[eigen] Test overloads for dense vs. sparse

.github/workflows/ci.yml

@@ -480,7 +480,8 @@ jobs:
     - uses: actions/checkout@v3
 
     - name: Add Python 3
-      run: apt-get update; apt-get install -y python3-dev python3-numpy python3-pytest python3-pip libeigen3-dev
+      # NOTE(drake): We explicitly test scipy here.
+      run: apt-get update; apt-get install -y python3-dev python3-numpy python3-pytest python3-pip libeigen3-dev python3-scipy
 
     - name: Update pip
       run: python3 -m pip install --upgrade pip

tests/test_eigen_matrix.cpp

@@ -32,6 +32,12 @@ typedef Eigen::Matrix<ADScalar, 5, 1> Vector5ADScalar;
 typedef Eigen::Matrix<ADScalar, 1, 6> Vector6ADScalarR;
 PYBIND11_NUMPY_OBJECT_DTYPE(ADScalar);
 
+struct MyScalar {
+  int value{};
+};
+PYBIND11_NUMPY_OBJECT_DTYPE(MyScalar);
+using VectorXMyScalar = Eigen::Matrix<MyScalar, Eigen::Dynamic, 1>;
+
 // Sets/resets a testing reference matrix to have values of 10*r + c, where r and c are the
 // (1-based) row/column number.
 template <typename M>
@@ -516,4 +522,34 @@ TEST_SUBMODULE(eigen_matrix, m) {
         py::module_::import("numpy").attr("ones")(10);
         return v[0](5);
     });
+
+    // test_eigen_dense_sparse_overload
+    // https://github.com/RobotLocomotion/drake/issues/20516
+    // Certain argument combinations seem to make overloads go sideways.
+    py::class_<MyScalar>(m, "MyScalar")
+      .def(py::init<int>(), py::arg("value"))
+      .def_readwrite("value", &MyScalar::value);
+
+    m.def(
+        "accept_matrix",
+        [](const Eigen::MatrixXd&) { return "dense"; });
+    m.def(
+        "accept_matrix",
+        [](const Eigen::SparseMatrix<double>&) { return "sparse"; });
+    m.def(
+        "accept_matrix_and_dtype_object",
+        [](const Eigen::MatrixXd&, const VectorXADScalar&) { return "dense"; });
+    m.def(
+        "accept_matrix_and_dtype_object",
+        [](const Eigen::SparseMatrix<double>&, const VectorXADScalar&) {
+          return "sparse";
+        });
+    m.def(
+        "accept_matrix_and_dtype_object",
+        [](const Eigen::MatrixXd&, const VectorXMyScalar&) { return "dense"; });
+    m.def(
+        "accept_matrix_and_dtype_object",
+        [](const Eigen::SparseMatrix<double>&, const VectorXMyScalar&) {
+          return "sparse";
+        });
 }

tests/test_eigen_matrix.py

@@ -903,3 +903,25 @@ def test_custom_operator_new():
     o = m.CustomOperatorNew()
     np.testing.assert_allclose(o.a, 0.0)
     np.testing.assert_allclose(o.b.diagonal(), 1.0)
+
+
+def test_eigen_dense_sparse_overload():
+    """Overloads that should prefer dense vs. sparse should work as
+    expected, even when combining with arguments like dtype=object."""
+
+    pytest.importorskip("scipy")
+    import scipy.sparse
+
+    A_dense = np.eye(2)
+    A_sparse = scipy.sparse.csc_matrix(np.eye(2))
+
+    assert m.accept_matrix(A_dense) == "dense"
+    assert m.accept_matrix(A_sparse) == "sparse"
+
+    x_ad = float_to_adscalar(np.ones(2), deriv=[1.0])
+    assert m.accept_matrix_and_dtype_object(A_dense, x_ad) == "dense"
+    assert m.accept_matrix_and_dtype_object(A_sparse, x_ad) == "sparse"
+
+    x_myscalar = np.array([m.MyScalar(1), m.MyScalar(2)])
+    assert m.accept_matrix_and_dtype_object(A_dense, x_myscalar) == "dense"
+    assert m.accept_matrix_and_dtype_object(A_sparse, x_myscalar) == "sparse"