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Improve py::array_t scalar type information (#724)

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* Add value_type member alias to py::array_t (resolve #632)

* Use numpy scalar name in py::array_t function signatures (e.g. float32/64 instead of just float)
This commit is contained in:
Dean Moldovan 2017-03-13 19:17:18 +01:00 committed by GitHub
parent dc5ce5930f
commit 16afbcef46
4 changed files with 25 additions and 5 deletions
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8
include/pybind11/numpy.h
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@ -577,6 +577,8 @@ protected:
template <typename T, int ExtraFlags = array::forcecast> class array_t : public array {
public:
using value_type = T;
array_t() : array(0, static_cast<const T *>(nullptr)) {}
array_t(handle h, borrowed_t) : array(h, borrowed) { }
array_t(handle h, stolen_t) : array(h, stolen) { }
@ -822,7 +824,7 @@ inline PYBIND11_NOINLINE void register_structured_dtype(
template <typename T, typename SFINAE> struct npy_format_descriptor {
static_assert(is_pod_struct<T>::value, "Attempt to use a non-POD or unimplemented POD type as a numpy dtype");
static PYBIND11_DESCR name() { return _("struct"); }
static PYBIND11_DESCR name() { return make_caster<T>::name(); }
static pybind11::dtype dtype() {
return reinterpret_borrow<pybind11::dtype>(dtype_ptr());
@ -1140,7 +1142,9 @@ struct vectorize_helper {
};
template <typename T, int Flags> struct handle_type_name<array_t<T, Flags>> {
static PYBIND11_DESCR name() { return _("numpy.ndarray[") + make_caster<T>::name() + _("]"); }
static PYBIND11_DESCR name() {
return _("numpy.ndarray[") + npy_format_descriptor<T>::name() + _("]");
}
};
NAMESPACE_END(detail)

1
tests/test_numpy_array.cpp
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@ -17,6 +17,7 @@
using arr = py::array;
using arr_t = py::array_t<uint16_t, 0>;
static_assert(std::is_same<arr_t::value_type, uint16_t>::value, "");
template<typename... Ix> arr data(const arr& a, Ix... index) {
return arr(a.nbytes() - a.offset_at(index...), (const uint8_t *) a.data(index...));

19
tests/test_numpy_array.py
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@ -279,6 +279,21 @@ def test_overload_resolution(msg):
# No exact match, should call first convertible version:
assert overloaded(np.array([1], dtype='uint8')) == 'double'
with pytest.raises(TypeError) as excinfo:
overloaded("not an array")
assert msg(excinfo.value) == """
overloaded(): incompatible function arguments. The following argument types are supported:
1. (arg0: numpy.ndarray[float64]) -> str
2. (arg0: numpy.ndarray[float32]) -> str
3. (arg0: numpy.ndarray[int32]) -> str
4. (arg0: numpy.ndarray[uint16]) -> str
5. (arg0: numpy.ndarray[int64]) -> str
6. (arg0: numpy.ndarray[complex128]) -> str
7. (arg0: numpy.ndarray[complex64]) -> str
Invoked with: 'not an array'
"""
assert overloaded2(np.array([1], dtype='float64')) == 'double'
assert overloaded2(np.array([1], dtype='float32')) == 'float'
assert overloaded2(np.array([1], dtype='complex64')) == 'float complex'
@ -289,8 +304,8 @@ def test_overload_resolution(msg):
assert overloaded3(np.array([1], dtype='intc')) == 'int'
expected_exc = """
overloaded3(): incompatible function arguments. The following argument types are supported:
1. (arg0: numpy.ndarray[int]) -> str
2. (arg0: numpy.ndarray[float]) -> str
1. (arg0: numpy.ndarray[int32]) -> str
2. (arg0: numpy.ndarray[float64]) -> str
Invoked with:"""

2
tests/test_numpy_vectorize.py
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@ -71,5 +71,5 @@ def test_docs(doc):
from pybind11_tests import vectorized_func
assert doc(vectorized_func) == """
vectorized_func(arg0: numpy.ndarray[int], arg1: numpy.ndarray[float], arg2: numpy.ndarray[float]) -> object
vectorized_func(arg0: numpy.ndarray[int32], arg1: numpy.ndarray[float32], arg2: numpy.ndarray[float64]) -> object
""" # noqa: E501 line too long