def bubble():
"""
Pseudo bubble simulation
"""
steps = 1000000
dt = 0.01
r_min = 1.5
rand_c = rc.RandCluster()
pset = ps.ParticlesSet(1000)
rand_c.insert3(X=pset.X,
M=pset.M,
start_indx=0,
n=pset.size,
radius=5.0,
mass_rng=(0.5, 0.8),
r_min=0.0)
bubble = pb.PseudoBubble(pset.size, pset.dim, Consts=(r_min, 10))
constf = cf.ConstForce(pset.size, dim=pset.dim, u_force=[0, 0, -10])
drag = dr.Drag(pset.size, pset.dim, Consts=0.01)
multif = mf.MultipleForce(pset.size, pset.dim)
multif.append_force(bubble)
multif.append_force(constf)
multif.append_force(drag)
multif.set_masses(pset.M)
#solver = els.EulerSolver( multif , pset , dt )
#solver = lps.LeapfrogSolver( lennard_jones , pset , dt )
solver = svs.StormerVerletSolver(multif, pset, dt)
#solver = rks.RungeKuttaSolver( lennard_jones , pset , dt )
#solver = mds.MidpointSolver( lennard_jones , pset , dt )
bound = rb.ReboundBoundary(bound=(-5.0, 5.0))
pset.set_boundary(bound)
a = aogl.AnimatedGl()
a.ode_solver = solver
a.pset = pset
a.steps = steps
a.build_animation()
a.start()
return
def fountain():
"""
Fountain demo
"""
steps = 10000000
dt = 0.01
pcnt = 250000
pset = ps.ParticlesSet(pcnt)
pset.M[:] = 0.1
pset.X[:, 2] = 0.7 * np.random.rand(pset.size)
grav = cf.ConstForce(pset.size, dim=pset.dim, u_force=(0.0, 0.0, -10.0))
drag = dr.Drag(pset.size, dim=pset.dim, Consts=0.01)
multi = mf.MultipleForce(pset.size, dim=pset.dim)
multi.append_force(grav)
multi.append_force(drag)
multi.set_masses(pset.M)
solver = mds.MidpointSolver(multi, pset, dt)
solver.update_force()
default_pos.sim_time = solver.get_sim_time()
bd = (-100.0, 100.0, -100.0, 100.0, 0.0, 100.0)
bound = db.DefaultBoundary(bd, dim=3, defualt_pos=default_pos)
pset.set_boundary(bound)
a = aogl.AnimatedGl()
a.ode_solver = solver
a.pset = pset
a.steps = steps
a.draw_particles.set_draw_model(a.draw_particles.DRAW_MODEL_VECTOR)
a.init_rotation(-80, [0.7, 0.05, 0])
a.build_animation()
a.start()
return
def build_animation(self):
self.steps = 6000
dt = 0.004
self.ip = 1
self.pset = ps.ParticlesSet(2, 3)
self.pset.M[:] = 1.0
self.pset.V[:] = 0.0
self.pset.X[0, :] = 0.0
self.pset.X[1, :] = 1.0 / np.sqrt(3)
ci = np.array([0])
cx = np.array([0.0, 0.0, 0.0])
costrs = csx.ConstrainedX(self.pset)
costrs.add_x_constraint(ci, cx)
self.t = np.zeros((self.steps))
self.x = np.zeros((self.steps, self.pset.dim))
self.xn = np.zeros((self.steps, self.pset.dim))
spring = ls.LinearSpring(self.pset.size, self.pset.dim, Consts=1.0)
damp = da.Damping(self.pset.size, self.pset.dim, Consts=0.5)
multi = mf.MultipleForce(self.pset.size)
multi.append_force(spring)
multi.append_force(damp)
multi.set_masses(self.pset.M)
self.odes = dict()
self.odes["Euler "] = els.EulerSolverConstrained(
multi, self.pset, dt, costrs)
self.odes["Runge Kutta"] = rks.RungeKuttaSolverConstrained(
multi, self.pset, dt, costrs)
self.odes["Leap Frog "] = lps.LeapfrogSolverConstrained(
multi, self.pset, dt, costrs)
self.odes["MidPoint "] = mps.MidpointSolverConstrained(
multi, self.pset, dt, costrs)
self.odes["Verlet "] = svs.StormerVerletSolverConstrained(
multi, self.pset, dt, costrs)
def build_animation(self):
self.steps = 3000
self.pset = ps.ParticlesSet(1, 3)
self.ip = 0
self.pset.M[:] = 1.0
self.pset.V[:] = 0.0
self.t = np.zeros((self.steps))
self.x = np.zeros((self.steps, self.pset.dim))
self.xn = np.zeros((self.steps, self.pset.dim))
constf = cf.ConstForce(self.pset.size,
u_force=[0, 0, -10.0],
dim=self.pset.dim)
drag = dr.Drag(self.pset.size, Consts=1.0)
multi = mf.MultipleForce(self.pset.size)
multi.append_force(constf)
multi.append_force(drag)
multi.set_masses(self.pset.M)
dt = 0.001
self.odes = dict()
self.odes["Euler "] = els.EulerSolver(multi, self.pset, dt)
self.odes["Runge Kutta"] = rks.RungeKuttaSolver(multi, self.pset, dt)
self.odes["Leap Frog "] = lps.LeapfrogSolver(multi, self.pset, dt)
self.odes["MidPoint "] = mps.MidpointSolver(multi, self.pset, dt)
self.odes["Verlet "] = svs.StormerVerletSolver(
multi, self.pset, dt)
def fountain():
"""
Fountain demo
"""
steps = 10000000
dt = 0.005
pcnt = 100000
fl = True
if test_pyopencl():
print("OpenCL is installed and enabled ")
print(" Try, at least, 200000 particles ")
while fl:
try:
print(" ")
pcnt = int(raw_input('How many particles: '))
except:
print("Please insert a number! ")
else:
fl = False
pset = ps.ParticlesSet(pcnt, dtype=np.float32)
pset.M[:] = 0.1
pset.X[:, 2] = 0.7 * np.random.rand(pset.size)
grav = cf.ConstForce(pset.size, dim=pset.dim, u_force=(0.0, 0.0, -10.0))
occx = None
if test_pyopencl():
occx = occ.OpenCLcontext(
pset.size, pset.dim,
(occ.OCLC_X | occ.OCLC_V | occ.OCLC_A | occ.OCLC_M))
drag = dr.DragOCL(pset.size,
dim=pset.dim,
Consts=0.01,
ocl_context=occx)
else:
drag = dr.Drag(pset.size, dim=pset.dim, Consts=0.01)
multi = mf.MultipleForce(pset.size, dim=pset.dim)
multi.append_force(grav)
multi.append_force(drag)
multi.set_masses(pset.M)
#solver = mds.MidpointSolver( multi , pset , dt )
if test_pyopencl():
solver = els.EulerSolverOCL(multi, pset, dt, ocl_context=occx)
else:
solver = els.EulerSolver(multi, pset, dt)
solver.update_force()
default_pos.sim_time = solver.get_sim_time()
bd = (-100.0, 100.0, -100.0, 100.0, 0.0, 100.0)
bound = db.DefaultBoundary(bd, dim=3, defualt_pos=default_pos)
pset.set_boundary(bound)
a = aogl.AnimatedGl()
a.ode_solver = solver
a.pset = pset
a.steps = steps
a.draw_particles.set_draw_model(a.draw_particles.DRAW_MODEL_VECTOR)
a.init_rotation(-80, [0.7, 0.05, 0])
a.build_animation()
a.start()
return
def spring_constr():
"""
Constrained catenary springs demo
"""
dt = 0.01
steps = 1000000
K = 60
x = list([])
m = list([])
#v = list([])
d = 0.1
ar = np.arange(-4.0, 4.0 + d, d)
for i in ar:
x.append(list([i, i, 3.0]))
m.append(list([1.0 / float(len(ar))]))
#v.append( list([0.0]) )
pset = ps.ParticlesSet(len(ar), 3)
pset.X[:] = np.array(x, np.float64)
pset.M[:] = np.array(m, np.float64)
pset.V[:] = 0.0
pset.X[10:12, 2] = 4
pset.X[15:20, 1] = 4
#pset.X[10:15,1] = 6
ci = np.array([0, len(ar) - 1])
cx = np.array([[-4.0, -4.0, 3.0], [4.0, 4.0, 3.0]])
f_conn = list([])
for i in range(len(ar) - 1):
f_conn.append(list([i, i + 1]))
f_conn = np.array(f_conn, np.float64)
costrs = csx.ConstrainedX(pset)
costrs.add_x_constraint(ci, cx)
fi = cfi.ConstrainedForceInteractions(pset)
fi.add_connections(f_conn)
spring = lsc.LinearSpringConstrained(pset.size,
pset.dim,
pset.M,
Consts=K,
f_inter=fi)
constf = cf.ConstForce(pset.size, dim=pset.dim, u_force=[0, 0, -10])
drag = dr.Drag(pset.size, pset.dim, Consts=0.003)
#damp = da.Damping( pset.size , pset.dim , Consts=0.003 )
multif = mf.MultipleForce(pset.size, pset.dim)
multif.append_force(spring)
multif.append_force(constf)
multif.append_force(drag)
multif.set_masses(pset.M)
solver = els.EulerSolverConstrained(multif, pset, dt, costrs)
#solver = lpc.LeapfrogSolverConstrained( multif , pset , dt , costrs )
#solver = svc.StormerVerletSolverConstrained( multif , pset , dt , costrs )
#solver = rkc.RungeKuttaSolverConstrained( multif , pset , dt , costrs )
#solver = mdc.MidpointSolverConstrained( multif , pset , dt , costrs )
a = aogl.AnimatedGl()
pset.enable_log(True, log_max_size=1000)
a.trajectory = False
a.trajectory_step = 1
a.ode_solver = solver
a.pset = pset
a.steps = steps
a.init_rotation(-80, [0.7, 0.05, 0])
a.build_animation()
a.start()
return
def springs():
"""
Springs demo
"""
dt = 0.02
steps = 1000000
G = 0.5
pset = ps.ParticlesSet(3, 3, label=True)
pset.label[0] = "1"
pset.label[1] = "2"
pset.label[2] = "3"
pset.X[:] = np.array([
[2.0, 4.0, 1.0], # 1
[-2.0, -2.0, 1.0], # 2
[3.0, -3.0, 2.0] # 3
])
pset.M[:] = np.array([[1.0], [1.0], [1.5]])
pset.V[:] = np.array([[0., 0., 0.], [0., 0, 0.], [0., 0, 0.]])
springs = ls.LinearSpring(pset.size, Consts=G)
constf = cf.ConstForce(pset.size, u_force=[0, 0, -1.5])
drag = dr.Drag(pset.size, Consts=0.2)
mlf = mf.MultipleForce(pset.size, 3)
mlf.append_force(springs)
#mlf.append_force( constf )
#mlf.append_force( drag )
pot = epe.ElasticPotentialEnergy(pset, springs)
ken = ke.KineticEnergy(pset, springs)
tot = te.TotalEnergy(ken, pot)
#
pot.update_measure()
ken.update_measure()
tot.update_measure()
#
#print( "Potential = %f " % pot.value() )
#print( "Kinetic = %f " % ken.value() )
#P = mm.MomentumParticles( pset , subset=np.array([1,2]) , model="part_by_part")
#
#P.update_measure()
#
#print( P.value() )
bound = rb.ReboundBoundary(bound=(-10, 10))
pset.set_boundary(bound)
mlf.set_masses(pset.M)
springs.set_masses(pset.M)
springs.update_force(pset)
mlf.update_force(pset)
#solver = rks.RungeKuttaSolver( springs , pset , dt )
solver = rks.RungeKuttaSolver(mlf, pset, dt)
pset.enable_log(True, log_max_size=1000)
a = aogl.AnimatedGl()
a.trajectory = True
a.trajectory_step = 1
a.ode_solver = solver
a.pset = pset
a.steps = steps
a.add_measure(ken)
a.add_measure(pot)
a.add_measure(tot)
a.build_animation()
a.start()
return
def bubble():
"""
Pseudo bubble simulation
"""
ocl_ok = test_pyopencl()
if ocl_ok:
pcnt = 9000
r_min = 0.5
occx = occ.OpenCLcontext(pcnt, 3)
else:
pcnt = 700
r_min = 1.5
steps = 1000000
dt = 0.01
rand_c = rc.RandCluster()
pset = ps.ParticlesSet(pcnt, dtype=np.float32)
rand_c.insert3(X=pset.X,
M=pset.M,
start_indx=0,
n=pset.size,
radius=3.0,
mass_rng=(0.5, 0.8),
r_min=0.0)
if ocl_ok:
bubble = pb.PseudoBubbleOCL(pset.size, pset.dim, Consts=(r_min, 10))
drag = dr.DragOCL(pset.size, pset.dim, Consts=0.01)
else:
bubble = pb.PseudoBubble(pset.size, pset.dim, Consts=(r_min, 10))
drag = dr.Drag(pset.size, pset.dim, Consts=0.01)
constf = cf.ConstForce(pset.size, dim=pset.dim, u_force=[0, 0, -10.0])
multif = mf.MultipleForce(pset.size, pset.dim)
multif.append_force(bubble)
multif.append_force(constf)
multif.append_force(drag)
multif.set_masses(pset.M)
#solver = els.EulerSolver( multif , pset , dt )
#solver = lps.LeapfrogSolver( multif , pset , dt )
solver = svs.StormerVerletSolver(multif, pset, dt)
#solver = rks.RungeKuttaSolver( lennard_jones , pset , dt )
#solver = mds.MidpointSolver( lennard_jones , pset , dt )
bound = rb.ReboundBoundary(bound=(-5.0, 5.0))
pset.set_boundary(bound)
a = aogl.AnimatedGl()
a.ode_solver = solver
a.pset = pset
a.steps = steps
if ocl_ok:
a.draw_particles.set_draw_model(a.draw_particles.DRAW_MODEL_VECTOR)
a.init_rotation(-80, [0.7, 0.05, 0])
a.build_animation()
a.start()
return
