(* A simple network of excitatory and inhibitory neurons *)

component ExcInhNetwork =
struct

 binding construct_diagram V t gL vL Isyn C theta tspike spike Vreset trefractory refractory_end tstep =

        binding subthreshold_eq       = [ D (V t) = (((- gL) * (V - vL)) + Isyn) / C ]
        val threshold_detect          = [ spike = (V >= theta) ]
        val tspike_assignment         = [ tspike = if spike then t else tspike ]
        val subthreshold_regime       = Diagram.SEQUENCE subthreshold_eq (Diagram.SEQUENCE threshold_detect tspike_assignment)
        val refractory_eq             = [ V = Vreset ]
        val refractory_regime         = [
                                          [ V = Vreset ]
                                          [ refractory_end = (t >= (tspike + trefractory)) ]
                                          [ t = t + tstep ]
                                        ] 
        return Diagram.RTRANSITION subthreshold_regime refractory_regime spike refractory_end 

  binding construct_network N_exc N_inh D_exc D_inh P =

         (* a graph to represent the excitatory population *)

         binding I_exc = Interval.closed_interval 0d1 N_exc
         binding excitatory_population = Graph.set_node_interval_property (Graph.nodes (N_exc)) 
                                                                          I_exc `synapticPrototype D_exc

         (* a graph to represent the inhibitory population *)

         binding I_inh = Interval.closed_interval 0d1 N_inh
         binding inhibitory_population = Graph.set_node_interval_property (Graph.nodes (N_inh)) 
                                                                          I_inh `synapticPrototype D_inh

         (* disjoint union of the two populations *)
         binding populations = Graph.disjoint_union excitatory_population inhibitory_population

         (* random graph G(N,P) *)
         binding P = 0.02
         binding connections = Graph.gnp_graph (N_exc + N_inh) P

         (* graph union: node attributes take precedence from left to right *)
         binding populations_and_connections = Graph.union populations connections

         (* this procedure determines the synapse prototype for a connection: *)
         binding synapse_prototype G S D = Graph.node_property G S `synapticPrototype 
  
         (* final network *)
         binding I_network = Interval.closed_interval 0d1 (N_exc + N_inh)
         binding network   = Graph.set_edge_interval_property populations_and_connections 
                                I_network I_network `synapticPrototype synapse_prototype


        return network

end