示例#1
0
文件: keywords.py 项目: mdavezac/LaDa
def test_bool():
  from pickle import loads, dumps
  from pylada.vasp import Vasp
  a = Vasp()

  assert a._input['addgrid'].keyword == 'addgrid'
  assert a._input['addgrid'].output_map() is None
  assert a.addgrid is None
  a.addgrid = False
  assert a.addgrid is False
  assert 'addgrid' in a._input['addgrid'].output_map()
  assert a._input['addgrid'].output_map()['addgrid'] == '.FALSE.'
  a.addgrid = True
  assert a.addgrid is True
  assert 'addgrid' in a._input['addgrid'].output_map()
  assert a._input['addgrid'].output_map()['addgrid'] == '.TRUE.'
  a.addgrid = None
  assert a._input['addgrid'].keyword == 'addgrid'
  assert a._input['addgrid'].output_map() is None
  a.addgrid = 0
  assert a.addgrid is False

  a.addgrid = False
  o = a._input['addgrid']
  d = {'BoolKeyword': o.__class__}
  assert repr(eval(repr(o), d)) == repr(o)
  assert eval(repr(o), d).output_map()['addgrid'] == '.FALSE.'
  assert repr(loads(dumps(o))) == repr(o)
  a.addgrid = True
  o = a._input['addgrid']
  assert repr(eval(repr(o), d)) == repr(o)
  assert eval(repr(o), d).output_map()['addgrid'] == '.TRUE.'
  assert repr(loads(dumps(o))) == repr(o)
  a.addgrid = None
  o = a._input['addgrid']
  assert repr(eval(repr(o), d)) == repr(o)
  assert eval(repr(o), d).output_map() is None
  assert repr(loads(dumps(o))) == repr(o)
def test_bool():
    from pickle import loads, dumps
    from pylada.vasp import Vasp
    a = Vasp()

    assert a._input['addgrid'].keyword == 'addgrid'
    assert a._input['addgrid'].output_map() is None
    assert a.addgrid is None
    a.addgrid = False
    assert a.addgrid is False
    assert 'addgrid' in a._input['addgrid'].output_map()
    assert a._input['addgrid'].output_map()['addgrid'] == '.FALSE.'
    a.addgrid = True
    assert a.addgrid is True
    assert 'addgrid' in a._input['addgrid'].output_map()
    assert a._input['addgrid'].output_map()['addgrid'] == '.TRUE.'
    a.addgrid = None
    assert a._input['addgrid'].keyword == 'addgrid'
    assert a._input['addgrid'].output_map() is None
    a.addgrid = 0
    assert a.addgrid is False

    a.addgrid = False
    o = a._input['addgrid']
    d = {'BoolKeyword': o.__class__}
    assert repr(eval(repr(o), d)) == repr(o)
    assert eval(repr(o), d).output_map()['addgrid'] == '.FALSE.'
    assert repr(loads(dumps(o))) == repr(o)
    a.addgrid = True
    o = a._input['addgrid']
    assert repr(eval(repr(o), d)) == repr(o)
    assert eval(repr(o), d).output_map()['addgrid'] == '.TRUE.'
    assert repr(loads(dumps(o))) == repr(o)
    a.addgrid = None
    o = a._input['addgrid']
    assert repr(eval(repr(o), d)) == repr(o)
    assert eval(repr(o), d).output_map() is None
    assert repr(loads(dumps(o))) == repr(o)
示例#3
0
文件: test.py 项目: mdavezac/LaDa
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)
示例#4
0
pseudoDir = '/home/vstevano/software/pseudos'
vasp.add_specie = "In", pseudoDir + "/In"
vasp.add_specie = "O", pseudoDir + "/O"

vasp.prec       = "accurate"
vasp.encut      = 340.
vasp.ismear     = 0
vasp.sigma      = 0.05
vasp.ediff      = 1.0e-6
vasp.ediffg     = -0.01
vasp.convergence= 1.0e-6
vasp.nsw        = 1
vasp.lwave      = True
vasp.lorbit     = 10
vasp.lplane     = True
vasp.addgrid    = True
vasp.npar       = 8
vasp.isym       = 0
vasp.lcharg     = True
vasp.lwave      = True
vasp.lmaxmix    = 4
vasp.loptics    = False
vasp.lpead      = False
vasp.algo = "Normal"
vasp.relaxation = "ionic"

relax = Relax(copy=vasp)

relax.nsw=75
relax.minrelsteps= 4
relax.maxiter = 10