Révision e5faf87a
| b/modules/screening.py | ||
|---|---|---|
| 220 | 220 |
for atom in molec: |
| 221 | 221 |
if atom.index == ctr_idx: |
| 222 | 222 |
continue |
| 223 |
if molec.get_distance(ctr_idx, atom) < min_dist: |
|
| 223 |
if molec.get_distance(ctr_idx, atom.index) < min_dist:
|
|
| 224 | 224 |
min_dist = molec.get_distance(ctr_idx, atom.index) |
| 225 | 225 |
min_idx = atom.index |
| 226 | 226 |
cutoffs[ctr_idx] = min_dist - cutoffs[min_idx] + 0.05 |
| ... | ... | |
| 228 | 228 |
self_interaction=False) |
| 229 | 229 |
neigh_vects = [vects[i] for i, atm in enumerate(refs) if atm == ctr_idx] |
| 230 | 230 |
target_vect = vect_avg(neigh_vects) |
| 231 |
# If the target vector is 0 it gets reassigned to the vector pointing |
|
| 232 |
# towards the nearest atom. |
|
| 233 |
if target_vect.tolist() == [0, 0, 0]: |
|
| 234 |
target_vect = np.array([np.inf] * 3) |
|
| 231 |
# If the target vector is 0 (the center is at the baricenter of its |
|
| 232 |
# neighbors). Assuming the adsorption center is coplanar or colinear to its |
|
| 233 |
# neighbors (it would not make a lot of sense to chose a center which is |
|
| 234 |
# the baricenter of neighbors distributed in 3D), the target_vector is |
|
| 235 |
# chosen perpendicular to the nearest neighbor. |
|
| 236 |
if np.allclose(target_vect, 0, rtol=1e-3): |
|
| 237 |
nn_vect = np.array([np.inf] * 3) |
|
| 235 | 238 |
for vect in neigh_vects: |
| 236 |
if np.linalg.norm(vect) < np.linalg.norm(target_vect): |
|
| 237 |
target_vect = vect |
|
| 239 |
if np.linalg.norm(vect) < np.linalg.norm(nn_vect): |
|
| 240 |
nn_vect = vect |
|
| 241 |
cart_axes = [[1, 0, 0], [0, 1, 0], [0, 0, 1]] |
|
| 242 |
axis = cart_axes[int(np.argmax([np.linalg.norm(np.cross(ax, nn_vect)) |
|
| 243 |
for ax in cart_axes]))] |
|
| 244 |
target_vect = np.cross(axis, nn_vect) |
|
| 238 | 245 |
|
| 239 | 246 |
rot_vect = np.cross(target_vect, ref_vect) |
| 240 | 247 |
if np.allclose(rot_vect, 0): |
| ... | ... | |
| 525 | 532 |
""" |
| 526 | 533 |
from copy import deepcopy |
| 527 | 534 |
slab_ads_list = [] |
| 528 |
if np.any([np.allclose(ctr_coord, atom.position, rtol=1e-2) |
|
| 529 |
for atom in orig_molec]): |
|
| 530 |
orig_molec = align_molec(orig_molec, ctr_coord, norm_vect) |
|
| 531 |
else: |
|
| 532 |
cart_axes = [[1, 0, 0], [0, 1, 0], [0, 0, 1]] |
|
| 533 |
axis = cart_axes[int(np.argmax([np.linalg.norm(np.cross(ax, norm_vect)) |
|
| 534 |
for ax in cart_axes]))] |
|
| 535 |
align_vect = np.cross(axis, norm_vect) |
|
| 536 |
orig_molec = align_molec(orig_molec, ctr_coord, align_vect) |
|
| 535 |
orig_molec = align_molec(orig_molec, ctr_coord, norm_vect) |
|
| 537 | 536 |
# rotation around z |
| 538 | 537 |
for alpha in np.arange(0, 360, 360 / num_pts): |
| 539 | 538 |
# rotation around x' |
Formats disponibles : Unified diff