Network (and jump) graph nodes contract down to 1 pixel -- improving the scolling tube for large 1d networks, improvements to enlarged DDLab window layout, load/save ascii seed files.
The Derrida plot (described in EDD#22) is usually applied as an order-chaos measure for large RBN in the context of models of genetic regulatory networks, but it also provides Liapunov-like insights into CA rules. New options allow automatic plots of sets of rules in ascending decimal order, filtering out equivalent binary rcode and tcode, and listing equivalence classes and rule clusters.
For Null Boundary Conditions, inputs beyond the network's edges are held at a constant value of zero. All DDLab functions can now be easily switched between Periodic and Null. Null boundaries are of interest in pattern recognition, and where the system is grounded or quenched, or bounded by an edge, skin or membrane.
The new 2d hex/triangular neighborhoods for k3 and k4 permit investigating the dynamics on these simpler lattices, with many instances of complexity.