PSL Systems to Neuromancer Blocks

[drgona]

Discussed in #200

^{Originally posted by cjb873 October 16, 2024}
The PSL system library has a lot of systems that are not implemented in neuromancer.dynamics, such as the Boid's system, RC Networks, etc. I see that the base classes have a forward function defined so that these dynamical systems can be wrapped with a Node and used with the System class, yet these forward functions as currently implemented do not support minibatching. I believe this is due to the fact that integrators are called within the forward function, as well as the actual equations of these systems not being able to act on two dimensional tensors.

I think it could be useful to pursue an implementation of forward for these systems that can be wrapped and placed in an integrator, in an example like:

sys = RC_Network(nx=5)


class RC_Block(ode.ODESystem):

    def __init__(self, net):
        super().__init__(net.nx, net.nu)
        self.net = net

    def ode_equations(self, x, u):
        return self.net(x, u)

integrator = integrators.Euler(RC_Block(sys), h=ts)
integrator_node = Node(integrator, ['x', 'u'], ['x'])

Or, it may be best to just implement a version of these dynamical systems inside of neuromancer.dynamics. Either way, I personally would like it to be easier to use white-box representations of these coupled systems to do DPC.