Simulate fish swarming behavior with the model by Iain Couzin et al. Use with caution as I can't seem to replicate some behavior (e.g. the torus swarming).
from couzinswarm import Swarm
swarm = Swarm()
r, v = swarm.simulate(1000)pip install couzinswarm
import numpy as np
import matplotlib.pyplot as pl
from mpl_toolkits.mplot3d import Axes3D
from couzinswarm import Swarm
# note: the dimension of space is measure in fish length,
# such that r = 1 means a length of one fish
swarm = Swarm(
number_of_fish=20,
repulsion_radius=1,
orientation_width=10,
attraction_width=10,
# this angle is given in radians
# up to np.pi (not 360 degrees as in
# the paper)
angle_of_perception=np.pi,
# radians per unit of time
turning_rate=0.1,
# fish lengths per unit of time
speed=0.1,
# in units of fish length
noise_sigma=0.1,
dt=0.1,
# geometry of box
box_lengths=[100,100,100],
# boundary conditions
reflect_at_boundary = [True, True, True],
verbose=False,
)
fig = pl.figure()
ax = fig.add_subplot(111, projection='3d')
N_t = 1000
t = np.arange(N_t+1)
# Note that r.shape = v.shape = ( N_fish, N_t+1, 3 )
positions, directions = swarm.simulate(N_t)
r, v = positions, directions
for i in range(swarm.number_of_fish):
ax.plot(r[i,:,0], r[i,:,1], r[i,:,2])
pl.show()