def fmm_m2l(c1, c2):
c1_grand_parent = get_grand_parent(c1)
c2_grand_parent = get_grand_parent(c2)
if c1_grand_parent != None and c2_grand_parent != None and \
c1_grand_parent == c2_grand_parent:
# reflect long-range interaction force mutually
f = m2l(c1, c2)
c1.l += f
c2.l += -f # actual M2L force calculation look probably different
elif (c1.is_root() and c2.is_root()) or \
c1.get_parent() == c2.get_parent():
for i, j in taco.product(c1.get_sub_cells(), c2.get_sub_cells()):
fmm_m2l(i, j)
def fmm_m2l(c1, c2):
c1_grand_parent = get_grand_parent(c1)
c2_grand_parent = get_grand_parent(c2)
if c1_grand_parent != None and c2_grand_parent != None and \
c1_grand_parent == c2_grand_parent:
# reflect long-range interaction force mutually
f = m2l(c1, c2)
c1.l += f
c2.l += -f # actual M2L force calculation look probably different
elif (c1.is_root() and c2.is_root()) or \
c1.get_parent() == c2.get_parent():
for i, j in taco.product(c1.get_sub_cells(), c2.get_sub_cells()):
fmm_m2l(i, j)
def interact(c1, c2, s):
if c1.get_num_particles() <= s and \
c2.get_num_particles() <= s:
common.direct([c1.particles[i] for i in c1.indices],
[c2.particles[i] for i in c2.indices],
c1.region == c2.region)
else:
if c1.get_num_particles() > s:
c1_children = c1.get_sub_cells()
else:
c1_children = [c1]
if c2.get_num_particles() > s:
c2_children = c2.get_sub_cells()
else:
c2_children = [c2]
for i, j in taco.product(c1_children, c2_children):
interact(i, j, s)
return
def interact(c1, c2, s):
if c1.get_num_particles() <= s and \
c2.get_num_particles() <= s:
common.direct([c1.particles[i] for i in c1.indices],
[c2.particles[i] for i in c2.indices],
c1.region == c2.region)
else:
if c1.get_num_particles() > s:
c1_children = c1.get_sub_cells()
else:
c1_children = [c1]
if c2.get_num_particles() > s:
c2_children = c2.get_sub_cells()
else:
c2_children = [c2]
for i, j in taco.product(c1_children, c2_children):
interact(i, j, s)
return
