vectorz-clj

Fast vector library for Clojure, building on the Vectorz library.

vectorz-clj is designed so that you don't have to compromise, offering both:

• An idiomatic high-level Clojure API.
• High performance (about as fast as you can get on the JVM)

The library was originally designed for games, simulations and machine learning applications, but should be applicable for any situations where you need numerical double arrays.

Important features:

• "Pure" functions for an idiomatic functional programming style are provided. These return new vectors without mutating their arguments.
• Primitive-backed special purpose vectors and matrices for performance, e.g. Vector3 for fast 3D maths.
• Flexible DSL-style functions for manipulating vectors and matrices, e.g. the ability to create a "view" into a subspace of a large vector.
• core.matrix fully supported - see: https://github.com/mikera/matrix-api
• Pure JVM code - no native dependencies
• "Impure" functions that mutate vectors are available for performance when you need it: i.e. you can use a nice functional style most of the time, but switch to mutation when you hit a bottleneck.

Documentation

For more information see the vectorz-clj Wiki.

Status

vectorz-clj requires Clojure 1.4 or above, and an up to date version of core.matrix

vectorz-clj is reasonably stable, and implements all of the core.matrix API feature set. The core.matrix API is still under development, so users may expect some minor changes to the API in future releases.

License

Like Vectorz, vectorz-clj is licensed under the LGPL license:

• http://www.gnu.org/licenses/lgpl.html

Usage

Follow the instructions to install with Leiningen / Maven from Clojars:

• https://clojars.org/net.mikera/vectorz-clj

You can then use Vectorz as a standard core.matrix implementation. Example:

    (use 'clojure.core.matrix)
    (use 'clojure.core.matrix.operators)           ;; overrides *, + etc. for matrices
    
    (set-current-implementation :vectorz)  ;; use Vectorz as default matrix implementation
    
    ;; define a 2x2 Matrix
    (def M (matrix [[1 2] [3 4]]))
    M
    => #<Matrix22 [[1.0,2.0][3.0,4.0]]>
    
    ;; define a length 2 vector (a 1D matrix is considered equivalent to a vector in core.matrix)
    (def v (matrix [1 2]))
    v
    => #<Vector2 [1.0,2.0]>
    
    ;; Matrix x Vector multiply
    (* M v)
    => #<Vector2 [5.0,11.0]>

For more examples see Wiki Examples