def get_ode_solver(self):
"""
Build and return an object for solving the Newton Law of motion (derived form the abstract class ode_solver)
"""
print("")
self.ode_solver = None
if self.ode_solver_name == "euler" :
self.ode_solver = els.EulerSolver( self.force , self.pset , self.time_step )
print( " setup - Integration method: EULER " )
elif self.ode_solver_name == "runge_kutta" :
self.ode_solver = rks.RungeKuttaSolver( self.force , self.pset , self.time_step )
print( " setup - Integration method: Runge Kutta " )
elif self.ode_solver_name == "leap_frog" :
self.ode_solver = lps.LeapfrogSolver( self.force , self.pset , self.time_step )
print( " setup - Integration method: Leap Frog " )
elif self.ode_solver_name == "stormer_verlet" :
self.ode_solver = svs.StormerVerletSolver( self.force , self.pset , self.time_step )
print( " setup - Integration method: Stormer Verlet " )
elif self.ode_solver_name == "midpoint" :
self.ode_solver = mds.MidpointSolver( self.force , self.pset , self.time_step )
print( " setup - Integration method: Midpoint " )
print( " setup - Integration method - time step: %e " % self.time_step )
return self.ode_solver
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 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 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