Change niche flavor to cellcharter_simple and default distance = 3

src/squidpy/_constants/_constants.py

@@ -129,6 +129,6 @@ class TenxVersions(str, ModeEnum):
 class NicheDefinitions(ModeEnum):
     NEIGHBORHOOD = "neighborhood"
     UTAG = "utag"
-    CELLCHARTER = "cellcharter"
+    CELLCHARTER = "cellcharter_simple"
     SPOT = "spot"
     BANKSY = "banksy"

src/squidpy/gr/_niche.py

@@ -29,7 +29,7 @@
 @inject_docs(fla=NicheDefinitions)
 def calculate_niche(
     data: AnnData | SpatialData,
-    flavor: Literal["neighborhood", "utag", "cellcharter"],
+    flavor: Literal["neighborhood", "utag", "cellcharter_simple"],
     library_key: str | None = None,
     table_key: str | None = None,
     mask: pd.core.series.Series = None,
@@ -58,7 +58,7 @@ def calculate_niche(
         Method to use for niche calculation. Available options are:
             - `{fla.NEIGHBORHOOD.s!r}` - cluster the neighborhood profile.
             - `{fla.UTAG.s!r}` - use utag algorithm (matrix multiplication).
-            - `{fla.CELLCHARTER.s!r}` - cluster adjacency matrix with Gaussian Mixture Model (GMM) using CellCharter's approach.
+            - `{fla.CELLCHARTER.s!r}` - a simplified version of CellCharter's approach, using PCA instead of scVI for dimensionality reduction.
     %(library_key)s
         If provided, niches will be calculated separately for each unique value in this column.
         Each niche will be prefixed with the library identifier.
@@ -108,7 +108,7 @@ def calculate_niche(
         If 'False', return a new AnnData object with the niche labels.
     """
 
-    if flavor == "cellcharter" and aggregation is None:
+    if flavor == "cellcharter_simple" and aggregation is None:
         aggregation = "mean"
 
     _validate_niche_args(
@@ -134,7 +134,7 @@ def calculate_niche(
         resolutions = [0.5]
 
     if distance is None:
-        distance = 1
+        distance = 3 if flavor == "cellcharter_simple" else 1
 
     if isinstance(data, SpatialData):
         orig_adata = data.tables[table_key]
@@ -187,7 +187,7 @@ def calculate_niche(
                 mask=lib_mask,
                 groups=groups,
                 n_neighbors=n_neighbors,
-                resolutions=None if flavor == "cellcharter" else resolutions,
+                resolutions=None if flavor == "cellcharter_simple" else resolutions,
                 min_niche_size=min_niche_size,
                 scale=scale,
                 abs_nhood=abs_nhood,
@@ -258,7 +258,7 @@ def _get_result_columns(
 
     library_str = f"_{library_key}" if library_key is not None else ""
 
-    if flavor == "cellcharter":
+    if flavor == "cellcharter_simple":
         base_column = "cellcharter_niche"
         if library_key is None:
             return [base_column]
@@ -311,7 +311,7 @@ def _calculate_niches(
         )
     elif flavor == "utag":
         _get_utag_niches(adata, n_neighbors, resolutions, spatial_connectivities_key)
-    elif flavor == "cellcharter":
+    elif flavor == "cellcharter_simple":
         assert isinstance(aggregation, str)  # for mypy
         assert isinstance(n_components, int)  # for mypy
         _get_cellcharter_niches(
@@ -667,7 +667,7 @@ def _jensen_shannon_divergence(adata: AnnData, niche_key: str, library_key: str)
 
 def _validate_niche_args(
     data: AnnData | SpatialData,
-    flavor: Literal["neighborhood", "utag", "cellcharter"],
+    flavor: Literal["neighborhood", "utag", "cellcharter_simple"],
     library_key: str | None,
     table_key: str | None,
     groups: str | None,
@@ -697,8 +697,10 @@ def _validate_niche_args(
     if not isinstance(data, AnnData | SpatialData):
         raise TypeError(f"'data' must be an AnnData or SpatialData object, got {type(data).__name__}")
 
-    if flavor not in ["neighborhood", "utag", "cellcharter"]:
-        raise ValueError(f"Invalid flavor '{flavor}'. Please choose one of 'neighborhood', 'utag', 'cellcharter'.")
+    if flavor not in ["neighborhood", "utag", "cellcharter_simple"]:
+        raise ValueError(
+            f"Invalid flavor '{flavor}'. Please choose one of 'neighborhood', 'utag', 'cellcharter_simple'."
+        )
 
     if library_key is not None:
         if not isinstance(library_key, str):
@@ -760,7 +762,7 @@ def _validate_niche_args(
                 "random_state",
             ],
         },
-        "cellcharter": {
+        "cellcharter_simple": {
             "required": ["distance", "aggregation", "n_components", "random_state"],
             "optional": [],
             "unused": [
@@ -809,7 +811,7 @@ def _validate_niche_args(
         if distance is not None and isinstance(distance, int) and distance < 1:
             raise ValueError(f"'distance' must be at least 1, got {distance}")
 
-    elif flavor == "cellcharter":
+    elif flavor == "cellcharter_simple":
         if distance is not None and not isinstance(distance, int):
             raise TypeError(f"'distance' must be an integer, got {type(distance).__name__}")
         if distance is not None and distance < 1:
@@ -843,7 +845,7 @@ def _check_unnecessary_args(flavor: str, param_dict: dict[str, Any], param_specs
     Parameters
     ----------
     flavor
-        The flavor being used ('neighborhood', 'utag', or 'cellcharter')
+        The flavor being used ('neighborhood', 'utag', or 'cellcharter_simple')
     param_dict
         Dictionary of parameter names to their values
     param_specs