In addition to the four aesthetic criteria the concept of a border line which induces an energy cost to nodes in proximity to the graph bounds is introduced to attempt to restrain the graph. All of the 5 factors can be switched on or off using the isOptimize... variables.
Simulated Annealing is a force-directed layout and is one of the more expensive, but generally effective layouts of this type. Layouts like the spring layout only really factor in edge length and inter-node distance being the lowest CPU intensive for the most aesthetic gain. The additional factors are more expensive but can have very attractive results.
The main loop of the algorithm consist of processing the nodes in a random order. During the processing of each node a circle of radius moveRadius is made around the node and split into triesPerCell equal segments. Each point between neighbour segments is determined and the new energy of the system if the node were moved to that position calculated. Only the necessary nodes and edges are processed new energy values resulting in quadratic performance, O(VE), whereas calculating the total system energy would be cubic. The default implementation only checks 8 points around the radius of the circle, as opposed to the suggested 30 in the paper. Doubling the number of points double the CPU load and 8 works almost as well as 30.
The moveRadius replaces the temperature as the influencing factor in the way the graph settles in later iterations. If the user does not set the initial move radius it is set to half the maximum dimension of the graph. Thus, in 2 iterations a node may traverse the entire graph, and it is more sensible to find minima this way that uphill moves, which are little more than an expensive 'tilt' method. The factor but which the radius is multiplied by after each iteration is important, lowering it improves performance but raising it towards 1.0 can improve the resulting graph aesthetics. When the radius hits the minimum move radius defined, the layout terminates. The minimum move radius should be set a value where the move distance is too minor to be of interest.
Also, the idea of a fine tuning phase is used, as described in the paper. This involves only calculating the edge to node distance energy cost at the end of the algorithm since it is an expensive calculation and it really an 'optimizating' function. fineTuningRadius defines the radius value that, when reached, causes the edge to node distance to be calculated.
There are other special cases that are processed after each iteration. unchangedEnergyRoundTermination defines the number of iterations, after which the layout terminates. If nothing is being moved it is assumed a good layout has been found. In addition to this if no nodes are moved during an iteration the move radius is halved, presuming that a finer granularity is required.
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