Before neither of the lerp(), slerp() had the shortest path check, while
sclerp() had it. Now, to be consistent, none of them has it and there
are lerpShortestPath(), slerpShortestPath() and sclerpShortestPath()
functions that have the shortest path check.
This is different from other engines, where there's usually only the
shortest path interpolation by default and either an optional
"non-shortest-path" interpolation or no alternative at all. I like to
give the users a choice, so there's both versions and the
non-shortest-path version is the default, because -- at least in case of
lerp() -- this results in a quite significant perf difference (15%
faster), so why not have it. Preprocess your data instead ;)
The fix done with https://github.com/mosra/magnum/pull/122
(0e05c7289e) was not tested properly (see
previous commit) and thus this code path never worked. This properly
lerps the translation part and recombines it with the rotation instead
of interpolating just a part of it.
Also I'm no longer having any "dotResult" that's done only on the
vector part of the rotation, but instead using the full
rotation quaternion dot product. I have no idea why it was done this
way. This branch was also never properly tested -- it'll be with the
introduction of "shortest path" variants in the next commit.
When rotation is identical, the rotation of the first dual quaternion is
returned instead, together with the linearly interpolated translation of
both (lerp of the vectors of the dual part). The additional include is
needed for `Math::lerp(Vector<3, T>, Vector<3, T>, T)`.
Signed-off-by: Squareys <Squareys@googlemail.com>
Making use of sincos() for Dual numbers, constructing DualQuaternion
from dual vector and scalar parts and using
DualQuaternion::isNormalized(). Also updated the math equation to be
consistent with conventions elsewhere.
- Use explicit conversion to `T`
- Use `std::` for `acos, cos, sin` to avoid use of double only functions
- Do not mutate variables in math code to avoid confusion
Signed-off-by: Squareys <Squareys@googlemail.com>
Should help people understand the code and counteracts the unreadability
caused by the optimization commit at least a bit.
Signed-off-by: Squareys <Squareys@googlemail.com>
Optimized with simple code tricks, some very complex math (like `2*0.5=1`),
and principal of locality. Things the compiler would probably do for me
anyway. Was able to remove about 6 useless float multiplications.
Signed-off-by: Squareys <Squareys@googlemail.com>
Now works both ways. The base class works with virtually any combination
that is supported by the underlying types, so e.g. Dual<Matrix3<T>>
could be multiplied/divided with Vector3<T> (result is Vector3<T>), with
Matrix3<T> (result is Matrix3<T>) or with T (result is Matrix3<T>).
The macros, on the other hand, because they are there only to help with
implementation of *my* subclasses, restrict that to the two only cases I
need (i.e. multiplication with Dual<T> and Dual<T::Type> and nothing
else). Could be extended in the future if it needs to be.