else:
self.body.fc = (0, 1, 0)
def algorithm_0(self):
self.body.cmd_vel(v=0)
def update(self):
self.algorithm_0()
super().update()
# MAIN
if __name__ == '__main__':
name = 'Demo' + strftime("%Y%m%d%H%M", localtime())
s = Space(name, T=RT, limits='')
p = KPIdata(name, 2, TS)
# a big nest in the second quadrant:
bignest = Nest('BigNest',
pos=(uniform(-0.8 * W, -0.2 * W), uniform(0.4 * H,
0.6 * H)),
area=0.02,
fc=(0, 0, 1))
smallnest = Nest('SmallNest',
pos=(uniform(0.8 * W,
0.2 * W), uniform(-0.4 * H, -0.6 * H)),
area=0.04,
fc=(1, 0, 0)) #
s.bodies.append(bignest)
s.bodies.append(smallnest)
N = 100
return np.arctan2((n.pos.y - self.body.pos.y),
(n.pos.x - self.body.pos.x)) - b.th
def rang(self, n):
return np.linalg.norm([(n.pos.y - self.body.pos.y),
(n.pos.x - self.body.pos.x)])
print('avarage: ', avarage)
print(len(neigh))
## MAIN
if __name__ == '__main__':
R = 1 # so goodistance=1 is little less than half R
name = 'Boids_R' + str(R) + '_' + strftime("%Y%m%d%H%M", localtime())
s = Space(name, T=RT, R=R, limits='')
N = 50
s.spawn_bodies(nm=N, room=[(-4, -4), (4, -4), (4, 4), (-4, 4)])
for b in s.bodies:
if isinstance(b, Mobot):
Boid(b, s, 0.7, 0.1 * TS) # ADD YOUR ARGUMENTS
p = KPIdata(name, 5, TS)
KPI = [0, 0, np.sqrt(N), 1, 0]
end = False
while not end:
for b in s.bodies:
if isinstance(b, MoBody):
# Alternative (fraction of tangential component): w = self.k_p * s_y
self.body.cmd_vel(u, w, 0.0)
# Draw the steering vector
self.vertices = [(self.body.pos.x, self.body.pos.y),
(self.body.pos.x + v_steering.x / 2,
self.body.pos.y + v_steering.y / 2)]
super().update()
## MAIN
R = 1.8 # so goodistance=1 is little less than half R
name = 'Boids_R' + str(R) + '_' + strftime("%Y%m%d%H%M", localtime())
s = Space(name, T=RT, R=R, limits='')
# KPI datastruct:
# [0]: Fraction of N still alive (1 means no collision)
# [1]: Fraction of still alive Mobot’s in the largest connected component (1 means all connected)
# [2]: Cohesion radius (maximum distance to centroid) divided by sqrt(N) * ”good distance”
# [3]: Average square (error to “good distance” divided by “good distance”)
# [4]: Effect of steering vector components
# [5]: ...
# [6]: ...
# [7]: ...
#p=KPIdata(name,7,TS)
N = 50
period = 0.1
total_time = 5 * 60
steps = int(total_time / period)
## Version: 20210510 ## Author: Enrique Teruel (ET) [email protected] ## License: CC-BY-SA from time import time_ns, time, localtime, strftime import numpy as np from random import uniform from matplotlib.animation import FFMpegWriter # requires having ffmpeg installed, from https://ffmpeg.org/ from small_worl2d_config import visual, TS, RT, room from small_worl2d import Space, KPIdata, Mobot, Voronoid ## MAIN name = 'BasicVoronoids' + strftime("%Y%m%d%H%M", localtime()) s = Space(name, T=RT, R=0, limits='') # No comm p = KPIdata(name, 1, 2 * TS) s.spawn_bodies(100) # Mobots only for b in s.bodies: if isinstance(b, Mobot): Voronoid( b, s, 5, T=uniform(TS, 2 * TS), Q=room ) # rng=uniform(0.75*np.pi,0.95*np.pi) would be WithoutRearView KPI = [1] end = False while not end: for b in s.bodies: if isinstance(b, Mobot): b.update() s.update_dist() s.remobodies(s.collisions())