mirror of https://github.com/pybind/pybind11.git
Merge 6e5df0f99b
into 1f8b4a7f1a
This commit is contained in:
commit
9083ee1712
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@ -225,16 +225,17 @@ struct EigenProps {
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= !show_c_contiguous && show_order && requires_col_major;
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static constexpr auto descriptor
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= const_name("numpy.ndarray[") + npy_format_descriptor<Scalar>::name + const_name("[")
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+ const_name<fixed_rows>(const_name<(size_t) rows>(), const_name("m")) + const_name(", ")
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+ const_name<fixed_cols>(const_name<(size_t) cols>(), const_name("n")) + const_name("]")
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+
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= const_name("numpy.typing.NDArray[") + npy_format_descriptor<Scalar>::name
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+ const_name("[") + const_name<fixed_rows>(const_name<(size_t) rows>(), const_name("m"))
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+ const_name(", ") + const_name<fixed_cols>(const_name<(size_t) cols>(), const_name("n"))
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+ const_name("]") +
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// For a reference type (e.g. Ref<MatrixXd>) we have other constraints that might need to
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// be satisfied: writeable=True (for a mutable reference), and, depending on the map's
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// stride options, possibly f_contiguous or c_contiguous. We include them in the
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// descriptor output to provide some hint as to why a TypeError is occurring (otherwise
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// it can be confusing to see that a function accepts a 'numpy.ndarray[float64[3,2]]' and
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// an error message that you *gave* a numpy.ndarray of the right type and dimensions.
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// it can be confusing to see that a function accepts a
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// 'numpy.typing.NDArray[float64[3,2]]' and an error message that you *gave* a
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// numpy.ndarray of the right type and dimensions.
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const_name<show_writeable>(", flags.writeable", "")
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+ const_name<show_c_contiguous>(", flags.c_contiguous", "")
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+ const_name<show_f_contiguous>(", flags.f_contiguous", "") + const_name("]");
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@ -128,7 +128,7 @@ struct get_tensor_descriptor {
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+ const_name<static_cast<int>(Type::Layout) == static_cast<int>(Eigen::RowMajor)>(
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", flags.c_contiguous", ", flags.f_contiguous");
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static constexpr auto value
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= const_name("numpy.ndarray[") + npy_format_descriptor<typename Type::Scalar>::name
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= const_name("numpy.typing.NDArray[") + npy_format_descriptor<typename Type::Scalar>::name
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+ const_name("[") + eigen_tensor_helper<remove_cv_t<Type>>::dimensions_descriptor
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+ const_name("]") + const_name<ShowDetails>(details, const_name("")) + const_name("]");
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};
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@ -2090,7 +2090,7 @@ vectorize_helper<Func, Return, Args...> vectorize_extractor(const Func &f, Retur
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template <typename T, int Flags>
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struct handle_type_name<array_t<T, Flags>> {
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static constexpr auto name
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= const_name("numpy.ndarray[") + npy_format_descriptor<T>::name + const_name("]");
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= const_name("numpy.typing.NDArray[") + npy_format_descriptor<T>::name + const_name("]");
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};
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PYBIND11_NAMESPACE_END(detail)
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@ -94,19 +94,20 @@ def test_mutator_descriptors():
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with pytest.raises(TypeError) as excinfo:
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m.fixed_mutator_r(zc)
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assert (
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"(arg0: numpy.ndarray[numpy.float32[5, 6],"
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"(arg0: numpy.typing.NDArray[numpy.float32[5, 6],"
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" flags.writeable, flags.c_contiguous]) -> None" in str(excinfo.value)
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)
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with pytest.raises(TypeError) as excinfo:
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m.fixed_mutator_c(zr)
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assert (
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"(arg0: numpy.ndarray[numpy.float32[5, 6],"
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"(arg0: numpy.typing.NDArray[numpy.float32[5, 6],"
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" flags.writeable, flags.f_contiguous]) -> None" in str(excinfo.value)
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)
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with pytest.raises(TypeError) as excinfo:
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m.fixed_mutator_a(np.array([[1, 2], [3, 4]], dtype="float32"))
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assert "(arg0: numpy.ndarray[numpy.float32[5, 6], flags.writeable]) -> None" in str(
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excinfo.value
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assert (
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"(arg0: numpy.typing.NDArray[numpy.float32[5, 6], flags.writeable]) -> None"
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in str(excinfo.value)
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)
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zr.flags.writeable = False
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with pytest.raises(TypeError):
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@ -200,7 +201,7 @@ def test_negative_stride_from_python(msg):
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msg(excinfo.value)
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== """
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double_threer(): incompatible function arguments. The following argument types are supported:
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1. (arg0: numpy.ndarray[numpy.float32[1, 3], flags.writeable]) -> None
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1. (arg0: numpy.typing.NDArray[numpy.float32[1, 3], flags.writeable]) -> None
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Invoked with: """
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+ repr(np.array([5.0, 4.0, 3.0], dtype="float32"))
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@ -212,7 +213,7 @@ def test_negative_stride_from_python(msg):
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msg(excinfo.value)
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== """
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double_threec(): incompatible function arguments. The following argument types are supported:
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1. (arg0: numpy.ndarray[numpy.float32[3, 1], flags.writeable]) -> None
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1. (arg0: numpy.typing.NDArray[numpy.float32[3, 1], flags.writeable]) -> None
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Invoked with: """
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+ repr(np.array([7.0, 4.0, 1.0], dtype="float32"))
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@ -697,25 +698,25 @@ def test_dense_signature(doc):
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assert (
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doc(m.double_col)
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== """
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double_col(arg0: numpy.ndarray[numpy.float32[m, 1]]) -> numpy.ndarray[numpy.float32[m, 1]]
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double_col(arg0: numpy.typing.NDArray[numpy.float32[m, 1]]) -> numpy.typing.NDArray[numpy.float32[m, 1]]
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"""
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)
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assert (
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doc(m.double_row)
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== """
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double_row(arg0: numpy.ndarray[numpy.float32[1, n]]) -> numpy.ndarray[numpy.float32[1, n]]
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double_row(arg0: numpy.typing.NDArray[numpy.float32[1, n]]) -> numpy.typing.NDArray[numpy.float32[1, n]]
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"""
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)
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assert doc(m.double_complex) == (
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"""
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double_complex(arg0: numpy.ndarray[numpy.complex64[m, 1]])"""
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""" -> numpy.ndarray[numpy.complex64[m, 1]]
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double_complex(arg0: numpy.typing.NDArray[numpy.complex64[m, 1]])"""
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""" -> numpy.typing.NDArray[numpy.complex64[m, 1]]
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"""
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)
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assert doc(m.double_mat_rm) == (
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"""
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double_mat_rm(arg0: numpy.ndarray[numpy.float32[m, n]])"""
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""" -> numpy.ndarray[numpy.float32[m, n]]
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double_mat_rm(arg0: numpy.typing.NDArray[numpy.float32[m, n]])"""
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""" -> numpy.typing.NDArray[numpy.float32[m, n]]
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"""
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)
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@ -268,23 +268,24 @@ def test_round_trip_references_actually_refer(m):
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@pytest.mark.parametrize("m", submodules)
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def test_doc_string(m, doc):
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assert (
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doc(m.copy_tensor) == "copy_tensor() -> numpy.ndarray[numpy.float64[?, ?, ?]]"
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doc(m.copy_tensor)
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== "copy_tensor() -> numpy.typing.NDArray[numpy.float64[?, ?, ?]]"
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)
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assert (
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doc(m.copy_fixed_tensor)
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== "copy_fixed_tensor() -> numpy.ndarray[numpy.float64[3, 5, 2]]"
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== "copy_fixed_tensor() -> numpy.typing.NDArray[numpy.float64[3, 5, 2]]"
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)
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assert (
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doc(m.reference_const_tensor)
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== "reference_const_tensor() -> numpy.ndarray[numpy.float64[?, ?, ?]]"
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== "reference_const_tensor() -> numpy.typing.NDArray[numpy.float64[?, ?, ?]]"
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)
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order_flag = f"flags.{m.needed_options.lower()}_contiguous"
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assert doc(m.round_trip_view_tensor) == (
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f"round_trip_view_tensor(arg0: numpy.ndarray[numpy.float64[?, ?, ?], flags.writeable, {order_flag}])"
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f" -> numpy.ndarray[numpy.float64[?, ?, ?], flags.writeable, {order_flag}]"
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f"round_trip_view_tensor(arg0: numpy.typing.NDArray[numpy.float64[?, ?, ?], flags.writeable, {order_flag}])"
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f" -> numpy.typing.NDArray[numpy.float64[?, ?, ?], flags.writeable, {order_flag}]"
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)
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assert doc(m.round_trip_const_view_tensor) == (
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f"round_trip_const_view_tensor(arg0: numpy.ndarray[numpy.float64[?, ?, ?], {order_flag}])"
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" -> numpy.ndarray[numpy.float64[?, ?, ?]]"
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f"round_trip_const_view_tensor(arg0: numpy.typing.NDArray[numpy.float64[?, ?, ?], {order_flag}])"
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" -> numpy.typing.NDArray[numpy.float64[?, ?, ?]]"
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)
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@ -320,13 +320,13 @@ def test_overload_resolution(msg):
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msg(excinfo.value)
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== """
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overloaded(): incompatible function arguments. The following argument types are supported:
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1. (arg0: numpy.ndarray[numpy.float64]) -> str
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2. (arg0: numpy.ndarray[numpy.float32]) -> str
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3. (arg0: numpy.ndarray[numpy.int32]) -> str
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4. (arg0: numpy.ndarray[numpy.uint16]) -> str
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5. (arg0: numpy.ndarray[numpy.int64]) -> str
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6. (arg0: numpy.ndarray[numpy.complex128]) -> str
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7. (arg0: numpy.ndarray[numpy.complex64]) -> str
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1. (arg0: numpy.typing.NDArray[numpy.float64]) -> str
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2. (arg0: numpy.typing.NDArray[numpy.float32]) -> str
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3. (arg0: numpy.typing.NDArray[numpy.int32]) -> str
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4. (arg0: numpy.typing.NDArray[numpy.uint16]) -> str
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5. (arg0: numpy.typing.NDArray[numpy.int64]) -> str
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6. (arg0: numpy.typing.NDArray[numpy.complex128]) -> str
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7. (arg0: numpy.typing.NDArray[numpy.complex64]) -> str
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Invoked with: 'not an array'
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"""
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@ -342,8 +342,8 @@ def test_overload_resolution(msg):
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assert m.overloaded3(np.array([1], dtype="intc")) == "int"
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expected_exc = """
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overloaded3(): incompatible function arguments. The following argument types are supported:
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1. (arg0: numpy.ndarray[numpy.int32]) -> str
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2. (arg0: numpy.ndarray[numpy.float64]) -> str
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1. (arg0: numpy.typing.NDArray[numpy.int32]) -> str
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2. (arg0: numpy.typing.NDArray[numpy.float64]) -> str
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Invoked with: """
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@ -527,7 +527,7 @@ def test_index_using_ellipsis():
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],
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)
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def test_format_descriptors_for_floating_point_types(test_func):
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assert "numpy.ndarray[numpy.float" in test_func.__doc__
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assert "numpy.typing.NDArray[numpy.float" in test_func.__doc__
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@pytest.mark.parametrize("forcecast", [False, True])
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@ -351,7 +351,7 @@ def test_complex_array():
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def test_signature(doc):
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assert (
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doc(m.create_rec_nested)
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== "create_rec_nested(arg0: int) -> numpy.ndarray[NestedStruct]"
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== "create_rec_nested(arg0: int) -> numpy.typing.NDArray[NestedStruct]"
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)
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@ -150,7 +150,7 @@ def test_docs(doc):
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assert (
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doc(m.vectorized_func)
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== """
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vectorized_func(arg0: numpy.ndarray[numpy.int32], arg1: numpy.ndarray[numpy.float32], arg2: numpy.ndarray[numpy.float64]) -> object
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vectorized_func(arg0: numpy.typing.NDArray[numpy.int32], arg1: numpy.typing.NDArray[numpy.float32], arg2: numpy.typing.NDArray[numpy.float64]) -> object
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"""
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)
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@ -212,12 +212,12 @@ def test_passthrough_arguments(doc):
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+ ", ".join(
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[
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"arg0: float",
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"arg1: numpy.ndarray[numpy.float64]",
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"arg2: numpy.ndarray[numpy.float64]",
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"arg3: numpy.ndarray[numpy.int32]",
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"arg1: numpy.typing.NDArray[numpy.float64]",
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"arg2: numpy.typing.NDArray[numpy.float64]",
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"arg3: numpy.typing.NDArray[numpy.int32]",
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"arg4: int",
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"arg5: m.numpy_vectorize.NonPODClass",
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"arg6: numpy.ndarray[numpy.float64]",
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"arg6: numpy.typing.NDArray[numpy.float64]",
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]
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)
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+ ") -> object"
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