def run_properties_direct(wf_path, input_dict):
"""
This procedure runs properties
outside of AiiDA graph and scheduler
"""
assert wf_path.endswith('fort.9')
assert 'band' in input_dict and 'dos' in input_dict
assert 'first' not in input_dict['dos'] and 'first' not in input_dict[
'band']
assert 'last' not in input_dict['dos'] and 'last' not in input_dict['band']
print('Working with %s' % wf_path)
work_folder = os.path.join(
config.get('local', 'data_dir'), '_'.join([
'props',
datetime.now().strftime('%Y%m%d_%H%M%S'),
''.join([random.choice(string.ascii_lowercase) for _ in range(4)])
]))
os.makedirs(work_folder, exist_ok=False)
shutil.copy(wf_path, work_folder)
shutil.copy(os.path.join(os.path.dirname(wf_path), 'fort.34'),
work_folder) # save structure
wf = Fort9(os.path.join(work_folder, 'fort.9'))
# automatic generation of k-point path
#structure = wf.get_structure()
# NB fort.9 may produce slightly different structure, so use fort.34
f34 = f34_input.read(os.path.join(os.path.dirname(wf_path), 'fort.34'))
structure = f34.to_aiida()
shrink, _, kpath = get_shrink_kpoints_path(structure)
last_state = wf.get_ao_number()
input_dict['band']['shrink'] = shrink
input_dict['band']['bands'] = kpath
# automatic generation of first and last state
input_dict['band']['first'] = 1
input_dict['band']['last'] = last_state
input_dict['dos']['first'] = 1
input_dict['dos']['last'] = last_state
d3_content = str(D3(input_dict))
inp = open(os.path.join(work_folder, 'INPUT'), "w")
inp.write(d3_content)
inp.close()
start_time = time.time()
p = subprocess.Popen(
exec_cmd %
(work_folder, EXEC_PATH, os.path.join(work_folder, 'OUTPUT')),
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
shell=True)
try:
p.wait(timeout=EXEC_TIMEOUT)
except subprocess.TimeoutExpired:
kill(p.pid)
print("Killed as too time-consuming")
print("Done in %1.2f sc" % (time.time() - start_time))
if p.returncode != 0:
return None, 'PROPERTIES failed, see %s' % work_folder
if not os.path.exists(os.path.join(work_folder, 'BAND.DAT')) \
or not os.path.exists(os.path.join(work_folder, 'DOSS.DAT')) \
or not os.path.exists(os.path.join(work_folder, 'fort.25')):
return None, 'No PROPERTIES outputs'
edata = Fort25(os.path.join(work_folder, 'fort.25')).parse()
assert sum(edata['DOSS']['e']) == 0 # all zeros, FIXME?
print('>N DOSS: %s' % len(edata['DOSS']['dos'][0]))
path = edata['BAND']['path']
k_number = edata['BAND']['n_k']
#cell = wf.get_cell(scale=True) # for path construction we're getting geometry from fort.9
# NB fort.9 may produce slightly different structure, so use fort.34
cell = f34.abc, f34.positions, f34.atomic_numbers
path_description = construct_kpoints_path(cell, path, shrink, k_number)
# find k-points along the path
k_points = get_explicit_kpoints_path(structure,
path_description)['explicit_kpoints']
# pass through the internal AiiDA repr, FIXME?
bands_data = DataFactory('array.bands')()
bands_data.set_kpointsdata(k_points)
bands_data.set_bands(edata['BAND']['bands'])
edata['BAND']['bands'] = bands_data.get_bands()
k_points = bands_data.get_kpoints().tolist()
print('>N KPOINTS: %s' % len(k_points))
print('>N BANDS: %s' % len(edata['BAND']['bands'][0]))
edata['BAND']['bands'] -= edata['DOSS']['e_fermi']
edata['BAND']['bands'] *= Hartree
edata['DOSS']['dos'] -= edata['DOSS']['e_fermi']
edata['DOSS']['dos'] *= Hartree
# get rid of the negative DOS artifacts
edata['DOSS']['dos'][edata['DOSS']['dos'] < 0] = 0
e_min, e_max = np.amin(edata['BAND']['bands']), np.amax(
edata['BAND']['bands'])
dos_energies = np.linspace(e_min, e_max, num=len(edata['DOSS']['dos'][0]))
stripes = edata['BAND']['bands'].transpose().copy()
if is_conductor(stripes):
indirect_gap, direct_gap = None, None
else:
indirect_gap, direct_gap = get_band_gap_info(stripes)
# save only the range of the interest
E_MIN, E_MAX = -15, 20
stripes = stripes[(stripes[:, 0] > E_MIN) & (stripes[:, 0] < E_MAX)]
dos = []
for n, i in enumerate(dos_energies): # FIXME use numpy advanced slicing
if E_MIN < i < E_MAX:
dos.append(edata['DOSS']['dos'][0][n])
dos_energies = dos_energies[(dos_energies > E_MIN)
& (dos_energies < E_MAX)]
return {
# - gaps
'direct_gap': direct_gap,
'indirect_gap': indirect_gap,
# - dos values
'dos': np.round(np.array(dos), 3).tolist(),
'levels': np.round(dos_energies, 3).tolist(),
# - bands values
'k_points': k_points,
'stripes': np.round(stripes, 3).tolist(),
# - auxiliary
'work_folder': work_folder,
'units': 'eV'
}, None
