Merge pull request #232 from nipreps/fix/revert-tox

MAINT: Revert addition of tox

.github/workflows/test.yml

@@ -73,12 +73,16 @@ jobs:
           path: /home/runner/eddymotion-tests/
           key: data-v0
 
-      - name: Show tox config
+      - name: Install editable
         shell: micromamba-shell {0}
-        run: tox c
-      - name: Run tox
+        run: |
+          pip install -e .
+
+      - name: Run tests
         shell: micromamba-shell {0}
-        run: tox -v --exit-and-dump-after 1200
+        run: |
+          pytest --doctest-modules --cov eddymotion -n auto -x --cov-report xml \
+                 --junitxml=test-results.xml -v src test
       - uses: codecov/codecov-action@v4
         if: ${{ always() }}
         with:

env.yml

@@ -13,16 +13,25 @@ dependencies:
   - ants=2.5
   - pip
   - pip:
+    - build
+    - coverage
     - datalad
-    - dipy>=1.3.0
+    - dipy >= 1.3.0
+    - hatch
+    - hatchling
     - h5py
     - joblib
-    - tox
-    - tox-gh-actions
-    - coverage
+    - nest-asyncio >= 1.5.1
+    - nipype >= 1.5.1, < 2.0
+    - nireports
+    - nitransforms >= 21, < 24
+    - numpy >= 1.17.3
     - pytest
     - pytest-cov
     - pytest-env
     - pytest-xdist
+    - scikit_learn >= 0.18
+    - scikit-image >= 0.14.2
+    - scipy >= 1.8.0
 variables:
   FSLOUTPUTTYPE: NIFTI_GZ

test/test_integration.py

@@ -22,18 +22,16 @@
 #
 """Integration tests."""
 
-import os
+from os import cpu_count
 
 import nibabel as nb
 import nitransforms as nt
 import numpy as np
-import pytest
 
 from eddymotion.data.dmri import DWI
 from eddymotion.estimator import EddyMotionEstimator
 
 
-@pytest.mark.skipif(os.getenv("GITHUB_ACTIONS", "false") == "true", reason="Skip GHA")
 def test_proximity_estimator_trivial_model(datadir):
     """Check the proximity of transforms estimated by the estimator with a trivial B0 model."""
 
@@ -78,6 +76,7 @@ def test_proximity_estimator_trivial_model(datadir):
         align_kwargs={
             "fixed_modality": "dwi",
             "moving_modality": "b0",
+            "num_threads": min(cpu_count(), 8),
         },
     )