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Include small world in plot_network_measures #131
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@KirstieJane I would like to add this measure while I am creating a function to restructure DataFrame obtained from I've run the I am calculating the small coefficient of "Real_Graph" in GraphBundle relative to each other Graph in GraphBundle. On the figure, I need to display eror bar for "Real_Graph" and for random networks - constant value 1. |
@KirstieJane, I've added small_world to network measures |
Ohhhh, plotting is slow, because inside the function I calculate the small coefficient of "real_graph" relative to each other graph in GraphBundle. It is needed to find a way how to store the calculated small world values and then inside the function simply access this data. |
At the moment plot_network_measures only includes assortativity, clustering, shortest path length, efficiency and modularity.
It really should also include the small world coefficient.
On thing that's important to note is that the small world coefficient is calculated for the real graph compared to each of the random graphs.
This means that - in comparison to the other measures - the variability will be on the "blue" bars - the bars representing the real graphs - rather than the grey ones (the random graphs).
That bar should be set to exactly 1.
The command:
bundleGraphs.report_small_world("real_graph")
returns a dictionary with keysreal_graph_R0
,real_graph_R1
,real_graph_R2
etc. These correspond to the comparison of the graph labelled "real_graph" with R0 (itself), R1, R2 etc.Another thing to note is that I don't think the small world measures are saved as part of the graph bundle after they've been calculated. It might be interesting to see if we can make it so you only have to run it once (similar to making random graphs etc).
(This might be better as its own issue, just shout if that's the case.)
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