Fix pandas and plotting warning (#1065)

* Fix setting categories

* Fix using `inplace` in `reorder_categories`

* Remove `Colorbar.draw()`

* Remove setting `pandas.DataFrame` attributes in `get_df`

---------

Co-authored-by: Philipp Weiler <weiler.philipp@gmail.com>

pyproject.toml

@@ -47,7 +47,7 @@ dependencies = [
     "umap-learn>=0.3.10",
     "numba>=0.41.0",
     "numpy>=1.17",
-    "pandas>=0.23, !=1.4.0",
+    "pandas>=1.1.1, !=1.4.0",
     "scipy>=1.4.1",
     "scikit-learn>=0.21.2, <1.2.0",
     "scvi-tools>=0.20.1",

scvelo/core/_anndata.py

@@ -292,17 +292,6 @@ def get_df(
         )
         df = df.sort_values(by=sort_by, ascending=False)
 
-    if hasattr(data, "var_names"):
-        if df.index[0] in data.var_names:
-            df.var_names = df.index
-        elif df.columns[0] in data.var_names:
-            df.var_names = df.columns
-    if hasattr(data, "obs_names"):
-        if df.index[0] in data.obs_names:
-            df.obs_names = df.index
-        elif df.columns[0] in data.obs_names:
-            df.obs_names = df.columns
-
     return df
 
 

scvelo/plotting/utils.py

@@ -641,7 +641,8 @@ def set_legend(
     if legend_fontoutline is None:
         legend_fontoutline = 1
     obs_vals = adata.obs[value_to_plot]
-    obs_vals.cat.categories = obs_vals.cat.categories.astype(str)
+    str_cats = obs_vals.cat.categories.astype(str)
+    obs_vals = obs_vals.cat.set_categories(str_cats, rename=True)
     color_keys = adata.uns[f"{value_to_plot}_colors"]
     if isinstance(color_keys, dict):
         color_keys = np.array([color_keys[c] for c in obs_vals.cat.categories])
@@ -964,7 +965,6 @@ def set_colorbar(smp, ax, orientation="vertical", labelsize=None):
     cb = pl.colorbar(smp, orientation=orientation, cax=cax)
     cb.set_alpha(1)
     cb.ax.tick_params(labelsize=labelsize)
-    cb.draw_all()
     cb.locator = MaxNLocator(nbins=3, integer=True)
     cb.update_ticks()
 

scvelo/settings.py

@@ -4,7 +4,8 @@
 from cycler import cycler
 from packaging.version import parse
 
-from matplotlib import cbook, cm, colors, rcParams
+import matplotlib as mpl
+from matplotlib import cm, colors, rcParams
 
 """Settings
 """
@@ -88,7 +89,7 @@
 # Functions
 # --------------------------------------------------------------------------------
 
-warnings.filterwarnings("ignore", category=cbook.mplDeprecation)
+warnings.filterwarnings("ignore", category=mpl.MatplotlibDeprecationWarning)
 
 
 # default matplotlib 2.0 palette slightly modified.

scvelo/tools/rank_velocity_genes.py

@@ -170,8 +170,8 @@ def velocity_clusters(
         vc = vdata.obs["louvain"]
         vc_cats = vc.cat.categories
         mean_times = [np.mean(vdata.obs[sort_by][vc == cat]) for cat in vc_cats]
-        vdata.obs["louvain"].cat.reorder_categories(
-            vc_cats[np.argsort(mean_times)], inplace=True
+        vdata.obs["louvain"] = vdata.obs["louvain"].cat.reorder_categories(
+            vc_cats[np.argsort(mean_times)]
         )
 
     if isinstance(match_with, str) and match_with in adata.obs.keys():

scvelo/tools/velocity_graph.py

@@ -156,11 +156,15 @@ def __init__(
         self.graph_neg = adata.uns[gkey_] if gkey_ in adata.uns.keys() else []
 
         if tkey in adata.obs.keys():
-            self.t0 = adata.obs[tkey].copy()
+            self.t0 = adata.obs[tkey].astype("category").copy()
             init = min(self.t0) if isinstance(min(self.t0), int) else 0
-            self.t0.cat.categories = np.arange(init, len(self.t0.cat.categories))
+            self.t0 = self.t0.cat.set_categories(
+                np.arange(init, len(self.t0.cat.categories)), rename=True
+            )
             self.t1 = self.t0.copy()
-            self.t1.cat.categories = self.t0.cat.categories + 1
+            self.t1 = self.t1.cat.set_categories(
+                self.t0.cat.categories + 1, rename=True
+            )
         else:
             self.t0 = None
 
@@ -184,6 +188,7 @@ def compute_cosines(self, n_jobs=None, backend="loky"):
             n_jobs=n_jobs,
             unit="cells",
             backend=backend,
+            as_array=False,
         )()
         uncertainties, vals, rows, cols = map(_flatten, zip(*res))
 

tests/conftest.py

@@ -4,6 +4,8 @@
 import pytest
 from hypothesis import settings
 
+import matplotlib as mpl
+
 import scanpy as sc
 from anndata import AnnData
 
@@ -25,6 +27,11 @@
 _pancreas_100obs_preprocessed = sc.read("tests/_data/pancreas_100obs_preprocessed.h5ad")
 
 
+def pytest_sessionstart(session: pytest.Session) -> None:
+    del session
+    mpl.use("Agg")
+
+
 @pytest.fixture
 def dentategyrus_50obs() -> AnnData:
     return _dentategyrus_50obs.copy()