Fix Eigen argument doc strings
Many of the Eigen type casters' name() methods weren't wrapping the type
description in a `type_descr` object, which thus wasn't adding the
"{...}" annotation used to identify an argument which broke the help
output by skipping eigen arguments.
The test code I had added even had some (unnoticed) broken output (with
the "arg0: " showing up in the return value).
This commit also adds test code to ensure that named eigen arguments
actually work properly, despite the invalid help output. (The added
tests pass without the rest of this commit).
diff --git a/include/pybind11/eigen.h b/include/pybind11/eigen.h
index 6abe8c4..69194a2 100644
--- a/include/pybind11/eigen.h
+++ b/include/pybind11/eigen.h
@@ -179,20 +179,21 @@
constexpr bool show_c_contiguous = show_order && requires_row_major;
constexpr bool show_f_contiguous = !show_c_contiguous && show_order && requires_col_major;
- return _("numpy.ndarray[") + npy_format_descriptor<Scalar>::name() +
- _("[") + _<fixed_rows>(_<(size_t) rows>(), _("m")) +
- _(", ") + _<fixed_cols>(_<(size_t) cols>(), _("n")) +
- _("]") +
- // For a reference type (e.g. Ref<MatrixXd>) we have other constraints that might need to be
- // satisfied: writeable=True (for a mutable reference), and, depending on the map's stride
- // options, possibly f_contiguous or c_contiguous. We include them in the descriptor output
- // to provide some hint as to why a TypeError is occurring (otherwise it can be confusing to
- // see that a function accepts a 'numpy.ndarray[float64[3,2]]' and an error message that you
- // *gave* a numpy.ndarray of the right type and dimensions.
- _<show_writeable>(", flags.writeable", "") +
- _<show_c_contiguous>(", flags.c_contiguous", "") +
- _<show_f_contiguous>(", flags.f_contiguous", "") +
- _("]");
+ return type_descr(_("numpy.ndarray[") + npy_format_descriptor<Scalar>::name() +
+ _("[") + _<fixed_rows>(_<(size_t) rows>(), _("m")) +
+ _(", ") + _<fixed_cols>(_<(size_t) cols>(), _("n")) +
+ _("]") +
+ // For a reference type (e.g. Ref<MatrixXd>) we have other constraints that might need to be
+ // satisfied: writeable=True (for a mutable reference), and, depending on the map's stride
+ // options, possibly f_contiguous or c_contiguous. We include them in the descriptor output
+ // to provide some hint as to why a TypeError is occurring (otherwise it can be confusing to
+ // see that a function accepts a 'numpy.ndarray[float64[3,2]]' and an error message that you
+ // *gave* a numpy.ndarray of the right type and dimensions.
+ _<show_writeable>(", flags.writeable", "") +
+ _<show_c_contiguous>(", flags.c_contiguous", "") +
+ _<show_f_contiguous>(", flags.f_contiguous", "") +
+ _("]")
+ );
}
};
@@ -318,7 +319,7 @@
return cast_impl(src, policy, parent);
}
- static PYBIND11_DESCR name() { return type_descr(props::descriptor()); }
+ static PYBIND11_DESCR name() { return props::descriptor(); }
operator Type*() { return &value; }
operator Type&() { return value; }
diff --git a/tests/test_eigen.cpp b/tests/test_eigen.cpp
index f2ec8fd..52358ab 100644
--- a/tests/test_eigen.cpp
+++ b/tests/test_eigen.cpp
@@ -287,6 +287,13 @@
m.def("iss738_f1", &adjust_matrix<const Eigen::Ref<const Eigen::MatrixXd> &>, py::arg().noconvert());
m.def("iss738_f2", &adjust_matrix<const Eigen::Ref<const Eigen::Matrix<double, -1, -1, Eigen::RowMajor>> &>, py::arg().noconvert());
+ // Make sure named arguments are working properly:
+ m.def("matrix_multiply", [](const py::EigenDRef<const Eigen::MatrixXd> A, const py::EigenDRef<const Eigen::MatrixXd> B)
+ -> Eigen::MatrixXd {
+ if (A.cols() != B.rows()) throw std::domain_error("Nonconformable matrices!");
+ return A * B;
+ }, py::arg("A"), py::arg("B"));
+
py::class_<CustomOperatorNew>(m, "CustomOperatorNew")
.def(py::init<>())
.def_readonly("a", &CustomOperatorNew::a)
diff --git a/tests/test_eigen.py b/tests/test_eigen.py
index df08edf..ffa678b 100644
--- a/tests/test_eigen.py
+++ b/tests/test_eigen.py
@@ -75,15 +75,15 @@
fixed_mutator_a(zc)
with pytest.raises(TypeError) as excinfo:
fixed_mutator_r(zc)
- assert ('(numpy.ndarray[float32[5, 6], flags.writeable, flags.c_contiguous]) -> arg0: None'
+ assert ('(arg0: numpy.ndarray[float32[5, 6], flags.writeable, flags.c_contiguous]) -> None'
in str(excinfo.value))
with pytest.raises(TypeError) as excinfo:
fixed_mutator_c(zr)
- assert ('(numpy.ndarray[float32[5, 6], flags.writeable, flags.f_contiguous]) -> arg0: None'
+ assert ('(arg0: numpy.ndarray[float32[5, 6], flags.writeable, flags.f_contiguous]) -> None'
in str(excinfo.value))
with pytest.raises(TypeError) as excinfo:
fixed_mutator_a(np.array([[1, 2], [3, 4]], dtype='float32'))
- assert ('(numpy.ndarray[float32[5, 6], flags.writeable]) -> arg0: None'
+ assert ('(arg0: numpy.ndarray[float32[5, 6], flags.writeable]) -> None'
in str(excinfo.value))
zr.flags.writeable = False
with pytest.raises(TypeError):
@@ -582,6 +582,29 @@
"""
+def test_named_arguments():
+ from pybind11_tests import matrix_multiply
+
+ a = np.array([[1.0, 2], [3, 4], [5, 6]])
+ b = np.ones((2, 1))
+
+ assert np.all(matrix_multiply(a, b) == np.array([[3.], [7], [11]]))
+ assert np.all(matrix_multiply(A=a, B=b) == np.array([[3.], [7], [11]]))
+ assert np.all(matrix_multiply(B=b, A=a) == np.array([[3.], [7], [11]]))
+
+ with pytest.raises(ValueError) as excinfo:
+ matrix_multiply(b, a)
+ assert str(excinfo.value) == 'Nonconformable matrices!'
+
+ with pytest.raises(ValueError) as excinfo:
+ matrix_multiply(A=b, B=a)
+ assert str(excinfo.value) == 'Nonconformable matrices!'
+
+ with pytest.raises(ValueError) as excinfo:
+ matrix_multiply(B=a, A=b)
+ assert str(excinfo.value) == 'Nonconformable matrices!'
+
+
@pytest.requires_eigen_and_scipy
def test_sparse():
from pybind11_tests import sparse_r, sparse_c, sparse_copy_r, sparse_copy_c