Ejemplo n.º 1
0
  def equation_partial_second_derivative(self, adjointer, adjoint, i, variable, m_dot):
    form = adjresidual.get_residual(i)
    if form is not None:
      form = -form

      mesh = ufl.algorithms.extract_arguments(form)[0].function_space().mesh()
      fn_space = backend.FunctionSpace(mesh, "R", 0)
      dparam = backend.Function(fn_space)
      dparam.vector()[:] = 1.0 * float(self.coeff)
      d2param = backend.Function(fn_space)
      d2param.vector()[:] = 1.0 * float(self.coeff) * m_dot

      diff_form = ufl.algorithms.expand_derivatives(backend.derivative(form, get_constant(self.a), dparam))
      if diff_form is None:
        return None

      diff_form  = ufl.algorithms.expand_derivatives(backend.derivative(diff_form, get_constant(self.a), d2param))
      if diff_form is None:
        return None

      # Let's see if the form actually depends on the parameter m
      if len(diff_form.integrals()) != 0:
        dFdm = backend.assemble(diff_form) # actually - dF/dm
        assert isinstance(dFdm, backend.GenericVector)

        out = dFdm.inner(adjoint.vector())
        return out
      else:
        return None # dF/dm is zero, return None
Ejemplo n.º 2
0
  def __call__(self, adjointer, i, dependencies, values, variable):
    form = adjresidual.get_residual(i)
    if form is not None:
      form = -form

      fn_space = ufl.algorithms.extract_arguments(form)[0].function_space()
      dparam = backend.Function(backend.FunctionSpace(fn_space.mesh(), "R", 0))
      dparam.vector()[:] = 1.0 * float(self.coeff)

      diff_form = ufl.algorithms.expand_derivatives(backend.derivative(form, get_constant(self.a), dparam))

      return adjlinalg.Vector(diff_form)
    else:
      return None
Ejemplo n.º 3
0
  def equation_partial_derivative(self, adjointer, adjoint, i, variable):
    form = adjresidual.get_residual(i)

    if form is None:
      return None
    else:
      form = -form

    fn_space = ufl.algorithms.extract_arguments(form)[0].function_space()
    dparam = backend.Function(backend.FunctionSpace(fn_space.mesh(), "R", 0))
    dparam.vector()[:] = 1.0

    dJdv = numpy.zeros(len(self.v))
    for (i, a) in enumerate(self.v):
      diff_form = ufl.algorithms.expand_derivatives(backend.derivative(form, a, dparam))

      dFdm = backend.assemble(diff_form) # actually - dF/dm
      assert isinstance(dFdm, backend.GenericVector)

      out = dFdm.inner(adjoint.vector())
      dJdv[i] = out

    return dJdv
Ejemplo n.º 4
0
  def __call__(self, adjointer, i, dependencies, values, variable):
    diff_form = None
    assert self.dv is not None, "Need a perturbation direction to use in the TLM."

    form = adjresidual.get_residual(i)

    if form is None:
      return None
    else:
      form = -form

    fn_space = ufl.algorithms.extract_arguments(form)[0].function_space()
    dparam = backend.Function(backend.FunctionSpace(fn_space.mesh(), "R", 0))
    dparam.vector()[:] = 1.0

    for (a, da) in zip(self.v, self.dv):
      out_form = da * backend.derivative(form, a, dparam)
      if diff_form is None:
        diff_form = out_form
      else:
        diff_form += out_form

    return adjlinalg.Vector(diff_form)