def from_dict(cls,d):
path = Path.from_dict(d['kpath'])
instance = cls(d['bands'],d['kpoints'],kpath=path,
fermie=d['fermie'],weights=d['weights'],**d['kwargs'])
instance._xlim = d['_xlim']
instance._ylim = d['_ylim']
return instance
def test_yamboanalyse_gw_si(self):
""" Analyse the yambo GW .json output files
"""
y = YamboAnalyser('gw_conv')
netcdf_files = y.get_files_type('netcdf_gw')
keys = sorted(netcdf_files.keys())
assert keys == [
'BndsRnXp_1_20', 'BndsRnXp_1_30', 'FFTGvecs_00010',
'FFTGvecs_00015', 'NGsBlkXp_00002', 'NGsBlkXp_00005', 'reference'
]
netcdf_files = y.get_files_type('netcdf_gw', 'FFTGvecs')
keys = sorted(netcdf_files.keys())
assert keys == ['FFTGvecs_00010', 'FFTGvecs_00015']
netcdf_files = y.get_files_type('netcdf_gw', ('FFTGvecs', 'reference'))
keys = sorted(netcdf_files.keys())
assert keys == ['FFTGvecs_00010', 'FFTGvecs_00015', 'reference']
#test getting data
ks_bands, qp_bands = y.get_bands(tags='reference')
ks_bands.plot(show=False)
print(ks_bands)
qp_bands.plot(show=False)
print(qp_bands)
#test get_path
path = Path([[[1.0, 1.0, 1.0], 'G'], [[0.0, 0.5, 0.5], 'X'],
[[0.0, 0.0, 0.0], 'G'], [[0.5, 0.0, 0.0], 'L']],
[20, 20, 20])
ks_bands_path, qp_bands_path = y.get_bands(tags='FFTGvecs',
path_kpoints=path,
type_calc=('gw'))
qp_bands_path.plot(show=False)
def test_yamboexcitondb(self):
#define path in reduced coordinates
npoints = 20
path = Path(
[[[0.0, 0.0, 0.0], '$\\Gamma$'], [[0.5, 0.0, 0.0], 'M'],
[[1. / 3, 1. / 3, 0.0], 'K'], [[0.0, 0.0, 0.0], '$\\Gamma$']],
[int(npoints * 2),
int(npoints),
int(np.sqrt(5) * npoints)])
#load databases
lat = YamboLatticeDB.from_db_file(
os.path.join(test_path, 'SAVE', 'ns.db1'))
exc = YamboExcitonDB.from_db_file(lat,
folder=os.path.join(
test_path, 'yambo'))
electrons = YamboElectronsDB(lat, save=os.path.join(test_path, 'SAVE'))
#show output
sort_e, sort_i = exc.get_sorted()
exc.get_degenerate(1)
#write exc_I.dat and exc_E.dat
exc.write_sorted('exc')
#calculate chi
w, chi = exc.get_chi()
#load reference
eps_filename = os.path.join(test_path, 'o-yambo.eps_q1_diago_bse')
w_ref, chi_imag_ref, chi_real_ref = np.loadtxt(eps_filename,
unpack=True)[:3]
#get amplitude and phases
kpoints, amplitude, phase = exc.get_amplitudes_phases((
1,
0,
))
#exciton_bandstructure
exc.plot_exciton_bs(electrons,
path, (
1,
2,
),
args_plot={'c': 'g'},
space='bands',
show=False)
def test_yambolatticedb(self):
""" test latticedb """
#open latticedb
filename = os.path.join(test_path,'SAVE/ns.db1')
ydb = YamboLatticeDB.from_db_file(filename)
#write json file
ydb.write_json('lattice.json')
string1 = str(ydb)
#read jsonfile
ydb.from_json_file('lattice.json')
string2 = str(ydb)
assert string1 == string2
p = Path([ [[1.0,1.0,1.0],'G'],
[[0.0,0.5,0.5],'X'],
[[0.0,0.0,0.0],'G'],
[[0.5,0.0,0.0],'L']], [20,20,20])
bands_kpoints, bands_indexes, path_car = ydb.get_path(p)
print(ydb)
import shutil
from yambopy.data.structures import BN
from qepy.lattice import Path
from qepy.matdyn import Matdyn
from yambopy.io.factories import PwNscfTasks, PwBandsTasks, PwRelaxTasks
from yambopy.flow import YambopyFlow, PwTask, E2yTask, YamboTask
from schedulerpy import Scheduler
from yambopy import yambopyenv
nscf_bands = 60
kpoints = [6,6,1]
nscf_kpoints = [12,12,1]
ecut = 20
npoints = 10
path_kpoints = Path([ [[0.0, 0.0, 0.0],'G'],
[[0.5, 0.0, 0.0],'M'],
[[1./3,1./3,0.0],'K'],
[[0.0, 0.0, 0.0],'G']], [int(npoints*2),int(npoints),int(sqrt(5)*npoints)])
def relax():
qe_relax_atoms_task, qe_relax_cell_task, qe_scf_task = PwRelaxTasks(BN,kpoints,ecut,cell_dofree='2Dxy',pseudo_dir="/Users/alejandro/Software/yambopy/tutorial/bn/pseudos")
relax_flow = YambopyFlow.from_tasks('relax_flow',[qe_relax_atoms_task,qe_relax_cell_task,qe_scf_task])
relax_flow.create(agressive=True)
relax_flow.run()
def bands():
pw_scf,pw_bands = PwBandsTasks(BN,kpoints,ecut,nscf_bands,path_kpoints,spin="spinor",pseudo_dir="/Users/alejandro/Software/yambopy/tutorial/bn/pseudos")
bands_flow = YambopyFlow.from_tasks('bands_flow',[pw_scf,pw_bands])
bands_flow.create(agressive=True)
bands_flow.run()
import shutil
from yambopy.data.structures import Si
from qepy import PwXML
from qepy.lattice import Path
from qepy.matdyn import Matdyn
from yambopy.io.factories import PwNscfTasks, PwBandsTasks, PwRelaxTasks
from yambopy.flow import YambopyFlow, PwTask, E2yTask, YamboTask
from schedulerpy import Scheduler
from yambopy import yambopyenv
nscf_bands = 10
kpoints = [2, 2, 2]
nscf_kpoints = [4, 4, 4]
ecut = 30
path_kpoints = Path([[[1.0, 1.0, 1.0], '$\Gamma$'], [[0.0, 0.5, 0.5], '$X$'],
[[0.0, 0.0, 0.0], '$\Gamma$'], [[0.5, 0.0, 0.0], '$L$']],
[20, 20, 20])
pseudo_dir = '../../pseudos'
def relax():
qe_relax_atoms_task, qe_relax_cell_task, qe_scf_task = PwRelaxTasks(
Si, kpoints, ecut, cell_dofree='all', pseudo_dir=pseudo_dir)
relax_flow = YambopyFlow.from_tasks(
'relax_flow', [qe_relax_atoms_task, qe_relax_cell_task, qe_scf_task])
relax_flow.create(agressive=True)
relax_flow.run()
def bands():
N=[14.0067,"N.pbe-mt_fhi.UPF"])
atoms_sc = [['N' , [0.0000000000 , 0.0000000000 ,-0.0000000000 ]],
['N' , [0.5000000000 , 0.0000000000 , 0.0000000000 ]],
['N' , [0.0000000000 , 0.5000000000 , 0.0000000000 ]],
['N' , [0.5000000000 , 0.5000000000 , 0.0000000000 ]],
['B' , [0.1666666667 , 0.3333333333 , 0.0000000000 ]],
['B' , [0.6666666667 , 0.3333333333 , 0.0000000000 ]],
['B' , [0.1666666667 , 0.8333333333 , 0.0000000000 ]],
['B' , [0.6666666667 , 0.8333333333 , 0.0000000000 ]]]
#occ = dict(occupations='smearing', smearing='mp', degauss=0.01)
BN_sc = dict(lattice=lattice_sc,atypes=atypes,atoms=atoms_sc)
path_kpoints_pc = Path([ [[0.0, 0.0, 0.0],'$\Gamma$'],
[[0.5, 0.0, 0.0],'M'],
[[1./3, 1./3,0.0],'K'],
[[0.0, 0.0, 0.0],'$\Gamma$']], [int(npoints*2),int(npoints),int(sqrt(5)*npoints)])
path_kpoints_sc = Path([ [[0.0, 0.0, 0.0],'$\Gamma$'],
[[1.0, 0.0, 0.0],'M'],
[[2./3, 2./3,0.0],'K'],
[[0.0, 0.0, 0.0],'$\Gamma$']], [int(npoints*2),int(npoints),int(sqrt(5)*npoints)])
def bands():
pw_scf_pc,pw_bands_pc = PwBandsTasks(BN,kpoints_pc,ecut,nscf_bands_pc,path_kpoints_pc,spin="spinor",pseudo_dir="../../../bn/pseudos")
bands_flow = YambopyFlow.from_tasks('bands_pc',[pw_scf_pc,pw_bands_pc])
bands_flow.create(agressive=True)
bands_flow.run()