To avoid computing the flux function at each internal edge twice, we now call the C implementation of compute_fluxes with the extra integer vector argument already_computed_flux. This is an array of dimension (N,3) in python (or 3N in C) and thus each entry corresponds to a triangle-edge pair. If triangle t has neighbour n across its i-th edge, and this edge is the m-th edge of triangle n, then we update this edge's flux contribution to explicit_update for both triangle n and triangle t. Both corresponding entries of already_computed_flux will be incremented so that, when we come to edge m of triangle n, we know that the update across this edge has already been done.
The array already_computed_flux is defined and initialised to zero in domain.py.
For run_profile.py, with N=128, the version of compute_fluxes in which each edge was computed twice consumed 13.64 seconds (averaged over 3 runs). By keeping track of which edges have been computed, compute_fluxes now consumes 8.68 seconds.
