Visualizing agents using Mesa & Networkx - graph

Question

I'm current doing a multi agent path finding using Mesa and Networkx. The nodes represent location where only 1 agent can reside at one point of time. The edges represent distance between the nodes. How do I visualize the moving of agents along the edges at each time step? For example at time step = 4, Agent A is in the middle of edge connecting node 1 and 2.

Answer 1

I guess you want to plot some agent traversing between the nodes using networkx and matplotlib.
import matplotlib.pyplot as plt
import networkx as nx
import matplotlib.animation as animation
import matplotlib
import numpy as np
matplotlib.use('TkAgg')
plt.ion()
H = nx.octahedral_graph() # generate a random graph
pos = nx.spring_layout(H, iterations=200) # find good positions for nodes
In order to do that, first we need to know the position of the agent in each step or frame while traversing. If we assume that there are 50 steps between each node (or on each edge), we can write a generator to update the agent's position in each frame:
def traverse(graph, start, end, steps_between_nodes=50):
"""Generate the new position of the agent.
:param graph: the graph you want to put your agent to traverse on.
:param start: the node to start from.
:param end: the node to end at.
:param steps_between_nodes: number of steps on each edge.
"""
steps = np.linspace(0, 1, steps_between_nodes)
# find the best path from start to end
path = nx.shortest_path(graph, source=start, target=end)
stops = np.empty((0, 2))
for i, j in zip(path[1:], path):
# get the position of the agent at each step
new_stops = steps[..., None] * pos[i] + (1 - steps[..., None]) * pos[j]
stops = np.vstack((stops, new_stops))
for s in stops:
yield s
Then we can animate it as follows:
agent_pos = traverse(H, 1, 4) # make an agent traversing from 1 to 4
def update_position(n):
plt.cla()
nx.draw(H, pos, node_size=700, with_labels=True, node_color='green')
c = plt.Circle(next(agent_pos), 0.05, color='purple', zorder=2, alpha=0.7)
plt.gca().add_patch(c)
ani = animation.FuncAnimation(plt.gcf(), update_position, interval=30, repeat=False)
plt.ioff()
plt.show()
Finally we will have something like this: