[skip ci] changed function definition to multiline layout for crystal, seeds and tensor module

python/damask/_crystal.py

@@ -311,7 +311,9 @@ class Crystal():
                         + _lattice_points.get(self.lattice if self.lattice == 'hP' else \
                                               self.lattice[-1],None),dtype=float)
 
-    def to_lattice(self, *, direction: np.ndarray = None, plane: np.ndarray = None) -> np.ndarray:
+    def to_lattice(self,
+                   *, direction: np.ndarray = None,
+                   plane: np.ndarray = None) -> np.ndarray:
         """
         Calculate lattice vector corresponding to crystal frame direction or plane normal.
 
@@ -335,7 +337,10 @@ class Crystal():
         return np.einsum('il,...l',basis,axis)
 
 
-    def to_frame(self, *, uvw: np.ndarray = None, hkl: np.ndarray = None) -> np.ndarray:
+    def to_frame(self,
+                 *,
+                 uvw: np.ndarray = None,
+                 hkl: np.ndarray = None) -> np.ndarray:
         """
         Calculate crystal frame vector along lattice direction [uvw] or plane normal (hkl).
 
@@ -358,7 +363,8 @@ class Crystal():
         return np.einsum('il,...l',basis,axis)
 
 
-    def kinematics(self, mode: str) -> Dict[str, List[np.ndarray]]:
+    def kinematics(self,
+                   mode: str) -> Dict[str, List[np.ndarray]]:
         """
         Return crystal kinematics systems.
 
@@ -617,7 +623,8 @@ class Crystal():
                     'plane':    [m[:,3:6] for m in master]}
 
 
-    def relation_operations(self, model: str) -> Tuple[str, Rotation]:
+    def relation_operations(self,
+                            model: str) -> Tuple[str, Rotation]:
         """
         Crystallographic orientation relationships for phase transformations.
 

python/damask/seeds.py

@@ -10,7 +10,9 @@ from . import util as _util
 from . import grid_filters as _grid_filters
 
 
-def from_random(size: _FloatSequence, N_seeds: int, cells: _IntSequence = None,
+def from_random(size: _FloatSequence,
+                N_seeds: int,
+                cells: _IntSequence = None,
                 rng_seed=None) -> _np.ndarray:
     """
     Place seeds randomly in space.
@@ -46,8 +48,12 @@ def from_random(size: _FloatSequence, N_seeds: int, cells: _IntSequence = None,
     return coords
 
 
-def from_Poisson_disc(size: _FloatSequence, N_seeds: int, N_candidates: int, distance: float,
-                      periodic: bool = True, rng_seed=None) -> _np.ndarray:
+def from_Poisson_disc(size: _FloatSequence,
+                      N_seeds: int,
+                      N_candidates: int,
+                      distance: float,
+                      periodic: bool = True,
+                      rng_seed=None) -> _np.ndarray:
     """
     Place seeds according to a Poisson disc distribution.
 
@@ -99,8 +105,11 @@ def from_Poisson_disc(size: _FloatSequence, N_seeds: int, N_candidates: int, dis
     return coords
 
 
-def from_grid(grid, selection: _IntSequence = None, invert_selection: bool = False,
-              average: bool = False, periodic: bool = True) -> _Tuple[_np.ndarray, _np.ndarray]:
+def from_grid(grid,
+              selection: _IntSequence = None,
+              invert_selection: bool = False,
+              average: bool = False,
+              periodic: bool = True) -> _Tuple[_np.ndarray, _np.ndarray]:
     """
     Create seeds from grid description.
 

python/damask/tensor.py

@@ -45,7 +45,8 @@ def eigenvalues(T_sym: _np.ndarray) -> _np.ndarray:
     return _np.linalg.eigvalsh(symmetric(T_sym))
 
 
-def eigenvectors(T_sym: _np.ndarray, RHS: bool = False) -> _np.ndarray:
+def eigenvectors(T_sym: _np.ndarray,
+                 RHS: bool = False) -> _np.ndarray:
     """
     Eigenvectors of a symmetric tensor.
 
@@ -70,7 +71,8 @@ def eigenvectors(T_sym: _np.ndarray, RHS: bool = False) -> _np.ndarray:
     return v
 
 
-def spherical(T: _np.ndarray, tensor: bool = True) -> _np.ndarray:
+def spherical(T: _np.ndarray,
+              tensor: bool = True) -> _np.ndarray:
     """
     Calculate spherical part of a tensor.