magnum-bindings

Commit Graph

Author	SHA1	Message	Date
Vladimír Vondruš	d011297c13	Here we go again.	1 year ago
Vladimír Vondruš	b0d714344a	It's October already?!	2 years ago
Vladimír Vondruš	305fdf81ee	It's 2023 already!	3 years ago
Vladimír Vondruš	2295f43873	Updated copyright year.	4 years ago
Vladimír Vondruš	0120b3f768	python: add remaining vector/scalar, exp and other math functions. Except for binomial coefficient, there the asserts are hard to replicate and would need a change on Magnum side.	4 years ago
Aaron Gokaslan	31785426d8	Typo fixing	5 years ago
Vladimír Vondruš	84f9bb2a9d	Updated copyright year.	5 years ago
Vladimír Vondruš	57db13422f	python: make this compatible with pybind11 2.6. Pybind changed py::module to py::module_ in order to support C++ modules, adapting to that change. It still builds on older versions, but we're using only the new APIs.	6 years ago
Vladimír Vondruš	b1d45fc85a	Updated copyright year.	6 years ago
Vladimír Vondruš	4718de1ed3	python: don't define negation on unsigned vector types. Thanks, MSVC.	7 years ago
Vladimír Vondruš	7e057863c8	python: fix Clang's -Wself-assign-overloaded warnings. It's unfortunate that the pybind11 operator helpers need this, but well.	7 years ago
Vladimír Vondruš	d157b55637	magnum: again (and hopefully for the last time) reorder constructors. The order should be (and now is): 1. magnum's own conversion constructors (double from integer and such) 2. stuff like implicit color3 -> color4, if applicable 3. buffer protocol constructors 4. general "init from a tuple" constructors last, because they're the slowest	7 years ago
Vladimír Vondruš	7549d107de	python: implement buffer protocol for Vector types as well. This makes Vector3 to np.array conversion about 20x faster. Yes, that much. Crazy. Timings from the benchmark added in previous commit before: np.array([]) 0.66096 µs np.array([1.0, 2.0, 3.0]) 0.70623 µs a = array.array("f", [1.0, 2.0, 3.0]); np.array(a) 0.57877 µs a = Vector3(1.0, 2.0, 3.0); np.array(a) 18.18542 µs after: np.array([]) 0.57162 µs np.array([1.0, 2.0, 3.0]) 0.68309 µs a = array.array("f", [1.0, 2.0, 3.0]); np.array(a) 0.53958 µs a = Vector3(1.0, 2.0, 3.0); np.array(a) 0.74818 µs There's still some overhead that could be removed I think, making the Vector3-to-numpy conversion faster than list-to-numpy.	7 years ago
Vladimír Vondruš	124980cec4	python: return proper type when doing operations on Color.	7 years ago
Vladimír Vondruš	464154adca	python: implement conversions between different underlying types. Such a tiny feature and such a pain when it's not there.	7 years ago
Vladimír Vondruš	081d32938a	python: expose all Vector variants.	7 years ago

16 Commits (4a0891ad259ab9f4fc90ffe1dccb5eabe1cfa9b2)