replace numba with numpy

.github/workflows/requirements-test.txt

@@ -7,5 +7,4 @@ numpy == 2.0
 ruptures == 1.1.9
 scikit-learn == 1.5
 pandas == 2.2.2
-numba == 0.60
 xarray == 2024.6

dupin/data/spatial.py

@@ -6,24 +6,11 @@
 from . import base
 
 
-def _njit(*args, **kwargs):
-    """Allow for JIT when numba is found."""
-    try:
-        import numba
-    except ImportError:
-        return lambda x: x
-    return numba.njit(*args, **kwargs)
-
-
-@_njit()
 def _freud_neighbor_summing(
-    arr: np.ndarray,
-    particle_index: np.ndarray,
-    neighbor_index: np.ndarray,
-    base: np.ndarray,
+    arr, particle_index, neighbor_index, base
 ) -> np.ndarray:
-    for i, j in zip(particle_index, neighbor_index):
-        base[i] += arr[j]
+    np.add.at(base, particle_index, arr[neighbor_index])
+    return base
 
 
 class NeighborAveraging(base.DataMap):