Write one interface, access many techniques

todo Not complete, say more, explain better

Pressio is applicable to any system expressible in a continuous-time form as

\frac{d \boldsymbol{y}}{dt} = \boldsymbol{f}(\boldsymbol{y},t; \ldots),

or in time-discrete form as

\boldsymbol R(\mathbf{y}, \mathbf{y}_{n-1} , \ldots, t_n, t_{n-1},\ldots) = \boldsymbol 0.

In the time-continuous case, \boldsymbol{y}(t,\cdots) denotes the state and \boldsymbol{f} denotes the velocity that may be linear or nonlinear in its first argument. In the time-discrete case, \mathbf{y} denotes the state at the current time instance, \mathbf{y}_{n-i} denotes the state at the i-th previous time instance, and \boldsymbol R denotes the time-discrete residual arrising, for example, from a linear mulstistep method.

We note that the model form above is highly expressive, as it may be derived from the spatial discretization of a PDE problem or from naturall discrete systems (e.g., molecular-dynamics problems).