def compute_bs():
from numpy import array
from pylada.escan import read_input, exec_input, ReducedBPoints
from pylada.vff import Vff
# reads input file.
input = read_input("input.py")
# creating unrelaxed structure.
structure = input.vff.lattice.to_structure()
structure.atoms[0].type = "Si"
structure.atoms[1].type = "Ge"
structure.scale = 5.65
# some kpoints + associated name
X = array( [1,0,0], dtype="float64" )
G = array( [0,0,0], dtype="float64" )
L = array( [0.5,0.5,0.5], dtype="float64" )
W = array( [0, 0.5,1], dtype="float64" )
# Each job is performed for a given kpoint (first argument), at a given
# reference energy (third argument). Results are stored in a specific directory
# (second arguement). The expected eigenvalues are given in the fourth argument.
input = read_input('input.py')
kescan = exec_input(repr(input.escan).replace('Escan', 'KEscan')).functional
kescan.fft_mesh = 14, 14, 14
kescan.kpoints = ReducedBPoints(density=20) + (X, G) + (G, L)
result = kescan( structure, outdir='results/projections',
nbstates = len(structure.atoms) * 4 + 4,
eref = None )
def create_sl(path, direction, nmin, nmax, nstep, x=0.5, density=10e0, input='input.py'):
""" Creates dictionary of superlattices.
:Parameters:
path : str
Path to output dictionary.
direction : callable(int)->(3x3, 3x1)
A callable taking the number of layers on input and returning a tuple
consisting of a supercell with the correct number of layers and the
direction of growth of the superlattice. The supercell must be
have the correct periodicity: two vectors should be parallel to the
substrate such that layers can actually be defined. Otherwise, there
is not one-to-one correspondance between atoms and layers: the same
atom could belong to different layers. A number of examples are given
in this module: `direction001`, `direction011`, `direction111`.
nmin : int
Minimum number of layers.
nmax : int
Maximum number of layers (excluded).
nstep : int
Step between layers: [``nmin``, ``nmin``+``nstep``,
``nmin``+2*``nstep``, ..., ``nmax``[
x : float
Concentration in Si of the superlattice. Should be between 0 and 1.
density : float
Kpoint density for escan calculations,
input : str
Path to input file containing escan functional.
"""
from IPython.ipapi import get as get_ipy
from numpy.linalg import norm, inv
from pylada.jobs import JobFolder
from pylada.escan import read_input, exec_input, ReducedKDensity
from pylada.crystal.binary import zinc_blende
from pylada.crystal import layer_iterator
ip = get_ipy()
input = read_input(input)
kescan = exec_input(repr(input.escan).replace('Escan', 'KEscan')).functional
lattice = zinc_blende()
lattice.sites[0].type = 'Si', 'Ge'
lattice.sites[1].type = 'Si', 'Ge'
lattice.scale = 5.45
lattice.find_space_group()
density = 10e0 * max([1e0/norm(u) for u in inv(lattice.cell)])
rootjobs = ip.user_ns.get('current_jobfolder', JobFolder())
for n0 in range(nmin, nmax, nstep):
# create structure
cell, dir = direction(n0)
structure = lattice.to_structure(cell) # reduction not necessary if cell function done right.
N0 = int(len([0 for layer in layer_iterator(structure, dir)]) * x+1e-8)
for i, layer in enumerate(layer_iterator(structure, dir)):
for atom in layer: atom.type = 'Si' if i < N0 else 'Ge'
xp = float(len([0 for atom in structure.atoms if atom.type == 'Si']))
xp /= float(len(structure.atoms))
assert abs(xp - x) < 1e-12
# name and scale.
structure.name = "{0[0]}{0[1]}{0[2]}/x_{1:0<4.3}/n_{2}".format(dir, x, n0)
structure.scale = scale(structure)
# creates job-folder.
jobfolder = rootjobs / structure.name
jobfolder.jobparams['structure'] = structure.copy()
jobfolder.functional = kescan.copy()
jobfolder.functional.kpoints = ReducedKDensity(density, (0.5, 0.5, 0.5))
jobfolder.functional.reference = None
jobfolder.functional.fft_mesh = fftmesh(structure.cell)
jobfolder.functional.nbstates = int(len(structure.atoms) * 4 * 1.5+0.5)
if 'current_jobfolder' not in ip.user_ns: ip.user_ns["current_jobfolder"] = rootjobs
ip.magic("savejobs " + path)
return
# your option) any later version.
#
# PyLaDa is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even
# the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
# Public License for more details.
#
# You should have received a copy of the GNU General Public License along with PyLaDa. If not, see
# <http://www.gnu.org/licenses/>.
###############################
from numpy import array
from pylada.escan import read_input, exec_input, ReducedBPoints
from pylada.crystal.binary import zinc_blende
X = array( [1,0,0], dtype="float64" )
G = array( [0,0,0], dtype="float64" )
L = array( [0.5,0.5,0.5], dtype="float64" )
W = array( [0, 0.5,1], dtype="float64" )
input = read_input('input.py')
kescan = exec_input(repr(input.escan).replace('Escan', 'KEscan')).functional
structure = zinc_blende().to_structure(subs={'A':'Si', 'B':'Si'})
structure.scale = 5.45
kescan.fft_mesh = 14, 14, 14
kescan.kpoints = ReducedBPoints(density=20) + (X, G) + (G, L)
result = kescan( structure, outdir='results/kescan',
nbstates = len(structure.atoms) * 4 + 4,
eref = None )
def create_start(path, nall = 3, nrand = 5, nmax=100, density=10e0, input='input.py'):
""" Creates dictionary with input structures for Si/Ge.
:Parameters:
path : str
Path to output dictionary.
nall : int
All structure with ``nall`` (excluded) unit-cells are included in the final dictionary.
nrand : int
Structures between ``nall`` (included) and ``nrand`` (excluded) unit-cells are
also considered for inclusion in the final dictionary. However, only
``nmax`` are randomly chosen in the end.
nmax : int
Structures between ``nall`` (included) and ``nrand`` (excluded) unit-cells are
also considered for inclusion in the final dictionary. However, only
``nmax`` are randomly chosen in the end.
density : float
Kpoint density for escan calculations,
input : str
Path to input file containing escan functional.
Creates a job-dictionary with a number of structures sampled from an
exhaustive list of structures to evaluate using escan.
"""
from random import shuffle
from itertools import chain
from IPython.ipapi import get as get_ipy
from numpy.linalg import norm, inv
from pylada.enumeration import Enum
from pylada.crystal.binary import zinc_blende
from pylada.jobs import JobFolder
from pylada.escan import read_input, exec_input, ReducedKDensity
from pylada.crystal.gruber import Reduction
input = read_input(input)
kescan = exec_input(repr(input.escan).replace('Escan', 'KEscan')).functional
enum = Enum(zinc_blende())
enum.sites[0].type = 'Si', 'Ge'
enum.sites[1].type = 'Si', 'Ge'
enum.scale = 5.45
enum.find_space_group()
density = density * max([1e0/norm(u) for u in inv(enum.cell * enum.scale).T])
strs = [u for n in range(nall, nrand) for u in enum.xn(n)]
shuffle(strs)
strs = [enum.as_structure(*u) for u in strs[:nmax]]
alls = [structure for n in range(nall) for structure in enum.structures(n)]
jobs = JobFolder()
for i, structure in enumerate(chain(alls, strs)):
structure.name = str(i)
nSi = len([a.type for a in structure.atoms if a.type == 'Si'])
structure.scale = float(nSi) / float(n) * enum.scale + float(n - nSi) / float(n) * 5.69
jobfolder = jobs / structure.name
jobfolder.jobparams['structure'] = structure.copy()
jobfolder.structure.cell = Reduction()(jobfolder.structure.cell)
jobfolder.functional = kescan.copy()
jobfolder.functional.kpoints = ReducedKDensity(density, (0.5, 0.5, 0.5))
jobfolder.functional.reference = None
jobfolder.functional.fft_mesh = fftmesh(structure.cell)
jobfolder.functional.nbstates = int(len(structure.atoms) * 4 * 1.5+0.5)
ip = get_ipy()
ip.user_ns["current_jobfolder"] = jobfolder.root
ip.magic("savejobs " + path)
return
