From 14adcd3b6c6ca951573cc47e528c751bc98a6a40 Mon Sep 17 00:00:00 2001
From: Arina Danilina <danilina@cip.ifi.lmu.de>
Date: Sat, 5 Oct 2024 00:00:36 +0200
Subject: [PATCH] categorical_dtype update

---
 docs/notebooks                      | 2 +-
 src/moscot/plotting/_utils.py       | 3 +--
 src/moscot/problems/time/_mixins.py | 4 ++--
 3 files changed, 4 insertions(+), 5 deletions(-)

diff --git a/docs/notebooks b/docs/notebooks
index c48edf3d0..5b9d4e07d 160000
--- a/docs/notebooks
+++ b/docs/notebooks
@@ -1 +1 @@
-Subproject commit c48edf3d0acb6dc191bb571320357b9119a6c559
+Subproject commit 5b9d4e07d7188b1c391ec47a1c5d957da1ab2bca
diff --git a/src/moscot/plotting/_utils.py b/src/moscot/plotting/_utils.py
index 358ae5fa2..49fdf3c8a 100644
--- a/src/moscot/plotting/_utils.py
+++ b/src/moscot/plotting/_utils.py
@@ -18,7 +18,6 @@
 
 import numpy as np
 import pandas as pd
-from pandas.api.types import is_categorical_dtype
 from sklearn.preprocessing import MinMaxScaler
 
 import matplotlib as mpl
@@ -523,7 +522,7 @@ def _color_transition(c1: str, c2: str, num: int, alpha: float) -> List[str]:
 def _create_col_colors(adata: AnnData, obs_col: str, subset: Union[str, List[str]]) -> Optional[mpl.colors.Colormap]:
     if isinstance(subset, list):
         subset = subset[0]
-    if not is_categorical_dtype(adata.obs[obs_col]):
+    if not isinstance(adata.obs[obs_col].dtype, pd.CategoricalDtype):
         raise TypeError(f"`adata.obs[{obs_col!r}] must be of categorical type.")
 
     for i, cat in enumerate(adata.obs[obs_col].cat.categories):
diff --git a/src/moscot/problems/time/_mixins.py b/src/moscot/problems/time/_mixins.py
index 29a44aed0..4673934c1 100644
--- a/src/moscot/problems/time/_mixins.py
+++ b/src/moscot/problems/time/_mixins.py
@@ -18,7 +18,7 @@
 
 import numpy as np
 import pandas as pd
-from pandas.api.types import infer_dtype, is_categorical_dtype, is_numeric_dtype
+from pandas.api.types import infer_dtype, is_numeric_dtype
 
 from anndata import AnnData
 
@@ -1034,7 +1034,7 @@ def temporal_key(self: TemporalMixinProtocol[K, B], key: Optional[str]) -> None:
             raise KeyError(f"Unable to find temporal key in `adata.obs[{key!r}]`.")
         self.adata.obs[key] = self.adata.obs[key].astype("category")
         col = self.adata.obs[key]
-        if not (is_categorical_dtype(col) and is_numeric_dtype(col.cat.categories)):
+        if not (isinstance(col.dtype, pd.CategoricalDtype) and is_numeric_dtype(col.cat.categories)):
             raise TypeError(
                 f"Expected `adata.obs[{key!r}]` to be categorical with numeric categories, "
                 f"found `{infer_dtype(col)}`."