[MNT] Add Python 3.11 and 3.12 support

.github/workflows/tests.yml

@@ -38,7 +38,7 @@ jobs:
     strategy:
       matrix:
         os: ['ubuntu-latest']
-        python-version: ['3.8', '3.9', '3.10']
+        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
     steps:
       - name: Checkout code
         uses: actions/checkout@v4

neuromaps/images.py

@@ -132,7 +132,7 @@ def load_nifti(img):
     try:
         img = nib.load(img)
     except (TypeError) as err:
-        if not ("os.PathLike" in str(err) and "not Nifti1Image" in str(err)):
+        if not ("os.PathLike" in str(err) and "Nifti1Image" in str(err)):
             raise err
     return img
 
@@ -164,7 +164,7 @@ def load_gifti(img):
         # it's not a pre-loaded GiftiImage so error out
         elif (isinstance(err, TypeError)
               and not (
-                  "os.PathLike" in str(err) and "not GiftiImage" in str(err)
+                  "os.PathLike" in str(err) and "GiftiImage" in str(err)
                   )
               ):
             raise err
@@ -213,7 +213,7 @@ def load_data(data):
         if (isinstance(err, AttributeError)
             or (
                 "os.PathLike" in str(err)
-                and "not Nifti1Image" in str(err)
+                and "Nifti1Image" in str(err)
                 )
            ):
             out = np.stack([load_nifti(img).get_fdata() for img in data],

neuromaps/stats.py

@@ -271,7 +271,7 @@ def efficient_pearsonr(a, b, ddof=1, nan_policy='propagate', return_pval=True):
     if return_pval:
         # taken from scipy.stats
         ab = (n_obs / 2) - 1
-        prob = 2 * special.btdtr(ab, ab, 0.5 * (1 - np.abs(corr)))
+        prob = 2 * special.betainc(ab, ab, 0.5 * (1 - np.abs(corr)))
 
         return corr, prob
 

neuromaps/tests/conftest.py

@@ -6,6 +6,13 @@
 import pytest
 
 
+def pytest_configure(config):
+    """Add markers for tests."""
+    config.addinivalue_line(
+        "markers", "workbench: mark test to run with Connectome Workbench"
+    )
+
+
 def pytest_runtest_setup(item):
     """Skip tests that require workbench if it's not installed."""
     markers = set(mark.name for mark in item.iter_markers())

neuromaps/tests/test_images.py

@@ -30,16 +30,69 @@ def test_fix_coordsys():
     assert False
 
 
-@pytest.mark.xfail
-def test_load_nifti():
+@pytest.fixture(scope="session")
+def dummy_img(request, tmp_path_factory):
+    """Return a valid image file."""
+    file_type = request.param["file_type"]
+    return_type = request.param["return_type"]
+
+    rng = np.random.default_rng()
+
+    # create a valid image file
+    if file_type == "nifti":
+        data = rng.random((10, 10, 10))
+        curr_img = nib.Nifti1Image(data, affine=np.eye(4))
+        curr_path = tmp_path_factory.mktemp("nifti") \
+            / "valid_nifti_file.nii.gz"
+        nib.save(curr_img, str(curr_path))
+    elif file_type == "gifti":
+        data = rng.random((10, 10), dtype=np.float32)
+        curr_img = nib.gifti.GiftiImage()
+        gifti_data_array = nib.gifti.GiftiDataArray(data)
+        curr_img.add_gifti_data_array(gifti_data_array)
+        curr_path = tmp_path_factory.mktemp("gifti") \
+            / "valid_gifti_file.gii"
+        nib.save(curr_img, str(curr_path))
+    else:
+        raise ValueError(f"Invalid file type: {file_type}")
+
+    # return the appropriate file type
+    if return_type == "str":
+        return str(curr_path)
+    elif return_type == "path":
+        return curr_path
+    elif return_type == "object":
+        return curr_img
+    else:
+        raise ValueError(f"Invalid return type: {return_type}")
+
+
+@pytest.mark.parametrize(
+    "dummy_img", [
+        pytest.param(
+            {"file_type": "nifti", "return_type": _},
+            id=_
+        ) for _ in ["str", "path", "object"]
+    ], indirect=True
+)
+def test_load_nifti(dummy_img):
     """Test loading a NIfTI image."""
-    assert False
-
-
-@pytest.mark.xfail
-def test_load_gifti():
+    res = images.load_nifti(dummy_img)
+    assert isinstance(res, nib.Nifti1Image)
+
+
+@pytest.mark.parametrize(
+    "dummy_img", [
+        pytest.param(
+            {"file_type": "gifti", "return_type": _},
+            id=_
+        ) for _ in ["str", "path", "object"]
+    ], indirect=True
+)
+def test_load_gifti(dummy_img):
     """Test loading a GIFTI image."""
-    assert False
+    res = images.load_gifti(dummy_img)
+    assert isinstance(res, nib.gifti.GiftiImage)
 
 
 @pytest.mark.xfail