def gen_perturb(path, irrep, io):
images = path.images
DG = path.distortion_group.matrices
num_unstar = path.distortion_group.num_unstar
numIm = len(images)
irrep_tools = IrrepTools()
# -- Generate starting basis
atoms1 = images[0].frac_coords
numAtoms = len(atoms1)
basis = np.zeros(numAtoms)
atoms2 = images[numIm - 1].frac_coords
m_vec = np.dot(np.linalg.inv(images[0].lattice.matrix),
[io.min_move, io.min_move, io.min_move])
for i in range(0, numAtoms):
if not closewrapped(atoms1[i, :], atoms2[i, :], m_vec):
basis[i] = 1
# -- Generate matrix showing atom mapping for each operations
a_map = path.gen_atom_map(basis=basis, vectol=io.vectol)
# -- Generate and apply modes for an irrep of arbitrary dimension
pt = np.zeros((numIm, numAtoms, 3))
pt_mode_init = irrep_tools.projection_diag(images=images,
symmop_list=DG,
irrep=irrep,
num_unstar=num_unstar,
a_map=a_map,
basis=basis)
if not np.any(pt_mode_init):
raise RuntimeError(
f"Uniform random initial perturbation does not contain any non-zero contributions from irrep {irrep.stokes_number}.\
Try a different irrep.")
pt_mode_init = pt_mode_init / np.linalg.norm(
np.ndarray.flatten(pt_mode_init))
pt += io.m_co[0] * pt_mode_init
if io.irr_dim > 1:
for i in range(1, io.irr_dim):
pt_mode = irrep_tools.projection_odiag(
images=images,
symmop_list=DG,
num_unstar=num_unstar,
irrep=irrep,
vec=pt_mode_init,
index=i,
a_map=a_map,
basis=basis,
)
pt += io.m_co[i] * (pt_mode /
np.linalg.norm(np.ndarray.flatten(pt_mode)))
p_vec = [
io.p_mag / np.linalg.norm(images[0].lattice.matrix[m, :])
for m in range(0, 3)
]
# print pt[3]/np.amax(abs(pt[3]))
# print(np.amax(p_vec*(pt[:,:,:]/np.amax(abs(pt)))))
images_alt = []
for i in range(numIm):
image_copy = images[i].copy()
alt_species = image_copy.species
perturbed_coords = image_copy.frac_coords + p_vec * (pt[i, :, :] /
np.amax(abs(pt)))
for j in range(numAtoms):
image_copy.replace(j, alt_species[j], perturbed_coords[j])
images_alt.append(image_copy)
return images_alt, basis
def gen_perturb(path, irrep, io):
images = path.images
DG = path.distortion_group.matrices
num_unstar = path.distortion_group.num_unstar
numIm = len(images)
irrep_tools = IrrepTools()
io.print("\n\n\n\n" + ("=" * 27 + "\n") * 2 +
"\nGenerating perturbations...\n\n" + ("=" * 27 + "\n") * 2 +
"\n")
io.print("***THE FOLLOWING DATA IS FOR THE PERTURBED IMAGES***\n\n")
# -- Generate starting basis
atoms1 = images[0].frac_coords
numAtoms = len(atoms1)
basis = np.zeros(numAtoms)
atoms2 = images[numIm - 1].frac_coords
m_vec = np.dot(np.linalg.inv(images[0].lattice.matrix),
[io.min_move, io.min_move, io.min_move])
for i in range(0, numAtoms):
if not closewrapped(atoms1[i, :], atoms2[i, :], m_vec):
basis[i] = 1
io.print("------- Atoms included in basis:")
symbols = images[0].species
for i in range(0, numAtoms):
if basis[i] == 0:
io.print(str(symbols[i]) + " No")
else:
io.print(str(symbols[i]) + " Yes")
# -- Generate matrix showing atom mapping for each operations
a_map = path.gen_atom_map(basis=basis, vectol=io.vectol)
# -- Generate and apply modes for an irrep of arbitrary dimension
pt = np.zeros((numIm, numAtoms, 3))
pt_mode_init = irrep_tools.projection_diag(images=images,
symmop_list=DG,
irrep=irrep,
num_unstar=num_unstar,
a_map=a_map,
basis=basis)
pt_mode_init = pt_mode_init / \
np.linalg.norm(np.ndarray.flatten(pt_mode_init))
pt += io.m_co[0] * pt_mode_init
if io.irr_dim > 1:
for i in range(1, io.irr_dim):
pt_mode = irrep_tools.projection_odiag(images=images,
symmop_list=DG,
num_unstar=num_unstar,
irrep=irrep,
vec=pt_mode_init,
index=i,
a_map=a_map,
basis=basis)
pt += io.m_co[i] * \
(pt_mode/np.linalg.norm(np.ndarray.flatten(pt_mode)))
p_vec = [
io.p_mag / np.linalg.norm(images[0].lattice.matrix[m, :])
for m in range(0, 3)
]
# print pt[3]/np.amax(abs(pt[3]))
# print(np.amax(p_vec*(pt[:,:,:]/np.amax(abs(pt)))))
images_alt = []
for i in range(numIm):
image_copy = images[i].copy()
alt_species = image_copy.species
perturbed_coords = image_copy.frac_coords + p_vec * (pt[i, :, :] /
np.amax(abs(pt)))
for j in range(numAtoms):
image_copy.replace(j, alt_species[j], perturbed_coords[j])
images_alt.append(image_copy)
return images_alt