From ca91fc55e11b06313d37a6ce8f00c8b01e36554e Mon Sep 17 00:00:00 2001
From: Mike Gevaert <michael.gevaert@epfl.ch>
Date: Fri, 22 Mar 2024 13:49:52 +0100
Subject: [PATCH] clean up test_mtype_densities_from_probability_map test

---
 atlas_densities/densities/fitting.py |   2 +-
 tests/app/test_mtype_densities.py    | 113 +++++++++++----------------
 2 files changed, 46 insertions(+), 69 deletions(-)

diff --git a/atlas_densities/densities/fitting.py b/atlas_densities/densities/fitting.py
index 6d1c961..25b9b0f 100644
--- a/atlas_densities/densities/fitting.py
+++ b/atlas_densities/densities/fitting.py
@@ -337,7 +337,7 @@ def compute_average_intensities(
             continue
         work.append(_helper(annotation, gene_marker_volumes, id_))
 
-    res = Parallel(n_jobs=-2)(work)
+    res = Parallel()(work)
     densities = (
         pd.DataFrame(list(it.chain(*res)), columns=["marker", "id", "voxel_count", "density"])
         .set_index("id")
diff --git a/tests/app/test_mtype_densities.py b/tests/app/test_mtype_densities.py
index 4927a80..3b43dff 100644
--- a/tests/app/test_mtype_densities.py
+++ b/tests/app/test_mtype_densities.py
@@ -93,78 +93,55 @@ def test_mtype_densities_from_profiles(tmp_path):
         assert "neuron density file" in str(result.exception)
 
 
-def get_result_from_probablity_map_(runner, td):
-    return runner.invoke(
-        tested.app,
-        [
-            "--log-output-path",
-            str(td),
-            "create-from-probability-map",
-            "--annotation-path",
-            "annotation.nrrd",
-            "--hierarchy-path",
-            "hierarchy.json",
-            "--probability-map",
-            "probability_map01.csv",
-            "--probability-map",
-            "probability_map02.csv",
-            "--marker",
-            "pv",
-            "pv.nrrd",
-            "--marker",
-            "sst",
-            "sst.nrrd",
-            "--marker",
-            "vip",
-            "vip.nrrd",
-            "--marker",
-            "gad67",
-            "gad67.nrrd",
-            "--marker",
-            "approx_lamp5",
-            "approx_lamp5.nrrd",
-            "--synapse-class",
-            "EXC",
-            "--output-dir",
-            "output_dir",
-        ],
-    )
-
-
-class Test_mtype_densities_from_probability_map:
-    def setup_method(self, method):
-        self.data = create_from_probability_map_data()
-
-    def save_input_data_to_file(self):
-        self.data["annotation"].save_nrrd("annotation.nrrd")
-        with open("hierarchy.json", "w", encoding="utf-8") as file:
-            json.dump(self.data["hierarchy"], file)
+def test_mtype_densities_from_probability_map(tmp_path):
+    data = create_from_probability_map_data()
+    runner = CliRunner()
+    with runner.isolated_filesystem(temp_dir=tmp_path) as td:
+        td = Path(td)
+        data["annotation"].save_nrrd(td / "annotation.nrrd")
+        with open(td / "hierarchy.json", "w", encoding="utf-8") as file:
+            json.dump(data["hierarchy"], file)
 
-        self.data["probability_map01"].to_csv("probability_map01.csv", index=True)
-        self.data["probability_map02"].to_csv("probability_map02.csv", index=True)
+        data["probability_map01"].to_csv(td / "probability_map01.csv", index=True)
+        data["probability_map02"].to_csv(td / "probability_map02.csv", index=True)
 
-        for molecular_type, data in self.data["molecular_type_densities"].items():
+        for molecular_type, raw in data["molecular_type_densities"].items():
             VoxelData(
-                data,
-                voxel_dimensions=self.data["annotation"].voxel_dimensions,
-            ).save_nrrd(f"{molecular_type}.nrrd")
+                raw,
+                voxel_dimensions=data["annotation"].voxel_dimensions,
+            ).save_nrrd(td / f"{molecular_type}.nrrd")
+
+        result = runner.invoke(
+            tested.app,
+            [
+                # fmt: off
+                    "--log-output-path", str(td),
+                    "create-from-probability-map",
+                    "--annotation-path", "annotation.nrrd",
+                    "--hierarchy-path", "hierarchy.json",
+                    "--probability-map", "probability_map01.csv",
+                    "--probability-map", "probability_map02.csv",
+                    "--marker", "pv", "pv.nrrd",
+                    "--marker", "sst", "sst.nrrd",
+                    "--marker", "vip", "vip.nrrd",
+                    "--marker", "gad67", "gad67.nrrd",
+                    "--marker", "approx_lamp5", "approx_lamp5.nrrd",
+                    "--synapse-class", "EXC",
+                    "--output-dir", "output_dir",
+                # fmt: on
+            ],
+        )
+        assert result.exit_code == 0
 
-    def test_output(self, tmp_path):
-        runner = CliRunner()
-        with runner.isolated_filesystem(temp_dir=tmp_path) as td:
-            self.save_input_data_to_file()
-            result = get_result_from_probablity_map_(runner, td)
-            assert result.exit_code == 0
-
-            BPbAC = VoxelData.load_nrrd(str(Path("output_dir") / "BP|bAC_EXC_densities.nrrd"))
-            assert BPbAC.raw.dtype == float
-            npt.assert_array_equal(BPbAC.voxel_dimensions, self.data["annotation"].voxel_dimensions)
-
-            with open(str(Path("output_dir") / "metadata.json"), "r") as file:
-                metadata = json.load(file)
-            assert "BP" in metadata["density_files"]
-            assert "bAC" in metadata["density_files"]["BP"]
-            assert "EXC" == metadata["synapse_class"]
+        BPbAC = VoxelData.load_nrrd(Path("output_dir") / "BP|bAC_EXC_densities.nrrd")
+        assert BPbAC.raw.dtype == float
+        npt.assert_array_equal(BPbAC.voxel_dimensions, data["annotation"].voxel_dimensions)
+
+        with open(Path("output_dir") / "metadata.json", "r") as file:
+            metadata = json.load(file)
+        assert "BP" in metadata["density_files"]
+        assert "bAC" in metadata["density_files"]["BP"]
+        assert "EXC" == metadata["synapse_class"]
 
 
 class Test_mtype_densities_from_composition: