def get_final_properties(self, path):
outputfile = get_final_abinit_out(path)
if outputfile is None:
raise ValueError("Not such dir: %s" % path)
# Reading the OUTPUT
abo = AbinitOutput(outputfile)
dmatpawu = abo.get_dmatpawu()
odmatpawu = np.array(dmatpawu).reshape(-1, self.ndim, self.ndim)
oparams = dmatpawu2params(odmatpawu, self.ndim)
if not abo.is_finished:
print('This output is not finished')
return None, None
data = abo.get_energetics()
nres2 = data['nres2'][-1]
etot = data['etot'][-1]
final_properties = None
if etot is not None and oparams is not None:
final_properties = {
'etot': etot,
'nres2': nres2,
'final_dmat': gs(oparams)
}
return final_properties, etot
def set_final_dmat(self, entry_id, abinitout):
abo = AbinitOutput(abinitout)
if not abo.is_finished:
return None
dmatpawu = abo.get_dmatpawu()
if dmatpawu is None:
return None
odmatpawu = np.array(dmatpawu).reshape(-1, self.ndim, self.ndim)
oparams = dmatpawu2params(odmatpawu, self.ndim)
data = abo.get_energetics()
if data is None:
return None
nres2 = data['nres2'][-1]
etot = data['etot'][-1]
if not np.all(
np.sum(oparams['occupations'], axis=1) == np.array(
self.num_electrons_dftu)):
print(
'ERROR: Inconsistent number of DFT+U electrons for correlated orbitals: %s'
% entry_id)
print('From the population : %s ' % self.num_electrons_dftu)
print('From %20s : %s ' % (abinitout, oparams['occupations']))
return self.pcdb.db.pychemia_entries.update({'_id': entry_id}, {
'$set': {
'properties.etot': etot,
'properties.nres2': nres2,
'properties.final_dmat': gs(oparams)
}
})
def get_final_properties(self, path):
outputfile = get_final_abinit_out(path)
if outputfile is None:
raise ValueError("Not such dir: %s" % path)
# Reading the OUTPUT
abo = AbinitOutput(outputfile)
dmatpawu = abo.get_dmatpawu()
odmatpawu = np.array(dmatpawu).reshape(-1, self.ndim, self.ndim)
oparams = dmatpawu2params(odmatpawu, self.ndim)
if not abo.is_finished:
print('This output is not finished')
return None, None
data = abo.get_energetics()
nres2 = data['nres2'][-1]
etot = data['etot'][-1]
final_properties = None
if etot is not None and oparams is not None:
final_properties = {'etot': etot,
'nres2': nres2,
'final_dmat': gs(oparams)}
return final_properties, etot
def set_final_dmat(self, entry_id, abinitout):
abo = AbinitOutput(abinitout)
if not abo.is_finished:
return None
dmatpawu = abo.get_dmatpawu()
if dmatpawu is None:
return None
odmatpawu = np.array(dmatpawu).reshape(-1, self.ndim, self.ndim)
oparams = dmatpawu2params(odmatpawu, self.ndim)
data = abo.get_energetics()
if data is None:
return None
nres2 = data['nres2'][-1]
etot = data['etot'][-1]
if not np.all(np.sum(oparams['occupations'], axis=1) == np.array(self.num_electrons_dftu)):
print('ERROR: Inconsistent number of DFT+U electrons for correlated orbitals: %s' % entry_id)
print('From the population : %s ' % self.num_electrons_dftu)
print('From %20s : %s ' % (abinitout, oparams['occupations']))
return self.pcdb.db.pychemia_entries.update({'_id': entry_id},
{'$set': {'properties.etot': etot,
'properties.nres2': nres2,
'properties.final_dmat': gs(oparams)}})
def get_final_abinit_out(path):
if not os.path.isdir(path):
raise ValueError("ERROR: Could not find folder: %s" % path)
outputfile = None
abos = [x for x in os.listdir(path) if x[-3:] in ['txt', 'out']]
if len(abos) == 0:
raise ValueError(
"ERROR: Not suitable ABINIT output files were found ('*out' or '*txt') for path: %s"
% path)
# Most recent mtime
mtime = 0
for ifile in abos:
fpath = path + os.sep + ifile
if os.path.getmtime(fpath) > mtime:
abo = AbinitOutput(fpath)
if abo.is_loaded and abo.is_finished:
mtime = os.path.getmtime(fpath)
outputfile = fpath
if outputfile is None:
print("WARNING: Could not find any good ABINIT output file: %s" % path)
return outputfile
def evaluator(self, pbs_settings, basedir):
print("Population size: %d" % len(self))
while True:
# 1. Get actives no evaluated
ane = self.actives_no_evaluated
if len(ane) > 0:
print("Candidates to be evaluated: %d" % len(ane))
else:
print("No candidates to be evaluated")
# 2. Get jobs in queue
if 'user' not in pbs_settings:
raise ValueError(
"PBS settings must contain a keys 'user', 'ppn' and 'walltime'"
)
username = pbs_settings['user']
jobs = get_jobs(username)
jobnames = [jobs[x]['Job_Name'] for x in jobs]
print("There are %d jobs in the system for user %s " %
(len(jobnames), username))
check = False
for entry_id in ane:
if str(entry_id) not in jobnames:
check = True
else:
jobids = [
jobs[x]['Job_Id'] for x in jobs
if jobs[x]['Job_Name'] == str(entry_id)
]
for jobid in jobids:
check = True
if jobs[jobid]['job_state'] != 'C':
check = False
break
to_submit = False
if check:
to_submit = True
if not os.path.isdir(basedir + os.sep + str(entry_id)):
self.prepare_folder(entry_id,
workdir=basedir,
source_dir=basedir)
elif os.path.isfile(basedir + os.sep + str(entry_id) +
os.sep + 'COMPLETE'):
abinitout = get_final_abinit_out(basedir + os.sep +
str(entry_id))
if abinitout is not None:
abo = AbinitOutput(abinitout)
# check if finished
if abo.is_finished:
# Collect results
self.collect(entry_id, basedir)
to_submit = False
if to_submit:
self.submit(entry_id, basedir, pbs_settings)
print('Sleeping for 20 minutes')
time.sleep(1200)
def evaluator(self,
username,
basedir,
queue,
walltime,
ppn,
features=None):
while True:
# 1. Get actives no evaluated
ane = self.actives_no_evaluated
if len(ane) > 0:
print("Candidates to be evaluated: %d" % len(ane))
else:
print("No candidates to be evaluated")
# 2. Get jobs in queue
jobs = get_jobs(username)
jobnames = [jobs[x]['Job_Name'] for x in jobs]
check = False
for entry_id in ane:
if str(entry_id) not in jobnames:
check = True
else:
jobids = [
jobs[x]['Job_Id'] for x in jobs
if jobs[x]['Job_Name'] == str(entry_id)
]
for jobid in jobids:
check = True
if jobs[jobid]['job_state'] != 'C':
check = False
break
to_submit = False
if check:
to_submit = True
if not os.path.isdir(basedir + os.sep + str(entry_id)):
self.prepare_folder(entry_id,
workdir=basedir,
source_dir=basedir)
elif os.path.isfile(basedir + os.sep + str(entry_id) +
os.sep + 'COMPLETE'):
abinitout = self.get_final_abinit_out(basedir +
os.sep +
str(entry_id))
if abinitout is not None:
abo = AbinitOutput(abinitout)
# check if finished
if abo.is_finished:
# Collect results
self.collect(entry_id, basedir)
to_submit = False
if to_submit:
self.submit(entry_id, basedir, queue, walltime, ppn,
features)
print('Sleeping for 10 minutes')
time.sleep(600)
def collect_data(self, entry_id, workdir, filename='abinit.out'):
if os.path.isfile(workdir + os.sep + filename):
abo = AbinitOutput(workdir + os.sep + filename)
dmatpawu = abo.get_dmatpawu()
dmat = dmatpawu2params(dmatpawu, self.ndim)
if 'etot' in abo.get_energetics():
etot = abo.get_energetics()['etot'][-1]
nres2 = abo.get_energetics()['nres2'][-1]
print('Uploading energy data for %s' % entry_id)
self.set_final_results(entry_id, dmat, etot, nres2)
return True
else:
return False
else:
return False
def collect_data(self, entry_id, workdir, filename='abinit.out'):
if os.path.isfile(workdir + os.sep + filename):
ao = AbinitOutput(workdir + os.sep + filename)
dmatpawu = get_final_dmatpawu(workdir + os.sep + filename)
dmat = dmatpawu2params(dmatpawu, self.ndim)
if 'etot' in ao.get_energetics():
etot = ao.get_energetics()['etot'][-1]
nres2 = ao.get_energetics()['nres2'][-1]
print('Uploading energy data for %s' % entry_id)
self.set_final_results(entry_id, dmat, etot, nres2)
return True
else:
return False
else:
return False
def check_status(basepath):
dirs = [x for x in os.listdir(basepath)
if os.path.isdir(basepath + os.sep + x) and os.path.isfile(basepath + os.sep + x + os.sep + 'abinit.in')]
print("%-40s %15s %15s %4s" % ("ABINIT output", "ETOT", 'nres2', 'nSCF'))
for i in dirs:
path = basepath + os.sep + i
abinitout = get_final_abinit_out(path)
if abinitout is None:
continue
abo = AbinitOutput(abinitout)
if not abo.is_finished:
continue
try:
nres2 = abo.get_energetics()['nres2'][-1]
etot = abo.get_energetics()['etot'][-1]
nscf = len(abo.get_energetics()['etot'])
print("%-40s %15.6f %15.6e %4d" % (abinitout, etot, nres2, nscf))
except:
print("ERROR: Could not get final energetics from %s" % abinitout)
def compare_params(path):
if not os.path.isfile(path + os.sep + 'abinit.in'):
print('ERROR: No abinit.in found at %s' % path)
return
# For making easier to see the values
np.set_printoptions(linewidth=200, suppress=True)
# Reading the INPUT
abi = AbinitInput(path + os.sep + 'abinit.in')
if 'lpawu' not in abi.variables:
raise ValueError("Variable lpawu not found")
ndim = 2 * max(abi['lpawu']) + 1
idmatpawu = np.array(abi['dmatpawu']).reshape(-1, ndim, ndim)
iparams = dmatpawu2params(idmatpawu, ndim)
# Reading the OUTPUT
abinitout = get_final_abinit_out(path)
abo = AbinitOutput(abinitout)
dmatpawu = abo.get_final_dmatpawu()
odmatpawu = np.array(dmatpawu).reshape(-1, ndim, ndim)
oparams = dmatpawu2params(odmatpawu, ndim)
print('DMATPAWU')
print('input')
print(idmatpawu)
print('output')
print(odmatpawu)
print('PARAMETRIC REPRESENTATION found at %s' % abinitout)
for i in sorted(list(iparams.keys())):
print(i)
print('input')
print(iparams[i])
print('output')
print(i)
print(oparams[i])
abo = AbinitOutput(abinitout)
if not abo.is_finished:
print('This output is not finished')
try:
nres2 = abo.get_energetics()['nres2'][-1]
etot = abo.get_energetics()['etot'][-1]
nscf = len(abo.get_energetics()['etot'])
print("%30s ETOT: %15.6f NRES2: %15.6e NumSCF: %3d" %
(path, etot, nres2, nscf))
except:
print("ERROR: Could not get energetics from %s" % abinitout)
def check_status(basepath):
dirs = [
x for x in os.listdir(basepath)
if os.path.isdir(basepath + os.sep +
x) and os.path.isfile(basepath + os.sep + x + os.sep +
'abinit.in')
]
print("%-40s %15s %15s %4s" % ("ABINIT output", "ETOT", 'nres2', 'nSCF'))
for i in dirs:
path = basepath + os.sep + i
abinitout = get_final_abinit_out(path)
if abinitout is None:
continue
abo = AbinitOutput(abinitout)
if not abo.is_finished:
continue
try:
nres2 = abo.get_energetics()['nres2'][-1]
etot = abo.get_energetics()['etot'][-1]
nscf = len(abo.get_energetics()['etot'])
print("%-40s %15.6f %15.6e %4d" % (abinitout, etot, nres2, nscf))
except:
print("ERROR: Could not get final energetics from %s" % abinitout)
def compare_params(path):
if not os.path.isfile(path + os.sep + 'abinit.in'):
print('ERROR: No abinit.in found at %s' % path)
return
# For making easier to see the values
np.set_printoptions(linewidth=200, suppress=True)
# Reading the INPUT
abi = AbinitInput(path + os.sep + 'abinit.in')
if 'lpawu' not in abi.variables:
raise ValueError("Variable lpawu not found")
ndim = 2 * max(abi['lpawu']) + 1
idmatpawu = np.array(abi['dmatpawu']).reshape(-1, ndim, ndim)
iparams = dmatpawu2params(idmatpawu, ndim)
# Reading the OUTPUT
abinitout = get_final_abinit_out(path)
abo = AbinitOutput(abinitout)
dmatpawu = abo.get_final_dmatpawu()
odmatpawu = np.array(dmatpawu).reshape(-1, ndim, ndim)
oparams = dmatpawu2params(odmatpawu, ndim)
print('DMATPAWU')
print('input')
print(idmatpawu)
print('output')
print(odmatpawu)
print('PARAMETRIC REPRESENTATION found at %s' % abinitout)
for i in sorted(list(iparams.keys())):
print(i)
print('input')
print(iparams[i])
print('output')
print(i)
print(oparams[i])
abo = AbinitOutput(abinitout)
if not abo.is_finished:
print('This output is not finished')
try:
nres2 = abo.get_energetics()['nres2'][-1]
etot = abo.get_energetics()['etot'][-1]
nscf = len(abo.get_energetics()['etot'])
print("%30s ETOT: %15.6f NRES2: %15.6e NumSCF: %3d" % (path, etot, nres2, nscf))
except:
print("ERROR: Could not get energetics from %s" % abinitout)
print("Renaming abinit.err")
os.rename('abinit.err', 'abinit_%02d.err' % index)
if os.path.isfile('abinit-o_WFK'):
print("Renaming abinit-o_WFK")
os.rename('abinit-o_WFK', 'abinit-i_WFK')
if os.path.isfile('abinit.out'):
print("Renaming abinit.out")
shutil.copy2('abinit.out', 'abinit_%02d.txt' % index)
os.rename('abinit.out', 'abinit_%02d.out' % index)
abiout = 'abinit_%02d.out' % index
else:
print("Could not find abinit.out")
# Opening the output file
print("Reading the output from 'abinit.out'...")
abo = AbinitOutput(abiout)
if not abo.is_finished:
print(
"abinit.out is truncated, discarting that output redoing the calculation"
)
continue
# The final density matrix is build from the outputi
ndim = 2 * max(abi['lpawu']) + 1
params = dmatpawu2params(abi['dmatpawu'], ndim)
print("Euler angles from 'abinit.in':")
for i in params['euler_angles']:
for j in i:
print(" %7.3f" % j, end=' ')
print("\n", end='')
def plot_status(basepath):
dirs = [
x for x in os.listdir(basepath)
if os.path.isdir(basepath + os.sep +
x) and os.path.isfile(basepath + os.sep + x + os.sep +
'abinit.in')
]
abi = AbinitInput(basepath + os.sep + 'abinit.in')
nstep = abi['nstep']
print('Plotting Status...')
xx = {}
yy = {}
# Get the data:
max_nruns = 0
for path in dirs:
xx[path] = np.array([])
yy[path] = {}
yy[path]['nres2'] = np.array([])
yy[path]['etot'] = np.array([])
yy[path]['delta'] = np.array([])
for i in range(100):
if os.path.isfile(basepath + os.sep + path + os.sep +
'abinit_%02d.txt' % i):
abo = AbinitOutput(basepath + os.sep + path + os.sep +
'abinit_%02d.txt' % i)
if not abo.is_finished:
print('This output is not finished')
continue
if max_nruns < i:
max_nruns = i
try:
energ = abo.get_energetics()
except:
raise RuntimeError("Failed procesing: %s" %
(basepath + os.sep + path + os.sep +
'abinit_%02d.txt' % i))
nres2 = energ['nres2'][-1]
etot = energ['etot'][-1]
nscf = len(energ['etot'])
x = np.arange(nstep * i, nstep * i + len(energ['nres2']))
yetot = np.array(energ['etot'])
ynres2 = np.array(energ['nres2'])
ydelta = np.array(np.abs(energ['deltaEh']))
xx[path] = np.concatenate((xx[path], x))
yy[path]['etot'] = np.concatenate((yy[path]['etot'], yetot))
yy[path]['nres2'] = np.concatenate((yy[path]['nres2'], ynres2))
yy[path]['delta'] = np.concatenate((yy[path]['delta'], ydelta))
print("%s ETOT:%15.6f NRES2=%15.6e Num SCF=%3d" %
(path, etot, nres2, nscf))
# RESIDUAL
plt.figure(figsize=(8, 11))
miny = 1E-1
maxy = 1E-16
plt.subplots_adjust(left=0.1,
bottom=0.05,
right=0.99,
top=0.99,
wspace=None,
hspace=None)
for path in dirs:
if len(xx) > 0:
plt.semilogy(xx[path], yy[path]['nres2'], label=path[-4:], lw=0.1)
if miny > min(yy[path]['nres2']):
miny = min(yy[path]['nres2'])
if maxy < max(yy[path]['nres2']):
maxy = max(yy[path]['nres2'])
plt.ylim(miny, maxy)
for i in nstep * np.arange(max_nruns + 1):
plt.semilogy([i, i], [miny, maxy], '0.5', lw=0.1)
plt.xlim(0, max([max(xx[path]) for path in dirs]))
plt.legend()
plt.xlabel("SCF iteration")
plt.ylabel("Density Residual$^2$")
plt.savefig('Orbital_Residual.pdf')
# ETOT
miny = 1E6
maxy = -1E6
avg = 0
minlen = 100
plt.figure(figsize=(8, 11))
for path in dirs:
if len(xx) > 0:
plt.plot(xx[path], yy[path]['etot'], label=path[-4:])
if len(yy[path]['etot']) < minlen:
minlen = len(yy[path]['etot'])
avg = np.average(yy[path]['etot'][-int(minlen / 2):])
if miny > min(yy[path]['etot'][-int(minlen / 2):]):
miny = min(yy[path]['etot'][-int(minlen / 2):])
if maxy < max(yy[path]['etot'][-int(minlen / 2):]):
maxy = max(yy[path]['etot'][-int(minlen / 2):])
plt.subplots_adjust(left=0.15,
bottom=0.05,
right=0.95,
top=0.95,
wspace=None,
hspace=None)
newminy = miny - 0.1 * (maxy - miny)
newmaxy = maxy + 0.1 * (maxy - miny)
miny = newminy
maxy = newmaxy
plt.ylim(miny, maxy)
for i in nstep * np.arange(max_nruns + 1):
plt.plot([i, i], [miny, maxy], '0.5', lw=0.1)
plt.xlim(0, max([max(xx[path]) for path in dirs]))
plt.legend()
plt.xlabel("SCF iteration")
plt.ylabel("Energy")
plt.savefig('Orbital_ETotal.pdf')
# deltaEh
plt.figure(figsize=(8, 11))
miny = 1E-1
for path in dirs:
if len(xx) > 0:
plt.semilogy(xx[path], yy[path]['delta'], label=path[-4:], lw=0.1)
if miny > min(yy[path]['delta']):
miny = min(yy[path]['delta'])
plt.subplots_adjust(left=0.1,
bottom=0.05,
right=0.99,
top=0.99,
wspace=None,
hspace=None)
for i in nstep * np.arange(max_nruns + 1):
plt.semilogy([i, i], [miny, 1E3], '0.5', lw=0.1)
plt.ylim(miny, 1E3)
plt.xlim(0, max([max(xx[path]) for path in dirs]))
plt.legend()
plt.xlabel("SCF iteration")
plt.ylabel("Delta Energy")
plt.savefig('Orbital_deltaEh.pdf')
def plot_status(basepath):
dirs = [x for x in os.listdir(basepath)
if os.path.isdir(basepath + os.sep + x) and os.path.isfile(basepath + os.sep + x + os.sep + 'abinit.in')]
abi = AbinitInput(basepath + os.sep + 'abinit.in')
nstep = abi['nstep']
print('Plotting Status...')
xx = {}
yy = {}
# Get the data:
max_nruns = 0
for path in dirs:
xx[path] = np.array([])
yy[path] = {}
yy[path]['nres2'] = np.array([])
yy[path]['etot'] = np.array([])
yy[path]['delta'] = np.array([])
for i in range(100):
if os.path.isfile(basepath + os.sep + path + os.sep + 'abinit_%02d.txt' % i):
abo = AbinitOutput(basepath + os.sep + path + os.sep + 'abinit_%02d.txt' % i)
if not abo.is_finished:
print('This output is not finished')
continue
if max_nruns < i:
max_nruns = i
try:
energ = abo.get_energetics()
except:
raise RuntimeError(
"Failed procesing: %s" % (basepath + os.sep + path + os.sep + 'abinit_%02d.txt' % i))
nres2 = energ['nres2'][-1]
etot = energ['etot'][-1]
nscf = len(energ['etot'])
x = np.arange(nstep * i, nstep * i + len(energ['nres2']))
yetot = np.array(energ['etot'])
ynres2 = np.array(energ['nres2'])
ydelta = np.array(np.abs(energ['deltaEh']))
xx[path] = np.concatenate((xx[path], x))
yy[path]['etot'] = np.concatenate((yy[path]['etot'], yetot))
yy[path]['nres2'] = np.concatenate((yy[path]['nres2'], ynres2))
yy[path]['delta'] = np.concatenate((yy[path]['delta'], ydelta))
print("%s ETOT:%15.6f NRES2=%15.6e Num SCF=%3d" % (path, etot, nres2, nscf))
# RESIDUAL
plt.figure(figsize=(8, 11))
miny = 1E-1
maxy = 1E-16
plt.subplots_adjust(left=0.1, bottom=0.05, right=0.99, top=0.99,
wspace=None, hspace=None)
for path in dirs:
if len(xx) > 0:
plt.semilogy(xx[path], yy[path]['nres2'], label=path[-4:], lw=0.1)
if miny > min(yy[path]['nres2']):
miny = min(yy[path]['nres2'])
if maxy < max(yy[path]['nres2']):
maxy = max(yy[path]['nres2'])
plt.ylim(miny, maxy)
for i in nstep * np.arange(max_nruns + 1):
plt.semilogy([i, i], [miny, maxy], '0.5', lw=0.1)
plt.xlim(0, max([max(xx[path]) for path in dirs]))
plt.legend()
plt.xlabel("SCF iteration")
plt.ylabel("Density Residual$^2$")
plt.savefig('Orbital_Residual.pdf')
# ETOT
miny = 1E6
maxy = -1E6
avg = 0
minlen = 100
plt.figure(figsize=(8, 11))
for path in dirs:
if len(xx) > 0:
plt.plot(xx[path], yy[path]['etot'], label=path[-4:])
if len(yy[path]['etot']) < minlen:
minlen = len(yy[path]['etot'])
avg = np.average(yy[path]['etot'][-int(minlen / 2):])
if miny > min(yy[path]['etot'][-int(minlen / 2):]):
miny = min(yy[path]['etot'][-int(minlen / 2):])
if maxy < max(yy[path]['etot'][-int(minlen / 2):]):
maxy = max(yy[path]['etot'][-int(minlen / 2):])
plt.subplots_adjust(left=0.15, bottom=0.05, right=0.95, top=0.95,
wspace=None, hspace=None)
newminy = miny - 0.1 * (maxy - miny)
newmaxy = maxy + 0.1 * (maxy - miny)
miny = newminy
maxy = newmaxy
plt.ylim(miny, maxy)
for i in nstep * np.arange(max_nruns + 1):
plt.plot([i, i], [miny, maxy], '0.5', lw=0.1)
plt.xlim(0, max([max(xx[path]) for path in dirs]))
plt.legend()
plt.xlabel("SCF iteration")
plt.ylabel("Energy")
plt.savefig('Orbital_ETotal.pdf')
# deltaEh
plt.figure(figsize=(8, 11))
miny = 1E-1
for path in dirs:
if len(xx) > 0:
plt.semilogy(xx[path], yy[path]['delta'], label=path[-4:], lw=0.1)
if miny > min(yy[path]['delta']):
miny = min(yy[path]['delta'])
plt.subplots_adjust(left=0.1, bottom=0.05, right=0.99, top=0.99,
wspace=None, hspace=None)
for i in nstep * np.arange(max_nruns + 1):
plt.semilogy([i, i], [miny, 1E3], '0.5', lw=0.1)
plt.ylim(miny, 1E3)
plt.xlim(0, max([max(xx[path]) for path in dirs]))
plt.legend()
plt.xlabel("SCF iteration")
plt.ylabel("Delta Energy")
plt.savefig('Orbital_deltaEh.pdf')