Docstring and type annotation fixes; rename redundant overview.

docs/index.md

@@ -3,7 +3,7 @@
 ```{toctree}
 :maxdepth: 2
 
-Overview <readme>
+Usage <readme>
 Contributions & Help <contributing>
 License <license>
 Authors <authors>

src/knncolle/find_knn.py

@@ -47,8 +47,8 @@ def find_knn(
     num_neighbors: Union[int, Sequence],
     num_threads: int = 1,
     subset: Optional[Sequence] = None, 
-    get_index = True,
-    get_distance = True,
+    get_index: bool = True,
+    get_distance: bool = True,
     **kwargs
 ) -> FindKnnResults:
     """Find the k-nearest neighbors for each observation.
@@ -99,8 +99,8 @@ def _find_knn_generic(
     num_neighbors: Union[int, Sequence],
     num_threads: int = 1,
     subset: Optional[Sequence] = None,
-    get_index = True,
-    get_distance = True,
+    get_index: bool = True,
+    get_distance: bool = True,
     **kwargs
 ) -> FindKnnResults:
     num_neighbors, force_variable = process_num_neighbors(num_neighbors)

src/knncolle/find_neighbors.py

@@ -38,8 +38,8 @@ def find_neighbors(
     threshold: Union[float, Sequence],
     num_threads: int = 1,
     subset: Optional[Sequence] = None, 
-    get_index = True,
-    get_distance = True,
+    get_index: bool = True,
+    get_distance: bool = True,
     **kwargs
 ) -> FindNeighborsResults:
     """Find all neighbors within a certain distance for each observation.
@@ -89,8 +89,8 @@ def _find_neighbors_generic(
     threshold: Union[int, Sequence],
     num_threads: int = 1,
     subset: Optional[Sequence] = None,
-    get_index = True,
-    get_distance = True,
+    get_index: bool = True,
+    get_distance: bool = True,
     **kwargs
 ) -> FindNeighborsResults:
     idx, dist = lib.generic_find_all(

src/knncolle/query_knn.py

@@ -40,8 +40,8 @@ def query_knn(
     query: numpy.ndarray,
     num_neighbors: Union[int, Sequence],
     num_threads: int = 1,
-    get_index = True,
-    get_distance = True,
+    get_index: bool = True,
+    get_distance: bool = True,
     **kwargs
 ) -> QueryKnnResults:
     """Find the k-nearest neighbors in the search index for each observation in
@@ -90,8 +90,8 @@ def _query_knn_generic(
     query: numpy.ndarray,
     num_neighbors: Union[int, Sequence],
     num_threads: int = 1,
-    get_index = True,
-    get_distance = True,
+    get_index: bool = True,
+    get_distance: bool = True,
     **kwargs
 ) -> QueryKnnResults:
     num_neighbors, force_variable = process_num_neighbors(num_neighbors)

src/knncolle/query_neighbors.py

@@ -33,8 +33,8 @@ def query_neighbors(
     threshold: Union[float, Sequence],
     num_threads: int = 1,
     subset: Optional[Sequence] = None, 
-    get_index = True,
-    get_distance = True,
+    get_index: bool = True,
+    get_distance: bool = True,
     **kwargs
 ) -> QueryNeighborsResults:
     """Find all observations in the search index that lie within a threshold
@@ -82,8 +82,8 @@ def _query_neighbors_generic(
     query: numpy.ndarray,
     threshold: Union[float, Sequence],
     num_threads: int = 1,
-    get_index = True,
-    get_distance = True,
+    get_index: bool = True,
+    get_distance: bool = True,
     **kwargs
 ) -> QueryNeighborsResults:
     idx, dist = lib.generic_query_all(

src/knncolle/vptree.py

@@ -55,7 +55,7 @@ def __init__(self, ptr):
 
     @property
     def ptr(self):
-        """Pointer to a prebuilt index, see :py:meth:`~__init-_`."""
+        """Pointer to a prebuilt index, see :py:meth:`~__init__`."""
         return self._ptr