def generate_parameters_dmrg(lattice='chain'):
# =======================================================
# No further changes are needed for these codes
model = ['chain', 'square', 'arbitrary', 'jigsaw', 'full', 'longRange']
if lattice is 'chain':
para = parameter_dmrg_chain()
elif lattice is 'square':
para = parameter_dmrg_square()
elif lattice is 'arbitrary':
para = parameter_dmrg_arbitrary()
elif lattice is 'jigsaw':
para = parameter_dmrg_jigsaw()
elif lattice is 'full':
para = parameter_dmrg_full()
elif lattice is 'longRange':
para = parameter_dmrg_long_range()
else:
para = dict()
print_error('Wrong input of lattice!')
print_options(model,
welcome='Set lattice as one of the following:\t',
quote='\'')
para1 = common_parameters_dmrg()
para = dict(para, **para1) # combine with the common parameters
para = make_consistent_parameter_dmrg(para)
return para
def check_consistency(self):
if self.n_tensor != len(self.indexes):
print_error('ErrorNCON: the number of tensors and number of index tuples are not consistent', False)
if self.bond_open[0] != -1:
print_error('NumberingError: the starting number of open bonds should be -1', False)
if self.bond_open.__len__() != (-self.bond_open[-1]):
print_error('NumberingError: all integers in [-1, -(number of open bonds)] should appear in the '
'numbering. Please check.')
if self.bond_ark[0] != 1:
print_error('NumberingError: the starting number of open bonds should be 1', False)
if self.bond_ark.__len__() != self.bond_ark[-1]:
print_error('NumberingError: all integers in [-1, -(number of ark bonds)] should appear in the '
'numbering. Please check.')
def check_continuity_pos_h2(pos_h2):
p0 = np.min(pos_h2)
if p0 != 0:
exit('The numbering of sites should start with 0, not %d. Please revise the numbering.' % p0)
p1 = np.max(pos_h2)
missing_number = list()
for n in range(p0+1, p1):
if n not in pos_h2:
missing_number.append(n)
if missing_number.__len__() > 0:
print_error('The pos_h2 is expected to contain all numbers from 0 to %d. The following numbers are missing:' % p1)
print(str(missing_number))
exit('Please check and revise you numbering')
def absorb_matrices2tensor(tensor, mats, bonds=np.zeros(0), mat_bond=-1):
"""
Absorb matrices to tensors on certain bonds
:param tensor: a tensor
:param mats: matrices
:param bonds: which bonds of tensor to absorb matrices, default by from 0 to n
:param mat_bond: which bond of matrices to contract to tensor, default as 0 bond
:return: tensor absorbed matrices
Example:
>>>T = np.array([[[1, 1], [1, 1]],[[1, 1], [1, 1]]])
>>>M = [np.array([[1, 2], [2, 3]]), np.array([[2, 3], [3, 4]])]
>>>print(absorb_matrices2tensor(T, M))
[[[15 15]
[21 21]]
[[25 25]
[35 35]]]
"""
# default: contract the 1st bond of mat with tensor
nm = len(mats) # number of matrices to be contracted
if is_debug:
if nm != tensor.ndim:
print_error(
'InputError: the number of matrices should be equal to the number of indexes of tensor'
)
if type(bonds) is list or tuple:
bonds = np.array(bonds)
if bonds.size == 0: # set default of bonds: contract all matrices in order, starting from the 0th bond
bonds = np.arange(0, nm)
if mat_bond < 0: # set default of mat_bond: contract the 1st bond of each matrix
mat_bond = np.zeros((nm, 1))
for i in range(
0,
nm): # permute if the second bond of a matrix is to be contracted
if mat_bond[i, 0] == 1:
mats[i] = mats[i].T
# check if full_fast function can be used
if np.array_equiv(np.sort(bonds), np.arange(0, tensor.ndim)):
order = np.argsort(bonds)
mats = sort_list(mats, order)
# this full_fast function can be used when each bond has a matrix which are arranged in the correct order
tensor = absorb_matrices2tensor_full_fast(tensor, mats)
else:
# can be optimized
for i in range(0, nm):
tensor = absorb_matrix2tensor(tensor, mats[i], bonds[i])
return tensor
def generate_parameters_dmrg():
lattice = 'arbitrary'
# =======================================================
# No further changes are needed for these codes
model = ['chain', 'square', 'arbitrary']
if lattice is 'chain':
para = parameter_dmrg_chain()
elif lattice is 'square':
para = parameter_dmrg_square()
elif lattice is 'arbitrary':
para = parameter_dmrg_arbitrary()
else:
para = None
print_error('Wrong input of lattice!')
print_options(model, welcome='Set lattice as one of the following:\t', quote='\'')
para['nh'] = para['index2'].shape[0] # number of two-body interactions
return para