def substep():
ti.no_activate(x)
for i in x:
r = x[i] - sun
r_sq_inverse = r / r.norm(1e-3)**3
acceleration = (pressure * inv_m[i] - gravity) * r_sq_inverse
v[i] += acceleration * dt
x[i] += v[i] * dt
color[i] *= ti.exp(-dt * color_decay)
if not all(-0.1 <= x[i] <= 1.1):
ti.deactivate(x.snode.parent(), [i])
def substep():
ti.no_activate(x)
for i in x:
r = x[i] - sun
ir = r / r.norm(1e-3)**3
acci = pressure * ir * inv_m[i]
acci += -gravity * ir
v[i] += acci * dt
x[i] += v[i] * dt
color[i] *= ti.exp(-dt * colordeg)
if not all(-0.1 <= x[i] <= 1.1):
ti.deactivate(x.snode.parent(), [i])
def sparse_api_demo():
ti.activate(block1, [0, 1])
ti.activate(block2, [1, 2])
for i, j in x:
print('field x[{}, {}] = {}'.format(i, j, x[i, j]))
# outputs:
# field x[2, 4] = 0
# field x[2, 5] = 0
# field x[3, 4] = 0
# field x[3, 5] = 0
for i, j in block2:
print('Active block2: [{}, {}]'.format(i, j))
# output: Active block2: [1, 2]
for i, j in block1:
print('Active block1: [{}, {}]'.format(i, j))
# output: Active block1: [0, 1]
for j in range(4):
print('Activity of block2[2, {}] = {}'.format(
j, ti.is_active(block2, [1, j])))
ti.deactivate(block2, [1, 2])
for i, j in block2:
print('Active block2: [{}, {}]'.format(i, j))
# output: nothing
for i, j in block1:
print('Active block1: [{}, {}]'.format(i, j))
# output: Active block1: [0, 1]
print(ti.rescale_index(x, block1, ti.Vector([9, 17])))
# output = [2, 4]
# Note: ti.Vector is optional in ti.rescale_index.
print(ti.rescale_index(x, block1, [9, 17]))
# output = [2, 4]
ti.activate(block2, [1, 2])
def clear():
for i in ptr:
ti.deactivate(ptr, i)
def deactivate():
ti.deactivate(ptr, 4)
def clear():
for i in range(n):
ti.deactivate(lst, [i])
def clear():
for i, j in a.parent():
ti.deactivate(a.parent().parent(), [i, j])
def snode_deactivate(b: ti.template()):
for I in ti.grouped(ti.SNode(b.ptr.get_ch(0))):
ti.deactivate(b, I)
def snode_deactivate_dynamic(b: ti.template()):
for I in ti.grouped(b.parent()):
ti.deactivate(b, I)
def clear():
for i in range(n):
ti.deactivate(x.parent(), i)
def clear_temp():
for i, j in x_temp.parent().parent():
ti.deactivate(x_temp.parent().parent(), [i, j])
def clear_particles(self):
self.n_particles[None] = 0
ti.deactivate(self.x.loop_range().parent().snode(), [])
def deact():
ti.deactivate(cell, [5, 10])
def deact():
for i, j in block2:
print(i, j)
if i % 32 == 0:
ti.deactivate(block2, [i, j])
def deactivate_y():
for i in x:
ti.deactivate(y_parent, i)
def deactivate_pointer_fields():
ti.deactivate(p, [1])
ti.deactivate(p, [4])
def deactivate():
ti.deactivate(x.parent().parent(), 4)
def deactivate():
ti.deactivate(a_a, [0])
def clear():
for i in x.parent().parent():
ti.deactivate(x.parent().parent(), i)
def clear():
for i, j in ptr1:
ti.deactivate(ptr1, [i, j])
def clear_temp():
for i, j in ptr2:
ti.deactivate(ptr2, [i, j])
def snode_deactivate(b: ti.template()):
for I in ti.grouped(b):
ti.deactivate(b, I)
def clear_pid():
for i, j, k in voxel_has_particle:
voxel_has_particle[i, j, k] = 0
for i, j, k in ti.ndrange(particle_grid_res * 4, particle_grid_res * 4,
particle_grid_res * 4):
ti.deactivate(pid.parent(), [i, j, k])
