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vectorize: pass-through of non-vectorizable args

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This extends py::vectorize to automatically pass through
non-vectorizable arguments.  This removes the need for the documented
"explicitly exclude an argument" workaround.

Vectorization now applies to arithmetic, std::complex, and POD types,
passed as plain value or by const lvalue reference (previously only
pass-by-value types were supported).  Non-const lvalue references and
any other types are passed through as-is.

Functions with rvalue reference arguments (whether vectorizable or not)
are explicitly prohibited: an rvalue reference is inherently not
something that can be passed multiple times and is thus unsuitable to
being in a vectorized function.

The vectorize returned value is also now more sensitive to inputs:
previously it would return by value when all inputs are of size 1; this
is now amended to having all inputs of size 1 *and* 0 dimensions.  Thus
if you pass in, for example, [[1]], you get back a 1x1, 2D array, while
previously you got back just the resulting single value.

Vectorization of member function specializations is now also supported
via `py::vectorize(&Class::method)`; this required passthrough support
for the initial object pointer on the wrapping function pointer.
This commit is contained in:
Jason Rhinelander
2017-03-26 00:51:40 -03:00
parent 41f8da4a95
commit f3ce00eaed
6 changed files with 212 additions and 80 deletions
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27
tests/test_numpy_vectorize.cpp
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@@ -20,6 +20,17 @@ std::complex<double> my_func3(std::complex<double> c) {
return c * std::complex<double>(2.f);
}
struct VectorizeTestClass {
VectorizeTestClass(int v) : value{v} {};
float method(int x, float y) { return y + (float) (x + value); }
int value = 0;
};
struct NonPODClass {
NonPODClass(int v) : value{v} {}
int value;
};
test_initializer numpy_vectorize([](py::module &m) {
// Vectorize all arguments of a function (though non-vector arguments are also allowed)
m.def("vectorized_func", py::vectorize(my_func));
@@ -40,6 +51,22 @@ test_initializer numpy_vectorize([](py::module &m) {
m.def("selective_func", [](py::array_t<std::complex<float>, py::array::c_style>) { return "Complex float branch taken."; });
// Passthrough test: references and non-pod types should be automatically passed through (in the
// function definition below, only `b`, `d`, and `g` are vectorized):
py::class_<NonPODClass>(m, "NonPODClass").def(py::init<int>());
m.def("vec_passthrough", py::vectorize(
[](double *a, double b, py::array_t<double> c, const int &d, int &e, NonPODClass f, const double g) {
return *a + b + c.at(0) + d + e + f.value + g;
}
));
py::class_<VectorizeTestClass> vtc(m, "VectorizeTestClass");
vtc .def(py::init<int>())
.def_readwrite("value", &VectorizeTestClass::value);
// Automatic vectorizing of methods
vtc.def("method", py::vectorize(&VectorizeTestClass::method));
// 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)