I would like to generate a NetworkX graph in a 2D grid with boundaries (100, 100) i.e x-axis ranges from (0,100) and y-axis ranges from (0,100).
import matplotlib.pyplot as plt
import networkx as nx
H = nx.gnm_random_graph(n=8, m=9, seed=5) # generate a random graph
pos = nx.spring_layout(H, iterations=500) # find good positions for nodes
nx.draw(H)
print(pos)
plt.show()
I would like to know how to scale the coordinates of nodes stored in pos
such that all nodes lie within boundary.
One approach is to use the scale and center arguments of nx.spring_layout
pos = nx.spring_layout(H, iterations=500, scale=50, center=(50, 50)) # find good positions for nodes
# verify positions are withing boundaries
positions_array = np.array(list(pos.values()))
print(((0 <= positions_array) & (positions_array <= 100)).all())
Output
True
The corresponding pos result (for one run) was:
{0: array([69.42667319, 77.61143687]), 1: array([81.63688581, 10.64742778]), 2: array([56.9561371, 0. ]), 3: array([71.3536673 , 41.34120577]), 4: array([16.61575096, 54.76920418]), 5: array([17.06331411, 87.49081365]), 6: array([41.68768891, 28.49815199]), 7: array([45.25988262, 99.64175977])}