Thanks for this.
Unfortunately my machine seems to fail with calling state.draw() for interactive visualisation which makes it difficult to understand exactly how this interacts. I am running it from the docker image, on macOS 10.14.16.
Following your instructions on installation page;
docker pull tiagopeixoto/graph-tool xhost +local: docker run -ti -u user -w /home/user --rm -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix tiagopeixoto/graph-tool ipython
from graph_tool.all import * ; import graph_tool.all as gt ; Unable to init server: Could not connect: Connection refused (ipython:1): Gdk-CRITICAL **: 12:54:59.581: gdk_cursor_new_for_display: assertion 'GDK_IS_DISPLAY (display)’ failed (ipython:1): Gdk-CRITICAL **: 12:54:59.598: gdk_cursor_new_for_display: assertion 'GDK_IS_DISPLAY (display)’ failed
g = gt.collection.data["celegansneural”] state = gt.minimize_nested_blockmodel_dl(g) state.draw() RuntimeError: Gtk couldn't be initialized. Use Gtk.init_check() if you want to handle this case.
Do you have a suggestion how to resolve this?
I can of course make use of the output function to review what changes are being made, but it still leaves me a little confused of how I can assign hvprop weightings and call upon them with state.draw.
Alternatively, could you kindly provide an example how to make use of the hvprops, add a set of parameters as weights (such as the eigenvector centrality of hierarchical nodes) and assign this as a propertymap for the output? I’m not sure if such an example is available on your repository, but do correct me if I’m wrong..
Appreciate your guidance!
On 6 Aug 2019, at 10:42, Tiago de Paula Peixoto email@example.com wrote:
Am 05.08.19 um 15:09 schrieb Ruffle, James:
This presumably then needs to be saved as a hvprops(?!). But, I am unclear how to do this, not least in a way that I know for sure that the correct hierarchical vertices within l1state and l2state are aligning to the generated centrality measures of x1 and x2, respectively.
Furthermore, if/when that is achieved, how can I call upon this in drawing, for example to size the level 1 hierarchical vertices according to centrality, or level 2 vertices by another measure, etc.?
If you call state.draw() (which calls draw_hierarchy()), it returns, among other things, the hierarchy tree as a graph. The 'hvprops' should be a dictionary with drawing attributes to that graph. It can contain property maps, which do not need to be owned by the hierarchy tree but need to have the same size.
To get the hang of it, you can call state.draw() once to obtain the hierarchy tree, and then pass values to hvprops to see how that affects the layout.
-- Tiago de Paula Peixoto firstname.lastname@example.org
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