refactor(aggregation): Rename simplex projection helper

src/torchjd/aggregation/_modo.py

@@ -11,7 +11,7 @@
 from torchjd.aggregation._mixins import _NonDifferentiable
 from torchjd.linalg import Matrix
 
-from ._utils.simplex import _projection2simplex
+from ._utils.simplex import project_onto_simplex
 from ._weighting_bases import _MatrixWeighting
 
 
@@ -167,7 +167,7 @@ def forward(self, matrix: Matrix, /) -> Tensor:
         lambd = cast(Tensor, self._lambda)
 
         grad = matrix @ lambd + self._rho * lambd
-        lambd = _projection2simplex(lambd - self._gamma * grad)
+        lambd = project_onto_simplex(lambd - self._gamma * grad)
 
         self._lambda = lambd
         return lambd

src/torchjd/aggregation/_sdmgrad.py

@@ -11,7 +11,7 @@
 from torchjd.aggregation._mixins import _NonDifferentiable
 from torchjd.linalg import Matrix
 
-from ._utils.simplex import _projection2simplex
+from ._utils.simplex import project_onto_simplex
 from ._weighting_bases import _MatrixWeighting
 
 
@@ -185,7 +185,7 @@ def forward(self, matrix: Matrix, /) -> Tensor:
         for _ in range(self._n_iter):
             grad = a @ (w + self._lambda * w_tilde)
             velocity = grad if velocity is None else self._momentum * velocity + grad
-            w = _projection2simplex(w - self._lr * velocity)
+            w = project_onto_simplex(w - self._lr * velocity)
 
         self._w = w
         return (w + self._lambda * w_tilde) / (1.0 + self._lambda)

src/torchjd/aggregation/_utils/simplex.py

@@ -2,7 +2,7 @@
 from torch import Tensor
 
 
-def _projection2simplex(y: Tensor) -> Tensor:
+def project_onto_simplex(y: Tensor) -> Tensor:
     """Euclidean projection of ``y`` onto the probability simplex."""
 
     m = len(y)

tests/unit/aggregation/_utils/test_simplex.py

@@ -1,19 +1,19 @@
 from torch.testing import assert_close
 from utils.tensors import tensor_
 
-from torchjd.aggregation._utils.simplex import _projection2simplex
+from torchjd.aggregation._utils.simplex import project_onto_simplex
 
 
-def test_projection2simplex_known_values() -> None:
+def test_project_onto_simplex_known_values() -> None:
     """The simplex projection matches hand-computed Euclidean projections."""
 
     # Already-positive input: the deficit (1 - sum) is spread equally, no clamping.
     assert_close(
-        _projection2simplex(tensor_([0.5, 0.1, 0.1])),
+        project_onto_simplex(tensor_([0.5, 0.1, 0.1])),
         tensor_([0.6, 0.2, 0.2]),
     )
     # Input with a negative entry: it gets clamped to zero.
     assert_close(
-        _projection2simplex(tensor_([1.0, 0.0, -0.5])),
+        project_onto_simplex(tensor_([1.0, 0.0, -0.5])),
         tensor_([1.0, 0.0, 0.0]),
     )