/[escript]/trunk/escriptcore/py_src/flows.py
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revision 2349 by gross, Mon Mar 30 08:14:23 2009 UTC revision 3995 by jfenwick, Wed Sep 26 12:43:17 2012 UTC
# Line 1  Line 1 
1  ########################################################  # -*- coding: utf-8 -*-
2    ##############################################################################
3  #  #
4  # Copyright (c) 2003-2008 by University of Queensland  # Copyright (c) 2003-2012 by University of Queensland
5  # Earth Systems Science Computational Center (ESSCC)  # http://www.uq.edu.au
 # http://www.uq.edu.au/esscc  
6  #  #
7  # Primary Business: Queensland, Australia  # Primary Business: Queensland, Australia
8  # Licensed under the Open Software License version 3.0  # Licensed under the Open Software License version 3.0
9  # http://www.opensource.org/licenses/osl-3.0.php  # http://www.opensource.org/licenses/osl-3.0.php
10  #  #
11  ########################################################  # Development until 2012 by Earth Systems Science Computational Center (ESSCC)
12    # Development since 2012 by School of Earth Sciences
13    #
14    ##############################################################################
15    
16  __copyright__="""Copyright (c) 2003-2008 by University of Queensland  __copyright__="""Copyright (c) 2003-2012 by University of Queensland
17  Earth Systems Science Computational Center (ESSCC)  http://www.uq.edu.au
 http://www.uq.edu.au/esscc  
18  Primary Business: Queensland, Australia"""  Primary Business: Queensland, Australia"""
19  __license__="""Licensed under the Open Software License version 3.0  __license__="""Licensed under the Open Software License version 3.0
20  http://www.opensource.org/licenses/osl-3.0.php"""  http://www.opensource.org/licenses/osl-3.0.php"""
# Line 21  __url__="https://launchpad.net/escript-f Line 23  __url__="https://launchpad.net/escript-f
23  """  """
24  Some models for flow  Some models for flow
25    
26  @var __author__: name of author  :var __author__: name of author
27  @var __copyright__: copyrights  :var __copyright__: copyrights
28  @var __license__: licence agreement  :var __license__: licence agreement
29  @var __url__: url entry point on documentation  :var __url__: url entry point on documentation
30  @var __version__: version  :var __version__: version
31  @var __date__: date of the version  :var __date__: date of the version
32  """  """
33    
34  __author__="Lutz Gross, l.gross@uq.edu.au"  __author__="Lutz Gross, l.gross@uq.edu.au"
35    
36  from escript import *  from . import escriptcpp
37  import util  escore=escriptcpp
38  from linearPDEs import LinearPDE, LinearPDESystem, LinearSinglePDE  #from . import escript
39  from pdetools import HomogeneousSaddlePointProblem,Projector, ArithmeticTuple, PCG, NegativeNorm, GMRES  from . import util
40    from .linearPDEs import LinearPDE, LinearPDESystem, LinearSinglePDE, SolverOptions
41    from .pdetools import HomogeneousSaddlePointProblem,Projector, ArithmeticTuple, PCG, NegativeNorm, GMRES
42    
43  class DarcyFlow(object):  class DarcyFlow(object):
44      """     """
45      solves the problem     solves the problem
46      
47      M{u_i+k_{ij}*p_{,j} = g_i}     *u_i+k_{ij}*p_{,j} = g_i*
48      M{u_{i,i} = f}     *u_{i,i} = f*
49      
50      where M{p} represents the pressure and M{u} the Darcy flux. M{k} represents the permeability,     where *p* represents the pressure and *u* the Darcy flux. *k* represents the permeability,
51      
52      @note: The problem is solved in a least squares formulation.     :cvar EVAL: direct pressure gradient evaluation for flux
53      """     :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*
54                   where *l* is the length scale, *K* is the inverse of the permeability tensor, and *w* is a positive weighting factor.
55      def __init__(self, domain,useReduced=False):     :cvar SMOOTH: global smoothing by solving the PDE *K_{ij} u_j= - p_{,j} + K_{ij} g_j*
56          """     """
57          initializes the Darcy flux problem     EVAL="EVAL"
58          @param domain: domain of the problem     SIMPLE="EVAL"
59          @type domain: L{Domain}     POST="POST"
60          """     SMOOTH="SMOOTH"
61          self.domain=domain     def __init__(self, domain, useReduced=False, solver="POST", verbose=False, w=1.):
62          self.__l=util.longestEdge(self.domain)**2        """
63          self.__pde_v=LinearPDESystem(domain)        initializes the Darcy flux problem.
64          if useReduced: self.__pde_v.setReducedOrderOn()  
65          self.__pde_v.setSymmetryOn()        :param domain: domain of the problem
66          self.__pde_v.setValue(D=util.kronecker(domain), A=self.__l*util.outer(util.kronecker(domain),util.kronecker(domain)))        :type domain: `Domain`
67          self.__pde_p=LinearSinglePDE(domain)        :param useReduced: uses reduced oreder on flux and pressure
68          self.__pde_p.setSymmetryOn()        :type useReduced: ``bool``
69          if useReduced: self.__pde_p.setReducedOrderOn()        :param solver: solver method
70          self.__f=Scalar(0,self.__pde_v.getFunctionSpaceForCoefficient("X"))        :type solver: in [`DarcyFlow.EVAL`, `DarcyFlow.POST`, `DarcyFlow.SMOOTH` ]
71          self.__g=Vector(0,self.__pde_v.getFunctionSpaceForCoefficient("Y"))        :param verbose: if ``True`` some information on the iteration progress are printed.
72          self.setTolerance()        :type verbose: ``bool``
73          self.setAbsoluteTolerance()        :param w: weighting factor for `DarcyFlow.POST` solver
74          self.setSubProblemTolerance()        :type w: ``float``
75          
76      def setValue(self,f=None, g=None, location_of_fixed_pressure=None, location_of_fixed_flux=None, permeability=None):        """
77          """        if not solver in [DarcyFlow.EVAL, DarcyFlow.POST,  DarcyFlow.SMOOTH ] :
78          assigns values to model parameters            raise ValueError("unknown solver %d."%solver)
79    
80          @param f: volumetic sources/sinks        self.domain=domain
81          @type f: scalar value on the domain (e.g. L{Data})        self.solver=solver
82          @param g: flux sources/sinks        self.useReduced=useReduced
83          @type g: vector values on the domain (e.g. L{Data})        self.verbose=verbose
84          @param location_of_fixed_pressure: mask for locations where pressure is fixed        self.l=None
85          @type location_of_fixed_pressure: scalar value on the domain (e.g. L{Data})        self.w=None
86          @param location_of_fixed_flux:  mask for locations where flux is fixed.      
87          @type location_of_fixed_flux: vector values on the domain (e.g. L{Data})        self.__pde_p=LinearSinglePDE(domain)
88          @param permeability: permeability tensor. If scalar C{s} is given the tensor with        self.__pde_p.setSymmetryOn()
89                               C{s} on the main diagonal is used. If vector C{v} is given the tensor with        if self.useReduced: self.__pde_p.setReducedOrderOn()
90                               C{v} on the main diagonal is used.  
91          @type permeability: scalar, vector or tensor values on the domain (e.g. L{Data})        if self.solver  == self.EVAL:
92             self.__pde_v=None
93          @note: the values of parameters which are not set by calling C{setValue} are not altered.           if self.verbose: print("DarcyFlow: simple solver is used.")
94          @note: at any point on the boundary of the domain the pressure (C{location_of_fixed_pressure} >0)  
95                 or the normal component of the flux (C{location_of_fixed_flux[i]>0} if direction of the normal        elif self.solver  == self.POST:
96                 is along the M{x_i} axis.           if util.inf(w)<0.:
97          """              raise ValueError("Weighting factor must be non-negative.")
98          if f !=None:           if self.verbose: print("DarcyFlow: global postprocessing of flux is used.")
99             f=util.interpolate(f, self.__pde_v.getFunctionSpaceForCoefficient("X"))           self.__pde_v=LinearPDESystem(domain)
100             if f.isEmpty():           self.__pde_v.setSymmetryOn()
101                 f=Scalar(0,self.__pde_v.getFunctionSpaceForCoefficient("X"))           if self.useReduced: self.__pde_v.setReducedOrderOn()
102             else:           self.w=w
103                 if f.getRank()>0: raise ValueError,"illegal rank of f."           x=self.domain.getX()
104             self.__f=f           self.l=min( [util.sup(x[i])-util.inf(x[i]) for i in xrange(self.domain.getDim()) ] )
105          if g !=None:           #self.l=util.vol(self.domain)**(1./self.domain.getDim()) # length scale
106             g=util.interpolate(g, self.__pde_p.getFunctionSpaceForCoefficient("Y"))  
107             if g.isEmpty():        elif self.solver  == self.SMOOTH:
108               g=Vector(0,self.__pde_v.getFunctionSpaceForCoefficient("Y"))           self.__pde_v=LinearPDESystem(domain)
109             else:           self.__pde_v.setSymmetryOn()
110               if not g.getShape()==(self.domain.getDim(),):           if self.useReduced: self.__pde_v.setReducedOrderOn()
111                 raise ValueError,"illegal shape of g"           if self.verbose: print("DarcyFlow: flux smoothing is used.")
112             self.__g=g           self.w=0
113    
114          if location_of_fixed_pressure!=None: self.__pde_p.setValue(q=location_of_fixed_pressure)        self.__f=escore.Data(0,self.__pde_p.getFunctionSpaceForCoefficient("X"))
115          if location_of_fixed_flux!=None: self.__pde_v.setValue(q=location_of_fixed_flux)        self.__g=escore.Vector(0,self.__pde_p.getFunctionSpaceForCoefficient("Y"))
116          self.__permeability_invXg=escore.Vector(0,self.__pde_p.getFunctionSpaceForCoefficient("Y"))
117          if permeability!=None:        self.__permeability_invXg_ref=util.numpy.zeros((self.domain.getDim()),util.numpy.float64)
118             perm=util.interpolate(permeability,self.__pde_p.getFunctionSpaceForCoefficient("A"))        self.ref_point_id=None
119             if perm.getRank()==0:        self.ref_point=util.numpy.zeros((self.domain.getDim()),util.numpy.float64)
120                 perm=perm*util.kronecker(self.domain.getDim())        self.location_of_fixed_pressure = escore.Data(0, self.__pde_p.getFunctionSpaceForCoefficient("q"))
121             elif perm.getRank()==1:        self.location_of_fixed_flux = escore.Vector(0, self.__pde_p.getFunctionSpaceForCoefficient("q"))
122                 perm, perm2=Tensor(0.,self.__pde_p.getFunctionSpaceForCoefficient("A")), perm        self.perm_scale=1.
123                 for i in range(self.domain.getDim()): perm[i,i]=perm2[i]      
124             elif perm.getRank()==2:          
125                pass     def setValue(self,f=None, g=None, location_of_fixed_pressure=None, location_of_fixed_flux=None, permeability=None):
126             else:        """
127                raise ValueError,"illegal rank of permeability."        assigns values to model parameters
128             self.__permeability=perm  
129             self.__pde_p.setValue(A=util.transposed_tensor_mult(self.__permeability,self.__permeability))        :param f: volumetic sources/sinks
130          :type f: scalar value on the domain (e.g. `escript.Data`)
131      def setTolerance(self,rtol=1e-4):        :param g: flux sources/sinks
132          """        :type g: vector values on the domain (e.g. `escript.Data`)
133          sets the relative tolerance C{rtol} used to terminate the solution process. The iteration is terminated if        :param location_of_fixed_pressure: mask for locations where pressure is fixed
134          :type location_of_fixed_pressure: scalar value on the domain (e.g. `escript.Data`)
135          M{|g-v-Qp| <= atol + rtol * min( max( |g-v|, |Qp| ), max( |v|, |g-Qp| ) ) }        :param location_of_fixed_flux:  mask for locations where flux is fixed.
136          :type location_of_fixed_flux: vector values on the domain (e.g. `escript.Data`)
137          where C{atol} is an absolut tolerance (see L{setAbsoluteTolerance}), M{|f|^2 = integrate(length(f)^2)} and M{(Qp)_i=k_{ij}p_{,j}} for the permeability M{k_{ij}}.        :param permeability: permeability tensor. If scalar ``s`` is given the tensor with ``s`` on the main diagonal is used.
138          :type permeability: scalar or symmetric tensor values on the domain (e.g. `escript.Data`)
139          @param rtol: relative tolerance for the pressure  
140          @type rtol: non-negative C{float}        :note: the values of parameters which are not set by calling ``setValue`` are not altered.
141          """        :note: at any point on the boundary of the domain the pressure
142          if rtol<0:               (``location_of_fixed_pressure`` >0) or the normal component of the
143              raise ValueError,"Relative tolerance needs to be non-negative."               flux (``location_of_fixed_flux[i]>0``) if direction of the normal
144          self.__rtol=rtol               is along the *x_i* axis.
145      def getTolerance(self):  
146          """        """
147          returns the relative tolerance        if location_of_fixed_pressure!=None:
148               self.location_of_fixed_pressure=util.wherePositive(util.interpolate(location_of_fixed_pressure, self.__pde_p.getFunctionSpaceForCoefficient("q")))
149          @return: current relative tolerance             self.ref_point_id=self.location_of_fixed_pressure.maxGlobalDataPoint()
150          @rtype: C{float}             if not self.location_of_fixed_pressure.getTupleForGlobalDataPoint(*self.ref_point_id)[0] > 0: raise ValueError("pressure needs to be fixed at least one point.")
151          """             self.ref_point=self.__pde_p.getFunctionSpaceForCoefficient("q").getX().getTupleForGlobalDataPoint(*self.ref_point_id)
152          return self.__rtol             if self.verbose: print(("DarcyFlow: reference point at %s."%(self.ref_point,)))
153               self.__pde_p.setValue(q=self.location_of_fixed_pressure)
154      def setAbsoluteTolerance(self,atol=0.):        if location_of_fixed_flux!=None:
155          """            self.location_of_fixed_flux=util.wherePositive(location_of_fixed_flux)
156          sets the absolute tolerance C{atol} used to terminate the solution process. The iteration is terminated if            if not self.__pde_v == None:
157                  self.__pde_v.setValue(q=self.location_of_fixed_flux)
158          M{|g-v-Qp| <= atol + rtol * min( max( |g-v|, |Qp| ), max( |v|, |g-Qp| ) ) }              
159          if permeability!=None:
160          where C{rtol} is an absolut tolerance (see L{setTolerance}), M{|f|^2 = integrate(length(f)^2)} and M{(Qp)_i=k_{ij}p_{,j}} for the permeability M{k_{ij}}.      
161             perm=util.interpolate(permeability,self.__pde_p.getFunctionSpaceForCoefficient("A"))
162          @param atol: absolute tolerance for the pressure           self.perm_scale=util.Lsup(util.length(perm))
163          @type atol: non-negative C{float}           if self.verbose: print(("DarcyFlow: permeability scaling factor = %e."%self.perm_scale))
164          """           perm=perm*(1./self.perm_scale)
165          if atol<0:          
166              raise ValueError,"Absolute tolerance needs to be non-negative."           if perm.getRank()==0:
167          self.__atol=atol  
168      def getAbsoluteTolerance(self):              perm_inv=(1./perm)
169         """              perm_inv=perm_inv*util.kronecker(self.domain.getDim())
170         returns the absolute tolerance              perm=perm*util.kronecker(self.domain.getDim())
171                  
172         @return: current absolute tolerance          
173         @rtype: C{float}           elif perm.getRank()==2:
174         """              perm_inv=util.inverse(perm)
        return self.__atol  
   
     def setSubProblemTolerance(self,rtol=None):  
          """  
          Sets the relative tolerance to solve the subproblem(s). If C{rtol} is not present  
          C{self.getTolerance()**2} is used.  
   
          @param rtol: relative tolerence  
          @type rtol: positive C{float}  
          """  
          if rtol == None:  
               if self.getTolerance()<=0.:  
                   raise ValueError,"A positive relative tolerance must be set."  
               self.__sub_tol=max(util.EPSILON**(0.75),self.getTolerance()**2)  
175           else:           else:
176               if rtol<=0:              raise ValueError("illegal rank of permeability.")
177                   raise ValueError,"sub-problem tolerance must be positive."          
178               self.__sub_tol=max(util.EPSILON**(0.75),rtol)           self.__permeability=perm
179             self.__permeability_inv=perm_inv
180      def getSubProblemTolerance(self):      
181           """           #====================
182           Returns the subproblem reduction factor.           self.__pde_p.setValue(A=self.__permeability)
183             if self.solver  == self.EVAL:
184           @return: subproblem reduction factor                pass # no extra work required
185           @rtype: C{float}           elif self.solver  == self.POST:
186           """                k=util.kronecker(self.domain.getDim())
187           return self.__sub_tol                self.omega = self.w*util.length(perm_inv)*self.l*self.domain.getSize()
188                  #self.__pde_v.setValue(D=self.__permeability_inv, A=self.omega*util.outer(k,k))
189      def solve(self,u0,p0, max_iter=100, verbose=False, show_details=False, max_num_corrections=10):                self.__pde_v.setValue(D=self.__permeability_inv, A_reduced=self.omega*util.outer(k,k))
190           """           elif self.solver  == self.SMOOTH:
191           solves the problem.              self.__pde_v.setValue(D=self.__permeability_inv)
192    
193           The iteration is terminated if the residual norm is less then self.getTolerance().        if g != None:
194            g=util.interpolate(g, self.__pde_p.getFunctionSpaceForCoefficient("Y"))
195           @param u0: initial guess for the flux. At locations in the domain marked by C{location_of_fixed_flux} the value of C{u0} is kept unchanged.          if g.isEmpty():
196           @type u0: vector value on the domain (e.g. L{Data}).               g=Vector(0,self.__pde_p.getFunctionSpaceForCoefficient("Y"))
          @param p0: initial guess for the pressure. At locations in the domain marked by C{location_of_fixed_pressure} the value of C{p0} is kept unchanged.  
          @type p0: scalar value on the domain (e.g. L{Data}).  
          @param verbose: if set some information on iteration progress are printed  
          @type verbose: C{bool}  
          @param show_details:  if set information on the subiteration process are printed.  
          @type show_details: C{bool}  
          @return: flux and pressure  
          @rtype: C{tuple} of L{Data}.  
   
          @note: The problem is solved as a least squares form  
   
          M{(I+D^*D)u+Qp=D^*f+g}  
          M{Q^*u+Q^*Qp=Q^*g}  
   
          where M{D} is the M{div} operator and M{(Qp)_i=k_{ij}p_{,j}} for the permeability M{k_{ij}}.  
          We eliminate the flux form the problem by setting  
   
          M{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  
   
          M{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 M{Q^*Q}). In each iteration step  
          PDEs with operator M{I+D^*D} and with M{Q^*Q} needs to be solved using a sub iteration scheme.  
          """  
          self.verbose=verbose or True  
          self.show_details= show_details and self.verbose  
          rtol=self.getTolerance()  
          atol=self.getAbsoluteTolerance()  
          if self.verbose: print "DarcyFlux: initial sub tolerance = %e"%self.getSubProblemTolerance()  
   
          num_corrections=0  
          converged=False  
          p=p0  
          norm_r=None  
          while not converged:  
                v=self.getFlux(p, fixed_flux=u0, show_details=self.show_details)  
                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.grad(p) = %e."%norm_Qp  
                     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,Function(self.domain))-Qp,self.__Aprod,p,self.__Msolve_PCG,self.__inner_PCG,atol=0.1*ATOL, rtol=0.,iter_max=max_iter, verbose=self.verbose)  
                    num_corrections+=1  
                else:  
                    converged=True  
          return v,p  
 #  
 #                
 #               r_hat=g-util.interpolate(v,Function(self.domain))-Qp  
 #               #===========================================================================  
 #               norm_r_hat=self.__L2(r_hat)  
 #               norm_v=self.__L2(v)  
 #               norm_g=self.__L2(g)  
 #               norm_gv=self.__L2(g-v)  
 #               norm_Qp=self.__L2(Qp)  
 #               norm_gQp=self.__L2(g-Qp)  
 #               fac=min(max(norm_v,norm_gQp),max(norm_Qp,norm_gv))  
 #               fac=min(norm_v,norm_Qp,norm_gv)  
 #               norm_r_hat_PCG=util.sqrt(self.__inner_PCG(self.__Msolve_PCG(r_hat),r_hat))  
 #               print "norm_r_hat = ",norm_r_hat,norm_r_hat_PCG, norm_r_hat_PCG/norm_r_hat  
 #               if r!=None:  
 #                   print "diff = ",self.__L2(r-r_hat)/norm_r_hat  
 #                   sub_tol=min(rtol/self.__L2(r-r_hat)*norm_r_hat,1.)*self.getSubProblemTolerance()  
 #                   self.setSubProblemTolerance(sub_tol)  
 #                   print "subtol_new=",self.getSubProblemTolerance()  
 #               print "norm_v = ",norm_v  
 #               print "norm_gv = ",norm_gv  
 #               print "norm_Qp = ",norm_Qp  
 #               print "norm_gQp = ",norm_gQp  
 #               print "norm_g = ",norm_g  
 #               print "max(norm_v,norm_gQp)=",max(norm_v,norm_gQp)  
 #               print "max(norm_Qp,norm_gv)=",max(norm_Qp,norm_gv)  
 #               if fac == 0:  
 #                   if self.verbose: print "DarcyFlux: trivial case!"  
 #                   return v,p  
 #               #===============================================================================  
 #               # norm_v=util.sqrt(self.__inner_PCG(self.__Msolve_PCG(v),v))  
 #               # norm_Qp=self.__L2(Qp)  
 #               norm_r_hat=util.sqrt(self.__inner_PCG(self.__Msolve_PCG(r_hat),r_hat))  
 #               # print "**** norm_v, norm_Qp :",norm_v,norm_Qp  
 #  
 #               ATOL=(atol+rtol*2./(1./norm_v+1./norm_Qp))  
 #               if self.verbose:  
 #                   print "DarcyFlux: residual = %e"%norm_r_hat  
 #                   print "DarcyFlux: absolute tolerance ATOL = %e."%ATOL  
 #               if norm_r_hat <= ATOL:  
 #                   print "DarcyFlux: iteration finalized."  
 #                   converged=True  
 #               else:  
 #                   # p=GMRES(r_hat,self.__Aprod, p, self.__inner_GMRES, atol=ATOL, rtol=0., iter_max=max_iter, iter_restart=20, verbose=self.verbose,P_R=self.__Msolve_PCG)  
 #                   # p,r=PCG(r_hat,self.__Aprod,p,self.__Msolve_PCG,self.__inner_PCG,atol=ATOL*min(0.1,norm_r_hat_PCG/norm_r_hat), rtol=0.,iter_max=max_iter, verbose=self.verbose)  
 #                   p,r, norm_r=PCG(r_hat,self.__Aprod,p,self.__Msolve_PCG,self.__inner_PCG,atol=0.1*ATOL, rtol=0.,iter_max=max_iter, verbose=self.verbose)  
 #               print "norm_r =",norm_r  
 #         return v,p  
     def __L2(self,v):  
          return util.sqrt(util.integrate(util.length(util.interpolate(v,Function(self.domain)))**2))  
   
     def __Q(self,p):  
           return util.tensor_mult(self.__permeability,util.grad(p))  
   
     def __Aprod(self,dp):  
           self.__pde_v.setTolerance(self.getSubProblemTolerance())  
           if self.show_details: print "DarcyFlux: Applying operator"  
           Qdp=self.__Q(dp)  
           self.__pde_v.setValue(Y=-Qdp,X=Data(), r=Data())  
           du=self.__pde_v.getSolution(verbose=self.show_details, iter_max = 100000)  
           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):  
           self.__pde_p.setTolerance(self.getSubProblemTolerance())  
           if self.show_details: print "DarcyFlux: Applying preconditioner"  
           self.__pde_p.setValue(X=util.transposed_tensor_mult(self.__permeability,r), Y=Data(), r=Data())  
           return self.__pde_p.getSolution(verbose=self.show_details, iter_max = 100000)  
   
     def getFlux(self,p=None, fixed_flux=Data(), show_details=False):  
         """  
         returns the flux for a given pressure C{p} where the flux is equal to C{fixed_flux}  
         on locations where C{location_of_fixed_flux} is positive (see L{setValue}).  
         Note that C{g} and C{f} are used, see L{setValue}.  
   
         @param p: pressure.  
         @type p: scalar value on the domain (e.g. L{Data}).  
         @param fixed_flux: flux on the locations of the domain marked be C{location_of_fixed_flux}.  
         @type fixed_flux: vector values on the domain (e.g. L{Data}).  
         @param tol: relative tolerance to be used.  
         @type tol: positive C{float}.  
         @return: flux  
         @rtype: L{Data}  
         @note: the method uses the least squares solution M{u=(I+D^*D)^{-1}(D^*f-g-Qp)} where M{D} is the M{div} operator and M{(Qp)_i=k_{ij}p_{,j}}  
                for the permeability M{k_{ij}}  
         """  
         self.__pde_v.setTolerance(self.getSubProblemTolerance())  
         g=self.__g  
         f=self.__f  
         self.__pde_v.setValue(X=self.__l*f*util.kronecker(self.domain), r=fixed_flux)  
         if p == None:  
            self.__pde_v.setValue(Y=g)  
197          else:          else:
198             self.__pde_v.setValue(Y=g-self.__Q(p))               if not g.getShape()==(self.domain.getDim(),): raise ValueError("illegal shape of g")
199          return self.__pde_v.getSolution(verbose=show_details, iter_max=100000)          self.__g=g
200            self.__permeability_invXg=util.tensor_mult(self.__permeability_inv,self.__g * (1./self.perm_scale ))
201            self.__permeability_invXg_ref=util.integrate(self.__permeability_invXg)/util.vol(self.domain)
202          if f !=None:
203             f=util.interpolate(f, self.__pde_p.getFunctionSpaceForCoefficient("Y"))
204             if f.isEmpty():      
205                 f=Scalar(0,self.__pde_p.getFunctionSpaceForCoefficient("Y"))
206             else:
207                 if f.getRank()>0: raise ValueError("illegal rank of f.")
208             self.__f=f
209    
210       def getSolverOptionsFlux(self):
211          """
212          Returns the solver options used to solve the flux problems
213          :return: `SolverOptions`
214          """
215          if self.__pde_v == None:
216              return None
217          else:
218              return self.__pde_v.getSolverOptions()
219          
220       def setSolverOptionsFlux(self, options=None):
221          """
222          Sets the solver options used to solve the flux problems
223          If ``options`` is not present, the options are reset to default
224          :param options: `SolverOptions`
225          """
226          if not self.__pde_v == None:
227              self.__pde_v.setSolverOptions(options)
228        
229       def getSolverOptionsPressure(self):
230          """
231          Returns the solver options used to solve the pressure problems
232          :return: `SolverOptions`
233          """
234          return self.__pde_p.getSolverOptions()
235          
236       def setSolverOptionsPressure(self, options=None):
237          """
238          Sets the solver options used to solve the pressure problems
239          If ``options`` is not present, the options are reset to default
240          
241          :param options: `SolverOptions`
242          :note: if the adaption of subtolerance is choosen, the tolerance set by ``options`` will be overwritten before the solver is called.
243          """
244          return self.__pde_p.setSolverOptions(options)
245          
246       def solve(self, u0, p0):
247          """
248          solves the problem.
249          
250          :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.
251          :type u0: vector value on the domain (e.g. `escript.Data`).
252          :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.
253          :type p0: scalar value on the domain (e.g. `escript.Data`).
254          :return: flux and pressure
255          :rtype: ``tuple`` of `escript.Data`.
256    
257          """
258          p0=util.interpolate(p0, self.__pde_p.getFunctionSpaceForCoefficient("q"))
259          if self.ref_point_id == None:
260              p_ref=0
261          else:
262              p_ref=p0.getTupleForGlobalDataPoint(*self.ref_point_id)[0]
263          p0_hydrostatic=p_ref+util.inner(self.__permeability_invXg_ref, self.__pde_p.getFunctionSpaceForCoefficient("q").getX() - self.ref_point)
264          g_2=self.__g - util.tensor_mult(self.__permeability, self.__permeability_invXg_ref * self.perm_scale)
265          self.__pde_p.setValue(X=g_2 * 1./self.perm_scale,
266                                Y=self.__f * 1./self.perm_scale,
267                                y= - util.inner(self.domain.getNormal(),u0 * self.location_of_fixed_flux * 1./self.perm_scale ),
268                                r=p0 - p0_hydrostatic)
269          pp=self.__pde_p.getSolution()
270          u = self._getFlux(pp, u0)
271          return u,pp + p0_hydrostatic
272          
273       def getFlux(self,p, u0=None):
274            """
275            returns the flux for a given pressure ``p`` where the flux is equal to ``u0``
276            on locations where ``location_of_fixed_flux`` is positive (see `setValue`).
277            Notice that ``g`` is used, see `setValue`.
278    
279            :param p: pressure.
280            :type p: scalar value on the domain (e.g. `escript.Data`).
281            :param u0: flux on the locations of the domain marked be ``location_of_fixed_flux``.
282            :type u0: vector values on the domain (e.g. `escript.Data`) or ``None``
283            :return: flux
284            :rtype: `escript.Data`
285            """
286            p=util.interpolate(p, self.__pde_p.getFunctionSpaceForCoefficient("q"))
287            if self.ref_point_id == None:
288                p_ref=0
289            else:
290                p_ref=p.getTupleForGlobalDataPoint(*self.ref_point_id)[0]
291            p_hydrostatic=p_ref+util.inner(self.__permeability_invXg_ref, self.__pde_p.getFunctionSpaceForCoefficient("q").getX() - self.ref_point)
292            return self._getFlux(p-p_hydrostatic, u0)
293    
294       def _getFlux(self, pp, u0=None):
295            """
296            returns the flux for a given pressure ``pp`` where the flux is equal to
297            ``u0`` on locations where ``location_of_fixed_flux`` is positive (see
298            `setValue`). Notice that ``g`` is used, see `setValue`.
299    
300            :param pp: pressure.
301            :type pp: scalar value on the domain (i.e. `escript.Data`).
302            :param u0: flux on the locations of the domain marked in ``location_of_fixed_flux``.
303            :type u0: vector values on the domain (i.e. `escript.Data`) or ``None``
304            :return: flux
305            :rtype: `escript.Data`
306            """
307            if self.solver  == self.EVAL:
308               u = self.__g - util.tensor_mult(self.__permeability, self.perm_scale * (util.grad(pp) + self.__permeability_invXg_ref))
309            elif self.solver  == self.POST or self.solver  == self.SMOOTH:
310                self.__pde_v.setValue(Y= self.__permeability_invXg - (util.grad(pp) + self.__permeability_invXg_ref))
311                print
312                if u0 == None:
313                   self.__pde_v.setValue(r=escore.Data())
314                else:
315                   if not isinstance(u0, escore.Data) : u0 = escore.Vector(u0, escore.Solution(self.domain))
316                   self.__pde_v.setValue(r=1./self.perm_scale * u0)
317                u= self.__pde_v.getSolution() * self.perm_scale
318            return u
319          
320  class StokesProblemCartesian(HomogeneousSaddlePointProblem):  class StokesProblemCartesian(HomogeneousSaddlePointProblem):
321       """       """
322       solves       solves
# Line 386  class StokesProblemCartesian(Homogeneous Line 335  class StokesProblemCartesian(Homogeneous
335              sp.setTolerance()              sp.setTolerance()
336              sp.initialize(...)              sp.initialize(...)
337              v,p=sp.solve(v0,p0)              v,p=sp.solve(v0,p0)
338                sp.setStokesEquation(...) # new values for some parameters
339                v1,p1=sp.solve(v,p)
340       """       """
341       def __init__(self,domain,**kwargs):       def __init__(self,domain,**kwargs):
342           """           """
343           initialize the Stokes Problem           initialize the Stokes Problem
344    
345           @param domain: domain of the problem. The approximation order needs to be two.           The approximation spaces used for velocity (=Solution(domain)) and pressure (=ReducedSolution(domain)) must be
346           @type domain: L{Domain}           LBB complient, for instance using quadratic and linear approximation on the same element or using linear approximation
347           @warning: The apprximation order needs to be two otherwise you may see oscilations in the pressure.           with macro elements for the pressure.
348    
349             :param domain: domain of the problem.
350             :type domain: `Domain`
351           """           """
352           HomogeneousSaddlePointProblem.__init__(self,**kwargs)           HomogeneousSaddlePointProblem.__init__(self,**kwargs)
353           self.domain=domain           self.domain=domain
354           self.vol=util.integrate(1.,Function(self.domain))           self.__pde_v=LinearPDE(domain,numEquations=self.domain.getDim(),numSolutions=self.domain.getDim())
355           self.__pde_u=LinearPDE(domain,numEquations=self.domain.getDim(),numSolutions=self.domain.getDim())           self.__pde_v.setSymmetryOn()
356           self.__pde_u.setSymmetryOn()      
          # self.__pde_u.setSolverMethod(self.__pde_u.DIRECT)  
          # self.__pde_u.setSolverMethod(preconditioner=LinearPDE.RILU)  
   
357           self.__pde_prec=LinearPDE(domain)           self.__pde_prec=LinearPDE(domain)
358           self.__pde_prec.setReducedOrderOn()           self.__pde_prec.setReducedOrderOn()
          # self.__pde_prec.setSolverMethod(self.__pde_prec.LUMPING)  
359           self.__pde_prec.setSymmetryOn()           self.__pde_prec.setSymmetryOn()
360    
361       def initialize(self,f=Data(),fixed_u_mask=Data(),eta=1,surface_stress=Data(),stress=Data()):           self.__pde_proj=LinearPDE(domain)
362             self.__pde_proj.setReducedOrderOn()
363             self.__pde_proj.setValue(D=1)
364             self.__pde_proj.setSymmetryOn()
365    
366         def getSolverOptionsVelocity(self):
367             """
368         returns the solver options used  solve the equation for velocity.
369        
370         :rtype: `SolverOptions`
371         """
372             return self.__pde_v.getSolverOptions()
373         def setSolverOptionsVelocity(self, options=None):
374             """
375         set the solver options for solving the equation for velocity.
376        
377         :param options: new solver  options
378         :type options: `SolverOptions`
379         """
380             self.__pde_v.setSolverOptions(options)
381         def getSolverOptionsPressure(self):
382             """
383         returns the solver options used  solve the equation for pressure.
384         :rtype: `SolverOptions`
385         """
386             return self.__pde_prec.getSolverOptions()
387         def setSolverOptionsPressure(self, options=None):
388             """
389         set the solver options for solving the equation for pressure.
390         :param options: new solver  options
391         :type options: `SolverOptions`
392         """
393             self.__pde_prec.setSolverOptions(options)
394    
395         def setSolverOptionsDiv(self, options=None):
396             """
397         set the solver options for solving the equation to project the divergence of
398         the velocity onto the function space of presure.
399        
400         :param options: new solver options
401         :type options: `SolverOptions`
402         """
403             self.__pde_proj.setSolverOptions(options)
404         def getSolverOptionsDiv(self):
405             """
406         returns the solver options for solving the equation to project the divergence of
407         the velocity onto the function space of presure.
408        
409         :rtype: `SolverOptions`
410         """
411             return self.__pde_proj.getSolverOptions()
412    
413         def updateStokesEquation(self, v, p):
414             """
415             updates the Stokes equation to consider dependencies from ``v`` and ``p``
416             :note: This method can be overwritten by a subclass. Use `setStokesEquation` to set new values to model parameters.
417             """
418             pass
419         def setStokesEquation(self, f=None,fixed_u_mask=None,eta=None,surface_stress=None,stress=None, restoration_factor=None):
420            """
421            assigns new values to the model parameters.
422    
423            :param f: external force
424            :type f: `Vector` object in `FunctionSpace` `Function` or similar
425            :param fixed_u_mask: mask of locations with fixed velocity.
426            :type fixed_u_mask: `Vector` object on `FunctionSpace` `Solution` or similar
427            :param eta: viscosity
428            :type eta: `Scalar` object on `FunctionSpace` `Function` or similar
429            :param surface_stress: normal surface stress
430            :type surface_stress: `Vector` object on `FunctionSpace` `FunctionOnBoundary` or similar
431            :param stress: initial stress
432        :type stress: `Tensor` object on `FunctionSpace` `Function` or similar
433            """
434            if eta !=None:
435                k=util.kronecker(self.domain.getDim())
436                kk=util.outer(k,k)
437                self.eta=util.interpolate(eta, escore.Function(self.domain))
438                self.__pde_prec.setValue(D=1/self.eta)
439                self.__pde_v.setValue(A=self.eta*(util.swap_axes(kk,0,3)+util.swap_axes(kk,1,3)))
440            if restoration_factor!=None:
441                n=self.domain.getNormal()
442                self.__pde_v.setValue(d=restoration_factor*util.outer(n,n))
443            if fixed_u_mask!=None:
444                self.__pde_v.setValue(q=fixed_u_mask)
445            if f!=None: self.__f=f
446            if surface_stress!=None: self.__surface_stress=surface_stress
447            if stress!=None: self.__stress=stress
448    
449         def initialize(self,f=escore.Data(),fixed_u_mask=escore.Data(),eta=1,surface_stress=escore.Data(),stress=escore.Data(), restoration_factor=0):
450          """          """
451          assigns values to the model parameters          assigns values to the model parameters
452    
453          @param f: external force          :param f: external force
454          @type f: L{Vector} object in L{FunctionSpace} L{Function} or similar          :type f: `Vector` object in `FunctionSpace` `Function` or similar
455          @param fixed_u_mask: mask of locations with fixed velocity.          :param fixed_u_mask: mask of locations with fixed velocity.
456          @type fixed_u_mask: L{Vector} object on L{FunctionSpace} L{Solution} or similar          :type fixed_u_mask: `Vector` object on `FunctionSpace` `Solution` or similar
457          @param eta: viscosity          :param eta: viscosity
458          @type eta: L{Scalar} object on L{FunctionSpace} L{Function} or similar          :type eta: `Scalar` object on `FunctionSpace` `Function` or similar
459          @param surface_stress: normal surface stress          :param surface_stress: normal surface stress
460          @type eta: L{Vector} object on L{FunctionSpace} L{FunctionOnBoundary} or similar          :type surface_stress: `Vector` object on `FunctionSpace` `FunctionOnBoundary` or similar
461          @param stress: initial stress          :param stress: initial stress
462      @type stress: L{Tensor} object on L{FunctionSpace} L{Function} or similar          :type stress: `Tensor` object on `FunctionSpace` `Function` or similar
         @note: All values needs to be set.  
   
463          """          """
464          self.eta=eta          self.setStokesEquation(f,fixed_u_mask, eta, surface_stress, stress, restoration_factor)
         A =self.__pde_u.createCoefficient("A")  
     self.__pde_u.setValue(A=Data())  
         for i in range(self.domain.getDim()):  
         for j in range(self.domain.getDim()):  
             A[i,j,j,i] += 1.  
             A[i,j,i,j] += 1.  
     self.__pde_prec.setValue(D=1/self.eta)  
         self.__pde_u.setValue(A=A*self.eta,q=fixed_u_mask)  
         self.__f=f  
         self.__surface_stress=surface_stress  
         self.__stress=stress  
465    
466       def inner_pBv(self,p,v):       def Bv(self,v,tol):
467           """           """
468           returns inner product of element p and div(v)           returns inner product of element p and div(v)
469    
470           @param p: a pressure increment           :param v: a residual
471           @param v: a residual           :return: inner product of element p and div(v)
472           @return: inner product of element p and div(v)           :rtype: ``float``
473           @rtype: C{float}           """
474             self.__pde_proj.setValue(Y=-util.div(v))
475             self.getSolverOptionsDiv().setTolerance(tol)
476             self.getSolverOptionsDiv().setAbsoluteTolerance(0.)
477             out=self.__pde_proj.getSolution()
478             return out
479    
480         def inner_pBv(self,p,Bv):
481             """
482             returns inner product of element p and Bv=-div(v)
483    
484             :param p: a pressure increment
485             :param Bv: a residual
486             :return: inner product of element p and Bv=-div(v)
487             :rtype: ``float``
488           """           """
489           return util.integrate(-p*util.div(v))           return util.integrate(util.interpolate(p,escore.Function(self.domain))*util.interpolate(Bv, escore.Function(self.domain)))
490    
491       def inner_p(self,p0,p1):       def inner_p(self,p0,p1):
492           """           """
493           Returns inner product of p0 and p1           Returns inner product of p0 and p1
494    
495           @param p0: a pressure           :param p0: a pressure
496           @param p1: a pressure           :param p1: a pressure
497           @return: inner product of p0 and p1           :return: inner product of p0 and p1
498           @rtype: C{float}           :rtype: ``float``
499           """           """
500           s0=util.interpolate(p0/self.eta,Function(self.domain))           s0=util.interpolate(p0, escore.Function(self.domain))
501           s1=util.interpolate(p1/self.eta,Function(self.domain))           s1=util.interpolate(p1, escore.Function(self.domain))
502           return util.integrate(s0*s1)           return util.integrate(s0*s1)
503    
504       def norm_v(self,v):       def norm_v(self,v):
505           """           """
506           returns the norm of v           returns the norm of v
507    
508           @param v: a velovity           :param v: a velovity
509           @return: norm of v           :return: norm of v
510           @rtype: non-negative C{float}           :rtype: non-negative ``float``
511           """           """
512           return util.sqrt(util.integrate(util.length(util.grad(v))))           return util.sqrt(util.integrate(util.length(util.grad(v))**2))
513    
514    
515       def getV(self, p, v0):       def getDV(self, p, v, tol):
516           """           """
517           return the value for v for a given p (overwrite)           return the value for v for a given p
518    
519           @param p: a pressure           :param p: a pressure
520           @param v0: a initial guess for the value v to return.           :param v: a initial guess for the value v to return.
521           @return: v given as M{v= A^{-1} (f-B^*p)}           :return: dv given as *Adv=(f-Av-B^*p)*
522           """           """
523           self.__pde_u.setTolerance(self.getSubProblemTolerance())           self.updateStokesEquation(v,p)
524           self.__pde_u.setValue(Y=self.__f, y=self.__surface_stress, r=v0)           self.__pde_v.setValue(Y=self.__f, y=self.__surface_stress)
525             self.getSolverOptionsVelocity().setTolerance(tol)
526             self.getSolverOptionsVelocity().setAbsoluteTolerance(0.)
527           if self.__stress.isEmpty():           if self.__stress.isEmpty():
528              self.__pde_u.setValue(X=p*util.kronecker(self.domain))              self.__pde_v.setValue(X=p*util.kronecker(self.domain)-2*self.eta*util.symmetric(util.grad(v)))
529           else:           else:
530              self.__pde_u.setValue(X=self.__stress+p*util.kronecker(self.domain))              self.__pde_v.setValue(X=self.__stress+p*util.kronecker(self.domain)-2*self.eta*util.symmetric(util.grad(v)))
531           out=self.__pde_u.getSolution(verbose=self.show_details)           out=self.__pde_v.getSolution()
532           return  out           return  out
533    
534         def norm_Bv(self,Bv):
          raise NotImplementedError,"no v calculation implemented."  
   
   
      def norm_Bv(self,v):  
535          """          """
536          Returns Bv (overwrite).          Returns Bv (overwrite).
537    
538          @rtype: equal to the type of p          :rtype: equal to the type of p
539          @note: boundary conditions on p should be zero!          :note: boundary conditions on p should be zero!
540          """          """
541          return util.sqrt(util.integrate(util.div(v)**2))          return util.sqrt(util.integrate(util.interpolate(Bv, escore.Function(self.domain))**2))
542    
543       def solve_AinvBt(self,p):       def solve_AinvBt(self,p, tol):
544           """           """
545           Solves M{Av=B^*p} with accuracy L{self.getSubProblemTolerance()}           Solves *Av=B^*p* with accuracy `tol`
546    
547           @param p: a pressure increment           :param p: a pressure increment
548           @return: the solution of M{Av=B^*p}           :return: the solution of *Av=B^*p*
549           @note: boundary conditions on v should be zero!           :note: boundary conditions on v should be zero!
550           """           """
551           self.__pde_u.setTolerance(self.getSubProblemTolerance())           self.__pde_v.setValue(Y=escore.Data(), y=escore.Data(), X=-p*util.kronecker(self.domain))
552           self.__pde_u.setValue(Y=Data(), y=Data(), r=Data(),X=-p*util.kronecker(self.domain))           out=self.__pde_v.getSolution()
          out=self.__pde_u.getSolution(verbose=self.show_details)  
553           return  out           return  out
554    
555       def solve_precB(self,v):       def solve_prec(self,Bv, tol):
556           """           """
557           applies preconditioner for for M{BA^{-1}B^*} to M{Bv}           applies preconditioner for for *BA^{-1}B^** to *Bv*
558           with accuracy L{self.getSubProblemTolerance()} (overwrite).           with accuracy ``self.getSubProblemTolerance()``
559    
560           @param v: velocity increment           :param Bv: velocity increment
561           @return: M{p=P(Bv)} where M{P^{-1}} is an approximation of M{BA^{-1}B^*}           :return: *p=P(Bv)* where *P^{-1}* is an approximation of *BA^{-1}B^ * )*
562           @note: boundary conditions on p are zero.           :note: boundary conditions on p are zero.
563           """           """
564           self.__pde_prec.setValue(Y=-util.div(v))           self.__pde_prec.setValue(Y=Bv)
565           self.__pde_prec.setTolerance(self.getSubProblemTolerance())           self.getSolverOptionsPressure().setTolerance(tol)
566           return self.__pde_prec.getSolution(verbose=self.show_details)           self.getSolverOptionsPressure().setAbsoluteTolerance(0.)
567             out=self.__pde_prec.getSolution()
568             return out

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