def add_random(self):
"""
Creates a new set of variables to reconstruct the dmatpawu
I (integers) is a matrix natpawu x ndim with entries are 0 or 1
D (deltas) is a matrix natpawu x ndim with entries are [0, 0.5)
P (matrices) is a set of matrices natpawu x ndim x ndim
Those three matrices allow to reconstruct the variable 'dmatpawu' used by ABINIT
:return:
"""
I = np.zeros((self.natpawu, self.ndim), dtype=int)
D = np.zeros((self.natpawu, self.ndim))
eigvec = np.zeros((self.natpawu, self.ndim, self.ndim))
# I and D for atoms 0 and 3
if self.oxidations[0] < 0:
nelect = self.ndim + self.oxidations[0]
else:
nelect = self.oxidations[0]
val = [
x for x in list(itertools.product(range(2), repeat=self.ndim))
if sum(x) == nelect
]
ii = val[np.random.randint(len(val))]
dd = 0.0 * np.random.random_sample((self.ndim, ))
I[0] = ii
D[0] = dd
I[3] = ii
D[3] = dd
# I and D for atoms 1 and 2
if self.oxidations[1] < 0:
nelect = self.ndim + self.oxidations[1]
else:
nelect = self.oxidations[1]
val = [
x for x in list(itertools.product(range(2), repeat=self.ndim))
if sum(x) == nelect
]
ii = val[np.random.randint(len(val))]
dd = 0.0 * np.random.random_sample((self.ndim, ))
I[1] = ii
D[1] = dd
I[2] = ii
D[2] = dd
p = gram_smith_qr(self.ndim)
eigvec[0] = p
eigvec[4] = np.dot(np.diag(self.connection), p)
p = gram_smith_qr(self.ndim)
eigvec[1] = p
eigvec[2] = np.dot(np.diag(self.connection), p)
data = {'eigvec': eigvec, 'I': I, 'D': D}
return self.new_entry(data), None
def add_random(self):
"""
Creates a new set of variables to reconstruct the dmatpawu
I (integers) is a matrix natpawu x ndim with entries are 0 or 1
D (deltas) is a matrix natpawu x ndim with entries are [0, 0.5)
P (matrices) is a set of matrices natpawu x ndim x ndim
Those three matrices allow to reconstruct the variable 'dmatpawu' used by ABINIT
:return:
"""
I = np.zeros((self.natpawu, self.ndim), dtype=int)
D = np.zeros((self.natpawu, self.ndim))
eigvec = np.zeros((self.natpawu, self.ndim, self.ndim))
# I and D for atoms 0 and 3
if self.oxidations[0] < 0:
nelect = self.ndim + self.oxidations[0]
else:
nelect = self.oxidations[0]
val = [x for x in list(itertools.product(range(2), repeat=self.ndim)) if sum(x) == nelect]
ii = val[np.random.randint(len(val))]
dd = 0.0 * np.random.random_sample((self.ndim,))
I[0] = ii
D[0] = dd
I[3] = ii
D[3] = dd
# I and D for atoms 1 and 2
if self.oxidations[1] < 0:
nelect = self.ndim + self.oxidations[1]
else:
nelect = self.oxidations[1]
val = [x for x in list(itertools.product(range(2), repeat=self.ndim)) if sum(x) == nelect]
ii = val[np.random.randint(len(val))]
dd = 0.0 * np.random.random_sample((self.ndim,))
I[1] = ii
D[1] = dd
I[2] = ii
D[2] = dd
p = gram_smith_qr(self.ndim)
eigvec[0] = p
eigvec[4] = np.dot(np.diag(self.connection), p)
p = gram_smith_qr(self.ndim)
eigvec[1] = p
eigvec[2] = np.dot(np.diag(self.connection), p)
data = {'eigvec': eigvec, 'I': I, 'D': D}
return self.new_entry(data), None
def add_random(self):
"""
Creates a new set of variables to reconstruct the dmatpawu
matrix_i (integers) is a matrix natpawu x ndim with entries are 0 or 1
matrix_d (deltas) is a matrix natpawu x ndim with entries are [0, 0.5)
P (matrices) is a set of matrices natpawu x ndim x ndim
Those three matrices allow to reconstruct the variable 'dmatpawu' used by ABINIT
:return:
"""
matrices_defined = []
matrix_i = self.num_indep_matrices*[None]
matrix_d = self.num_indep_matrices*[None]
euler = self.num_indep_matrices*[None]
for i in range(self.num_indep_matrices):
nelect = self.num_electrons_dftu[i]
val = [x for x in list(itertools.product(range(2), repeat=self.ndim)) if sum(x) == nelect]
ii = val[np.random.randint(len(val))]
dd = np.zeros(self.ndim)
matrix_i[i] = list(ii)
matrix_d[i] = list(dd)
matrices_defined.append(self.connections[i])
p = gram_smith_qr(self.ndim)
euler[i] = gea_all_angles(p)
data = {'E': euler, 'O': matrix_i, 'D': matrix_d}
return self.new_entry(data), None
def add_random(self):
"""
Creates a new set of variables to reconstruct the dmatpawu
matrix_i (integers) is a matrix natpawu x ndim with entries are 0 or 1
matrix_d (deltas) is a matrix natpawu x ndim with entries are [0, 0.5)
P (matrices) is a set of matrices natpawu x ndim x ndim
Those three matrices allow to reconstruct the variable 'dmatpawu' used by ABINIT
:return:
"""
matrices_defined = []
matrix_i = self.num_indep_matrices * [None]
matrix_d = self.num_indep_matrices * [None]
euler = self.num_indep_matrices * [None]
for i in range(self.num_indep_matrices):
nelect = self.num_electrons_dftu[i]
val = [
x for x in list(
itertools.product(list(range(2)), repeat=self.ndim))
if sum(x) == nelect
]
ii = val[np.random.randint(len(val))]
dd = np.zeros(self.ndim)
matrix_i[i] = list(ii)
matrix_d[i] = list(dd)
matrices_defined.append(self.connections[i])
p = gram_smith_qr(self.ndim)
euler[i] = gea_all_angles(p)
data = {
'euler_angles': euler,
'occupations': matrix_i,
'deltas': matrix_d,
'num_matrices': self.num_indep_matrices,
'ndim': self.ndim
}
return self.new_entry(data), None