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vectorize: trivial handling for F-order arrays

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This extends the trivial handling to support trivial handling for
Fortran-order arrays (i.e. column major): if inputs aren't all
C-contiguous, but *are* all F-contiguous, the resulting array will be
F-contiguous and we can do trivial processing.

For anything else (e.g. C-contiguous, or inputs requiring non-trivial
processing), the result is in (numpy-default) C-contiguous layout.
This commit is contained in:
Jason Rhinelander
2017-03-18 21:11:59 -03:00
parent ae5a8f7eb3
commit b0292c1df3
3 changed files with 127 additions and 51 deletions
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4
tests/test_numpy_vectorize.cpp
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@@ -41,6 +41,10 @@ test_initializer numpy_vectorize([](py::module &m) {
// Internal optimization test for whether the input is trivially broadcastable:
py::enum_<py::detail::broadcast_trivial>(m, "trivial")
.value("f_trivial", py::detail::broadcast_trivial::f_trivial)
.value("c_trivial", py::detail::broadcast_trivial::c_trivial)
.value("non_trivial", py::detail::broadcast_trivial::non_trivial);
m.def("vectorized_is_trivial", [](
py::array_t<int, py::array::forcecast> arg1,
py::array_t<float, py::array::forcecast> arg2,