How Can One Modify the Outline Color of a Node in Networkx

How can one modify the outline color of a node In networkx?

UPDATE (3/2019): as of networkx 2.1, the kwargs are forwarded from draw(), so you should be able to simply call draw() with the edge_color kwarg.

Ok, this is kind of hacky, but it works. Here's what I came up with.

The Problem

networkx.draw() calls networkx.draw_networkx_nodes(), which then calls pyplot.scatter() to draw the nodes. The problem is that the keyword args accepted by draw_networkx_nodes() aren't passed on to scatter(). (source here)

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To solve this, I basically broke apart networkx.draw() into its components: draw_networkx_nodes, draw_networkx_edges, and draw_networkx_labels.

The Solution

We can take the return value of draw_networkx_nodes() -- a PathCollection -- and operate on that: you can use PathCollection.set_edgecolor() or PathCollection.set_edgecolors() with either a color or a list, respectively.

Example code:

from networkx import *
import matplotlib.pyplot as plt
G = Graph()
G.add_node(1)
# Need to specify a layout when calling the draw functions below
# spring_layout is the default layout used within networkx (e.g. by `draw`)
pos = spring_layout(G)
nodes = draw_networkx_nodes(G, pos)
# Set edge color to red
nodes.set_edgecolor('r')
draw_networkx_edges(G, pos)
# Uncomment this if you want your labels
## draw_networkx_labels(G, pos)
plt.show()

If you're going to be using this a lot, it probably makes more sense (IMO) to just redefine draw_networkx_nodes to actually pass the kwargs to scatter. But the above will work.

To remove the marker edges entirely, simply set the color to None instead of 'r'.

Networkx, changing node colors

Something like this could works:

import networkx as nx
import matplotlib.pyplot as plt
M = nx.erdos_renyi_graph(10, 2)
color = []
for node in M:
    if node > 1:
        color.append('red')
    else:
        color.append('green')
nx.draw(M, node_color=color)
plt.show()

Here the application with your example

import numpy as np
import matplotlib.pyplot as plt
from random import randint
import networkx as nx

N = 10 #Lattice Size

#Random Coordinate Generator
def random(m, n):
    seen = set()

    x, y = randint(m, n), randint(m, n)

    while True:
        seen.add((x, y))
        yield (x, y)
        x, y = randint(m, n), randint(m, n)
        while (x, y) in seen:
            x, y = randint(m, n), randint(m, n)


#Generates Lattice
G=nx.grid_2d_graph(N,N)
pos = dict( (n, n) for n in G.nodes() )
labels = nx.get_node_attributes(G, 'status')
G.add_nodes_from(G.nodes,status='1')

#Change Node attribute
num_nodes=N*N
half=int(num_nodes/2)
decaying = [0]*half
a=random(0,N-1)

for i in range(half):
    cor=next(a)
    decaying[i]=cor
for j in range(half):
    a=decaying[j]
    G.add_node(a, status='0')

node_color = []
for status in  list(nx.get_node_attributes(G, 'status').values()):
    if status == '1':
        node_color.append('red')
    else:
        node_color.append('green')
#Plot nodes
labels = nx.get_node_attributes(G, 'status')
nx.draw(G,pos=pos,node_color=node_color, labels=labels,node_size=200)

plt.show()

Change Edge color in NetworkX Graph depending on what edges has been visisted by Dijkstras algorithm

Try adding edge_color to nx.draw()

import networkx as nx
import matplotlib.pyplot as plt

G = nx.karate_club_graph()

nodes = G.nodes()

position = nx.spring_layout(G)
color = {"Mr. Hi": "#3DA3F5", "Officer": "#E0D91B"}
dijkstra_route = nx.dijkstra_path(G, 24, 16)

colors = ["red" if n in dijkstra_route else color[G.nodes[n]["club"]] for n in nodes]

dijkstra_edges = []
for index in range(0, len(dijkstra_route) - 1):
   edge = (dijkstra_route[index], dijkstra_route[index + 1])
   dijkstra_edges.append(edge)

edge_colors = ["red" if edge in dijkstra_edges else "black" for edge in G.edges()]


nx.draw(G, position, node_color=colors, edge_color=edge_colors, with_labels=True)
plt.show()

shows this, which is close to what you want, although I can't figure out why edge (31,0) isn't colored

Coloring specific nodes in networkx

You can draw your nodes in groups based on color similar to the example they provide. With each group that you draw, just specify node_color to the color that you want.

import networkx as nx

G = nx.cubical_graph()
pos = nx.spring_layout(G)

nodes = {
    'r': [1, 3, 5],
    'b': [0, 2],
    'g': [4]
}
for node_color, nodelist in nodes.items():
    nx.draw_networkx_nodes(G, pos, nodelist=nodelist, node_color=node_color)

labels = {x: x for x in G.nodes}
nx.draw_networkx_labels(G, pos, labels, font_size=16, font_color='w')

Python NetworkX -- set node color automatically based on number of attribute options

Here is an example of how to use a colormap. It's a little tricky. If you want a customized discrete colormap you can try this SO answer Matplotlib discrete colorbar

import matplotlib.pyplot as plt
# create number for each group to allow use of colormap
from itertools import count
# get unique groups
groups = set(nx.get_node_attributes(g,'group').values())
mapping = dict(zip(sorted(groups),count()))
nodes = g.nodes()
colors = [mapping[g.node[n]['group']] for n in nodes]

# drawing nodes and edges separately so we can capture collection for colobar
pos = nx.spring_layout(g)
ec = nx.draw_networkx_edges(g, pos, alpha=0.2)
nc = nx.draw_networkx_nodes(g, pos, nodelist=nodes, node_color=colors, 
                            with_labels=False, node_size=100, cmap=plt.cm.jet)
plt.colorbar(nc)
plt.axis('off')
plt.show()

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