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).
This commit is contained in:
Jason Rhinelander 2017-04-08 19:26:42 -04:00
parent 501135fa76
commit e9e17746c8
3 changed files with 49 additions and 18 deletions

View File

@ -179,20 +179,21 @@ template <typename Type_> struct EigenProps {
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 @@ public:
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; }

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@ -287,6 +287,13 @@ test_initializer eigen([](py::module &m) {
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)

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@ -75,15 +75,15 @@ def test_mutator_descriptors():
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_dense_signature(doc):
"""
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