diff --git a/.github/workflows/testing.yml b/.github/workflows/testing.yml
index 0ad25ff..52d1fa6 100644
--- a/.github/workflows/testing.yml
+++ b/.github/workflows/testing.yml
@@ -32,7 +32,7 @@
          ]
          include:
            - environment-file: ci/py312-latest.yaml
-             os: macos-latest
+             os: macos-13 # Intel
            - environment-file: ci/py312-latest.yaml
              os: macos-14 # Apple Silicon
            - environment-file: ci/py312-latest.yaml
@@ -60,7 +60,7 @@
 
        - name: environment info
          run: "micromamba info && micromamba list"
-       
+
        - name: run tests
          run: |
            pytest \
@@ -71,8 +71,18 @@
            --cov fastpair \
            --cov-append \
            --cov-report term-missing \
-           --cov-report xml .
-       
+           --cov-report xml . \
+
+       - name: run doctests (dev only)
+         if: contains(matrix.environment-file, 'dev')
+         run: |
+           pytest \
+           fastpair/ \
+           --verbose \
+           -r a \
+           --color yes \
+           --doctest-only
+
        - name: codecov
          uses: codecov/codecov-action@v4
          with:
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index df0f70d..d6ad7ce 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -5,3 +5,11 @@ repos:
     hooks:
       - id: ruff
       - id: ruff-format
+  - repo: https://github.com/pre-commit/mirrors-mypy
+    rev: "v1.10.1"
+    hooks:
+      - id: mypy
+
+ci:
+  autofix_prs: false
+  autoupdate_schedule: quarterly
diff --git a/ci/py310-oldest.yaml b/ci/py310-oldest.yaml
index 3f799f6..e6caa59 100644
--- a/ci/py310-oldest.yaml
+++ b/ci/py310-oldest.yaml
@@ -5,6 +5,7 @@ dependencies:
   - python=3.10
   - numpy=1.24
   - scipy=1.10
+  - typing_extensions
   # testing
   - pytest
   - pytest-cov
diff --git a/ci/py311-latest.yaml b/ci/py311-latest.yaml
index d92f8db..4b99501 100644
--- a/ci/py311-latest.yaml
+++ b/ci/py311-latest.yaml
@@ -4,6 +4,7 @@ channels:
 dependencies:
   - python=3.11
   - scipy
+  - typing_extensions
   # testing
   - pytest
   - pytest-cov
diff --git a/ci/py312-dev.yaml b/ci/py312-dev.yaml
index 1664a5e..8e2221d 100644
--- a/ci/py312-dev.yaml
+++ b/ci/py312-dev.yaml
@@ -4,9 +4,11 @@ channels:
 dependencies:
   - python=3.12
   - pip
+  - typing_extensions
   # testing
   - pytest
   - pytest-cov
+  - pytest-doctestplus
   - pip:
     # nightly builds
     - --pre \
diff --git a/ci/py312-latest.yaml b/ci/py312-latest.yaml
index d5c5642..3ea1f5a 100644
--- a/ci/py312-latest.yaml
+++ b/ci/py312-latest.yaml
@@ -4,6 +4,7 @@ channels:
 dependencies:
   - python=3.12
   - scipy
+  - typing_extensions
   # testing
   - pytest
   - pytest-cov
diff --git a/fastpair/base.py b/fastpair/base.py
index 7b5226f..3576c39 100644
--- a/fastpair/base.py
+++ b/fastpair/base.py
@@ -2,16 +2,30 @@
 # Copyright (c) 2002-2015, David Eppstein
 # Licensed under the MIT Licence (http://opensource.org/licenses/MIT).
 
+
 from collections import defaultdict
 from itertools import combinations, cycle
 
 import scipy.spatial.distance as dist
 
+from .types import (
+    AllNeighs,
+    Callable,
+    ClosestPair,
+    Dist,
+    DistNeighDict,  # noqa: F401
+    DistNeighTuple,
+    Iterable,
+    PointCoords,
+    PointsInput,
+    Self,
+)
+
 __all__ = ["FastPair", "dist"]
 
 
 class AttrDict(dict):
-    """Simple dict with support for accessing elements as attributes."""
+    """Simple ``dict`` with support for accessing elements as attributes."""
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
@@ -21,7 +35,7 @@ def __init__(self, *args, **kwargs):
 class FastPair:
     """FastPair: Data-structure for the dynamic closest-pair problem.
 
-    This data-structure is based on the observation that the conga line data
+    This data structure is based on the observation that the conga line data
     structure, in practice, does better the more subsets you give to it: even
     though the worst case time for :math:`k` subsets is :math:`O(nk log (n/k))`,
     that worst case seems much harder to reach than the nearest neighbor algorithm.
@@ -50,35 +64,125 @@ class FastPair:
         https://doi.org/10.1145/351827.351829
     """
 
-    def __init__(self, min_points=10, dist=dist.euclidean):
-        """Initialize an empty FastPair data-structure.
+    def __init__(self, min_points: int = 10, dist: Callable = dist.euclidean) -> None:
+        """Initialize an empty ``FastPair`` data-structure.
 
         Parameters
         ----------
         min_points : int, default=10
             The minimum number of points to add before initializing the
-            data-structure. Queries _before_ `min_points` have been added to
-            the data-structure will be brute-force.
-        dist : function, default=scipy.spatial.distance.euclidean
+            data structure. Queries *before* ``min_points`` have been added to
+            the data structure will be brute-force.
+        dist : Callable, default=scipy.spatial.distance.euclidean
             Can be any Python function that returns a distance (float) between
-            between two vectors (tuples) `u` and `v`. Any distance function
-            from `scipy.spatial.distance` will do the trick. By default, the
+            between two vectors (tuples) ``u`` and ``v``. Any distance function
+            from ``scipy.spatial.distance`` will do the trick. By default, the
             Euclidean distance function is used. This function should play
-            nicely with the `merge` function.
+            nicely with the ``merge`` function.
+
+        Attributes
+        ----------
+        initialized : bool
+            ``True`` after the ``build()`` method is called.
+        neighbors : defaultdict[AttrDict]
+            Internally defined ``dict`` with support for accessing
+            elements as attributes where keys are ``PointCoords``
+            and values are ``DistNeighDict``.
+        points : None | PointsInput
+            An list of 2D (two-dimensional) point tuples in the point set.
+            All objects in ``points`` **must** have equivalent dimensions.
+
+        Examples
+        --------
+        Create empty data structure with default values.
+
+        >>> import fastpair
+        >>> fp = fastpair.FastPair()
+        >>> fp
+        <FastPair[min_points=10, dist=euclidean]
+         Current state: not initialized with 0 0D points>
+
+        Add points and build conga line.
+
+        >>> points_2d = ((1, 1), (2, 2), (4, 4))
+        >>> fp.build(points_2d)
+        <FastPair[min_points=10, dist=euclidean]
+         Current state: initialized with 3 2D points>
+
+        Query closest pair.
+
+        >>> fp.closest_pair()
+        (np.float64(1.4142135623730951), ((1, 1), (2, 2)))
+
+        Add a point to the data structure.
+
+        >>> fp += (1, 0)
+        >>> fp
+        <FastPair[min_points=10, dist=euclidean]
+         Current state: initialized with 4 2D points>
+
+        Query again for closest pair.
+
+        >>> fp.closest_pair()
+        (np.float64(1.0), ((1, 0), (1, 1)))
+
+        Remove a point from the data structure.
+
+        >>> fp -= (1, 1)
+        >>> fp
+        <FastPair[min_points=10, dist=euclidean]
+         Current state: initialized with 3 2D points>
+
+        Query again for closest pair.
+
+        >>> fp.closest_pair()
+        (np.float64(2.23606797749979), ((1, 0), (2, 2)))
+
+        The default distance metric is ``scipy.spatial.distance.euclidean``.
+        Let's rebuild the ``FastPair`` with another metric. Many of the
+        distance functions available via ``scipy.spatial.distance`` can used.
+        Here we'll try ``cityblock``, which Manhattan distance.
+
+        >>> from scipy.spatial import distance
+        >>> fp = fastpair.FastPair(min_points=3, dist=distance.cityblock)
+        >>> fp.build(points_2d)
+        <FastPair[min_points=3, dist=cityblock]
+         Current state: initialized with 3 2D points>
+
+        While the closet pair remains the same, the distance between the
+        pair has increased with the new distance function.
+
+        >>> fp.closest_pair()
+        (np.int64(2), ((1, 1), (2, 2)))
         """
+
         self.min_points = min_points
         self.dist = dist
-        self.initialized = False  # Has the data-structure been initialized?
-        self.neighbors = defaultdict(AttrDict)  # Dict of neighbor points and dists
-        self.points = []  # Internal point set; entries may be non-unique
-
-    def __add__(self, p):
+        # Has the data-structure been initialized?
+        self.initialized = False
+        # Dict of neighbor points and dists
+        self.neighbors: defaultdict = defaultdict(AttrDict)
+        # Internal point set; entries may be non-unique
+        self.points: list = []
+
+    def __repr__(self) -> str:
+        mp = self.min_points
+        d = self.dist.__name__
+        init = "" if self.initialized else "not "
+        curr_pnts = len(self)
+        dim = 0 if not self.points else len(self.points[0])
+        return (
+            f"<FastPair[min_points={mp}, dist={d}]\n"
+            f" Current state: {init}initialized with {curr_pnts} {dim}D points>"
+        )
+
+    def __add__(self, p: PointCoords) -> Self:
         """Add a point and find its nearest neighbor.
 
         There is some extra logic here to allow us to gradually build up the
-        FastPair data-structure until we reach `min_points`. Once `min_points`
-        has been reached, we initialize the data-structure and start to take
-        advantage of the FastPair efficiencies.
+        ``FastPair`` data structure until we reach ``min_points``. Once ``min_points``
+        has been reached, we initialize the data structure and start to take
+        advantage of the ``FastPair`` efficiencies.
         """
         self.points.append(p)
         if self.initialized:
@@ -87,7 +191,7 @@ def __add__(self, p):
             self.build()
         return self
 
-    def __sub__(self, p):
+    def __sub__(self, p: PointCoords) -> Self:
         """Remove a point and update neighbors."""
         self.points.remove(p)
         if self.initialized:
@@ -97,51 +201,75 @@ def __sub__(self, p):
                     self._find_neighbor(q)
         return self
 
-    def __len__(self):
+    def __len__(self) -> int:
         """Number of points in data structure."""
         return len(self.points)
 
-    def __call__(self):
+    def __call__(self) -> ClosestPair:
         """Find closest pair by scanning list of nearest neighbors."""
         return self.closest_pair()
 
-    def __contains__(self, p):
+    def __contains__(self, p: PointCoords) -> bool:
         return p in self.points
 
-    def __iter__(self):
+    def __iter__(self) -> Iterable:
         return iter(self.points)
 
-    def __getitem__(self, item):
+    def __getitem__(self, item: PointCoords) -> DistNeighTuple:
         if item not in self:
             raise KeyError(f"{item} not found")
         return self.neighbors[item]
 
-    def __setitem__(self, item, value):
+    def __setitem__(self, item: PointCoords, value: Dist | PointCoords):
         if item not in self:
             raise KeyError(f"{item} not found")
         self._update_point(item, value)
 
-    def build(self, points=None):
-        """Build a FastPairs data-structure from a set of (new) points.
+    def build(self, points: None | PointsInput = None) -> Self:
+        """Build a ``FastPair`` data-structure from a set of (new) points.
 
         Here we use a conga line rather than calling explicitly (re)building
         the neighbors map multiple times as it is more efficient. This method
-        needs to be called _before_ querying the data-structure or adding/
+        needs to be called *before* querying the data structure or adding/
         removing any new points. Once it has been called, the internal
-        `initialized` flag will be set to True. Otherwise, simple brute-force
-        versions of queries and calculations will be used.
+        ``initialized`` flag will be set to ``True``. Otherwise, simple
+        brute-force versions of queries and calculations will be used.
 
         Parameters
         ----------
-        points : list of tuples/vectors, default=None
-            An optional list of point tuples to be added to the point set,
-            prior to computing the conga line and main FastPair data structure.
+        points : None | PointsInput, default=None
+            An optional list of 2D+ (two-dimensional or greater) point tuples
+            to be added to the point set, prior to computing the conga line
+            and main ``FastPair`` data structure. All objects in ``points``
+            **must** have equivalent dimensions.
+
+        Examples
+        --------
+
+        Initialize and build the data structure 300 equally-spaced 2D points.
+
+        >>> import fastpair
+        >>> fp = fastpair.FastPair().build([(i, 1) for i in range(300)])
+        >>> fp
+        <FastPair[min_points=10, dist=euclidean]
+         Current state: initialized with 300 2D points>
+
+        Ensure all neighbor distances are exactly 1.0 (except the last point
+        which has no conga-style neighbor).
+
+        >>> all([fp.neighbors[i]["dist"] == 1.0 for i in fp.points[:-1]])
+        True
+
+        Since the last point has no neighbors, its distance is assigned as ``inf``.
+
+        >>> fp.neighbors[fp.points[-1]]["dist"]
+        inf
         """
         if points is not None:
             self.points += list(points)
         np = len(self)
 
-        # Go through and find all neighbors, placing then in a conga line
+        # Go through and find all neighbors, placing them in a conga line
         for i in range(np - 1):
             # Find neighbor to p[0] to start
             nbr = i + 1
@@ -163,13 +291,29 @@ def build(self, points=None):
         self.initialized = True
         return self
 
-    def closest_pair(self):
+    def closest_pair(self) -> ClosestPair:
         """Find closest pair by scanning list of nearest neighbors.
 
-        If `npoints` is less than `min_points`, a brute-force version
-        of the closest pair algrithm is used.
+        If ``npoints`` is less than ``min_points``, a brute-force version
+        of the closest pair algorithm is used.
+
+        Examples
+        --------
+        Create and build the data structure with default values.
+
+        >>> import fastpair
+        >>> fp = fastpair.FastPair(min_points=3).build(((1, 1), (2, 2), (4, 4)))
+        >>> fp
+        <FastPair[min_points=3, dist=euclidean]
+         Current state: initialized with 3 2D points>
+
+        Query closest pair.
+
+        >>> fp.closest_pair()
+        (np.float64(1.4142135623730951), ((1, 1), (2, 2)))
         """
-        if len(self) < 2:
+        npoints = len(self)
+        if npoints < 2:
             raise ValueError("Must have `npoints >= 2` to form a pair.")
         elif not self.initialized:
             return self.closest_pair_brute_force()
@@ -182,28 +326,39 @@ def closest_pair(self):
         b = self.neighbors[a].neigh
         return d, (a, b)
 
-    def closest_pair_brute_force(self):
+    def closest_pair_brute_force(self) -> ClosestPair:
         """Find closest pair using brute-force algorithm."""
         return _closest_pair_brute_force(self.points, self.dist)
 
-    def sdist(self, p):
-        """Compute distances from input to all other points in data-structure.
+    def sdist(self, p: PointCoords) -> AllNeighs:
+        """Compute distances from input to all other points in data structure.
 
         This returns an iterator over all other points and their distance
-        from the input point `p`. The resulting iterator returns tuples with
+        from the input point ``p``. The resulting iterator returns tuples with
         the first item giving the distance, and the second item giving in
-        neighbor point. The `min` of this iterator is essentially a brute-
-        force 'nearest-neighbor' calculation. To do this, supply `itemgetter`
-        (or a lambda version) as the `key` argument to `min`.
+        neighbor point. The ``min`` of this iterator is essentially a brute-
+        force 'nearest-neighbor' calculation. To do this, supply ``operator.itemgetter``
+        (or a ``lambda`` function) as the ``key`` argument to ``min``.
 
         Examples
         --------
-        >>> fp = FastPair().build(points)
-        >>> min(fp.sdist(point), key=itemgetter(0))
+        Initialize and build the data structure.
+
+        >>> import fastpair, operator
+        >>> points = ((1, 1), (2, 2), (4, 4))
+        >>> fp = fastpair.FastPair().build(points)
+
+        Query the data structure using the ``.sdist()`` method for the closest
+        single point to ``(1, 1)``.
+
+        >>> focal_point = (1, 1)
+        >>> min(fp.sdist(focal_point), key=operator.itemgetter(0))
+        (np.float64(1.4142135623730951), (2, 2))
         """
+
         return ((self.dist(a, b), b) for a, b in zip(cycle([p]), self.points) if b != a)
 
-    def _find_neighbor(self, p):
+    def _find_neighbor(self, p: PointCoords):
         """Find and update nearest neighbor of a given point."""
         # If no neighbors available, set flag for `_update_point` to find
         if len(self) < 2:
@@ -225,16 +380,15 @@ def _find_neighbor(self, p):
                         self.neighbors[p].neigh = q
         return dict(self.neighbors[p])  # Return plain ol' dict
 
-    def _update_point(self, old, new):
+    def _update_point(self, old: PointCoords, new: PointCoords):
         """Update point location, neighbors, and distances.
 
         All distances to point have changed, we need to recompute all aspects
         of the data structure that may be affected. Note that although we
-        completely recompute the neighbors of the original point (`old`), we
+        completely recompute the neighbors of the original point (``old``), we
         don't explicitly rebuild the neighbors map, since that would double the
         number of distance computations made by this routine. Also, like
-        deletion, we don't change any _other_ point's neighbor to the updated
-        point.
+        deletion, we don't change any *other* point's neighbor to the updated point.
         """
         # Out with the old, in with the new...
         self.points.remove(old)
@@ -265,13 +419,15 @@ def _update_point(self, old, new):
     #     return self._update_point(a, c)
 
 
-def _closest_pair_brute_force(pts, dst=dist.euclidean):
+def _closest_pair_brute_force(
+    pts: PointsInput, dst: Callable = dist.euclidean
+) -> ClosestPair:
     """Compute closest pair of points using brute-force algorithm.
 
     Notes
     -----
     Computes all possible combinations of points and compares their distances.
-    This is _not_ efficient, nor scalable, but it provides a useful reference
+    This is *not* efficient, nor scalable, but it provides a useful reference
     for more efficient algorithms. This version is actually pretty fast due
     to its use of fast Python builtins.
     """
diff --git a/fastpair/tests/conftest.py b/fastpair/tests/conftest.py
index 36b8bc4..0119bd8 100644
--- a/fastpair/tests/conftest.py
+++ b/fastpair/tests/conftest.py
@@ -2,12 +2,12 @@
 import pytest
 
 
-def rand_tuple(dim: int = 2, seed: None | int = None) -> tuple[float]:
+def rand_tuple(dim: int = 2, seed: None | int = None) -> tuple[float, ...]:
     rng = numpy.random.default_rng(seed)
     return tuple([round(rng.uniform(), 4) for j in range(dim)])
 
 
-def point_set(n: int = 50, d: int = 10, seed: int = 0) -> list[tuple[float, float]]:
+def point_set(n: int = 50, d: int = 10, seed: int = 0) -> list[tuple[float, ...]]:
     """Return ``numpy.array`` of shape ``(n, d)``."""
     return [rand_tuple(dim=d, seed=seed + i) for i in range(n)]
 
diff --git a/fastpair/tests/test_fastpair.py b/fastpair/tests/test_fastpair.py
index 3f762ff..634dc97 100644
--- a/fastpair/tests/test_fastpair.py
+++ b/fastpair/tests/test_fastpair.py
@@ -11,6 +11,7 @@
 from itertools import combinations, cycle
 from operator import itemgetter
 from types import FunctionType
+from typing import Any
 
 import numpy
 import pytest
@@ -18,7 +19,7 @@
 from fastpair import FastPair
 
 
-def normalized_distance(_a: numpy.array, _b: numpy.array) -> float:
+def normalized_distance(_a: numpy.ndarray, _b: numpy.ndarray) -> numpy.floating[Any]:
     """Compute the normalized distance between 2 arrays."""
     b = _b.astype(int)
     a = _a.astype(int)
@@ -28,7 +29,7 @@ def normalized_distance(_a: numpy.array, _b: numpy.array) -> float:
     return norm_diff / (norm1 + norm2)
 
 
-def image_distance(image1: tuple, image2: tuple) -> float:
+def image_distance(image1: tuple, image2: tuple) -> numpy.floating[Any]:
     """Custom distance metric."""
     (sig1, _) = image1
     (sig2, _) = image2
@@ -37,9 +38,8 @@ def image_distance(image1: tuple, image2: tuple) -> float:
     return normalized_distance(sig1, sig2)
 
 
-def contains_same(s: list, t: list) -> bool:
-    """Determine if 2 lists contain the same (set-theoretic) elements."""
-    s, t = set(s), set(t)
+def contains_same(s: set, t: set) -> bool:
+    """Determine if 2 set[list] objects contain the same (set-theoretic) elements."""
     return s >= t and s <= t
 
 
@@ -386,7 +386,7 @@ def test_basic(self):
             ps.remove(e)
             ps.remove(f)
             ps.append(g)
-            assert contains_same(fp.points, ps)
+            assert contains_same(set(fp.points), set(ps))
 
         assert len(fp.points) == len(ps) == 1
 
@@ -414,7 +414,7 @@ def test_complex(self):
             ps.remove(e)
             ps.remove(f)
             ps.append(g)
-            assert contains_same(fp.points, ps)
+            assert contains_same(set(fp.points), set(ps))
 
         assert len(fp.points) == len(ps) == 1
 
diff --git a/fastpair/types.py b/fastpair/types.py
new file mode 100644
index 0000000..db9d3bb
--- /dev/null
+++ b/fastpair/types.py
@@ -0,0 +1,71 @@
+# Copyright (c) 2016, Carson J. Q. Farmer <carson.farmer@gmail.com>
+# Copyright (c) 2002-2015, David Eppstein
+# Licensed under the MIT Licence (http://opensource.org/licenses/MIT).
+
+import sys
+from collections.abc import Callable, Generator, Iterable
+from typing import Annotated, TypeAlias, TypedDict, TypeVar
+
+################################################################
+# See GH#73 -- remove once Python 3.11 is minimum
+if sys.version_info.minor < 11:
+    from typing_extensions import Self
+else:
+    from typing import Self
+################################################################
+
+import numpy
+
+__all__ = [
+    "Callable",
+    "Iterable",
+    "Self",
+    "NumericCoord",
+    "PointCoords",
+    "PointsInput",
+    "Dist",
+    "DistNeighTuple",
+    "AllNeighs",
+    "DistNeighDict",
+    "NeighCoords",
+    "ClosestPair",
+]
+
+
+# point typing ---------------------------------------------------------------------
+_Numeric = TypeVar("_Numeric", float, int, complex, numpy.number)
+_NumericAnnotation = Annotated[_Numeric, "Any numeric value."]
+NumericCoord: TypeAlias = _NumericAnnotation
+
+_PointCoords = TypeVar("_PointCoords", bound=tuple[NumericCoord])
+PointCoords = Annotated[_PointCoords, "A tuple of at least 2 numeric elements."]
+
+_PointsInput = TypeVar("_PointsInput", bound=Iterable[PointCoords])
+PointsInput = Annotated[_PointsInput, "Input for ``.build()``."]
+
+
+# distance typing ------------------------------------------------------------------
+Dist: TypeAlias = _NumericAnnotation
+
+_DistNeighTuple = TypeVar("_DistNeighTuple", bound=tuple[Dist, PointCoords])
+DistNeighTuple = Annotated[_DistNeighTuple, "Returned from ``.__getitem__()``."]
+
+_AllNeighs = Generator[DistNeighTuple, None, None]
+AllNeighs = Annotated[_AllNeighs, "Returned from ``.sdist()``."]
+
+
+# pair typing ----------------------------------------------------------------------
+class DistNeighDict(TypedDict):
+    """The values of the ``FastPair.neighbors`` dictionary. Also potentially
+    returned from ``._update_point()``. See GH#69.
+    """
+
+    dist: Dist
+    neigh: PointCoords
+
+
+_NeighCoords = tuple[PointCoords, PointCoords]
+NeighCoords = Annotated[_NeighCoords, "2 instances of ``PointCoords``."]
+
+_ClosestPair = TypeVar("_ClosestPair", bound=tuple[Dist, NeighCoords])
+ClosestPair = Annotated[_ClosestPair, "Returned from ``.closest_pair()``."]
diff --git a/notebooks/basic_usage.ipynb b/notebooks/basic_usage.ipynb
index 5ae2c52..738399b 100644
--- a/notebooks/basic_usage.ipynb
+++ b/notebooks/basic_usage.ipynb
@@ -18,11 +18,11 @@
    "id": "2da42c3d-a668-456c-9d05-5b826d2ca963",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.402265Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.401881Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.431762Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.430862Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.402240Z"
+     "iopub.execute_input": "2024-07-10T21:57:06.485142Z",
+     "iopub.status.busy": "2024-07-10T21:57:06.484639Z",
+     "iopub.status.idle": "2024-07-10T21:57:06.517136Z",
+     "shell.execute_reply": "2024-07-10T21:57:06.516878Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:06.485114Z"
     }
    },
    "outputs": [
@@ -30,11 +30,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Last updated: 2024-06-15T14:59:33.420817-04:00\n",
+      "Last updated: 2024-07-10T17:57:06.508030-04:00\n",
       "\n",
       "Python implementation: CPython\n",
-      "Python version       : 3.12.3\n",
-      "IPython version      : 8.25.0\n",
+      "Python version       : 3.12.4\n",
+      "IPython version      : 8.26.0\n",
       "\n",
       "Compiler    : Clang 16.0.6 \n",
       "OS          : Darwin\n",
@@ -59,11 +59,11 @@
    "id": "5f2c2691-2f11-4649-aafd-eaf734d5c368",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.432574Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.432449Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.660652Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.660447Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.432556Z"
+     "iopub.execute_input": "2024-07-10T21:57:06.517885Z",
+     "iopub.status.busy": "2024-07-10T21:57:06.517779Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.053924Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.053552Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:06.517867Z"
     }
    },
    "outputs": [
@@ -73,8 +73,8 @@
      "text": [
       "Watermark: 2.4.3\n",
       "\n",
+      "fastpair  : 0.1.1.dev12+gb5fa448.d20240622\n",
       "matplotlib: 3.9.0\n",
-      "fastpair  : 0.1.1.dev8+g5f8e7a5.d20240611\n",
       "\n"
      ]
     }
@@ -106,11 +106,11 @@
    "id": "c4845e9d-f5d5-4f92-94f8-72f809f0fac9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.661746Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.661641Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.664384Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.664183Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.661739Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.055454Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.055178Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.058404Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.058190Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.055443Z"
     }
    },
    "outputs": [
@@ -147,18 +147,19 @@
    "id": "7e37b5d2-e626-486d-a02f-c982eea73907",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.664794Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.664731Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.666585Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.666413Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.664787Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.058848Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.058776Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.060804Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.060608Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.058841Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<fastpair.base.FastPair at 0x118a22840>"
+       "<FastPair[min_points=10, dist=euclidean]\n",
+       " Current state: not initialized with 0 0D points>"
       ]
      },
      "execution_count": 4,
@@ -185,18 +186,19 @@
    "id": "895e21eb-9449-4aa5-999b-5ac13f9e4219",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.666934Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.666875Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.668678Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.668503Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.666927Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.061227Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.061159Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.063703Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.063503Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.061219Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<fastpair.base.FastPair at 0x118a22840>"
+       "<FastPair[min_points=10, dist=euclidean]\n",
+       " Current state: initialized with 3 2D points>"
       ]
      },
      "execution_count": 5,
@@ -237,11 +239,11 @@
    "id": "01160597-4c0f-4cd1-9cd4-b7dc8bce6b2a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.669075Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.668999Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.670639Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.670479Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.669069Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.064497Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.064278Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.067597Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.067095Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.064467Z"
     }
    },
    "outputs": [
@@ -276,11 +278,11 @@
    "id": "9d7adeb7-36a4-41e7-93e9-9a1fee6edbed",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.671017Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.670952Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.672651Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.672478Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.671011Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.068239Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.068145Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.070957Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.070608Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.068231Z"
     }
    },
    "outputs": [
@@ -313,11 +315,11 @@
    "id": "30355b1a-3757-43c0-ab95-0733f4f50e81",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.672954Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.672898Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.674490Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.674320Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.672948Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.071672Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.071569Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.074085Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.073893Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.071651Z"
     }
    },
    "outputs": [
@@ -352,18 +354,18 @@
    "id": "78034246-f548-4a1c-9872-ea071462c058",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.674824Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.674719Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.676467Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.676278Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.674818Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.074626Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.074543Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.076670Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.076477Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.074618Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(1.4142135623730951, ((1, 1), (2, 2)))"
+       "(np.float64(1.4142135623730951), ((1, 1), (2, 2)))"
       ]
      },
      "execution_count": 9,
@@ -389,18 +391,18 @@
    "id": "9f7315f7-72d0-4693-9808-d1e325f93c8d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.676827Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.676771Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.678580Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.678391Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.676821Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.077363Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.077295Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.079470Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.079253Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.077356Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(1.4142135623730951, ((1, 1), (2, 2)))"
+       "(np.float64(1.4142135623730951), ((1, 1), (2, 2)))"
       ]
      },
      "execution_count": 10,
@@ -426,18 +428,18 @@
    "id": "37366768-415c-42ab-9c18-110750160483",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.678945Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.678887Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.681266Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.681076Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.678939Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.080075Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.080011Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.082084Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.081898Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.080068Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(1.4142135623730951, ((1, 1), (2, 2)))"
+       "(np.float64(1.4142135623730951), ((1, 1), (2, 2)))"
       ]
      },
      "execution_count": 11,
@@ -465,11 +467,11 @@
    "id": "65890425-a4c6-45f2-8c57-90c7afd9a204",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.683179Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.683091Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.684782Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.684599Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.683171Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.084025Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.083910Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.086158Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.085795Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.084008Z"
     }
    },
    "outputs": [
@@ -492,11 +494,11 @@
    "id": "ac10107e-1f1b-437c-a0c5-0323460a9bff",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.685173Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.685115Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.687289Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.687107Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.685167Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.087276Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.086911Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.089871Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.089651Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.087267Z"
     }
    },
    "outputs": [
@@ -530,18 +532,18 @@
    "id": "9284e7a7-0765-4d9e-9f51-0c64217fe778",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.687723Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.687661Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.689574Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.689367Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.687716Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.090462Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.090344Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.092428Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.092229Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.090454Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "1.4142135623730951"
+       "np.float64(1.4142135623730951)"
       ]
      },
      "execution_count": 14,
@@ -567,11 +569,11 @@
    "id": "2e255c57-90c4-4596-8f31-9f352cc89357",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.690071Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.689975Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.691883Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.691718Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.690064Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.092773Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.092711Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.095051Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.094662Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.092766Z"
     }
    },
    "outputs": [
@@ -597,18 +599,18 @@
    "id": "dcc5c91e-1ab4-4ee9-acad-a9a349de8793",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.692191Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.692136Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.694180Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.693986Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.692185Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.095713Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.095629Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.097711Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.097487Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.095706Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "29.698484809834994"
+       "np.float64(29.698484809834994)"
       ]
      },
      "execution_count": 16,
@@ -636,20 +638,20 @@
    "id": "05d78d6f-1f73-4718-b070-cc81e27154ec",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.694597Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.694529Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.696568Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.696373Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.694591Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.098137Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.098074Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.100071Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.099866Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.098129Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "((2.8284271247461903, (1, 1)),\n",
-       " (4.242640687119285, (2, 2)),\n",
-       " (7.0710678118654755, (4, 4)))"
+       "((np.float64(2.8284271247461903), (1, 1)),\n",
+       " (np.float64(4.242640687119285), (2, 2)),\n",
+       " (np.float64(7.0710678118654755), (4, 4)))"
       ]
      },
      "execution_count": 17,
@@ -685,18 +687,18 @@
    "id": "aa6bab3b-18d0-489e-9d56-2b1e215b8f36",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.696931Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.696865Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.699292Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.699068Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.696924Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.100591Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.100362Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.102711Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.102402Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.100584Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(1.4142135623730951, ((1, 1), (2, 2)))"
+       "(np.float64(1.4142135623730951), ((1, 1), (2, 2)))"
       ]
      },
      "execution_count": 18,
@@ -727,11 +729,11 @@
    "id": "62b69b65-7070-4667-a447-cc8f7b2a6396",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.699861Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.699640Z",
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-     "shell.execute_reply": "2024-06-15T18:59:33.786306Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.699853Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.103301Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.103033Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.232355Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.232095Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.103270Z"
     }
    },
    "outputs": [
@@ -775,11 +777,11 @@
    "id": "55c1f26a-62e1-4c9b-a407-23f476967f65",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.787074Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.786995Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.789125Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.788914Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.787066Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.232900Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.232828Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.235550Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.235289Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.232893Z"
     }
    },
    "outputs": [],
@@ -803,18 +805,18 @@
    "id": "58e711ce-4774-4e26-958e-13dabb91c7f2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.789448Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.789378Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.791875Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.791673Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.789440Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.236088Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.236016Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.238308Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.238128Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.236080Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(1.0, ((1, 2), (1, 1)))"
+       "(np.float64(1.0), ((1, 2), (1, 1)))"
       ]
      },
      "execution_count": 21,
@@ -847,11 +849,11 @@
    "id": "f44c118b-cca2-4c40-b0a1-f66436f0ab22",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.792296Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.792234Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.873693Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.873470Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.792289Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.238663Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.238590Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.321617Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.321356Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.238656Z"
     }
    },
    "outputs": [
@@ -896,11 +898,11 @@
    "id": "100f2b17-9c34-4d43-9e21-f293744fcb68",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.874275Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.874202Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.876386Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.876170Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.874268Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.322224Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.322154Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.324133Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.323882Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.322217Z"
     }
    },
    "outputs": [],
@@ -924,18 +926,18 @@
    "id": "3c729bbd-6e6d-4e1d-bc04-e8bbdb81c9a7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.876768Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.876686Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.878895Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.878683Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.876760Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.324707Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.324636Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.327169Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.326972Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.324699Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(1.0, ((1, 2), (1, 1)))"
+       "(np.float64(1.0), ((1, 2), (1, 1)))"
       ]
      },
      "execution_count": 24,
@@ -969,11 +971,11 @@
    "id": "1a071985-2d07-4473-a5a4-5c2ab151139d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:33.879285Z",
-     "iopub.status.busy": "2024-06-15T18:59:33.879227Z",
-     "iopub.status.idle": "2024-06-15T18:59:33.963223Z",
-     "shell.execute_reply": "2024-06-15T18:59:33.962995Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:33.879279Z"
+     "iopub.execute_input": "2024-07-10T21:57:07.327711Z",
+     "iopub.status.busy": "2024-07-10T21:57:07.327600Z",
+     "iopub.status.idle": "2024-07-10T21:57:07.410781Z",
+     "shell.execute_reply": "2024-07-10T21:57:07.410256Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:07.327703Z"
     }
    },
    "outputs": [
@@ -1028,7 +1030,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/n-dimensional_pointsets.ipynb b/notebooks/n-dimensional_pointsets.ipynb
index cb470f5..44978f7 100644
--- a/notebooks/n-dimensional_pointsets.ipynb
+++ b/notebooks/n-dimensional_pointsets.ipynb
@@ -18,11 +18,11 @@
    "id": "2da42c3d-a668-456c-9d05-5b826d2ca963",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:19.800738Z",
-     "iopub.status.busy": "2024-06-15T18:59:19.800507Z",
-     "iopub.status.idle": "2024-06-15T18:59:19.832881Z",
-     "shell.execute_reply": "2024-06-15T18:59:19.832503Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:19.800703Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.422228Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.422038Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.450826Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.450544Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.422207Z"
     }
    },
    "outputs": [
@@ -30,11 +30,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Last updated: 2024-06-15T14:59:19.824932-04:00\n",
+      "Last updated: 2024-07-10T17:57:28.442134-04:00\n",
       "\n",
       "Python implementation: CPython\n",
-      "Python version       : 3.12.3\n",
-      "IPython version      : 8.25.0\n",
+      "Python version       : 3.12.4\n",
+      "IPython version      : 8.26.0\n",
       "\n",
       "Compiler    : Clang 16.0.6 \n",
       "OS          : Darwin\n",
@@ -59,11 +59,11 @@
    "id": "5f2c2691-2f11-4649-aafd-eaf734d5c368",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:19.833802Z",
-     "iopub.status.busy": "2024-06-15T18:59:19.833671Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.062575Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.062380Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:19.833784Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.451498Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.451397Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.708230Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.707977Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.451475Z"
     }
    },
    "outputs": [
@@ -73,9 +73,9 @@
      "text": [
       "Watermark: 2.4.3\n",
       "\n",
-      "fastpair  : 0.1.1.dev8+g5f8e7a5.d20240611\n",
+      "numpy     : 2.0.0\n",
+      "fastpair  : 0.1.1.dev12+gb5fa448.d20240622\n",
       "matplotlib: 3.9.0\n",
-      "numpy     : 1.26.4\n",
       "\n"
      ]
     }
@@ -114,11 +114,11 @@
    "id": "26917e2e-d996-469e-9028-3edd638ffe10",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.063748Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.063563Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.065445Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.065238Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.063740Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.709409Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.709287Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.711253Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.711056Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.709401Z"
     }
    },
    "outputs": [],
@@ -151,18 +151,18 @@
    "id": "e7078d76-f6db-43c9-aff8-8c541ea385f9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.065764Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.065702Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.068272Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.068088Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.065758Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.711632Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.711561Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.714223Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.713985Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.711624Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[(10.236432494005134,)]"
+       "[(np.float64(10.236432494005134),)]"
       ]
      },
      "execution_count": 4,
@@ -188,20 +188,20 @@
    "id": "c9a81f46-a864-4d96-a9a3-9e801a8a6e42",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.068756Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.068653Z",
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-     "shell.execute_reply": "2024-06-15T18:59:20.070230Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.068750Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.714664Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.714573Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.716675Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.716445Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.714657Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[(10.236432494005134, 19.009273926518706),\n",
-       " (2.8831922543926747, 18.972988942744877),\n",
-       " (6.236629040209709, 8.466528979451514)]"
+       "[(np.float64(10.236432494005134), np.float64(19.009273926518706)),\n",
+       " (np.float64(2.8831922543926747), np.float64(18.972988942744877)),\n",
+       " (np.float64(6.236629040209709), np.float64(8.466528979451514))]"
       ]
      },
      "execution_count": 5,
@@ -231,18 +231,19 @@
    "id": "8a43ef42-621d-42b1-9ca6-cc1e5ec1d0b1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.070857Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.070765Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.072578Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.072408Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.070851Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.717099Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.717038Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.719730Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.719515Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.717092Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<fastpair.base.FastPair at 0x11ef8ab10>"
+       "<FastPair[min_points=10, dist=euclidean]\n",
+       " Current state: initialized with 4 3D points>"
       ]
      },
      "execution_count": 6,
@@ -272,11 +273,11 @@
    "id": "cccf5da4-94ad-46d6-89a6-17a1444ca15a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.072982Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.072923Z",
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-     "shell.execute_reply": "2024-06-15T18:59:20.074665Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.072976Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.720286Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.720211Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.723221Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.722929Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.720279Z"
     }
    },
    "outputs": [
@@ -284,8 +285,12 @@
      "data": {
       "text/plain": [
        "(4.0502751383410684,\n",
-       " ((18.870650112211077, 7.188420666831464, 15.696108239399543),\n",
-       "  (17.38663089357139, 7.282768525810457, 19.463536292657878)))"
+       " ((np.float64(18.870650112211077),\n",
+       "   np.float64(7.188420666831464),\n",
+       "   np.float64(15.696108239399543)),\n",
+       "  (np.float64(17.38663089357139),\n",
+       "   np.float64(7.282768525810457),\n",
+       "   np.float64(19.463536292657878))))"
       ]
      },
      "execution_count": 7,
@@ -316,11 +321,11 @@
    "id": "c8c7dd0d-20ca-43cd-b22a-c0308f203497",
    "metadata": {
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-     "iopub.execute_input": "2024-06-15T18:59:20.075343Z",
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-     "shell.execute_reply": "2024-06-15T18:59:20.167365Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.075337Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.723751Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.723664Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.818350Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.818114Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.723743Z"
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    "outputs": [
@@ -367,11 +372,11 @@
    "id": "626ff3e1-727a-49ab-ad1b-91fd4eae5541",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.168108Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.168036Z",
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-     "shell.execute_reply": "2024-06-15T18:59:20.169784Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.168100Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.818858Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.818778Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.820742Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.820511Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.818850Z"
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@@ -402,11 +407,11 @@
    "id": "144bebae-d91b-432a-b048-6b4f6d7e68d5",
    "metadata": {
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-     "iopub.execute_input": "2024-06-15T18:59:20.170357Z",
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-     "shell.execute_reply": "2024-06-15T18:59:20.171978Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.170350Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.821165Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.821097Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.823480Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.823249Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.821157Z"
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    "outputs": [
@@ -414,8 +419,12 @@
      "data": {
       "text/plain": [
        "(3.738192198648357,\n",
-       " ((1.7129833428724872, 4.736210131921994, 16.025489304127937),\n",
-       "  (5.232242684986328, 5.969822868282466, 16.284514811885607)))"
+       " ((np.float64(1.7129833428724872),\n",
+       "   np.float64(4.736210131921994),\n",
+       "   np.float64(16.025489304127937)),\n",
+       "  (np.float64(5.232242684986328),\n",
+       "   np.float64(5.969822868282466),\n",
+       "   np.float64(16.284514811885607))))"
       ]
      },
      "execution_count": 10,
@@ -448,11 +457,11 @@
    "id": "d26a20cc-5710-43d4-911f-733f85b5d882",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.172555Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.172491Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.265862Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.265608Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.172549Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.823968Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.823886Z",
+     "iopub.status.idle": "2024-07-10T21:57:28.915380Z",
+     "shell.execute_reply": "2024-07-10T21:57:28.915121Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.823959Z"
     }
    },
    "outputs": [
@@ -507,11 +516,11 @@
    "id": "5c7921d4-9fd5-4fa0-9d9e-e39a4b12e2b4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.267699Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.267595Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.395680Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.395397Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.267689Z"
+     "iopub.execute_input": "2024-07-10T21:57:28.917381Z",
+     "iopub.status.busy": "2024-07-10T21:57:28.917271Z",
+     "iopub.status.idle": "2024-07-10T21:57:29.045927Z",
+     "shell.execute_reply": "2024-07-10T21:57:29.045598Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:28.917372Z"
     }
    },
    "outputs": [
@@ -573,18 +582,19 @@
    "id": "a25c1e2b-7b5e-4cf4-ab8a-e267dca0b502",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.396449Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.396296Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.411426Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.411189Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.396438Z"
+     "iopub.execute_input": "2024-07-10T21:57:29.046477Z",
+     "iopub.status.busy": "2024-07-10T21:57:29.046386Z",
+     "iopub.status.idle": "2024-07-10T21:57:29.060710Z",
+     "shell.execute_reply": "2024-07-10T21:57:29.060485Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:29.046468Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<fastpair.base.FastPair at 0x11f8eef60>"
+       "<FastPair[min_points=10, dist=euclidean]\n",
+       " Current state: initialized with 100 4D points>"
       ]
      },
      "execution_count": 13,
@@ -612,11 +622,11 @@
    "id": "e56fcf7d-739d-4e44-967e-b157fdc408b5",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.411981Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.411911Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.414050Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.413832Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.411974Z"
+     "iopub.execute_input": "2024-07-10T21:57:29.061295Z",
+     "iopub.status.busy": "2024-07-10T21:57:29.061169Z",
+     "iopub.status.idle": "2024-07-10T21:57:29.063850Z",
+     "shell.execute_reply": "2024-07-10T21:57:29.063617Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:29.061287Z"
     }
    },
    "outputs": [
@@ -649,33 +659,33 @@
    "id": "3a2dda4b-e65a-44c9-881b-1267bffe0425",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.414516Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.414451Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.416562Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.416371Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.414509Z"
+     "iopub.execute_input": "2024-07-10T21:57:29.064633Z",
+     "iopub.status.busy": "2024-07-10T21:57:29.064540Z",
+     "iopub.status.idle": "2024-07-10T21:57:29.067659Z",
+     "shell.execute_reply": "2024-07-10T21:57:29.067431Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:29.064625Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "([(18.870650112211077,\n",
-       "   7.188420666831464,\n",
-       "   15.696108239399543,\n",
-       "   11.825563704588236),\n",
-       "  (19.463536292657878,\n",
-       "   4.490486614702625,\n",
-       "   16.10991735856244,\n",
-       "   13.617924625616881)],\n",
-       " [(6.281485191595186,\n",
-       "   15.617152919852579,\n",
-       "   18.501034362350563,\n",
-       "   0.8032379106434839),\n",
-       "  (19.60606658563202,\n",
-       "   0.9476558986387795,\n",
-       "   18.152996427027382,\n",
-       "   3.1155672960451475)])"
+       "([(np.float64(18.870650112211077),\n",
+       "   np.float64(7.188420666831464),\n",
+       "   np.float64(15.696108239399543),\n",
+       "   np.float64(11.825563704588236)),\n",
+       "  (np.float64(19.463536292657878),\n",
+       "   np.float64(4.490486614702625),\n",
+       "   np.float64(16.10991735856244),\n",
+       "   np.float64(13.617924625616881))],\n",
+       " [(np.float64(6.281485191595186),\n",
+       "   np.float64(15.617152919852579),\n",
+       "   np.float64(18.501034362350563),\n",
+       "   np.float64(0.8032379106434839)),\n",
+       "  (np.float64(19.60606658563202),\n",
+       "   np.float64(0.9476558986387795),\n",
+       "   np.float64(18.152996427027382),\n",
+       "   np.float64(3.1155672960451475))])"
       ]
      },
      "execution_count": 15,
@@ -701,11 +711,11 @@
    "id": "cfedf7c1-83f2-4c4e-a83c-4741a681ba3d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.416957Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.416891Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.419429Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.419202Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.416950Z"
+     "iopub.execute_input": "2024-07-10T21:57:29.068203Z",
+     "iopub.status.busy": "2024-07-10T21:57:29.068117Z",
+     "iopub.status.idle": "2024-07-10T21:57:29.070228Z",
+     "shell.execute_reply": "2024-07-10T21:57:29.070032Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:29.068195Z"
     }
    },
    "outputs": [
@@ -713,14 +723,14 @@
      "data": {
       "text/plain": [
        "(1.471913992306667,\n",
-       " ((12.143319051427731,\n",
-       "   8.096696612806012,\n",
-       "   8.069117114956994,\n",
-       "   1.7566196855998584),\n",
-       "  (12.855616484647092,\n",
-       "   8.883192737858987,\n",
-       "   7.978835783535024,\n",
-       "   0.7405309621851197)))"
+       " ((np.float64(12.143319051427731),\n",
+       "   np.float64(8.096696612806012),\n",
+       "   np.float64(8.069117114956994),\n",
+       "   np.float64(1.7566196855998584)),\n",
+       "  (np.float64(12.855616484647092),\n",
+       "   np.float64(8.883192737858987),\n",
+       "   np.float64(7.978835783535024),\n",
+       "   np.float64(0.7405309621851197))))"
       ]
      },
      "execution_count": 16,
@@ -753,11 +763,11 @@
    "id": "38fb8d6c-7a2b-48b3-b473-c2793451880c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-06-15T18:59:20.419997Z",
-     "iopub.status.busy": "2024-06-15T18:59:20.419923Z",
-     "iopub.status.idle": "2024-06-15T18:59:20.796052Z",
-     "shell.execute_reply": "2024-06-15T18:59:20.795820Z",
-     "shell.execute_reply.started": "2024-06-15T18:59:20.419990Z"
+     "iopub.execute_input": "2024-07-10T21:57:29.070730Z",
+     "iopub.status.busy": "2024-07-10T21:57:29.070629Z",
+     "iopub.status.idle": "2024-07-10T21:57:29.511556Z",
+     "shell.execute_reply": "2024-07-10T21:57:29.511305Z",
+     "shell.execute_reply.started": "2024-07-10T21:57:29.070723Z"
     }
    },
    "outputs": [
@@ -766,36 +776,36 @@
      "output_type": "stream",
      "text": [
       "points=100, dimensions=7\n",
-      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "  fp.closest_pair()=(np.float64(22.22611077089287), ((np.int64(75), np.int64(82), np.int64(62), np.int64(53), np.int64(97), np.int64(30), np.int64(37)), (np.int64(77), np.int64(89), np.int64(72), np.int64(61), np.int64(97), np.int64(44), np.int64(46))))\n",
       "points=200, dimensions=7\n",
-      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "  fp.closest_pair()=(np.float64(15.491933384829668), ((np.int64(62), np.int64(28), np.int64(18), np.int64(58), np.int64(90), np.int64(59), np.int64(24)), (np.int64(60), np.int64(33), np.int64(17), np.int64(52), np.int64(92), np.int64(58), np.int64(37))))\n",
       "\n",
       "points=100, dimensions=7\n",
-      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "  fp.closest_pair()=(np.float64(22.22611077089287), ((np.int64(75), np.int64(82), np.int64(62), np.int64(53), np.int64(97), np.int64(30), np.int64(37)), (np.int64(77), np.int64(89), np.int64(72), np.int64(61), np.int64(97), np.int64(44), np.int64(46))))\n",
       "points=200, dimensions=7\n",
-      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "  fp.closest_pair()=(np.float64(15.491933384829668), ((np.int64(62), np.int64(28), np.int64(18), np.int64(58), np.int64(90), np.int64(59), np.int64(24)), (np.int64(60), np.int64(33), np.int64(17), np.int64(52), np.int64(92), np.int64(58), np.int64(37))))\n",
       "\n",
       "points=100, dimensions=7\n",
-      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "  fp.closest_pair()=(np.float64(22.22611077089287), ((np.int64(75), np.int64(82), np.int64(62), np.int64(53), np.int64(97), np.int64(30), np.int64(37)), (np.int64(77), np.int64(89), np.int64(72), np.int64(61), np.int64(97), np.int64(44), np.int64(46))))\n",
       "points=200, dimensions=7\n",
-      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "  fp.closest_pair()=(np.float64(15.491933384829668), ((np.int64(62), np.int64(28), np.int64(18), np.int64(58), np.int64(90), np.int64(59), np.int64(24)), (np.int64(60), np.int64(33), np.int64(17), np.int64(52), np.int64(92), np.int64(58), np.int64(37))))\n",
       "\n",
       "points=100, dimensions=7\n",
-      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "  fp.closest_pair()=(np.float64(22.22611077089287), ((np.int64(75), np.int64(82), np.int64(62), np.int64(53), np.int64(97), np.int64(30), np.int64(37)), (np.int64(77), np.int64(89), np.int64(72), np.int64(61), np.int64(97), np.int64(44), np.int64(46))))\n",
       "points=200, dimensions=7\n",
-      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "  fp.closest_pair()=(np.float64(15.491933384829668), ((np.int64(62), np.int64(28), np.int64(18), np.int64(58), np.int64(90), np.int64(59), np.int64(24)), (np.int64(60), np.int64(33), np.int64(17), np.int64(52), np.int64(92), np.int64(58), np.int64(37))))\n",
       "\n",
       "points=100, dimensions=7\n",
-      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "  fp.closest_pair()=(np.float64(22.22611077089287), ((np.int64(75), np.int64(82), np.int64(62), np.int64(53), np.int64(97), np.int64(30), np.int64(37)), (np.int64(77), np.int64(89), np.int64(72), np.int64(61), np.int64(97), np.int64(44), np.int64(46))))\n",
       "points=200, dimensions=7\n",
-      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "  fp.closest_pair()=(np.float64(15.491933384829668), ((np.int64(62), np.int64(28), np.int64(18), np.int64(58), np.int64(90), np.int64(59), np.int64(24)), (np.int64(60), np.int64(33), np.int64(17), np.int64(52), np.int64(92), np.int64(58), np.int64(37))))\n",
       "\n",
       "points=100, dimensions=7\n",
-      "  fp.closest_pair()=(22.22611077089287, ((75, 82, 62, 53, 97, 30, 37), (77, 89, 72, 61, 97, 44, 46)))\n",
+      "  fp.closest_pair()=(np.float64(22.22611077089287), ((np.int64(75), np.int64(82), np.int64(62), np.int64(53), np.int64(97), np.int64(30), np.int64(37)), (np.int64(77), np.int64(89), np.int64(72), np.int64(61), np.int64(97), np.int64(44), np.int64(46))))\n",
       "points=200, dimensions=7\n",
-      "  fp.closest_pair()=(15.491933384829668, ((62, 28, 18, 58, 90, 59, 24), (60, 33, 17, 52, 92, 58, 37)))\n",
+      "  fp.closest_pair()=(np.float64(15.491933384829668), ((np.int64(62), np.int64(28), np.int64(18), np.int64(58), np.int64(90), np.int64(59), np.int64(24)), (np.int64(60), np.int64(33), np.int64(17), np.int64(52), np.int64(92), np.int64(58), np.int64(37))))\n",
       "\n",
-      "62.2 ms ± 5.66 ms per loop (mean ± std. dev. of 3 runs, 2 loops each)\n"
+      "73 ms ± 4.84 ms per loop (mean ± std. dev. of 3 runs, 2 loops each)\n"
      ]
     }
    ],
@@ -845,7 +855,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,
diff --git a/pyproject.toml b/pyproject.toml
index ba8b498..0ac6a18 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -35,6 +35,7 @@ requires-python = ">=3.10"
 dependencies = [
     "numpy>=1.24",
     "scipy>=1.10",
+    "typing_extensions",  # only for 3.10 -- remove when 3.11+
 ]
 
 [project.urls]
@@ -48,6 +49,7 @@ tests = [
     "pre-commit",
     "pytest",
     "pytest-cov",
+    "pytest-doctestplus",
     "ruff",
     "setuptools_scm",
 ]
@@ -93,3 +95,8 @@ include = [
  "*__init__.py" = [
      "F401",  # imported but unused
 ]
+
+[tool.mypy]
+non_interactive = true
+install_types = true
+ignore_missing_imports = true