====== Functional networks ======

Piran, August 12, 2017

The values of nodes/links can be computed using functions attached to nodes and links - a kind of generalized Excel.

There are different strategies to compute these values:

  - **stepwise**: current state -> new state. New value in each node/link is computed considering current state value. At the end the new state becomes the current state; [[.exe:life|LIFE]]; [[.exe:lifp|LIFEplane]]
  - **[[.exe:wave|wave front]]**: can be applied only in acyclic networks. The values are update in a topological sort order;
  - **rules for destroying cycles**: for example introducing the specifier old. (A,C), (B,C), (C,D), (D,B),  T(C) = f(T(A), old(T(B))); 
  - **computing temporal quantities**: difference equations; problem: are the values well defined? ; [[.exe:lift|LIFEtime]]
  - **computing temporal curves**: differential equations; formal solutions or numerical approximations 
  - **recursive**: if a value in a predecessor is not known it is computed recursively (dictionary time:value) )
  
See: Netlogo, Stella, ???

LIFE on rectangle, Moebius strip, torus, ...

<code>
>>> import os
>>> os.chdir("C:/Users/batagelj/work/Python/graph/Nets")
</code>

===== References =====

  * Yves Hilpisch: Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging
  * Jose M. Garrido: Introduction to Computational Models with Python
  * Ankur Ankan, Abinash Panda: Mastering Probabilistic Graphical Models using Python
  * Mitchell Model, Tisdall James: Bioinformatics Programming Using Python