Transpose exchanges roles of left and right indices

example/DMRG/dmrg_two_sites_U1.py

@@ -19,7 +19,7 @@ def matvec(self, v):
             lbl = v.labels()
             self.anet.PutUniTensor("psi",v)
             out = self.anet.Launch()
-            out.relabel_(lbl)
+            out.relabels_(lbl)
             return out
 
     def optimize_psi(psi, functArgs, maxit=2, krydim=4):
@@ -41,14 +41,15 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
         return psivec, energy[0].item()
 
 
-    ## Initialiaze MPO
+    ## Initialize MPO
     ##>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
     d = 2
     s = 0.5
     bd_inner = cytnx.Bond(cytnx.BD_KET,[[0],[-2],[2],[0]],[1,1,1,1])
     bd_phys = cytnx.Bond(cytnx.BD_KET,[[1],[-1]],[1,1])
 
     M = cytnx.UniTensor([bd_inner,bd_inner.redirect(),bd_phys, bd_phys.redirect()],rowrank=2)
+    M.set_name("MPO")
 
     # I
     M.set_elem([0,0,0,0],1);
@@ -69,7 +70,9 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
     VbdL = cytnx.Bond(cytnx.BD_KET,[[0]],[1])
     VbdR = cytnx.Bond(cytnx.BD_KET,[[q]],[1])
     L0 = cytnx.UniTensor([bd_inner.redirect(),VbdL.redirect(),VbdL],rowrank=1) #Left boundary
+    L0.set_name("L0")
     R0 = cytnx.UniTensor([bd_inner,VbdR,VbdR.redirect()],rowrank=1) #Right boundary
+    R0.set_name("R0")
     L0.set_elem([0,0,0],1)
     R0.set_elem([3,0,0],1)
 
@@ -83,6 +86,7 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
 
     A[0] = cytnx.UniTensor([VbdL,bd_phys.redirect(),cytnx.Bond(cytnx.BD_BRA,[[qcntr]],[1])],rowrank=2)
     A[0].get_block_()[0] = 1
+    A[0].set_name("A0")
 
     lbls = []
     lbls.append(["0","1","2"]) # store the labels for later convinience.
@@ -96,9 +100,10 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
         B3 = cytnx.Bond(cytnx.BD_BRA,[[qcntr]],[1])
 
         A[k] = cytnx.UniTensor([B1,B2,B3],rowrank=2)
+        A[k].set_name(f"A{k}")
 
         lbl = [str(2*k),str(2*k+1),str(2*k+2)]
-        A[k].relabel_(lbl)
+        A[k].set_labels(lbl)
 
         A[k].get_block_()[0] = 1
         lbls.append(lbl) # store the labels for later convinience.
@@ -114,8 +119,11 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
                     "A_Conj: -3,-5,2",\
                     "TOUT: 0;1,2"])
     for p in range(Nsites - 1):
-        anet.PutUniTensors(["L","A","A_Conj","M"],[LR[p],A[p],A[p].Dagger(),M])
+        # Dagger() swaps left/right index order; permute_ restores original label order
+        anet.PutUniTensors(["L","A","A_Conj","M"], \
+                           [LR[p],A[p],A[p].Dagger().permute_(A[p].labels()),M])
         LR[p+1] = anet.Launch()
+        LR[p+1].set_name(f"LR{p+1}")
 
     Ekeep = []
     for k in range(1, numsweeps+1):
@@ -131,12 +139,15 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
 
             psi.set_rowrank_(2) # maintain rowrank to perform the svd
             s,A[p],A[p+1] = cytnx.linalg.Svd_truncate(psi,new_dim)
-            A[p+1].relabel_(lbls[p+1]); # set the label back to be consistent
+            A[p+1].relabels_(lbls[p+1]); # set the label back to be consistent
 
             s = s/s.Norm().item() # normalize s
 
             A[p] = cytnx.Contract(A[p],s) # absorb s into next neighbor
-            A[p].relabel_(lbls[p]); # set the label back to be consistent
+            A[p].relabels_(lbls[p]); # set the label back to be consistent
+
+            A[p].set_name(f"A{p}")
+            A[p+1].set_name(f"A{p+1}")
 
             # update LR from right to left:
             anet = cytnx.Network()
@@ -145,14 +156,16 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
                         "M: 0,-2,-4,-5",\
                         "B_Conj: 2,-5,-3",\
                         "TOUT: 0;1,2"])
-            anet.PutUniTensors(["R","B","M","B_Conj"],[LR[p+2],A[p+1],M,A[p+1].Dagger()])
+            anet.PutUniTensors(["R","B","M","B_Conj"], \
+                               [LR[p+2],A[p+1],M,A[p+1].Dagger().permute_(A[p+1].labels())])  # Dagger() swaps index order; permute_ restores it
             LR[p+1] = anet.Launch()
+            LR[p+1].set_name(f"LR{p+1}")
 
             print('Sweep[r->l]: %d/%d, Loc: %d,Energy: %f' % (k, numsweeps, p, Ekeep[-1]))
 
         A[0].set_rowrank_(1)
         _,A[0] = cytnx.linalg.Gesvd(A[0],is_U=False, is_vT=True)
-        A[0].relabel_(lbls[0]); #set the label back to be consistent
+        A[0].relabels_(lbls[0]); #set the label back to be consistent
 
         for p in range(Nsites-1):
             dim_l = A[p].shape()[0]
@@ -165,12 +178,15 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
 
             psi.set_rowrank_(2) # maintain rowrank to perform the svd
             s,A[p],A[p+1] = cytnx.linalg.Svd_truncate(psi,new_dim)
-            A[p].relabel_(lbls[p]); #set the label back to be consistent
+            A[p].relabels_(lbls[p]); #set the label back to be consistent
 
             s = s/s.Norm().item() # normalize s
 
             A[p+1] = cytnx.Contract(s,A[p+1]) ## absorb s into next neighbor.
-            A[p+1].relabel_(lbls[p+1]); #set the label back to be consistent
+            A[p+1].relabels_(lbls[p+1]); #set the label back to be consistent
+
+            A[p].set_name(f"A{p}")
+            A[p+1].set_name(f"A{p+1}")
 
             # update LR from left to right:
             anet = cytnx.Network()
@@ -179,14 +195,17 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
                         "M: -2,0,-4,-5",\
                         "A_Conj: -3,-5,2",\
                         "TOUT: 0;1,2"])
-            anet.PutUniTensors(["L","A","A_Conj","M"],[LR[p],A[p],A[p].Dagger(),M])
+            anet.PutUniTensors(["L","A","A_Conj","M"], \
+                               [LR[p],A[p],A[p].Dagger().permute_(A[p].labels()),M])  # Dagger() swaps index order; permute_ restores it
             LR[p+1] = anet.Launch()
+            LR[p+1].set_name(f"LR{p+1}")
 
             print('Sweep[l->r]: %d/%d, Loc: %d,Energy: %f' % (k, numsweeps, p, Ekeep[-1]))
 
         A[-1].set_rowrank_(2)
         _,A[-1] = cytnx.linalg.Gesvd(A[-1],is_U=True,is_vT=False) ## last one.
-        A[-1].relabel_(lbls[-1]); #set the label back to be consistent
+        A[-1].relabels_(lbls[-1]); #set the label back to be consistent
+        A[-1].set_name(f"A{Nsites-1}")
 
     return Ekeep
 

example/DMRG/dmrg_two_sites_dense.py

@@ -18,7 +18,7 @@ def matvec(self, v):
             lbl = v.labels()
             self.anet.PutUniTensor("psi",v)
             out = self.anet.Launch()
-            out.relabel_(lbl)
+            out.relabels_(lbl)
             return out
 
     def optimize_psi(psi, functArgs, maxit=2, krydim=4):
@@ -53,25 +53,32 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
     M[0,1] = M[2,3] = 2**0.5*sp.real()
     M[0,2] = M[1,3] = 2**0.5*sm.real()
     M = cytnx.UniTensor(M,0)
+    M.set_name("MPO")
 
     L0 = cytnx.UniTensor(cytnx.zeros([4,1,1]), rowrank = 0) #Left boundary
     R0 = cytnx.UniTensor(cytnx.zeros([4,1,1]), rowrank = 0) #Right boundary
-    L0[0,0,0] = 1.; R0[3,0,0] = 1.
+    L0.set_name("L0")
+    R0.set_name("R0")
+    L0[0,0,0] = 1.
+    R0[3,0,0] = 1.
 
-    lbls = [] # List for storing the MPS labels
     A = [None for i in range(Nsites)]
     A[0] = cytnx.UniTensor(cytnx.random.normal([1, d, min(chi, d)], 0., 1.), rowrank = 2)
-    A[0].relabel_(["0","1","2"])
-    lbls.append(["0","1","2"]) # store the labels for later convinience.
+    A[0].relabels_(["0","1","2"])
+    A[0].set_name("A0")
+
+    lbls = [] # List for storing the MPS labels
+    lbls.append(["0","1","2"]) # store the labels for later convenience.
 
     for k in range(1,Nsites):
         dim1 = A[k-1].shape()[2]; dim2 = d
         dim3 = min(min(chi, A[k-1].shape()[2] * d), d ** (Nsites - k - 1))
         A[k] = cytnx.UniTensor(cytnx.random.normal([dim1, dim2, dim3],0.,1.), rowrank = 2)
+        A[k].set_name(f"A{k}")
 
         lbl = [str(2*k),str(2*k+1),str(2*k+2)]
-        A[k].relabel_(lbl)
-        lbls.append(lbl) # store the labels for later convinience.
+        A[k].relabels_(lbl)
+        lbls.append(lbl) # store the labels for later convenience.
 
     LR = [None for i in range(Nsites+1)]
     LR[0]  = L0
@@ -84,23 +91,30 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
         s, A[p] ,vt = cytnx.linalg.Gesvd(A[p])
         A[p+1] = cytnx.Contract(cytnx.Contract(s,vt),A[p+1])
 
-        ## Calculate enviroments:
+        A[p].set_name(f"A{p}")
+        A[p+1].set_name(f"A{p+1}")
+
+        ## Calculate environments:
         anet = cytnx.Network()
         anet.FromString(["L: -2,-1,-3",\
                         "A: -1,-4,1",\
                         "M: -2,0,-4,-5",\
                         "A_Conj: -3,-5,2",\
                         "TOUT: 0,1,2"])
         # or you can do: anet = cytnx.Network("L_AMAH.net")
-        anet.PutUniTensors(["L","A","A_Conj","M"],[LR[p],A[p],A[p].Conj(),M])
+        # Dagger() swaps left/right index order; permute_ restores original label order
+        anet.PutUniTensors(["L","A","A_Conj","M"], \
+                           [LR[p],A[p],A[p].Dagger().permute_(A[p].labels()),M])
         LR[p+1] = anet.Launch()
+        LR[p+1].set_name(f"LR{p+1}")
 
         # Recover the original MPS labels
-        A[p].relabel_(lbls[p])
-        A[p+1].relabel_(lbls[p+1])
+        A[p].relabels_(lbls[p])
+        A[p+1].relabels_(lbls[p+1])
 
     _,A[-1] = cytnx.linalg.Gesvd(A[-1],is_U=True,is_vT=False) ## last one.
-    A[-1].relabel_(lbls[-1]) # Recover the original MPS labels
+    A[-1].relabels_(lbls[-1]) # Recover the original MPS labels
+    A[-1].set_name(f"A{Nsites-1}")
 
     Ekeep = []
     for k in range(1, numsweeps+1):
@@ -116,12 +130,15 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
 
             psi.set_rowrank_(2) # maintain rowrank to perform the svd
             s,A[p],A[p+1] = cytnx.linalg.Svd_truncate(psi,new_dim)
-            A[p+1].relabel_(lbls[p+1]); # set the label back to be consistent
+            A[p+1].relabels_(lbls[p+1]); # set the label back to be consistent
 
             s = s/s.Norm().item() # normalize s
 
             A[p] = cytnx.Contract(A[p],s) # absorb s into next neighbor
-            A[p].relabel_(lbls[p]); # set the label back to be consistent
+            A[p].relabels_(lbls[p]); # set the label back to be consistent
+
+            A[p].set_name(f"A{p}")
+            A[p+1].set_name(f"A{p+1}")
 
             # update LR from right to left:
             anet = cytnx.Network()
@@ -131,14 +148,17 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
                             "B_Conj: 2,-5,-3",\
                             "TOUT: 0;1,2"])
             # or you can do: anet = cytnx.Network("R_AMAH.net")
-            anet.PutUniTensors(["R","B","M","B_Conj"],[LR[p+2],A[p+1],M,A[p+1].Conj()])
+            anet.PutUniTensors(["R","B","M","B_Conj"], \
+                               [LR[p+2],A[p+1],M,A[p+1].Dagger().permute_(A[p+1].labels())])  # Dagger() swaps index order; permute_ restores it
             LR[p+1] = anet.Launch()
+            LR[p+1].set_name(f"LR{p+1}")
 
             print('Sweep[r->l]: %d/%d, Loc: %d,Energy: %f' % (k, numsweeps, p, Ekeep[-1]))
 
         A[0].set_rowrank_(1)
         _,A[0] = cytnx.linalg.Gesvd(A[0],is_U=False, is_vT=True)
-        A[0].relabel_(lbls[0]); #set the label back to be consistent
+        A[0].relabels_(lbls[0]); #set the label back to be consistent
+        A[0].set_name("A0")
 
         for p in range(Nsites-1):
             dim_l = A[p].shape()[0]
@@ -151,12 +171,15 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
 
             psi.set_rowrank_(2) # maintain rowrank to perform the svd
             s,A[p],A[p+1] = cytnx.linalg.Svd_truncate(psi,new_dim)
-            A[p].relabel_(lbls[p]); #set the label back to be consistent
+            A[p].relabels_(lbls[p]); #set the label back to be consistent
 
             s = s/s.Norm().item() # normalize s
 
             A[p+1] = cytnx.Contract(s,A[p+1]) ## absorb s into next neighbor.
-            A[p+1].relabel_(lbls[p+1]); #set the label back to be consistent
+            A[p+1].relabels_(lbls[p+1]); #set the label back to be consistent
+
+            A[p].set_name(f"A{p}")
+            A[p+1].set_name(f"A{p+1}")
 
             # update LR from left to right:
             anet = cytnx.Network()
@@ -167,14 +190,17 @@ def optimize_psi(psi, functArgs, maxit=2, krydim=4):
                             "TOUT: 0,1,2"])
             # or you can do: anet = cytnx.Network("L_AMAH.net")
 
-            anet.PutUniTensors(["L","A","A_Conj","M"],[LR[p],A[p],A[p].Conj(),M])
+            anet.PutUniTensors(["L","A","A_Conj","M"], \
+                               [LR[p],A[p],A[p].Dagger().permute_(A[p].labels()),M])  # Dagger() swaps index order; permute_ restores it
             LR[p+1] = anet.Launch()
+            LR[p+1].set_name(f"LR{p+1}")
 
             print('Sweep[l->r]: %d/%d, Loc: %d,Energy: %f' % (k, numsweeps, p, Ekeep[-1]))
 
         A[-1].set_rowrank_(2)
         _,A[-1] = cytnx.linalg.Gesvd(A[-1],is_U=True,is_vT=False) ## last one.
-        A[-1].relabel_(lbls[-1]); #set the label back to be consistent
+        A[-1].relabels_(lbls[-1]); #set the label back to be consistent
+        A[-1].set_name(f"A{Nsites-1}")
     return Ekeep
 
 if __name__ == '__main__':

example/TDVP/tdvp1_dense.py

@@ -80,7 +80,9 @@ def get_energy(A, M):
                         "TOUT: 0,1,2"])
         # or you can do: anet = cytnx.Network("L_AMAH.net")
         for p in range(0, N):
-            anet.PutUniTensors(["L","A","A_Conj","M"],[L,A[p],A[p].Conj(),M])
+            # Dagger() swaps left/right index order; permute_ restores original label order
+            anet.PutUniTensors(["L","A","A_Conj","M"], \
+                               [L,A[p],A[p].Dagger().permute_(A[p].labels()),M])
             L = anet.Launch()
         E = cytnx.Contract(L, R0).item()
         print('energy:', E)
@@ -138,7 +140,8 @@ def get_energy(A, M):
                         "A_Conj: -3,-5,2",\
                         "TOUT: 0,1,2"])
         # or you can do: anet = cytnx.Network("L_AMAH.net")
-        anet.PutUniTensors(["L","A","A_Conj","M"],[LR[p],A[p],A[p].Conj(),M])
+        anet.PutUniTensors(["L","A","A_Conj","M"], \
+                           [LR[p],A[p],A[p].Dagger().permute_(A[p].labels()),M])  # Dagger() swaps index order; permute_ restores it
         LR[p+1] = anet.Launch()
 
         # Recover the original MPS labels
@@ -175,7 +178,8 @@ def get_energy(A, M):
                             "B_Conj: 2,-5,-3",\
                             "TOUT: ;0,1,2"])
             # or you can do: anet = cytnx.Network("R_AMAH.net")
-            anet.PutUniTensors(["R","B","M","B_Conj"],[LR[p+1],A[p],M,A[p].Conj()])
+            anet.PutUniTensors(["R","B","M","B_Conj"], \
+                               [LR[p+1],A[p],M,A[p].Dagger().permute_(A[p].labels())])  # Dagger() swaps index order; permute_ restores it
             old_LR = LR[p].clone()
             if p != 0:
                 LR[p] = anet.Launch()
@@ -215,7 +219,8 @@ def get_energy(A, M):
                             "A_Conj: -3,-5,2",\
                             "TOUT: 0,1,2"])
 
-            anet.PutUniTensors(["L","A","A_Conj","M"],[LR[p],A[p],A[p].Conj(),M])
+            anet.PutUniTensors(["L","A","A_Conj","M"], \
+                               [LR[p],A[p],A[p].Dagger().permute_(A[p].labels()),M])  # Dagger() swaps index order; permute_ restores it
             old_LR = LR[p+1].clone()
 
 
@@ -246,15 +251,17 @@ def Local_meas(A, B, Op, site):
                     "TOUT: 2;4"])
     for i in range(0, N):
         if i != site:
-            anet.PutUniTensors(["l","A","B"],[l,A[i],B[i].Conj()])
+            anet.PutUniTensors(["l","A","B"], \
+                               [l,A[i],B[i].Dagger().permute_(B[i].labels())])  # Dagger() swaps index order; permute_ restores it
             l = anet.Launch()
         else:
             tmp = A[i].relabel(1, "_aux_up")
             Op = Op.relabel(["_aux_up", "_aux_low"])
             tmp = cytnx.Contract(tmp, Op)
             tmp.relabel_("_aux_low", A[i].labels()[1])
             tmp.permute_(A[i].labels())
-            anet.PutUniTensors(["l","A","B"],[l,tmp,B[i].Conj()])
+            anet.PutUniTensors(["l","A","B"], \
+                               [l,tmp,B[i].Dagger().permute_(B[i].labels())])  # Dagger() swaps index order; permute_ restores it
             l = anet.Launch()
 
     return l.reshape(1).item()

include/Bond.hpp

@@ -799,7 +799,7 @@ namespace cytnx {
 
     /**
     @brief Group the duplicated quantum number and return the new instance
-            of the Bond ojbect.
+            of the Bond object.
         @details This function will group the duplicated quantum number and return
             the new instance of the Bond object. It will also the \p mapper, where
                 \p mapper is about the new index from old index via\n