Fix tests

Author: Intron7

src/rapids_singlecell/squidpy_gpu/_niche.py

@@ -199,7 +199,7 @@ def _neighborhood_profile(
     weights: Sequence[float] | None,
     abs_nhood: bool,
     key: str,
-) -> np.ndarray:
+) -> cp.ndarray:
     """Cells x categories matrix of cell-type counts (or relative frequencies) over n-hop neighbors."""
     cats = pd.Categorical(adata.obs[groups])
     n_cats = len(cats.categories)
@@ -218,6 +218,8 @@ def _neighborhood_profile(
         weights = [1.0] * distance
     elif len(weights) < distance:
         weights = list(weights) + [weights[-1]] * (distance - len(weights))
+    if not abs_nhood and sum(weights) == 0:
+        raise ValueError("`n_hop_weights` must not sum to zero.")
 
     profile = cp.zeros((n_obs, n_cats), dtype=cp.float32)
     adj_k = adj_bin
@@ -325,7 +327,7 @@ def _cellcharter_features(
     fused ``mul_csr`` kernel used for utag, then aggregated as either:
 
     - ``"mean"``: ``Âₖ @ X``
-    - ``"variance"``: ``Âₖ @ (X·X) − (Âₖ @ X)²``  (matches squidpy's path; densifies X)
+    - ``"variance"``: ``Âₖ @ (X·X) - (Âₖ @ X)²``  (matches squidpy's path; densifies X)
 
     All layers are concatenated horizontally.
     """

tests/test_gmm.py

@@ -121,11 +121,11 @@ def _cuda_e_step(
         means,
         prec_chol,
         log_det_half,
-        log_prob,
-        responsibilities,
-        ll_per_cell,
-        centered,
-        e_step_y,
+        log_prob=log_prob,
+        responsibilities=responsibilities,
+        ll_per_cell=ll_per_cell,
+        centered=centered,
+        e_step_y=e_step_y,
         e_step_route=e_step_route,
         stream=cp.cuda.get_current_stream().ptr,
         handle=cp.cuda.device.get_cublas_handle(),
@@ -147,11 +147,11 @@ def _cuda_m_step(
         weights,
         means,
         covariances,
-        reg_covar,
-        cp.ones(X.shape[0], dtype=X.dtype),
-        cp.empty(K, dtype=X.dtype),
-        cp.empty((K, X.shape[1]), dtype=X.dtype),
-        cp.empty_like(X),
+        reg_covar=reg_covar,
+        ones=cp.ones(X.shape[0], dtype=X.dtype),
+        effective_counts=cp.empty(K, dtype=X.dtype),
+        weighted_sums=cp.empty((K, X.shape[1]), dtype=X.dtype),
+        centered=cp.empty_like(X),
         stream=cp.cuda.get_current_stream().ptr,
         handle=cp.cuda.device.get_cublas_handle(),
     )
@@ -332,9 +332,9 @@ def test_cuda_matches_reference_steps():
         means,
         prec_chol,
         log_det_half,
-        log_prob,
-        resp,
-        ll_per_cell,
+        log_prob=log_prob,
+        responsibilities=resp,
+        ll_per_cell=ll_per_cell,
         stream=cp.cuda.get_current_stream().ptr,
     )
 
@@ -380,11 +380,11 @@ def test_cuda_512_e_step_matches_reference_for_cublas_route():
         means,
         prec_chol,
         log_det_half,
-        centered,
-        e_step_y,
-        log_prob,
-        resp,
-        ll_per_cell,
+        centered=centered,
+        e_step_y=e_step_y,
+        log_prob=log_prob,
+        responsibilities=resp,
+        ll_per_cell=ll_per_cell,
         stream=cp.cuda.get_current_stream().ptr,
         handle=cp.cuda.device.get_cublas_handle(),
     )
@@ -415,11 +415,11 @@ def test_cuda_768_e_step_uses_cublas_route():
         means,
         prec_chol,
         log_det_half,
-        log_prob,
-        resp,
-        ll_per_cell,
-        centered,
-        e_step_y,
+        log_prob=log_prob,
+        responsibilities=resp,
+        ll_per_cell=ll_per_cell,
+        centered=centered,
+        e_step_y=e_step_y,
         e_step_route="cublas",
         stream=stream,
         handle=handle,
@@ -433,11 +433,11 @@ def test_cuda_768_e_step_uses_cublas_route():
         means,
         prec_chol,
         log_det_half,
-        centered_b,
-        e_step_y_b,
-        log_prob_b,
-        resp_b,
-        ll_per_cell_b,
+        centered=centered_b,
+        e_step_y=e_step_y_b,
+        log_prob=log_prob_b,
+        responsibilities=resp_b,
+        ll_per_cell=ll_per_cell_b,
         stream=stream,
         handle=handle,
     )
@@ -468,11 +468,11 @@ def test_cuda_float64_wide_e_step_uses_cublas_route():
         means,
         prec_chol,
         log_det_half,
-        log_prob,
-        resp,
-        ll_per_cell,
-        centered,
-        e_step_y,
+        log_prob=log_prob,
+        responsibilities=resp,
+        ll_per_cell=ll_per_cell,
+        centered=centered,
+        e_step_y=e_step_y,
         e_step_route=route,
         stream=cp.cuda.get_current_stream().ptr,
         handle=cp.cuda.device.get_cublas_handle(),
@@ -517,11 +517,11 @@ def test_cuda_fused_e_step_matches_reference_for_50_pc_regime():
         means,
         prec_chol,
         log_det_half,
-        log_prob,
-        resp,
-        ll_per_cell,
-        centered,
-        e_step_y,
+        log_prob=log_prob,
+        responsibilities=resp,
+        ll_per_cell=ll_per_cell,
+        centered=centered,
+        e_step_y=e_step_y,
         e_step_route="fused",
         stream=cp.cuda.get_current_stream().ptr,
         handle=cp.cuda.device.get_cublas_handle(),