I would like to improve my graph. There are problems as follow:
Appreciate if anyone could give some notes or advices
This is my codes:
Unique_liss= ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm']
edgesList= [('a', 'b'), ('b', 'c '), ('c ', 'd'), ('d', 'e'), ('d', 'f'), ('e', 'g'), ('f', 'g'), ('g', 'h'), ('h', 'i '), ('i ', 'j'), ('j', 'k'), ('j', 'l'), ('k', 'm'), ('l', 'm')]
import networkx as nx
g = nx.DiGraph()
g.add_nodes_from(Unique_liss)
g.add_edges_from(edgesList)
nx.to_pandas_adjacency(g)
G = nx.DiGraph()
for node in edgesList:
G.add_edge(*node,sep=',')
A = nx.adjacency_matrix(G).A
nx.draw(G, with_labels=True, node_size = 2000,
node_color = 'skyblue')
In order to have deterministic node layouts, you can use one of NetworkX's layouts, which allow you to specify a seed
. Here's an example using nx.spring_layout
for the above graph:
from matplotlib import pyplot as plt
seed = 31
pos = nx.spring_layout(G, seed=seed)
plt.figure(figsize=(10,6))
nx.draw(G, pos=pos, with_labels=True, node_size = 1500, node_color = 'skyblue')
You'll get the exact same layout if you re-run the above.
In order to customize the graph size you have several options. The simplest one baing setting the figure size as plt.figure(figsize=(x,y))
as above. And you can also control the size of the graph within the figure using the scale
paramater in nx.spring_layout
.
As per the last point, it looks like you cannot set specific arrow sizes for each edge. From the [docs](arrowsize : int, optional (default=10)) what you have is:
arrowsize : int, optional (default=10)
So you can only set this value to an int
, which will result in an equal size for all edge arrows.