I'm looking at two different source for the Slerp method of interpolation between two quaternions. They are pretty similar except for one notable difference: one clamps the dot product between 0 and 1, and the other between -1 and 1. Here is one of them:

Code :glm::fquat Slerp(const glm::fquat &v0, const glm::fquat &v1, float alpha) { float dot = glm::dot(v0, v1); const float DOT_THRESHOLD = 0.9995f; if (dot > DOT_THRESHOLD) return Lerp(v0, v1, alpha); glm::clamp(dot, -1.0f, 1.0f); //<-- The line in question float theta_0 = acosf(dot); float theta = theta_0*alpha; glm::fquat v2 = v1 - v0*dot; v2 = glm::normalize(v2); return v0*cos(theta) + v2*sin(theta); }

Here is the other:

Code :template <typename T> inline QuaternionT<T> QuaternionT<T>::Slerp(T t, const QuaternionT<T>& v1) const { const T epsilon = 0.0005f; T dot = Dot(v1); if (dot > 1 - epsilon) { QuaternionT<T> result = v1 + (*this - v1).Scaled(t); result.Normalize(); return result; } if (dot < 0) //<-The lower clamp dot = 0; if (dot > 1) dot = 1; T theta0 = std::acos(dot); T theta = theta0 * t; QuaternionT<T> v2 = (v1 - Scaled(dot)); v2.Normalize(); QuaternionT<T> q = Scaled(std::cos(theta)) + v2.Scaled(std::sin(theta)); q.Normalize(); return q; }

I think it is worth noting also the the Lerp algorithm in the second one doesn't seem right for all cases?

I just want some feedback on these differences and if they really matter at all.