def Mult(self, k, y):
add_vector(self.v, self.dt, k, self.w)
add_vector(self.x, self.dt, self.w, self.z)
self.H.Mult(self.z, y)
self.M.TrueAddMult(k, y)
self.S.TrueAddMult(self.w, y)
y.SetSubVector(self.ess_tdof_list, 0.0)
def __sub__(self, other):
from mfem.par import HypreParVector as Vector
from mfem.par import add_vector
add_vector
if self[0] is not None and other[0] is not None:
r = Vector(self[0])
add_vector(self[0], -1, other[0], r)
elif self[0] is not None:
r = Vector(self[0])
elif other[0] is not None:
r = Vector(other[0])
r *= -1.
else:
r = None
if self[1] is not None and other[1] is not None:
i = Vector(self[1])
add_vector(self[1], -1, other[1], i)
elif self[1] is not None:
i = Vector(self[1])
elif other[1] is not None:
i = Vector(other[1])
i *= -1.
else:
i = None
return CHypreVec(r, i, horizontal=self._horizontal)
def ImplicitSolve(self, dt, vx, dvx_dt):
sc = self.Height() / 2
v = mfem.Vector(vx, 0, sc)
x = mfem.Vector(vx, sc, sc)
dv_dt = mfem.Vector(dvx_dt, 0, sc)
dx_dt = mfem.Vector(dvx_dt, sc, sc)
#print("v = ")
#v.Print()
#print("x = ")
#x.Print()
# By eliminating kx from the coupled system:
# kv = -M^{-1}*[H(x + dt*kx) + S*(v + dt*kv)]
# kx = v + dt*kv
# we reduce it to a linear equation for kv,
# represented by the backward_euler_oper
ndt = -1 * dt
self.VX = mfem.Add(1.0, self.Mmat, ndt, self.Smat)
self.VX_solver.SetOperator(self.VX)
#add_vector(x, dt, dv_dt, self.w)
self.Kmat.Mult(x, self.z)
#self.S.TrueAddMult(v, self.z)
self.Smat.Mult(v, self.tmpVec)
add_vector(self.z, 1.0, self.tmpVec, self.z)
self.z.Neg()
self.z += self.Bx
self.z += self.Bv
self.VX_solver.Mult(self.z, dv_dt)
add_vector(v, dt, dv_dt, dx_dt)
def GetGradient(self, k):
localJ = mfem.add_sparse(1.0, self.M.SpMat(), self.dt, self.S.SpMat());
add_vector(self.v, self.dt, k, self.w)
add_vector(self.x, self.dt, self.w, self.z)
localJ.Add(self.dt * self.dt, self.H.GetLocalGradient(self.z))
Jacobian = self.M.ParallelAssemble(localJ)
return Jacobian
def GetGradient(self, k):
localJ = mfem.Add(1.0, self.M.SpMat(), self.dt, self.S.SpMat())
add_vector(self.v, self.dt, k, self.w)
add_vector(self.x, self.dt, self.w, self.z)
localJ.Add(self.dt * self.dt, self.H.GetLocalGradient(self.z))
Jacobian = self.M.ParallelAssemble(localJ)
Jacobian.EliminateRowsCols(self.ess_tdof_list)
return Jacobian
def ImplicitSolve(self, dt, vx, dvx_dt):
sc = self.Height() // 2
v = mfem.Vector(vx, 0, sc)
x = mfem.Vector(vx, sc, sc)
dv_dt = mfem.Vector(dvx_dt, 0, sc)
dx_dt = mfem.Vector(dvx_dt, sc, sc)
# By eliminating kx from the coupled system:
# kv = -M^{-1}*[H(x + dt*kx) + S*(v + dt*kv)]
# kx = v + dt*kv
# we reduce it to a nonlinear equation for kv, represented by the
# backward_euler_oper. This equation is solved with the newton_solver
# object (using J_solver and J_prec internally).
self.reduced_oper.SetParameters(dt, v, x)
zero = mfem.Vector() # empty vector is interpreted as
# zero r.h.s. by NewtonSolver
self.newton_solver.Mult(zero, dv_dt)
add_vector(v, dt, dv_dt, dx_dt)
def __add__(self, other):
Vector = mfem.par.HypreParVector
if self[0] is not None and other[0] is not None:
r = Vector(self[0])
add_vector(self[0], others[0], r)
elif self[0] is not None:
r = Vector(self[0])
elif other[0] is not None:
r = Vector(other[0])
else:
r = None
if self[1] is not None and other[1] is not None:
i = Vector(self[1])
add_vector(self[1], others[1], i)
elif self[1] is not None:
i = Vector(self[1])
elif other[1] is not None:
i = Vector(other[1])
else:
i = None
return CHypreVec(r, i, horizontal=self._horizontal)
def Mult(self, k, y):
add_vector(self.v, self.dt, k, self.w)
add_vector(self.x, self.dt, self.w, self.z)
self.H.Mult(self.z, y)
self.M.TrueAddMult(k, y)
self.S.TrueAddMult(self.w, y)
