Fix semantics of operator overloads on matrices. about linalg HOT 4 CLOSED

In my libraries, I define a Hadamard operator for element-wise operations.

https://en.wikipedia.org/wiki/Hadamard_product_(matrices)

It's useful, and comes up frequently in signal processing and quantum computing. Some languages define an operator for it .* (dot star)

On the topic of matrix * vector, homogeneous and non-homogenous multiplies are interesting, as are v3f multiplications with an implicit w of 1.

from linalg.

I think this is a question of semantics. Element-wise is behavior of ndarray. It is like numpy arrays etc.
I still think it was a good decision to interpret matrix and vectors in ndarray's semantic.

If it go back to algebraic semantics, the library will no longer look so basic as it now looks.

On the question immediately comes to mind the question, what about the multiplication of quaternions? In the current state, this is simply the same superstructure above ndarray's semantics as algebraic matrix operations. If you put matrix operations at the center, the status of quaternions and other objects that can be built on the basis of this library will be strange.

P.S. I allow myself to express the opinion that feedback from users could be unrepresentative, since the number of messages from users who found the current state of affairs would obviously be less than the number of messages from those who found it strange, while the number of such users could be identical.

from linalg.

Indeed it is a question of semantics. I'm one of the authors of Imath, so naturally I am biased to the algebraic conventions found there :)

from linalg.

Implemented in the v3 branch, which additionally introduces a quat<T> type. Component-wise operations are still explicitly available via the apply(...) function, which subsumes the original behavior of map(...) and zip(...).

The most recent commit that retains the original semantics of the library has been tagged v2.1. I'll be open to providing small bugfixes and improvements to v2.1.

from linalg.