A : NumPy 2darray
Square N-by-N connection matrix of the network
coords: dict
Nodal coordinates of the graph. Format is
{0: (x, y, z),
{1: (x, y, z),
{2: (x, y, z),
Note that the dictionary has to have N keys.
colorvec : NumPy 1darray
Vector of color-values for each node. This could be nodal strength or modular information of nodes
(i.e., to which module does node i belong to). Thus colorvec has to be of length N and all its
components must be in [0,1].
sizevec : NumPy 1darray
Vector of nodal sizes. This could be degree, centrality, etc. Thus sizevec has to be of length
N and all its components must be >= 0.
labels : list or NumPy 1darray
Nodal labels. Format is [‘Name1’,’Name2’,’Name3’,...] where the ordering HAS to be the same
as in the coords dictionary. Note that the list/array has to have length N.
threshs : list or NumPy 1darray
Thresholds for visualization. Edges with weights larger than threshs[0] are drawn
thickest, weights > threshs[1] are thinner and so on. Note that if threshs[-1]>0 not all
edges of the network are plotted (since edges with 0 < weight < threshs[-1] will be ignored).
lwdths : list or NumPy 1darray
Line-widths associated to the thresholds provided by threshs. Edges with weights larger than
threshs[0] are drawn with line-width lwdths[0], edges with weights > threshs[1]
have line-width lwdths[1] and so on. Thus len(lwdths) == len(threshs).
nodecmap : str
Mayavi colormap to be used for plotting nodes. See Notes for details.
edgecmap : str
Mayavi colormap to be used for plotting edges. See Notes for details.
textscale : float
Scaling factor for labels (larger numbers -> larger text)
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