title: Are there packages to visualize causal models relations (DAGs) in a highly interactive and customizable way (e.g. dynamical parameters variationsetc)?
body: <p>I need to come up with a visualization of the cause-effect relations for a particular phenomenon. So far I only found static representations or interactive representations which however did not have the features I needed.</p>
  <p>I need to represent causes and effects as DAGs (directed acyclic graphs). Each node represent for instance a physical quantity (e.g. 'cause'-nodes: mass, height and 'effect'-nodes: kinetic energy, potential energy etc) that I want to be able to vary in a specific range interactively (e.g. mass goes from 0 -no mass- to 100kg) and I want that such change is quickly shown through the network (so, for instance, if I change the mass I want the effect-node kinetic energy to be updated as quickly as possible). Also, I would like to have the graphics of such nodes to be dependant on the values (e.g. the higher the value the bigger the node, and if for instance kinetic energy is above some threshold the color of the node changes).</p>
  <p>Is there a way to do it in python or in any other way?
  Thank you!</p>