Auto-metric and fix logs (scverse#3186)

src/scanpy/preprocessing/_pca.py

@@ -338,10 +338,10 @@ def pca(
         logg.info("    finished", time=logg_start)
         logg.debug(
             "and added\n"
-            "    'X_pca', the PCA coordinates (adata.obs)\n"
-            "    'PC1', 'PC2', ..., the loadings (adata.var)\n"
-            "    'pca_variance', the variance / eigenvalues (adata.uns)\n"
-            "    'pca_variance_ratio', the variance ratio (adata.uns)"
+            f"    {key_obsm!r}, the PCA coordinates (adata.obs)\n"
+            f"    {key_varm!r}, the loadings (adata.varm)\n"
+            f"    'pca_variance', the variance / eigenvalues (adata.uns[{key_uns!r}])\n"
+            f"    'pca_variance_ratio', the variance ratio (adata.uns[{key_uns!r}])"
         )
         return adata if copy else None
     else:

src/scanpy/tools/_tsne.py

@@ -180,7 +180,11 @@ def tsne(
     logg.info(
         "    finished",
         time=start,
-        deep="added\n    'X_tsne', tSNE coordinates (adata.obsm)",
+        deep=(
+            f"added\n"
+            f"    {key_obsm!r}, tSNE coordinates (adata.obsm)\n"
+            f"    {key_uns!r}, tSNE parameters (adata.uns)"
+        ),
     )
 
     return adata if copy else None

src/scanpy/tools/_umap.py

@@ -263,6 +263,10 @@ def umap(
     logg.info(
         "    finished",
         time=start,
-        deep=("added\n" "    'X_umap', UMAP coordinates (adata.obsm)"),
+        deep=(
+            "added\n"
+            f"    {key_obsm!r}, UMAP coordinates (adata.obsm)\n"
+            f"    {key_uns!r}, UMAP parameters (adata.uns)"
+        ),
     )
     return adata if copy else None

tests/test_aggregated.py

@@ -1,5 +1,7 @@
 from __future__ import annotations
 
+from typing import get_args
+
 import anndata as ad
 import numpy as np
 import pandas as pd
@@ -9,11 +11,17 @@
 
 import scanpy as sc
 from scanpy._utils import _resolve_axis
+from scanpy.get._aggregated import AggType
 from testing.scanpy._helpers import assert_equal
 from testing.scanpy._helpers.data import pbmc3k_processed
 from testing.scanpy._pytest.params import ARRAY_TYPES_MEM
 
 
+@pytest.fixture(params=get_args(AggType))
+def metric(request: pytest.FixtureRequest) -> AggType:
+    return request.param
+
+
 @pytest.fixture
 def df_base():
     ax_base = ["A", "B"]
@@ -88,7 +96,6 @@ def test_mask(axis):
 
 
 @pytest.mark.parametrize("array_type", ARRAY_TYPES_MEM)
-@pytest.mark.parametrize("metric", ["sum", "mean", "var", "count_nonzero"])
 def test_aggregate_vs_pandas(metric, array_type):
     adata = pbmc3k_processed().raw.to_adata()
     adata = adata[
@@ -135,7 +142,6 @@ def test_aggregate_vs_pandas(metric, array_type):
 
 
 @pytest.mark.parametrize("array_type", ARRAY_TYPES_MEM)
-@pytest.mark.parametrize("metric", ["sum", "mean", "var", "count_nonzero"])
 def test_aggregate_axis(array_type, metric):
     adata = pbmc3k_processed().raw.to_adata()
     adata = adata[
@@ -222,7 +228,8 @@ def test_aggregate_axis_specification(axis_name):
                 {
                     "a": ["a", "a", "b", "b"],
                     "b": ["c", "d", "d", "d"],
-                }
+                },
+                index=["a_c", "a_d", "b_d1", "b_d2"],
             ),
             ["a", "b"],
             ["count_nonzero"],  # , "sum", "mean"],
@@ -253,7 +260,8 @@ def test_aggregate_axis_specification(axis_name):
                 {
                     "a": ["a", "a", "b", "b"],
                     "b": ["c", "d", "d", "d"],
-                }
+                },
+                index=["a_c", "a_d", "b_d1", "b_d2"],
             ),
             ["a", "b"],
             ["sum", "mean", "count_nonzero"],
@@ -284,7 +292,8 @@ def test_aggregate_axis_specification(axis_name):
                 {
                     "a": ["a", "a", "b", "b"],
                     "b": ["c", "d", "d", "d"],
-                }
+                },
+                index=["a_c", "a_d", "b_d1", "b_d2"],
             ),
             ["a", "b"],
             ["mean"],
@@ -381,7 +390,6 @@ def test_combine_categories(label_cols, cols, expected):
 
 
 @pytest.mark.parametrize("array_type", ARRAY_TYPES_MEM)
-@pytest.mark.parametrize("metric", ["sum", "mean", "var", "count_nonzero"])
 def test_aggregate_arraytype(array_type, metric):
     adata = pbmc3k_processed().raw.to_adata()
     adata = adata[