more tests

brainlit/BrainLine/apply_ilastik.py

@@ -36,7 +36,7 @@ class ApplyIlastik:
     Attributes:
         ilastk_path (str): Path to ilastik executable.
         project_path (str): Path to ilastik project.
-        brains_path (str): Path to directory that contains brain samples subdirectories.
+        brains_path (Path): Path to directory that contains brain samples subdirectories.
         brains (list): List of brain sample names.
 
     """
@@ -46,7 +46,7 @@ def __init__(
     ):
         self.ilastik_path = ilastik_path
         self.project_path = project_path
-        self.brains_path = brains_path
+        self.brains_path = Path(brains_path)
         self.brains = brains
 
     def _apply_ilastik(self, fnames):
@@ -76,7 +76,7 @@ def process_subvols(self, dset: str = "val", ncpu: int = 6):
                 brain_name = "r2"
             else:
                 brain_name = brain
-            path = f"{self.brains_path}brain{brain_name}/{dset}/"
+            path = self.brains_path / f"brain{brain_name}" / dset
 
             items_total += _find_sample_names(path, dset="", add_dir=True)
             print(f"Applying ilastik to {items_total}")
@@ -102,17 +102,18 @@ def move_results(self):
             # else:
             #     brain_name = brain
 
-            brain_dir = f"{self.brains_path}brain{brain}/val/"
-            results_dir = brain_dir + "results" + str(date.today()) + "/"
+            brain_dir = self.brains_path / f"brain{brain}" / "val"
+            results_dir = brain_dir / f"results{date.today()}"
 
             if not os.path.exists(results_dir):
                 print(f"Creating directory: {results_dir}")
                 os.makedirs(results_dir)
 
             items = _find_sample_names(brain_dir, dset="", add_dir=False)
             for item in items:
-                result_path = brain_dir + item[:-3] + "_Probabilities.h5"
-                shutil.move(result_path, results_dir + item[:-3] + "_Probabilities.h5")
+                prob_fname = f"{item[:-3]}_Probabilities.h5"
+                result_path = brain_dir / prob_fname
+                shutil.move(result_path, results_dir / prob_fname)
 
 
 def plot_results(

brainlit/BrainLine/tests/test_apply_ilastik.py

@@ -10,6 +10,7 @@
 import pytest
 import matplotlib.pyplot as plt
 from pathlib import Path
+from datetime import date
 
 
 def test_ApplyIlastik():
@@ -46,19 +47,9 @@ def axon_data_dir(tmp_path_factory):
     return data_dir
 
 
-def test_move_results(axon_data_dir):
-    data_dir_str = str(axon_data_dir)
-    apl = ApplyIlastik(
-        ilastik_path="test",
-        project_path="test",
-        brains_path=data_dir_str,
-        brains=["test"],
-    )
-    apl.move_results()
-
-
 def test_plot_results_axon(axon_data_dir):
     data_dir_str = str(axon_data_dir)
+
     test_max_fscore, test_best_threshold = plot_results(
         data_dir=data_dir_str,
         brain_ids=["test"],
@@ -158,3 +149,19 @@ def test_ApplyIlastik_LargeImage():
         ilastik_path="", ilastik_project="", ncpu=1, data_file=data_file
     )
     # Sample data is there but file path in data json is specific to thomastathey
+
+
+def test_move_results(axon_data_dir):
+    data_dir_str = str(axon_data_dir)
+
+    apl = ApplyIlastik(
+        ilastik_path="test",
+        project_path="test",
+        brains_path=data_dir_str,
+        brains=["test"],
+    )
+
+    apl.move_results()
+
+    newdir = apl.brains_path / f"braintest/val/results{date.today()}"
+    assert len(os.listdir(newdir)) == 1

brainlit/BrainLine/tests/test_util.py

@@ -5,6 +5,8 @@
 from cloudvolume import CloudVolume
 from pathlib import Path
 import os
+import json
+from skimage import io
 
 
 @pytest.fixture(scope="session")
@@ -193,3 +195,24 @@ def test_fold():
     test_fold = util._fold(img)
 
     assert_array_equal(true_fold, test_fold)
+
+
+def test_dir_to_atlas_pts(tmp_path):
+    json_dir = tmp_path / "json_data"
+    json_dir.mkdir()
+
+    json_data = [{"point": [-1, 0, 0]}, {"point": [1, 1, 1]}, {"point": [2, 1, 1]}]
+    with open(json_dir / "json1.json", "w") as f:
+        json.dump(json_data, f)
+
+    json_data = [{"point": [0, 0, 0]}, {"point": [1, 2, 1]}]
+    with open(json_dir / "json2.json", "w") as f:
+        json.dump(json_data, f)
+
+    atlas_file = tmp_path / "atlas.tif"
+    atlas_im = np.zeros((3, 3, 3), dtype="uint16")
+    atlas_im[1:, 1:, 1:] = 1
+    io.imsave(atlas_file, atlas_im)
+
+    outname = tmp_path / "filtered.txt"
+    util.dir_to_atlas_pts(dir=json_dir, outname=outname, atlas_file=atlas_file)