def __init__(self, dim):
num_equation = globals()['num_equation']
self.flux = mfem.DenseMatrix(num_equation, dim)
self.shape = mfem.Vector()
self.dshapedr = mfem.DenseMatrix()
self.dshapedx = mfem.DenseMatrix()
super(DomainIntegrator, self).__init__()
def Mult(self, x, y):
globals()['max_char_speed'] = 0.;
num_equation = globals()['num_equation']
# 1. Create the vector z with the face terms -<F.n(u), [w]>.
self.A.Mult(x, self.z);
# 2. Add the element terms.
# i. computing the flux approximately as a grid function by interpolating
# at the solution nodes.
# ii. multiplying this grid function by a (constant) mixed bilinear form for
# each of the num_equation, computing (F(u), grad(w)) for each equation.
xmat = mfem.DenseMatrix(x.GetData(), self.vfes.GetNDofs(), num_equation)
self.GetFlux(xmat, self.flux)
for k in range(num_equation):
fk = mfem.Vector(self.flux[k].GetData(), self.dim * self.vfes.GetNDofs())
o = k * self.vfes.GetNDofs()
zk = self.z[o: o+self.vfes.GetNDofs()]
self.Aflux.AddMult(fk, zk)
# 3. Multiply element-wise by the inverse mass matrices.
zval = mfem.Vector()
vdofs = mfem.intArray()
dof = self.vfes.GetFE(0).GetDof()
zmat = mfem.DenseMatrix()
ymat = mfem.DenseMatrix(dof, num_equation)
for i in range(self.vfes.GetNE()):
# Return the vdofs ordered byNODES
vdofs = mfem.intArray(self.vfes.GetElementVDofs(i))
self.z.GetSubVector(vdofs, zval)
zmat.UseExternalData(zval.GetData(), dof, num_equation)
mfem.Mult(self.Me_inv[i], zmat, ymat);
y.SetSubVector(vdofs, ymat.GetData())
def __init__(self, lambda_, mu_, si=0, sj=0):
super(StressCoefficient, self).__init__(0)
self.lam = lambda_ # coefficient
self.mu = mu_ # coefficient
self.si = si ; self.sj = sj # component
self.u = None # displacement GridFunction
self.grad = mfem.DenseMatrix()
def __init__(self, vfes, A, A_flux):
self.dim = vfes.GetFE(0).GetDim()
self.vfes = vfes
self.A = A
self.Aflux = A_flux
self.Me_inv = mfem.DenseTensor(vfes.GetFE(0).GetDof(),
vfes.GetFE(0).GetDof(),
vfes.GetNE())
self.state = mfem.Vector(num_equation)
self.f = mfem.DenseMatrix(num_equation, self.dim)
self.flux = mfem.DenseTensor(vfes.GetNDofs(), self.dim, num_equation)
self.z = mfem.Vector(A.Height())
dof = vfes.GetFE(0).GetDof()
Me = mfem.DenseMatrix(dof)
inv = mfem.DenseMatrixInverse(Me)
mi = mfem.MassIntegrator()
for i in range(vfes.GetNE()):
mi.AssembleElementMatrix(vfes.GetFE(i), vfes.GetElementTransformation(i), Me)
inv.Factor()
inv.GetInverseMatrix(self.Me_inv(i))
super(FE_Evolution, self).__init__(A.Height())
def make_mask(values, X, Y, Z, mask_start=0, logfile=None):
'''
mask for interpolation
'''
mask = np.zeros(len(X.flatten()), dtype=int) - 1
for kk, data in enumerate(values):
ptx, ret, gfr = data
xmax = np.max(ptx[:, 0])
xmin = np.min(ptx[:, 0])
ymax = np.max(ptx[:, 1])
ymin = np.min(ptx[:, 1])
zmax = np.max(ptx[:, 2])
zmin = np.min(ptx[:, 2])
i1 = np.logical_and(xmax >= X.flatten(), xmin <= X.flatten())
i2 = np.logical_and(ymax >= Y.flatten(), ymin <= Y.flatten())
i3 = np.logical_and(zmax >= Z.flatten(), zmin <= Z.flatten())
ii = np.logical_and(np.logical_and(i1, i2), i3)
mesh = gfr.FESpace().GetMesh()
XX = X.flatten()[ii]
YY = Y.flatten()[ii]
ZZ = Z.flatten()[ii]
size = len(XX)
m = mfem.DenseMatrix(3, size)
ptx = np.vstack([XX, YY, ZZ])
if logfile is not None:
txt = strftime("%a, %d %b %Y %H:%M:%S +0000", gmtime())
logfile.write(txt + "\n")
logfile.write("calling FindPoints : size = " + str(XX.shape) +
" " + str(kk + 1) + '/' + str(len(values)) + "\n")
m.Assign(ptx)
ips = mfem.IntegrationPointArray()
elem_ids = mfem.intArray()
pts_found = mesh.FindPoints(m, elem_ids, ips)
ii = np.where(ii)[0][np.array(elem_ids.ToList()) != -1]
mask[ii] = kk + mask_start
if logfile is not None:
logfile.write("done\n")
return mask
def AssembleFaceVector(self, el1, el2, Tr, elfun, elvect):
num_equation = globals()['num_equation']
# Compute the term <F.n(u),[w]> on the interior faces.
dof1 = el1.GetDof()
dof2 = el2.GetDof()
self.shape1.SetSize(dof1)
self.shape2.SetSize(dof2)
elvect.SetSize((dof1 + dof2) * num_equation)
elvect.Assign(0.0)
elfun1_mat = mfem.DenseMatrix(elfun.GetData(), dof1, num_equation)
elfun2_mat = mfem.DenseMatrix(elfun[dof1 * num_equation:].GetData(),
dof2, num_equation)
elvect1_mat = mfem.DenseMatrix(elvect.GetData(), dof1, num_equation)
elvect2_mat = mfem.DenseMatrix(elvect[dof1 * num_equation:].GetData(),
dof2, num_equation)
# Integration order calculation from DGTraceIntegrator
if (Tr.Elem2No >= 0):
intorder = (min(Tr.Elem1.OrderW(), Tr.Elem2.OrderW()) +
2 * max(el1.GetOrder(), el2.GetOrder()))
else:
intorder = Tr.Elem1.OrderW() + 2 * el1.GetOrder()
if (el1.Space() == mfem.FunctionSpace().Pk):
intorder += 1
ir = mfem.IntRules.Get(Tr.FaceGeom, intorder)
for i in range(ir.GetNPoints()):
ip = ir.IntPoint(i)
Tr.Loc1.Transform(ip, self.eip1)
Tr.Loc2.Transform(ip, self.eip2)
# Calculate basis functions on both elements at the face
el1.CalcShape(self.eip1, self.shape1)
el2.CalcShape(self.eip2, self.shape2)
# Interpolate elfun at the point
elfun1_mat.MultTranspose(self.shape1, self.funval1)
elfun2_mat.MultTranspose(self.shape2, self.funval2)
Tr.Face.SetIntPoint(ip)
# Get the normal vector and the flux on the face
mfem.CalcOrtho(Tr.Face.Jacobian(), self.nor)
mcs = self.rsolver.Eval(self.funval1, self.funval2, self.nor,
self.fluxN)
# Update max char speed
if mcs > globals()['max_char_speed']:
globals()['max_char_speed'] = mcs
self.fluxN *= ip.weight
#
fluxN = np.atleast_2d(self.fluxN.GetDataArray())
shape1 = np.atleast_2d(self.shape1.GetDataArray())
shape2 = np.atleast_2d(self.shape2.GetDataArray())
mat1 = elvect1_mat.GetDataArray()
mat2 = elvect2_mat.GetDataArray()
mat1 -= shape1.transpose().dot(fluxN)
mat2 += shape2.transpose().dot(fluxN)
'''
def __init__(self, model, x):
self.x = x
self.model = model
self.J = mfem.DenseMatrix()
mfem.PyCoefficient.__init__(self)
