Create function for simulating whole trajectories

[smith-garrett]

Simulate solution of master equation by applying uniformization incrementally, e.g., starting at time point 0 w/ initial conditions, solve for t=0.01. That solution is now the initial state for getting the solution at t=0.02, e.g. This avoids problems related to stiffness: When the (time * uniformization rate) gets large, uniformization becomes inefficient due to the many matrix multiplications that have to be performed.

It would be interesting to consider adaptive time stepping or adaptation of the uniformization rate, but that might be too much initially.

[smith-garrett]

Should take advantage of the fact that p(t + dt) = exp((t + dt) * Q) p(t)

[smith-garrett]

Sketch:

function solve(Q, p0, tspan, dt, params)
soln = zeros(maximum(tspan) / dt + 1, size(Q, 1))

if minimum(tspan) != 0
soln[1,:] = uniformize(Q, p0, params.k, minimum(tspan))
else
soln[1,:] = p0
end

for i in 2:size(soln, 1)
soln[i, :] = uniformize(Q, soln[i-1,:], params.k, dt)
end
soln
end

Will probably need to redo interface of uniformization() to take a params NamedTuple (#14) first to make passing parameters smoother.