Computer algebra for Clojure

Question

Short version: I am interested in some Clojure code which will allow me to specify the transformations of x (e.g. permutations, rotations) under which the value of a function f(x) is invariant, so that I can efficiently generate a sequence of x's that satisfy r = f(x). Is there some development in computer algebra for Clojure? For (a trivial) example

(defn #^{:domain #{3 4 7} 
         :range #{0,1,2}
         :invariance-group :full} 
          f [x]  (- x x))

I could call (preimage f #{0}) and it would efficiently return #{3 4 7}. Naturally, it would also be able to annotate the codomain correctly. Any suggestions?

Longer version: I have a specific problem that makes me interested in finding out about development of computer algebra for Clojure. Can anyone point me to such a project? My specific problem involves finding all the combinations of words that satisfy F(x) = r, where F is a ranking function and r a positive integer. In my particular case f can be computed as a sum

F(x) = f(x[0]) + f(x[1]) + ... f(x[N-1])

Furthermore I have a set of disjoint sets S = {s_i}, such that f(a)=f(b) for a,b in s, s in S. So a strategy to generate all x such that F(x) = r should rely on this factorization of F and the invariance of f under each s_i. In words, I compute all permutations of sites containing elements of S that sum to r and compose them with all combinations of the elements in each s_i. This is done quite sloppily in the following:

(use 'clojure.contrib.combinatorics)
(use 'clojure.contrib.seq-utils)


(defn expand-counter [c]
 (flatten (for [m c] (let [x (m 0) y (m 1)] (repeat y x)))))

(defn partition-by-rank-sum [A N f r]
  (let [M (group-by f A)
    image-A (set (keys M))
    ;integer-partition computes restricted integer partitions,
    ;returning a multiset as key value pairs
    rank-partitions (integer-partition r (disj image-A 0))
    ]
    (apply concat (for [part rank-partitions]
        (let [k (- N (reduce + (vals part)))
          rank-map (if (pos? k) (assoc part 0 k) part) 
          all-buckets (lex-permutations (expand-counter rank-map))
          ]
          (apply concat (for [bucket all-buckets]
        (let [val-bucket (map M bucket)
              filled-buckets (apply cartesian-product val-bucket)]
          (map vec filled-buckets)))))))))

This gets the job done but misses the underlying picture. For example, if the associative operation were a product instead of a sum I would have to rewrite portions.

Answer 1

The system below does not yet support combinatorics, though it would not be a huge effort to add them, loads of good code already exists, and this could be a good platform to graft it onto, since the basics are pretty sound. I hope a short plug is not inappropriate here, this is the only serious Clojure CAS I know of, but hey, what a system...

=======

It may be of interest to readers of this thread that Gerry Sussman's scmutils system is being ported to Clojure. This is a very advanced CAS, offering things like automatic differentiation, literal functions, etc, much in the style of Maple. It is used at MIT for advanced programs on dynamics and differential geometry, and a fair bit of electrical engineering stuff. It is also the system used in Sussman&Wisdom's "sequel" (LOL) to SICP, SICM (Structure and Interpretation of Classical Mechanics). Although originally a Scheme program, this is not a direct translation, but a ground-up rewrite to take advantage of the best features of Clojure. It's been named sicmutils, both in honour of the original and of the book This superb effort is the work of Colin Smith and you can find it at https://github.com/littleredcomputer/sicmutils .

I believe that this could form the basis of an amazing Computer Algebra System for Clojure, competitive with anything else available. Although it is quite a huge beast, as you can imagine, and tons of stuff remains to be ported, the basics are pretty much there, the system will differentiate, and handle literals and literal functions pretty well. It is a work in progress. The system also uses the "generic" approach advocated by Sussman, whereby operations can be applied to functions, creating a great abstraction that simplifies notation no end.

Here's a taster:

> (def unity (+ (square sin) (square cos)))
> (unity 2.0)  ==>  1.0
> (unity 'x)   ==> 1 ;; yes we can deal with symbols
> (def zero (D unity))  ;; Let's differentiate
> (zero 2.0)   ==> 0

SicmUtils introduces two new vector types “up” and “down” (called “structures”), they work pretty much as you would expect vectors to, but have some special mathematical (covariant, contravariant) properties, and also some programming properties, in that they are executable!

> (def fnvec (up sin cos tan))  => fnvec
> (fnvec 1)   ==> (up 0.8414709848078965 0.5403023058681398 1.5574077246549023)
> ;; differentiated
> ((D fnvec) 1)  ==>  (up 0.5403023058681398 -0.8414709848078965 3.425518820814759) 
> ;; derivative with symbolic argument
> ((D fnvec) 'θ) ==> (up (cos θ) (* -1 (sin θ)) (/ 1 (expt (cos θ) 2)))  

Partial differentiation is fully supported

> (defn ff [x y] (* (expt x 3)(expt y 5)))
> ((D ff) 'x 'y) ==> (down (* 3 (expt x 2) (expt y 5)) (* 5 (expt x 3) (expt y 4))) 
> ;; i.e. vector of results wrt to both variables

The system also supports TeX output, polynomial factorization, and a host of other goodies. Lots of stuff, however, that could be easily implemented has not been done purely out of lack of human resources. Graphic output and a "notepad/worksheet" interface (using Clojure's Gorilla) are also being worked on.

I hope this has gone some way towards whetting your appetite enough to visit the site and give it a whirl. You don't even need Clojure, you could run it off the provided jar file.

Answer 2

There's Clojuratica, an interface between Clojure and Mathematica:

http://clojuratica.weebly.com/

See also this mailing list post by Clojuratica's author.

While not a CAS, Incanter also has several very nice features and might be a good reference/foundation to build your own ideas on.

Regarding "For example, if the associative operation were a product instead of a sum I would have to rewrite portions.": if you structure your code accordingly, couldn't you accomplish this by using higher-order functions and passing in the associative operation? Think map-reduce.