calculate_nodal_measures doesn't work on graph bundles about scona

[wingedRuslan]

@KirstieJane, this is the GraphBundle's behavior we have right now and I hope @Islast will confirm my below-mentioned explanations.

So, in general, it is a feature 😃
GraphBundle is a dictionary, where value - is the BrainNetwork Graph and key - is the name of the graph. Right now methods like calculate_nodal_measures && report_nodal_measures for this class GraphBundle are not implemented. That's why there are errors saying that these operations (methods) on GraphBundle do not exist.

And to be clear bundleGraphs['real_graph'].calculate_nodal_measures() works as expected too

This works as expected because we take one BrainNetwork Graph (keyed by the name - real_graph]) from a bunch of Graphs (GraphBundle) and perform nodal measures calculation only on this one Graph.
bundleGraphs['real_graph'] returns the BrainNetwork Graph, as this is a single BrainNetwork object we can calculate_nodal_measures().
In your case these 2 lines calculate nodal measures on the same object G10 :

bundleGraphs['real_graph'].calculate_nodal_measures()  
G10.calculate_nodal_measures()

Speaking about calculate_global_measures(), we have report_global_measures that will calculate global measures (if not already calculated) and report the results as a pandas dataframe.

PS. adding the support of calculate_nodal_measures for GraphBundle is pretty straightforward (pseudocode):

for each graph in GraphBundle:
    measures = graph.calculate_nodal_measures()
    store the reported nodal measures of each graph in a dataframe

return dataframe

We can discuss this in details during the next week's meeting if you want to have this functionality ;)