def bh_interact(c1, c2, theta):
if c1.get_num_particles() == 0 or c2.get_num_particles() == 0:
return
elif c1.get_num_particles() > 1:
c1_children = c1.get_sub_cells()
for i in c1_children:
bh_interact(i, c2, theta)
elif c2.get_num_particles() == 1:
p1 = c1.particles[iter(c1.indices).next()]
p2 = c1.particles[iter(c2.indices).next()]
p1.f = p1.f.add(common.compute_force(p1.pos, p2.pos, p1.m, p2.m))
return
else:
approximate(c2)
p = c1.particles[iter(c1.indices).next()]
d = math.sqrt(p.pos.distance_r2(c2.center))
s = c2.region.r[0][1] - c2.region.r[0][0]
if s / d < theta:
# sufficiently far away
p.f = p.f.add(common.compute_force(p.pos, c2.center, p.m, c2.m))
pass
else:
# recursively visit sub regions
for i in c2.get_sub_cells():
bh_interact(c1, i, theta)
pass
return
def bh_interact2(c1, c2, theta):
if c2.get_num_particles() == 0:
return
elif c2.get_num_particles() == 1:
p1 = c1.particles[iter(c1.indices).next()]
p2 = c1.particles[iter(c2.indices).next()]
p1.f = p1.f.add(common.compute_force(p1.pos, p2.pos, p1.m, p2.m))
return
else:
# assume this has been called already
#approximate(c2)
p = c1.particles[iter(c1.indices).next()]
d = math.sqrt(p.pos.distance_r2(c2.center))
s = c2.region.r[0][1] - c2.region.r[0][0]
if s / d < theta:
# sufficiently far away
p.f = p.f.add(common.compute_force(p.pos, c2.center, p.m, c2.m))
skip_children()
return
def bh_interact2(c1, c2, theta):
if c2.get_num_particles() == 0:
return
elif c2.get_num_particles() == 1:
p1 = c1.particles[iter(c1.indices).next()]
p2 = c1.particles[iter(c2.indices).next()]
p1.f = p1.f.add(common.compute_force(p1.pos, p2.pos, p1.m, p2.m))
return
else:
# assume this has been called already
# approximate(c2)
p = c1.particles[iter(c1.indices).next()]
d = math.sqrt(p.pos.distance_r2(c2.center))
s = c2.region.r[0][1] - c2.region.r[0][0]
if s / d < theta:
# sufficiently far away
p.f = p.f.add(common.compute_force(p.pos, c2.center, p.m, c2.m))
skip_children()
return
