fixed optimize_nsc calls in geometry finalization

Added rest of the typing.

Signed-off-by: Nick Papior <nickpapior@gmail.com>

src/sisl/geom/_common.py

@@ -9,11 +9,12 @@
 def geometry_define_nsc(geometry, periodic=(True, True, True)):
     """Define the number of supercells for a geometry based on the periodicity """
     if np.all(geometry.maxR(True) > 0.):
-        geometry.optimize_nsc()
+        # strip away optimizing nsc for the non-periodic directions
+        axes = [i for i, p in enumerate(periodic) if p]
+
+        geometry.optimize_nsc(axes)
         for d, per in zip("abc", periodic):
-            if per:
-                geometry.lattice.set_boundary_condition(**{d: "Periodic"})
-            else:
+            if not per:
                 geometry.set_nsc(**{d: 1})
     else:
         nsc = [3 if p else 1 for p in periodic]

src/sisl/geom/flat.py

@@ -79,8 +79,12 @@ def graphene(bond: float=1.42,
         atoms = Atom(Z=6, R=bond * 1.01)
     return honeycomb(bond, atoms, orthogonal)
 
+
 @set_module("sisl.geom")
-def honeycomb_flake(shells: int, bond: float, atoms, vacuum: float = 20.) -> Geometry:
+def honeycomb_flake(shells: int,
+                    bond: float,
+                    atoms,
+                    vacuum: float = 20.) -> Geometry:
     """Hexagonal flake of a honeycomb lattice, with zig-zag edges.
 
     Parameters
@@ -165,8 +169,12 @@ def _minimal_op(shells):
 
     return geom
 
+
 @set_module("sisl.geom")
-def graphene_flake(shells: int, bond: float = 1.42, atoms=None, vacuum: float = 20.) -> Geometry:
+def graphene_flake(shells: int,
+                   bond: float = 1.42,
+                   atoms=None,
+                   vacuum: float = 20.) -> Geometry:
     """Hexagonal flake of graphene, with zig-zag edges.
 
     Parameters

src/sisl/geometry.py

@@ -12,7 +12,7 @@
 from math import acos
 from numbers import Integral, Real
 from pathlib import Path
-from typing import TYPE_CHECKING, Iterator, List, Optional, Tuple, Union
+from typing import TYPE_CHECKING, Iterator, List, Optional, Sequence, Tuple, Union
 
 import numpy as np
 from numpy import (
@@ -1762,7 +1762,7 @@ def update_flag(kw, arg, val):
         return self.sub(atoms_flat)
 
     def optimize_nsc(self,
-                     axis=None,
+                     axes: Optional[Union[int, Sequence[int]]]=None,
                      R: Optional[float]=None) -> ndarray:
         """ Optimize the number of supercell connections based on ``self.maxR()``
 
@@ -1772,15 +1772,17 @@ def optimize_nsc(self,
 
         Parameters
         ----------
-        axis : int or array_like, optional
-           only optimize the specified axis (default to all)
+        axes :
+           only optimize the specified axes (default to all)
         R :
            the maximum connection radius for each atom
         """
-        if axis is None:
-            axis = [0, 1, 2]
+        if axes is None:
+            axes = [0, 1, 2]
         else:
-            axis = _a.asarrayi(axis).ravel()
+            axes = _a.asarrayi(axes).ravel()
+        if len(axes) == 0:
+            return self.nsc
 
         if R is None:
             R = self.maxR() + 0.001
@@ -1802,12 +1804,12 @@ def optimize_nsc(self,
         # I don't think we need anything other than this.
         # However, until I am sure that this wouldn't change, regardless of the
         # cell. I will keep it.
-        Rimcell = R * fnorm(imcell)[axis]
-        nsc[axis] = (floor(Rimcell) + ceil(Rimcell % 0.5 - 0.5)).astype(np.int32)
+        Rimcell = R * fnorm(imcell)[axes]
+        nsc[axes] = (floor(Rimcell) + ceil(Rimcell % 0.5 - 0.5)).astype(np.int32)
         # Since for 1 it is not sure that it is a connection or not, we limit the search by
         # removing it.
-        nsc[axis] = np.where(nsc[axis] > 1, nsc[axis], 0)
-        for i in axis:
+        nsc[axes] = np.where(nsc[axes] > 1, nsc[axes], 0)
+        for i in axes:
             # Initialize the isc for this direction
             # (note we do not take non-orthogonal directions
             #  into account)