I m trying to make an interactive graph on plotly, where I first create the network graph using networkx, and then graph it with plotly so that it can be hosted and be interative and shared, very similar to what's described here: https://plotly.com/python/network-graphs/
I would like to make the edges curved -- in networkx I can do this with connectionstyle="arc3,rad=-0.3". How do I do this in Plotly?
My main problem is that edges are overlapping, I want to remove that overlapping if there is any better option please suggest but restricted to plotly only.
I searched in documentations of go.scatter too but didn't found anything relevant to my query.
NetworkX is powerful but I was trying to plot a graph which shows node labels by default and I was surprised how tedious this seemingly simple task could be for someone new to Networkx. There is an example which shows how to add labels to the plot.
https://networkx.github.io/documentation/latest/examples/drawing/labels_and_colors.html
The problem with this example is that it uses too many steps and methods when all I want to do is just show labels which are same as the node name while drawing the graph.
# Add nodes and edges
G.add_node("Node1")
G.add_node("Node2")
G.add_edge("Node1", "Node2")
nx.draw(G) # Doesn't draw labels. How to make it show labels Node1, Node2 along?
Is there a way to make nx.draw(G) show the default labels (Node1, Node2 in this case) inline in the graph?
tl/dr: just add with_labels=True to the nx.draw call.
The page you were looking at is somewhat complex because it shows how to set lots of different things as the labels, how to give different nodes different colors, and how to provide carefully control node positions. So there's a lot going on.
However, it appears you just want each node to use its own name, and you're happy with the default color and default position. So
import networkx as nx
import pylab as plt
G=nx.Graph()
# Add nodes and edges
G.add_edge("Node1", "Node2")
nx.draw(G, with_labels = True)
plt.savefig('labels.png')
If you wanted to do something so that the node labels were different you could send a dict as an argument. So for example,
labeldict = {}
labeldict["Node1"] = "shopkeeper"
labeldict["Node2"] = "angry man with parrot"
nx.draw(G, labels=labeldict, with_labels = True)
I feel a better answer is not to use networkx to draw. They explicitly warn you that graph visualization is hard and networkx is mainly meant for graph analysis (from https://networkx.org/documentation/stable/reference/drawing.html#module-networkx.drawing.layout):
Drawing
NetworkX provides basic functionality for visualizing graphs, but its main goal is to enable graph analysis rather than perform graph visualization. In the future, graph visualization functionality may be removed from NetworkX or only available as an add-on package.
Proper graph visualization is hard, and we highly recommend that people visualize their graphs with tools dedicated to that task. Notable examples of dedicated and fully-featured graph visualization tools are Cytoscape, Gephi, Graphviz and, for LaTeX typesetting, PGF/TikZ. To use these and other such tools, you should export your NetworkX graph into a format that can be read by those tools. For example, Cytoscape can read the GraphML format, and so, networkx.write_graphml(G, path) might be an appropriate choice.
thus my suggestion is to transform the graph to some format that has dedicated software for graph visualization and then draw (e.g. pydot, pygraphviz, graphviz etc). My suspicion is that pydot and pygraphviz are the best for some reason since networkx only supports those two. It seems from the docs in pygraphviz that it has a similar api so it might be the easiest to use if you already want like to use networkx (https://pygraphviz.github.io/documentation/stable/tutorial.html):
The API is very similar to that of NetworkX. Much of the NetworkX tutorial at https://networkx.org/documentation/latest/tutorial.html is applicable to PyGraphviz. See http://pygraphviz.github.io/documentation/latest/reference/api_notes.html for major differences.
In addition, pydot as of now does not really have docs (which personally bothers me. Idk if it's that it doesn't look nice on my browser or that it makes me feel that project is not being taken seriously by it's developers idk something just doesn't feel right even if it has a higher set of users pydot 15k vs pygraphviz 4k) reference: https://github.com/pydot/pydot/pull/241.
Also it seems that pygraphviz has more granular control than regular graphviz ref: Graphviz vs PyGraphViz. In addition, I don't know how to convert a networkx directly to a graphviz obj (since graphviz has the best docs and highest user base ~19k so I did prefer that), so I will go with pygraphviz for those reasons. Pygravix also has docs which although small make me happy (though not as good as graphviz but idk how to make graphviz graphs from networkx). It's hard to make these decisions but I can't stay on this forever and this seems mindful enough. Also, networkx is nice because I can transform dgl graphs to networkx too (and the relabeling was simple).
Considering those reasons let me give you the example code I wrote that does what you want using pygraphviz (but you could do it with pydot if you figured out how, transforming to pydot obj is trivial using networkx see my previous link):
# https://stackoverflow.com/questions/28533111/plotting-networkx-graph-with-node-labels-defaulting-to-node-name
import dgl
import numpy as np
import torch
import networkx as nx
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from pathlib import Path
g = dgl.graph(([0, 0, 0, 0, 0], [1, 2, 3, 4, 5]), num_nodes=6)
print(f'{g=}')
print(f'{g.edges()=}')
# Since the actual graph is undirected, we convert it for visualization purpose.
g = g.to_networkx().to_undirected()
print(f'{g=}')
# relabel
int2label = {0: "app", 1: "cons", 2: "with", 3: "app3", 4: "app4", 5: "app5"}
g = nx.relabel_nodes(g, int2label)
# https://networkx.org/documentation/stable/reference/drawing.html#module-networkx.drawing.layout
g = nx.nx_agraph.to_agraph(g)
print(f'{g=}')
print(f'{g.string()=}')
# draw
g.layout()
g.draw("file.png")
# https://stackoverflow.com/questions/20597088/display-a-png-image-from-python-on-mint-15-linux
img = mpimg.imread('file.png')
plt.imshow(img)
plt.show()
# remove file https://stackoverflow.com/questions/6996603/how-to-delete-a-file-or-folder
Path('./file.png').expanduser().unlink()
# import os
# os.remove('./file.png')
output:
g=Graph(num_nodes=6, num_edges=5,
ndata_schemes={}
edata_schemes={})
g.edges()=(tensor([0, 0, 0, 0, 0]), tensor([1, 2, 3, 4, 5]))
g=<networkx.classes.multigraph.MultiGraph object at 0x7f8443e94250>
g=<AGraph <Swig Object of type 'Agraph_t *' at 0x7f846117a930>>
g.string()='graph "" {\n\tapp -- cons [key=0,\n\tid=0];\napp -- with [key=0,\nid=1];\napp -- app3 [key=0,\nid=2];\napp -- app4 [key=0,\nid=3];\napp -- app5 [key=0,\nid=4];\n}\n'
though I want to leave this link about pydot visualization since it seems very useful in general: Display graph without saving using pydot and probably provides the pydot answer for others if they need it. Though, I'd love to see arguments in favour of pydot.
Edit1: if you want to plot by attributed and not by label, see this answer: NetworkX node attribute drawing note that relabeling the way I suggested does not always have the intended semantics (e.g. it might join two nodes that were NOT meant to be joined).
Edit2: if you want to plot the attribute instead without self loops happening by accident see this answer: Draw more information on graph\nodes using PyGraphviz
I have a graph built with networkx and graphviz in Python using pygraphviz and networkx's graphviz_layout it is then displayed in Plotly.
I wish to change the space between nodes of the graph.
I currently have the graph displayed in plotly like this:
However, when I try to use args on the graph to change the distance between nodes like so:
pos=graphviz_layout(G,prog='dot',args='-Gnodesep="10.0" -Granksep="1.0"')
I do not see any changes on the plotly plot. Am I doing something wrong with the args?
I am having trouble with large graph visualization in python and networkx. The graph is wish to visualize is directed, and has an edge and vertex set size of 215,000 From the documenation (which is linked at the top page) it is clear that networkx supports plotting with matplotlib and GraphViz. In matplotlib and networkx the drawing is done as follows:
import
networkx as nx
import matplotlib.pyplot as plt
#Let g be a graph that I created
nx.draw(g)
I get a memory error after nx.draw(g), afterwards you would normally do plt.show() or plt.[some_function] to save the file in a format for efficient and so forth.
Next I tried GraphViz. From the wikipedia page the dot format is used for directed graphs and I created a dot file:
nx.write_dot(g, "g.dot")
This worked well and I had a dot file in my current directory that is 12 megabytes. Next I ran the dot program (part of graphviz to create a postscript file):
dot -Tps g.dot -o g.ps
This slows down my computer, runs for a few minutes and then display Killed in the terminal. So it never could execute... While reading the documentation for graphviz it seems that only undirected graphs were supported for large graph visualization.
Question:
With these two unsuccessful attempts can anyone show me how to visualize my large graph using python and networkx with about 215,000 vertices and 215,000 edges? I suspect as with Graphviz I will have to output into an intermediate format (although this shouldn't be that hard it won't be as easy as a builtin function) and then use another tool to read the intermediate format and then output a visualization.
So, I am looking for the following:
Output graph from networkx into an intermediate format
With new package/software/tool (ideally python-interactive) read intermediate format and visualize the large graph
If you need more information let me know!
from matplotlib import pylab
import networkx as nx
def save_graph(graph,file_name):
#initialze Figure
plt.figure(num=None, figsize=(20, 20), dpi=80)
plt.axis('off')
fig = plt.figure(1)
pos = nx.spring_layout(graph)
nx.draw_networkx_nodes(graph,pos)
nx.draw_networkx_edges(graph,pos)
nx.draw_networkx_labels(graph,pos)
cut = 1.00
xmax = cut * max(xx for xx, yy in pos.values())
ymax = cut * max(yy for xx, yy in pos.values())
plt.xlim(0, xmax)
plt.ylim(0, ymax)
plt.savefig(file_name,bbox_inches="tight")
pylab.close()
del fig
#Assuming that the graph g has nodes and edges entered
save_graph(g,"my_graph.pdf")
#it can also be saved in .svg, .png. or .ps formats
This answers your first issue.
Networkx does not have the facility to zoom into nodes. Use Gephi for this functionality.
Gephi accepts an edge list in CSV format and produces a visualization, where zooming can be done interactively.
I try to draw multigraph in Python using graphviz.
For now I can draw usual graphs in Python somehow like:
import pygraphviz as pgv
G=pgv.AGraph()
G.add_node('a')
G.add_node('b')
G.layout()
G.add_edge('a','b','first')
G.add_edge('a','b','second')
sorted(G.edges(keys=True))
G.draw('file.png')
And I get on the output:
But actually I want get multigraph, i.e.
But documentation stays that it should differentiate :
I have no idea about drawing multigraph but not just graph.
Thanks for any help.
Addition:
it seems that there are no yet such libraries in python that can do it, so I did it using Wolfram Mathematica. But question is still opened.
Addition
Now working code looks so:
import pygraphviz as pgv
G=pgv.AGraph(strict=False)
G.add_node('a')
G.add_node('b')
G.layout()
G.add_edge('a','b','first')
G.add_edge('a','b','second')
sorted(G.edges(keys=True))
G.draw('file.png')
As the documentation you quoted says, you need to specify strict=False when creating a multi-edge graph. Since you didn't do this your graph doesn't support parallel edges.