def datamining(filep):
"""
Read some output variables from abinit-o_OUT.nc
"""
print('Extracting ecut and etotal')
if os.path.isfile(filep + os.sep + 'abinit-o_OUT.nc'):
data = netcdf2dict(filep + os.sep + 'abinit-o_OUT.nc')
else:
data = netcdf2dict(path + os.sep + 'abinit_04' + os.sep + 'abinit-o_OUT.nc')
print(data)
print(data['ecut'], data['etotal'])
return data['ecut'], data['etotal']
def datamining(filep):
"""
Read some output variables from abinit-o_OUT.nc
"""
print('Extracting ecut and etotal')
if os.path.isfile(filep + os.sep + 'abinit-o_OUT.nc'):
data = netcdf2dict(filep + os.sep + 'abinit-o_OUT.nc')
else:
data = netcdf2dict(path + os.sep + 'abinit_04' + os.sep +
'abinit-o_OUT.nc')
print(data)
print(data['ecut'], data['etotal'])
return data['ecut'], data['etotal']
def test_abinit_utils():
"""
Test (pychemia.code.abinit) [utils] :
"""
from pychemia.utils.netcdf import netcdf2dict
from pychemia.code.abinit import xyz2input, psp_name
filename = "tests/data/abinit_05/abinit-o_OUT.nc"
print(len(netcdf2dict(filename)))
assert len(netcdf2dict(filename)) == 45
assert psp_name(1, 'LDA', 'FHI') == '01-H.LDA.fhi'
filename = "tests/data/abinit_01/abinit_DS11.xyz"
assert xyz2input(filename).variables['natom'] == 2
def test_abinit_utils():
"""
Tests (pychemia.code.abinit) [utils] :
"""
from pychemia.utils.netcdf import netcdf2dict
from pychemia.code.abinit import xyz2input, psp_name
filename = "tests/data/abinit_05/abinit-o_OUT.nc"
print(len(netcdf2dict(filename)))
assert len(netcdf2dict(filename)) == 45
assert psp_name(1, 'LDA', 'FHI') == '01-H.LDA.fhi'
filename = "tests/data/abinit_01/abinit_DS11.xyz"
assert xyz2input(filename).variables['natom'] == 2
def __init__(self, input_filename=None):
CodeInput.__init__(self)
if input_filename is None:
self.input_file = 'abinit.in'
else:
self.input_file = input_filename
if os.path.isfile(self.input_file):
if self.input_file[-6:] == 'OUT.nc':
self.variables = netcdf2dict(self.input_file)
else:
self.read()
def __init__(self, input_filename=None):
CodeInput.__init__(self)
if input_filename is None:
self.input_file = 'abinit.in'
else:
self.input_file = input_filename
if os.path.isfile(self.input_file):
if self.input_file[-6:] == 'OUT.nc':
self.variables = netcdf2dict(self.input_file)
else:
self.read()
def test_example2():
"""
Example of a multiple calc :
"""
path = 'tests/data'
assert (os.path.isdir(path))
if which('abinit') is None:
print('The executable "abinit" is not in the PATH')
print('Using the results of a previous calc')
check_results(path + os.sep + 'abinit_04')
return
workdir = tempfile.mkdtemp()
print("Work directory: %s" % workdir)
assert (os.path.isfile(path + '/abinit_04/t44.in'))
av = pychemia.code.abinit.AbinitInput(path + '/abinit_04/t44.in')
print('Original input:\n%s' % av)
abifiles = pychemia.code.abinit.AbiFiles(workdir)
abifiles.set_input(av)
abifiles.set_psps('LDA', 'FHI')
abifiles.create()
res = []
wf = open(workdir + '/results.json', 'w')
cwd = os.getcwd()
os.chdir(workdir)
for i in range(3):
av.set_value('ecut', av.get_value('ecut') + 3)
print('Computing convergence study with ecut=%f ' %
av.get_value('ecut'),
end='')
if i > 0:
av.set_value('irdwfk', 1)
av.write(abifiles.get_input_filename())
abifile = open(workdir + '/abinit.files')
logfile = open(workdir + '/abinit.log', 'w')
subprocess.call(['abinit'], stdin=abifile, stdout=logfile)
if os.path.isfile('abinit-o_WFK'):
shutil.copyfile('abinit-o_WFK', 'abinit-i_WFK')
data = netcdf2dict(workdir + '/abinit-o_OUT.nc')
os.rename(workdir + '/abinit-o_OUT.nc',
'%s/abinit-o_OUT.nc_%d' % (workdir, i))
res.append({'ecut': data['ecut'], 'etotal': data['etotal']})
print('Total energy: %f' % data['etotal'])
os.chdir(cwd)
json.dump(res, wf)
wf.close()
check_results(workdir)
shutil.rmtree(workdir)
def test_example2():
"""
Example of a multiple calc :
"""
path = 'tests/data'
assert (os.path.isdir(path))
if which('abinit') is None:
print('The executable "abinit" is not in the PATH')
print('Using the results of a previous calc')
check_results(path + os.sep + 'abinit_04')
return
workdir = tempfile.mkdtemp()
print("Work directory: %s" % workdir)
assert (os.path.isfile(path + '/abinit_04/t44.in'))
av = pychemia.code.abinit.AbinitInput(path + '/abinit_04/t44.in')
print('Original input:\n%s' % av)
abifiles = pychemia.code.abinit.AbiFiles(workdir)
abifiles.set_input(av)
abifiles.set_psps('LDA', 'FHI')
abifiles.create()
res = []
wf = open(workdir + '/results.json', 'w')
cwd = os.getcwd()
os.chdir(workdir)
for i in range(3):
av.set_value('ecut', av.get_value('ecut') + 3)
print('Computing convergence study with ecut=%f ' % av.get_value('ecut'), end='')
if i > 0:
av.set_value('irdwfk', 1)
av.write(abifiles.get_input_filename())
abifile = open(workdir + '/abinit.files')
logfile = open(workdir + '/abinit.log', 'w')
subprocess.call(['abinit'], stdin=abifile, stdout=logfile)
if os.path.isfile('abinit-o_WFK'):
shutil.copyfile('abinit-o_WFK', 'abinit-i_WFK')
data = netcdf2dict(workdir + '/abinit-o_OUT.nc')
os.rename(workdir + '/abinit-o_OUT.nc', '%s/abinit-o_OUT.nc_%d' % (workdir, i))
res.append({'ecut': data['ecut'], 'etotal': data['etotal']})
print('Total energy: %f' % data['etotal'])
os.chdir(cwd)
json.dump(res, wf)
wf.close()
check_results(workdir)
shutil.rmtree(workdir)