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Beautiful networkx graph
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import copy | |
import networkx | |
import matplotlib.pyplot as plt | |
# Generate a graph. | |
# Here I chose an ER graph. | |
g = nx.erdos_renyi_graph(20, 0.3) | |
# Get positions. | |
# Here I use the spectral layout and add a little bit of noise. | |
pos = nx.layout.spectral_layout(g) | |
pos = nx.spring_layout(g, pos=pos, iterations=50) | |
# Create position copies for shadows, and shift shadows | |
pos_shadow = copy.deepcopy(pos) | |
shift_amount = 0.006 | |
for idx in pos_shadow: | |
pos_shadow[idx][0] += shift_amount | |
pos_shadow[idx][1] -= shift_amount | |
#~~~~~~~~~~~~ | |
# Draw graph | |
#~~~~~~~~~~~~ | |
fig = plt.figure(frameon=False) | |
ax = fig.add_axes([0, 0, 1, 1]) | |
ax.axis('off') | |
nx.draw_networkx_nodes(g, pos_shadow, node_color='k', alpha=0.5) | |
nx.draw_networkx_nodes(g, pos, node_color="#3182bd", linewidths=1) | |
nx.draw_networkx_edges(g, pos, width=1) |
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