I generated a graph with networkx
import networkx as nx
s = 5
G = nx.grid_graph(dim=[s,s])
nodes = list(G.nodes)
edges = list(G.edges)
p = []
for i in range(0, s):
for j in range(0, s):
p.append([i,j])
for i in range(0, len(nodes)):
G.nodes[nodes[i]]['pos'] = p[i]
pos = {}
for i in range(0, len(nodes)):
pos[nodes[i]] = p[i]
nx.draw(G, pos)
Now I would like to assign a value to each node between 0
and 4
from random import randint
val = []
for i in range(0, len(G.nodes())):
val.append(randint(0,4))
And I would like to assign the color to each node base on the val
list and plot something like shown here
nbunch. An nbunch is a single node, container of nodes or None (representing all nodes). It can be a list, set, graph, etc.. To filter an nbunch so that only nodes actually in G appear, use G.
Due to its dependence on a pure-Python "dictionary of dictionary" data structure, NetworkX is a reasonably efficient, very scalable, highly portable framework for network and social network analysis.
networkx.draw
has the node_color, vmin, vmax and cmap parameters:
cmap (Matplotlib colormap, optional (default=None)) – Colormap for mapping intensities of nodes
vmin,vmax (float, optional (default=None)) – Minimum and maximum for node colormap scaling
node_color (color string, or array of floats, (default=’#1f78b4’)) – Node color. Can be a single color format string, or a sequence of colors with the same length as nodelist. If numeric values are specified they will be mapped to colors using the cmap and vmin,vmax parameters. See matplotlib.scatter for more details.
You can write a list in it so your nodes will be colored (for example):
colors = [i/len(G.nodes) for i in range(len(G.nodes))]
...
...
nx.draw(G, pos, node_color=colors)
To set a node property, you can use:
nx.set_node_attributes(G, val, 'val')
Networkx draw calls down to draw_networkx_nodes, this takes a cmap and color list, so all you would have to do would be something like:
nx.draw(G, pos, node_color = nx.get_node_attributes(G,'val'), vmin=0, vmax=4, cmap = plt.cm.get_cmap('rainbow'))
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