Python Vasp.nbands方法代码示例

# 需要导入模块: from pylada.vasp import Vasp [as 别名]
# 或者: from pylada.vasp.Vasp import nbands [as 别名]
def test_typed():
  from pylada.vasp import Vasp
  from pylada.error import ValueError
  a = Vasp()

  assert a.nbands is None
  assert a._input['nbands'].keyword == 'nbands'
  assert a._input['nbands'].output_map() is None

  a.nbands = 50
  assert a.nbands == 50
  assert 'nbands' in a._input['nbands'].output_map()
  assert a._input['nbands'].output_map()['nbands'] == str(a.nbands)
  a.nbands = '51'
  assert a.nbands == 51
  assert 'nbands' in a._input['nbands'].output_map()
  assert a._input['nbands'].output_map()['nbands'] == str(a.nbands)
  a.nbands = None
  assert a.nbands is None
  assert a._input['nbands'].output_map() is None

  try: a.nbands = 'a'
  except ValueError: pass
  else: raise Exception()

  assert a.smearings is None
  assert a._input['smearings'].keyword == 'smearings'
  assert a._input['smearings'].output_map() is None
  a.smearings = [1.5, 1.0, 0.5]
  assert len(a.smearings) == 3
  assert all(abs(i-v) < 1e-8 for i, v in zip(a.smearings, [1.5, 1.0, 0.5]))
  assert 'smearings' in a._input['smearings'].output_map()
  assert all(abs(float(i)-v) < 1e-8 for i, v in zip(a._input['smearings'].output_map()['smearings'].split(), [1.5, 1.0, 0.5]))
  a.smearings = ['1.2', '0.2']
  assert len(a.smearings) == 2
  assert all(abs(i-v) < 1e-8 for i, v in zip(a.smearings, [1.2, 0.2]))
  assert 'smearings' in a._input['smearings'].output_map()
  assert all(abs(float(i)-v) < 1e-8 for i, v in zip(a._input['smearings'].output_map()['smearings'].split(), [1.2, 0.2]))
  a.smearings = '1.3 0.3'
  assert len(a.smearings) == 2
  assert all(abs(i-v) < 1e-8 for i, v in zip(a.smearings, [1.3, 0.3]))
  assert 'smearings' in a._input['smearings'].output_map()
  assert all(abs(float(i)-v) < 1e-8 for i, v in zip(a._input['smearings'].output_map()['smearings'].split(), [1.3, 0.3]))
  a.smearings = '1.3, 0.3'
  assert len(a.smearings) == 2
  assert all(abs(i-v) < 1e-8 for i, v in zip(a.smearings, [1.3, 0.3]))
  a.smearings = '1.3; 0.3'
  assert len(a.smearings) == 2
  assert all(abs(i-v) < 1e-8 for i, v in zip(a.smearings, [1.3, 0.3]))
  a.smearings = None
  assert a.smearings is None
  assert a._input['smearings'].output_map() is None
  
  try: a.smearings = 5.5
  except ValueError: pass
  else: raise Exception()
  try: a.smearings = [5.5, 'a']
  except ValueError: pass
  else: raise Exception()

# 需要导入模块: from pylada.vasp import Vasp [as 别名]
# 或者: from pylada.vasp.Vasp import nbands [as 别名]
    def __call__(self, structure, outdir=None, **kwargs ):

        from copy import deepcopy
        from os import getcwd
        from os.path import join
        from pylada.misc import RelativePath
        from pylada.error import ExternalRunFailed
        from pylada.vasp.extract import Extract
        from pylada.vasp import Vasp
        from pylada.vasp.relax import Relax

        # make this function stateless.
        structure_ = structure.copy()
        outdir = getcwd() if outdir is None else RelativePath(outdir).path

        ############ Calc 1 ###############
        name  = self.names[0]

        ## functional for Calc 1
        relax = Relax(copy=deepcopy(self.vasp))
        relax.relaxation = "volume ionic cellshape"
        relax.maxiter = 10
        relax.keep_steps = True
        relax.first_trial = { "kpoints": "\n0\nAuto\n10", "encut": 0.9 }
        ## end of the functional
        
        params = deepcopy(kwargs)
        fulldir = join(outdir, name)
        
        ## if this calculation has not been done run it
        output = relax(structure_, outdir=fulldir, **params)
        if not output.success: 
            raise ExternalRunFailed("VASP calculation did not succeed.") 

        ############ Calc 2 ###############  
        name  = self.names[1]

        ## functional for Calc 2
        wfn = Vasp(copy=deepcopy(self.vasp))
        wfn.isym    = 1
        wfn.ismear  = -5
        wfn.nbands=24*len(structure_)
        wfn.kpoints="\n0\nGamma\n4 4 4\n0. 0. 0.\n"
        ## end of the functional
        
        params = deepcopy(kwargs)
        fulldir = join(outdir, name)
        
        ## if this calculation has not been done, run it
        output = wfn(structure_, outdir=fulldir, restart=output, **params)
        if not output.success: 
            raise ExternalRunFailed("VASP calculation did not succeed.") 

        return self.Extract(fulldir)

# 需要导入模块: from pylada.vasp import Vasp [as 别名]
# 或者: from pylada.vasp.Vasp import nbands [as 别名]
    def __call__(self, structure, outdir=None, vasp=None, **kwargs ):

        from copy import deepcopy
        from os import getcwd
        from os.path import join
        from pylada.misc import RelativePath
        from pylada.error import ExternalRunFailed
        from pylada.vasp.extract import Extract, MassExtract
        from pylada.vasp import Vasp
        from pylada.vasp.relax import Relax

        # make this function stateless.
        structure_ = structure.copy()
        outdir = getcwd() if outdir is None else RelativePath(outdir).path

        ############ Calc 1 ###############
        name  = self.names[0]

        ## functional for Calc 1
        relax = Relax(copy=vasp)
        relax.relaxation = "volume ionic cellshape"
        relax.maxiter = 10
        relax.keep_steps = True
        relax.first_trial = { "kpoints": "\n0\nAuto\n10", "encut": 0.9 }
        ## end of the functional

        params = deepcopy(kwargs)
        fulldir = join(outdir, name)

        ## if this calculation has not been done run it
        output = relax(structure_, outdir=fulldir, restart=None, **params)
        if not output.success:
            raise ExternalRunFailed("VASP calculation did not succeed.") 

        ############ Calc 2 ###############  
        name  = self.names[1]

        ## functional for Calc 2
        final = Vasp(copy=vasp)
        final.nbands=24*len(structure_)
        final.kpoints="\n0\nGamma\n2 2 2\n0. 0. 0.\n"
        final.loptics=True
        final.relaxation="static"
        ## end of the functional

        params = deepcopy(kwargs)
        fulldir = join(outdir, name)

        ## if this calculation has not been done, run it
        output = final(structure_, outdir=fulldir, restart=output, **params)
        if not output.success:
            raise ExternalRunFailed("VASP calculation did not succeed.") 

        ############## GW Loop ########################
        for name in self.names[2:]:

            gw = Vasp(copy=vasp)

            gw.kpoints    ="\n0\nGamma\n2 2 2\n0. 0. 0.\n"
            gw.nbands     =24*len(structure_)
            gw.lcharg     = True

            gw.add_keyword('nelm',1)
            gw.add_keyword('algo','gw')
            gw.add_keyword('LMAXFOCKAE',4)
            gw.add_keyword('nomega',64)
            gw.add_keyword('precfock','fast')
            gw.add_keyword('encutgw',50)
            gw.add_keyword('encutlf',50)
            gw.add_keyword('lrpa',False)
            gw.add_keyword('nkred',2)

            params = deepcopy(kwargs)
            fulldir = join(outdir, name)

            ## if this calculation has not been done, run it
            output = gw(structure_, outdir=fulldir, restart=output, **params)
            if not output.success:
                raise ExternalRunFailed("VASP calculation did not succeed.") 
        #########################

        return self.Extract(fulldir)

# 需要导入模块: from pylada.vasp import Vasp [as 别名]
# 或者: from pylada.vasp.Vasp import nbands [as 别名]
def main():
  from boost.mpi import world
  from scipy.optimize import fmin as scipy_simplex
  from pylada.vasp import Extract, ExtractGW, Vasp, Specie
  from pylada.vasp.specie import nlep as nlep_parameters, U as u_parameters
  from pylada.vasp.incar import Standard, NBands
  from sys import exit

  indir = "SnO2"
  dft_in = Extract(directory=indir, comm=world)
  dft_in.OUTCAR = "OUTCAR_pbe"
  dft_in.CONTCAR = "POSCAR"
  gw_in = ExtractGW(directory=indir, comm=world)
  gw_in.OUTCAR = "OUTCAR_gw"
  gw_in.CONTCAR = "POSCAR"

  # Creates species with nlep parameters to optimize
  species = Specie\
            (
              "Sn", 
              path="pseudos/Sn", 
              U=[nlep_parameters(type="Dudarev", l=i, U0=0e0) for i in ["s", "p", "d"]]
            ),\
            Specie\
            (
              "O", 
              path="pseudos/O",
              U=[nlep_parameters(type="Dudarev", l=i, U0=0e0) for i in ["s", "p"]]
            )
  # add U to Sn atoms.
  species[0].U.append( u_parameters(type="Dudarev", U=2e0, l=2) )
  # creates vasp launcher
  vasp = Vasp\
         (
           kpoints    = lambda x: "Automatic generation\n0\ngamma\n6 6 10\n0 0 0",
           precision  = "accurate",
           smearing   = "bloechl",
           ediff      = 1e-5,
           relaxation = "ionic",
           encut      = 1, # uses ENMAX * 1, which is VASP default
           species    = species
         )
  # adds some extra parameters.
  vasp.nbands     = Standard("NBANDS", 64)
  vasp.lorbit     = Standard("LORBIT", 10)
  vasp.npar       = Standard("NPAR", 2)
  vasp.lplane     = Standard("LPLANE", ".TRUE.")
  vasp.addgrid    = Standard("ADDGRID", ".TRUE.")
  del vasp.fftgrid

  # creates objective function.
  objective = Objective(vasp, dft_in, gw_in)

  x0, f0, iter, funcalls, warnflag = scipy_simplex(objective, objective.x, maxfun=150, full_output=1, xtol=0.2)
  world.barrier()
  if world.rank == 0:
    print "minimum value:", f0
    print "for: ", x0 * units
    print "after %i iterations and %i function calls." % (iter, funcalls)
    print "with warning flag: ", warnflag 
    print final(x0)