def get_hessian(iterable):
LR = ListReader(iterable)
LR.go_by_keys("++ Symmetrized Mass Weighted Hessian ++")
LR.get_next_lines(2)
part = LR.get_all_by_keys(
"* Projecting out translational and rotational degrees of freedom",
"Mass Weighted Hessian Eigenvalues")
temporary = []
for line in part:
try:
[int(i) for i in line.replace("\n", "").split()[3]]
except IndexError:
pass
except ValueError:
if not "* Vibrational frequencies, " in line:
if "averaged" in line:
print(1)
temporary.append(
[float(i) for i in line.replace("\n", "").split()[1:]])
ndim = int(math.sqrt((len(temporary) - 1) * 6 + len(temporary[-1])))
hessian = np.zeros((ndim, ndim))
for i in range(len(temporary)):
for j in range(len(temporary[i])):
index1 = (i // ndim) * 6
index2 = (i % ndim)
hessian[index1 + j, index2] = temporary[i][j]
return np.array(hessian)
def get_force(self, lines) -> np.ndarray:
LR = ListReader(lines)
LR.go_by_keys(*self.stop_keys["force_start"])
LR.get_next_lines(2)
part = LR.get_all_by_keys(*self.stop_keys["force_end"])
result = []
for line in part:
result.extend(map(float, line.replace("\n" , "").split()[2:]))
return np.array(result)
def get_criteria(self, lines) -> dict:
result = dict()
LR = ListReader(lines)
LR.go_by_keys(*self.stop_keys["crit_start"])
part = LR.get_all_by_keys(*self.stop_keys["crit_end"])
try:
for line in part:
result.update({line.split()[0] + " " + line.split()[1]: line.split()[2]})
return result
except:
return np.nan
def get_MO(self, lines):
LR = ListReader(lines)
line = LR.go_by_keys(*self.stop_keys["pop_end"])
coeff = []
coeff.extend(map(float, line.replace("\n", "").split()[4:]))
part = LR.get_all_if_keys(*self.stop_keys["pop_end"])
for line in part:
coeff.extend(map(float, line.replace("\n", "").split()[4:]))
n_basis = len(coeff)
MO = np.zeros((n_basis, n_basis))
LR.get_next_lines(3)
for i in range(int(n_basis/5)):
part = LR.get_all_by_keys("Eigenvalues --")
part = iter(part)
j = 0
for line in part:
if j == n_basis:
break
if len(line.split()) == 5:
break
elif len(line.split()) == 9:
MO[i * 5: i * 5 + 5, j] = line.replace("\n", "").split()[4:]
else:
MO[i * 5: i * 5 + 5, j] = line.replace("\n", "").split()[2:]
j = j + 1
last_orb = n_basis % 5
part = LR.get_all_by_keys("orbital", "pop", "Density Matrix:")
j = 0
i = int(n_basis/5)
res = n_basis % 5
if res is not 0:
for line in part:
if len(line.split()) == last_orb + 4:
MO[i * 5: i * 5 + res, j] = line.replace("\n", "").split()[4:]
else:
MO[i * 5: i * 5 + res, j] = line.replace("\n", "").split()[2:]
j = j + 1
for i in range(MO.shape[0]):
for j in range(MO.shape[1]):
MO[i, j] = float(MO[i, j])
return coeff, MO
def get_geometry_from_bagel(iterable):
LR = ListReader(iterable)
LR.go_by_keys("*** Geometry ***")
LR.get_next_lines(1)
part_of_file = LR.get_all_by_keys(
" The gradients will be computed analytically.")
coord = []
for line in part_of_file:
line = line.replace(",", "")
if len(line.split()) < 4:
break
coord.extend([float(i) for i in line.split()[7:10]])
LR.go_by_keys("* Nuclear energy gradient")
LR.get_next_lines(1)
part_of_file = LR.get_all_by_keys("* Gradient computed with")
grads = []
for line in part_of_file:
line = line.replace("\n", "")
if " x " in line or " y " in line or " z " in line:
grads.append(float(line.replace("\n", "").split()[-1]))
return np.array(coord), np.array(grads)
def get_coord(self, lines) -> tuple:
LR = ListReader(lines)
LR.go_by_keys(*self.stop_keys["opt_geom_start"])
LR.go_by_keys("--------------------------")
LR.get_next_lines(3)
part = LR.get_all_by_keys(*self.stop_keys["opt_geom_end"])
charges = []
coords = []
for line in part:
charges.append(line.split()[1])
coords.extend(map(float, line.replace("\n", "").split()[3:]))
return charges, np.array(coords)
def get_hessian(self, lines):
LR = ListReader(lines)
LR.go_by_keys("The second derivative matrix:")
LR.get_next_lines(1)
part = LR.get_all_by_keys("ITU= 0")
part1 = iter(part)
n = 0
for i in part1:
try:
_ = float(i.split()[1])
except:
break
n = n + 1
part = iter(part)
hessian = np.zeros((n, n))
i = 0
shifts = int(n / 5)
if n % 5 != 0:
shifts = shifts + 1
for j in range(shifts):
for i in range(n - j*5):
try:
line = next(part)
line = line.replace("\n", "")
l = i + 1
if l > 5:
l = 5
hessian[i + j*5, j*5: j*5 + l] = [x for x in map(float, line.split()[1:])]
except StopIteration:
break
try:
next(part)
except StopIteration:
break
for i in range(n):
for j in range(i):
hessian[j, i] = hessian[i, j]
return hessian