dvec 0.0.6

dvec - Easy linear algebra for D

dvec is a library that offers vector and matrix data structures and functions in a way that's intuitive, easy to use, tested, and well-documented. It takes advantage of the D language's advanced templating system and compile-time code-generation to help optimize performance and type safety.

dvec offers the basic linear algebra primitives:

• Vectors
• Matrices

Each of these can be of any desired integer size (within the limits of your system). For example, Vec!(float, 5) v; defines a 5-dimensional floating-point vector, and Mat!(int, 2, 3) m; defines a 2x3 (2 rows by 3 columns) integer matrix. However, this can get to be a bit tedious, so we've included the most common vectors and matrices as aliases for you:

• 2, 3, and 4-dimensional vectors of float, double, and int types: Vec3d, Vec2i, and Vec4f, for example.
• 2, 3, and 4-dimensional square matrices of float, double, and int types: Mat2f, Mat3i, and Mat4d, for example.

Each primitive is a simple struct with a fully transparent internal structure, and implements all the basic arithmetic operators, so you can do things like this easily:

Vec3f v = Vec3f(1f, 2f, 3f) * 5 - Vec3f(0.5f);
// v.data == [4.5f, 9.5f, 14.5f]

Besides the `toString()` methods, no parts of this library make use of the GC, and are thus @nogc compatible.

Vectors

Certain vector types get access to extra special functions:

• Any floating-point (float, double) vector supports the norm() method, to normalize the vector to a unit vector of length 1.
• Any floating-point (float, double) 2-dimensional vector supports the toPolar() and toCartesian() methods, so that the vector can be treated as polar or cartesian coordinates and converted between the two.
• Any floating-point (float, double) 3-dimensional vector supports the cross() method for computing the cross product with another 3-dimensional vector.

Matrices

Certain matrix types get access to extra special functions:

• Square matrices (NxM matrices where N = M) support a variety of additional methods that are useful for linear algebra, like det() (determinant), inv() (inverse), and so on.
• 3x3 matrices support linear transformation methods in 2 dimensions, like translation, rotation, skew, and scaling.
• 4x4 matrices support linear transformation methods in 3 dimensions.

For more information, please see dub project page and its associated documentation.

A lot of effort has gone into making sure everything in this library is well-documented and explained well. If you find that documentation is missing or insufficient for a certain part, please make an issue on GitHub!