def main():
from sumpy.kernel import ( # noqa: F401
YukawaKernel, HelmholtzKernel, LaplaceKernel)
tctx = t.ToyContext(
cl.create_some_context(),
#LaplaceKernel(2),
YukawaKernel(2),
extra_kernel_kwargs={"lam": 5},
#HelmholtzKernel(2), extra_kernel_kwargs={"k": 0.3},
)
pt_src = t.PointSources(tctx, np.random.rand(2, 50) - 0.5, np.ones(50))
fp = FieldPlotter([3, 0], extent=8)
if 0 and plt is not None:
t.logplot(fp, pt_src, cmap="jet")
plt.colorbar()
plt.show()
mexp = t.multipole_expand(pt_src, [0, 0], 5)
mexp2 = t.multipole_expand(mexp, [0, 0.25]) # noqa: F841
lexp = t.local_expand(mexp, [3, 0])
lexp2 = t.local_expand(lexp, [3, 1], 3)
#diff = mexp - pt_src
#diff = mexp2 - pt_src
diff = lexp2 - pt_src
print(t.l_inf(diff, 1.2, center=lexp2.center))
if 1 and plt is not None:
t.logplot(fp, diff, cmap="jet", vmin=-3, vmax=0)
plt.colorbar()
plt.show()
def __init__(self,
ambient_dim: int,
*,
dim: Optional[int] = None,
precond: str = "left",
yukawa_k_name: str = "k") -> None:
from sumpy.kernel import YukawaKernel
super().__init__(
YukawaKernel(ambient_dim, yukawa_lambda_name=yukawa_k_name),
dim=dim,
precond=precond,
kernel_arguments={yukawa_k_name: sym.var(yukawa_k_name)})
(LaplaceKernel(2), LaplaceConformingVolumeTaylorLocalExpansion,
LaplaceConformingVolumeTaylorMultipoleExpansion),
(LaplaceKernel(3), VolumeTaylorLocalExpansion,
VolumeTaylorMultipoleExpansion),
(LaplaceKernel(3), LaplaceConformingVolumeTaylorLocalExpansion,
LaplaceConformingVolumeTaylorMultipoleExpansion),
(HelmholtzKernel(2), VolumeTaylorLocalExpansion,
VolumeTaylorMultipoleExpansion),
(HelmholtzKernel(2), HelmholtzConformingVolumeTaylorLocalExpansion,
HelmholtzConformingVolumeTaylorMultipoleExpansion),
(HelmholtzKernel(2), H2DLocalExpansion, H2DMultipoleExpansion),
(HelmholtzKernel(3), VolumeTaylorLocalExpansion,
VolumeTaylorMultipoleExpansion),
(HelmholtzKernel(3), HelmholtzConformingVolumeTaylorLocalExpansion,
HelmholtzConformingVolumeTaylorMultipoleExpansion),
(YukawaKernel(2), Y2DLocalExpansion, Y2DMultipoleExpansion),
])
def test_sumpy_fmm(ctx_getter, knl, local_expn_class, mpole_expn_class):
logging.basicConfig(level=logging.INFO)
ctx = ctx_getter()
queue = cl.CommandQueue(ctx)
nsources = 1000
ntargets = 300
dtype = np.float64
from boxtree.tools import (make_normal_particle_array as p_normal)
sources = p_normal(queue, nsources, knl.dim, dtype, seed=15)
if 1:
def get_sumpy_kernel(self, dim, kernel_type):
"""Sumpy (symbolic) version of the kernel.
"""
if kernel_type == "Laplace":
from sumpy.kernel import LaplaceKernel
return LaplaceKernel(dim)
if kernel_type == "Laplace-Dx":
from sumpy.kernel import LaplaceKernel, AxisTargetDerivative
return AxisTargetDerivative(0, LaplaceKernel(dim))
if kernel_type == "Laplace-Dy":
from sumpy.kernel import LaplaceKernel, AxisTargetDerivative
return AxisTargetDerivative(1, LaplaceKernel(dim))
if kernel_type == "Laplace-Dz":
from sumpy.kernel import LaplaceKernel, AxisTargetDerivative
assert dim >= 3
return AxisTargetDerivative(2, LaplaceKernel(dim))
elif kernel_type == "Constant":
return ConstantKernel(dim)
elif kernel_type == "Yukawa":
from sumpy.kernel import YukawaKernel
return YukawaKernel(dim)
elif kernel_type == "Yukawa-Dx":
from sumpy.kernel import YukawaKernel, AxisTargetDerivative
return AxisTargetDerivative(0, YukawaKernel(dim))
elif kernel_type == "Yukawa-Dy":
from sumpy.kernel import YukawaKernel, AxisTargetDerivative
return AxisTargetDerivative(1, YukawaKernel(dim))
elif kernel_type == "Cahn-Hilliard":
from sumpy.kernel import FactorizedBiharmonicKernel
return FactorizedBiharmonicKernel(dim)
elif kernel_type == "Cahn-Hilliard-Laplacian":
from sumpy.kernel import (
FactorizedBiharmonicKernel,
LaplacianTargetDerivative,
)
return LaplacianTargetDerivative(FactorizedBiharmonicKernel(dim))
elif kernel_type == "Cahn-Hilliard-Dx":
from sumpy.kernel import FactorizedBiharmonicKernel, AxisTargetDerivative
return AxisTargetDerivative(0, FactorizedBiharmonicKernel(dim))
elif kernel_type == "Cahn-Hilliard-Laplacian-Dx":
from sumpy.kernel import (
FactorizedBiharmonicKernel,
LaplacianTargetDerivative,
)
from sumpy.kernel import AxisTargetDerivative
return AxisTargetDerivative(
0, LaplacianTargetDerivative(FactorizedBiharmonicKernel(dim)))
elif kernel_type == "Cahn-Hilliard-Laplacian-Dy":
from sumpy.kernel import (
FactorizedBiharmonicKernel,
LaplacianTargetDerivative,
)
from sumpy.kernel import AxisTargetDerivative
return AxisTargetDerivative(
1, LaplacianTargetDerivative(FactorizedBiharmonicKernel(dim)))
elif kernel_type == "Cahn-Hilliard-Dy":
from sumpy.kernel import FactorizedBiharmonicKernel, AxisTargetDerivative
return AxisTargetDerivative(1, FactorizedBiharmonicKernel(dim))
elif kernel_type in self.supported_kernels:
return None
else:
raise NotImplementedError("Kernel type not supported.")
def __init__(self, dim, lam):
self.kernel = YukawaKernel(dim)
self.lam = lam
self.extra_kwargs = {"lam": lam}