pos = nx.spring_layout(G_test) nx.draw_networkx( G_test, pos=pos, with_labels=False, ) My questions are: I want those edges (cosine similarity) <0.5 to show a different color rather than black. For the nodes, currently I hid the node labels since nodes are the sentences that are too long, I want to ask how I can use shorter labels? Thank you so ...
There is a way to create hierarchical graphs using only NetworkX and matplotlib by using NetworkX 's multipartite_layout(). This layout allows you to create hierarchical graphs by specifying nodes to be in certain subset s which will be columns or rows depending if the align parameter is "horizontal" or "vertical".
I have plot a figure to highlight the gas flow and direction in gas network like enter image description here however, i wish make it interactive. I tried several ways but failed, is there idea to
Given any graph G created in NetworkX, I want to be able to assign some weights to G.edges() after the graph is created. The graphs involved are grids, erdos-reyni, barabasi-albert, and so forth.
from networkx.drawing.nx_pydot import graphviz_layout T = nx.balanced_tree(2, 5) pos = graphviz_layout(T, prog="twopi") nx.draw(T, pos) plt.show() If you adjust the window to make it square, the result is Or, if you prefer a top-down tree, you could replace the string "twopi" in that code with "dot", and if you make the resulting window wider ...
I have a multigraph object and would like to convert it to a simple graph object with weighted edges. I have looked through the networkx documentation and can't seem to find a built in function to
For a complete example you can look at the code of the networkx gallery here. Edit: To fit the name inside the node, you have to play with the node size and font size.
