Change variable truncation to strategy

seemps/truncate/simplify.py

@@ -23,7 +23,7 @@
 
 def simplify(
     state: Union[MPS, MPSSum], 
-    truncation: Strategy = SIMPLIFICATION_STRATEGY, 
+    strategy: Strategy = SIMPLIFICATION_STRATEGY, 
     direction: int = +1
 
 ) -> MPS:
@@ -34,7 +34,7 @@ def simplify(
     ----------
     state : MPS | MPSSum
         State to approximate.
-    truncation : Strategy
+    strategy : Strategy
         Truncation strategy. Defaults to `SIMPLIFICATION_STRATEGY`.
     direction : { +1, -1 }
        Initial direction for the sweeping algorithm.
@@ -48,20 +48,20 @@ def simplify(
         return combine(
             state.weights,
             state.states,
-            truncation=truncation,
+            strategy=strategy,
             direction=direction,
         )
 
     size = state.size
     start = 0 if direction > 0 else size - 1
-    normalize= truncation.get_normalize_flag()
-    maxsweeps = truncation.get_max_sweeps()
-    simplification_tolerance = truncation.get_simplification_tolerance()
-    max_bond_dimension = truncation.get_max_bond_dimension()
-    mps = CanonicalMPS(state, center=start, strategy=truncation)
+    normalize= strategy.get_normalize_flag()
+    maxsweeps = strategy.get_max_sweeps()
+    simplification_tolerance = strategy.get_simplification_tolerance()
+    max_bond_dimension = strategy.get_max_bond_dimension()
+    mps = CanonicalMPS(state, center=start, strategy=strategy)
     if normalize:
         mps.normalize_inplace()
-    if not truncation.get_simplification_method():
+    if not strategy.get_simplification_method():
         return mps
     if max_bond_dimension == 0 and simplification_tolerance <= 0:
         return mps
@@ -76,12 +76,12 @@ def simplify(
     for sweep in range(maxsweeps):
         if direction > 0:
             for n in range(0, size - 1):
-                mps.update_2site_right(form.tensor2site(direction), n, truncation)
+                mps.update_2site_right(form.tensor2site(direction), n, strategy)
                 form.update(direction)
             last = size - 1
         else:
             for n in reversed(range(0, size - 1)):
-                mps.update_2site_left(form.tensor2site(direction), n, truncation)
+                mps.update_2site_left(form.tensor2site(direction), n, strategy)
                 form.update(direction)
             last = 0
         #
@@ -157,7 +157,7 @@ def combine(
     weights: list[Weight],
     states: list[MPS],
     guess: Optional[MPS] = None, 
-    truncation: Strategy = SIMPLIFICATION_STRATEGY, 
+    strategy: Strategy = SIMPLIFICATION_STRATEGY, 
     direction: int = +1
 ) -> MPS:
     """Approximate a linear combination of MPS :math:`\\sum_i w_i \\psi_i` by
@@ -171,7 +171,7 @@ def combine(
         List of states :math:`\\psi_i`.
     guess : MPS, optional
         Initial guess for the iterative algorithm.
-    truncation : Strategy
+    strategy : Strategy
         Truncation strategy. Defaults to `SIMPLIFICATION_STRATEGY`.
     direction : {+1, -1}
         Initial direction for the sweeping algorithm.
@@ -187,11 +187,11 @@ def combine(
         np.sqrt(np.abs(weights)) * np.sqrt(state.error())
         for weights, state in zip(weights, states)
     )
-    normalize= truncation.get_normalize_flag()
-    maxsweeps = truncation.get_max_sweeps()
-    simplification_tolerance = truncation.get_simplification_tolerance()
+    normalize= strategy.get_normalize_flag()
+    maxsweeps = strategy.get_max_sweeps()
+    simplification_tolerance = strategy.get_simplification_tolerance()
     start = 0 if direction > 0 else guess.size - 1
-    φ = CanonicalMPS(guess, center=start, strategy=truncation, normalize=normalize)
+    φ = CanonicalMPS(guess, center=start, strategy=strategy, normalize=normalize)
     err = norm_ψsqr = multi_norm_squared(weights, states)
     if norm_ψsqr < simplification_tolerance:
         return MPS([np.zeros((1, P.shape[1], 1)) for P in φ])
@@ -209,7 +209,7 @@ def combine(
                     weights * f.tensor2site(direction)
                     for weights, f in zip(weights, forms)
                 )  # type: ignore
-                φ.update_2site_right(tensor, n, truncation)
+                φ.update_2site_right(tensor, n, strategy)
                 for f in forms:
                     f.update(direction)
         else:
@@ -218,7 +218,7 @@ def combine(
                     weights * f.tensor2site(direction)
                     for weights, f in zip(weights, forms)
                 )  # type: ignore
-                φ.update_2site_left(tensor, n, truncation)
+                φ.update_2site_left(tensor, n, strategy)
                 for f in forms:
                     f.update(direction)
             last = 0