smftools.preprocessing.clean_NaN

smftools.preprocessing.clean_NaN(adata, layer=None, uns_flag='clean_NaN_performed', bypass=False, force_redo=True, layers_to_build=None)

Append layers to adata that contain NaN-cleaning strategies.

Uses numpy float32 operations throughout to avoid the memory overhead of converting to a float64 pandas DataFrame.

Parameters:

• adata (AnnData) -- AnnData object.

• layer (str | None (default: None)) -- Layer to fill NaN values in. If None, uses adata.X.

• uns_flag (str (default: 'clean_NaN_performed')) -- Flag in adata.uns indicating prior completion.

• bypass (bool (default: False)) -- Whether to skip processing.

• force_redo (bool (default: True)) -- Whether to rerun even if uns_flag is set.

• layers_to_build (Optional[List[str]] (default: None)) -- Which NaN-fill strategy layers to create. Valid values: fill_nans_closest, nan0_0minus1, nan1_12, nan_minus_1, nan_half. Defaults to ["nan0_0minus1", "nan_half"].

Return type:

None