change default ttno construction algo to QR

renormalizer/mps/mpo.py

@@ -275,7 +275,7 @@ def __init__(self, model: Model = None, terms: Union[Op, List[Op]] = None, offse
 
         self.dtype = factor.dtype
 
-        mpo_symbol, self.qn, self.qntot, self.qnidx, self.symbolic_out_ops_list, self.primary_ops \
+        self.symbolic_mpo, self.qn, self.qntot, self.qnidx, self.symbolic_out_ops_list, self.primary_ops \
             = construct_symbolic_mpo(table, factor, algo=algo)
         # from renormalizer.mps.symbolic_mpo import _format_symbolic_mpo
         # print(_format_symbolic_mpo(mpo_symbol))
@@ -285,7 +285,7 @@ def __init__(self, model: Model = None, terms: Union[Op, List[Op]] = None, offse
         # evaluate the symbolic mpo
         assert model.basis is not None
 
-        for impo, mo in enumerate(mpo_symbol):
+        for impo, mo in enumerate(self.symbolic_mpo):
             mo_mat = symbolic_mo_to_numeric_mo(model.basis[impo], mo, self.dtype)
             self.append(mo_mat)
 

renormalizer/mps/symbolic_mpo.py

@@ -308,7 +308,7 @@ def _decompose_qr(term_row, term_col, non_red, in_ops_list, factor, primary_ops,
 
     """
     assert non_red.shape == (len(term_row), len(term_col))
-    assert k == 1
+
     non_red.data = factor[non_red.data - 1]
     gamma = non_red.todense()
 

renormalizer/tn/symbolic_mpo.py → renormalizer/tn/symbolic_ttno.py

@@ -52,8 +52,7 @@ def symbolic_mo_to_numeric_mo_general(basis_sets: List[BasisSet], mo, dtype):
     return np.moveaxis(mo_tensor, mo.ndim - 1, -1)
 
 
-def construct_symbolic_mpo(tn: BasisTree, terms: List[Op], const: float = 0):
-    algo = "Hopcroft-Karp"
+def construct_symbolic_ttno(tn: BasisTree, terms: List[Op], const: float = 0, algo: str = "qr"):
     nodes = tn.postorder_list()
     basis = list(chain(*[n.basis_sets for n in nodes]))
     model = Model(basis, [])

renormalizer/tn/tree.py

@@ -16,7 +16,7 @@
 from renormalizer.utils import calc_vn_entropy, calc_vn_entropy_dm
 from renormalizer.tn.node import TreeNodeTensor, TreeNodeBasis, copy_connection, TreeNodeEnviron
 from renormalizer.tn.treebase import Tree, BasisTree
-from renormalizer.tn.symbolic_mpo import construct_symbolic_mpo, symbolic_mo_to_numeric_mo_general
+from renormalizer.tn.symbolic_ttno import construct_symbolic_ttno, symbolic_mo_to_numeric_mo_general
 
 
 logger = logging.getLogger(__name__)
@@ -138,19 +138,19 @@ def dummy(cls, basis: BasisTree):
             basis.dummy_ttno = cls(new_basis, [new_basis.identity_op])
         return basis.dummy_ttno
 
-    def __init__(self, basis: BasisTree, terms: Union[List[Op], Op], root: TreeNodeTensor = None):
+    def __init__(self, basis: BasisTree, terms: Union[List[Op], Op], root: TreeNodeTensor = None, algo: str = "qr"):
         self.basis: BasisTree = basis
         if isinstance(terms, Op):
             terms = [terms]
         self.terms: List[Op] = terms
 
         if not root:
-            symbolic_mpo, mpoqn = construct_symbolic_mpo(basis, terms)
+            self.symbolic_ttno, mpoqn = construct_symbolic_ttno(basis, terms, algo=algo)
             # from renormalizer.mps.symbolic_mpo import _format_symbolic_mpo
             # print(_format_symbolic_mpo(symbolic_mpo))
             node_list_basis = self.basis.postorder_list()
             node_list_op = []
-            for impo, (mo, qn) in enumerate(zip(symbolic_mpo, mpoqn)):
+            for impo, (mo, qn) in enumerate(zip(self.symbolic_ttno, mpoqn)):
                 node_basis: TreeNodeBasis = node_list_basis[impo]
                 mo_mat = symbolic_mo_to_numeric_mo_general(node_basis.basis_sets, mo, backend.real_dtype)
                 node_list_op.append(TreeNodeTensor(mo_mat, qn))