diff --git a/Cell_BLAST/blast.py b/Cell_BLAST/blast.py
index 896417e..e8f51ae 100644
--- a/Cell_BLAST/blast.py
+++ b/Cell_BLAST/blast.py
@@ -23,7 +23,8 @@
 MINIMAL = 0
 
 
-def _wasserstein_distance_impl(x: np.ndarray, y: np.ndarray):  # pragma: no cover
+@numba.jit(nopython=True, nogil=True, cache=True)
+def wasserstein_distance(x: np.ndarray, y: np.ndarray):  # pragma: no cover
     x_sorter = np.argsort(x)
     y_sorter = np.argsort(y)
     xy = np.concatenate((x, y))
@@ -34,37 +35,6 @@ def _wasserstein_distance_impl(x: np.ndarray, y: np.ndarray):  # pragma: no cove
     return np.sum(np.multiply(np.abs(x_cdf - y_cdf), deltas))
 
 
-def _energy_distance_impl(x: np.ndarray, y: np.ndarray):  # pragma: no cover
-    x_sorter = np.argsort(x)
-    y_sorter = np.argsort(y)
-    xy = np.concatenate((x, y))
-    xy.sort()
-    deltas = np.diff(xy)
-    x_cdf = np.searchsorted(x[x_sorter], xy[:-1], "right") / x.size
-    y_cdf = np.searchsorted(y[y_sorter], xy[:-1], "right") / y.size
-    return np.sqrt(2 * np.sum(np.multiply(np.square(x_cdf - y_cdf), deltas)))
-
-
-@numba.extending.overload(
-    scipy.stats.wasserstein_distance, jit_options={"nogil": True, "cache": True}
-)
-def _wasserstein_distance(x: np.ndarray, y: np.ndarray):  # pragma: no cover
-    if (
-        x == numba.float32[::1] and y == numba.float32[::1]
-    ) or (
-        x == numba.float64[::1] and y == numba.float64[::1]
-    ):
-        return _wasserstein_distance_impl
-
-
-@numba.extending.overload(
-    scipy.stats.energy_distance, jit_options={"nogil": True, "cache": True}
-)
-def _energy_distance(x: np.ndarray, y: np.ndarray):  # pragma: no cover
-    if x == numba.float32[::1] and y == numba.float32[::1]:
-        return _energy_distance_impl
-
-
 @numba.jit(nopython=True, nogil=True, cache=True)
 def ed(x: np.ndarray, y: np.ndarray):  # pragma: no cover
     r"""
@@ -230,10 +200,10 @@ def npd_v1(
         np.std(y_posterior) + np.float32(eps)
     )
     return 0.5 * (
-        scipy.stats.wasserstein_distance(
+        wasserstein_distance(
             xy_posterior1[: len(x_posterior)], xy_posterior1[-len(y_posterior) :]
         )
-        + scipy.stats.wasserstein_distance(
+        + wasserstein_distance(
             xy_posterior2[: len(x_posterior)], xy_posterior2[-len(y_posterior) :]
         )
     )
@@ -939,13 +909,15 @@ def query(
             hits,
             dist,
             pval,
-            query
-            if store_dataset
-            else anndata.AnnData(
-                X=scipy.sparse.csr_matrix((query.shape[0], 0)),
-                obs=pd.DataFrame(index=query.obs.index),
-                var=pd.DataFrame(),
-                uns={},
+            (
+                query
+                if store_dataset
+                else anndata.AnnData(
+                    X=scipy.sparse.csr_matrix((query.shape[0], 0)),
+                    obs=pd.DataFrame(index=query.obs.index),
+                    var=pd.DataFrame(),
+                    uns={},
+                )
             ),
         )