def disl_boundary_fix(system,
bwidth,
bshape='circle',
m=[1, 0, 0],
n=[0, 1, 0]):
"""
Creates a boundary region by changing atom types.
Parameters
----------
system : atomman.System
The system to add the boundary region to.
bwidth : float
The minimum thickness of the boundary region.
bshape : str, optional
The shape to make the boundary region. Options are 'circle' and
'rect' (default is 'circle').
"""
natypes = system.natypes
atype = system.atoms_prop(key='atype')
pos = system.atoms.pos
x = np.dot(pos, np.asaray(m, dtype='float64'))
y = np.dot(pos, np.asaray(n, dtype='float64'))
if bshape == 'circle':
# Find x or y bound closest to 0
smallest_xy = min([
abs(system.box.xlo),
abs(system.box.xhi),
abs(system.box.ylo),
abs(system.box.yhi)
])
radius = smallest_xy - bwidth
xy_mag = np.linalg.norm(pos[:, :2], axis=1)
atype[xy_mag > radius] += natypes
elif bshape == 'rect':
index = np.unique(
np.hstack((np.where(pos[:, 0] < system.box.xlo + bwidth),
np.where(pos[:, 0] > system.box.xhi - bwidth),
np.where(pos[:, 1] < system.box.ylo + bwidth),
np.where(pos[:, 1] > system.box.yhi - bwidth))))
atype[index] += natypes
else:
raise ValueError(
"Unknown boundary shape type! Enter 'circle' or 'rect'")
new_system = deepcopy(system)
new_system.atoms.atype = atype
new_system.symbols = list(system.symbols) * 2
return new_system
def gain(col, tag_col):
I_tab = Entropy(tag_col)
tt_count = np.asarray(col).size
dist_term = np.unique(col)
tm_count = np.array(dist_term).size
info = 0
for i in range(tm_count):
_listt = []
for j in range(tt_count):
if (col[j] == dist_term[i]):
_list.append(tag_col[j])
e = Entropy(_list)
w = np.asaray(_list).size / tt_count
info += e * w
gain = I_tab - info
return gain
def text_to_instance(
self, # type: ignore
answer: str,
question: str,
passages: List[str],
passages_length: List[int],
passages_is_selected: List[int],
concatenated_passage: str) -> Instance:
passage_field = TextField(tokenized_passage, self._token_indexers)
passages_length_field = ArrayField(np.asaray(passages_length))
passages_is_selected_field = ArrayField(
np.asarray(passages_is_selected))
fields = {
'answer': answer_field,
'question': question_field,
'passage': passage_field,
'passages_length': passages_length_field,
'passages_is_selected': passages_is_selected_field
}
return Instance(fields)