def _getSolution(self, system):
     """returns exact solution"""
     dim = self.domain.getDim()
     x = Solution(self.domain).getX()
     if system:
         u_ex = Vector(0., Solution(self.domain))
         if dim == 2:
             u_ex[0] = 1. + 2. * x[0] + 3. * x[1] + 4. * x[0]**2 + 5. * x[
                 1] * x[0] + 6. * x[1]**2
             u_ex[1] = -1. + 4. * x[0] + 2. * x[1] + 1. * x[0]**2 + 6. * x[
                 1] * x[0] + 4. * x[1]**2
         else:
             u_ex[0] = 1.+2.*x[0]+3.*x[1]+4.*x[2]+\
                       6.*x[0]*x[1]+7.*x[1]*x[2]+8.*x[2]*x[0]+\
                       9.*x[0]**2+10.*x[1]**2+11.*x[2]**2
             u_ex[1] = 2.+4.*x[0]+1.*x[1]-6.*x[2]+\
                       3.*x[0]*x[1]+2.*x[1]*x[2]-8.*x[2]*x[0]-\
                       2.*x[0]**2+7.*x[1]**2+5.*x[2]**2
             u_ex[2] = -2.+7.*x[0]+9.*x[1]+2*x[2]-\
                       6.*x[0]*x[1]+8.*x[1]*x[2]+2.*x[2]*x[0]+\
                       2.*x[0]**2+8.*x[1]**2+1.*x[2]**2
     else:
         if dim == 2:
             u_ex = 1. + 2. * x[0] + 3. * x[1] + 4. * x[0]**2 + 5. * x[
                 1] * x[0] + 6. * x[1]**2
         else:
             u_ex = 1.+2.*x[0]+3.*x[1]+4.*x[2]+\
                    6.*x[0]*x[1]+7.*x[1]*x[2]+8.*x[2]*x[0]+\
                    9.*x[0]**2+10.*x[1]**2+11.*x[2]**2
     return u_ex
 def _getGrad(self, system):
     """returns exact gradient"""
     dim = self.domain.getDim()
     x = Solution(self.domain).getX()
     if system:
         g_ex = Data(0., (dim, dim), Solution(self.domain))
         if dim == 2:
             g_ex[0, 0] = 2. + 8. * x[0] + 5. * x[1]
             g_ex[0, 1] = 3. + 5. * x[0] + 12. * x[1]
             g_ex[1, 0] = 4. + 2. * x[0] + 6. * x[1]
             g_ex[1, 1] = 2. + 6. * x[0] + 8. * x[1]
         else:
             g_ex[0, 0] = 2. + 6. * x[1] + 8. * x[2] + 18. * x[0]
             g_ex[0, 1] = 3. + 6. * x[0] + 7. * x[2] + 20. * x[1]
             g_ex[0, 2] = 4. + 7. * x[1] + 8. * x[0] + 22. * x[2]
             g_ex[1, 0] = 4. + 3. * x[1] - 8. * x[2] - 4. * x[0]
             g_ex[1, 1] = 1. + 3. * x[0] + 2. * x[2] + 14. * x[1]
             g_ex[1, 2] = -6. + 2. * x[1] - 8. * x[0] + 10. * x[2]
             g_ex[2, 0] = 7. - 6. * x[1] + 2. * x[2] + 4. * x[0]
             g_ex[2, 1] = 9. - 6. * x[0] + 8. * x[2] + 16. * x[1]
             g_ex[2, 2] = 2. + 8. * x[1] + 2. * x[0] + 2. * x[2]
     else:
         g_ex = Data(0., (dim, ), Solution(self.domain))
         if dim == 2:
             g_ex[0] = 2. + 8. * x[0] + 5. * x[1]
             g_ex[1] = 3. + 5. * x[0] + 12. * x[1]
         else:
             g_ex[0] = 2. + 6. * x[1] + 8. * x[2] + 18. * x[0]
             g_ex[1] = 3. + 6. * x[0] + 7. * x[2] + 20. * x[1]
             g_ex[2] = 4. + 7. * x[1] + 8. * x[0] + 22. * x[2]
     return g_ex
 def getGrad(self, system):
     """returns exact gradient"""
     dim = self.domain.getDim()
     if system:
         g_ex = Data(0., (dim,dim), Solution(self.domain))
         if dim == 2:
             g_ex[0,0] = 2.
             g_ex[0,1] = 3.
             g_ex[1,0] = 3.
             g_ex[1,1] = 2.
         else:
             g_ex[0,0] = 2.
             g_ex[0,1] = 3.
             g_ex[0,2] = 4.
             g_ex[1,0] = 4.
             g_ex[1,1] = 1.
             g_ex[1,2] = -2.
             g_ex[2,0] = 8.
             g_ex[2,1] = 4.
             g_ex[2,2] = 5.
     else:
         g_ex = Data(0., (dim,), Solution(self.domain))
         if dim == 2:
             g_ex[0] = 2.
             g_ex[1] = 3.
         else:
             g_ex[0] = 2.
             g_ex[1] = 3.
             g_ex[2] = 4.
     return g_ex
Exemple #4
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def interpolateEscriptData(domain, data):
    """
    esys.weipa does not support the function spaces Solution and
    ReducedSolution. This function interpolates Data defined on those function
    spaces to compatible alternatives.
    """
    from esys.escript import Solution, ReducedSolution
    from esys.escript import ContinuousFunction, ReducedContinuousFunction
    from esys.escript.util import interpolate
    
    new_data={}
    for n,d in sorted(list(data.items()), key=lambda x: x[0]):
        if not d.isEmpty():
            fs=d.getFunctionSpace()
            if domain is None:
                domain=fs.getDomain()
            elif domain != fs.getDomain():
                raise ValueError("weipa: All Data must be on the same domain!")
            new_data[n]=d
            try:
                if fs == Solution(domain):
                    new_data[n]=interpolate(d, ContinuousFunction(domain))
                elif domain.getDescription().startswith("speckley"):
                    new_data[n]=interpolate(d, ContinuousFunction(domain))
                elif fs == ReducedSolution(domain):
                    new_data[n]=interpolate(d, ReducedContinuousFunction(domain))
            except RuntimeError as e:
                if str(e).startswith("FunctionSpaceException"):
                    pass
                else:
                    raise e

    return domain,new_data
    def setCoefficients(self, pde, system):
        """sets PDE coefficients"""        
        FAC_DIAG = self.FAC_DIAG
        FAC_OFFDIAG =self.FAC_OFFDIAG
        x = Solution(self.domain).getX()
        mask = whereZero(x[0])
        dim = self.domain.getDim()
        u_ex = self.getSolution(system)
        g_ex = self.getGrad(system)

        if system:
            A = Tensor4(0., Function(self.domain))
            for i in range(dim):
                A[i,:,i,:] = kronecker(dim)

            Y = Vector(0., Function(self.domain))
            if dim == 2:
                Y[0] = u_ex[0]*FAC_DIAG+u_ex[1]*FAC_OFFDIAG-20
                Y[1] = u_ex[1]*FAC_DIAG+u_ex[0]*FAC_OFFDIAG-10
            else:
                Y[0] = u_ex[0]*FAC_DIAG+u_ex[2]*FAC_OFFDIAG+u_ex[1]*FAC_OFFDIAG-60
                Y[1] = u_ex[1]*FAC_DIAG+u_ex[0]*FAC_OFFDIAG+u_ex[2]*FAC_OFFDIAG-20
                Y[2] = u_ex[2]*FAC_DIAG+u_ex[1]*FAC_OFFDIAG+u_ex[0]*FAC_OFFDIAG-22
            pde.setValue(r=u_ex, q=mask*numpy.ones(dim,),
                         A=A,
                         D=kronecker(dim)*(FAC_DIAG-FAC_OFFDIAG)+numpy.ones((dim,dim))*FAC_OFFDIAG,
                         Y=Y,
                         y=matrixmult(g_ex,self.domain.getNormal()))
        else:
            pde.setValue(r=u_ex, q=mask, A=kronecker(dim),
                         y=inner(g_ex, self.domain.getNormal()))
            if dim == 2:
                pde.setValue(Y=-20.)
            else:
                pde.setValue(Y=-60.)
 def getSolution(self, system):
     """returns exact solution"""
     dim = self.domain.getDim()
     x = Solution(self.domain).getX()
     if system:
         u_ex = Vector(0., Solution(self.domain))
         if dim == 2:
             u_ex[0] =  1.+2.*x[0]+3.*x[1]
             u_ex[1] = -1.+3.*x[0]+2.*x[1]
         else:
             u_ex[0] =  1.+2.*x[0]+3.*x[1]+4.*x[2]
             u_ex[1] = -1.+4.*x[0]+1.*x[1]-2.*x[2]
             u_ex[2] =  5.+8.*x[0]+4.*x[1]+5.*x[2]
     else:
         if dim == 2:
             u_ex = 1.+2.*x[0]+3.*x[1]
         else:
             u_ex = 1.+2.*x[0]+3.*x[1]+4.*x[2]
     return u_ex