There is SymPy.jl. The matrix bit could use some ironing out. By default, it uses an Array of symbolic objects, rather than a symbolic array. This means taking an inverse is bit cumbersome:
using SymPy r = sympy.Rational m = [r(1,2) r(2,3); r(3,4) r(4,5)] ## Array of Sym objects inv(m) ## converts to float, so no good m = convert(SymMatrix, m) ## SymMatrix object m[:inv]() Might be better to just interface directly with sympy through PyCall for this. On Thursday, January 9, 2014 1:48:12 AM UTC-5, Alasdair McAndrew wrote: > > Since Julia plays so nicely with Python, why not just - at least in the > short term - create a package that interfaces with SymPy ( > http://sympy.org/en/index.html)? This will certainly give you what you > want, and a great deal more besides. > > On Thursday, January 9, 2014 6:50:01 AM UTC+11, David Zhang wrote: >> >> Does Julia have any support for linear algebra on rational-valued >> matrices? Currently, most linear algebra functionality seems to be provided >> by BLAS/LAPACK, which only support operations on floating-point matrices. >> >> I am interested in this because I would like to use Julia to derive >> high-order numerical integration methods, whose coefficients are the >> solutions of rational linear system. >> >> (Continuation from >> http://stackoverflow.com/questions/20985783/rational-matrix-division-in-julia >> ) >> >>
