import networkx as nx
import matplotlib.pyplot as plt
# read in the graph
G = nx.read_gpickle('major_us_cities')
# In[15]:
# draw the graph using the default spring layout
plt.figure(figsize=(10, 9))
nx.draw_networkx(G)
# In[16]:
# See what layouts are available in networkX
[x for x in nx.__dir__() if x.endswith('_layout')]
# In[17]:
# Draw the graph using the random layout
plt.figure(figsize=(10, 9))
pos = nx.random_layout(G)
nx.draw_networkx(G, pos)
# In[18]:
# Draw the graph using the circular layout
plt.figure(figsize=(10, 9))
pos = nx.circular_layout(G)
nx.draw_networkx(G, pos)
# Visualizing Networks
import networkx as nx
import matplotlib.pyplot as plt
# Read the graph
G = nx.read_gpickle('major_us_cities')
# Have a look at the data
print(G.nodes(data=True)[0])
print(G.edges(data=True)[0])
# Have a look at different layouts in networkx
print('Layouts:',
[layout for layout in nx.__dir__() if layout.endswith('_layout')])
#######################################################################################
# ==> 1. Default Spring Layout
plt.figure(figsize=(10, 7))
nx.draw_networkx(G)
# ==> 2. Random Layout
plt.figure(figsize=(10, 7))
nx.draw_networkx(G, pos=nx.random_layout(G))
# ==> 3. Circular layout
plt.figure(figsize=(10, 7))
nx.draw_networkx(G, pos=nx.circular_layout(G))
# ==> 4. Spectral layout