Hi again, Regarding the OSX version I now managed to install cairo, but it doesn't work properly:
Fatal Python error: PyThreadState_Get: no current thread Abort trap: 6 I get the same error when I simply try importing cairo into python. Jan On 27 February 2015 at 14:30, Jan Zaucha <[email protected]> wrote: > 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 > -- Jan Zaucha Bristol Centre for Complexity Sciences Computational Genomics Group University of Bristol
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