Merge pull request #160 from pyiron/type_hints

Add type hints

structuretoolkit/analyse/distance.py

@@ -1,7 +1,15 @@
+from typing import Optional
+from ase.atoms import Atoms
 import numpy as np
 
 
-def get_distances_array(structure, p1=None, p2=None, mic=True, vectors=False):
+def get_distances_array(
+    structure: Atoms,
+    p1: Optional[np.ndarray] = None,
+    p2: Optional[np.ndarray] = None,
+    mic: bool = True,
+    vectors: bool = False,
+):
     """
     Return distance matrix of every position in p1 with every position in
     p2. If p2 is not set, it is assumed that distances between all
@@ -39,7 +47,7 @@ def get_distances_array(structure, p1=None, p2=None, mic=True, vectors=False):
     return find_mic(structure=structure, v=diff_relative, vectors=vectors)
 
 
-def find_mic(structure, v, vectors=True):
+def find_mic(structure: Atoms, v: np.ndarray, vectors: bool = True):
     """
     Find vectors following minimum image convention (mic). In principle this
     function does the same as ase.geometry.find_mic

structuretoolkit/analyse/dscribe.py

@@ -1,22 +1,27 @@
+import numpy as np
+from ase.atoms import Atoms
+from typing import Optional
+
+
 def soap_descriptor_per_atom(
-    structure,
-    r_cut=None,
-    n_max=None,
-    l_max=None,
-    sigma=1.0,
-    rbf="gto",
-    weighting=None,
-    average="off",
-    compression={"mode": "off", "species_weighting": None},
-    species=None,
-    periodic=True,
-    sparse=False,
-    dtype="float64",
-    centers=None,
-    n_jobs=1,
-    only_physical_cores=False,
-    verbose=False,
-):
+    structure: Atoms,
+    r_cut: Optional[float] = None,
+    n_max: Optional[int] = None,
+    l_max: Optional[int] = None,
+    sigma: Optional[float] = 1.0,
+    rbf: str = "gto",
+    weighting: Optional[np.ndarray] = None,
+    average: str = "off",
+    compression: dict = {"mode": "off", "species_weighting": None},
+    species: Optional[list] = None,
+    periodic: bool = True,
+    sparse: bool = False,
+    dtype: str = "float64",
+    centers: Optional[np.ndarray] = None,
+    n_jobs: int = 1,
+    only_physical_cores: bool = False,
+    verbose: bool = False,
+) -> np.ndarray:
     from dscribe.descriptors import SOAP
 
     if species is None: