Data

Flow Networks

Thousands of pre-computed flow networks are available for download in a number of different archives. Each archive corresponds to a particular parameter setup as indicated by the following two tables. Each archive contains three sub-directories, one for each type of robustness. Within those directories you find thousands of files whose names conform to the following regular expression "sim[0-9]{1-5}_(flow|final).pkl", "flow" or "final" stand for networks after phase one or two of the simulated evolution, respectively. They are Python pickle files and you need our custom analysis package to open and analyse them.

You can obtain all files via the File Manager.

Output Pattern Parameter Setups

Archive Name Input Nodes Output Nodes Activated Output Nodes
standard.tar.bz2 8 8 4
2_activated.tar.bz2 8 8 2
6_activated.tar.bz2 8 8 6
8_activated.tar.bz2 8 8 8
4_input.tar.bz2 4 8 4
6_input.tar.bz2 6 8 4
10_input.tar.bz2 10 8 4
12_input.tar.bz2 12 8 4

Artificial Output Patterns

Archive Name Scalar Complexity
low_complexity.tar.bz2 2.2
equal_complexity.tar.bz2 4.0
equal_spread.tar.bz2 9.3
high_complexity.tar.bz2 12.9

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