def test_gen_diamond_lattice():
"""
Create a conventional cell of diamond from lattice information.
"""
from structure import generate_structure
diamond = generate_structure(
lattice='cubic', # cubic tetragonal orthorhombic rhombohedral
# hexagonal triclinic monoclinic
cell='conventional', # primitive, conventional
centering='F', # P A B C I R F
constants=3.57, # a,b,c,alpha,beta,gamma
units='A', # A or B
atoms='C', # species in primitive cell
basis=[
[0, 0, 0], # basis vectors (optional)
[.25, .25, .25]
],
)
ref = generate_structure(
units='A',
axes=[[3.57, 0.00, 0.00], [0.00, 3.57, 0.00], [0.00, 0.00, 3.57]],
elem=8 * ['C'],
posu=[[0.00, 0.00, 0.00], [0.25, 0.25, 0.25], [0.00, 0.50, 0.50],
[0.25, 0.75, 0.75], [0.50, 0.00, 0.50], [0.75, 0.25, 0.75],
[0.50, 0.50, 0.00], [0.75, 0.75, 0.25]],
)
assert (structure_same(diamond, ref))
def test_embed():
"""
Embed a "relaxed" structure in a larger pristine cell.
"""
import numpy as np
from structure import generate_structure
center = (0, 0, 0)
g = generate_structure(
structure='graphene',
cell='prim',
tiling=(4, 4, 1),
)
g.recenter(center)
# Represent the "relaxed" cell
gr = g.copy()
npos = len(gr.pos)
dr = gr.min_image_vectors(center)
dr.shape = npos, 3
r = np.linalg.norm(dr, axis=1)
dilation = 2 * r * np.exp(-r)
for i in range(npos):
gr.pos[i] += dilation[i] / r[i] * dr[i]
#end for
# Represent the unrelaxed large cell
gl = generate_structure(
structure='graphene',
cell='rect',
tiling=(8, 4, 1),
)
gl.recenter(center)
# Embed the relaxed cell in the large unrelaxed cell
ge = gl.copy()
ge.embed(gr)
assert (len(ge.elem) == len(gl.elem))
assert (len(ge.pos) == len(gl.pos))
# check that the large local distortion made in the small cell
# is present in the large cell after embedding
rnn_max_ref = 2.1076122431022664
rnn_max = np.linalg.norm(gr.pos[1] - gr.pos[30])
assert (value_eq(rnn_max, rnn_max_ref))
rnn_max = np.linalg.norm(ge.pos[1] - ge.pos[28])
assert (value_eq(rnn_max, rnn_max_ref))
def demo_opt_tiling():
"""
Search for the "best" tiling matrix for a graphene supercell.
"""
g11 = generate_structure(
structure='graphene',
cell='prim',
)
# Look for an optimal cell 20x larger than the primitive cell
gopt = g11.tile_opt(20)
print('\nOptimal(?) tiling matrix between primitive and supercell:')
print(gopt.tilematrix(g11))
# Plot the tiled structure
plt.figure(tight_layout=True)
gopt.plot2d_ax(0, 1, 'k', lw=2)
g11.plot2d_ax(0, 1, 'r', lw=2)
gopt.plot2d_pos(0, 1, 'bo')
plt.axis('equal')
plt.xlabel('x (A)')
plt.ylabel('y (A)')
plt.title('demo tiling: optimally tiled graphene')
plt.show()
def demo_matrix_tiling():
"""
Make a matrix tiled cell of graphene and plot it.
"""
g11 = generate_structure(
structure='graphene',
cell='prim',
)
tmat = [[3, 0, 0], [3, 6, 0], [0, 0, 1]]
gmat = g11.tile(tmat)
# For any two structures related by tiling, tiling matrix can be found:
print('\nTiling matrix between primitive and supercell:')
print(gmat.tilematrix(g11))
# Plot the tiled structure
plt.figure(tight_layout=True)
gmat.plot2d_ax(0, 1, 'k', lw=2)
g11.plot2d_ax(0, 1, 'r', lw=2)
gmat.plot2d_pos(0, 1, 'bo')
plt.axis('equal')
plt.xlabel('x (A)')
plt.ylabel('y (A)')
plt.title('demo tiling: matrix tiled graphene')
plt.show()
def demo_write():
"""
Write conventional diamond cell to XYZ, XSF, and POSCAR formats.
"""
d8 = generate_structure(
structure='diamond',
cell='conv',
)
# Write an XYZ file
d8.write('diamond8.xyz') # loses cell info, appropriate for molecules
# Write an XSF file
d8.write('diamond8.xsf')
# Write a POSCAR file
d8.write('diamond8.POSCAR')
# Print the contents of each file
print('\nXYZ file:')
os.system('cat diamond8.xyz')
print('\nXSF file:')
os.system('cat diamond8.xsf')
print('\nPOSCAR file:')
os.system('cat diamond8.POSCAR')
def demo_primitive_search():
"""
Find the primitive cell given a supercell.
"""
# Note: this demo requires SeeKpath
d2 = generate_structure(
structure='diamond',
cell='prim',
)
# Construct the cubic 64 atom supercell
d64 = d2.tile_opt(32)
# Remove all traces of the 2 atom cell, supercell is all that remains
d64.remove_folded()
del d2
# Find the primitive cell from the supercell
dprim = d64.primitive()
# Print the supercell axes
print('\nSupercell axes:\n{}'.format(d64.axes))
# Print the primitive cell axes
print('\nPrimitive cell axes:\n{}'.format(dprim.axes))
# Print the tiling matrix
print('\nTiling matrix:\n{}'.format(d64.tilematrix(dprim)))
def test_unit_coords():
"""
Get atomic positions in unit coordinates.
"""
import numpy as np
from structure import generate_structure
s = generate_structure(
structure='diamond',
cell='prim',
tiling=(2, 2, 2),
)
upos_ref = np.array([[0.000, 0.000, 0.000], [0.125, 0.125, 0.125],
[0.500, 0.000, 0.000], [0.625, 0.125, 0.125],
[0.000, 0.500, 0.000], [0.125, 0.625, 0.125],
[0.500, 0.500, 0.000], [0.625, 0.625, 0.125],
[0.000, 0.000, 0.500], [0.125, 0.125, 0.625],
[0.500, 0.000, 0.500], [0.625, 0.125, 0.625],
[0.000, 0.500, 0.500], [0.125, 0.625, 0.625],
[0.500, 0.500, 0.500], [0.625, 0.625, 0.625]])
upos = s.pos_unit()
upos[np.abs(upos - 1.0) < 1e-10] = 0.0
assert (value_eq(upos, upos_ref))
def test_gen_diamond_direct():
"""
Create a conventional cell of diamond directly.
"""
import numpy as np
from structure import generate_structure
diamond = generate_structure(
units='A',
axes=[[3.57, 0.00, 0.00], [0.00, 3.57, 0.00], [0.00, 0.00, 3.57]],
elem=8 * ['C'],
posu=[[0.00, 0.00, 0.00], [0.25, 0.25, 0.25], [0.00, 0.50, 0.50],
[0.25, 0.75, 0.75], [0.50, 0.00, 0.50], [0.75, 0.25, 0.75],
[0.50, 0.50, 0.00], [0.75, 0.75, 0.25]],
)
assert (diamond.units == 'A')
assert (tuple(diamond.bconds) == tuple('ppp'))
assert (value_eq(diamond.axes, 3.57 * np.eye(3)))
assert (value_eq(list(diamond.center), 3 * [1.785]))
assert (value_eq(diamond.kaxes, 1.75999588 * np.eye(3)))
assert (list(diamond.elem) == 8 * ['C'])
assert (value_eq(tuple(diamond.pos[-1]), (2.6775, 2.6775, 0.8925)))
assert (len(diamond.kpoints) == 0)
assert (len(diamond.kweights) == 0)
assert (diamond.frozen is None)
assert (diamond.folded_structure is None)
def test_read_cif():
"""
Read La2CuO4 structure from a CIF file.
"""
from structure import read_structure, generate_structure
files = get_files()
# Read from CIF file
s = read_structure(files['La2CuO4_ICSD69312.cif'])
ref = generate_structure(
units='A',
axes=[[2.665, 0., -6.5525], [0., 5.4126, 0.], [2.665, 0., 6.5525]],
elem='La La La La Cu Cu O O O O O O O O'.split(),
pos=[[2.665, 5.37038172,
-1.8071795], [2.665, 2.74851828, 4.7453205],
[2.665, 2.66408172, -4.7453205],
[2.665, 0.04221828, 1.8071795], [0., 0., 0.],
[2.665, 2.7063, 0.], [1.3325, 1.35315, -0.128429],
[3.9975, 4.05945, 0.128429], [3.9975, 1.35315, -0.128429],
[1.3325, 4.05945, 0.128429], [2.665, 0.23490684, -4.1398695],
[2.665, 2.47139316,
2.4126305], [2.665, 2.94120684, -2.4126305],
[2.665, 5.17769316, 4.1398695]],
)
assert (structure_same(s, ref))
def demo_freeze():
"""
Freeze sets of atoms to prevent relaxation.
"""
g = generate_structure(
structure='graphene',
cell='prim',
tiling=(6, 6, 1),
)
g.recenter((0, 0, 0))
# Select atoms to be frozen
outer_atoms = np.sqrt((g.pos**2).sum(1)) > 3.2
# Freeze the atoms
g.freeze(outer_atoms)
# Get a mask array identifying the frozen atoms
frozen = g.is_frozen()
# Plot the frozen and movable atoms
plt.figure(tight_layout=True)
g.plot2d_ax(0, 1, 'k', lw=2)
t = 2 * np.pi * np.linspace(0, 1, 400)
plt.plot(3.2 * np.cos(t), 3.2 * np.sin(t), 'g--')
plt.plot(g.pos[frozen, 0], g.pos[frozen, 1], 'bo', label='frozen')
plt.plot(g.pos[~frozen, 0], g.pos[~frozen, 1], 'ro', label='movable')
plt.axis('equal')
plt.legend()
plt.xlabel('x (A)')
plt.ylabel('y (A)')
plt.title('demo freeze: prevent atoms from relaxing')
plt.show()
def test_bounding_box():
import numpy as np
from structure import generate_structure, read_structure
files = get_files()
h2o = generate_structure(
elem=['O', 'H', 'H'],
pos=[[0.000000, 0.000000, 0.000000], [0.000000, -0.757160, 0.586260],
[0.000000, 0.757160, 0.586260]],
units='A', # Angstroms
)
# add a box by hand to the water molecule
h2o_diy = h2o.copy()
h2o_diy.set_axes(8.0 * np.eye(3))
assert (value_eq(h2o_diy.axes, 8. * np.eye(3)))
# automatically add a bounding box to the water molecule
h2o_auto = h2o.copy()
h2o_auto.bounding_box(box='cubic', minsize=8.0)
assert (value_eq(h2o_auto.axes, 8. * np.eye(3)))
assert (value_eq(tuple(h2o_auto.pos[-1]), (4., 4.75716, 4.29313)))
s = read_structure(files['coronene.xyz'])
# make a bounding box that is at least 5 A from the nearest atom
s.bounding_box(mindist=5.0)
ref_axes = np.array([[16.4035, 0., 0.], [0., 16.3786, 0.], [0., 0., 10.]])
assert (value_eq(s.axes, ref_axes))
assert (value_eq(s.pos[:, 2].min(), 5.0))
assert (value_eq(s.pos[:, 2].max(), 5.0))
def test_primitive_search():
"""
Find the primitive cell given a supercell.
"""
from structure import generate_structure
d2 = generate_structure(
structure='diamond',
cell='prim',
)
tmatrix = [[2, -2, 2], [2, 2, -2], [-2, 2, 2]]
d64 = d2.tile(tmatrix)
# Remove all traces of the 2 atom cell, supercell is all that remains
d64.remove_folded()
del d2
# Find the primitive cell from the supercell
dprim = d64.primitive()
tmatrix = d64.tilematrix(dprim)
axes_ref = np.array([[0., 1.785, 1.785], [1.785, 0., 1.785],
[1.785, 1.785, 0.]])
tmatrix_ref = np.array([[-2, 2, 2], [2, -2, 2], [2, 2, -2]])
assert (value_eq(dprim.axes, axes_ref))
assert (value_eq(tmatrix, tmatrix_ref))
def demo_cell_constants():
"""
Compute the cell volume, Madelung constant, and Makov Payne correction
"""
d2 = generate_structure(
structure='diamond',
cell='prim',
)
# Construct the cubic 64 atom supercell
d64 = d2.tile_opt(32)
# Print the volume
print('\nVolume of 64 atom cell (A): {}'.format(d64.volume()))
# Print the Madelung constant
# ( see equation 7 in PRB 78 125106 (2008) )
print('\nMadelung constant (Ha): {}'.format(d64.madelung()))
# Print Makov-Payne corrections
mp_q1 = d64.makov_payne(q=1, eps=5.68)
mp_q2 = d64.makov_payne(q=2, eps=5.68)
print(
'\nMakov-Payne corr. (Ha) for charged defect (q=1): {}'.format(mp_q1))
print(
'\nMakov-Payne corr. (Ha) for charged defect (q=2): {}'.format(mp_q2))
def demo_symm_kpoints():
"""
Add symmetrized Monkhorst-Pack kpoints.
"""
# Note: this demo requires spglib
g44 = generate_structure(
structure='graphene',
cell='prim',
tiling=(4, 4, 1),
kgrid=(4, 4, 1),
kshift=(0, 0, 0),
symm_kgrid=True,
)
g11 = g44.folded_structure
# Print the symmtrized kpoints
print('Symmetrized k-points:\n{}'.format(g44.kpoints_unit()))
print('Symmetrized weights:\n{}'.format(g44.kweights))
# Plot the symmetrized kpoints
plt.figure(tight_layout=True)
g11.plot2d_kax(0, 1, 'r', lw=2, label='primcell')
g44.plot2d_kax(0, 1, 'k', lw=2, label='supercell')
g11.plot2d_kp(0, 1, 'g.')
g44.plot2d_kp(0, 1, 'bo')
plt.legend()
plt.axis('equal')
plt.xlabel('x (A)')
plt.ylabel('y (A)')
plt.title('demo kpoints: symmetrized kpoints in 4x4 graphene')
plt.show()
def demo_random_kpoints():
"""
Add random k-points.
"""
g11 = generate_structure(
structure='graphene',
cell='prim',
)
# Perform a 4x4 tiling of the primitive cell
g44 = g11.tile(4, 4, 1)
# Add random kpoints instead of an MP mesh
rand = np.random.uniform(size=(20, 2))
kpoints = np.dot(rand, g44.kaxes[0:2])
g44.add_kpoints(kpoints)
g11 = g44.folded_structure
# Plot the random kpoints
plt.figure(tight_layout=True)
g11.plot2d_kax(0, 1, 'r', lw=2, label='primcell')
g44.plot2d_kax(0, 1, 'k', lw=2, label='supercell')
g11.plot2d_kp(0, 1, 'g.')
g44.plot2d_kp(0, 1, 'bo')
plt.legend()
plt.axis('equal')
plt.xlabel('x (A)')
plt.ylabel('y (A)')
plt.title('demo kpoints: random kpoints in 4x4 graphene')
plt.show()
def demo_mp_kpoints():
"""
Add k-points according to Monkhorst-Pack grid.
"""
g11 = generate_structure(
structure='graphene',
cell='prim',
)
# Perform a 4x4 tiling of the primitive cell
g44 = g11.tile(4, 4, 1)
# Add a Gamma-centered 2x2 Monkhorst-Pack grid
g44g = g44.copy()
g11g = g44g.folded_structure
g44g.add_kmesh(kgrid=(2, 2, 1), kshift=(0, 0, 0))
# Add a shifted 2x2 Monkhorst-Pack grid
g44s = g44.copy()
g11s = g44s.folded_structure
g44s.add_kmesh(kgrid=(2, 2, 1), kshift=(0.5, 0.5, 0))
# Get the mapping between supercell and primitive cell k-points
print('Monk-horst pack grid')
kmap = g44s.kmap()
print('# of k-points in supercell: {}'.format(len(g44s.kpoints)))
print('# of k-points in primcell : {}'.format(len(g11s.kpoints)))
print('index mapping from super to prim:\n{}'.format(
str(kmap).replace(' ', '')))
# Plot kpoints for the 2x2 unshifted MP mesh
plt.figure(tight_layout=True)
g11g.plot2d_kax(0, 1, 'r', lw=2, label='primcell')
g44g.plot2d_kax(0, 1, 'k', lw=2, label='supercell')
g11g.plot2d_kp(0, 1, 'g.')
g44g.plot2d_kp(0, 1, 'bo')
plt.legend()
plt.axis('equal')
plt.xlabel('x (A)')
plt.ylabel('y (A)')
plt.title('demo kpoints: unshifted 2x2 MP mesh in 4x4 graphene')
# Plot kpoints for the 2x2 shifted MP mesh
plt.figure(tight_layout=True)
g11s.plot2d_kax(0, 1, 'r', lw=2, label='primcell')
g44s.plot2d_kax(0, 1, 'k', lw=2, label='supercell')
g11s.plot2d_kp(0, 1, 'g.')
g44s.plot2d_kp(0, 1, 'bo')
plt.legend()
plt.axis('equal')
plt.xlabel('x (A)')
plt.ylabel('y (A)')
plt.title('demo kpoints: shifted 2x2 MP mesh in 4x4 graphene')
plt.show()
def test_rwigner():
from structure import generate_structure
s = generate_structure(
structure='graphene',
cell='prim',
tiling=(4, 4, 1),
)
rw = s.rwigner()
assert (value_eq(float(rw), 4.924))
def test_rinscribe():
from structure import generate_structure
s = generate_structure(
structure='graphene',
cell='prim',
tiling=(4, 4, 1),
)
ri = s.rinscribe()
assert (value_eq(float(ri), 4.2643090882345795))
def demo_water_box():
"""
Make simulation cells for water molecule and dimer.
"""
h2o = generate_structure(
elem=['O', 'H', 'H'],
pos=[[0.000000, 0.000000, 0.000000], [0.000000, -0.757160, 0.586260],
[0.000000, 0.757160, 0.586260]],
units='A', # Angstroms
)
# add a box by hand to the water molecule
h2o_diy = h2o.copy()
h2o_diy.set_axes(8.0 * np.eye(3))
# automatically add a bounding box to the water molecule
h2o_auto = h2o.copy()
h2o_auto.bounding_box(box='cubic', minsize=8.0)
# make a water dimer configuration
h2o1 = h2o.copy()
h2o1.bounding_box(box='cubic', minsize=8.0)
h2o2 = h2o1.copy()
h2o1.translate((0, 0, -1.1))
h2o2.translate((0, 0, 1.1))
h2o_dimer = h2o1.copy()
h2o_dimer.incorporate(h2o2)
# plot the water molecule with DIY box
plt.figure(tight_layout=True)
h2o_diy.plot2d_ax(1, 2, 'k', lw=2)
h2o_diy.plot2d_pos(1, 2, 'bo')
plt.axis('equal')
plt.xlabel('y (A)')
plt.ylabel('z (A)')
plt.title('demo water box: DIY box')
# plot the water molecule with an automatic box
plt.figure(tight_layout=True)
h2o_auto.plot2d_ax(1, 2, 'k', lw=2)
h2o_auto.plot2d_pos(1, 2, 'bo')
plt.axis('equal')
plt.xlabel('y (A)')
plt.ylabel('z (A)')
plt.title('demo water box: automatic box')
# plot the water dimer
plt.figure(tight_layout=True)
h2o_dimer.plot2d_ax(1, 2, 'k', lw=2)
h2o_dimer.plot2d_pos(1, 2, 'bo')
plt.axis('equal')
plt.xlabel('y (A)')
plt.ylabel('z (A)')
plt.title('demo water box: water dimer')
plt.show()
def get_crystal_structures():
from generic import obj
from structure import Crystal, generate_structure
if len(crystal_structures) == 0:
crys = crystal_structures
for (latt, cell), inputs in Crystal.known_crystals.items():
s = generate_structure(structure=latt, cell=cell)
crys[latt + '_' + cell] = s
#end for
#end if
return obj(crystal_structures)
def get_generated_structures():
from generic import obj
from structure import generate_structure
if len(generated_structures) == 0:
ref_in = get_reference_inputs()
gen = generated_structures
for name, inputs in ref_in.items():
gen[name] = generate_structure(**inputs)
#end for
#end if
return obj(generated_structures)
def test_gen_graphene():
"""
Create a graphene cell using stored information.
"""
from structure import generate_structure
graphene = generate_structure(
structure='graphene',
cell='prim',
)
ref = generate_structure(
units='A',
axes=[[2.46200000e+00, 0.00000000e+00, 0.00000000e+00],
[-1.23100000e+00, 2.13215454e+00, 0.00000000e+00],
[9.18485099e-16, 1.59086286e-15, 1.50000000e+01]],
elem=['C', 'C'],
pos=[[0., 0., 0.], [1.231, 0.71071818, 0.]],
)
assert (structure_same(graphene, ref))
def demo_gen_graphene():
"""
Create a graphene cell using stored information.
"""
graphene = generate_structure(
structure='graphene',
cell='prim',
)
# print structure data
print(graphene)
def test_interpolate():
"""
Interpolate between two "relaxed" structures for NEB initialization.
"""
import numpy as np
from structure import generate_structure
g = generate_structure(
structure='graphene',
cell='prim',
tiling=(4, 4, 1),
)
g11 = g.folded_structure
# Make chromium atom positions (pretend like they are above the surface)
npos = np.dot((1. / 3, 2. / 3, 0), g11.axes)
npos1 = npos + 3 * g11.axes[0]
npos2 = npos1 + g11.axes[0] + g11.axes[1]
# "Relaxed" structure with additional atom on one ring
gr1 = g.copy()
gr1.add_atoms(['Cr'], [npos1])
# "Relaxed" structure with additional atom on neighboring ring
gr2 = g.copy()
gr2.add_atoms(['Cr'], [npos2])
gr2.recenter()
# Interpolate between the two structures within min. image convention
spath = gr1.interpolate(gr2, 10)
Cr_positions_ref = np.array([[7.386, 1.42143636, 0.],
[7.49790909, 1.61526859, 0.],
[7.60981818, 1.80910083, 0.],
[7.72172727, 2.00293306, 0.],
[7.83363636, 2.19676529, 0.],
[7.94554545, 2.39059752, 0.],
[8.05745455, 2.58442975, 0.],
[8.16936364, 2.77826198, 0.],
[-1.56672727, 2.97209421, 0.],
[-1.45481818, 3.16592644, 0.],
[-1.34290909, 3.35975868, 0.],
[-1.231, 3.55359091, 0.]])
Cr_positions = []
for gr in spath:
Cr_positions.append(gr.pos[-1])
#end for
Cr_positions = np.array(Cr_positions)
assert (value_eq(Cr_positions, Cr_positions_ref))
def generate_physical_system(**kwargs):
for var,val in ps_defaults.iteritems():
if not var in kwargs:
kwargs[var] = val
#end if
#end for
if 'type' in kwargs and kwargs['type']=='atom':
del kwargs['kshift']
if not 'units' in kwargs:
kwargs['units'] = 'B'
#end if
#end if
generation_info = obj()
generation_info.transfer_from(deepcopy(kwargs))
net_charge = kwargs['net_charge']
net_spin = kwargs['net_spin']
del kwargs['net_spin']
del kwargs['net_charge']
if 'particles' in kwargs:
particles = kwargs['particles']
del kwargs['particles']
else:
generation_info.particles = None
#end if
valency = dict()
remove = []
for var in kwargs:
if var in Matter.elements:
valency[var] = kwargs[var]
remove.append(var)
#end if
#end if
generation_info.valency = deepcopy(valency)
for var in remove:
del kwargs[var]
#end for
ps = PhysicalSystem(
structure = generate_structure(**kwargs),
net_charge = net_charge,
net_spin = net_spin,
**valency
)
ps.generation_info = generation_info
return ps
def test_opt_tiling():
import numpy as np
from structure import generate_structure
dprim = generate_structure(
structure='diamond',
cell='prim',
)
dopt = dprim.tile_opt(4)
tmatrix_ref = np.array([[1, -1, 1], [1, 1, -1], [-1, 1, 1]])
assert (value_eq(dopt.tmatrix, tmatrix_ref))
assert (len(dopt.elem) == 4 * len(dprim.elem))
assert (value_eq(dopt.axes, 3.57 * np.eye(3)))
def demo_unit_coords():
"""
Get atomic positions and k-points in unit coordinates.
"""
s = generate_structure(
structure='diamond',
cell='prim',
tiling=(2, 2, 2),
kgrid=(2, 2, 2),
kshift=(0.5, 0.5, 0.5),
)
print('\nAtomic positions in unit coordinates:\n{}'.format(s.pos_unit()))
print('\nk-points in unit coordinates:\n{}'.format(s.kpoints_unit()))
def test_gen_molecule():
"""
Create an H2O molecule.
"""
from structure import generate_structure
h2o = generate_structure(
elem=['O', 'H', 'H'],
pos=[[0.000000, 0.000000, 0.000000], [0.000000, -0.757160, 0.586260],
[0.000000, 0.757160, 0.586260]],
units='A', # Angstroms
)
# print important internal attributes
assert (tuple(h2o.elem) == tuple('OHH'))
assert (value_eq(h2o.pos[2, 2], 0.586260))
assert (h2o.units == 'A')
def demo_interpolate():
"""
Interpolate between two "relaxed" structures for NEB initialization.
"""
g = generate_structure(
structure='graphene',
cell='prim',
tiling=(4, 4, 1),
)
g11 = g.folded_structure
# Make chromium atom positions (pretend like they are above the surface)
npos = np.dot((1. / 3, 2. / 3, 0), g11.axes)
npos1 = npos + 3 * g11.axes[0]
npos2 = npos1 + g11.axes[0] + g11.axes[1]
# "Relaxed" structure with additional atom on one ring
gr1 = g.copy()
gr1.add_atoms(['Cr'], [npos1])
# "Relaxed" structure with additional atom on neighboring ring
gr2 = g.copy()
gr2.add_atoms(['Cr'], [npos2])
gr2.recenter()
# Interpolate between the two structures within min. image convention
spath = gr1.interpolate(gr2, 10)
# Plot the (linear) interpolation path
plt.figure(tight_layout=True)
for gr in spath:
gr.plot2d_ax(0, 1, 'k', lw=2)
gr.plot2d_pos(0, 1, 'bo')
npos = gr.pos[-1]
plt.plot([npos[0]], [npos[1]], 'go')
#end for
plt.axis('equal')
plt.xlabel('x (A)')
plt.ylabel('y (A)')
plt.title('demo interpolate: paths for NEB')
plt.show()
def test_min_image_distances():
"""
Compute minimum image distances between nearest neighbors.
"""
import numpy as np
from structure import generate_structure
g = generate_structure(
structure='graphene',
cell='prim',
tiling=(4, 4, 1),
)
# Get the neighbor (index) table, along with sorted distance
# and displacement tables.
nt, dt, vt = g.neighbor_table(distances=True, vectors=True)
# Restrict to 3 nearest neighbors (not including self at index 0)
nt = nt[:, 1:4]
dt = dt[:, 1:4]
vt = vt[:, 1:4]
nt_ref = np.array([[1, 11, 9], [30, 0, 24], [3, 11, 13], [2, 26, 24],
[5, 15, 13], [4, 26, 28], [7, 9, 15], [6, 30, 28],
[9, 19, 17], [8, 6, 0], [11, 19, 21], [10, 0, 2],
[13, 23, 21], [12, 2, 4], [15, 17, 23], [14, 4, 6],
[17, 27, 25], [16, 8, 14], [19, 27, 29], [18, 10, 8],
[21, 29, 31], [20, 12, 10], [23, 25, 31], [22, 12, 14],
[25, 1, 3], [24, 22, 16], [27, 3, 5], [26, 18, 16],
[29, 5, 7], [28, 18, 20], [31, 1, 7], [30, 22, 20]])
for nti, nti_ref in zip(nt, nt_ref):
assert (set(nti) == set(nti_ref))
#end for
dist = dt.ravel()
assert (value_eq(dist.min(), 1.42143636))
assert (value_eq(dist.max(), 1.42143636))
vec = vt.ravel()
vec.shape = np.prod(dt.shape), 3
vdist = np.linalg.norm(vec, axis=1)
assert (value_eq(vdist, dist))
def generate_physical_system(**kwargs):
for var,val in ps_defaults.iteritems():
if not var in kwargs:
kwargs[var] = val
#end if
#end for
type = kwargs['type']
if type=='atom' or type=='dimer' or type=='trimer':
del kwargs['kshift']
del kwargs['tiling']
#if not 'units' in kwargs:
# kwargs['units'] = 'B'
##end if
tiling = None
else:
tiling = kwargs['tiling']
#end if
if 'structure' in kwargs:
s = kwargs['structure']
is_str = isinstance(s,str)
if is_str and os.path.exists(s):# and '.' in os.path.split(s)[1]:
if 'elem' in kwargs:
print 'system using elem'
kwargs['structure'] = read_structure(s,elem=kwargs['elem'])
else:
kwargs['structure'] = read_structure(s)
#end if
elif is_str and '/' in s:
PhysicalSystem.class_error('path provided for structure file does not exist: '+s,'generate_physical_system')
#end if
#end if
generation_info = obj()
generation_info.transfer_from(deepcopy(kwargs))
net_charge = kwargs['net_charge']
net_spin = kwargs['net_spin']
tiled_spin = kwargs['tiled_spin']
extensive = kwargs['extensive']
del kwargs['net_spin']
del kwargs['net_charge']
del kwargs['tiled_spin']
del kwargs['extensive']
if 'particles' in kwargs:
particles = kwargs['particles']
del kwargs['particles']
else:
generation_info.particles = None
#end if
pretile = kwargs['pretile']
del kwargs['pretile']
valency = dict()
remove = []
for var in kwargs:
#if var in Matter.elements:
if is_element(var):
valency[var] = kwargs[var]
remove.append(var)
#end if
#end if
generation_info.valency = deepcopy(valency)
for var in remove:
del kwargs[var]
#end for
if pretile is None:
structure = generate_structure(**kwargs)
else:
for d in range(len(pretile)):
if tiling[d]%pretile[d]!=0:
PhysicalSystem.class_error('pretile does not divide evenly into tiling\n tiling provided: {0}\n pretile provided: {1}'.format(tiling,pretile),'generate_physical_system')
#end if
#end for
tiling = tuple(array(tiling)/array(pretile))
kwargs['tiling'] = pretile
pre = generate_structure(**kwargs)
pre.remove_folded_structure()
structure = pre.tile(tiling)
#end if
if tiling!=None and tiling!=(1,1,1):
fps = PhysicalSystem(
structure = structure.folded_structure,
net_charge = net_charge,
net_spin = net_spin,
**valency
)
structure.remove_folded()
folded_structure = fps.structure
if extensive:
ncells = int(round(structure.volume()/folded_structure.volume()))
net_charge = ncells*net_charge
net_spin = ncells*net_spin
#end if
if tiled_spin!=None:
net_spin = tiled_spin
#end if
ps = PhysicalSystem(
structure = structure,
net_charge = net_charge,
net_spin = net_spin,
**valency
)
structure.set_folded(folded_structure)
ps.folded_system = fps
else:
ps = PhysicalSystem(
structure = structure,
net_charge = net_charge,
net_spin = net_spin,
**valency
)
#end if
ps.generation_info = generation_info
return ps
net_charge = net_charge,
net_spin = net_spin,
**valency
)
#end if
ps.generation_info = generation_info
return ps
#end def generate_physical_system
if __name__=='__main__':
from structure import generate_structure
ps = PhysicalSystem(
structure = generate_structure('diamond','sc','Ge',(2,2,2),scale=5.639,units='A'),
net_charge = 1,
net_spin = 1,
Ge = 4
)
print 'net_charge',ps.net_charge
print 'net_spin ',ps.net_spin
print ps.particles
#end if
def generate_physical_system(**kwargs):
for var,val in ps_defaults.iteritems():
if not var in kwargs:
kwargs[var] = val
#end if
#end for
if 'type' in kwargs and kwargs['type']=='atom':
del kwargs['kshift']
if not 'units' in kwargs:
kwargs['units'] = 'B'
#end if
#end if
generation_info = obj()
generation_info.transfer_from(deepcopy(kwargs))
net_charge = kwargs['net_charge']
net_spin = kwargs['net_spin']
del kwargs['net_spin']
del kwargs['net_charge']
if 'particles' in kwargs:
particles = kwargs['particles']
del kwargs['particles']
else:
generation_info.particles = None
#end if
pretile = kwargs['pretile']
del kwargs['pretile']
valency = dict()
remove = []
for var in kwargs:
if var in Matter.elements:
valency[var] = kwargs[var]
remove.append(var)
#end if
#end if
generation_info.valency = deepcopy(valency)
for var in remove:
del kwargs[var]
#end for
if pretile is None:
structure = generate_structure(**kwargs)
else:
tiling = kwargs['tiling']
for d in range(len(pretile)):
if tiling[d]%pretile[d]!=0:
PhysicalSystem.class_error('pretile does not divide evenly into tiling\n tiling provided: {0}\n pretile provided: {1}'.format(tiling,pretile))
#end if
#end for
tiling = tuple(array(tiling)/array(pretile))
kwargs['tiling'] = pretile
pre = generate_structure(**kwargs)
pre.remove_folded_structure()
structure = pre.tile(tiling)
#end if
ps = PhysicalSystem(
structure = structure,
net_charge = net_charge,
net_spin = net_spin,
**valency
)
ps.generation_info = generation_info
return ps
