def setUp(self):
self.l = l = 1.0
n = 20
dx = l / n
hdx = 1.5
x, y, z = G.get_3d_block(dx, l, l, l)
h = np.ones_like(x) * hdx * dx
m = np.ones_like(x) * dx * dx * dx
V = np.zeros_like(x)
fluid = get_particle_array(name='fluid', x=x, y=y, z=z, h=h, m=m, V=V)
x, y = G.get_2d_block(dx, l, l)
z = np.ones_like(x) * (l + 5 * dx) / 2.0
z = np.concatenate([z, -z])
x = np.tile(x, 2)
y = np.tile(y, 2)
m = np.ones_like(x) * dx * dx * dx
h = np.ones_like(x) * hdx * dx
V = np.zeros_like(x)
channel = get_particle_array(name='channel',
x=x,
y=y,
z=z,
h=h,
m=m,
V=V)
self.particles = [fluid, channel]
self.kernel = get_compiled_kernel(Gaussian(dim=3))
def common_setup(self):
# create the particle arrays
L = 1.0
n = 10
dx = L / n
hdx = 1.5
self.L = L
_x = np.arange(dx / 2, L, dx)
self.vol = vol = dx * dx
# fluid particles
xx, yy = np.meshgrid(_x, _x)
x = xx.ravel()
y = yy.ravel() # particle positions
p = self._get_pressure(x, y, 0.0)
h = np.ones_like(x) * hdx * dx # smoothing lengths
m = np.ones_like(x) * vol # mass
V = np.zeros_like(x) # volumes
fluid = get_particle_array(name='fluid', x=x, y=y, h=h, m=m, V=V, p=p)
# particles and domain
self.fluid = fluid
self.domain = DomainManager(xmin=0, xmax=L, ymin=0, ymax=L,
periodic_in_x=True, periodic_in_y=True,
backend=self.backend
)
self.kernel = get_compiled_kernel(Gaussian(dim=2))
def __init__(self, dim, dst, src, kernel=None):
self.dst = dst; self.src = src
if kernel is None:
self.kernel = get_compiled_kernel(Gaussian(dim))
# create the neighbor locator object
self.nnps = nnps = NNPS(dim=dim, particles=[dst, src],
radius_scale=self.kernel.radius_scale)
nnps.update()
def __init__(self, dim, dst, src, kernel=None):
self.dst = dst
self.src = src
if kernel is None:
self.kernel = get_compiled_kernel(Gaussian(dim))
# create the neighbor locator object
self.nnps = nnps = NNPS(dim=dim,
particles=[dst, src],
radius_scale=self.kernel.radius_scale)
nnps.update()
def setUp(self):
# create the particle arrays
L = 1.0
n = 100
dx = L / n
hdx = 1.5
_x = np.arange(dx / 2, L, dx)
self.vol = vol = dx * dx
# fluid particles
xx, yy = np.meshgrid(_x, _x)
x = xx.ravel()
y = yy.ravel() # particle positions
h = np.ones_like(x) * hdx * dx # smoothing lengths
m = np.ones_like(x) * vol # mass
V = np.zeros_like(x) # volumes
fluid = get_particle_array(name='fluid', x=x, y=y, h=h, m=m, V=V)
# channel particles
_y = np.arange(L + dx / 2, L + dx / 2 + 10 * dx, dx)
xx, yy = np.meshgrid(_x, _y)
xtop = xx.ravel()
ytop = yy.ravel()
_y = np.arange(-dx / 2, -dx / 2 - 10 * dx, -dx)
xx, yy = np.meshgrid(_x, _y)
xbot = xx.ravel()
ybot = yy.ravel()
x = np.concatenate((xtop, xbot))
y = np.concatenate((ytop, ybot))
h = np.ones_like(x) * hdx * dx
m = np.ones_like(x) * vol
V = np.zeros_like(x)
channel = get_particle_array(name='channel', x=x, y=y, h=h, m=m, V=V)
# particles and domain
self.particles = particles = [fluid, channel]
self.domain = domain = DomainManager(xmin=0,
xmax=L,
periodic_in_x=True)
self.kernel = get_compiled_kernel(Gaussian(dim=2))
def setUp(self):
# create the particle arrays
L = 1.0
n = 5
dx = L / n
hdx = 1.5
self.L = L
self.vol = vol = dx * dx * dx
# fluid particles
xx, yy, zz = np.mgrid[dx / 2:L:dx, dx / 2:L:dx, dx / 2:L:dx]
x = xx.ravel()
y = yy.ravel()
z = zz.ravel() # particle positions
p = self._get_pressure(x, y, z)
h = np.ones_like(x) * hdx * dx # smoothing lengths
m = np.ones_like(x) * vol # mass
V = np.zeros_like(x) # volumes
fluid = get_particle_array(name='fluid',
x=x,
y=y,
z=z,
h=h,
m=m,
V=V,
p=p)
# particles and domain
self.fluid = fluid
self.domain = DomainManager(xmin=0,
xmax=L,
ymin=0,
ymax=L,
zmin=0,
zmax=L,
periodic_in_x=True,
periodic_in_y=True,
periodic_in_z=True)
self.kernel = get_compiled_kernel(Gaussian(dim=3))
self.orig_n = self.fluid.get_number_of_particles()
self.nnps = LinkedListNNPS(dim=3,
particles=[self.fluid],
domain=self.domain,
radius_scale=self.kernel.radius_scale)
def sd_evaluate(nnps, pm, mass, src_index, dst_index):
# the destination particle array
dst = nnps.particles[dst_index]
src = nnps.particles[src_index]
# particle coordinates
dx, dy, dz, dh, drho = dst.get('x',
'y',
'z',
'h',
'rho',
only_real_particles=True)
sx, sy, sz, sh, srho = src.get('x',
'y',
'z',
'h',
'rho',
only_real_particles=False)
neighbors = UIntArray()
cubic = get_compiled_kernel(CubicSpline(dim=dim))
# compute density for each destination particle
num_particles = dst.num_real_particles
# the number of local particles should have tag Local
assert (num_particles == pm.num_local[dst_index])
for i in range(num_particles):
hi = dh[i]
nnps.get_nearest_particles(src_index, dst_index, i, neighbors)
nnbrs = neighbors.length
rho_sum = 0.0
for indexj in range(nnbrs):
j = neighbors[indexj]
wij = cubic.kernel(dx[i], dy[i], dz[i], sx[j], sy[j], sz[j], hi)
rho_sum = rho_sum + mass * wij
drho[i] += rho_sum
def setUp(self):
# create the particle arrays
L = 1.0; n = 100; dx = L/n; hdx = 1.5
_x = np.arange(dx/2, L, dx)
self.vol = vol = dx*dx
# fluid particles
xx, yy = np.meshgrid(_x, _x)
x = xx.ravel(); y = yy.ravel() # particle positions
h = np.ones_like(x) * hdx*dx # smoothing lengths
m = np.ones_like(x) * vol # mass
V = np.zeros_like(x) # volumes
fluid = get_particle_array(name='fluid', x=x, y=y, h=h, m=m, V=V)
# channel particles
_y = np.arange(L+dx/2, L+dx/2 + 10*dx, dx)
xx, yy = np.meshgrid(_x, _y)
xtop = xx.ravel(); ytop = yy.ravel()
_y = np.arange(-dx/2, -dx/2-10*dx, -dx)
xx, yy = np.meshgrid(_x, _y)
xbot = xx.ravel(); ybot = yy.ravel()
x = np.concatenate( (xtop, xbot) )
y = np.concatenate( (ytop, ybot) )
h = np.ones_like(x) * hdx*dx
m = np.ones_like(x) * vol
V = np.zeros_like(x)
channel = get_particle_array(name='channel', x=x, y=y, h=h, m=m, V=V)
# particles and domain
self.particles = particles = [fluid, channel]
self.domain = domain = DomainManager(xmin=0, xmax=L, periodic_in_x=True)
self.kernel = get_compiled_kernel(Gaussian(dim=2))
def setUpClass(cls):
cls.wrapper = get_compiled_kernel(cls.kernel_factory())
cls.kernel = cls.wrapper.kernel
cls.gradient = cls.wrapper.gradient
def setUpClass(cls):
cls.wrapper = get_compiled_kernel(cls.kernel_factory())
cls.kernel = cls.wrapper.kernel
cls.gradient = cls.wrapper.gradient
