Description Usage Arguments Details Value Author(s) References See Also Examples
Given a correlations thingy as produced by const.cor.list
,
produce a list of adjacency matrices fiddled to have a preferred number of edges
Actually this is not quite possible, but come as close as choose.thresh.nbedges
will allow us. A functional parameter allows us to say things like produce the graphs with n log n edges where n is the number of nodes
1 2 3 | correlations.to.adjacencies(correlations, edge.func)
ideal.wavelet.levels(brain)
distance(x,y,z)
|
correlations |
a list of correlation matrices produced by |
edge.func |
a function to mention the way to choose the number of edges given the number of nodes in the graph. In the companion scripts files, the small-limit is used and by default |
brain |
matrix containing the data time series. Each column of the matrix represents one time series. |
x |
x coordinate |
y |
y coordinate |
z |
z coordinate |
Functions produced to manipulate better nice outputs of the package
correlations.to.adjacencies |
Description of 'comp1' |
ideal.wavelets.levels |
number indicating up to each wavelet scale it is possible to go given the length of the time series |
disctance |
the euclidean distance in 3D |
John Aspden, external collaborator of the brainwaver package
S. Achard, R. Salvador, B. Whitcher, J. Suckling, Ed Bullmore (2006) A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs. Journal of Neuroscience, Vol. 26, N. 1, pages 63-72.
1 2 3 4 5 6 7 8 |
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