REF: Allow bvals and bvecs to be separate fixtures

Allow bvals and bvecs to be separate fixtures. The DWI shell selection
test was failing in
https://github.com/nipreps/nifreeze/actions/runs/18065201218/job/51406989162#step:11:2848
with
```
          if not shellmask.sum():
  >           raise RuntimeError(f"Shell corresponding to index {index} (b={bcenter}) is empty.")
  E           RuntimeError: Shell corresponding to index 3 (b=2000.0) is empty.
```

When changing `conftest.py` for other purposes, the above test, which
was affected since the `bvals` generated by the
`setupt_random_gtab_data` fixture did not match the previous version,
and the test's hard-coded expected values no longer matched the existing
ones.

Solve the issue by adding two separate fixtures for bvals an bvecs. For
the above test bvals will have some fixed values (i.e. will not used the
fixture), and the bvecs fixture will provide some random values
depending on the bvals (i.e. the number of created directions depending
on the number of b0s and number of non-zero b-values).

Do not use make the bvec fixture be invoked automatically for all tests
(i.e. do not use `autouse=True`) to avoid the
```
fixture 'bvals' not found
```

error. This way, only tests that explicitly request the bvec fixture
(`setup_random_bvec_data`) and are properly parametrized with `bvals`
will use it.

Refactor the gtab fixture to call the private functions that create
random bval and bvec values.

The issue is related to commit e353bbd.

Author: jhlegarreta

pyproject.toml

@@ -211,6 +211,8 @@ addopts = "-v --doctest-modules"
 doctest_optionflags = "ALLOW_UNICODE NORMALIZE_WHITESPACE ELLIPSIS"
 env = "PYTHONHASHSEED=0"
 markers = [
+  "random_bval_data: Custom marker for random b-val data tests",
+  "random_bvec_data: Custom marker for random b-vec data tests",
   "random_gtab_data: Custom marker for random gtab data tests",
   "random_dwi_data: Custom marker for random dwi data tests",
   "random_pet_data: Custom marker for random pet data tests",

test/conftest.py

@@ -209,9 +209,7 @@ def setup_random_uniform_ndim_data(request):
     return _generate_random_uniform_nd_data(request, size, a, b)
 
 
-def _generate_random_choices(request, values, count):
-    rng = request.node.rng
-
+def _generate_random_choices(rng, values, count):
     values = set(values)
 
     num_elements = len(values)
@@ -235,6 +233,46 @@ def _generate_random_choices(request, values, count):
     return sorted(selected_values)
 
 
+def _generate_random_bvals(rng, b0s, shells, n_gradients):
+    # Generate a random number of elements for each shell
+    bvals_shells = _generate_random_choices(rng, shells, n_gradients)
+
+    bvals = np.hstack([b0s * [0], bvals_shells])
+
+    return bvals
+
+
+def _generate_random_bvecs(rng, b0s, n_gradients):
+    return np.hstack([np.zeros((3, b0s)), normalized_vector(rng.random((3, n_gradients)), axis=0)])
+
+
+@pytest.fixture(autouse=True)
+def setup_random_bval_data(request):
+    """Automatically generate random b-val data for tests."""
+    marker = request.node.get_closest_marker("random_bval_data")
+
+    n_gradients = 10
+    shells = (1000, 2000, 3000)
+    b0s = 1
+    if marker:
+        n_gradients, shells, b0s = marker.args
+
+    rng = request.node.rng
+    return _generate_random_bvals(rng, b0s, shells, n_gradients)
+
+
+@pytest.fixture
+def setup_random_bvec_data(request, bvals, bval_tolerance):
+    """Automatically generate random b-vec data for tests."""
+    rng = request.node.rng
+
+    is_b0 = np.abs(bvals) <= bval_tolerance
+    b0s = np.sum(is_b0)
+    n_gradients = np.sum(~is_b0)
+
+    return _generate_random_bvecs(rng, b0s, n_gradients)
+
+
 @pytest.fixture(autouse=True)
 def setup_random_gtab_data(request):
     """Automatically generate random gtab data for tests."""
@@ -248,13 +286,8 @@ def setup_random_gtab_data(request):
 
     rng = request.node.rng
 
-    # Generate a random number of elements for each shell
-    bvals_shells = _generate_random_choices(request, shells, n_gradients)
-
-    bvals = np.hstack([b0s * [0], bvals_shells])
-    bvecs = np.hstack(
-        [np.zeros((3, b0s)), normalized_vector(rng.random((3, n_gradients)), axis=0)]
-    )
+    bvals = _generate_random_bvals(rng, b0s, shells, n_gradients)
+    bvecs = _generate_random_bvecs(rng, b0s, n_gradients)
 
     return bvals, bvecs
 

test/test_filtering.py

@@ -93,16 +93,23 @@ def test_advanced_clip(
     )
 
 
-@pytest.mark.random_gtab_data(5, (1000, 2000, 3000), 1)
 @pytest.mark.parametrize(
-    "index, expect_exception, expected_output",
+    "bvals, index, expect_exception, expected_output, bval_tolerance",
     [
-        (3, False, np.asarray([False, True, True, False, False, False])),
-        (0, True, np.asarray([])),
+        (
+            np.asarray([0, 1000, 1000, 1000, 2000, 3000]),
+            3,
+            False,
+            np.asarray([False, True, True, False, False, False]),
+            50,
+        ),
+        (np.asarray([0, 1000, 1000, 1000, 2000, 3000]), 0, True, np.asarray([]), 50),
     ],
 )
-def test_dwi_select_shells(setup_random_gtab_data, index, expect_exception, expected_output):
-    bvals, bvecs = setup_random_gtab_data
+def test_dwi_select_shells(
+    setup_random_bvec_data, bvals, index, expect_exception, expected_output, bval_tolerance
+):
+    bvecs = setup_random_bvec_data
 
     gradients = np.vstack([bvecs, bvals[np.newaxis, :]], dtype="float32")