Comments (3)
@KirstieJane I would like to add this measure while I am creating a function to restructure DataFrame obtained from GraphBundle.report_global_measures()
to an acceptable DataFrame for seaborn.barplot.
I've run the GraphBundle.report_small_world
.
Did I understand the results correctly?
I am calculating the small coefficient of "Real_Graph" in GraphBundle relative to each other Graph in GraphBundle.
So, the small coefficient for "Real_Graph" and "Real_Graph_R0" is 1.6565, for "Real_Graph" and "Real_Graph_R1" is 1.6507 and so on.
On the figure, I need to display eror bar for "Real_Graph" and for random networks - constant value 1.
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@KirstieJane, I've added small_world to network measures
Do you like it?
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Ohhhh, plotting is slow, because inside the function I calculate the small coefficient of "real_graph" relative to each other graph in GraphBundle.
small_world = bundleGraphs.report_small_world(real_network)
It is needed to find a way how to store the calculated small world values and then inside the function simply access this data.
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Related Issues (20)
- Add padding to the colorbar at the bottom HOT 3
- calculate_nodal_measures doesn't work on graph bundles HOT 1
- Pad random graphs with 0s so they are in the right order HOT 4
- Set seed for Erdos Renyi graph in plot degree distribution HOT 4
- Which version of nilearn do we need? HOT 1
- Cut covars columns from residuals matrix HOT 1
- feature request: tell brainbundle the total number of brains you want
- Catch error if name of graph doesn't exist in brain bundle for plot_rich_club HOT 4
- Adjust legend of plot_rich_club HOT 3
- small_world calculations HOT 1
- Nodal measures for plotting with nilearn HOT 5
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- View Connectome with nilearn HOT 5
- Error with nilearn.plot_connectome HOT 1
- Test for visualisations HOT 1
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- View_corr_mat() - make new || leave old HOT 5
- Make new get_anatomical_layouts() function HOT 1
- Two similar tutorials HOT 1
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