def laplacian(k):
''' Calculate the laplacian matrix for the Dubiner basis.
Returns L where \nabla^2 u = u . L for any vandermonde matrix u
N.B. would be easy to generalise this to any polynomial basis (indeed, the calculation
of the mass matrix is currently superfluous as the Dubiner basis is orthonomal)
THIS IS NOT USED - see p.c.b.reference.py for the alternative implemenation
'''
tp, tw = puq.trianglequadrature(k+1)
dt = DubinerTriangle(k,tp)
vtp = dt.values()
dtp = dt.derivs()
mass = np.tensordot(vtp * tw, vtp, (0,0))
stiffness = -np.tensordot(dtp * tw, dtp, ((0,1),(0,1)))
ex, ew = puq.legendrequadrature(k+1)
# Now do the boundary integrals
ew = ew.reshape(-1,1)
ep1 = np.hstack((ex, np.zeros_like(ex)))
ep2 = np.hstack((np.zeros_like(ex),ex))
ep3 = np.hstack((ex,1-ex))
for p, n in ((ep1,[0,-1]),(ep2,[-1,0]), (ep3, [1,1])):
dt = DubinerTriangle(k, p)
vn = np.tensordot(dt.derivs(), np.array(n), (0,0))
stiffness+=np.tensordot(dt.values() * ew, vn, (0,0))
return np.linalg.solve(mass, stiffness)
def testTriangle(self):
for n in range(1, 10):
x, w = puq.trianglequadrature(n)
# test integration of constants
self.assertAlmostEqual(sum(w), 0.5)
# integrate x
self.assertAlmostEqual(np.dot(x[:, 0], w), 1.0 / 6)
# integrate y
self.assertAlmostEqual(np.dot(x[:, 1], w), 1.0 / 6)
def testOrthonormal(self):
''' Test that the Dubiner polynomials are L^2-orthonormal over the reference triangle'''
N = 8
for k in range(0, N):
x,w = puq.trianglequadrature(k+1)
dt = pup.DubinerTriangle(k,x)
dtV = dt.values()
l2 = np.dot(dtV.T, w * dtV)
np.testing.assert_almost_equal(l2, np.eye(dtV.shape[1],dtV.shape[1]))
def testValues(self):
N = 5
for k in range(N):
x,w = puq.trianglequadrature(k+1)
dt = pup.DubinerTriangle(k, x)
V = dt.values()
n = ((k+1)*(k+2))/2
self.assertEquals(V.shape[1], n) # test that we get the correct number of basis functions
VV = np.dot(V.T, w * V)
np.testing.assert_almost_equal(VV, np.eye(n)) # test that they are orthonormal
def testLaplacian(self):
''' Use finite differences to check the Lapalcian calculations'''
N = 6
h = 1E-4
x,w = puq.trianglequadrature(5)
for k in range(1,N):
v = pup.DubinerTriangle(k, x).values()
L = pup.laplacian(k)
Lv = np.dot(v, L)
Lhv = (sum([pup.DubinerTriangle(k, x+xh).values() for xh in ([0,h],[0,-h],[h,0],[-h,0])]) - 4*v)/(h**2)
np.testing.assert_almost_equal(Lv, Lhv, decimal=3)
def testOptimalBasis2(self):
""" Can we find the right direction to approximate a plane wave?"""
k = 4
g = pcb.PlaneWaves(numpy.array([[3.0/5,4.0/5]]), k).values
# g = pcb.FourierBessel(numpy.array([-2,-1]), numpy.array([5]),k)
npw = 3
nq = 8
gen, ini = puo.pwbasisgeneration(k, npw)
triquad = puq.trianglequadrature(nq)
basis, (coeffs, l2err) = puo.optimalbasis2(g, gen, ini, triquad)
self.assertAlmostEqual(sum(l2err),0)
def testConstrainedOptimisation(self):
k = 4
g = pcb.PlaneWaves(numpy.array([[3.0/5,4.0/5]]), k).values
# g = pcb.FourierBessel(numpy.array([-2,-1]), numpy.array([5]),k)
npw = 3
nq = 8
ini = pcb.circleDirections(npw)
triquad = puq.trianglequadrature(nq)
linearopt = puo.LeastSquaresFit(g, triquad)
pwpg = puo.PWPenaltyBasisGenerator(k, 1, 2)
basis = puo.optimalbasis3(linearopt.optimise, pwpg.finalbasis, ini)
(coeffs, l2err) = linearopt.optimise(basis)
self.assertAlmostEqual(sum(l2err),0)
def testDerivs(self):
N = 5
h = 1E-8
for k in range(0,N):
x,w = puq.trianglequadrature(k+1)
dt = pup.DubinerTriangle(k,x)
dtV = dt.values()
dtxh = pup.DubinerTriangle(k, x+[h,0])
dtxhV = dtxh.values()
dtyh = pup.DubinerTriangle(k, x+[0,h])
dtyhV = dtyh.values()
dtD = dt.derivs()
dtxhD = (dtxhV - dtV)/h
dtyhD = (dtyhV - dtV)/h
np.testing.assert_almost_equal(dtD[0],dtxhD, decimal=4)
np.testing.assert_almost_equal(dtD[1],dtyhD, decimal=4)
def raytracesoln(problem, etods, pdeg = 2, npw = 15, radius = 0.5):
quadpoints = 15
k = problem.k
rtpw = prb.OldRaytracedBasisRule(etods)
fb = FourierBesselRule()
shadow = RaytracedShadowRule(etods, fb)
crt = SourceBasisRule()
poly = pcbr.ReferenceBasisRule(pcbr.Dubiner(pdeg))
# unonpw = pcbu.UnionBasisRule([shadow, crt])
# polynonpw = pcb.ProductBasisRule(poly, unonpw)
# basisrule = pcbu.UnionBasisRule([polynonpw,rtpw])
# unionall = pcbu.UnionBasisRule([shadow, rtpw, crt])
# polyall = pcb.ProductBasisRule(poly, unionall)
# basisrule = polyall
rt = pcbu.UnionBasisRule([rtpw, shadow])
polyrt = pcb.ProductBasisRule(poly, rt)
basisrule = polyrt
# pw = pcb.planeWaveBases(2, k, nplanewaves=npw)
# basisrule = CornerMultiplexBasisRule(pw, basisrule, radius)
# polyrt2 = pcbu.UnionBasisRule([rt,pcb.ProductBasisRule(poly, crt)])
# basisrule = polyrt2
basisrule = pcbred.SVDBasisReduceRule(puq.trianglequadrature(quadpoints), basisrule, threshold=1E-5)
p = 1 if pdeg < 1 else pdeg
h = 4.0/40
alpha = ((p*1.0)**2 ) / (k*h)
beta = np.min([(k*h) / (p * 1.0),1])
computation = psc.Computation(problem, basisrule, pcp.HelmholtzSystem, quadpoints, alpha = alpha, beta = beta)
solution = computation.solution(psc.DirectSolver().solve, dovolumes=True)
bounds=array([[-2,2],[-2,2]],dtype='d')
npoints=array([200,200])
pos.standardoutput(computation, solution, 20, bounds, npoints, mploutput = True, cmap=pom.mp.cm.get_cmap('binary'))
def testDubiner(self):
# The Dubiner basis is L^2-orthogonal, so we can test that the SVN reduction doesn't do much to it
# ... On reflection, this doesn't test very much. But it at least exercises the code, so leaving it in
k = 10
N = 3
bounds=np.array([[0.1,0.1],[0.9,0.9]],dtype='d')
npoints=np.array([20,20])
sp = pug.StructuredPoints(bounds, npoints)
for n in range(1,4):
mesh = tum.regularsquaremesh(n)
dubrule = pcbr.ReferenceBasisRule(pcbr.Dubiner(N))
problem = psp.Problem(mesh, k, {})
dubbasis = psp.constructBasis(problem, dubrule)
refquad = puq.trianglequadrature(N+1)
svnrule = pcbred.SVDBasisReduceRule(refquad, dubrule)
svnbasis = psp.constructBasis(problem, svnrule)
# The bases should be equivalent:
testEquivalentBases(dubbasis, svnbasis, mesh, sp)
from pypwdg.output.vtk_output import VTKStructuredPoints
from pypwdg.output.vtk_output import VTKGrid
from pypwdg.mesh.meshutils import MeshQuadratures
from pypwdg.core.vandermonde import LocalVandermondes
mesh_dict=gmsh_reader('../../examples/3D/scattmesh.msh')
mesh=gmshMesh(mesh_dict,dim=3)
boundaryentities = [82, 83]
Nq = 16
Np = 3
dirs = cubeRotations(cubeDirections(Np))
quad=trianglequadrature(Nq)
elttobasis = [[PlaneWaves(dirs, k)]] * mesh.nelements
params={'alpha':.5, 'beta':.5,'delta':.5}
l_coeffs=[-1j*k, 1]
r_coeffs=[-1j*k, 1]
bnddata={82:zero_impedance(k), 83:dirichlet(g) }
mqs = MeshQuadratures(mesh, quad)
lv = LocalVandermondes(mesh, elttobasis, mqs, usecache=False)
bndvs=[]
for data in bnddata.values():
def testMEQ(self):
for n in range(1, 6):
mesh = tum.regularsquaremesh(n)
mq = pmmu.MeshElementQuadratures(mesh, puq.trianglequadrature(5))
for i in range(2 * n ** 2):
self.assertAlmostEquals(sum(mq.quadweights(i)), 1.0 / (2 * n ** 2))
def test3DQuadratures(self):
""" Ensure quadratures on neighbouring faces of various 3D meshes match """
self.compareQuadratures(tum.meshes3d(), puq.trianglequadrature(4))
def __init__(self, k):
self.k = k
self.n = ((k+1) * (k+2)) / 2
self.volume = puq.trianglequadrature(k+1)
self.face = puq.legendrequadrature(k+1)
entityton ={9:1}
problem=psp.VariableNProblem(entityton, mesh,k, bnddata)
etods = prc.tracemesh(problem, {10:lambda x:direction})
etob = [[pcb.PlaneWaves(ds, k)] if len(ds) else [] for ds in etods]
pob.vtkbasis(mesh,etob,'soundsoftrays.vtu',None)
b0=pcbv.PlaneWaveVariableN(pcb.circleDirections(30))
b=pcb.PlaneWaveFromDirectionsRule(etods)
origins=np.array([[-.5,-.5],[-.5,.5],[.5,-.5],[.5,.5]])
h=pcb.FourierHankelBasisRule(origins,[0])
h2=pcb.ProductBasisRule(h,pcbr.ReferenceBasisRule(pcbr.Dubiner(p)))
b1=pcb.ProductBasisRule(b,pcbr.ReferenceBasisRule(pcbr.Dubiner(p)))
bh=pcb.UnionBasisRule([h2,b1])
b2=pcbr.ReferenceBasisRule(pcbr.Dubiner(p))
basisrule = pcbred.SVDBasisReduceRule(puq.trianglequadrature(quadpoints), bh, threshold=1E-5)
computation = psc.Computation(problem, basisrule, pcp.HelmholtzSystem, quadpoints,alpha=alpha,beta=beta,delta=delta)
solution = computation.solution(psc.DirectSolver().solve, dovolumes=True)
pos.standardoutput(computation, solution, quadpoints, bounds, npoints, 'soundsoft_pol', mploutput = True)
print solution.getError('Dirichlet')
print solution.getError('Neumann')
print solution.getError('Boundary')
