Awesome

Clatrix matrix

A stupid name for a smart matrix library, because who doesn't love smart matrices? Being implemented as a data type around the native BLAS hooks of jblas gives it speed. Being implemented as a Clojure sequence makes it clever.

Clatrix works as an implementation of core.matrix so it is fully compatible with other libraries and tools that use the core.matrix API.

Usage

For now, you can read the Marginalia documentation or take a look at a few examples below. (Note: To be updated!)

(in-ns 'clatrix.core)

(matrix (repeat 5 (range 10)))

; A 5x10 matrix
; -------------
; 0.00e+00  1.00e+00  2.00e+00  .  7.00e+00  8.00e+00  9.00e+00
; 0.00e+00  1.00e+00  2.00e+00  .  7.00e+00  8.00e+00  9.00e+00
; 0.00e+00  1.00e+00  2.00e+00  .  7.00e+00  8.00e+00  9.00e+00
; 0.00e+00  1.00e+00  2.00e+00  .  7.00e+00  8.00e+00  9.00e+00
; 0.00e+00  1.00e+00  2.00e+00  .  7.00e+00  8.00e+00  9.00e+00


(from-indices 5 5 *)

; A 5x5 matrix
; ------------
; 0.00e+00  0.00e+00  0.00e+00  0.00e+00  0.00e+00
; 0.00e+00  1.00e+00  2.00e+00  3.00e+00  4.00e+00
; 0.00e+00  2.00e+00  4.00e+00  6.00e+00  8.00e+00
; 0.00e+00  3.00e+00  6.00e+00  9.00e+00  1.20e+01
; 0.00e+00  4.00e+00  8.00e+00  1.20e+01  1.60e+01

(time (solve (rand 1000 1000) (rand 1000)))

; "Elapsed time: 158.216 msecs"
; ....

(time (rank (rand 1000 1000)))

; "Elapsed time: 13469.51 msecs"
; 1000

(let [A (rand 10 14)
      B (* A (t A))     ; B is symmetric
      lu (lu B)
      P (rspectral 10)  ; `respectral` makes positive definite matrices
      G (cholesky P)]   ; so we can get their square root
  (and (= A (c/t (c/t A)))
       (= B (* (:p lu) (:l lu) (:u lu)))
       (= P (* (t G) G))))

; true