def setup_in_volume(volume, count, h, spc=1., orig=(0.,0.,0.), offset=0., offset_inner=None, steps=100, fact=0.0001, maxneighs=1000, radius=0.):
max_x_cl = CLScalar(volume.shape[0]*spc)
max_y_cl = CLScalar(volume.shape[1]*spc)
max_z_cl = CLScalar(volume.shape[2]*spc)
particles_cl = CLReal4()
oi = None
if not offset_inner == None:
oi = offset_inner - radius
particles_cl.value = rand_particles_in_volume(volume, count, spc=spc, orig=(0.,0.,0.), offset=offset + radius, offset_inner=oi)
maxneighs_cl = CLScalar(maxneighs)
volume.shape = (volume.shape[0],volume.shape[1],volume.shape[2],1)
vol_cl = CLReal()
vol_cl.value = volume
neighsearch = Neighsearch(particles_cl, h=h, maxneighs=int(maxneighs_cl.value))
neighsearch.search()
h_cl = CLScalar(h)
fact_cl = CLScalar(fact)
vol_shp0_cl = CLScalar(volume.shape[0])
vol_shp1_cl = CLScalar(volume.shape[1])
vol_shp2_cl = CLScalar(volume.shape[2])
offset_cl = CLScalar(offset)
if offset_inner == None:
offset_inner = -pow(10., 38)
offset_inner_cl = CLScalar(offset_inner)
print "offsets: ", offset_cl, offset_inner_cl
gradient_cl = CLReal4()
gradient_cl.value = gradient_field(volume)
kern = CLTemplateKernel(src=_RELAXPART_SRC, pre=_GET_DIST_GRAD_SRC)
kern.pos = particles_cl
kern.h = h_cl
kern.maxneighs = maxneighs_cl
kern.neighbors = neighsearch.neighbors
kern.fact = fact_cl
kern.volume = vol_cl
kern.spacing = CLScalar(spc)
kern.vol_shp0 = vol_shp0_cl
kern.vol_shp1 = vol_shp1_cl
kern.vol_shp2 = vol_shp2_cl
kern.offset = offset_cl
kern.offset_inner = offset_inner_cl
kern.gradient = gradient_cl
kern.max_x = max_x_cl
kern.max_y = max_y_cl
kern.max_z = max_z_cl
kern.compile()
print 'Particle initialization'
for i in range(steps):
neighsearch.search()
kern()
kern.finish()
print 'Step', i+1, 'of', steps
ret = particles_cl.value
ret[:,0] += orig[0]
ret[:,1] += orig[1]
ret[:,2] += orig[2]
return ret
def __init__(self):
self.env = SPHEnv()
self.env.h = 1.0
self.env.maxneighs = 100
self.env.dt = 0.0001
self.env.g = 9.81
self.env.avgneighs = 50
self.env.maxdvar = 0.1
self.env.avgdvar = 0.1
self.env.maxiter = 500
self.env.slipcoeff = 1.
self.env.auto_dt_coeff = 0.01
self.env.dt_min = 0.01
self.wkernels = {}
self.wkernels['WendlandC2'] = WendC2_mod(self.h, self.avgneighs)
self.wkernels['WendlandC4'] = WendC4_mod(self.h, self.avgneighs)
self.wkernels['WendlandC6'] = WendC6_mod(self.h, self.avgneighs)
self.wkrn = 'WendlandC2'
self.particles = ParticleField()
self.particles.setup_vec('pos', 'vel', 'vel_adv', 'force', 'pforce', 'dii', 'sum_dijpjl')
self.particles.setup_scal('press', 'new_press', 'rho0', 'rho', 'rho_adv', 'new_rho', 'mass', 'visc', 'dcorr', 'aii', 'kappa', 'rho_err')
self.particles.info = CLChar()
self.particles.index = CLUInt()
self.particles.indvec = CLUInt4()
self.neighsearch = Neighsearch(posarg=self.particles.pos, group=self.particles._group, h=self.h, maxneighs=self.maxneighs, index=self.particles.index, indvec=self.particles.indvec)
self.steps = {}
def setup_with_particles(particles_in, volume, count, h, spc=1., orig=(0.,0.,0.), offset=0., offset_inner=None, steps=100, fact=0.0001, maxneighs=300):
max_x_cl = CLScalar(volume.shape[0]*spc + orig[0])
max_y_cl = CLScalar(volume.shape[1]*spc + orig[1])
max_z_cl = CLScalar(volume.shape[2]*spc + orig[2])
min_x_cl = CLScalar(orig[0])
min_y_cl = CLScalar(orig[1])
min_z_cl = CLScalar(orig[2])
maxneighs_cl = CLScalar(maxneighs)
parts_new = rand_particles_in_volume(volume, count, spc=spc, orig=orig, offset=offset, offset_inner=offset_inner)
particles_cl = CLReal4()
particles_cl.value = np.vstack((parts_new, particles_in))
flag_cl = CLChar()
flag_cl.value = np.vstack((np.zeros((len(parts_new),1)), np.ones((len(particles_in),1))))# 1->boundary particle, 0->movable particle
grp = Syncgroup(particles_cl, flag_cl)
neighsearch = Neighsearch(particles_cl, h=h, maxneighs=int(maxneighs_cl.value), group=grp)
neighsearch.search()
h_cl = CLScalar(h)
fact_cl = CLScalar(fact)
kern = CLTemplateKernel(src=_RELAXPART_WITH_PART_SRC)
kern.pos = particles_cl
kern.flag = flag_cl
kern.h = h_cl
kern.maxneighs = maxneighs_cl
kern.neighbors = neighsearch.neighbors
kern.fact = fact_cl
kern.max_x = max_x_cl
kern.max_y = max_y_cl
kern.max_z = max_z_cl
kern.min_x = min_x_cl
kern.min_y = min_y_cl
kern.min_z = min_z_cl
kern.compile()
print 'Particle initialization'
for i in range(steps):
neighsearch.search()
kern()
print 'Step', i+1, 'of', steps
parts = particles_cl.value
ret = []
flags = flag_cl.value
for i in range(len(parts)):
if flags[i,0] == 0:
ret.append(parts[i])
return np.array(ret)
class IISPHSolver(object):
consts = {}
consts['MAT_IGNORE'] = - 1
consts['MAT_FLUID'] = 0
consts['MAT_FIXEDBOUND'] = 1
CONSTS_SRC = ''
for i in consts.iteritems():
CONSTS_SRC += 'constant int ' + i[0] + ' = ' + str(i[1]) + ';\n'
CONSTS_SRC += NEIGHSEARCH_MACRO
def __init__(self):
self.env = SPHEnv()
self.env.h = 1.0
self.env.maxneighs = 100
self.env.dt = 0.0001
self.env.g = 9.81
self.env.avgneighs = 50
self.env.maxdvar = 0.1
self.env.avgdvar = 0.1
self.env.maxiter = 500
self.env.slipcoeff = 1.
self.env.auto_dt_coeff = 0.01
self.env.dt_min = 0.01
self.wkernels = {}
self.wkernels['WendlandC2'] = WendC2_mod(self.h, self.avgneighs)
self.wkernels['WendlandC4'] = WendC4_mod(self.h, self.avgneighs)
self.wkernels['WendlandC6'] = WendC6_mod(self.h, self.avgneighs)
self.wkrn = 'WendlandC2'
self.particles = ParticleField()
self.particles.setup_vec('pos', 'vel', 'vel_adv', 'force', 'pforce', 'dii', 'sum_dijpjl')
self.particles.setup_scal('press', 'new_press', 'rho0', 'rho', 'rho_adv', 'new_rho', 'mass', 'visc', 'dcorr', 'aii', 'kappa', 'rho_err')
self.particles.info = CLChar()
self.particles.index = CLUInt()
self.particles.indvec = CLUInt4()
self.neighsearch = Neighsearch(posarg=self.particles.pos, group=self.particles._group, h=self.h, maxneighs=self.maxneighs, index=self.particles.index, indvec=self.particles.indvec)
self.steps = {}
@property
def wkrn(self):
return self._wkrn
@wkrn.setter
def wkrn(self, value):
self._wkrn = self.wkernels[value]
@property
def h(self):
return self.env.h.value
@h.setter
def h(self, value):
self.env.h.value = value
for kernel in self.wkernels.values():
kernel.update(self.h, self.avgneighs)
@property
def maxneighs(self):
return int(self.env.maxneighs.value)
@maxneighs.setter
def maxneighs(self, value):
self.env.maxneighs.value = value
@property
def dt(self):
return self.env.dt.value
@dt.setter
def dt(self, value):
self.env.dt.value = value
@property
def g(self):
return self.env.g.value
@g.setter
def g(self, value):
self.env.g.value = value
@property
def avgneighs(self):
return self.env.avgneighs.value
@avgneighs.setter
def avgneighs(self, value):
self.env.avgneighs.value = value
for kernel in self.wkernels.values():
kernel.update(self.h, self.avgneighs)
@property
def maxdvar(self):
return self.env.maxdvar.value
@maxdvar.setter
def maxdvar(self, value):
self.env.maxdvar.value = value
@property
def avgdvar(self):
return self.env.avgdvar.value
@avgdvar.setter
def avgdvar(self, value):
self.env.avgdvar.value = value
@property
def maxiter(self):
return self.env.maxiter.value
@maxiter.setter
def maxiter(self, value):
self.env.maxiter.value = value
@property
def auto_dt_coeff(self):
return self.env.auto_dt_coeff.value
@auto_dt_coeff.setter
def auto_dt_coeff(self, value):
self.env.auto_dt_coeff.value = value
@property
def dt_min(self):
return self.env.dt_min.value
@dt_min.setter
def dt_min(self, value):
self.env.dt_min.value = value
def setup(self):
self.steps['compute_bound_mass'] = SolverStep(src=COMPUTE_BOUND_MASS, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_bound_mass')
self.steps['compute_density'] = SolverStep(src=COMPUTE_DENSITY, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_density')
self.steps['reset_force'] = SolverStep(src=RESET_FORCE, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='reset_force')
self.steps['apply_gravity'] = SolverStep(src=APPLY_GRAVITY, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='apply_gravity')
self.steps['apply_viscosity'] = SolverStep(src=APPLY_VISCOSITY, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='apply_viscosity')
self.steps['apply_surface_tension'] = SolverStep(src=APPLY_SURFACE_TENSION, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='apply_surface_tension')
self.steps['compute_vel_adv'] = SolverStep(src=COMPUTE_VEL_ADV, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_vel_adv')
self.steps['compute_dii'] = SolverStep(src=COMPUTE_DII, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_dii')
self.steps['compute_rho_adv_init_press'] = SolverStep(src=COMPUTE_RHO_ADV_INIT_PRESS, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_rho_adv_init_press')
self.steps['compute_aii'] = SolverStep(src=COMPUTE_AII, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_aii')
self.steps['compute_sum_dijpjl'] = SolverStep(src=COMPUTE_SUM_DIJPJL, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_sum_dijpjl')
self.steps['compute_pressure'] = SolverStep(src=COMPUTE_PRESSURE, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_pressure')
self.steps['set_pressure_clamped'] = SolverStep(src=SET_PRESSURE_CLAMPED, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='set_pressure_clamped')
self.steps['compute_new_rho'] = SolverStep(src=COMPUTE_NEW_RHO, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_new_rho')
self.steps['compute_density_error'] = SolverStep(src=COMPUTE_DENSITY_ERROR, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_density_error')
self.steps['compute_pressure_force'] = SolverStep(src=COMPUTE_PRESSURE_FORCE, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='compute_pressure_force')
self.steps['integrate'] = SolverStep(src=INTEGRATE, field=self.particles, env=self.env, wkrn=self.wkrn, consts=IISPHSolver.CONSTS_SRC, neighsearch=self.neighsearch, name='integrate')
def autoset_dt(self):
vmax = max_length_real4(self.particles.vel)
vadvmax = max_length_real4(self.particles.vel_adv)
dt_new_v = self.dt
dt_new_adv = self.dt
if (vmax > 0.0):
dt_new_v = self.auto_dt_coeff*self.h/vmax
if (vadvmax > 0.0):
dt_new_adv = self.auto_dt_coeff*self.h/vadvmax
if dt_new_v < dt_new_adv:
self.dt = min(dt_new_v, self.dt_min)
#print 'vel', self.dt
else:
self.dt = min(dt_new_adv, self.dt_min)
#print 'vel_adv', self.dt
@timing
def update(self):
self.neighsearch.search(h=self.h, maxneighs=self.maxneighs)
self.autoset_dt()
self.steps['compute_bound_mass']()
self.steps['compute_density']()
self.steps['reset_force']()
self.steps['apply_gravity']()
self.steps['apply_viscosity']()
self.steps['apply_surface_tension']()
self.steps['compute_vel_adv']()
self.steps['compute_dii']()
self.steps['compute_rho_adv_init_press']()
self.steps['compute_aii']()
for i in range(self.maxiter):
self.steps['compute_sum_dijpjl']()
self.steps['compute_pressure']()
self.steps['set_pressure_clamped']()
self.steps['compute_new_rho']()
self.steps['compute_density_error']()
maxerr = max_reduce(self.particles.rho_err)
avgerr = maxerr/len(self.particles.rho_err)
if ((maxerr < self.maxdvar) or (avgerr < self.avgdvar)) and (i >= 2):
#print 'pressure solve iterations: ', i
break
self.steps['compute_pressure_force']()
self.steps['integrate']()
ret[n][0] = x_n*h + rx
ret[n][1] = y_n*h + ry
ret[n][2] = z_n*h + rz
n += 1
return ret
ax_cnt = 7
spacing = 0.1
maxneighs = 100
h = 2.*spacing
pos_np = create_pos_cube(ax_cnt, spacing)
pos = CLReal4(name='pos')
pos.value = pos_np
ns = Neighsearch(posarg=pos, h=h, maxneighs=maxneighs)
t1 = timeit.default_timer()
ns.search()
t2 = timeit.default_timer()
print 'Finding each max. ' + str(maxneighs) + ' neighbors took ' + str(t2-t1) + 's for ' + str(len(pos)) + ' items on ' + str(ncl._ctrl.cldevice) + '.'
#assert
p = pos.value
n = np.zeros((len(p), maxneighs), np.int32) - 1
for i in range(len(p)):
count = 0
for j in range(len(p)):
if not(i == j):
pi = np.array(p[i,:3])
def do_test(ax_cnt):
def create_pos_cube(n_ax, h):
ret = np.zeros((n_ax*n_ax*n_ax, 4), np.float)
n = 0
for x_n in range(n_ax):
for y_n in range(n_ax):
for z_n in range(n_ax):
rx = random()*spacing*0.0#0.1
ry = random()*spacing*0.0#0.1
rz = random()*spacing*0.0#0.1
ret[n][0] = x_n*h + rx
ret[n][1] = y_n*h + ry
ret[n][2] = z_n*h + rz
n += 1
return ret
spacing = 0.1
maxneighs = 100
h = 2.*spacing
pos_np = create_pos_cube(ax_cnt, spacing)
pos = CLReal4(name='pos')
pos.value = pos_np
ns = Neighsearch(posarg=pos, h=h, maxneighs=maxneighs)
t1 = timeit.default_timer()
ns.search()
t2 = timeit.default_timer()
print 'Finding each max. ' + str(maxneighs) + ' neighbors took ' + str(t2-t1) + 's for ' + str(len(pos)) + ' items.'
#assert
p = pos.value
n = np.zeros((len(p), maxneighs), np.int32) - 1
for i in range(len(p)):
count = 0
for j in range(len(p)):
if not(i == j):
pi = np.array(p[i,:3])
pj = np.array(p[j,:3])
d = np.linalg.norm(pi - pj)
if d < h:
n[i,count] = j
count += 1
n_cl = ns.neighbors.value.reshape((len(p), maxneighs))
err = 0
errind = []
for i in range(len(p)):
nu = np.sort(n[i][(n[i] > -1)])
nc = np.sort(n_cl[i][(n_cl[i] > -1)])
#print nu, nc
if not np.all((nu == nc)):
err += 1
errind.append(i)
#print nu, nc
print 'neigh search errors:', str(err), '\n---\n'
return err
