Thanks Tamas, This seems to be very easy to use, but I have trouble with the graphics software:
On my Linux desktop when I run 'plot' the script freezes -after a few seconds the CPUs go idle, no output goes to the terminal, no windows open, when I ctrl-c out I also get no information on what the script was doing, it just terminates. I also tried on my OSX laptop, but here I ran into trouble with installing the pycario graphics library interface. I download the source code but './configure' fails with the error: configure: error: cannot find install-sh, install.sh, or shtool in "." "./.." "./../.." I have tried googling for the solution, installed a few suggested libraries with brew but had no success. Any ideas on how to proceed on either of the systems? Jan On 25 February 2015 at 09:32, Tamas Nepusz <[email protected]> wrote: > Hi Jan, > > > I have different datasets- the smallest networks consist of 80 nodes, the > > largest even 10,000 (yes I have a lot of RAM), but I'm happy to only > > visualise the small ones. At the moment I've got a numpy matrix, but I > can > > convert it into a list of lists or anything else that is needed. > > [...] And additionally I have a list (or numpy array) with node labels, > and > > another list with binary values which I would like to use to specify the > node > > colour. > > Then it is probably as simple as: > > import igraph > import numpy > > # ...create your NumPy matrix in m... > > # if you want to keep only edges with a weight above a certain cutoff: > m[m < cutoff] = 0.0 > > # create the graph > g = igraph.Graph.Weighted_Adjacency(m) > > # construct a layout > layout = g.layout_fruchterman_reingold(weights=g.es["weight"]) > > # construct the plot settings > plot_settings = dict( > layout=layout, > edge_width=igraph.rescale(g.es["weight"], out_range=(0.0, 5.0)), > vertex_label=any_list_of_strings, > vertex_color=["red" if value else "blue" for value in > any_list_of_booleans] > ) > > # plot the graph > plot(g, **plot_settings) > > See the documentation of Graph.Weighted_Adjacency(), > Graph.layout_fruchterman_reingold(), Graph.__plot__() and rescale() for > more > information. > > All the best, > Tamas > -- Jan Zaucha Bristol Centre for Complexity Sciences Computational Genomics Group University of Bristol
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