/[escript]/trunk/escript/py_src/flows.py
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revision 3452 by caltinay, Tue Jan 25 01:53:57 2011 UTC revision 3620 by gross, Wed Oct 5 06:06:14 2011 UTC
# Line 37  import util Line 37  import util
37  from linearPDEs import LinearPDE, LinearPDESystem, LinearSinglePDE, SolverOptions  from linearPDEs import LinearPDE, LinearPDESystem, LinearSinglePDE, SolverOptions
38  from pdetools import HomogeneousSaddlePointProblem,Projector, ArithmeticTuple, PCG, NegativeNorm, GMRES  from pdetools import HomogeneousSaddlePointProblem,Projector, ArithmeticTuple, PCG, NegativeNorm, GMRES
39    
 print dir(escript)  
   
40  class DarcyFlow(object):  class DarcyFlow(object):
41     """     """
42     solves the problem     solves the problem
# Line 48  class DarcyFlow(object): Line 46  class DarcyFlow(object):
46        
47     where *p* represents the pressure and *u* the Darcy flux. *k* represents the permeability,     where *p* represents the pressure and *u* the Darcy flux. *k* represents the permeability,
48        
49     :note: The problem is solved in a least squares formulation.     :cvar EVAL: direct pressure gradient evaluation for flux
50       :cvar POST: global postprocessing of flux by solving the PDE *K_{ij} u_j + (w * K * l u_{k,k})_{,i}= - p_{,j} + K_{ij} g_j*
51                   where *l* is the length scale, *K* is the inverse of the permeability tensor, and *w* is a positive weighting factor.
52       :cvar SMOOTH: global smoothing by solving the PDE *K_{ij} u_j= - p_{,j} + K_{ij} g_j*
53     """     """
54         EVAL="EVAL"
55     def __init__(self, domain, useReduced=False, adaptSubTolerance=True, solveForFlux=False, useVPIteration=True, weighting_scale=0.1):     SIMPLE="EVAL"
56       POST="POST"
57       SMOOTH="SMOOTH"
58       def __init__(self, domain, useReduced=False, solver="EVAL", verbose=False, w=1.):
59        """        """
60        initializes the Darcy flux problem        initializes the Darcy flux problem
61        :param domain: domain of the problem        :param domain: domain of the problem
62        :type domain: `Domain`        :type domain: `Domain`
63        :param useReduced: uses reduced oreder on flux and pressure        :param useReduced: uses reduced oreder on flux and pressure
64        :type useReduced: ``bool``        :type useReduced: ``bool``
65        :param adaptSubTolerance: switches on automatic subtolerance selection        :param solver: solver method
66        :type adaptSubTolerance: ``bool``        :type solver: in [`DarcyFlow.EVAL`, `DarcyFlow.POST',  `DarcyFlow.SMOOTH' ]
67        :param solveForFlux: if True the solver solves for the flux (do not use!)        :param verbose: if ``True`` some information on the iteration progress are printed.
68        :type solveForFlux: ``bool``          :type verbose: ``bool``
69        :param useVPIteration: if True altenative iteration over v and p is performed. Otherwise V and P are calculated in a single PDE.        :param w: weighting factor for `DarcyFlow.POST` solver
70        :type useVPIteration: ``bool``            :type w: ``float``
       """  
       self.domain=domain  
       self.useVPIteration=useVPIteration  
       self.useReduced=useReduced  
       self.weighting_scale=weighting_scale  
       if self.useVPIteration:  
          self.solveForFlux=solveForFlux  
          self.__adaptSubTolerance=adaptSubTolerance  
          self.verbose=False  
           
          self.__pde_k=LinearPDESystem(domain)  
          self.__pde_k.setSymmetryOn()  
          if self.useReduced: self.__pde_k.setReducedOrderOn()  
     
          self.__pde_p=LinearSinglePDE(domain)  
          self.__pde_p.setSymmetryOn()  
          if self.useReduced: self.__pde_p.setReducedOrderOn()  
          self.setTolerance()  
          self.setAbsoluteTolerance()  
       else:  
          self.__pde_k=LinearPDE(self.domain, numEquations=self.domain.getDim()+1)  
          self.__pde_k.setSymmetryOn()  
          if self.useReduced: self.__pde_k.setReducedOrderOn()  
          C=self.__pde_k.createCoefficient("C")  
          B=self.__pde_k.createCoefficient("B")  
          for i in range(self.domain.getDim()):  
             C[i,self.domain.getDim(),i]=1  
             B[self.domain.getDim(),i,i]=1  
          self.__pde_k.setValue(C=C, B=B)  
       self.__f=escript.Scalar(0,self.__pde_k.getFunctionSpaceForCoefficient("X"))  
       self.__g=escript.Vector(0,self.__pde_k.getFunctionSpaceForCoefficient("Y"))  
         
    def getSolverOptionsFlux(self):  
       """  
       Returns the solver options used to solve the flux problems  
         
       *K^{-1} u=F*  
         
       :return: `SolverOptions`  
       """  
       return self.__pde_k.getSolverOptions()  
         
    def setSolverOptionsFlux(self, options=None):  
       """  
       Sets the solver options used to solve the flux problems  
         
       *K^{-1}u=F*  
         
       If ``options`` is not present, the options are reset to default  
         
       :param options: `SolverOptions`  
       :note: if the adaption of subtolerance is choosen, the tolerance set by ``options`` will be overwritten before the solver is called.  
       """  
       return self.__pde_v.setSolverOptions(options)  
       
    def getSolverOptionsPressure(self):  
       """  
       Returns the solver options used to solve the pressure problems  
         
       *(Q^* K Q)p=-Q^*G*  
         
       :return: `SolverOptions`  
       """  
       return self.__pde_p.getSolverOptions()  
         
    def setSolverOptionsPressure(self, options=None):  
       """  
       Sets the solver options used to solve the pressure problems  
         
       *(Q^* K Q)p=-Q^*G*  
         
       If ``options`` is not present, the options are reset to default  
71                
       :param options: `SolverOptions`  
       :note: if the adaption of subtolerance is choosen, the tolerance set by ``options`` will be overwritten before the solver is called.  
72        """        """
73        return self.__pde_p.setSolverOptions(options)        if not solver in [DarcyFlow.EVAL, DarcyFlow.POST,  DarcyFlow.SMOOTH ] :
74              raise ValueError,"unknown solver %d."%solver
75    
76          self.domain=domain
77          self.solver=solver
78          self.useReduced=useReduced
79          self.verbose=verbose
80          self.l=None
81          self.w=None
82        
83          self.__pde_p=LinearSinglePDE(domain)
84          self.__pde_p.setSymmetryOn()
85          if self.useReduced: self.__pde_p.setReducedOrderOn()
86    
87          if self.solver  == self.EVAL:
88             self.__pde_v=None
89         if self.verbose: print "DarcyFlow: simple solver is used."
90    
91          elif self.solver  == self.POST:
92         if util.inf(w)<0.:
93            raise ValueError,"Weighting factor must be non-negative."
94         if self.verbose: print "DarcyFlow: global postprocessing of flux is used."
95             self.__pde_v=LinearPDESystem(domain)
96             self.__pde_v.setSymmetryOn()
97             if self.useReduced: self.__pde_v.setReducedOrderOn()
98         self.w=w
99             self.l=util.vol(self.domain)**(1./self.domain.getDim()) # length scale
100    
101          elif self.solver  == self.SMOOTH:
102             self.__pde_v=LinearPDESystem(domain)
103             self.__pde_v.setSymmetryOn()
104             if self.useReduced: self.__pde_v.setReducedOrderOn()
105         if self.verbose: print "DarcyFlow: flux smoothing is used."
106         self.w=0
107    
108          self.__f=escript.Scalar(0,self.__pde_p.getFunctionSpaceForCoefficient("X"))
109          self.__g=escript.Vector(0,self.__pde_p.getFunctionSpaceForCoefficient("Y"))
110          self.location_of_fixed_pressure = escript.Scalar(0, self.__pde_p.getFunctionSpaceForCoefficient("q"))
111          self.location_of_fixed_flux = escript.Vector(0, self.__pde_p.getFunctionSpaceForCoefficient("q"))
112          self.perm_scale=1.
113        
114            
115     def setValue(self,f=None, g=None, location_of_fixed_pressure=None, location_of_fixed_flux=None, permeability=None):     def setValue(self,f=None, g=None, location_of_fixed_pressure=None, location_of_fixed_flux=None, permeability=None):
116        """        """
117        assigns values to model parameters        assigns values to model parameters
# Line 156  class DarcyFlow(object): Line 125  class DarcyFlow(object):
125        :param location_of_fixed_flux:  mask for locations where flux is fixed.        :param location_of_fixed_flux:  mask for locations where flux is fixed.
126        :type location_of_fixed_flux: vector values on the domain (e.g. `escript.Data`)        :type location_of_fixed_flux: vector values on the domain (e.g. `escript.Data`)
127        :param permeability: permeability tensor. If scalar ``s`` is given the tensor with ``s`` on the main diagonal is used.        :param permeability: permeability tensor. If scalar ``s`` is given the tensor with ``s`` on the main diagonal is used.
128        :type permeability: scalar or tensor values on the domain (e.g. `escript.Data`)        :type permeability: scalar or symmetric tensor values on the domain (e.g. `escript.Data`)
129    
130        :note: the values of parameters which are not set by calling ``setValue`` are not altered.        :note: the values of parameters which are not set by calling ``setValue`` are not altered.
131        :note: at any point on the boundary of the domain the pressure        :note: at any point on the boundary of the domain the pressure
# Line 165  class DarcyFlow(object): Line 134  class DarcyFlow(object):
134               is along the *x_i* axis.               is along the *x_i* axis.
135    
136        """        """
137        if self.useVPIteration:        if location_of_fixed_pressure!=None:
138           if location_of_fixed_pressure!=None: self.__pde_p.setValue(q=location_of_fixed_pressure)             self.location_of_fixed_pressure=util.wherePositive(location_of_fixed_pressure)
139           if location_of_fixed_flux!=None: self.__pde_k.setValue(q=location_of_fixed_flux)             self.__pde_p.setValue(q=self.location_of_fixed_pressure)
140        else:        if location_of_fixed_flux!=None:
141           q=self.__pde_k.getCoefficient("q")            self.location_of_fixed_flux=util.wherePositive(location_of_fixed_flux)
142           if q.isEmpty(): q=self.__pde_k.createCoefficient("q")            if not self.__pde_v == None: self.__pde_v.setValue(q=self.location_of_fixed_flux)
          if location_of_fixed_pressure!=None: q[self.domain.getDim()]=location_of_fixed_pressure  
          if location_of_fixed_flux!=None: q[:self.domain.getDim()]=location_of_fixed_flux  
          self.__pde_k.setValue(q=q)  
143                            
       # flux is rescaled by the factor mean value(perm_inv)*length where length**self.domain.getDim()=vol(self.domain)  
144        if permeability!=None:        if permeability!=None:
145       perm=util.interpolate(permeability,self.__pde_k.getFunctionSpaceForCoefficient("A"))      
146           V=util.vol(self.domain)       perm=util.interpolate(permeability,self.__pde_p.getFunctionSpaceForCoefficient("A"))
147             self.perm_scale=util.Lsup(util.length(perm))
148         if self.verbose: print "DarcyFlow: permeability scaling factor = %e."%self.perm_scale
149             perm=perm*(1./self.perm_scale)
150            
151       if perm.getRank()==0:       if perm.getRank()==0:
         perm_inv=(1./perm)  
             if self.useVPIteration:  
               self.scale=1.  
             else:  
               self.scale=util.integrate(perm_inv)*V**(1./self.domain.getDim()-1.)  
152    
153          perm_inv=perm_inv*((1./self.scale)*util.kronecker(self.domain.getDim()))          perm_inv=(1./perm)
154          perm=perm*(self.scale*util.kronecker(self.domain.getDim()))          perm_inv=perm_inv*util.kronecker(self.domain.getDim())
155            perm=perm*util.kronecker(self.domain.getDim())
156            
157            
158       elif perm.getRank()==2:       elif perm.getRank()==2:
159          perm_inv=util.inverse(perm)          perm_inv=util.inverse(perm)
             if self.useVPIteration:  
               self.scale=1.  
             else:  
               self.scale=util.sqrt(util.integrate(util.length(perm_inv)**2)*V**(2./self.domain.getDim()-1.)/self.domain.getDim())  
           perm_inv*=(1./self.scale)  
           perm=perm*self.scale  
160       else:       else:
161          raise ValueError,"illegal rank of permeability."          raise ValueError,"illegal rank of permeability."
162            
163       self.__permeability=perm       self.__permeability=perm
164       self.__permeability_inv=perm_inv       self.__permeability_inv=perm_inv
165        
166       self.__l2 =(util.longestEdge(self.domain)**2*util.length(self.__permeability_inv))*self.weighting_scale           #====================
167           if self.useVPIteration:       self.__pde_p.setValue(A=self.__permeability)
168          if  self.solveForFlux:           if self.solver  == self.EVAL:
169             self.__pde_k.setValue(D=self.__permeability_inv)                pass # no extra work required
170          else:           elif self.solver  == self.POST:
171             self.__pde_k.setValue(D=self.__permeability_inv, A=self.__l2*util.outer(util.kronecker(self.domain),util.kronecker(self.domain)))          k=util.kronecker(self.domain.getDim())
172          self.__pde_p.setValue(A=self.__permeability)          self.omega = self.w*util.length(perm_inv)*self.l*self.domain.getSize()
173           else:          self.__pde_v.setValue(D=self.__permeability_inv, A=self.omega*util.outer(k,k))
174              D=self.__pde_k.createCoefficient("D")           elif self.solver  == self.SMOOTH:
175              A=self.__pde_k.createCoefficient("A")          self.__pde_v.setValue(D=self.__permeability_inv)
176              D[:self.domain.getDim(),:self.domain.getDim()]=self.__permeability_inv  
177              for i in range(self.domain.getDim()):        if g != None:
178                 for j in range(self.domain.getDim()):      g=util.interpolate(g, self.__pde_p.getFunctionSpaceForCoefficient("Y"))
179                   A[i,i,j,j]=self.__l2      if g.isEmpty():
180              A[self.domain.getDim(),:,self.domain.getDim(),:]=self.__permeability            g=Vector(0,self.__pde_p.getFunctionSpaceForCoefficient("Y"))
181              self.__pde_k.setValue(A=A, D=D)      else:
182        if g !=None:          if not g.getShape()==(self.domain.getDim(),): raise ValueError,"illegal shape of g"
183       g=util.interpolate(g, self.__pde_k.getFunctionSpaceForCoefficient("Y"))      self.__g=g
      if g.isEmpty():  
           g=Vector(0,self.__pde_k.getFunctionSpaceForCoefficient("Y"))  
      else:  
         if not g.getShape()==(self.domain.getDim(),):  
               raise ValueError,"illegal shape of g"  
         self.__g=g  
       elif permeability!=None:  
              X  
184        if f !=None:        if f !=None:
185       f=util.interpolate(f, self.__pde_k.getFunctionSpaceForCoefficient("X"))       f=util.interpolate(f, self.__pde_p.getFunctionSpaceForCoefficient("Y"))
186       if f.isEmpty():       if f.isEmpty():      
187            f=Scalar(0,self.__pde_k.getFunctionSpaceForCoefficient("X"))            f=Scalar(0,self.__pde_p.getFunctionSpaceForCoefficient("Y"))
188       else:       else:
189           if f.getRank()>0: raise ValueError,"illegal rank of f."           if f.getRank()>0: raise ValueError,"illegal rank of f."
190           self.__f=f       self.__f=f
191    
192       def getSolverOptionsFlux(self):
193          """
194          Returns the solver options used to solve the flux problems
195          :return: `SolverOptions`
196          """
197          if self.__pde_v == None:
198              return None
199          else:
200              return self.__pde_v.getSolverOptions()
201                
202     def solve(self,u0,p0, max_iter=100, verbose=False, max_num_corrections=10):     def setSolverOptionsFlux(self, options=None):
203        """        """
204        solves the problem.        Sets the solver options used to solve the flux problems
205          If ``options`` is not present, the options are reset to default
206          :param options: `SolverOptions`
207          """
208          if not self.__pde_v == None:
209              self.__pde_v.setSolverOptions(options)
210        
211       def getSolverOptionsPressure(self):
212          """
213          Returns the solver options used to solve the pressure problems
214          :return: `SolverOptions`
215          """
216          return self.__pde_p.getSolverOptions()
217                
218        The iteration is terminated if the residual norm is less then self.getTolerance().     def setSolverOptionsPressure(self, options=None):
   
       :param u0: initial guess for the flux. At locations in the domain marked by ``location_of_fixed_flux`` the value of ``u0`` is kept unchanged.  
       :type u0: vector value on the domain (e.g. `escript.Data`).  
       :param p0: initial guess for the pressure. At locations in the domain marked by ``location_of_fixed_pressure`` the value of ``p0`` is kept unchanged.  
       :type p0: scalar value on the domain (e.g. `escript.Data`).  
       :param verbose: if set some information on iteration progress are printed  
       :type verbose: ``bool``  
       :return: flux and pressure  
       :rtype: ``tuple`` of `escript.Data`.  
   
       :note: The problem is solved as a least squares form  
              *(K^[-1]+D^* l2 D)u+G p=D^* l2 * f + K^[-1]g*  
              *G^*u+*G^* K Gp=G^*g*  
              where *D* is the *div* operator and *(Gp)_i=p_{,i}* for the permeability *K=k_{ij}*.  
219        """        """
220        self.verbose=verbose        Sets the solver options used to solve the pressure problems
221        if self.useVPIteration:        If ``options`` is not present, the options are reset to default
222            return self.__solveVP(u0,p0,max_iter,max_num_corrections)        
223        else:        :param options: `SolverOptions`
224            X=self.__pde_k.createCoefficient("X")        :note: if the adaption of subtolerance is choosen, the tolerance set by ``options`` will be overwritten before the solver is called.
225            Y=self.__pde_k.createCoefficient("Y")        """
226            Y[:self.domain.getDim()]=self.scale*util.tensor_mult(self.__permeability_inv,self.__g)        return self.__pde_p.setSolverOptions(options)
227            rtmp=self.__f * self.__l2 * self.scale        
228            for i in range(self.domain.getDim()): X[i,i]=rtmp     def solve(self, u0, p0):
           X[self.domain.getDim(),:]=self.__g*self.scale  
           r=self.__pde_k.createCoefficient("r")  
           r[:self.domain.getDim()]=u0*self.scale  
           r[self.domain.getDim()]=p0  
           self.__pde_k.setValue(X=X, Y=Y, r=r)  
           self.__pde_k.getSolverOptions().setVerbosity(self.verbose)  
           #self.__pde_k.getSolverOptions().setPreconditioner(self.__pde_k.getSolverOptions().AMG)  
           self.__pde_k.getSolverOptions().setSolverMethod(self.__pde_k.getSolverOptions().DIRECT)  
           U=self.__pde_k.getSolution()  
           # self.__pde_k.getOperator().saveMM("k.mm")  
           u=U[:self.domain.getDim()]*(1./self.scale)  
           p=U[self.domain.getDim()]  
           if self.verbose:  
         KGp=util.tensor_mult(self.__permeability,util.grad(p)/self.scale)  
         def_p=self.__g-(u+KGp)  
         def_v=self.__f-util.div(u, self.__pde_k.getFunctionSpaceForCoefficient("X"))  
         print "DarcyFlux: L2: g-v-K*grad(p) = %e (v = %e)."%(self.__L2(def_p),self.__L2(u))  
         print "DarcyFlux: L2: f-div(v) = %e (grad(v) = %e)."%(self.__L2(def_v),self.__L2(util.grad(u)))  
           return u,p  
   
    def __solveVP(self,u0,p0, max_iter=100, max_num_corrections=10):  
229        """        """
230        solves the problem.        solves the problem.
231                
       The iteration is terminated if the residual norm is less than self.getTolerance().  
   
232        :param u0: initial guess for the flux. At locations in the domain marked by ``location_of_fixed_flux`` the value of ``u0`` is kept unchanged.        :param u0: initial guess for the flux. At locations in the domain marked by ``location_of_fixed_flux`` the value of ``u0`` is kept unchanged.
233        :type u0: vector value on the domain (e.g. `escript.Data`).        :type u0: vector value on the domain (e.g. `escript.Data`).
234        :param p0: initial guess for the pressure. At locations in the domain marked by ``location_of_fixed_pressure`` the value of ``p0`` is kept unchanged.        :param p0: initial guess for the pressure. At locations in the domain marked by ``location_of_fixed_pressure`` the value of ``p0`` is kept unchanged.
# Line 299  class DarcyFlow(object): Line 236  class DarcyFlow(object):
236        :return: flux and pressure        :return: flux and pressure
237        :rtype: ``tuple`` of `escript.Data`.        :rtype: ``tuple`` of `escript.Data`.
238    
       :note: The problem is solved as a least squares form  
              *(K^[-1]+D^* (DKD^*)^[-1] D)u+G p=D^* (DKD^*)^[-1] f + K^[-1]g*  
              *G^*u+*G^* K Gp=G^*g*  
              where *D* is the *div* operator and *(Gp)_i=p_{,i}* for the permeability *K=k_{ij}*.  
       """  
       rtol=self.getTolerance()  
       atol=self.getAbsoluteTolerance()  
       self.setSubProblemTolerance()  
       num_corrections=0  
       converged=False  
       norm_r=None  
         
       # Eliminate the hydrostatic pressure:  
       if self.verbose: print "DarcyFlux: calculate hydrostatic pressure component."  
       self.__pde_p.setValue(X=self.__g, r=p0, y=-util.inner(self.domain.getNormal(),u0))          
       p0=self.__pde_p.getSolution()  
       g2=self.__g - util.tensor_mult(self.__permeability, util.grad(p0))  
       norm_g2=util.integrate(util.inner(g2,util.tensor_mult(self.__permeability_inv,g2)))**0.5      
   
       p=p0*0  
       if self.solveForFlux:  
      v=u0.copy()  
       else:  
      v=self.__getFlux(p, u0, f=self.__f, g=g2)  
   
       while not converged and norm_g2 > 0:  
      Gp=util.grad(p)  
      KGp=util.tensor_mult(self.__permeability,Gp)  
      if self.verbose:  
         def_p=g2-(v+KGp)  
         def_v=self.__f-util.div(v)  
         print "DarcyFlux: L2: g-v-K*grad(p) = %e (v = %e)."%(self.__L2(def_p),self.__L2(v))  
         print "DarcyFlux: L2: f-div(v) = %e (grad(v) = %e)."%(self.__L2(def_v),self.__L2(util.grad(v)))  
         print "DarcyFlux: K^{-1}-norm of v = %e."%util.integrate(util.inner(v,util.tensor_mult(self.__permeability_inv,v)))**0.5  
         print "DarcyFlux: K^{-1}-norm of g2 = %e."%norm_g2  
         print "DarcyFlux: K-norm of grad(dp) = %e."%util.integrate(util.inner(Gp,KGp))**0.5  
      ATOL=atol+rtol*norm_g2  
      if self.verbose: print "DarcyFlux: absolute tolerance ATOL = %e."%(ATOL,)  
      if norm_r == None or norm_r>ATOL:  
         if num_corrections>max_num_corrections:  
            raise ValueError,"maximum number of correction steps reached."  
         
         if self.solveForFlux:  
            # initial residual is r=K^{-1}*(g-v-K*Gp)+D^*L^{-1}(f-Du)  
            v,r, norm_r=PCG(ArithmeticTuple(util.tensor_mult(self.__permeability_inv,g2-v)-Gp,self.__applWeight(v,self.__f),p),  
                self.__Aprod_v,  
                v,  
                self.__Msolve_PCG_v,  
                self.__inner_PCG_v,  
                atol=ATOL, rtol=0.,iter_max=max_iter, verbose=self.verbose)  
            p=r[2]  
         else:  
            # initial residual is r=G^*(g2-KGp - v)  
            p,r, norm_r=PCG(ArithmeticTuple(g2-KGp,v),  
                  self.__Aprod_p,  
                  p,  
                  self.__Msolve_PCG_p,  
                  self.__inner_PCG_p,  
                  atol=ATOL, rtol=0.,iter_max=max_iter, verbose=self.verbose)  
            v=r[1]  
         if self.verbose: print "DarcyFlux: residual norm = %e."%norm_r  
         num_corrections+=1  
      else:  
         if self.verbose: print "DarcyFlux: stopping criterium reached."  
         converged=True  
       return v,p+p0  
   
    def __applWeight(self, v, f=None):  
       # solves L p = f-Dv with p = 0  
       if self.verbose: print "DarcyFlux: Applying weighting operator"  
       if f == None:  
      return -util.div(v)*self.__l2  
       else:  
      return (f-util.div(v))*self.__l2  
    def __getPressure(self, v, p0, g=None):  
       # solves (G*KG)p = G^(g-v) with p = p0 where location_of_fixed_pressure>0  
       if self.getSolverOptionsPressure().isVerbose() or self.verbose: print "DarcyFlux: Pressure update"  
       if g == None:  
      self.__pde_p.setValue(X=-v, r=p0)  
       else:  
      self.__pde_p.setValue(X=g-v, r=p0)        
       p=self.__pde_p.getSolution()  
       return p  
   
    def __Aprod_v(self,dv):  
       # calculates: (a,b,c) = (K^{-1}(dv + KG * dp), L^{-1}Ddv, dp)  with (G*KG)dp = - G^*dv    
       dp=self.__getPressure(dv, p0=escript.Data()) # dp = (G*KG)^{-1} (0-G^*dv)  
       a=util.tensor_mult(self.__permeability_inv,dv)+util.grad(dp) # a= K^{-1}u+G*dp  
       b= - self.__applWeight(dv) # b = - (D K D^*)^{-1} (0-Dv)  
       return ArithmeticTuple(a,b,-dp)  
   
    def __Msolve_PCG_v(self,r):  
       # K^{-1} u = r[0] + D^*r[1] = K^{-1}(dv + KG * dp) + D^*L^{-1}Ddv  
       if self.getSolverOptionsFlux().isVerbose() or self.verbose: print "DarcyFlux: Applying preconditioner"  
       self.__pde_k.setValue(X=r[1]*util.kronecker(self.domain), Y=r[0], r=escript.Data())  
       return self.__pde_k.getSolution()  
   
    def __inner_PCG_v(self,v,r):  
       return util.integrate(util.inner(v,r[0])+util.div(v)*r[1])  
         
    def __Aprod_p(self,dp):  
       if self.getSolverOptionsFlux().isVerbose(): print "DarcyFlux: Applying operator"  
       Gdp=util.grad(dp)  
       self.__pde_k.setValue(Y=-Gdp,X=escript.Data(), r=escript.Data())  
       du=self.__pde_k.getSolution()  
       return ArithmeticTuple(util.tensor_mult(self.__permeability,Gdp),-du)  
   
    def __getFlux(self,p, v0, f=None, g=None):  
       # solves (K^{-1}+D^*L^{-1} D) v = D^*L^{-1}f + K^{-1}g - Gp  
       if f!=None:  
      self.__pde_k.setValue(X=self.__applWeight(v0*0,self.__f)*util.kronecker(self.domain))  
       self.__pde_k.setValue(r=v0)  
       g2=util.tensor_mult(self.__permeability_inv,g)  
       if p == None:  
      self.__pde_k.setValue(Y=g2)  
       else:  
      self.__pde_k.setValue(Y=g2-util.grad(p))  
       return self.__pde_k.getSolution()    
         
       #v=self.__getFlux(p, u0, f=self.__f, g=g2)        
    def __Msolve_PCG_p(self,r):  
       if self.getSolverOptionsPressure().isVerbose(): print "DarcyFlux: Applying preconditioner"  
       self.__pde_p.setValue(X=r[0]-r[1], Y=escript.Data(), r=escript.Data(), y=escript.Data())  
       return self.__pde_p.getSolution()  
           
    def __inner_PCG_p(self,p,r):  
        return util.integrate(util.inner(util.grad(p), r[0]-r[1]))  
   
    def __L2(self,v):  
       return util.sqrt(util.integrate(util.length(util.interpolate(v,escript.Function(self.domain)))**2))  
   
    def __L2_r(self,v):  
       return util.sqrt(util.integrate(util.length(util.interpolate(v,escript.ReducedFunction(self.domain)))**2))  
   
    def setTolerance(self,rtol=1e-4):  
       """  
       sets the relative tolerance ``rtol`` used to terminate the solution process. The iteration is terminated if  
   
       *|g-v-K gard(p)|_PCG <= atol + rtol * |K^{1/2}g2|_0*  
         
       where ``atol`` is an absolut tolerance (see `setAbsoluteTolerance`).  
         
       :param rtol: relative tolerance for the pressure  
       :type rtol: non-negative ``float``  
       """  
       if rtol<0:  
      raise ValueError,"Relative tolerance needs to be non-negative."  
       self.__rtol=rtol  
    def getTolerance(self):  
       """  
       returns the relative tolerance  
       :return: current relative tolerance  
       :rtype: ``float``  
       """  
       return self.__rtol  
   
    def setAbsoluteTolerance(self,atol=0.):  
239        """        """
240        sets the absolute tolerance ``atol`` used to terminate the solution process. The iteration is terminated if        self.__pde_p.setValue(X=self.__g * 1./self.perm_scale,
241                                Y=self.__f * 1./self.perm_scale,
242                                y= - util.inner(self.domain.getNormal(),u0 * self.location_of_fixed_flux * 1./self.perm_scale ),
243                                r=p0)
244          p=self.__pde_p.getSolution()
245          u = self.getFlux(p, u0)
246          return u,p
247                
248        *|g-v-K gard(p)|_PCG <= atol + rtol * |K^{1/2}g2|_0*     def getFlux(self,p, u0=None):
   
   
       where ``rtol`` is an absolut tolerance (see `setTolerance`), *|f|^2 = integrate(length(f)^2)* and *(Qp)_i=k_{ij}p_{,j}* for the permeability *k_{ij}*.  
   
       :param atol: absolute tolerance for the pressure  
       :type atol: non-negative ``float``  
       """  
       if atol<0:  
      raise ValueError,"Absolute tolerance needs to be non-negative."  
       self.__atol=atol  
    def getAbsoluteTolerance(self):  
       """  
       returns the absolute tolerance  
       :return: current absolute tolerance  
       :rtype: ``float``  
       """  
       return self.__atol  
    def getSubProblemTolerance(self):  
       """  
       Returns a suitable subtolerance  
       :type: ``float``  
       """  
       return max(util.EPSILON**(0.5),self.getTolerance()**2)  
   
    def setSubProblemTolerance(self):  
       """  
       Sets the relative tolerance to solve the subproblem(s) if subtolerance adaption is selected.  
       """  
       if self.__adaptSubTolerance:  
      sub_tol=self.getSubProblemTolerance()  
      self.getSolverOptionsFlux().setTolerance(sub_tol)  
      self.getSolverOptionsFlux().setAbsoluteTolerance(0.)  
      self.getSolverOptionsPressure().setTolerance(sub_tol)  
      self.getSolverOptionsPressure().setAbsoluteTolerance(0.)  
      if self.verbose: print "DarcyFlux: relative subtolerance is set to %e."%sub_tol  
   
   
 class DarcyFlowOld(object):  
     """  
     solves the problem  
   
     *u_i+k_{ij}*p_{,j} = g_i*  
     *u_{i,i} = f*  
   
     where *p* represents the pressure and *u* the Darcy flux. *k* represents the permeability,  
   
     :note: The problem is solved in a least squares formulation.  
     """  
   
     def __init__(self, domain, weight=None, useReduced=False, adaptSubTolerance=True):  
         """  
         initializes the Darcy flux problem  
         :param domain: domain of the problem  
         :type domain: `Domain`  
     :param useReduced: uses reduced oreder on flux and pressure  
     :type useReduced: ``bool``  
     :param adaptSubTolerance: switches on automatic subtolerance selection  
     :type adaptSubTolerance: ``bool``    
249          """          """
250          self.domain=domain          returns the flux for a given pressure ``p`` where the flux is equal to ``u0``
         if weight == None:  
            s=self.domain.getSize()  
            self.__l2=(3.*util.longestEdge(self.domain)*s/util.sup(s))**2  
            # self.__l2=(3.*util.longestEdge(self.domain))**2  
            #self.__l2=(0.1*util.longestEdge(self.domain)*s/util.sup(s))**2  
         else:  
            self.__l2=weight  
         self.__pde_v=LinearPDESystem(domain)  
         if useReduced: self.__pde_v.setReducedOrderOn()  
         self.__pde_v.setSymmetryOn()  
         self.__pde_v.setValue(D=util.kronecker(domain), A=self.__l2*util.outer(util.kronecker(domain),util.kronecker(domain)))  
         self.__pde_p=LinearSinglePDE(domain)  
         self.__pde_p.setSymmetryOn()  
         if useReduced: self.__pde_p.setReducedOrderOn()  
         self.__f=escript.Scalar(0,self.__pde_v.getFunctionSpaceForCoefficient("X"))  
         self.__g=escript.Vector(0,self.__pde_v.getFunctionSpaceForCoefficient("Y"))  
         self.setTolerance()  
         self.setAbsoluteTolerance()  
     self.__adaptSubTolerance=adaptSubTolerance  
     self.verbose=False  
     def getSolverOptionsFlux(self):  
     """  
     Returns the solver options used to solve the flux problems  
       
     *(I+D^*D)u=F*  
       
     :return: `SolverOptions`  
     """  
     return self.__pde_v.getSolverOptions()  
     def setSolverOptionsFlux(self, options=None):  
     """  
     Sets the solver options used to solve the flux problems  
       
     *(I+D^*D)u=F*  
       
     If ``options`` is not present, the options are reset to default  
     :param options: `SolverOptions`  
     :note: if the adaption of subtolerance is choosen, the tolerance set by ``options`` will be overwritten before the solver is called.  
     """  
     return self.__pde_v.setSolverOptions(options)  
     def getSolverOptionsPressure(self):  
     """  
     Returns the solver options used to solve the pressure problems  
       
     *(Q^*Q)p=Q^*G*  
       
     :return: `SolverOptions`  
     """  
     return self.__pde_p.getSolverOptions()  
     def setSolverOptionsPressure(self, options=None):  
     """  
     Sets the solver options used to solve the pressure problems  
       
     *(Q^*Q)p=Q^*G*  
       
     If ``options`` is not present, the options are reset to default  
     :param options: `SolverOptions`  
     :note: if the adaption of subtolerance is choosen, the tolerance set by ``options`` will be overwritten before the solver is called.  
     """  
     return self.__pde_p.setSolverOptions(options)  
   
     def setValue(self,f=None, g=None, location_of_fixed_pressure=None, location_of_fixed_flux=None, permeability=None):  
         """  
         assigns values to model parameters  
   
         :param f: volumetic sources/sinks  
         :type f: scalar value on the domain (e.g. `escript.Data`)  
         :param g: flux sources/sinks  
         :type g: vector values on the domain (e.g. `escript.Data`)  
         :param location_of_fixed_pressure: mask for locations where pressure is fixed  
         :type location_of_fixed_pressure: scalar value on the domain (e.g. `escript.Data`)  
         :param location_of_fixed_flux:  mask for locations where flux is fixed.  
         :type location_of_fixed_flux: vector values on the domain (e.g. `escript.Data`)  
         :param permeability: permeability tensor. If scalar ``s`` is given the tensor with  
                              ``s`` on the main diagonal is used. If vector ``v`` is given the tensor with  
                              ``v`` on the main diagonal is used.  
         :type permeability: scalar, vector or tensor values on the domain (e.g. `escript.Data`)  
   
         :note: the values of parameters which are not set by calling ``setValue`` are not altered.  
         :note: at any point on the boundary of the domain the pressure (``location_of_fixed_pressure`` >0)  
                or the normal component of the flux (``location_of_fixed_flux[i]>0`` if direction of the normal  
                is along the *x_i* axis.  
         """  
         if f !=None:  
            f=util.interpolate(f, self.__pde_v.getFunctionSpaceForCoefficient("X"))  
            if f.isEmpty():  
                f=escript.Scalar(0,self.__pde_v.getFunctionSpaceForCoefficient("X"))  
            else:  
                if f.getRank()>0: raise ValueError,"illegal rank of f."  
            self.__f=f  
         if g !=None:  
            g=util.interpolate(g, self.__pde_p.getFunctionSpaceForCoefficient("Y"))  
            if g.isEmpty():  
              g=escript.Vector(0,self.__pde_v.getFunctionSpaceForCoefficient("Y"))  
            else:  
              if not g.getShape()==(self.domain.getDim(),):  
                raise ValueError,"illegal shape of g"  
            self.__g=g  
   
         if location_of_fixed_pressure!=None: self.__pde_p.setValue(q=location_of_fixed_pressure)  
         if location_of_fixed_flux!=None: self.__pde_v.setValue(q=location_of_fixed_flux)  
   
         if permeability!=None:  
            perm=util.interpolate(permeability,self.__pde_p.getFunctionSpaceForCoefficient("A"))  
            if perm.getRank()==0:  
                perm=perm*util.kronecker(self.domain.getDim())  
            elif perm.getRank()==1:  
                perm, perm2=Tensor(0.,self.__pde_p.getFunctionSpaceForCoefficient("A")), perm  
                for i in range(self.domain.getDim()): perm[i,i]=perm2[i]  
            elif perm.getRank()==2:  
               pass  
            else:  
               raise ValueError,"illegal rank of permeability."  
            self.__permeability=perm  
            self.__pde_p.setValue(A=util.transposed_tensor_mult(self.__permeability,self.__permeability))  
   
     def setTolerance(self,rtol=1e-4):  
         """  
         sets the relative tolerance ``rtol`` used to terminate the solution process. The iteration is terminated if  
   
         *|g-v-Qp| <= atol + rtol * min( max( |g-v|, |Qp| ), max( |v|, |g-Qp| ) )*  
   
         where ``atol`` is an absolut tolerance (see `setAbsoluteTolerance`), *|f|^2 = integrate(length(f)^2)* and *(Qp)_i=k_{ij}p_{,j}* for the permeability *k_{ij}*.  
   
         :param rtol: relative tolerance for the pressure  
         :type rtol: non-negative ``float``  
         """  
         if rtol<0:  
             raise ValueError,"Relative tolerance needs to be non-negative."  
         self.__rtol=rtol  
     def getTolerance(self):  
         """  
         returns the relative tolerance  
   
         :return: current relative tolerance  
         :rtype: ``float``  
         """  
         return self.__rtol  
   
     def setAbsoluteTolerance(self,atol=0.):  
         """  
         sets the absolute tolerance ``atol`` used to terminate the solution process. The iteration is terminated if  
   
         *|g-v-Qp| <= atol + rtol * min( max( |g-v|, |Qp| ), max( |v|, |g-Qp| ) )*  
   
         where ``rtol`` is an absolut tolerance (see `setTolerance`), *|f|^2 = integrate(length(f)^2)* and *(Qp)_i=k_{ij}p_{,j}* for the permeability *k_{ij}*.  
   
         :param atol: absolute tolerance for the pressure  
         :type atol: non-negative ``float``  
         """  
         if atol<0:  
             raise ValueError,"Absolute tolerance needs to be non-negative."  
         self.__atol=atol  
     def getAbsoluteTolerance(self):  
        """  
        returns the absolute tolerance  
         
        :return: current absolute tolerance  
        :rtype: ``float``  
        """  
        return self.__atol  
     def getSubProblemTolerance(self):  
     """  
     Returns a suitable subtolerance  
     @type: ``float``  
     """  
     return max(util.EPSILON**(0.75),self.getTolerance()**2)  
     def setSubProblemTolerance(self):  
          """  
          Sets the relative tolerance to solve the subproblem(s) if subtolerance adaption is selected.  
          """  
      if self.__adaptSubTolerance:  
          sub_tol=self.getSubProblemTolerance()  
              self.getSolverOptionsFlux().setTolerance(sub_tol)  
          self.getSolverOptionsFlux().setAbsoluteTolerance(0.)  
          self.getSolverOptionsPressure().setTolerance(sub_tol)  
          self.getSolverOptionsPressure().setAbsoluteTolerance(0.)  
          if self.verbose: print "DarcyFlux: relative subtolerance is set to %e."%sub_tol  
   
     def solve(self,u0,p0, max_iter=100, verbose=False, max_num_corrections=10):  
          """  
          solves the problem.  
   
          The iteration is terminated if the residual norm is less then self.getTolerance().  
   
          :param u0: initial guess for the flux. At locations in the domain marked by ``location_of_fixed_flux`` the value of ``u0`` is kept unchanged.  
          :type u0: vector value on the domain (e.g. `escript.Data`).  
          :param p0: initial guess for the pressure. At locations in the domain marked by ``location_of_fixed_pressure`` the value of ``p0`` is kept unchanged.  
          :type p0: scalar value on the domain (e.g. `escript.Data`).  
          :param verbose: if set some information on iteration progress are printed  
          :type verbose: ``bool``  
          :return: flux and pressure  
          :rtype: ``tuple`` of `escript.Data`.  
   
          :note: The problem is solved as a least squares form  
   
          *(I+D^*D)u+Qp=D^*f+g*  
          *Q^*u+Q^*Qp=Q^*g*  
   
          where *D* is the *div* operator and *(Qp)_i=k_{ij}p_{,j}* for the permeability *k_{ij}*.  
          We eliminate the flux form the problem by setting  
   
          *u=(I+D^*D)^{-1}(D^*f-g-Qp)* with u=u0 on location_of_fixed_flux  
   
          form the first equation. Inserted into the second equation we get  
   
          *Q^*(I-(I+D^*D)^{-1})Qp= Q^*(g-(I+D^*D)^{-1}(D^*f+g))* with p=p0  on location_of_fixed_pressure  
   
          which is solved using the PCG method (precondition is *Q^*Q*). In each iteration step  
          PDEs with operator *I+D^*D* and with *Q^*Q* needs to be solved using a sub iteration scheme.  
          """  
          self.verbose=verbose  
          rtol=self.getTolerance()  
          atol=self.getAbsoluteTolerance()  
      self.setSubProblemTolerance()  
          num_corrections=0  
          converged=False  
          p=p0  
          norm_r=None  
          while not converged:  
                v=self.getFlux(p, fixed_flux=u0)  
                Qp=self.__Q(p)  
                norm_v=self.__L2(v)  
                norm_Qp=self.__L2(Qp)  
                if norm_v == 0.:  
                   if norm_Qp == 0.:  
                      return v,p  
                   else:  
                     fac=norm_Qp  
                else:  
                   if norm_Qp == 0.:  
                     fac=norm_v  
                   else:  
                     fac=2./(1./norm_v+1./norm_Qp)  
                ATOL=(atol+rtol*fac)  
                if self.verbose:  
                     print "DarcyFlux: L2 norm of v = %e."%norm_v  
                     print "DarcyFlux: L2 norm of k.util.grad(p) = %e."%norm_Qp  
                     print "DarcyFlux: L2 defect u = %e."%(util.integrate(util.length(self.__g-util.interpolate(v,escript.Function(self.domain))-Qp)**2)**(0.5),)  
                     print "DarcyFlux: L2 defect div(v) = %e."%(util.integrate((self.__f-util.div(v))**2)**(0.5),)  
                     print "DarcyFlux: absolute tolerance ATOL = %e."%ATOL  
                if norm_r == None or norm_r>ATOL:  
                    if num_corrections>max_num_corrections:  
                          raise ValueError,"maximum number of correction steps reached."  
                    p,r, norm_r=PCG(self.__g-util.interpolate(v,escript.Function(self.domain))-Qp,self.__Aprod,p,self.__Msolve_PCG,self.__inner_PCG,atol=0.5*ATOL, rtol=0.,iter_max=max_iter, verbose=self.verbose)  
                    num_corrections+=1  
                else:  
                    converged=True  
          return v,p  
     def __L2(self,v):  
          return util.sqrt(util.integrate(util.length(util.interpolate(v,escript.Function(self.domain)))**2))  
   
     def __Q(self,p):  
           return util.tensor_mult(self.__permeability,util.grad(p))  
   
     def __Aprod(self,dp):  
           if self.getSolverOptionsFlux().isVerbose(): print "DarcyFlux: Applying operator"  
           Qdp=self.__Q(dp)  
           self.__pde_v.setValue(Y=-Qdp,X=escript.Data(), r=escript.Data())  
           du=self.__pde_v.getSolution()  
           return Qdp+du  
     def __inner_GMRES(self,r,s):  
          return util.integrate(util.inner(r,s))  
   
     def __inner_PCG(self,p,r):  
          return util.integrate(util.inner(self.__Q(p), r))  
   
     def __Msolve_PCG(self,r):  
       if self.getSolverOptionsPressure().isVerbose(): print "DarcyFlux: Applying preconditioner"  
           self.__pde_p.setValue(X=util.transposed_tensor_mult(self.__permeability,r), Y=escript.Data(), r=escript.Data())  
           return self.__pde_p.getSolution()  
   
     def getFlux(self,p=None, fixed_flux=escript.Data()):  
         """  
         returns the flux for a given pressure ``p`` where the flux is equal to ``fixed_flux``  
251          on locations where ``location_of_fixed_flux`` is positive (see `setValue`).          on locations where ``location_of_fixed_flux`` is positive (see `setValue`).
252          Note that ``g`` and ``f`` are used, see `setValue`.          Notice that ``g`` is used, see `setValue`.
253    
254          :param p: pressure.          :param p: pressure.
255          :type p: scalar value on the domain (e.g. `escript.Data`).          :type p: scalar value on the domain (e.g. `escript.Data`).
256          :param fixed_flux: flux on the locations of the domain marked be ``location_of_fixed_flux``.          :param u0: flux on the locations of the domain marked be ``location_of_fixed_flux``.
257          :type fixed_flux: vector values on the domain (e.g. `escript.Data`).          :type u0: vector values on the domain (e.g. `escript.Data`) or ``None``
258          :return: flux          :return: flux
259          :rtype: `escript.Data`          :rtype: `escript.Data`
         :note: the method uses the least squares solution *u=(I+D^*D)^{-1}(D^*f-g-Qp)* where *D* is the *div* operator and *(Qp)_i=k_{ij}p_{,j}*  
                for the permeability *k_{ij}*  
260          """          """
261      self.setSubProblemTolerance()          if self.solver  == self.EVAL:
262          g=self.__g             u = self.__g-self.perm_scale * util.tensor_mult(self.__permeability,util.grad(p))
263          f=self.__f          elif self.solver  == self.POST or self.solver  == self.SMOOTH:
264          self.__pde_v.setValue(X=self.__l2*f*util.kronecker(self.domain), r=fixed_flux)              self.__pde_v.setValue(Y=util.tensor_mult(self.__permeability_inv,self.__g * 1./self.perm_scale)-util.grad(p))
265          if p == None:              if u0 == None:
266             self.__pde_v.setValue(Y=g)             self.__pde_v.setValue(r=escript.Data())
267          else:          else:
268             self.__pde_v.setValue(Y=g-self.__Q(p))             self.__pde_v.setValue(r=u0/self.perm_scale)
269          return self.__pde_v.getSolution()              u= self.__pde_v.getSolution() * self.perm_scale
270        return u
271          
272  class StokesProblemCartesian(HomogeneousSaddlePointProblem):  class StokesProblemCartesian(HomogeneousSaddlePointProblem):
273       """       """
274       solves       solves
# Line 835  class StokesProblemCartesian(Homogeneous Line 287  class StokesProblemCartesian(Homogeneous
287              sp.setTolerance()              sp.setTolerance()
288              sp.initialize(...)              sp.initialize(...)
289              v,p=sp.solve(v0,p0)              v,p=sp.solve(v0,p0)
290                sp.setStokesEquation(...) # new values for some parameters
291                v1,p1=sp.solve(v,p)
292       """       """
293       def __init__(self,domain,**kwargs):       def __init__(self,domain,**kwargs):
294           """           """
# Line 849  class StokesProblemCartesian(Homogeneous Line 303  class StokesProblemCartesian(Homogeneous
303           """           """
304           HomogeneousSaddlePointProblem.__init__(self,**kwargs)           HomogeneousSaddlePointProblem.__init__(self,**kwargs)
305           self.domain=domain           self.domain=domain
306           self.__pde_u=LinearPDE(domain,numEquations=self.domain.getDim(),numSolutions=self.domain.getDim())           self.__pde_v=LinearPDE(domain,numEquations=self.domain.getDim(),numSolutions=self.domain.getDim())
307           self.__pde_u.setSymmetryOn()           self.__pde_v.setSymmetryOn()
308            
309           self.__pde_prec=LinearPDE(domain)           self.__pde_prec=LinearPDE(domain)
310           self.__pde_prec.setReducedOrderOn()           self.__pde_prec.setReducedOrderOn()
# Line 867  class StokesProblemCartesian(Homogeneous Line 321  class StokesProblemCartesian(Homogeneous
321            
322       :rtype: `SolverOptions`       :rtype: `SolverOptions`
323       """       """
324       return self.__pde_u.getSolverOptions()       return self.__pde_v.getSolverOptions()
325       def setSolverOptionsVelocity(self, options=None):       def setSolverOptionsVelocity(self, options=None):
326           """           """
327       set the solver options for solving the equation for velocity.       set the solver options for solving the equation for velocity.
# Line 875  class StokesProblemCartesian(Homogeneous Line 329  class StokesProblemCartesian(Homogeneous
329       :param options: new solver  options       :param options: new solver  options
330       :type options: `SolverOptions`       :type options: `SolverOptions`
331       """       """
332           self.__pde_u.setSolverOptions(options)           self.__pde_v.setSolverOptions(options)
333       def getSolverOptionsPressure(self):       def getSolverOptionsPressure(self):
334           """           """
335       returns the solver options used  solve the equation for pressure.       returns the solver options used  solve the equation for pressure.
# Line 911  class StokesProblemCartesian(Homogeneous Line 365  class StokesProblemCartesian(Homogeneous
365       def updateStokesEquation(self, v, p):       def updateStokesEquation(self, v, p):
366           """           """
367           updates the Stokes equation to consider dependencies from ``v`` and ``p``           updates the Stokes equation to consider dependencies from ``v`` and ``p``
368           :note: This method can be overwritten by a subclass. Use `setStokesEquation` to set new values.           :note: This method can be overwritten by a subclass. Use `setStokesEquation` to set new values to model parameters.
369           """           """
370           pass           pass
371       def setStokesEquation(self, f=None,fixed_u_mask=None,eta=None,surface_stress=None,stress=None, restoration_factor=None):       def setStokesEquation(self, f=None,fixed_u_mask=None,eta=None,surface_stress=None,stress=None, restoration_factor=None):
# Line 934  class StokesProblemCartesian(Homogeneous Line 388  class StokesProblemCartesian(Homogeneous
388              kk=util.outer(k,k)              kk=util.outer(k,k)
389              self.eta=util.interpolate(eta, escript.Function(self.domain))              self.eta=util.interpolate(eta, escript.Function(self.domain))
390          self.__pde_prec.setValue(D=1/self.eta)          self.__pde_prec.setValue(D=1/self.eta)
391              self.__pde_u.setValue(A=self.eta*(util.swap_axes(kk,0,3)+util.swap_axes(kk,1,3)))              self.__pde_v.setValue(A=self.eta*(util.swap_axes(kk,0,3)+util.swap_axes(kk,1,3)))
392          if restoration_factor!=None:          if restoration_factor!=None:
393              n=self.domain.getNormal()              n=self.domain.getNormal()
394              self.__pde_u.setValue(d=restoration_factor*util.outer(n,n))              self.__pde_v.setValue(d=restoration_factor*util.outer(n,n))
395          if fixed_u_mask!=None:          if fixed_u_mask!=None:
396              self.__pde_u.setValue(q=fixed_u_mask)              self.__pde_v.setValue(q=fixed_u_mask)
397          if f!=None: self.__f=f          if f!=None: self.__f=f
398          if surface_stress!=None: self.__surface_stress=surface_stress          if surface_stress!=None: self.__surface_stress=surface_stress
399          if stress!=None: self.__stress=stress          if stress!=None: self.__stress=stress
# Line 1012  class StokesProblemCartesian(Homogeneous Line 466  class StokesProblemCartesian(Homogeneous
466    
467       def getDV(self, p, v, tol):       def getDV(self, p, v, tol):
468           """           """
469           return the value for v for a given p (overwrite)           return the value for v for a given p
470    
471           :param p: a pressure           :param p: a pressure
472           :param v: a initial guess for the value v to return.           :param v: a initial guess for the value v to return.
473           :return: dv given as *Adv=(f-Av-B^*p)*           :return: dv given as *Adv=(f-Av-B^*p)*
474           """           """
475           self.updateStokesEquation(v,p)           self.updateStokesEquation(v,p)
476           self.__pde_u.setValue(Y=self.__f, y=self.__surface_stress)           self.__pde_v.setValue(Y=self.__f, y=self.__surface_stress)
477       self.getSolverOptionsVelocity().setTolerance(tol)       self.getSolverOptionsVelocity().setTolerance(tol)
478       self.getSolverOptionsVelocity().setAbsoluteTolerance(0.)       self.getSolverOptionsVelocity().setAbsoluteTolerance(0.)
479           if self.__stress.isEmpty():           if self.__stress.isEmpty():
480              self.__pde_u.setValue(X=p*util.kronecker(self.domain)-2*self.eta*util.symmetric(util.grad(v)))              self.__pde_v.setValue(X=p*util.kronecker(self.domain)-2*self.eta*util.symmetric(util.grad(v)))
481           else:           else:
482              self.__pde_u.setValue(X=self.__stress+p*util.kronecker(self.domain)-2*self.eta*util.symmetric(util.grad(v)))              self.__pde_v.setValue(X=self.__stress+p*util.kronecker(self.domain)-2*self.eta*util.symmetric(util.grad(v)))
483           out=self.__pde_u.getSolution()           out=self.__pde_v.getSolution()
484           return  out           return  out
485    
486       def norm_Bv(self,Bv):       def norm_Bv(self,Bv):
# Line 1046  class StokesProblemCartesian(Homogeneous Line 500  class StokesProblemCartesian(Homogeneous
500           :return: the solution of *Av=B^*p*           :return: the solution of *Av=B^*p*
501           :note: boundary conditions on v should be zero!           :note: boundary conditions on v should be zero!
502           """           """
503           self.__pde_u.setValue(Y=escript.Data(), y=escript.Data(), X=-p*util.kronecker(self.domain))           self.__pde_v.setValue(Y=escript.Data(), y=escript.Data(), X=-p*util.kronecker(self.domain))
504           out=self.__pde_u.getSolution()           out=self.__pde_v.getSolution()
505           return  out           return  out
506    
507       def solve_prec(self,Bv, tol):       def solve_prec(self,Bv, tol):

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