Improve interpolation from PaulaGarciaMolina/main

src/seemps/analysis/interpolation.py

@@ -1,10 +1,14 @@
 from __future__ import annotations
+
 import copy
-import numpy as np
 from math import sqrt
-from ..qft import qft_mpo
-from ..state import MPS, MPSSum, Strategy, DEFAULT_STRATEGY
+from typing import List
+
+import numpy as np
+
 from ..operators import MPO
+from ..qft import qft_mpo
+from ..state import DEFAULT_STRATEGY, MPS, CanonicalMPS, MPSSum, Strategy
 from ..truncate import simplify
 from .finite_differences import mpo_combined
 from .space import Space, mpo_flip
@@ -24,7 +28,14 @@ def twoscomplement(L, **kwdargs):
     return MPO([A0] + [A] * (L - 2) + [Aend], **kwdargs)
 
 
-def fourier_interpolation_1D(ψ0mps, space, M0, Mf, dim, strategy=DEFAULT_STRATEGY):
+def fourier_interpolation_1D(
+    ψ0mps: MPS,
+    space: Space,
+    M0: int,
+    Mf: int,
+    dim: int,
+    strategy: Strategy = DEFAULT_STRATEGY,
+):
     """Obtain the Fourier interpolated MPS over the chosen dimension
     with a new number of sites Mf.
 
@@ -73,12 +84,19 @@ def fourier_interpolation_1D(ψ0mps, space, M0, Mf, dim, strategy=DEFAULT_STRATE
     )
     U2c = new_space.extend(mpo_flip(twoscomplement(Mf, strategy=strategy)), dim)
     ψfmps = iQFT_op @ (U2c @ Fψfmps)
-    ψfmps = ψfmps * (1 / sqrt(ψfmps.norm_squared()))
-
+    ψfmps = (Mf / M0) * ψfmps
+    if strategy.get_normalize_flag():
+        ψfmps = ψfmps.normalize_inplace()
     return ψfmps, new_space
 
 
-def fourier_interpolation(ψmps, space, old_sites, new_sites, **kwargs):
+def fourier_interpolation(
+    ψmps: MPS,
+    space: Space,
+    old_sites: List,
+    new_sites: List,
+    strategy: Strategy = DEFAULT_STRATEGY,
+):
     """Fourier interpolation on an MPS.
 
     Parameters
@@ -91,8 +109,8 @@ def fourier_interpolation(ψmps, space, old_sites, new_sites, **kwargs):
         List of integers with the original number of sites for each dimension.
     new_sites : list[int]
         List of integers with the new number of sites for each dimension.
-    **kwargs :
-        Arguments accepted by :class:`MPO`
+    strategy : Strategy, optional
+            Truncation strategy, defaults to DEFAULT_STRATEGY.
 
     Returns
     -------
@@ -101,9 +119,11 @@ def fourier_interpolation(ψmps, space, old_sites, new_sites, **kwargs):
 
     """
     space = copy.copy(space)
+    if not isinstance(ψmps, CanonicalMPS):
+        ψmps = CanonicalMPS(ψmps, strategy=strategy)
     for i, sites in enumerate(new_sites):
         ψmps, space = fourier_interpolation_1D(
-            ψmps, space, old_sites[i], sites, dim=i, **kwargs
+            ψmps, space, old_sites[i], sites, dim=i, strategy=strategy
         )
     return ψmps
 
@@ -232,7 +252,9 @@ def finite_differences_interpolation_1D(
         return simplify(odd + even, strategy=strategy), new_space
 
 
-def finite_differences_interpolation(ψmps, space, **kwargs):
+def finite_differences_interpolation(
+    ψmps: MPS, space: Space, strategy: Strategy = DEFAULT_STRATEGY
+):
     """Finite differences interpolation of an MPS representing
     a multidimensional function.
 
@@ -242,8 +264,8 @@ def finite_differences_interpolation(ψmps, space, **kwargs):
         MPS representing a multidimensional function.
     space : Space
         Space on which the function is defined.
-    **kwargs :
-        Other arguments accepted by :class:`MPO`
+    strategy : Strategy, optional
+            Truncation strategy, defaults to DEFAULT_STRATEGY.
 
     Returns
     -------
@@ -252,5 +274,7 @@ def finite_differences_interpolation(ψmps, space, **kwargs):
     """
     space = copy.deepcopy(space)
     for i, q in enumerate(space.qubits_per_dimension):
-        ψmps, space = finite_differences_interpolation_1D(ψmps, space, dim=i, **kwargs)
+        ψmps, space = finite_differences_interpolation_1D(
+            ψmps, space, dim=i, strategy=strategy
+        )
     return ψmps

src/seemps/truncate/simplify.py

@@ -1,7 +1,10 @@
 from __future__ import annotations
-from typing import Optional, Union
+
 from math import sqrt
+from typing import Optional, Union
+
 import numpy as np
+
 from .. import tools
 from ..state import (
     DEFAULT_TOLERANCE,