ValueError: b'Extrapolation not allowed with blending' when using `"sc.pp.highly_variable_genes"` function

Please make sure these conditions are met

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of scanpy.
• (optional) I have confirmed this bug exists on the master branch of scanpy.

What happened?

During preprocessing of concatenated adata file for scvi-based label transfer, processing fails when applying "sc.pp.highly_variable_genes" function with "ValueError: b'Extrapolation not allowed with blending'"

Minimal code sample

aadata = aadata.concatenate(ref_data_WT)

aadata.X
<15445x13343 sparse matrix of type '<class 'numpy.float64'>'
	with 107849393 stored elements in Compressed Sparse Row format>

# pre-processing:
aadata.layers["counts"] = aadata.X.copy()
sc.pp.normalize_total(aadata, target_sum=1e4)
sc.pp.log1p(aadata)
aadata.raw = aadata

sc.pp.highly_variable_genes(aadata, flavor = 'seurat_v3', n_top_genes=2000,
                            layer = "counts", batch_key="batch", subset = True)#, span =0.5

Error output

ValueError                                Traceback (most recent call last)
Cell In[37], line 7
      4 sc.pp.log1p(aadata)
      5 aadata.raw = aadata
----> 7 sc.pp.highly_variable_genes(aadata, flavor = 'seurat_v3', n_top_genes=2000,
      8                             layer = "counts", batch_key="batch", subset = True)#, span =0.5

File ~/mambaforge/envs/soupxEnv/lib/python3.10/site-packages/scanpy/preprocessing/_highly_variable_genes.py:441, in highly_variable_genes(adata, layer, n_top_genes, min_disp, max_disp, min_mean, max_mean, span, n_bins, flavor, subset, inplace, batch_key, check_values)
    439         sig = signature(_highly_variable_genes_seurat_v3)
    440         n_top_genes = cast(int, sig.parameters["n_top_genes"].default)
--> 441     return _highly_variable_genes_seurat_v3(
    442         adata,
    443         layer=layer,
    444         n_top_genes=n_top_genes,
    445         batch_key=batch_key,
    446         check_values=check_values,
    447         span=span,
    448         subset=subset,
    449         inplace=inplace,
    450     )
    452 if batch_key is None:
    453     df = _highly_variable_genes_single_batch(
    454         adata,
    455         layer=layer,
   (...)
    462         flavor=flavor,
    463     )

File ~/mambaforge/envs/soupxEnv/lib/python3.10/site-packages/scanpy/preprocessing/_highly_variable_genes.py:87, in _highly_variable_genes_seurat_v3(adata, layer, n_top_genes, batch_key, check_values, span, subset, inplace)
     85 x = np.log10(mean[not_const])
     86 model = loess(x, y, span=span, degree=2)
---> 87 model.fit()
     88 estimat_var[not_const] = model.outputs.fitted_values
     89 reg_std = np.sqrt(10**estimat_var)

File _loess.pyx:899, in _loess.loess.fit()

ValueError: b'Extrapolation not allowed with blending'

Versions

scanpy==1.9.8 anndata==0.10.2 umap==0.5.4 numpy==1.24.4 scipy==1.11.3 pandas==2.1.1 scikit-learn==1.3.1 statsmodels==0.14.0 igraph==0.10.8 pynndescent==0.5.10

Reproduce the supplied concatenated AnnData example with scanpy 1.9.8 and inspect scanpy/preprocessing/_highly_variable_genes.py, especially the seurat_v3 path and model.fit() call. Check how the loess fit reaches the “Extrapolation not allowed with blending” error, then verify that the reported batch-key and layer configuration completes and produces the requested highly variable genes.