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Scipy 1.15 compat, some test refactors (#3409)
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@flying-sheep
flying-sheep authored Dec 19, 2024
1 parent e3efba2 commit 1cd5a00
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Showing 4 changed files with 79 additions and 141 deletions.
2 changes: 1 addition & 1 deletion src/scanpy/tools/_rank_genes_groups.py
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Expand Up @@ -854,7 +854,7 @@ def filter_rank_genes_groups(

if not use_logfolds or not use_fraction:
sub_X = adata.raw[:, var_names].X if use_raw else adata[:, var_names].X
in_group = adata.obs[groupby] == cluster
in_group = (adata.obs[groupby] == cluster).to_numpy()
X_in = sub_X[in_group]
X_out = sub_X[~in_group]

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4 changes: 2 additions & 2 deletions tests/test_backed.py
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Original file line number Diff line number Diff line change
Expand Up @@ -91,8 +91,8 @@ def test_log1p_backed_errors(backed_adata):

def test_scatter_backed(backed_adata):
sc.pp.pca(backed_adata, chunked=True)
sc.pl.scatter(backed_adata, color="0", basis="pca")
sc.pl.scatter(backed_adata, color="0", basis="pca", show=False)


def test_dotplot_backed(backed_adata):
sc.pl.dotplot(backed_adata, ["0", "1", "2", "3"], groupby="cat")
sc.pl.dotplot(backed_adata, ["0", "1", "2", "3"], groupby="cat", show=False)
211 changes: 74 additions & 137 deletions tests/test_filter_rank_genes_groups.py
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Original file line number Diff line number Diff line change
@@ -1,159 +1,96 @@
from __future__ import annotations

import numpy as np
import pytest

from scanpy.tools import filter_rank_genes_groups, rank_genes_groups
from testing.scanpy._helpers.data import pbmc68k_reduced

names_no_reference = np.array(
NAMES_NO_REF = [
["CD3D", "ITM2A", "CD3D", "CCL5", "CD7", "nan", "CD79A", "nan", "NKG7", "LYZ"],
["CD3E", "CD3D", "nan", "NKG7", "CD3D", "AIF1", "CD79B", "nan", "GNLY", "CST3"],
["IL32", "RPL39", "nan", "CST7", "nan", "nan", "nan", "SNHG7", "CD7", "nan"],
["nan", "SRSF7", "IL32", "GZMA", "nan", "LST1", "IGJ", "nan", "CTSW", "nan"],
["nan", "nan", "CD2", "CTSW", "CD8B", "TYROBP", "ISG20", "SNHG8", "GZMB", "nan"],
]

NAMES_REF = [
["CD3D", "ITM2A", "CD3D", "nan", "CD3D", "nan", "CD79A", "nan", "CD7"],
["nan", "nan", "nan", "CD3D", "nan", "AIF1", "nan", "nan", "NKG7"],
["nan", "nan", "nan", "NKG7", "nan", "FCGR3A", "ISG20", "SNHG7", "CTSW"],
["nan", "CD3D", "nan", "CCL5", "CD7", "nan", "CD79B", "nan", "GNLY"],
["CD3E", "IL32", "nan", "IL32", "CD27", "FCER1G", "nan", "nan", "nan"],
]

NAMES_NO_REF_COMPARE_ABS = [
[
["CD3D", "ITM2A", "CD3D", "CCL5", "CD7", "nan", "CD79A", "nan", "NKG7", "LYZ"],
["CD3E", "CD3D", "nan", "NKG7", "CD3D", "AIF1", "CD79B", "nan", "GNLY", "CST3"],
["IL32", "RPL39", "nan", "CST7", "nan", "nan", "nan", "SNHG7", "CD7", "nan"],
["nan", "SRSF7", "IL32", "GZMA", "nan", "LST1", "IGJ", "nan", "CTSW", "nan"],
[
"nan",
"nan",
"CD2",
"CTSW",
"CD8B",
"TYROBP",
"ISG20",
"SNHG8",
"GZMB",
"nan",
],
]
)

names_reference = np.array(
*("CD3D", "ITM2A", "HLA-DRB1", "CCL5", "HLA-DPA1"),
*("nan", "CD79A", "nan", "NKG7", "LYZ"),
],
[
["CD3D", "ITM2A", "CD3D", "nan", "CD3D", "nan", "CD79A", "nan", "CD7"],
["nan", "nan", "nan", "CD3D", "nan", "AIF1", "nan", "nan", "NKG7"],
["nan", "nan", "nan", "NKG7", "nan", "FCGR3A", "ISG20", "SNHG7", "CTSW"],
["nan", "CD3D", "nan", "CCL5", "CD7", "nan", "CD79B", "nan", "GNLY"],
["CD3E", "IL32", "nan", "IL32", "CD27", "FCER1G", "nan", "nan", "nan"],
]
)

names_compare_abs = np.array(
*("HLA-DPA1", "nan", "CD3D", "NKG7", "HLA-DRB1"),
*("AIF1", "CD79B", "nan", "GNLY", "CST3"),
],
[
[
"CD3D",
"ITM2A",
"HLA-DRB1",
"CCL5",
"HLA-DPA1",
"nan",
"CD79A",
"nan",
"NKG7",
"LYZ",
],
[
"HLA-DPA1",
"nan",
"CD3D",
"NKG7",
"HLA-DRB1",
"AIF1",
"CD79B",
"nan",
"GNLY",
"CST3",
],
[
"nan",
"PSAP",
"CD74",
"CST7",
"CD74",
"PSAP",
"FCER1G",
"SNHG7",
"CD7",
"HLA-DRA",
],
[
"IL32",
"nan",
"HLA-DRB5",
"GZMA",
"HLA-DRB5",
"LST1",
"nan",
"nan",
"CTSW",
"HLA-DRB1",
],
[
"nan",
"FCER1G",
"HLA-DPB1",
"CTSW",
"HLA-DPB1",
"TYROBP",
"TYROBP",
"S100A10",
"GZMB",
"HLA-DPA1",
],
]
)


def test_filter_rank_genes_groups():
adata = pbmc68k_reduced()

# fix filter defaults
args = {
"adata": adata,
"key_added": "rank_genes_groups_filtered",
"min_in_group_fraction": 0.25,
"min_fold_change": 1,
"max_out_group_fraction": 0.5,
}

rank_genes_groups(
adata, "bulk_labels", reference="Dendritic", method="wilcoxon", n_genes=5
)
filter_rank_genes_groups(**args)

assert np.array_equal(
names_reference,
np.array(adata.uns["rank_genes_groups_filtered"]["names"].tolist()),
)
*("nan", "PSAP", "CD74", "CST7", "CD74"),
*("PSAP", "FCER1G", "SNHG7", "CD7", "HLA-DRA"),
],
[
*("IL32", "nan", "HLA-DRB5", "GZMA", "HLA-DRB5"),
*("LST1", "nan", "nan", "CTSW", "HLA-DRB1"),
],
[
*("nan", "FCER1G", "HLA-DPB1", "CTSW", "HLA-DPB1"),
*("TYROBP", "TYROBP", "S100A10", "GZMB", "HLA-DPA1"),
],
]

rank_genes_groups(adata, "bulk_labels", method="wilcoxon", n_genes=5)
filter_rank_genes_groups(**args)

assert np.array_equal(
names_no_reference,
np.array(adata.uns["rank_genes_groups_filtered"]["names"].tolist()),
)
EXPECTED = {
("Dendritic", False): np.array(NAMES_REF),
("rest", False): np.array(NAMES_NO_REF),
("rest", True): np.array(NAMES_NO_REF_COMPARE_ABS),
}

rank_genes_groups(adata, "bulk_labels", method="wilcoxon", pts=True, n_genes=5)
filter_rank_genes_groups(**args)

assert np.array_equal(
names_no_reference,
np.array(adata.uns["rank_genes_groups_filtered"]["names"].tolist()),
)
@pytest.mark.parametrize(
("reference", "pts", "abs"),
[
pytest.param("Dendritic", False, False, id="ref-no_pts-no_abs"),
pytest.param("rest", False, False, id="rest-no_pts-no_abs"),
pytest.param("rest", True, False, id="rest-pts-no_abs"),
pytest.param("rest", True, True, id="rest-pts-abs"),
],
)
def test_filter_rank_genes_groups(reference, pts, abs):
adata = pbmc68k_reduced()

# test compare_abs
rank_genes_groups(
adata, "bulk_labels", method="wilcoxon", pts=True, rankby_abs=True, n_genes=5
)

filter_rank_genes_groups(
adata,
compare_abs=True,
min_in_group_fraction=-1,
max_out_group_fraction=1,
min_fold_change=3.1,
"bulk_labels",
reference=reference,
pts=pts,
method="wilcoxon",
rankby_abs=abs,
n_genes=5,
)
if abs:
filter_rank_genes_groups(
adata,
compare_abs=True,
min_in_group_fraction=-1,
max_out_group_fraction=1,
min_fold_change=3.1,
)
else:
filter_rank_genes_groups(
adata,
min_in_group_fraction=0.25,
min_fold_change=1,
max_out_group_fraction=0.5,
)

assert np.array_equal(
names_compare_abs,
EXPECTED[reference, abs],
np.array(adata.uns["rank_genes_groups_filtered"]["names"].tolist()),
)
3 changes: 2 additions & 1 deletion tests/test_preprocessing_distributed.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,13 +40,13 @@ def adata() -> AnnData:
return a


@filter_oldformatwarning
@pytest.fixture(
params=[
pytest.param("direct", marks=[needs.zappy]),
pytest.param("dask", marks=[needs.dask, pytest.mark.anndata_dask_support]),
]
)
@filter_oldformatwarning
def adata_dist(request: pytest.FixtureRequest) -> AnnData:
# regular anndata except for X, which we replace on the next line
a = read_zarr(input_file)
Expand Down Expand Up @@ -75,6 +75,7 @@ def test_log1p(adata: AnnData, adata_dist: AnnData):
npt.assert_allclose(result, adata.X)


@pytest.mark.filterwarnings("ignore:Use sc.pp.normalize_total instead:FutureWarning")
def test_normalize_per_cell(
request: pytest.FixtureRequest, adata: AnnData, adata_dist: AnnData
):
Expand Down

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