], all_fe_sys_err[ii]))
elif 'npt' in ens :
print('#%8s %15s %15s %9s %9s' % ('T(ctrl)', 'P(ctrl)', 'F', 'stat_err', 'inte_err'))
for ii in range(len(all_temps)) :
print ('%9.2f %15.8e %20.12f %9.2e %9.2e'
% (all_temps[ii], all_press[ii], all_fe[ii], all_fe_err[ii], all_fe_sys_err[ii]))
def post_tasks(iter_name, jdata, Eo, Eo_err = 0, To = None, natoms = None, scheme = 'simpson', shift = 0.0) :
equi_conf = get_task_file_abspath(iter_name, jdata['equi_conf'])
if natoms == None :
natoms = get_natoms(equi_conf)
if 'copies' in jdata :
natoms *= np.prod(jdata['copies'])
stat_skip = jdata['stat_skip']
stat_bsize = jdata['stat_bsize']
ens = jdata['ens']
path = jdata['path']
all_tasks = glob.glob(os.path.join(iter_name, 'task.[0-9]*'))
all_tasks.sort()
ntasks = len(all_tasks)
all_t = []
all_e = []
all_e_err = []
integrand = []
integrand_err = []
all_enthalpy = []
all_msd_xyz = []
if 'nvt' in ens and path == 't' :
# TotEng
stat_col = 3
print('# TI in NVT along T path')
elif 'npt' in ens and (path == 't' or path == 't-ginv') :
# Enthalpy
stat_col = 4
print('# TI in NPT along T path')
elif 'npt' in ens and path == 'p' :
# volume
stat_col = 7
print('# TI in NPT along P path')
else:
raise RuntimeError('invalid ens or path setting' )
print('# natoms: %d' % natoms)
for ii in all_tasks :
# get T or P
thermo_name = os.path.join(ii, 'thermo.out')
tt = float(open(thermo_name).read())
all_t.append(tt)
# get energy stat
log_name = os.path.join(ii, 'log.lammps')
data = get_thermo(log_name)
np.savetxt(os.path.join(ii, 'data'), data, fmt = '%.6e')
ea, ee = block_avg(data[:, stat_col],
skip = stat_skip,
block_size = stat_bsize)
enthalpy, _ = block_avg(data[:, 5], skip = stat_skip, block_size = stat_bsize)
msd_xyz = data[-1, -1]
# COM corr
if path == 't' or path == 't-ginv' :
ea += 1.5 * pc.Boltzmann * tt / pc.electron_volt
# print('~~', tt, ea, 1.5 * pc.Boltzmann * tt / pc.electron_volt)
elif path == 'p' :
temp = jdata['temp']
ea += 1.5 * pc.Boltzmann * temp / pc.electron_volt
else :
raise RuntimeError('invalid path setting' )
# normalized by number of atoms
ea /= natoms
if path == 't' or path == 't-ginv':
ea -= shift
ee /= np.sqrt(natoms)
all_e.append(ea)
all_e_err.append(ee)
all_enthalpy.append(enthalpy)
all_msd_xyz.append(msd_xyz)
# gen integrand
if path == 't' or path == 't-ginv':
integrand.append(ea / (tt * tt))
integrand_err.append(ee / (tt * tt))
elif path == 'p' :
# cvt from barA^3 to eV
unit_cvt = 1e5 * (1e-10**3) / pc.electron_volt
integrand.append(ea * unit_cvt)
integrand_err.append(ee * unit_cvt)
else:
raise RuntimeError('invalid path setting' )
all_print = []
all_print.append(all_t)
all_print.append(integrand)
all_print.append(all_e)
all_print.append(all_e_err)
all_print.append(all_enthalpy)
all_print.append(all_msd_xyz)
all_print = np.array(all_print)
np.savetxt(os.path.join(iter_name, 'ti.out'),
all_print.T,
fmt = '%.8e',
header = 't/p Integrand U/V U/V_err enthalpy msd_xyz')
info0 = _compute_thermo(os.path.join(all_tasks[ 0], 'log.lammps'), natoms, stat_skip, stat_bsize)
info1 = _compute_thermo(os.path.join(all_tasks[-1], 'log.lammps'), natoms, stat_skip, stat_bsize)
_print_thermo_info(info0, 'at start point')
_print_thermo_info(info1, 'at end point')
if To is not None :
index = all_t.index(To)
if index == None :
if 'nvt' == ens :
raise RuntimeError('cannot find %f in T', To)
elif 'npt' in ens :
raise RuntimeError('cannot find %f in P', To)
all_t_1 = all_t[0:index+1]
integrand_1 = integrand[0:index+1]
integrand_err_1 = integrand_err[0:index+1]
all_t_1 = np.flip(all_t_1, 0)
integrand_1 = np.flip(integrand_1, 0)
integrand_err_1 = np.flip(integrand_err_1, 0)
all_t_2 = all_t[index:]
integrand_2 = integrand[index:]
integrand_err_2 = integrand_err[index:]
all_temps_1, all_press_1, all_fe_1, all_fe_err_1, all_fe_sys_err_1 \
= _thermo_inte(jdata, Eo, Eo_err, all_t_1, integrand_1, integrand_err_1, scheme = scheme)
all_temps_2, all_press_2, all_fe_2, all_fe_err_2, all_fe_sys_err_2 \
= _thermo_inte(jdata, Eo, Eo_err, all_t_2, integrand_2, integrand_err_2, scheme = scheme)
all_temps_1 = np.flip(all_temps_1, 0)
all_press_1 = np.flip(all_press_1, 0)
all_fe_1 = np.flip(all_fe_1, 0)
all_fe_err_1 = np.flip(all_fe_err_1, 0)
all_fe_sys_err_1 = np.flip(all_fe_sys_err_1, 0)
all_temps = np.append(all_temps_1, all_temps_2[1:])
all_press = np.append(all_press_1, all_press_2[1:])
all_fe = np.append(all_fe_1, all_fe_2[1:])
all_fe_err = np.append(all_fe_err_1, all_fe_err_2[1:])
all_fe_sys_err = np.append(all_fe_sys_err_1, all_fe_sys_err_2[1:])
else :
all_temps, all_press, all_fe, all_fe_err, all_fe_sys_err \
= _thermo_inte(jdata, Eo, Eo_err, all_t, integrand, integrand_err, scheme = scheme, all_e=all_e)
# print('ti.py:debug:data', data)
result = ""
# result_file = open(f"{iter_name}/../result", 'w')
if 'nvt' == ens :
print('#%8s %20s %9s %9s %9s' % ('T(ctrl)', 'F', 'stat_err', 'inte_err', 'err'))
result += ('#%8s %20s %9s %9s %9s\n' % ('T(ctrl)', 'F', 'stat_err', 'inte_err', 'err'))
for ii in range(len(all_temps)) :
print ('%9.2f %20.12f %9.2e %9.2e %9.2e'
% (all_temps[ii], all_fe[ii], all_fe_err[ii], all_fe_sys_err[ii], np.linalg.norm([all_fe_err[ii], all_fe_sys_err[ii]])))
result += ('%9.2f %20.12f %9.2e %9.2e %9.2e\n'
% (all_temps[ii], all_fe[ii], all_fe_err[ii], all_fe_sys_err[ii], np.linalg.norm([all_fe_err[ii], all_fe_sys_err[ii]])))
elif 'npt' in ens :
print('#%8s %15s %20s %9s %9s %9s' % ('T(ctrl)', 'P(ctrl)', 'F', 'stat_err', 'inte_err', 'err'))
result += ('#%8s %15s %20s %9s %9s %9s\n' % ('T(ctrl)', 'P(ctrl)', 'F', 'stat_err', 'inte_err', 'err'))
for ii in range(len(all_temps)) :
print ('%9.2f %15.8e %20.12f %9.2e %9.2e %9.2e'
% (all_temps[ii], all_press[ii], all_fe[ii], all_fe_err[ii], all_fe_sys_err[ii], np.linalg.norm([all_fe_err[ii], all_fe_sys_err[ii]])))
result += ('%9.2f %15.8e %20.12f %9.2e %9.2e %9.2e\n'
% (all_temps[ii], all_press[ii], all_fe[ii], all_fe_err[ii], all_fe_sys_err[ii], np.linalg.norm([all_fe_err[ii], all_fe_sys_err[ii]])))
# print(all_temps[ii], all_press[ii], all_fe[ii], all_fe_err[ii], all_fe_sys_err[ii], np.linalg.norm([all_fe_err[ii], all_fe_sys_err[ii]]))
# result_file.close()
data = dict(all_temps=all_temps.tolist(), all_press=all_press.tolist(),
all_fe=all_fe.tolist(), all_fe_stat_err=all_fe_err.tolist(), all_fe_inte_err=all_fe_sys_err.tolist(),
all_fe_tot_err=np.linalg.norm([all_fe_err[ii], all_fe_sys_err[ii]]).tolist())
# data = [all_temps.tolist(), all_press.tolist(),
# all_fe.tolist(), all_fe_err.tolist(), all_fe_sys_err.tolist(),
# np.linalg.norm([all_fe_err[ii], all_fe_sys_err[ii]]).tolist()]
info = dict(start_point_info=info0, end_point_info=info1, data=data)
# print('result', result)
with open(os.path.join(iter_name, '../', 'result'), 'w') as f:
f.write(result)
with open(os.path.join(iter_name, 'result.json'), 'w') as f:
f.write(json.dumps(info))
return info
def _post_tasks_mbar(iter_name, step, natoms) :
jdata = json.load(open(os.path.join(iter_name, 'in.json')))
stat_skip = jdata['stat_skip']
stat_bsize = jdata['stat_bsize']
temp = jdata['temp']
all_tasks = glob.glob(os.path.join(iter_name, 'task.[0-9]*'))
all_tasks.sort()
ntasks = len(all_tasks)
all_lambda = []
for ii in all_tasks :
lmda_name = os.path.join(ii, 'lambda.out')
ll = float(open(lmda_name).read())
all_lambda.append(ll)
all_lambda = np.array(all_lambda)
nlambda = all_lambda.size
ukn = np.array([])
nk = []
kt_in_ev = pc.Boltzmann * temp / pc.electron_volt
for idx,ii in enumerate(all_tasks) :
log_name = os.path.join(ii, 'log.lammps')
data = get_thermo(log_name)
np.savetxt(os.path.join(ii, 'data'), data, fmt = '%.6e')
bd_e = data[stat_skip:, 8]/kt_in_ev
ag_e = data[stat_skip:, 9]/kt_in_ev
dp_e = data[stat_skip:,10]/kt_in_ev
if step == 'angle_on' :
de = ag_e / all_lambda[idx] + dp_e
elif step == 'deep_on' :
de = dp_e
elif step == 'bond_angle_off' :
de = -(bd_e + ag_e) / (1 - all_lambda[idx]) + dp_e
else :
raise RuntimeError("unknow step")
nk.append(de.size)
block_u = []
for ll in all_lambda :
if step == 'angle_on' or 'deep_on':
block_u.append(de * ll)
else :
block_u.append(-de * (1-ll))
block_u = np.reshape(block_u, [nlambda, -1])
if ukn.size == 0 :
ukn = block_u
else :
ukn = np.concatenate((ukn, block_u), axis = 1)
nk = np.array(nk)
mbar = pymbar.MBAR(ukn, nk)
Deltaf_ij, dDeltaf_ij, Theta_ij = mbar.getFreeEnergyDifferences()
Deltaf_ij = Deltaf_ij / natoms
dDeltaf_ij = dDeltaf_ij / np.sqrt(natoms)
diff_e = Deltaf_ij[0,-1] * kt_in_ev
err = dDeltaf_ij[0,-1] * kt_in_ev
sys_err = 0
thermo_info = _compute_thermo(os.path.join(all_tasks[-1], 'log.lammps'),
natoms,
stat_skip, stat_bsize)
return diff_e, [err, sys_err], thermo_info
def _post_tasks(iter_name, step, natoms, scheme = 's') :
jdata = json.load(open(os.path.join(iter_name, 'in.json')))
stat_skip = jdata['stat_skip']
stat_bsize = jdata['stat_bsize']
all_tasks = glob.glob(os.path.join(iter_name, 'task.[0-9]*'))
all_tasks.sort()
ntasks = len(all_tasks)
all_lambda = []
all_bd_a = []
all_bd_e = []
all_ag_a = []
all_ag_e = []
all_dp_a = []
all_dp_e = []
for ii in all_tasks :
log_name = os.path.join(ii, 'log.lammps')
data = get_thermo(log_name)
np.savetxt(os.path.join(ii, 'data'), data, fmt = '%.6e')
bd_a, bd_e = block_avg(data[:, 8], skip = stat_skip, block_size = stat_bsize)
ag_a, ag_e = block_avg(data[:, 9], skip = stat_skip, block_size = stat_bsize)
dp_a, dp_e = block_avg(data[:,10], skip = stat_skip, block_size = stat_bsize)
bd_a /= natoms
ag_a /= natoms
dp_a /= natoms
bd_e /= np.sqrt(natoms)
ag_e /= np.sqrt(natoms)
dp_e /= np.sqrt(natoms)
lmda_name = os.path.join(ii, 'lambda.out')
ll = float(open(lmda_name).read())
all_lambda.append(ll)
all_bd_a.append(bd_a)
all_bd_e.append(bd_e)
all_ag_a.append(ag_a)
all_ag_e.append(ag_e)
all_dp_a.append(dp_a)
all_dp_e.append(dp_e)
all_lambda = np.array(all_lambda)
all_bd_a = np.array(all_bd_a)
all_bd_e = np.array(all_bd_e)
all_ag_a = np.array(all_ag_a)
all_ag_e = np.array(all_ag_e)
all_dp_a = np.array(all_dp_a)
all_dp_e = np.array(all_dp_e)
if step == 'angle_on' :
de = all_ag_a / all_lambda + all_dp_a
all_err = np.sqrt(np.square(all_ag_e / all_lambda) +
np.square(all_dp_e))
elif step == 'deep_on' :
de = all_dp_a
all_err = all_dp_e
elif step == 'bond_angle_off' :
de = - (all_bd_a + all_ag_a) / (1 - all_lambda) + all_dp_a
all_err = np.sqrt(np.square(all_bd_e / (1 - all_lambda)) +
np.square(all_ag_e / (1 - all_lambda)) +
np.square(all_dp_e))
all_print = []
# all_print.append(np.arange(len(all_lambda)))
all_print.append(all_lambda)
all_print.append(de)
all_print.append(all_err)
all_print = np.array(all_print)
np.savetxt(os.path.join(iter_name, 'hti.out'),
all_print.T,
fmt = '%.8e',
header = 'lmbda dU dU_err')
new_lambda, i, i_e, s_e = integrate_range(all_lambda, de, all_err, scheme = scheme)
if new_lambda[-1] != all_lambda[-1] :
if new_lambda[-1] == all_lambda[-2]:
_, i1, i_e1, s_e1 = integrate_range(all_lambda[-2:], de[-2:], all_err[-2:], scheme='t')
diff_e = i[-1] + i1[-1]
err = np.linalg.norm([s_e[-1], s_e1[-1]])
sys_err = i_e[-1] + i_e1[-1]
else :
raise RuntimeError("lambda does not match!")
else:
diff_e = i[-1]
err = s_e[-1]
sys_err = i_e[-1]
# diff_e, err = integrate(all_lambda, de, all_err)
# sys_err = integrate_sys_err(all_lambda, de)
thermo_info = _compute_thermo(os.path.join(all_tasks[-1], 'log.lammps'),
natoms,
stat_skip, stat_bsize)
return diff_e, [err, sys_err], thermo_info