/[escript]/trunk/escript/src/Data.cpp
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revision 790 by bcumming, Wed Jul 26 23:12:34 2006 UTC revision 2635 by jfenwick, Thu Aug 27 04:54:41 2009 UTC
# Line 1  Line 1 
 // $Id$  
1    
2  /*  /*******************************************************
3   ************************************************************  *
4   *          Copyright 2006 by ACcESS MNRF                   *  * Copyright (c) 2003-2009 by University of Queensland
5   *                                                          *  * Earth Systems Science Computational Center (ESSCC)
6   *              http://www.access.edu.au                    *  * http://www.uq.edu.au/esscc
7   *       Primary Business: Queensland, Australia            *  *
8   *  Licensed under the Open Software License version 3.0    *  * Primary Business: Queensland, Australia
9   *     http://www.opensource.org/licenses/osl-3.0.php       *  * Licensed under the Open Software License version 3.0
10   *                                                          *  * http://www.opensource.org/licenses/osl-3.0.php
11   ************************************************************  *
12  */  *******************************************************/
13    
14    
15  #include "Data.h"  #include "Data.h"
16    
17  #include "DataExpanded.h"  #include "DataExpanded.h"
18  #include "DataConstant.h"  #include "DataConstant.h"
19  #include "DataTagged.h"  #include "DataTagged.h"
20  #include "DataEmpty.h"  #include "DataEmpty.h"
21  #include "DataArray.h"  #include "DataLazy.h"
 #include "DataArrayView.h"  
 #include "DataProf.h"  
22  #include "FunctionSpaceFactory.h"  #include "FunctionSpaceFactory.h"
23  #include "AbstractContinuousDomain.h"  #include "AbstractContinuousDomain.h"
24  #include "UnaryFuncs.h"  #include "UnaryFuncs.h"
25    #include "FunctionSpaceException.h"
26    #include "EscriptParams.h"
27    
28    extern "C" {
29    #include "esysUtils/blocktimer.h"
30    }
31    
32  #include <fstream>  #include <fstream>
33  #include <algorithm>  #include <algorithm>
34  #include <vector>  #include <vector>
35  #include <functional>  #include <functional>
36    #include <sstream>  // so we can throw messages about ranks
37    
38  #include <boost/python/dict.hpp>  #include <boost/python/dict.hpp>
39  #include <boost/python/extract.hpp>  #include <boost/python/extract.hpp>
40  #include <boost/python/long.hpp>  #include <boost/python/long.hpp>
41    #include "WrappedArray.h"
42    
43  using namespace std;  using namespace std;
44  using namespace boost::python;  using namespace boost::python;
45  using namespace boost;  using namespace boost;
46  using namespace escript;  using namespace escript;
47    
48  #if defined DOPROF  // ensure the current object is not a DataLazy
49  //  // The idea was that we could add an optional warning whenever a resolve is forced
50  // global table of profiling data for all Data objects  // #define forceResolve() if (isLazy()) {#resolve();}
51  DataProf dataProfTable;  
52  #endif  #define AUTOLAZYON escriptParams.getAUTOLAZY()
53    #define MAKELAZYOP(X)   if (isLazy() || (AUTOLAZYON && m_data->isExpanded())) \
54      {\
55        DataLazy* c=new DataLazy(borrowDataPtr(),X);\
56        return Data(c);\
57      }
58    #define MAKELAZYOPOFF(X,Y) if (isLazy() || (AUTOLAZYON && m_data->isExpanded())) \
59      {\
60        DataLazy* c=new DataLazy(borrowDataPtr(),X,Y);\
61        return Data(c);\
62      }
63    
64    #define MAKELAZYOP2(X,Y,Z) if (isLazy() || (AUTOLAZYON && m_data->isExpanded())) \
65      {\
66        DataLazy* c=new DataLazy(borrowDataPtr(),X,Y,Z);\
67        return Data(c);\
68      }
69    
70    #define MAKELAZYBINSELF(R,X)   if (isLazy() || R.isLazy() || (AUTOLAZYON && (isExpanded() || R.isExpanded()))) \
71      {\
72        DataLazy* c=new DataLazy(m_data,R.borrowDataPtr(),X);\
73    /*         m_data=c->getPtr();*/     set_m_data(c->getPtr());\
74        return (*this);\
75      }
76    
77    // like the above but returns a new data rather than *this
78    #define MAKELAZYBIN(R,X)   if (isLazy() || R.isLazy() || (AUTOLAZYON && (isExpanded() || R.isExpanded()))) \
79      {\
80        DataLazy* c=new DataLazy(m_data,R.borrowDataPtr(),X);\
81        return Data(c);\
82      }
83    
84    #define MAKELAZYBIN2(L,R,X)   if (L.isLazy() || R.isLazy() || (AUTOLAZYON && (L.isExpanded() || R.isExpanded()))) \
85      {\
86        DataLazy* c=new DataLazy(L.borrowDataPtr(),R.borrowDataPtr(),X);\
87        return Data(c);\
88      }
89    
90    // Do not use the following unless you want to make copies on assignment rather than
91    // share data.  CopyOnWrite should make this unnescessary.
92    // #define ASSIGNMENT_MEANS_DEEPCOPY
93    
94    namespace
95    {
96    
97    template <class ARR>
98    inline
99    boost::python::tuple
100    pointToTuple1(const DataTypes::ShapeType& shape, ARR v, unsigned long offset)
101    {
102        using namespace boost::python;
103        using boost::python::tuple;
104        using boost::python::list;
105    
106        list l;
107        unsigned int dim=shape[0];
108        for (size_t i=0;i<dim;++i)
109        {
110        l.append(v[i+offset]);
111        }
112        return tuple(l);
113    }
114    
115    template <class ARR>
116    inline
117    boost::python::tuple
118    pointToTuple2(const DataTypes::ShapeType& shape, ARR v, unsigned long offset)
119    {
120        using namespace boost::python;
121        using boost::python::tuple;
122        using boost::python::list;
123    
124        unsigned int shape0=shape[0];
125        unsigned int shape1=shape[1];
126        list lj;
127        for (size_t j=0;j<shape0;++j)
128        {
129            list li;
130        for (size_t i=0;i<shape1;++i)
131        {
132            li.append(v[offset+DataTypes::getRelIndex(shape,j,i)]);
133        }
134        lj.append(tuple(li));
135        }
136        return tuple(lj);
137    }
138    
139    template <class ARR>
140    inline
141    boost::python::tuple
142    pointToTuple3(const DataTypes::ShapeType& shape, ARR v, unsigned long offset)
143    {
144        using namespace boost::python;
145        using boost::python::tuple;
146        using boost::python::list;
147    
148        unsigned int shape0=shape[0];
149        unsigned int shape1=shape[1];
150        unsigned int shape2=shape[2];
151    
152        list lk;
153        for (size_t k=0;k<shape0;++k)
154        {
155            list lj;
156        for (size_t j=0;j<shape1;++j)
157        {
158            list li;
159            for (size_t i=0;i<shape2;++i)
160            {
161                    li.append(v[offset+DataTypes::getRelIndex(shape,k,j,i)]);
162                }
163            lj.append(tuple(li));
164            }
165            lk.append(tuple(lj));
166        }
167        return tuple(lk);
168    }
169    
170    template <class ARR>
171    inline
172    boost::python::tuple
173    pointToTuple4(const DataTypes::ShapeType& shape, ARR v, unsigned long offset)
174    {
175        using namespace boost::python;
176        using boost::python::tuple;
177        using boost::python::list;
178    
179        unsigned int shape0=shape[0];
180        unsigned int shape1=shape[1];
181        unsigned int shape2=shape[2];
182        unsigned int shape3=shape[3];
183    
184        list ll;
185        for (size_t l=0;l<shape0;++l)
186        {
187            list lk;
188        for (size_t k=0;k<shape1;++k)
189        {
190                list lj;
191                for (size_t j=0;j<shape2;++j)
192                {
193                    list li;
194                    for (size_t i=0;i<shape3;++i)
195                    {
196                        li.append(v[offset+DataTypes::getRelIndex(shape,l,k,j,i)]);
197                    }
198                    lj.append(tuple(li));
199                }
200                lk.append(tuple(lj));
201        }
202            ll.append(tuple(lk));
203        }
204        return tuple(ll);
205    }
206    
207    
208    // This should be safer once the DataC RO changes have been brought in
209    template <class ARR>
210    boost::python::tuple
211    pointToTuple( const DataTypes::ShapeType& shape,ARR v)
212    {
213       using namespace boost::python;
214       using boost::python::list;
215       int rank=shape.size();
216       if (rank==0)
217       {
218        return make_tuple(v[0]);
219       }
220       else if (rank==1)
221       {
222            return pointToTuple1(shape,v,0);
223       }
224       else if (rank==2)
225       {
226        return pointToTuple2(shape,v,0);
227       }
228       else if (rank==3)
229       {
230        return pointToTuple3(shape,v,0);
231       }
232       else if (rank==4)
233       {
234        return pointToTuple4(shape,v,0);
235       }
236       else
237         throw DataException("Unknown rank in pointToTuple.");
238    }
239    
240    }  // anonymous namespace
241    
242  Data::Data()  Data::Data()
243        : m_shared(false), m_lazy(false)
244  {  {
245    //    //
246    // Default data is type DataEmpty    // Default data is type DataEmpty
247    DataAbstract* temp=new DataEmpty();    DataAbstract* temp=new DataEmpty();
248    shared_ptr<DataAbstract> temp_data(temp);  //   m_data=temp->getPtr();
249    m_data=temp_data;    set_m_data(temp->getPtr());
250    m_protected=false;    m_protected=false;
 #if defined DOPROF  
   // create entry in global profiling table for this object  
   profData = dataProfTable.newData();  
 #endif  
251  }  }
252    
253  Data::Data(double value,  Data::Data(double value,
254             const tuple& shape,             const tuple& shape,
255             const FunctionSpace& what,             const FunctionSpace& what,
256             bool expanded)             bool expanded)
257        : m_shared(false), m_lazy(false)
258  {  {
259    DataArrayView::ShapeType dataPointShape;    DataTypes::ShapeType dataPointShape;
260    for (int i = 0; i < shape.attr("__len__")(); ++i) {    for (int i = 0; i < shape.attr("__len__")(); ++i) {
261      dataPointShape.push_back(extract<const int>(shape[i]));      dataPointShape.push_back(extract<const int>(shape[i]));
262    }    }
263    DataArray temp(dataPointShape,value);  
264    initialise(temp.getView(),what,expanded);    int len = DataTypes::noValues(dataPointShape);
265      DataVector temp_data(len,value,len);
266      initialise(temp_data, dataPointShape, what, expanded);
267    m_protected=false;    m_protected=false;
 #if defined DOPROF  
   // create entry in global profiling table for this object  
   profData = dataProfTable.newData();  
 #endif  
268  }  }
269    
270  Data::Data(double value,  Data::Data(double value,
271         const DataArrayView::ShapeType& dataPointShape,         const DataTypes::ShapeType& dataPointShape,
272         const FunctionSpace& what,         const FunctionSpace& what,
273             bool expanded)             bool expanded)
274        : m_shared(false), m_lazy(false)
275  {  {
276    DataArray temp(dataPointShape,value);    int len = DataTypes::noValues(dataPointShape);
277    pair<int,int> dataShape=what.getDataShape();    DataVector temp_data(len,value,len);
278    initialise(temp.getView(),what,expanded);    initialise(temp_data, dataPointShape, what, expanded);
279    m_protected=false;    m_protected=false;
 #if defined DOPROF  
   // create entry in global profiling table for this object  
   profData = dataProfTable.newData();  
 #endif  
280  }  }
281    
282  Data::Data(const Data& inData)  Data::Data(const Data& inData)
283        : m_shared(false), m_lazy(false)
284  {  {
285    m_data=inData.m_data;    set_m_data(inData.m_data);
286    m_protected=inData.isProtected();    m_protected=inData.isProtected();
 #if defined DOPROF  
   // create entry in global profiling table for this object  
   profData = dataProfTable.newData();  
 #endif  
287  }  }
288    
289    
290  Data::Data(const Data& inData,  Data::Data(const Data& inData,
291             const DataArrayView::RegionType& region)             const DataTypes::RegionType& region)
292        : m_shared(false), m_lazy(false)
293  {  {
294      DataAbstract_ptr dat=inData.m_data;
295      if (inData.isLazy())
296      {
297        dat=inData.m_data->resolve();
298      }
299      else
300      {
301        dat=inData.m_data;
302      }
303    //    //
304    // Create Data which is a slice of another Data    // Create Data which is a slice of another Data
305    DataAbstract* tmp = inData.m_data->getSlice(region);    DataAbstract* tmp = dat->getSlice(region);
306    shared_ptr<DataAbstract> temp_data(tmp);    set_m_data(DataAbstract_ptr(tmp));
   m_data=temp_data;  
307    m_protected=false;    m_protected=false;
308  #if defined DOPROF  
   // create entry in global profiling table for this object  
   profData = dataProfTable.newData();  
 #endif  
309  }  }
310    
311  Data::Data(const Data& inData,  Data::Data(const Data& inData,
312             const FunctionSpace& functionspace)             const FunctionSpace& functionspace)
313        : m_shared(false), m_lazy(false)
314  {  {
315  #if defined DOPROF    if (inData.isEmpty())
316    // create entry in global profiling table for this object    {
317    profData = dataProfTable.newData();      throw DataException("Error - will not interpolate for instances of DataEmpty.");
318  #endif    }
319    if (inData.getFunctionSpace()==functionspace) {    if (inData.getFunctionSpace()==functionspace) {
320      m_data=inData.m_data;      set_m_data(inData.m_data);
321    } else {    }
322      #if defined DOPROF    else
323      profData->interpolate++;    {
324      #endif  
325      Data tmp(0,inData.getPointDataView().getShape(),functionspace,true);      if (inData.isConstant()) {  // for a constant function, we just need to use the new function space
326      // Note: Must use a reference or pointer to a derived object        if (!inData.probeInterpolation(functionspace))
327      // in order to get polymorphic behaviour. Shouldn't really        {           // Even though this is constant, we still need to check whether interpolation is allowed
328      // be able to create an instance of AbstractDomain but that was done      throw FunctionSpaceException("Cannot interpolate across to the domain of the specified FunctionSpace. (DataConstant)");
329      // as a boost:python work around which may no longer be required.        }
330      const AbstractDomain& inDataDomain=inData.getDomain();        // if the data is not lazy, this will just be a cast to DataReady
331      if  (inDataDomain==functionspace.getDomain()) {        DataReady_ptr dr=inData.m_data->resolve();
332        inDataDomain.interpolateOnDomain(tmp,inData);        DataConstant* dc=new DataConstant(functionspace,inData.m_data->getShape(),dr->getVectorRO());
333    //       m_data=DataAbstract_ptr(dc);
334          set_m_data(DataAbstract_ptr(dc));
335      } else {      } else {
336        inDataDomain.interpolateACross(tmp,inData);        Data tmp(0,inData.getDataPointShape(),functionspace,true);
337          // Note: Must use a reference or pointer to a derived object
338          // in order to get polymorphic behaviour. Shouldn't really
339          // be able to create an instance of AbstractDomain but that was done
340          // as a boost:python work around which may no longer be required.
341          /*const AbstractDomain& inDataDomain=inData.getDomain();*/
342          const_Domain_ptr inDataDomain=inData.getDomain();
343          if  (inDataDomain==functionspace.getDomain()) {
344            inDataDomain->interpolateOnDomain(tmp,inData);
345          } else {
346            inDataDomain->interpolateACross(tmp,inData);
347          }
348    //       m_data=tmp.m_data;
349          set_m_data(tmp.m_data);
350      }      }
     m_data=tmp.m_data;  
351    }    }
352    m_protected=false;    m_protected=false;
353  }  }
354    
355  Data::Data(const DataTagged::TagListType& tagKeys,  Data::Data(DataAbstract* underlyingdata)
356             const DataTagged::ValueListType & values,      : m_shared(false), m_lazy(false)
            const DataArrayView& defaultValue,  
            const FunctionSpace& what,  
            bool expanded)  
357  {  {
358    DataAbstract* temp=new DataTagged(tagKeys,values,defaultValue,what);      set_m_data(underlyingdata->getPtr());
359    shared_ptr<DataAbstract> temp_data(temp);      m_protected=false;
   m_data=temp_data;  
   m_protected=false;  
   if (expanded) {  
     expand();  
   }  
 #if defined DOPROF  
   // create entry in global profiling table for this object  
   profData = dataProfTable.newData();  
 #endif  
360  }  }
361    
362  Data::Data(const numeric::array& value,  Data::Data(DataAbstract_ptr underlyingdata)
363         const FunctionSpace& what,      : m_shared(false), m_lazy(false)
            bool expanded)  
364  {  {
365    initialise(value,what,expanded);      set_m_data(underlyingdata);
366    m_protected=false;      m_protected=false;
 #if defined DOPROF  
   // create entry in global profiling table for this object  
   profData = dataProfTable.newData();  
 #endif  
367  }  }
368    
369  Data::Data(const DataArrayView& value,  Data::Data(const DataTypes::ValueType& value,
370         const FunctionSpace& what,           const DataTypes::ShapeType& shape,
371             bool expanded)                   const FunctionSpace& what,
372                     bool expanded)
373        : m_shared(false), m_lazy(false)
374  {  {
375    initialise(value,what,expanded);     initialise(value,shape,what,expanded);
376    m_protected=false;     m_protected=false;
 #if defined DOPROF  
   // create entry in global profiling table for this object  
   profData = dataProfTable.newData();  
 #endif  
377  }  }
378    
379    
380  Data::Data(const object& value,  Data::Data(const object& value,
381         const FunctionSpace& what,         const FunctionSpace& what,
382             bool expanded)             bool expanded)
383        : m_shared(false), m_lazy(false)
384  {  {
385    numeric::array asNumArray(value);    WrappedArray w(value);
386    initialise(asNumArray,what,expanded);    initialise(w,what,expanded);
387    m_protected=false;    m_protected=false;
 #if defined DOPROF  
   // create entry in global profiling table for this object  
   profData = dataProfTable.newData();  
 #endif  
388  }  }
389    
390    
391  Data::Data(const object& value,  Data::Data(const object& value,
392             const Data& other)             const Data& other)
393        : m_shared(false), m_lazy(false)
394  {  {
395    //    WrappedArray w(value);
396    // Create DataConstant using the given value and all other parameters  
397    // copied from other. If value is a rank 0 object this Data    // extract the shape of the array
398    // will assume the point data shape of other.    const DataTypes::ShapeType& tempShape=w.getShape();
399    DataArray temp(value);    if (w.getRank()==0) {
400    if (temp.getView().getRank()==0) {  
401      //  
402      // Create a DataArray with the scalar value for all elements      // get the space for the data vector
403      DataArray temp2(other.getPointDataView().getShape(),temp.getView()());      int len1 = DataTypes::noValues(tempShape);
404      initialise(temp2.getView(),other.getFunctionSpace(),false);      DataVector temp_data(len1, 0.0, len1);
405        temp_data.copyFromArray(w,1);
406    
407        int len = DataTypes::noValues(other.getDataPointShape());
408    
409        DataVector temp2_data(len, temp_data[0], len);
410        DataConstant* t=new DataConstant(other.getFunctionSpace(),other.getDataPointShape(),temp2_data);
411    //     m_data=DataAbstract_ptr(t);
412        set_m_data(DataAbstract_ptr(t));
413    
414    } else {    } else {
415      //      //
416      // Create a DataConstant with the same sample shape as other      // Create a DataConstant with the same sample shape as other
417      initialise(temp.getView(),other.getFunctionSpace(),false);      DataConstant* t=new DataConstant(w,other.getFunctionSpace());
418    //     m_data=DataAbstract_ptr(t);
419        set_m_data(DataAbstract_ptr(t));
420    }    }
421    m_protected=false;    m_protected=false;
 #if defined DOPROF  
   // create entry in global profiling table for this object  
   profData = dataProfTable.newData();  
 #endif  
422  }  }
423    
424  Data::~Data()  Data::~Data()
425  {  {
426      set_m_data(DataAbstract_ptr());
427    }
428    
429    
430    // only call in thread safe contexts.
431    // This method should be atomic
432    void Data::set_m_data(DataAbstract_ptr p)
433    {
434      if (m_data.get()!=0)  // release old ownership
435      {
436        m_data->removeOwner(this);
437      }
438      if (p.get()!=0)
439      {
440        m_data=p;
441        m_data->addOwner(this);
442        m_shared=m_data->isShared();
443        m_lazy=m_data->isLazy();
444      }
445    }
446    
447    void Data::initialise(const WrappedArray& value,
448                     const FunctionSpace& what,
449                     bool expanded)
450    {
451      //
452      // Construct a Data object of the appropriate type.
453      // Construct the object first as there seems to be a bug which causes
454      // undefined behaviour if an exception is thrown during construction
455      // within the shared_ptr constructor.
456      if (expanded) {
457        DataAbstract* temp=new DataExpanded(value, what);
458    //     m_data=temp->getPtr();
459        set_m_data(temp->getPtr());
460      } else {
461        DataAbstract* temp=new DataConstant(value, what);
462    //     m_data=temp->getPtr();
463        set_m_data(temp->getPtr());
464      }
465    }
466    
467    
468    void
469    Data::initialise(const DataTypes::ValueType& value,
470             const DataTypes::ShapeType& shape,
471                     const FunctionSpace& what,
472                     bool expanded)
473    {
474      //
475      // Construct a Data object of the appropriate type.
476      // Construct the object first as there seems to be a bug which causes
477      // undefined behaviour if an exception is thrown during construction
478      // within the shared_ptr constructor.
479      if (expanded) {
480        DataAbstract* temp=new DataExpanded(what, shape, value);
481    //     m_data=temp->getPtr();
482        set_m_data(temp->getPtr());
483      } else {
484        DataAbstract* temp=new DataConstant(what, shape, value);
485    //     m_data=temp->getPtr();
486        set_m_data(temp->getPtr());
487      }
488  }  }
489    
490    
491  escriptDataC  escriptDataC
492  Data::getDataC()  Data::getDataC()
493  {  {
# Line 247  Data::getDataC() const Line 504  Data::getDataC() const
504    return temp;    return temp;
505  }  }
506    
507    size_t
508    Data::getSampleBufferSize() const
509    {
510      return m_data->getSampleBufferSize();
511    }
512    
513    
514  const boost::python::tuple  const boost::python::tuple
515  Data::getShapeTuple() const  Data::getShapeTuple() const
516  {  {
517    const DataArrayView::ShapeType& shape=getDataPointShape();    const DataTypes::ShapeType& shape=getDataPointShape();
518    switch(getDataPointRank()) {    switch(getDataPointRank()) {
519       case 0:       case 0:
520          return make_tuple();          return make_tuple();
# Line 267  Data::getShapeTuple() const Line 531  Data::getShapeTuple() const
531    }    }
532  }  }
533    
534    
535    // The different name is needed because boost has trouble with overloaded functions.
536    // It can't work out what type the function is based soley on its name.
537    // There are ways to fix this involving creating function pointer variables for each form
538    // but there doesn't seem to be a need given that the methods have the same name from the python point of view
539    Data
540    Data::copySelf()
541    {
542       DataAbstract* temp=m_data->deepCopy();
543       return Data(temp);
544    }
545    
546  void  void
547  Data::copy(const Data& other)  Data::copy(const Data& other)
548  {  {
549    //    DataAbstract* temp=other.m_data->deepCopy();
550    // Perform a deep copy    DataAbstract_ptr p=temp->getPtr();
551    //   m_data=p;
552      set_m_data(p);
553    }
554    
555    
556    Data
557    Data::delay()
558    {
559      DataLazy* dl=new DataLazy(m_data);
560      return Data(dl);
561    }
562    
563    void
564    Data::delaySelf()
565    {
566      if (!isLazy())
567    {    {
568      DataExpanded* temp=dynamic_cast<DataExpanded*>(other.m_data.get());  //  m_data=(new DataLazy(m_data))->getPtr();
569      if (temp!=0) {      set_m_data((new DataLazy(m_data))->getPtr());
       //  
       // Construct a DataExpanded copy  
       DataAbstract* newData=new DataExpanded(*temp);  
       shared_ptr<DataAbstract> temp_data(newData);  
       m_data=temp_data;  
       return;  
     }  
570    }    }
571    }
572    
573    
574    // For lazy data, it would seem that DataTagged will need to be treated differently since even after setting all tags
575    // to zero, all the tags from all the DataTags would be in the result.
576    // However since they all have the same value (0) whether they are there or not should not matter.
577    // So I have decided that for all types this method will create a constant 0.
578    // It can be promoted up as required.
579    // A possible efficiency concern might be expanded->constant->expanded which has an extra memory management
580    // but we can deal with that if it arises.
581    //
582    void
583    Data::setToZero()
584    {
585      if (isEmpty())
586    {    {
587      DataTagged* temp=dynamic_cast<DataTagged*>(other.m_data.get());       throw DataException("Error - Operations not permitted on instances of DataEmpty.");
     if (temp!=0) {  
       //  
       // Construct a DataTagged copy  
       DataAbstract* newData=new DataTagged(*temp);  
       shared_ptr<DataAbstract> temp_data(newData);  
       m_data=temp_data;  
       return;  
     }  
588    }    }
589      if (isLazy())
590    {    {
591      DataConstant* temp=dynamic_cast<DataConstant*>(other.m_data.get());       DataTypes::ValueType v(getNoValues(),0);
592      if (temp!=0) {       DataConstant* dc=new DataConstant(getFunctionSpace(),getDataPointShape(),v);
593        //       DataLazy* dl=new DataLazy(dc->getPtr());
594        // Construct a DataConstant copy       set_m_data(dl->getPtr());
       DataAbstract* newData=new DataConstant(*temp);  
       shared_ptr<DataAbstract> temp_data(newData);  
       m_data=temp_data;  
       return;  
     }  
595    }    }
596      else
597    {    {
598      DataEmpty* temp=dynamic_cast<DataEmpty*>(other.m_data.get());       exclusiveWrite();
599      if (temp!=0) {       m_data->setToZero();
       //  
       // Construct a DataEmpty copy  
       DataAbstract* newData=new DataEmpty();  
       shared_ptr<DataAbstract> temp_data(newData);  
       m_data=temp_data;  
       return;  
     }  
600    }    }
   throw DataException("Error - Copy not implemented for this Data type.");  
601  }  }
602    
603    
604  void  void
605  Data::copyWithMask(const Data& other,  Data::copyWithMask(const Data& other,
606                     const Data& mask)                     const Data& mask)
607  {  {
608    Data mask1;    // 1. Interpolate if required so all Datas use the same FS as this
609    Data mask2;    // 2. Tag or Expand so that all Data's are the same type
610      // 3. Iterate over the data vectors copying values where mask is >0
611      if (other.isEmpty() || mask.isEmpty())
612      {
613        throw DataException("Error - copyWithMask not permitted using instances of DataEmpty.");
614      }
615      Data other2(other);
616      Data mask2(mask);
617      other2.resolve();
618      mask2.resolve();
619      this->resolve();
620      FunctionSpace myFS=getFunctionSpace();
621      FunctionSpace oFS=other2.getFunctionSpace();
622      FunctionSpace mFS=mask2.getFunctionSpace();
623      if (oFS!=myFS)
624      {
625         if (other2.probeInterpolation(myFS))
626         {
627        other2=other2.interpolate(myFS);
628         }
629         else
630         {
631        throw DataException("Error - copyWithMask: other FunctionSpace is not compatible with this one.");
632         }
633      }
634      if (mFS!=myFS)
635      {
636         if (mask2.probeInterpolation(myFS))
637         {
638        mask2=mask2.interpolate(myFS);
639         }
640         else
641         {
642        throw DataException("Error - copyWithMask: mask FunctionSpace is not compatible with this one.");
643         }
644      }
645                // Ensure that all args have the same type
646      if (this->isExpanded() || mask2.isExpanded() || other2.isExpanded())
647      {
648        this->expand();
649        other2.expand();
650        mask2.expand();
651      }
652      else if (this->isTagged() || mask2.isTagged() || other2.isTagged())
653      {
654        this->tag();
655        other2.tag();
656        mask2.tag();
657      }
658      else if (this->isConstant() && mask2.isConstant() && other2.isConstant())
659      {
660      }
661      else
662      {
663        throw DataException("Error - Unknown DataAbstract passed to copyWithMask.");
664      }
665      unsigned int selfrank=getDataPointRank();
666      unsigned int otherrank=other2.getDataPointRank();
667      unsigned int maskrank=mask2.getDataPointRank();
668      if ((selfrank==0) && (otherrank>0 || maskrank>0))
669      {
670        // to get here we must be copying from a large object into a scalar
671        // I am not allowing this.
672        // If you are calling copyWithMask then you are considering keeping some existing values
673        // and so I'm going to assume that you don't want your data objects getting a new shape.
674        throw DataException("Attempt to copyWithMask into a scalar from an object or mask with rank>0.");
675      }
676      exclusiveWrite();
677      // Now we iterate over the elements
678      DataVector& self=getReady()->getVectorRW();;
679      const DataVector& ovec=other2.getReadyPtr()->getVectorRO();
680      const DataVector& mvec=mask2.getReadyPtr()->getVectorRO();
681    
682      if ((selfrank>0) && (otherrank==0) &&(maskrank==0))
683      {
684        // Not allowing this combination.
685        // it is not clear what the rank of the target should be.
686        // Should it be filled with the scalar (rank stays the same);
687        // or should the target object be reshaped to be a scalar as well.
688        throw DataException("Attempt to copyWithMask from scalar mask and data into non-scalar target.");
689      }
690      if ((selfrank>0) && (otherrank>0) &&(maskrank==0))
691      {
692        if (mvec[0]>0)      // copy whole object if scalar is >0
693        {
694            copy(other);
695        }
696        return;
697      }
698      if (isTagged())       // so all objects involved will also be tagged
699      {
700        // note the !
701        if (!((getDataPointShape()==mask2.getDataPointShape()) &&
702            ((other2.getDataPointShape()==mask2.getDataPointShape()) || (otherrank==0))))
703        {
704            throw DataException("copyWithMask, shape mismatch.");
705        }
706    
707    mask1 = mask.wherePositive();      // We need to consider the possibility that tags are missing or in the wrong order
708    mask2.copy(mask1);      // My guiding assumption here is: All tagged Datas are assumed to have the default value for
709        // all tags which are not explicitly defined
710    
711        const DataTagged* mptr=dynamic_cast<const DataTagged*>(mask2.m_data.get());
712        const DataTagged* optr=dynamic_cast<const DataTagged*>(other2.m_data.get());
713        DataTagged* tptr=dynamic_cast<DataTagged*>(m_data.get());
714    
715        // first, add any tags missing from other or mask
716        const DataTagged::DataMapType& olookup=optr->getTagLookup();
717            const DataTagged::DataMapType& mlookup=mptr->getTagLookup();
718        const DataTagged::DataMapType& tlookup=tptr->getTagLookup();
719        DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
720        for (i=olookup.begin();i!=olookup.end();i++)
721        {
722               tptr->addTag(i->first);
723            }
724            for (i=mlookup.begin();i!=mlookup.end();i++) {
725               tptr->addTag(i->first);
726            }
727        // now we know that *this has all the required tags but they aren't guaranteed to be in
728        // the same order
729    
730    mask1 *= other;      // There are two possibilities: 1. all objects have the same rank. 2. other is a scalar
731    mask2 *= *this;      if ((selfrank==otherrank) && (otherrank==maskrank))
732    mask2 = *this - mask2;      {
733            for (i=tlookup.begin();i!=tlookup.end();i++)
734            {
735                // get the target offset
736                DataTypes::ValueType::size_type toff=tptr->getOffsetForTag(i->first);
737                    DataTypes::ValueType::size_type moff=mptr->getOffsetForTag(i->first);
738                DataTypes::ValueType::size_type ooff=optr->getOffsetForTag(i->first);
739                for (int j=0;j<getDataPointSize();++j)
740                {
741                    if (mvec[j+moff]>0)
742                    {
743                        self[j+toff]=ovec[j+ooff];
744                    }
745                }
746                }
747            // now for the default value
748            for (int j=0;j<getDataPointSize();++j)
749            {
750                if (mvec[j+mptr->getDefaultOffset()]>0)
751                {
752                    self[j+tptr->getDefaultOffset()]=ovec[j+optr->getDefaultOffset()];
753                }
754            }
755        }
756        else    // other is a scalar
757        {
758            for (i=tlookup.begin();i!=tlookup.end();i++)
759            {
760                // get the target offset
761                DataTypes::ValueType::size_type toff=tptr->getOffsetForTag(i->first);
762                    DataTypes::ValueType::size_type moff=mptr->getOffsetForTag(i->first);
763                DataTypes::ValueType::size_type ooff=optr->getOffsetForTag(i->first);
764                for (int j=0;j<getDataPointSize();++j)
765                {
766                    if (mvec[j+moff]>0)
767                    {
768                        self[j+toff]=ovec[ooff];
769                    }
770                }
771                }
772            // now for the default value
773            for (int j=0;j<getDataPointSize();++j)
774            {
775                if (mvec[j+mptr->getDefaultOffset()]>0)
776                {
777                    self[j+tptr->getDefaultOffset()]=ovec[0];
778                }
779            }
780        }
781    
782    *this = mask1 + mask2;      return;         // ugly
783      }
784      // mixed scalar and non-scalar operation
785      if ((selfrank>0) && (otherrank==0) && (mask2.getDataPointShape()==getDataPointShape()))
786      {
787            size_t num_points=self.size();
788        // OPENMP 3.0 allows unsigned loop vars.
789        #if defined(_OPENMP) && (_OPENMP < 200805)
790        long i;
791        #else
792        size_t i;
793        #endif  
794        size_t psize=getDataPointSize();    
795        #pragma omp parallel for private(i) schedule(static)
796        for (i=0;i<num_points;++i)
797        {
798            if (mvec[i]>0)
799            {
800                self[i]=ovec[i/psize];      // since this is expanded there is one scalar
801            }                   // dest point
802        }
803        return;         // ugly!
804      }
805      // tagged data is already taken care of so we only need to worry about shapes
806      // special cases with scalars are already dealt with so all we need to worry about is shape
807      if ((getDataPointShape()!=other2.getDataPointShape()) || getDataPointShape()!=mask2.getDataPointShape())
808      {
809        ostringstream oss;
810        oss <<"Error - size mismatch in arguments to copyWithMask.";
811        oss << "\nself_shape=" << DataTypes::shapeToString(getDataPointShape());
812        oss << " other2_shape=" << DataTypes::shapeToString(other2.getDataPointShape());
813        oss << " mask2_shape=" << DataTypes::shapeToString(mask2.getDataPointShape());
814        throw DataException(oss.str());
815      }
816      size_t num_points=self.size();
817    
818      // OPENMP 3.0 allows unsigned loop vars.
819    #if defined(_OPENMP) && (_OPENMP < 200805)
820      long i;
821    #else
822      size_t i;
823    #endif
824      #pragma omp parallel for private(i) schedule(static)
825      for (i=0;i<num_points;++i)
826      {
827        if (mvec[i]>0)
828        {
829           self[i]=ovec[i];
830        }
831      }
832  }  }
833    
834  bool  bool
# Line 344  Data::isExpanded() const Line 839  Data::isExpanded() const
839  }  }
840    
841  bool  bool
842    Data::actsExpanded() const
843    {
844      return m_data->actsExpanded();
845    
846    }
847    
848    
849    bool
850  Data::isTagged() const  Data::isTagged() const
851  {  {
852    DataTagged* temp=dynamic_cast<DataTagged*>(m_data.get());    DataTagged* temp=dynamic_cast<DataTagged*>(m_data.get());
853    return (temp!=0);    return (temp!=0);
854  }  }
855    
 /* TODO */  
 /* global reduction -- the local data being empty does not imply that it is empty on other processers*/  
856  bool  bool
857  Data::isEmpty() const  Data::isEmpty() const
858  {  {
# Line 366  Data::isConstant() const Line 867  Data::isConstant() const
867    return (temp!=0);    return (temp!=0);
868  }  }
869    
870    bool
871    Data::actsConstant() const
872    {
873        return m_data->actsConstant();
874    }
875    
876    
877    bool
878    Data::isLazy() const
879    {
880      return m_lazy;    // not asking m_data because we need to be able to ask this while m_data is changing
881    }
882    
883    // at the moment this is synonymous with !isLazy() but that could change
884    bool
885    Data::isReady() const
886    {
887      return (dynamic_cast<DataReady*>(m_data.get())!=0);
888    }
889    
890    
891  void  void
892  Data::setProtection()  Data::setProtection()
893  {  {
894     m_protected=true;     m_protected=true;
895  }  }
896    
897  bool  bool
898  Data::isProtected() const  Data::isProtected() const
899  {  {
900     return m_protected;     return m_protected;
901  }  }
902    
# Line 386  Data::expand() Line 908  Data::expand()
908    if (isConstant()) {    if (isConstant()) {
909      DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());      DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());
910      DataAbstract* temp=new DataExpanded(*tempDataConst);      DataAbstract* temp=new DataExpanded(*tempDataConst);
911      shared_ptr<DataAbstract> temp_data(temp);  //     m_data=temp->getPtr();
912      m_data=temp_data;      set_m_data(temp->getPtr());
913    } else if (isTagged()) {    } else if (isTagged()) {
914      DataTagged* tempDataTag=dynamic_cast<DataTagged*>(m_data.get());      DataTagged* tempDataTag=dynamic_cast<DataTagged*>(m_data.get());
915      DataAbstract* temp=new DataExpanded(*tempDataTag);      DataAbstract* temp=new DataExpanded(*tempDataTag);
916      shared_ptr<DataAbstract> temp_data(temp);  //     m_data=temp->getPtr();
917      m_data=temp_data;      set_m_data(temp->getPtr());
918    } else if (isExpanded()) {    } else if (isExpanded()) {
919      //      //
920      // do nothing      // do nothing
921    } else if (isEmpty()) {    } else if (isEmpty()) {
922      throw DataException("Error - Expansion of DataEmpty not possible.");      throw DataException("Error - Expansion of DataEmpty not possible.");
923      } else if (isLazy()) {
924        resolve();
925        expand();       // resolve might not give us expanded data
926    } else {    } else {
927      throw DataException("Error - Expansion not implemented for this Data type.");      throw DataException("Error - Expansion not implemented for this Data type.");
928    }    }
# Line 409  Data::tag() Line 934  Data::tag()
934    if (isConstant()) {    if (isConstant()) {
935      DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());      DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());
936      DataAbstract* temp=new DataTagged(*tempDataConst);      DataAbstract* temp=new DataTagged(*tempDataConst);
937      shared_ptr<DataAbstract> temp_data(temp);  //     m_data=temp->getPtr();
938      m_data=temp_data;      set_m_data(temp->getPtr());
939    } else if (isTagged()) {    } else if (isTagged()) {
940      // do nothing      // do nothing
941    } else if (isExpanded()) {    } else if (isExpanded()) {
942      throw DataException("Error - Creating tag data from DataExpanded not possible.");      throw DataException("Error - Creating tag data from DataExpanded not possible.");
943    } else if (isEmpty()) {    } else if (isEmpty()) {
944      throw DataException("Error - Creating tag data from DataEmpty not possible.");      throw DataException("Error - Creating tag data from DataEmpty not possible.");
945      } else if (isLazy()) {
946         DataAbstract_ptr res=m_data->resolve();
947         if (m_data->isExpanded())
948         {
949        throw DataException("Error - data would resolve to DataExpanded, tagging is not possible.");
950         }
951    //      m_data=res;
952         set_m_data(res);
953         tag();
954    } else {    } else {
955      throw DataException("Error - Tagging not implemented for this Data type.");      throw DataException("Error - Tagging not implemented for this Data type.");
956    }    }
957  }  }
958    
959  void  void
960  Data::reshapeDataPoint(const DataArrayView::ShapeType& shape)  Data::resolve()
961    {
962      if (isLazy())
963      {
964    //      m_data=m_data->resolve();
965        set_m_data(m_data->resolve());
966      }
967    }
968    
969    void
970    Data::requireWrite()
971  {  {
972    m_data->reshapeDataPoint(shape);    resolve();
973      exclusiveWrite();
974    }
975    
976    Data
977    Data::oneOver() const
978    {
979      MAKELAZYOP(RECIP)
980      return C_TensorUnaryOperation(*this, bind1st(divides<double>(),1.));
981  }  }
982    
983  Data  Data
984  Data::wherePositive() const  Data::wherePositive() const
985  {  {
986  #if defined DOPROF    MAKELAZYOP(GZ)
987    profData->where++;    return C_TensorUnaryOperation(*this, bind2nd(greater<double>(),0.0));
 #endif  
   return escript::unaryOp(*this,bind2nd(greater<double>(),0.0));  
988  }  }
989    
990  Data  Data
991  Data::whereNegative() const  Data::whereNegative() const
992  {  {
993  #if defined DOPROF    MAKELAZYOP(LZ)
994    profData->where++;    return C_TensorUnaryOperation(*this, bind2nd(less<double>(),0.0));
 #endif  
   return escript::unaryOp(*this,bind2nd(less<double>(),0.0));  
995  }  }
996    
997  Data  Data
998  Data::whereNonNegative() const  Data::whereNonNegative() const
999  {  {
1000  #if defined DOPROF    MAKELAZYOP(GEZ)
1001    profData->where++;    return C_TensorUnaryOperation(*this, bind2nd(greater_equal<double>(),0.0));
 #endif  
   return escript::unaryOp(*this,bind2nd(greater_equal<double>(),0.0));  
1002  }  }
1003    
1004  Data  Data
1005  Data::whereNonPositive() const  Data::whereNonPositive() const
1006  {  {
1007  #if defined DOPROF    MAKELAZYOP(LEZ)
1008    profData->where++;    return C_TensorUnaryOperation(*this, bind2nd(less_equal<double>(),0.0));
 #endif  
   return escript::unaryOp(*this,bind2nd(less_equal<double>(),0.0));  
1009  }  }
1010    
1011  Data  Data
1012  Data::whereZero(double tol) const  Data::whereZero(double tol) const
1013  {  {
1014  #if defined DOPROF  //   Data dataAbs=abs();
1015    profData->where++;  //   return C_TensorUnaryOperation(dataAbs, bind2nd(less_equal<double>(),tol));
1016  #endif     MAKELAZYOPOFF(EZ,tol)
1017    Data dataAbs=abs();     return C_TensorUnaryOperation(*this, bind2nd(AbsLTE(),tol));
1018    return escript::unaryOp(dataAbs,bind2nd(less_equal<double>(),tol));  
1019  }  }
1020    
1021  Data  Data
1022  Data::whereNonZero(double tol) const  Data::whereNonZero(double tol) const
1023  {  {
1024  #if defined DOPROF  //   Data dataAbs=abs();
1025    profData->where++;  //   return C_TensorUnaryOperation(dataAbs, bind2nd(greater<double>(),tol));
1026  #endif    MAKELAZYOPOFF(NEZ,tol)
1027    Data dataAbs=abs();    return C_TensorUnaryOperation(*this, bind2nd(AbsGT(),tol));
1028    return escript::unaryOp(dataAbs,bind2nd(greater<double>(),tol));  
1029  }  }
1030    
1031  Data  Data
1032  Data::interpolate(const FunctionSpace& functionspace) const  Data::interpolate(const FunctionSpace& functionspace) const
1033  {  {
 #if defined DOPROF  
   profData->interpolate++;  
 #endif  
1034    return Data(*this,functionspace);    return Data(*this,functionspace);
1035  }  }
1036    
1037  bool  bool
1038  Data::probeInterpolation(const FunctionSpace& functionspace) const  Data::probeInterpolation(const FunctionSpace& functionspace) const
1039  {  {
1040    if (getFunctionSpace()==functionspace) {    return getFunctionSpace().probeInterpolation(functionspace);
     return true;  
   } else {  
     const AbstractDomain& domain=getDomain();  
     if  (domain==functionspace.getDomain()) {  
       return domain.probeInterpolationOnDomain(getFunctionSpace().getTypeCode(),functionspace.getTypeCode());  
     } else {  
       return domain.probeInterpolationACross(getFunctionSpace().getTypeCode(),functionspace.getDomain(),functionspace.getTypeCode());  
     }  
   }  
1041  }  }
1042    
1043  Data  Data
1044  Data::gradOn(const FunctionSpace& functionspace) const  Data::gradOn(const FunctionSpace& functionspace) const
1045  {  {
1046  #if defined DOPROF    if (isEmpty())
1047    profData->grad++;    {
1048  #endif      throw DataException("Error - operation not permitted on instances of DataEmpty.");
1049      }
1050      double blocktimer_start = blocktimer_time();
1051    if (functionspace.getDomain()!=getDomain())    if (functionspace.getDomain()!=getDomain())
1052      throw DataException("Error - gradient cannot be calculated on different domains.");      throw DataException("Error - gradient cannot be calculated on different domains.");
1053    DataArrayView::ShapeType grad_shape=getPointDataView().getShape();    DataTypes::ShapeType grad_shape=getDataPointShape();
1054    grad_shape.push_back(functionspace.getDim());    grad_shape.push_back(functionspace.getDim());
1055    Data out(0.0,grad_shape,functionspace,true);    Data out(0.0,grad_shape,functionspace,true);
1056    getDomain().setToGradient(out,*this);    getDomain()->setToGradient(out,*this);
1057      blocktimer_increment("grad()", blocktimer_start);
1058    return out;    return out;
1059  }  }
1060    
1061  Data  Data
1062  Data::grad() const  Data::grad() const
1063  {  {
1064    return gradOn(escript::function(getDomain()));    if (isEmpty())
1065      {
1066        throw DataException("Error - operation not permitted on instances of DataEmpty.");
1067      }
1068      return gradOn(escript::function(*getDomain()));
1069  }  }
1070    
1071  int  int
1072  Data::getDataPointSize() const  Data::getDataPointSize() const
1073  {  {
1074    return getPointDataView().noValues();    return m_data->getNoValues();
1075  }  }
1076    
1077  DataArrayView::ValueType::size_type  
1078    DataTypes::ValueType::size_type
1079  Data::getLength() const  Data::getLength() const
1080  {  {
1081    return m_data->getLength();    return m_data->getLength();
1082  }  }
1083    
1084  const DataArrayView::ShapeType&  
1085  Data::getDataPointShape() const  // There is no parallelism here ... elements need to be added in the correct order.
1086    //   If we could presize the list and then fill in the elements it might work
1087    //   This would need setting elements to be threadsafe.
1088    //   Having mulitple C threads calling into one interpreter is aparently a no-no.
1089    const boost::python::object
1090    Data::toListOfTuples(bool scalarastuple)
1091    {
1092        using namespace boost::python;
1093        using boost::python::list;
1094        if (get_MPISize()>1)
1095        {
1096            throw DataException("::toListOfTuples is not available for MPI with more than one process.");
1097        }
1098        unsigned int rank=getDataPointRank();
1099        unsigned int size=getDataPointSize();
1100    
1101        int npoints=getNumDataPoints();
1102        expand();           // This will also resolve if required
1103        const DataTypes::ValueType& vec=getReady()->getVectorRO();
1104        boost::python::list temp;
1105        temp.append(object());
1106        boost::python::list res(temp*npoints);// presize the list by the "[None] * npoints"  trick
1107        if (rank==0)
1108        {
1109            long count;
1110            if (scalarastuple)
1111            {
1112                for (count=0;count<npoints;++count)
1113                {
1114            res[count]=make_tuple(vec[count]);
1115                }
1116            }
1117            else
1118            {
1119                for (count=0;count<npoints;++count)
1120                {
1121                    res[count]=vec[count];
1122                }
1123            }
1124        }
1125        else if (rank==1)
1126        {
1127            size_t count;
1128            size_t offset=0;
1129            for (count=0;count<npoints;++count,offset+=size)
1130            {
1131                res[count]=pointToTuple1(getDataPointShape(), vec, offset);
1132            }
1133        }
1134        else if (rank==2)
1135        {
1136            size_t count;
1137            size_t offset=0;
1138            for (count=0;count<npoints;++count,offset+=size)
1139            {
1140            res[count]=pointToTuple2(getDataPointShape(), vec, offset);
1141            }
1142        }
1143        else if (rank==3)
1144        {
1145            size_t count;
1146            size_t offset=0;
1147            for (count=0;count<npoints;++count,offset+=size)
1148            {
1149                res[count]=pointToTuple3(getDataPointShape(), vec, offset);
1150            }
1151        }
1152        else if (rank==4)
1153        {
1154            size_t count;
1155            size_t offset=0;
1156            for (count=0;count<npoints;++count,offset+=size)
1157            {
1158                res[count]=pointToTuple4(getDataPointShape(), vec, offset);
1159            }
1160        }
1161        else
1162        {
1163            throw DataException("Unknown rank in ::toListOfTuples()");
1164        }
1165        return res;
1166    }
1167    
1168    const boost::python::object
1169    Data::getValueOfDataPointAsTuple(int dataPointNo)
1170    {
1171       forceResolve();
1172       if (getNumDataPointsPerSample()>0) {
1173           int sampleNo = dataPointNo/getNumDataPointsPerSample();
1174           int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
1175           //
1176           // Check a valid sample number has been supplied
1177           if ((sampleNo >= getNumSamples()) || (sampleNo < 0 )) {
1178               throw DataException("Error - Data::getValueOfDataPointAsTuple: invalid sampleNo.");
1179           }
1180    
1181           //
1182           // Check a valid data point number has been supplied
1183           if ((dataPointNoInSample >= getNumDataPointsPerSample()) || (dataPointNoInSample < 0)) {
1184               throw DataException("Error - Data::getValueOfDataPointAsTuple: invalid dataPointNoInSample.");
1185           }
1186           // TODO: global error handling
1187           DataTypes::ValueType::size_type offset=getDataOffset(sampleNo, dataPointNoInSample);
1188           return pointToTuple(getDataPointShape(),&(getDataAtOffsetRO(offset)));
1189      }
1190      else
1191      {
1192        // The pre-numpy method would return an empty array of the given shape
1193        // I'm going to throw an exception because if we have zero points per sample we have problems
1194        throw DataException("Error - need at least 1 datapoint per sample.");
1195      }
1196    
1197    }
1198    
1199    
1200    void
1201    Data::setValueOfDataPointToPyObject(int dataPointNo, const boost::python::object& py_object)
1202  {  {
1203    return getPointDataView().getShape();      // this will throw if the value cannot be represented
1204        setValueOfDataPointToArray(dataPointNo,py_object);
1205  }  }
1206    
1207  void  void
1208  Data::fillFromNumArray(const boost::python::numeric::array num_array)  Data::setValueOfDataPointToArray(int dataPointNo, const boost::python::object& obj)
1209  {  {
1210    if (isProtected()) {    if (isProtected()) {
1211          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
1212    }    }
1213      forceResolve();
1214    
1215      WrappedArray w(obj);
1216    //    //
1217    // check rank    // check rank
1218    if (num_array.getrank()<getDataPointRank())    if (static_cast<unsigned int>(w.getRank())<getDataPointRank())
1219        throw DataException("Rank of numarray does not match Data object rank");        throw DataException("Rank of array does not match Data object rank");
1220    
1221    //    //
1222    // check shape of num_array    // check shape of array
1223    for (int i=0; i<getDataPointRank(); i++) {    for (unsigned int i=0; i<getDataPointRank(); i++) {
1224      if (extract<int>(num_array.getshape()[i+1])!=getDataPointShape()[i])      if (w.getShape()[i]!=getDataPointShape()[i])
1225         throw DataException("Shape of numarray does not match Data object rank");         throw DataException("Shape of array does not match Data object rank");
1226    }    }
   
1227    //    //
1228    // make sure data is expanded:    // make sure data is expanded:
1229      //
1230    if (!isExpanded()) {    if (!isExpanded()) {
1231      expand();      expand();
1232    }    }
1233      if (getNumDataPointsPerSample()>0) {
1234    //         int sampleNo = dataPointNo/getNumDataPointsPerSample();
1235    // and copy over         int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
1236    m_data->copyAll(num_array);         m_data->copyToDataPoint(sampleNo, dataPointNoInSample,w);
1237      } else {
1238           m_data->copyToDataPoint(-1, 0,w);
1239      }
1240  }  }
1241    
1242  const  void
1243  boost::python::numeric::array  Data::setValueOfDataPoint(int dataPointNo, const double value)
 Data::convertToNumArray()  
1244  {  {
1245    //    if (isProtected()) {
1246    // determine the total number of data points          throw DataException("Error - attempt to update protected Data object.");
   int numSamples = getNumSamples();  
   int numDataPointsPerSample = getNumDataPointsPerSample();  
   int numDataPoints = numSamples * numDataPointsPerSample;  
   
   //  
   // determine the rank and shape of each data point  
   int dataPointRank = getDataPointRank();  
   DataArrayView::ShapeType dataPointShape = getDataPointShape();  
   
   //  
   // create the numeric array to be returned  
   boost::python::numeric::array numArray(0.0);  
   
   //  
   // the rank of the returned numeric array will be the rank of  
   // the data points, plus one. Where the rank of the array is n,  
   // the last n-1 dimensions will be equal to the shape of the  
   // data points, whilst the first dimension will be equal to the  
   // total number of data points. Thus the array will consist of  
   // a serial vector of the data points.  
   int arrayRank = dataPointRank + 1;  
   DataArrayView::ShapeType arrayShape;  
   arrayShape.push_back(numDataPoints);  
   for (int d=0; d<dataPointRank; d++) {  
      arrayShape.push_back(dataPointShape[d]);  
1247    }    }
   
1248    //    //
1249    // resize the numeric array to the shape just calculated    // make sure data is expanded:
1250    if (arrayRank==1) {    forceResolve();
1251      numArray.resize(arrayShape[0]);    if (!isExpanded()) {
1252    }      expand();
   if (arrayRank==2) {  
     numArray.resize(arrayShape[0],arrayShape[1]);  
   }  
   if (arrayRank==3) {  
     numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2]);  
   }  
   if (arrayRank==4) {  
     numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2],arrayShape[3]);  
   }  
   if (arrayRank==5) {  
     numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2],arrayShape[3],arrayShape[4]);  
1253    }    }
1254      if (getNumDataPointsPerSample()>0) {
1255    //         int sampleNo = dataPointNo/getNumDataPointsPerSample();
1256    // loop through each data point in turn, loading the values for that data point         int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
1257    // into the numeric array.         m_data->copyToDataPoint(sampleNo, dataPointNoInSample,value);
1258    int dataPoint = 0;    } else {
1259    for (int sampleNo = 0; sampleNo < numSamples; sampleNo++) {         m_data->copyToDataPoint(-1, 0,value);
     for (int dataPointNo = 0; dataPointNo < numDataPointsPerSample; dataPointNo++) {  
       DataArrayView dataPointView = getDataPoint(sampleNo, dataPointNo);  
       if (dataPointRank==0) {  
         numArray[dataPoint]=dataPointView();  
       }  
       if (dataPointRank==1) {  
         for (int i=0; i<dataPointShape[0]; i++) {  
           numArray[dataPoint][i]=dataPointView(i);  
         }  
       }  
       if (dataPointRank==2) {  
         for (int i=0; i<dataPointShape[0]; i++) {  
           for (int j=0; j<dataPointShape[1]; j++) {  
             numArray[dataPoint][i][j] = dataPointView(i,j);  
           }  
         }  
       }  
       if (dataPointRank==3) {  
         for (int i=0; i<dataPointShape[0]; i++) {  
           for (int j=0; j<dataPointShape[1]; j++) {  
             for (int k=0; k<dataPointShape[2]; k++) {  
               numArray[dataPoint][i][j][k]=dataPointView(i,j,k);  
             }  
           }  
         }  
       }  
       if (dataPointRank==4) {  
         for (int i=0; i<dataPointShape[0]; i++) {  
           for (int j=0; j<dataPointShape[1]; j++) {  
             for (int k=0; k<dataPointShape[2]; k++) {  
               for (int l=0; l<dataPointShape[3]; l++) {  
                 numArray[dataPoint][i][j][k][l]=dataPointView(i,j,k,l);  
               }  
             }  
           }  
         }  
       }  
       dataPoint++;  
     }  
1260    }    }
   
   //  
   // return the loaded array  
   return numArray;  
1261  }  }
1262    
1263  const  const
1264  boost::python::numeric::array  boost::python::object
1265  Data::convertToNumArrayFromSampleNo(int sampleNo)  Data::getValueOfGlobalDataPointAsTuple(int procNo, int dataPointNo)
1266  {  {
1267    //    // This could be lazier than it is now
1268    // Check a valid sample number has been supplied    forceResolve();
   if (sampleNo >= getNumSamples()) {  
     throw DataException("Error - Data::convertToNumArray: invalid sampleNo.");  
   }  
   
   //  
   // determine the number of data points per sample  
   int numDataPointsPerSample = getNumDataPointsPerSample();  
1269    
1270    //    // copy datapoint into a buffer
1271    // determine the rank and shape of each data point    // broadcast buffer to all nodes
1272    int dataPointRank = getDataPointRank();    // convert buffer to tuple
1273    DataArrayView::ShapeType dataPointShape = getDataPointShape();    // return tuple
1274    
1275    //    const DataTypes::ShapeType& dataPointShape = getDataPointShape();
1276    // create the numeric array to be returned    size_t length=DataTypes::noValues(dataPointShape);
1277    boost::python::numeric::array numArray(0.0);  
1278      // added for the MPI communication
1279    //    double *tmpData = new double[length];
1280    // the rank of the returned numeric array will be the rank of  
1281    // the data points, plus one. Where the rank of the array is n,    // updated for the MPI case
1282    // the last n-1 dimensions will be equal to the shape of the    if( get_MPIRank()==procNo ){
1283    // data points, whilst the first dimension will be equal to the        if (getNumDataPointsPerSample()>0) {
1284    // total number of data points. Thus the array will consist of      int sampleNo = dataPointNo/getNumDataPointsPerSample();
1285    // a serial vector of the data points.      int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
1286    int arrayRank = dataPointRank + 1;      //
1287    DataArrayView::ShapeType arrayShape;      // Check a valid sample number has been supplied
1288    arrayShape.push_back(numDataPointsPerSample);      if ((sampleNo >= getNumSamples()) || (sampleNo < 0 )) {
1289    for (int d=0; d<dataPointRank; d++) {          throw DataException("Error - Data::getValueOfGlobalDataPointAsTuple: invalid sampleNo.");
1290       arrayShape.push_back(dataPointShape[d]);      }
   }  
1291    
1292    //      //
1293    // resize the numeric array to the shape just calculated      // Check a valid data point number has been supplied
1294    if (arrayRank==1) {      if ((dataPointNoInSample >= getNumDataPointsPerSample()) || (dataPointNoInSample < 0)) {
1295      numArray.resize(arrayShape[0]);          throw DataException("Error - Data::getValueOfGlobalDataPointAsTuple: invalid dataPointNoInSample.");
1296    }      }
1297    if (arrayRank==2) {      // TODO: global error handling
1298      numArray.resize(arrayShape[0],arrayShape[1]);      DataTypes::ValueType::size_type offset=getDataOffset(sampleNo, dataPointNoInSample);
   }  
   if (arrayRank==3) {  
     numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2]);  
   }  
   if (arrayRank==4) {  
     numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2],arrayShape[3]);  
   }  
   if (arrayRank==5) {  
     numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2],arrayShape[3],arrayShape[4]);  
   }  
1299    
1300    //      memcpy(tmpData,&(getDataAtOffsetRO(offset)),length*sizeof(double));
1301    // loop through each data point in turn, loading the values for that data point       }
   // into the numeric array.  
   for (int dataPoint = 0; dataPoint < numDataPointsPerSample; dataPoint++) {  
     DataArrayView dataPointView = getDataPoint(sampleNo, dataPoint);  
     if (dataPointRank==0) {  
       numArray[dataPoint]=dataPointView();  
     }  
     if (dataPointRank==1) {  
       for (int i=0; i<dataPointShape[0]; i++) {  
         numArray[dataPoint][i]=dataPointView(i);  
       }  
     }  
     if (dataPointRank==2) {  
       for (int i=0; i<dataPointShape[0]; i++) {  
         for (int j=0; j<dataPointShape[1]; j++) {  
           numArray[dataPoint][i][j] = dataPointView(i,j);  
         }  
       }  
     }  
     if (dataPointRank==3) {  
       for (int i=0; i<dataPointShape[0]; i++) {  
         for (int j=0; j<dataPointShape[1]; j++) {  
           for (int k=0; k<dataPointShape[2]; k++) {  
             numArray[dataPoint][i][j][k]=dataPointView(i,j,k);  
           }  
         }  
       }  
     }  
     if (dataPointRank==4) {  
       for (int i=0; i<dataPointShape[0]; i++) {  
         for (int j=0; j<dataPointShape[1]; j++) {  
           for (int k=0; k<dataPointShape[2]; k++) {  
             for (int l=0; l<dataPointShape[3]; l++) {  
               numArray[dataPoint][i][j][k][l]=dataPointView(i,j,k,l);  
             }  
           }  
         }  
       }  
     }  
1302    }    }
1303    #ifdef PASO_MPI
1304      // broadcast the data to all other processes
1305      MPI_Bcast( tmpData, length, MPI_DOUBLE, procNo, get_MPIComm() );
1306    #endif
1307    
1308      boost::python::tuple t=pointToTuple(dataPointShape,tmpData);
1309      delete [] tmpData;
1310    //    //
1311    // return the loaded array    // return the loaded array
1312    return numArray;    return t;
1313    
1314  }  }
1315    
 const  
 boost::python::numeric::array  
 Data::convertToNumArrayFromDPNo(int procNo,  
                                 int sampleNo,  
                                                                 int dataPointNo)  
1316    
1317    boost::python::object
1318    Data::integrateToTuple_const() const
1319  {  {
1320      size_t length=0;    if (isLazy())
1321      int i, j, k, l, pos;    {
1322        throw DataException("Error - cannot integrate for constant lazy data.");
   //  
   // Check a valid sample number has been supplied  
   if (sampleNo >= getNumSamples()) {  
     throw DataException("Error - Data::convertToNumArray: invalid sampleNo.");  
   }  
   
   //  
   // Check a valid data point number has been supplied  
   if (dataPointNo >= getNumDataPointsPerSample()) {  
     throw DataException("Error - Data::convertToNumArray: invalid dataPointNo.");  
   }  
   
   //  
   // determine the rank and shape of each data point  
   int dataPointRank = getDataPointRank();  
   DataArrayView::ShapeType dataPointShape = getDataPointShape();  
   
   //  
   // create the numeric array to be returned  
   boost::python::numeric::array numArray(0.0);  
   
   //  
   // the shape of the returned numeric array will be the same  
   // as that of the data point  
   int arrayRank = dataPointRank;  
   DataArrayView::ShapeType arrayShape = dataPointShape;  
   
   //  
   // resize the numeric array to the shape just calculated  
   if (arrayRank==0) {  
     numArray.resize(1);  
   }  
   if (arrayRank==1) {  
     numArray.resize(arrayShape[0]);  
   }  
   if (arrayRank==2) {  
     numArray.resize(arrayShape[0],arrayShape[1]);  
   }  
   if (arrayRank==3) {  
     numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2]);  
   }  
   if (arrayRank==4) {  
     numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2],arrayShape[3]);  
1323    }    }
1324      return integrateWorker();
1325    }
1326    
1327      // added for the MPI communication  boost::python::object
1328      length=1;  Data::integrateToTuple()
1329      for( i=0; i<arrayRank; i++ )  {
1330          length *= arrayShape[i];    if (isLazy())
1331      double *tmpData = new double[length];    {
1332        expand();
   //  
   // load the values for the data point into the numeric array.  
   
     // updated for the MPI case  
     if( get_MPIRank()==procNo ){  
         // create a view of the data if it is stored locally  
         DataArrayView dataPointView = getDataPoint(sampleNo, dataPointNo);  
           
         // pack the data from the view into tmpData for MPI communication  
         pos=0;  
         switch( dataPointRank ){  
             case 0 :  
                 tmpData[0] = dataPointView();  
                 break;  
             case 1 :          
                 for( i=0; i<dataPointShape[0]; i++ )  
                     tmpData[i]=dataPointView(i);  
                 break;  
             case 2 :          
                 for( i=0; i<dataPointShape[0]; i++ )  
                     for( j=0; j<dataPointShape[1]; j++, pos++ )  
                         tmpData[pos]=dataPointView(i,j);  
                 break;  
             case 3 :          
                 for( i=0; i<dataPointShape[0]; i++ )  
                     for( j=0; j<dataPointShape[1]; j++ )  
                         for( k=0; k<dataPointShape[2]; k++, pos++ )  
                             tmpData[pos]=dataPointView(i,j,k);  
                 break;  
             case 4 :  
                 for( i=0; i<dataPointShape[0]; i++ )  
                     for( j=0; j<dataPointShape[1]; j++ )  
                         for( k=0; k<dataPointShape[2]; k++ )  
                             for( l=0; l<dataPointShape[3]; l++, pos++ )  
                                 tmpData[pos]=dataPointView(i,j,k,l);  
                 break;  
         }  
     }  
 #ifdef PASO_MPI  
         // broadcast the data to all other processes  
         MPI_Bcast( tmpData, length, MPI_DOUBLE, procNo, get_MPIComm() );  
 #endif  
   
     // unpack the data  
     switch( dataPointRank ){  
         case 0 :  
             numArray[i]=tmpData[0];  
             break;  
         case 1 :          
             for( i=0; i<dataPointShape[0]; i++ )  
                 numArray[i]=tmpData[i];  
             break;  
         case 2 :          
             for( i=0; i<dataPointShape[0]; i++ )  
                 for( j=0; j<dataPointShape[1]; j++ )  
                     tmpData[i+j*dataPointShape[0]];  
             break;  
         case 3 :          
             for( i=0; i<dataPointShape[0]; i++ )  
                 for( j=0; j<dataPointShape[1]; j++ )  
                     for( k=0; k<dataPointShape[2]; k++ )  
                         tmpData[i+dataPointShape[0]*(j*+k*dataPointShape[1])];  
             break;  
         case 4 :  
             for( i=0; i<dataPointShape[0]; i++ )  
                 for( j=0; j<dataPointShape[1]; j++ )  
                     for( k=0; k<dataPointShape[2]; k++ )  
                         for( l=0; l<dataPointShape[3]; l++ )  
                             tmpData[i+dataPointShape[0]*(j*+dataPointShape[1]*(k+l*dataPointShape[2]))];  
             break;  
     }  
   
     delete [] tmpData;    
 /*  
   if (dataPointRank==0) {  
     numArray[0]=dataPointView();  
   }  
   if (dataPointRank==1) {  
     for (int i=0; i<dataPointShape[0]; i++) {  
       numArray[i]=dataPointView(i);  
     }  
   }  
   if (dataPointRank==2) {  
     for (int i=0; i<dataPointShape[0]; i++) {  
       for (int j=0; j<dataPointShape[1]; j++) {  
         numArray[i][j] = dataPointView(i,j);  
       }  
     }  
   }  
   if (dataPointRank==3) {  
     for (int i=0; i<dataPointShape[0]; i++) {  
       for (int j=0; j<dataPointShape[1]; j++) {  
         for (int k=0; k<dataPointShape[2]; k++) {  
           numArray[i][j][k]=dataPointView(i,j,k);  
         }  
       }  
     }  
   }  
   if (dataPointRank==4) {  
     for (int i=0; i<dataPointShape[0]; i++) {  
       for (int j=0; j<dataPointShape[1]; j++) {  
         for (int k=0; k<dataPointShape[2]; k++) {  
           for (int l=0; l<dataPointShape[3]; l++) {  
             numArray[i][j][k][l]=dataPointView(i,j,k,l);  
           }  
         }  
       }  
     }  
1333    }    }
1334  */    return integrateWorker();
1335    
   //  
   // return the loaded array  
   return numArray;  
1336  }  }
1337    
1338  boost::python::numeric::array  boost::python::object
1339  Data::integrate() const  Data::integrateWorker() const
1340  {  {
1341    int index;    DataTypes::ShapeType shape = getDataPointShape();
1342    int rank = getDataPointRank();    int dataPointSize = getDataPointSize();
   DataArrayView::ShapeType shape = getDataPointShape();  
   
 #if defined DOPROF  
   profData->integrate++;  
 #endif  
1343    
1344    //    //
1345    // calculate the integral values    // calculate the integral values
1346    vector<double> integrals(getDataPointSize());    vector<double> integrals(dataPointSize);
1347    AbstractContinuousDomain::asAbstractContinuousDomain(getDomain()).setToIntegrals(integrals,*this);    vector<double> integrals_local(dataPointSize);
1348      const AbstractContinuousDomain* dom=dynamic_cast<const AbstractContinuousDomain*>(getDomain().get());
1349    //    if (dom==0)
1350    // create the numeric array to be returned    {            
1351    // and load the array with the integral values      throw DataException("Can not integrate over non-continuous domains.");
   boost::python::numeric::array bp_array(1.0);  
   if (rank==0) {  
     bp_array.resize(1);  
     index = 0;  
     bp_array[0] = integrals[index];  
   }  
   if (rank==1) {  
     bp_array.resize(shape[0]);  
     for (int i=0; i<shape[0]; i++) {  
       index = i;  
       bp_array[i] = integrals[index];  
     }  
   }  
   if (rank==2) {  
        bp_array.resize(shape[0],shape[1]);  
        for (int i=0; i<shape[0]; i++) {  
          for (int j=0; j<shape[1]; j++) {  
            index = i + shape[0] * j;  
            bp_array[make_tuple(i,j)] = integrals[index];  
          }  
        }  
   }  
   if (rank==3) {  
     bp_array.resize(shape[0],shape[1],shape[2]);  
     for (int i=0; i<shape[0]; i++) {  
       for (int j=0; j<shape[1]; j++) {  
         for (int k=0; k<shape[2]; k++) {  
           index = i + shape[0] * ( j + shape[1] * k );  
           bp_array[make_tuple(i,j,k)] = integrals[index];  
         }  
       }  
     }  
   }  
   if (rank==4) {  
     bp_array.resize(shape[0],shape[1],shape[2],shape[3]);  
     for (int i=0; i<shape[0]; i++) {  
       for (int j=0; j<shape[1]; j++) {  
         for (int k=0; k<shape[2]; k++) {  
           for (int l=0; l<shape[3]; l++) {  
             index = i + shape[0] * ( j + shape[1] * ( k + shape[2] * l ) );  
             bp_array[make_tuple(i,j,k,l)] = integrals[index];  
           }  
         }  
       }  
     }  
1352    }    }
1353    #ifdef PASO_MPI
1354      dom->setToIntegrals(integrals_local,*this);
1355      // Global sum: use an array instead of a vector because elements of array are guaranteed to be contiguous in memory
1356      double *tmp = new double[dataPointSize];
1357      double *tmp_local = new double[dataPointSize];
1358      for (int i=0; i<dataPointSize; i++) { tmp_local[i] = integrals_local[i]; }
1359      MPI_Allreduce( &tmp_local[0], &tmp[0], dataPointSize, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD );
1360      for (int i=0; i<dataPointSize; i++) { integrals[i] = tmp[i]; }
1361      tuple result=pointToTuple(shape,tmp);
1362      delete[] tmp;
1363      delete[] tmp_local;
1364    #else
1365      dom->setToIntegrals(integrals,*this);
1366    /*  double *tmp = new double[dataPointSize];
1367      for (int i=0; i<dataPointSize; i++) { tmp[i]=integrals[i]; }*/
1368      tuple result=pointToTuple(shape,integrals);
1369    //   delete tmp;
1370    #endif
1371    
1372    //  
1373    // return the loaded array    return result;
   return bp_array;  
1374  }  }
1375    
1376  Data  Data
1377  Data::sin() const  Data::sin() const
1378  {  {
1379  #if defined DOPROF    MAKELAZYOP(SIN)
1380    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::sin);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::sin);  
1381  }  }
1382    
1383  Data  Data
1384  Data::cos() const  Data::cos() const
1385  {  {
1386  #if defined DOPROF    MAKELAZYOP(COS)
1387    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::cos);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::cos);  
1388  }  }
1389    
1390  Data  Data
1391  Data::tan() const  Data::tan() const
1392  {  {
1393  #if defined DOPROF    MAKELAZYOP(TAN)
1394    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::tan);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::tan);  
1395  }  }
1396    
1397  Data  Data
1398  Data::asin() const  Data::asin() const
1399  {  {
1400  #if defined DOPROF    MAKELAZYOP(ASIN)
1401    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::asin);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::asin);  
1402  }  }
1403    
1404  Data  Data
1405  Data::acos() const  Data::acos() const
1406  {  {
1407  #if defined DOPROF    MAKELAZYOP(ACOS)
1408    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::acos);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::acos);  
1409  }  }
1410    
1411    
1412  Data  Data
1413  Data::atan() const  Data::atan() const
1414  {  {
1415  #if defined DOPROF    MAKELAZYOP(ATAN)
1416    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::atan);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::atan);  
1417  }  }
1418    
1419  Data  Data
1420  Data::sinh() const  Data::sinh() const
1421  {  {
1422  #if defined DOPROF    MAKELAZYOP(SINH)
1423    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::sinh);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::sinh);  
1424  }  }
1425    
1426  Data  Data
1427  Data::cosh() const  Data::cosh() const
1428  {  {
1429  #if defined DOPROF    MAKELAZYOP(COSH)
1430    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::cosh);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::cosh);  
1431  }  }
1432    
1433  Data  Data
1434  Data::tanh() const  Data::tanh() const
1435  {  {
1436  #if defined DOPROF    MAKELAZYOP(TANH)
1437    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::tanh);
1438    }
1439    
1440    
1441    Data
1442    Data::erf() const
1443    {
1444    #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1445      throw DataException("Error - Data:: erf function is not supported on _WIN32 platforms.");
1446    #else
1447      MAKELAZYOP(ERF)
1448      return C_TensorUnaryOperation(*this, ::erf);
1449  #endif  #endif
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::tanh);  
1450  }  }
1451    
1452  Data  Data
1453  Data::asinh() const  Data::asinh() const
1454  {  {
1455  #if defined DOPROF    MAKELAZYOP(ASINH)
1456    profData->unary++;  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1457      return C_TensorUnaryOperation(*this, escript::asinh_substitute);
1458    #else
1459      return C_TensorUnaryOperation(*this, ::asinh);
1460  #endif  #endif
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::asinh);  
1461  }  }
1462    
1463  Data  Data
1464  Data::acosh() const  Data::acosh() const
1465  {  {
1466  #if defined DOPROF    MAKELAZYOP(ACOSH)
1467    profData->unary++;  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1468      return C_TensorUnaryOperation(*this, escript::acosh_substitute);
1469    #else
1470      return C_TensorUnaryOperation(*this, ::acosh);
1471  #endif  #endif
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::acosh);  
1472  }  }
1473    
1474  Data  Data
1475  Data::atanh() const  Data::atanh() const
1476  {  {
1477  #if defined DOPROF    MAKELAZYOP(ATANH)
1478    profData->unary++;  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1479      return C_TensorUnaryOperation(*this, escript::atanh_substitute);
1480    #else
1481      return C_TensorUnaryOperation(*this, ::atanh);
1482  #endif  #endif
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::atanh);  
1483  }  }
1484    
1485  Data  Data
1486  Data::log10() const  Data::log10() const
1487  {  {
1488  #if defined DOPROF    MAKELAZYOP(LOG10)
1489    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::log10);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::log10);  
1490  }  }
1491    
1492  Data  Data
1493  Data::log() const  Data::log() const
1494  {  {
1495  #if defined DOPROF    MAKELAZYOP(LOG)
1496    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::log);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::log);  
1497  }  }
1498    
1499  Data  Data
1500  Data::sign() const  Data::sign() const
1501  {  {
1502  #if defined DOPROF    MAKELAZYOP(SIGN)
1503    profData->unary++;    return C_TensorUnaryOperation(*this, escript::fsign);
 #endif  
   return escript::unaryOp(*this,escript::fsign);  
1504  }  }
1505    
1506  Data  Data
1507  Data::abs() const  Data::abs() const
1508  {  {
1509  #if defined DOPROF    MAKELAZYOP(ABS)
1510    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::fabs);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::fabs);  
1511  }  }
1512    
1513  Data  Data
1514  Data::neg() const  Data::neg() const
1515  {  {
1516  #if defined DOPROF    MAKELAZYOP(NEG)
1517    profData->unary++;    return C_TensorUnaryOperation(*this, negate<double>());
 #endif  
   return escript::unaryOp(*this,negate<double>());  
1518  }  }
1519    
1520  Data  Data
1521  Data::pos() const  Data::pos() const
1522  {  {
1523  #if defined DOPROF      // not doing lazy check here is deliberate.
1524    profData->unary++;      // since a deep copy of lazy data should be cheap, I'll just let it happen now
 #endif  
1525    Data result;    Data result;
1526    // perform a deep copy    // perform a deep copy
1527    result.copy(*this);    result.copy(*this);
# Line 1196  Data::pos() const Line 1531  Data::pos() const
1531  Data  Data
1532  Data::exp() const  Data::exp() const
1533  {  {
1534  #if defined DOPROF    MAKELAZYOP(EXP)
1535    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::exp);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::exp);  
1536  }  }
1537    
1538  Data  Data
1539  Data::sqrt() const  Data::sqrt() const
1540  {  {
1541  #if defined DOPROF    MAKELAZYOP(SQRT)
1542    profData->unary++;    return C_TensorUnaryOperation<double (*)(double)>(*this, ::sqrt);
 #endif  
   return escript::unaryOp(*this,(Data::UnaryDFunPtr)::sqrt);  
1543  }  }
1544    
1545  double  double
1546  Data::Lsup() const  Data::Lsup_const() const
1547  {  {
1548    double localValue, globalValue;     if (isLazy())
1549  #if defined DOPROF     {
1550    profData->reduction1++;      throw DataException("Error - cannot compute Lsup for constant lazy data.");
1551  #endif     }
1552    //     return LsupWorker();
1553    // set the initial absolute maximum value to zero  }
1554    
1555    AbsMax abs_max_func;  double
1556    localValue = algorithm(abs_max_func,0);  Data::Lsup()
1557  #ifdef PASO_MPI  {
1558    MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MAX, MPI_COMM_WORLD );     if (isLazy())
1559    return globalValue;     {
1560  #else      resolve();
1561    return localValue;     }
1562  #endif     return LsupWorker();
1563  }  }
1564    
1565  double  double
1566  Data::Linf() const  Data::sup_const() const
1567  {  {
1568    double localValue, globalValue;     if (isLazy())
1569  #if defined DOPROF     {
1570    profData->reduction1++;      throw DataException("Error - cannot compute sup for constant lazy data.");
1571  #endif     }
1572       return supWorker();
1573    }
1574    
1575    double
1576    Data::sup()
1577    {
1578       if (isLazy())
1579       {
1580        resolve();
1581       }
1582       return supWorker();
1583    }
1584    
1585    double
1586    Data::inf_const() const
1587    {
1588       if (isLazy())
1589       {
1590        throw DataException("Error - cannot compute inf for constant lazy data.");
1591       }
1592       return infWorker();
1593    }
1594    
1595    double
1596    Data::inf()
1597    {
1598       if (isLazy())
1599       {
1600        resolve();
1601       }
1602       return infWorker();
1603    }
1604    
1605    double
1606    Data::LsupWorker() const
1607    {
1608      double localValue;
1609    //    //
1610    // set the initial absolute minimum value to max double    // set the initial absolute maximum value to zero
   AbsMin abs_min_func;  
   localValue = algorithm(abs_min_func,numeric_limits<double>::max());  
1611    
1612      AbsMax abs_max_func;
1613      localValue = algorithm(abs_max_func,0);
1614  #ifdef PASO_MPI  #ifdef PASO_MPI
1615    MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MIN, MPI_COMM_WORLD );    double globalValue;
1616      MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MAX, MPI_COMM_WORLD );
1617    return globalValue;    return globalValue;
1618  #else  #else
1619    return localValue;    return localValue;
# Line 1252  Data::Linf() const Line 1621  Data::Linf() const
1621  }  }
1622    
1623  double  double
1624  Data::sup() const  Data::supWorker() const
1625  {  {
1626    double localValue, globalValue;    double localValue;
 #if defined DOPROF  
   profData->reduction1++;  
 #endif  
1627    //    //
1628    // set the initial maximum value to min possible double    // set the initial maximum value to min possible double
1629    FMax fmax_func;    FMax fmax_func;
1630    localValue = algorithm(fmax_func,numeric_limits<double>::max()*-1);    localValue = algorithm(fmax_func,numeric_limits<double>::max()*-1);
1631  #ifdef PASO_MPI  #ifdef PASO_MPI
1632      double globalValue;
1633    MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MAX, MPI_COMM_WORLD );    MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MAX, MPI_COMM_WORLD );
1634    return globalValue;    return globalValue;
1635  #else  #else
# Line 1271  Data::sup() const Line 1638  Data::sup() const
1638  }  }
1639    
1640  double  double
1641  Data::inf() const  Data::infWorker() const
1642  {  {
1643    double localValue, globalValue;    double localValue;
 #if defined DOPROF  
   profData->reduction1++;  
 #endif  
1644    //    //
1645    // set the initial minimum value to max possible double    // set the initial minimum value to max possible double
1646    FMin fmin_func;    FMin fmin_func;
1647    localValue = algorithm(fmin_func,numeric_limits<double>::max());    localValue = algorithm(fmin_func,numeric_limits<double>::max());
1648  #ifdef PASO_MPI  #ifdef PASO_MPI
1649      double globalValue;
1650    MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MIN, MPI_COMM_WORLD );    MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MIN, MPI_COMM_WORLD );
1651    return globalValue;    return globalValue;
1652  #else  #else
# Line 1294  Data::inf() const Line 1659  Data::inf() const
1659  Data  Data
1660  Data::maxval() const  Data::maxval() const
1661  {  {
1662  #if defined DOPROF    if (isLazy())
1663    profData->reduction2++;    {
1664  #endif      Data temp(*this);   // to get around the fact that you can't resolve a const Data
1665        temp.resolve();
1666        return temp.maxval();
1667      }
1668    //    //
1669    // set the initial maximum value to min possible double    // set the initial maximum value to min possible double
1670    FMax fmax_func;    FMax fmax_func;
# Line 1306  Data::maxval() const Line 1674  Data::maxval() const
1674  Data  Data
1675  Data::minval() const  Data::minval() const
1676  {  {
1677  #if defined DOPROF    if (isLazy())
1678    profData->reduction2++;    {
1679  #endif      Data temp(*this);   // to get around the fact that you can't resolve a const Data
1680        temp.resolve();
1681        return temp.minval();
1682      }
1683    //    //
1684    // set the initial minimum value to max possible double    // set the initial minimum value to max possible double
1685    FMin fmin_func;    FMin fmin_func;
# Line 1316  Data::minval() const Line 1687  Data::minval() const
1687  }  }
1688    
1689  Data  Data
1690  Data::trace() const  Data::swapaxes(const int axis0, const int axis1) const
1691  {  {
1692  #if defined DOPROF       int axis0_tmp,axis1_tmp;
1693    profData->reduction2++;       DataTypes::ShapeType s=getDataPointShape();
1694  #endif       DataTypes::ShapeType ev_shape;
1695    Trace trace_func;       // Here's the equivalent of python s_out=s[axis_offset:]+s[:axis_offset]
1696    return dp_algorithm(trace_func,0);       // which goes thru all shape vector elements starting with axis_offset (at index=rank wrap around to 0)
1697         int rank=getDataPointRank();
1698         if (rank<2) {
1699            throw DataException("Error - Data::swapaxes argument must have at least rank 2.");
1700         }
1701         if (axis0<0 || axis0>rank-1) {
1702            throw DataException("Error - Data::swapaxes: axis0 must be between 0 and rank-1=" + rank-1);
1703         }
1704         if (axis1<0 || axis1>rank-1) {
1705             throw DataException("Error - Data::swapaxes: axis1 must be between 0 and rank-1=" + rank-1);
1706         }
1707         if (axis0 == axis1) {
1708             throw DataException("Error - Data::swapaxes: axis indices must be different.");
1709         }
1710         MAKELAZYOP2(SWAP,axis0,axis1)
1711         if (axis0 > axis1)
1712         {
1713        axis0_tmp=axis1;
1714        axis1_tmp=axis0;
1715         }
1716         else
1717         {
1718        axis0_tmp=axis0;
1719        axis1_tmp=axis1;
1720         }
1721         for (int i=0; i<rank; i++)
1722         {
1723        if (i == axis0_tmp)
1724        {
1725            ev_shape.push_back(s[axis1_tmp]);
1726        }
1727        else if (i == axis1_tmp)
1728        {
1729            ev_shape.push_back(s[axis0_tmp]);
1730        }
1731        else
1732        {
1733            ev_shape.push_back(s[i]);
1734        }
1735         }
1736         Data ev(0.,ev_shape,getFunctionSpace());
1737         ev.typeMatchRight(*this);
1738         m_data->swapaxes(ev.m_data.get(), axis0_tmp, axis1_tmp);
1739         return ev;
1740  }  }
1741    
1742  Data  Data
1743  Data::symmetric() const  Data::symmetric() const
1744  {  {
      #if defined DOPROF  
         profData->unary++;  
      #endif  
1745       // check input       // check input
1746       DataArrayView::ShapeType s=getDataPointShape();       DataTypes::ShapeType s=getDataPointShape();
1747       if (getDataPointRank()==2) {       if (getDataPointRank()==2) {
1748          if(s[0] != s[1])          if(s[0] != s[1])
1749             throw DataException("Error - Data::symmetric can only be calculated for rank 2 object with equal first and second dimension.");             throw DataException("Error - Data::symmetric can only be calculated for rank 2 object with equal first and second dimension.");
1750       }       }
1751       else if (getDataPointRank()==4) {       else if (getDataPointRank()==4) {
# Line 1344  Data::symmetric() const Line 1755  Data::symmetric() const
1755       else {       else {
1756          throw DataException("Error - Data::symmetric can only be calculated for rank 2 or 4 object.");          throw DataException("Error - Data::symmetric can only be calculated for rank 2 or 4 object.");
1757       }       }
1758         MAKELAZYOP(SYM)
1759       Data ev(0.,getDataPointShape(),getFunctionSpace());       Data ev(0.,getDataPointShape(),getFunctionSpace());
1760       ev.typeMatchRight(*this);       ev.typeMatchRight(*this);
1761       m_data->symmetric(ev.m_data.get());       m_data->symmetric(ev.m_data.get());
# Line 1353  Data::symmetric() const Line 1765  Data::symmetric() const
1765  Data  Data
1766  Data::nonsymmetric() const  Data::nonsymmetric() const
1767  {  {
1768       #if defined DOPROF       MAKELAZYOP(NSYM)
         profData->unary++;  
      #endif  
1769       // check input       // check input
1770       DataArrayView::ShapeType s=getDataPointShape();       DataTypes::ShapeType s=getDataPointShape();
1771       if (getDataPointRank()==2) {       if (getDataPointRank()==2) {
1772          if(s[0] != s[1])          if(s[0] != s[1])
1773             throw DataException("Error - Data::nonsymmetric can only be calculated for rank 2 object with equal first and second dimension.");             throw DataException("Error - Data::nonsymmetric can only be calculated for rank 2 object with equal first and second dimension.");
1774          DataArrayView::ShapeType ev_shape;          DataTypes::ShapeType ev_shape;
1775          ev_shape.push_back(s[0]);          ev_shape.push_back(s[0]);
1776          ev_shape.push_back(s[1]);          ev_shape.push_back(s[1]);
1777          Data ev(0.,ev_shape,getFunctionSpace());          Data ev(0.,ev_shape,getFunctionSpace());
# Line 1372  Data::nonsymmetric() const Line 1782  Data::nonsymmetric() const
1782       else if (getDataPointRank()==4) {       else if (getDataPointRank()==4) {
1783          if(!(s[0] == s[2] && s[1] == s[3]))          if(!(s[0] == s[2] && s[1] == s[3]))
1784             throw DataException("Error - Data::nonsymmetric can only be calculated for rank 4 object with dim0==dim2 and dim1==dim3.");             throw DataException("Error - Data::nonsymmetric can only be calculated for rank 4 object with dim0==dim2 and dim1==dim3.");
1785          DataArrayView::ShapeType ev_shape;          DataTypes::ShapeType ev_shape;
1786          ev_shape.push_back(s[0]);          ev_shape.push_back(s[0]);
1787          ev_shape.push_back(s[1]);          ev_shape.push_back(s[1]);
1788          ev_shape.push_back(s[2]);          ev_shape.push_back(s[2]);
# Line 1388  Data::nonsymmetric() const Line 1798  Data::nonsymmetric() const
1798  }  }
1799    
1800  Data  Data
1801  Data::matrixtrace(int axis_offset) const  Data::trace(int axis_offset) const
1802  {  {    
1803       #if defined DOPROF       MAKELAZYOPOFF(TRACE,axis_offset)
1804          profData->unary++;       if ((axis_offset<0) || (axis_offset>getDataPointRank()))
1805       #endif       {
1806       DataArrayView::ShapeType s=getDataPointShape();      throw DataException("Error - Data::trace, axis_offset must be between 0 and rank-2 inclusive.");
1807         }
1808         DataTypes::ShapeType s=getDataPointShape();
1809       if (getDataPointRank()==2) {       if (getDataPointRank()==2) {
1810          DataArrayView::ShapeType ev_shape;          DataTypes::ShapeType ev_shape;
1811          Data ev(0.,ev_shape,getFunctionSpace());          Data ev(0.,ev_shape,getFunctionSpace());
1812          ev.typeMatchRight(*this);          ev.typeMatchRight(*this);
1813          m_data->matrixtrace(ev.m_data.get(), axis_offset);          m_data->trace(ev.m_data.get(), axis_offset);
1814          return ev;          return ev;
1815       }       }
1816       if (getDataPointRank()==3) {       if (getDataPointRank()==3) {
1817          DataArrayView::ShapeType ev_shape;          DataTypes::ShapeType ev_shape;
1818          if (axis_offset==0) {          if (axis_offset==0) {
1819            int s2=s[2];            int s2=s[2];
1820            ev_shape.push_back(s2);            ev_shape.push_back(s2);
# Line 1413  Data::matrixtrace(int axis_offset) const Line 1825  Data::matrixtrace(int axis_offset) const
1825          }          }
1826          Data ev(0.,ev_shape,getFunctionSpace());          Data ev(0.,ev_shape,getFunctionSpace());
1827          ev.typeMatchRight(*this);          ev.typeMatchRight(*this);
1828          m_data->matrixtrace(ev.m_data.get(), axis_offset);          m_data->trace(ev.m_data.get(), axis_offset);
1829          return ev;          return ev;
1830       }       }
1831       if (getDataPointRank()==4) {       if (getDataPointRank()==4) {
1832          DataArrayView::ShapeType ev_shape;          DataTypes::ShapeType ev_shape;
1833          if (axis_offset==0) {          if (axis_offset==0) {
1834            ev_shape.push_back(s[2]);            ev_shape.push_back(s[2]);
1835            ev_shape.push_back(s[3]);            ev_shape.push_back(s[3]);
# Line 1432  Data::matrixtrace(int axis_offset) const Line 1844  Data::matrixtrace(int axis_offset) const
1844      }      }
1845          Data ev(0.,ev_shape,getFunctionSpace());          Data ev(0.,ev_shape,getFunctionSpace());
1846          ev.typeMatchRight(*this);          ev.typeMatchRight(*this);
1847      m_data->matrixtrace(ev.m_data.get(), axis_offset);      m_data->trace(ev.m_data.get(), axis_offset);
1848          return ev;          return ev;
1849       }       }
1850       else {       else {
1851          throw DataException("Error - Data::matrixtrace can only be calculated for rank 2, 3 or 4 object.");          throw DataException("Error - Data::trace can only be calculated for rank 2, 3 or 4 object.");
1852       }       }
1853  }  }
1854    
1855  Data  Data
1856  Data::transpose(int axis_offset) const  Data::transpose(int axis_offset) const
1857  {  {    
1858  #if defined DOPROF       MAKELAZYOPOFF(TRANS,axis_offset)
1859       profData->reduction2++;       DataTypes::ShapeType s=getDataPointShape();
1860  #endif       DataTypes::ShapeType ev_shape;
      DataArrayView::ShapeType s=getDataPointShape();  
      DataArrayView::ShapeType ev_shape;  
1861       // Here's the equivalent of python s_out=s[axis_offset:]+s[:axis_offset]       // Here's the equivalent of python s_out=s[axis_offset:]+s[:axis_offset]
1862       // which goes thru all shape vector elements starting with axis_offset (at index=rank wrap around to 0)       // which goes thru all shape vector elements starting with axis_offset (at index=rank wrap around to 0)
1863       int rank=getDataPointRank();       int rank=getDataPointRank();
# Line 1467  Data::transpose(int axis_offset) const Line 1877  Data::transpose(int axis_offset) const
1877  Data  Data
1878  Data::eigenvalues() const  Data::eigenvalues() const
1879  {  {
1880       #if defined DOPROF       if (isLazy())
1881          profData->unary++;       {
1882       #endif      Data temp(*this);   // to get around the fact that you can't resolve a const Data
1883        temp.resolve();
1884        return temp.eigenvalues();
1885         }
1886       // check input       // check input
1887       DataArrayView::ShapeType s=getDataPointShape();       DataTypes::ShapeType s=getDataPointShape();
1888       if (getDataPointRank()!=2)       if (getDataPointRank()!=2)
1889          throw DataException("Error - Data::eigenvalues can only be calculated for rank 2 object.");          throw DataException("Error - Data::eigenvalues can only be calculated for rank 2 object.");
1890       if(s[0] != s[1])       if(s[0] != s[1])
1891          throw DataException("Error - Data::eigenvalues can only be calculated for object with equal first and second dimension.");          throw DataException("Error - Data::eigenvalues can only be calculated for object with equal first and second dimension.");
1892       // create return       // create return
1893       DataArrayView::ShapeType ev_shape(1,s[0]);       DataTypes::ShapeType ev_shape(1,s[0]);
1894       Data ev(0.,ev_shape,getFunctionSpace());       Data ev(0.,ev_shape,getFunctionSpace());
1895       ev.typeMatchRight(*this);       ev.typeMatchRight(*this);
1896       m_data->eigenvalues(ev.m_data.get());       m_data->eigenvalues(ev.m_data.get());
# Line 1487  Data::eigenvalues() const Line 1900  Data::eigenvalues() const
1900  const boost::python::tuple  const boost::python::tuple
1901  Data::eigenvalues_and_eigenvectors(const double tol) const  Data::eigenvalues_and_eigenvectors(const double tol) const
1902  {  {
1903       #if defined DOPROF       if (isLazy())
1904          profData->unary++;       {
1905       #endif      Data temp(*this);   // to get around the fact that you can't resolve a const Data
1906       DataArrayView::ShapeType s=getDataPointShape();      temp.resolve();
1907       if (getDataPointRank()!=2)      return temp.eigenvalues_and_eigenvectors(tol);
1908         }
1909         DataTypes::ShapeType s=getDataPointShape();
1910         if (getDataPointRank()!=2)
1911          throw DataException("Error - Data::eigenvalues and eigenvectors can only be calculated for rank 2 object.");          throw DataException("Error - Data::eigenvalues and eigenvectors can only be calculated for rank 2 object.");
1912       if(s[0] != s[1])       if(s[0] != s[1])
1913          throw DataException("Error - Data::eigenvalues and eigenvectors can only be calculated for object with equal first and second dimension.");          throw DataException("Error - Data::eigenvalues and eigenvectors can only be calculated for object with equal first and second dimension.");
1914       // create return       // create return
1915       DataArrayView::ShapeType ev_shape(1,s[0]);       DataTypes::ShapeType ev_shape(1,s[0]);
1916       Data ev(0.,ev_shape,getFunctionSpace());       Data ev(0.,ev_shape,getFunctionSpace());
1917       ev.typeMatchRight(*this);       ev.typeMatchRight(*this);
1918       DataArrayView::ShapeType V_shape(2,s[0]);       DataTypes::ShapeType V_shape(2,s[0]);
1919       Data V(0.,V_shape,getFunctionSpace());       Data V(0.,V_shape,getFunctionSpace());
1920       V.typeMatchRight(*this);       V.typeMatchRight(*this);
1921       m_data->eigenvalues_and_eigenvectors(ev.m_data.get(),V.m_data.get(),tol);       m_data->eigenvalues_and_eigenvectors(ev.m_data.get(),V.m_data.get(),tol);
# Line 1507  Data::eigenvalues_and_eigenvectors(const Line 1923  Data::eigenvalues_and_eigenvectors(const
1923  }  }
1924    
1925  const boost::python::tuple  const boost::python::tuple
1926  Data::mindp() const  Data::minGlobalDataPoint() const
1927  {  {
1928    // NB: calc_mindp had to be split off from mindp as boost::make_tuple causes an    // NB: calc_minGlobalDataPoint( had to be split off from minGlobalDataPoint( as boost::make_tuple causes an
1929    // abort (for unknown reasons) if there are openmp directives with it in the    // abort (for unknown reasons) if there are openmp directives with it in the
1930    // surrounding function    // surrounding function
1931    
   int SampleNo;  
1932    int DataPointNo;    int DataPointNo;
1933      int ProcNo;    int ProcNo;
1934    calc_mindp(ProcNo,SampleNo,DataPointNo);    calc_minGlobalDataPoint(ProcNo,DataPointNo);
1935    return make_tuple(ProcNo,SampleNo,DataPointNo);    return make_tuple(ProcNo,DataPointNo);
1936  }  }
1937    
1938  void  void
1939  Data::calc_mindp(   int& ProcNo,  Data::calc_minGlobalDataPoint(int& ProcNo,
1940                  int& SampleNo,                          int& DataPointNo) const
         int& DataPointNo) const  
1941  {  {
1942      if (isLazy())
1943      {
1944        Data temp(*this);   // to get around the fact that you can't resolve a const Data
1945        temp.resolve();
1946        return temp.calc_minGlobalDataPoint(ProcNo,DataPointNo);
1947      }
1948    int i,j;    int i,j;
1949    int lowi=0,lowj=0;    int lowi=0,lowj=0;
1950    double min=numeric_limits<double>::max();    double min=numeric_limits<double>::max();
# Line 1535  Data::calc_mindp(  int& ProcNo, Line 1955  Data::calc_mindp(  int& ProcNo,
1955    int numDPPSample=temp.getNumDataPointsPerSample();    int numDPPSample=temp.getNumDataPointsPerSample();
1956    
1957    double next,local_min;    double next,local_min;
1958    int local_lowi,local_lowj;    int local_lowi=0,local_lowj=0;    
1959    
1960    #pragma omp parallel private(next,local_min,local_lowi,local_lowj)    #pragma omp parallel firstprivate(local_lowi,local_lowj) private(next,local_min)
1961    {    {
1962      local_min=min;      local_min=min;
1963      #pragma omp for private(i,j) schedule(static)      #pragma omp for private(i,j) schedule(static)
1964      for (i=0; i<numSamples; i++) {      for (i=0; i<numSamples; i++) {
1965        for (j=0; j<numDPPSample; j++) {        for (j=0; j<numDPPSample; j++) {
1966          next=temp.getDataPoint(i,j)();          next=temp.getDataAtOffsetRO(temp.getDataOffset(i,j));
1967          if (next<local_min) {          if (next<local_min) {
1968            local_min=next;            local_min=next;
1969            local_lowi=i;            local_lowi=i;
# Line 1552  Data::calc_mindp(  int& ProcNo, Line 1972  Data::calc_mindp(  int& ProcNo,
1972        }        }
1973      }      }
1974      #pragma omp critical      #pragma omp critical
1975      if (local_min<min) {      if (local_min<min) {    // If we found a smaller value than our sentinel
1976        min=local_min;        min=local_min;
1977        lowi=local_lowi;        lowi=local_lowi;
1978        lowj=local_lowj;        lowj=local_lowj;
# Line 1560  Data::calc_mindp(  int& ProcNo, Line 1980  Data::calc_mindp(  int& ProcNo,
1980    }    }
1981    
1982  #ifdef PASO_MPI  #ifdef PASO_MPI
1983      // determine the processor on which the minimum occurs    // determine the processor on which the minimum occurs
1984      next = temp.getDataPoint(lowi,lowj)();    next = temp.getDataPointRO(lowi,lowj);
1985      int lowProc = 0;    int lowProc = 0;
1986      double *globalMins = new double[get_MPISize()+1];    double *globalMins = new double[get_MPISize()+1];
1987      int error = MPI_Gather ( &next, 1, MPI_DOUBLE, globalMins, 1, MPI_DOUBLE, 0, get_MPIComm() );    int error;
1988          error = MPI_Gather ( &next, 1, MPI_DOUBLE, globalMins, 1, MPI_DOUBLE, 0, get_MPIComm() );
1989      if( get_MPIRank()==0 ){  
1990          next = globalMins[lowProc];    if( get_MPIRank()==0 ){
1991          for( i=1; i<get_MPISize(); i++ )      next = globalMins[lowProc];
1992              if( next>globalMins[i] ){      for( i=1; i<get_MPISize(); i++ )
1993                  lowProc = i;          if( next>globalMins[i] ){
1994                  next = globalMins[i];              lowProc = i;
1995              }              next = globalMins[i];
1996      }          }
1997      MPI_Bcast( &lowProc, 1, MPI_DOUBLE, 0, get_MPIComm() );    }
1998      MPI_Bcast( &lowProc, 1, MPI_INT, 0, get_MPIComm() );
1999    
2000      delete [] globalMins;
2001      ProcNo = lowProc;
2002    #else
2003      ProcNo = 0;
2004    #endif
2005      DataPointNo = lowj + lowi * numDPPSample;
2006    }
2007    
2008    
2009    const boost::python::tuple
2010    Data::maxGlobalDataPoint() const
2011    {
2012      int DataPointNo;
2013      int ProcNo;
2014      calc_maxGlobalDataPoint(ProcNo,DataPointNo);
2015      return make_tuple(ProcNo,DataPointNo);
2016    }
2017    
2018    void
2019    Data::calc_maxGlobalDataPoint(int& ProcNo,
2020                            int& DataPointNo) const
2021    {
2022      if (isLazy())
2023      {
2024        Data temp(*this);   // to get around the fact that you can't resolve a const Data
2025        temp.resolve();
2026        return temp.calc_maxGlobalDataPoint(ProcNo,DataPointNo);
2027      }
2028      int i,j;
2029      int highi=0,highj=0;
2030    //-------------
2031      double max=numeric_limits<double>::min();
2032    
2033      Data temp=maxval();
2034    
2035      int numSamples=temp.getNumSamples();
2036      int numDPPSample=temp.getNumDataPointsPerSample();
2037    
2038      double next,local_max;
2039      int local_highi=0,local_highj=0;  
2040    
2041      delete [] globalMins;    #pragma omp parallel firstprivate(local_highi,local_highj) private(next,local_max)
2042      ProcNo = lowProc;    {
2043        local_max=max;
2044        #pragma omp for private(i,j) schedule(static)
2045        for (i=0; i<numSamples; i++) {
2046          for (j=0; j<numDPPSample; j++) {
2047            next=temp.getDataAtOffsetRO(temp.getDataOffset(i,j));
2048            if (next>local_max) {
2049              local_max=next;
2050              local_highi=i;
2051              local_highj=j;
2052            }
2053          }
2054        }
2055        #pragma omp critical
2056        if (local_max>max) {    // If we found a larger value than our sentinel
2057          max=local_max;
2058          highi=local_highi;
2059          highj=local_highj;
2060        }
2061      }
2062    
2063    #ifdef PASO_MPI
2064      // determine the processor on which the maximum occurs
2065      next = temp.getDataPointRO(highi,highj);
2066      int highProc = 0;
2067      double *globalMaxs = new double[get_MPISize()+1];
2068      int error;
2069      error = MPI_Gather ( &next, 1, MPI_DOUBLE, globalMaxs, 1, MPI_DOUBLE, 0, get_MPIComm() );
2070    
2071      if( get_MPIRank()==0 ){
2072      next = globalMaxs[highProc];
2073      for( i=1; i<get_MPISize(); i++ )
2074        if( next>globalMaxs[i] ){
2075            highProc = i;
2076            next = globalMaxs[i];
2077        }
2078      }
2079      MPI_Bcast( &highProc, 1, MPI_INT, 0, get_MPIComm() );
2080      delete [] globalMaxs;
2081      ProcNo = highProc;
2082  #else  #else
2083      ProcNo = 0;    ProcNo = 0;
2084  #endif  #endif
2085    SampleNo = lowi;    DataPointNo = highj + highi * numDPPSample;
   DataPointNo = lowj;  
2086  }  }
2087    
2088  void  void
2089  Data::saveDX(std::string fileName) const  Data::saveDX(std::string fileName) const
2090  {  {
2091      if (isEmpty())
2092      {
2093        throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2094      }
2095      if (isLazy())
2096      {
2097         Data temp(*this);  // to get around the fact that you can't resolve a const Data
2098         temp.resolve();
2099         temp.saveDX(fileName);
2100         return;
2101      }
2102    boost::python::dict args;    boost::python::dict args;
2103    args["data"]=boost::python::object(this);    args["data"]=boost::python::object(this);
2104    getDomain().saveDX(fileName,args);    getDomain()->saveDX(fileName,args);
2105    return;    return;
2106  }  }
2107    
2108  void  void
2109  Data::saveVTK(std::string fileName) const  Data::saveVTK(std::string fileName) const
2110  {  {
2111      if (isEmpty())
2112      {
2113        throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2114      }
2115      if (isLazy())
2116      {
2117         Data temp(*this);  // to get around the fact that you can't resolve a const Data
2118         temp.resolve();
2119         temp.saveVTK(fileName);
2120         return;
2121      }
2122    boost::python::dict args;    boost::python::dict args;
2123    args["data"]=boost::python::object(this);    args["data"]=boost::python::object(this);
2124    getDomain().saveVTK(fileName,args);    getDomain()->saveVTK(fileName,args,"","");
2125    return;    return;
2126  }  }
2127    
2128    
2129    
2130  Data&  Data&
2131  Data::operator+=(const Data& right)  Data::operator+=(const Data& right)
2132  {  {
2133    if (isProtected()) {    if (isProtected()) {
2134          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2135    }    }
2136  #if defined DOPROF    MAKELAZYBINSELF(right,ADD)    // for lazy + is equivalent to +=
2137    profData->binary++;    exclusiveWrite();         // Since Lazy data does not modify its leaves we only need to worry here
 #endif  
2138    binaryOp(right,plus<double>());    binaryOp(right,plus<double>());
2139    return (*this);    return (*this);
2140  }  }
# Line 1622  Data::operator+=(const boost::python::ob Line 2145  Data::operator+=(const boost::python::ob
2145    if (isProtected()) {    if (isProtected()) {
2146          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2147    }    }
2148  #if defined DOPROF    Data tmp(right,getFunctionSpace(),false);
2149    profData->binary++;    (*this)+=tmp;
2150      return *this;
2151    }
2152    
2153    // Hmmm, operator= makes a deep copy but the copy constructor does not?
2154    Data&
2155    Data::operator=(const Data& other)
2156    {
2157    #if defined ASSIGNMENT_MEANS_DEEPCOPY  
2158    // This should not be used.
2159    // Just leaving this here until I have completed transition
2160      copy(other);
2161    #else
2162      m_protected=false;        // since any changes should be caught by exclusiveWrite();
2163    //   m_data=other.m_data;
2164      set_m_data(other.m_data);
2165  #endif  #endif
   binaryOp(right,plus<double>());  
2166    return (*this);    return (*this);
2167  }  }
2168    
# Line 1635  Data::operator-=(const Data& right) Line 2172  Data::operator-=(const Data& right)
2172    if (isProtected()) {    if (isProtected()) {
2173          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2174    }    }
2175  #if defined DOPROF    MAKELAZYBINSELF(right,SUB)
2176    profData->binary++;    exclusiveWrite();
 #endif  
2177    binaryOp(right,minus<double>());    binaryOp(right,minus<double>());
2178    return (*this);    return (*this);
2179  }  }
# Line 1648  Data::operator-=(const boost::python::ob Line 2184  Data::operator-=(const boost::python::ob
2184    if (isProtected()) {    if (isProtected()) {
2185          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2186    }    }
2187  #if defined DOPROF    Data tmp(right,getFunctionSpace(),false);
2188    profData->binary++;    (*this)-=tmp;
 #endif  
   binaryOp(right,minus<double>());  
2189    return (*this);    return (*this);
2190  }  }
2191    
# Line 1661  Data::operator*=(const Data& right) Line 2195  Data::operator*=(const Data& right)
2195    if (isProtected()) {    if (isProtected()) {
2196          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2197    }    }
2198  #if defined DOPROF    MAKELAZYBINSELF(right,MUL)
2199    profData->binary++;    exclusiveWrite();
 #endif  
2200    binaryOp(right,multiplies<double>());    binaryOp(right,multiplies<double>());
2201    return (*this);    return (*this);
2202  }  }
2203    
2204  Data&  Data&
2205  Data::operator*=(const boost::python::object& right)  Data::operator*=(const boost::python::object& right)
2206  {  {  
2207    if (isProtected()) {    if (isProtected()) {
2208          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2209    }    }
2210  #if defined DOPROF    Data tmp(right,getFunctionSpace(),false);
2211    profData->binary++;    (*this)*=tmp;
 #endif  
   binaryOp(right,multiplies<double>());  
2212    return (*this);    return (*this);
2213  }  }
2214    
# Line 1687  Data::operator/=(const Data& right) Line 2218  Data::operator/=(const Data& right)
2218    if (isProtected()) {    if (isProtected()) {
2219          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2220    }    }
2221  #if defined DOPROF    MAKELAZYBINSELF(right,DIV)
2222    profData->binary++;    exclusiveWrite();
 #endif  
2223    binaryOp(right,divides<double>());    binaryOp(right,divides<double>());
2224    return (*this);    return (*this);
2225  }  }
# Line 1700  Data::operator/=(const boost::python::ob Line 2230  Data::operator/=(const boost::python::ob
2230    if (isProtected()) {    if (isProtected()) {
2231          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2232    }    }
2233  #if defined DOPROF    Data tmp(right,getFunctionSpace(),false);
2234    profData->binary++;    (*this)/=tmp;
 #endif  
   binaryOp(right,divides<double>());  
2235    return (*this);    return (*this);
2236  }  }
2237    
2238  Data  Data
2239  Data::rpowO(const boost::python::object& left) const  Data::rpowO(const boost::python::object& left) const
2240  {  {
   if (isProtected()) {  
         throw DataException("Error - attempt to update protected Data object.");  
   }  
 #if defined DOPROF  
   profData->binary++;  
 #endif  
2241    Data left_d(left,*this);    Data left_d(left,*this);
2242    return left_d.powD(*this);    return left_d.powD(*this);
2243  }  }
# Line 1723  Data::rpowO(const boost::python::object& Line 2245  Data::rpowO(const boost::python::object&
2245  Data  Data
2246  Data::powO(const boost::python::object& right) const  Data::powO(const boost::python::object& right) const
2247  {  {
2248  #if defined DOPROF    Data tmp(right,getFunctionSpace(),false);
2249    profData->binary++;    return powD(tmp);
 #endif  
   Data result;  
   result.copy(*this);  
   result.binaryOp(right,(Data::BinaryDFunPtr)::pow);  
   return result;  
2250  }  }
2251    
2252  Data  Data
2253  Data::powD(const Data& right) const  Data::powD(const Data& right) const
2254  {  {
2255  #if defined DOPROF    MAKELAZYBIN(right,POW)
2256    profData->binary++;    return C_TensorBinaryOperation<double (*)(double, double)>(*this, right, ::pow);
 #endif  
   Data result;  
   result.copy(*this);  
   result.binaryOp(right,(Data::BinaryDFunPtr)::pow);  
   return result;  
2257  }  }
2258    
   
2259  //  //
2260  // NOTE: It is essential to specify the namespace this operator belongs to  // NOTE: It is essential to specify the namespace this operator belongs to
2261  Data  Data
2262  escript::operator+(const Data& left, const Data& right)  escript::operator+(const Data& left, const Data& right)
2263  {  {
2264    Data result;    MAKELAZYBIN2(left,right,ADD)
2265    //    return C_TensorBinaryOperation(left, right, plus<double>());
   // perform a deep copy  
   result.copy(left);  
   result+=right;  
   return result;  
2266  }  }
2267    
2268  //  //
# Line 1763  escript::operator+(const Data& left, con Line 2270  escript::operator+(const Data& left, con
2270  Data  Data
2271  escript::operator-(const Data& left, const Data& right)  escript::operator-(const Data& left, const Data& right)
2272  {  {
2273    Data result;    MAKELAZYBIN2(left,right,SUB)
2274    //    return C_TensorBinaryOperation(left, right, minus<double>());
   // perform a deep copy  
   result.copy(left);  
   result-=right;  
   return result;  
2275  }  }
2276    
2277  //  //
# Line 1776  escript::operator-(const Data& left, con Line 2279  escript::operator-(const Data& left, con
2279  Data  Data
2280  escript::operator*(const Data& left, const Data& right)  escript::operator*(const Data& left, const Data& right)
2281  {  {
2282    Data result;    MAKELAZYBIN2(left,right,MUL)
2283    //    return C_TensorBinaryOperation(left, right, multiplies<double>());
   // perform a deep copy  
   result.copy(left);  
   result*=right;  
   return result;  
2284  }  }
2285    
2286  //  //
# Line 1789  escript::operator*(const Data& left, con Line 2288  escript::operator*(const Data& left, con
2288  Data  Data
2289  escript::operator/(const Data& left, const Data& right)  escript::operator/(const Data& left, const Data& right)
2290  {  {
2291    Data result;    MAKELAZYBIN2(left,right,DIV)
2292    //    return C_TensorBinaryOperation(left, right, divides<double>());
   // perform a deep copy  
   result.copy(left);  
   result/=right;  
   return result;  
2293  }  }
2294    
2295  //  //
# Line 1802  escript::operator/(const Data& left, con Line 2297  escript::operator/(const Data& left, con
2297  Data  Data
2298  escript::operator+(const Data& left, const boost::python::object& right)  escript::operator+(const Data& left, const boost::python::object& right)
2299  {  {
2300    //    Data tmp(right,left.getFunctionSpace(),false);
2301    // Convert to DataArray format if possible    MAKELAZYBIN2(left,tmp,ADD)
2302    DataArray temp(right);    return left+tmp;
   Data result;  
   //  
   // perform a deep copy  
   result.copy(left);  
   result+=right;  
   return result;  
2303  }  }
2304    
2305  //  //
# Line 1818  escript::operator+(const Data& left, con Line 2307  escript::operator+(const Data& left, con
2307  Data  Data
2308  escript::operator-(const Data& left, const boost::python::object& right)  escript::operator-(const Data& left, const boost::python::object& right)
2309  {  {
2310    //    Data tmp(right,left.getFunctionSpace(),false);
2311    // Convert to DataArray format if possible    MAKELAZYBIN2(left,tmp,SUB)
2312    DataArray temp(right);    return left-tmp;
   Data result;  
   //  
   // perform a deep copy  
   result.copy(left);  
   result-=right;  
   return result;  
2313  }  }
2314    
2315  //  //
# Line 1834  escript::operator-(const Data& left, con Line 2317  escript::operator-(const Data& left, con
2317  Data  Data
2318  escript::operator*(const Data& left, const boost::python::object& right)  escript::operator*(const Data& left, const boost::python::object& right)
2319  {  {
2320    //    Data tmp(right,left.getFunctionSpace(),false);
2321    // Convert to DataArray format if possible    MAKELAZYBIN2(left,tmp,MUL)
2322    DataArray temp(right);    return left*tmp;
   Data result;  
   //  
   // perform a deep copy  
   result.copy(left);  
   result*=right;  
   return result;  
2323  }  }
2324    
2325  //  //
# Line 1850  escript::operator*(const Data& left, con Line 2327  escript::operator*(const Data& left, con
2327  Data  Data
2328  escript::operator/(const Data& left, const boost::python::object& right)  escript::operator/(const Data& left, const boost::python::object& right)
2329  {  {
2330    //    Data tmp(right,left.getFunctionSpace(),false);
2331    // Convert to DataArray format if possible    MAKELAZYBIN2(left,tmp,DIV)
2332    DataArray temp(right);    return left/tmp;
   Data result;  
   //  
   // perform a deep copy  
   result.copy(left);  
   result/=right;  
   return result;  
2333  }  }
2334    
2335  //  //
# Line 1866  escript::operator/(const Data& left, con Line 2337  escript::operator/(const Data& left, con
2337  Data  Data
2338  escript::operator+(const boost::python::object& left, const Data& right)  escript::operator+(const boost::python::object& left, const Data& right)
2339  {  {
2340    //    Data tmp(left,right.getFunctionSpace(),false);
2341    // Construct the result using the given value and the other parameters    MAKELAZYBIN2(tmp,right,ADD)
2342    // from right    return tmp+right;
   Data result(left,right);  
   result+=right;  
   return result;  
2343  }  }
2344    
2345  //  //
# Line 1879  escript::operator+(const boost::python:: Line 2347  escript::operator+(const boost::python::
2347  Data  Data
2348  escript::operator-(const boost::python::object& left, const Data& right)  escript::operator-(const boost::python::object& left, const Data& right)
2349  {  {
2350    //    Data tmp(left,right.getFunctionSpace(),false);
2351    // Construct the result using the given value and the other parameters    MAKELAZYBIN2(tmp,right,SUB)
2352    // from right    return tmp-right;
   Data result(left,right);  
   result-=right;  
   return result;  
2353  }  }
2354    
2355  //  //
# Line 1892  escript::operator-(const boost::python:: Line 2357  escript::operator-(const boost::python::
2357  Data  Data
2358  escript::operator*(const boost::python::object& left, const Data& right)  escript::operator*(const boost::python::object& left, const Data& right)
2359  {  {
2360    //    Data tmp(left,right.getFunctionSpace(),false);
2361    // Construct the result using the given value and the other parameters    MAKELAZYBIN2(tmp,right,MUL)
2362    // from right    return tmp*right;
   Data result(left,right);  
   result*=right;  
   return result;  
2363  }  }
2364    
2365  //  //
# Line 1905  escript::operator*(const boost::python:: Line 2367  escript::operator*(const boost::python::
2367  Data  Data
2368  escript::operator/(const boost::python::object& left, const Data& right)  escript::operator/(const boost::python::object& left, const Data& right)
2369  {  {
2370    //    Data tmp(left,right.getFunctionSpace(),false);
2371    // Construct the result using the given value and the other parameters    MAKELAZYBIN2(tmp,right,DIV)
2372    // from right    return tmp/right;
   Data result(left,right);  
   result/=right;  
   return result;  
2373  }  }
2374    
 //  
 //bool escript::operator==(const Data& left, const Data& right)  
 //{  
 //  /*  
 //  NB: this operator does very little at this point, and isn't to  
 //  be relied on. Requires further implementation.  
 //  */  
 //  
 //  bool ret;  
 //  
 //  if (left.isEmpty()) {  
 //    if(!right.isEmpty()) {  
 //      ret = false;  
 //    } else {  
 //      ret = true;  
 //    }  
 //  }  
 //  
 //  if (left.isConstant()) {  
 //    if(!right.isConstant()) {  
 //      ret = false;  
 //    } else {  
 //      ret = true;  
 //    }  
 // }  
 //  
 //  if (left.isTagged()) {  
 //   if(!right.isTagged()) {  
 //      ret = false;  
 //    } else {  
 //      ret = true;  
 //    }  
 //  }  
 //  
 //  if (left.isExpanded()) {  
 //    if(!right.isExpanded()) {  
 //      ret = false;  
 //    } else {  
 //      ret = true;  
 //    }  
 //  }  
 //  
 //  return ret;  
 //}  
2375    
2376  /* TODO */  /* TODO */
2377  /* global reduction */  /* global reduction */
2378  Data  Data
2379  Data::getItem(const boost::python::object& key) const  Data::getItem(const boost::python::object& key) const
2380  {  {
   const DataArrayView& view=getPointDataView();  
2381    
2382    DataArrayView::RegionType slice_region=view.getSliceRegion(key);    DataTypes::RegionType slice_region=DataTypes::getSliceRegion(getDataPointShape(),key);
2383    
2384    if (slice_region.size()!=view.getRank()) {    if (slice_region.size()!=getDataPointRank()) {
2385      throw DataException("Error - slice size does not match Data rank.");      throw DataException("Error - slice size does not match Data rank.");
2386    }    }
2387    
# Line 1977  Data::getItem(const boost::python::objec Line 2391  Data::getItem(const boost::python::objec
2391  /* TODO */  /* TODO */
2392  /* global reduction */  /* global reduction */
2393  Data  Data
2394  Data::getSlice(const DataArrayView::RegionType& region) const  Data::getSlice(const DataTypes::RegionType& region) const
2395  {  {
 #if defined DOPROF  
   profData->slicing++;  
 #endif  
2396    return Data(*this,region);    return Data(*this,region);
2397  }  }
2398    
# Line 1995  Data::setItemO(const boost::python::obje Line 2406  Data::setItemO(const boost::python::obje
2406    setItemD(key,tempData);    setItemD(key,tempData);
2407  }  }
2408    
 /* TODO */  
 /* global reduction */  
2409  void  void
2410  Data::setItemD(const boost::python::object& key,  Data::setItemD(const boost::python::object& key,
2411                 const Data& value)                 const Data& value)
2412  {  {
2413    const DataArrayView& view=getPointDataView();    DataTypes::RegionType slice_region=DataTypes::getSliceRegion(getDataPointShape(),key);
2414      if (slice_region.size()!=getDataPointRank()) {
   DataArrayView::RegionType slice_region=view.getSliceRegion(key);  
   if (slice_region.size()!=view.getRank()) {  
2415      throw DataException("Error - slice size does not match Data rank.");      throw DataException("Error - slice size does not match Data rank.");
2416    }    }
2417      exclusiveWrite();
2418    if (getFunctionSpace()!=value.getFunctionSpace()) {    if (getFunctionSpace()!=value.getFunctionSpace()) {
2419       setSlice(Data(value,getFunctionSpace()),slice_region);       setSlice(Data(value,getFunctionSpace()),slice_region);
2420    } else {    } else {
# Line 2014  Data::setItemD(const boost::python::obje Line 2422  Data::setItemD(const boost::python::obje
2422    }    }
2423  }  }
2424    
 /* TODO */  
 /* global reduction */  
2425  void  void
2426  Data::setSlice(const Data& value,  Data::setSlice(const Data& value,
2427                 const DataArrayView::RegionType& region)                 const DataTypes::RegionType& region)
2428  {  {
2429    if (isProtected()) {    if (isProtected()) {
2430          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2431    }    }
2432  #if defined DOPROF    forceResolve();
2433    profData->slicing++;    exclusiveWrite();     // In case someone finds a way to call this without going through setItemD
 #endif  
2434    Data tempValue(value);    Data tempValue(value);
2435    typeMatchLeft(tempValue);    typeMatchLeft(tempValue);
2436    typeMatchRight(tempValue);    typeMatchRight(tempValue);
2437    m_data->setSlice(tempValue.m_data.get(),region);    getReady()->setSlice(tempValue.m_data.get(),region);
2438  }  }
2439    
2440  void  void
2441  Data::typeMatchLeft(Data& right) const  Data::typeMatchLeft(Data& right) const
2442  {  {
2443      if (right.isLazy() && !isLazy())
2444      {
2445        right.resolve();
2446      }
2447    if (isExpanded()){    if (isExpanded()){
2448      right.expand();      right.expand();
2449    } else if (isTagged()) {    } else if (isTagged()) {
# Line 2047  Data::typeMatchLeft(Data& right) const Line 2456  Data::typeMatchLeft(Data& right) const
2456  void  void
2457  Data::typeMatchRight(const Data& right)  Data::typeMatchRight(const Data& right)
2458  {  {
2459      if (isLazy() && !right.isLazy())
2460      {
2461        resolve();
2462      }
2463    if (isTagged()) {    if (isTagged()) {
2464      if (right.isExpanded()) {      if (right.isExpanded()) {
2465        expand();        expand();
# Line 2060  Data::typeMatchRight(const Data& right) Line 2473  Data::typeMatchRight(const Data& right)
2473    }    }
2474  }  }
2475    
2476  /* TODO */  // The normal TaggedValue adds the tag if it is not already present
2477  /* global reduction */  // This form does not. It throws instead.
2478    // This is because the names are maintained by the domain and cannot be added
2479    // without knowing the tag number to map it to.
2480    void
2481    Data::setTaggedValueByName(std::string name,
2482                               const boost::python::object& value)
2483    {
2484         if (getFunctionSpace().getDomain()->isValidTagName(name)) {
2485        forceResolve();
2486        exclusiveWrite();
2487            int tagKey=getFunctionSpace().getDomain()->getTag(name);
2488            setTaggedValue(tagKey,value);
2489         }
2490         else
2491         {                  // The
2492        throw DataException("Error - unknown tag in setTaggedValueByName.");
2493         }
2494    }
2495    
2496  void  void
2497  Data::setTaggedValue(int tagKey,  Data::setTaggedValue(int tagKey,
2498                       const boost::python::object& value)                       const boost::python::object& value)
# Line 2071  Data::setTaggedValue(int tagKey, Line 2502  Data::setTaggedValue(int tagKey,
2502    }    }
2503    //    //
2504    // Ensure underlying data object is of type DataTagged    // Ensure underlying data object is of type DataTagged
2505    tag();    forceResolve();
2506      exclusiveWrite();
2507      if (isConstant()) tag();
2508      WrappedArray w(value);
2509    
2510    if (!isTagged()) {    DataVector temp_data2;
2511      throw DataException("Error - DataTagged conversion failed!!");    temp_data2.copyFromArray(w,1);
   }  
   
   //  
   // Construct DataArray from boost::python::object input value  
   DataArray valueDataArray(value);  
2512    
2513    //    m_data->setTaggedValue(tagKey,w.getShape(), temp_data2);
   // Call DataAbstract::setTaggedValue  
   m_data->setTaggedValue(tagKey,valueDataArray.getView());  
2514  }  }
2515    
2516  /* TODO */  
 /* global reduction */  
2517  void  void
2518  Data::setTaggedValueFromCPP(int tagKey,  Data::setTaggedValueFromCPP(int tagKey,
2519                              const DataArrayView& value)                  const DataTypes::ShapeType& pointshape,
2520                                const DataTypes::ValueType& value,
2521                    int dataOffset)
2522  {  {
2523    if (isProtected()) {    if (isProtected()) {
2524          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2525    }    }
2526    //    //
2527    // Ensure underlying data object is of type DataTagged    // Ensure underlying data object is of type DataTagged
2528    tag();    forceResolve();
2529      if (isConstant()) tag();
2530    if (!isTagged()) {    exclusiveWrite();
     throw DataException("Error - DataTagged conversion failed!!");  
   }  
                                                                                                                 
2531    //    //
2532    // Call DataAbstract::setTaggedValue    // Call DataAbstract::setTaggedValue
2533    m_data->setTaggedValue(tagKey,value);    m_data->setTaggedValue(tagKey,pointshape, value, dataOffset);
2534  }  }
2535    
 /* TODO */  
 /* global reduction */  
2536  int  int
2537  Data::getTagNumber(int dpno)  Data::getTagNumber(int dpno)
2538  {  {
2539    return m_data->getTagNumber(dpno);    if (isEmpty())
2540  }    {
2541        throw DataException("Error - operation not permitted on instances of DataEmpty.");
 /* TODO */  
 /* global reduction */  
 void  
 Data::setRefValue(int ref,  
                   const boost::python::numeric::array& value)  
 {  
   if (isProtected()) {  
         throw DataException("Error - attempt to update protected Data object.");  
2542    }    }
2543    //    return getFunctionSpace().getTagFromDataPointNo(dpno);
   // Construct DataArray from boost::python::object input value  
   DataArray valueDataArray(value);  
   
   //  
   // Call DataAbstract::setRefValue  
   m_data->setRefValue(ref,valueDataArray);  
2544  }  }
2545    
 /* TODO */  
 /* global reduction */  
 void  
 Data::getRefValue(int ref,  
                   boost::python::numeric::array& value)  
 {  
   //  
   // Construct DataArray for boost::python::object return value  
   DataArray valueDataArray(value);  
2546    
2547    //  ostream& escript::operator<<(ostream& o, const Data& data)
2548    // Load DataArray with values from data-points specified by ref  {
2549    m_data->getRefValue(ref,valueDataArray);    o << data.toString();
2550      return o;
2551    //  }
   // Load values from valueDataArray into return numarray  
2552    
2553    // extract the shape of the numarray  Data
2554    int rank = value.getrank();  escript::C_GeneralTensorProduct(Data& arg_0,
2555    DataArrayView::ShapeType shape;                       Data& arg_1,
2556    for (int i=0; i < rank; i++) {                       int axis_offset,
2557      shape.push_back(extract<int>(value.getshape()[i]));                       int transpose)
2558    {
2559      // General tensor product: res(SL x SR) = arg_0(SL x SM) * arg_1(SM x SR)
2560      // SM is the product of the last axis_offset entries in arg_0.getShape().
2561    
2562      // deal with any lazy data
2563    //   if (arg_0.isLazy()) {arg_0.resolve();}
2564    //   if (arg_1.isLazy()) {arg_1.resolve();}
2565      if (arg_0.isLazy() || arg_1.isLazy() || (AUTOLAZYON && (arg_0.isExpanded() || arg_1.isExpanded())))
2566      {
2567        DataLazy* c=new DataLazy(arg_0.borrowDataPtr(), arg_1.borrowDataPtr(), PROD, axis_offset,transpose);
2568        return Data(c);
2569    }    }
2570    
2571    // and load the numarray with the data from the DataArray    // Interpolate if necessary and find an appropriate function space
2572    DataArrayView valueView = valueDataArray.getView();    Data arg_0_Z, arg_1_Z;
2573      if (arg_0.getFunctionSpace()!=arg_1.getFunctionSpace()) {
2574    if (rank==0) {      if (arg_0.probeInterpolation(arg_1.getFunctionSpace())) {
2575        boost::python::numeric::array temp_numArray(valueView());        arg_0_Z = arg_0.interpolate(arg_1.getFunctionSpace());
2576        value = temp_numArray;        arg_1_Z = Data(arg_1);
2577    }      }
2578    if (rank==1) {      else if (arg_1.probeInterpolation(arg_0.getFunctionSpace())) {
2579      for (int i=0; i < shape[0]; i++) {        arg_1_Z=arg_1.interpolate(arg_0.getFunctionSpace());
2580        value[i] = valueView(i);        arg_0_Z =Data(arg_0);
2581      }      }
2582    }      else {
2583    if (rank==2) {        throw DataException("Error - C_GeneralTensorProduct: arguments have incompatible function spaces.");
     for (int i=0; i < shape[0]; i++) {  
       for (int j=0; j < shape[1]; j++) {  
         value[i][j] = valueView(i,j);  
       }  
2584      }      }
2585      } else {
2586          arg_0_Z = Data(arg_0);
2587          arg_1_Z = Data(arg_1);
2588    }    }
2589    if (rank==3) {    // Get rank and shape of inputs
2590      for (int i=0; i < shape[0]; i++) {    int rank0 = arg_0_Z.getDataPointRank();
2591        for (int j=0; j < shape[1]; j++) {    int rank1 = arg_1_Z.getDataPointRank();
2592          for (int k=0; k < shape[2]; k++) {    const DataTypes::ShapeType& shape0 = arg_0_Z.getDataPointShape();
2593            value[i][j][k] = valueView(i,j,k);    const DataTypes::ShapeType& shape1 = arg_1_Z.getDataPointShape();
2594          }  
2595        }    // Prepare for the loops of the product and verify compatibility of shapes
2596      int start0=0, start1=0;
2597      if (transpose == 0)       {}
2598      else if (transpose == 1)  { start0 = axis_offset; }
2599      else if (transpose == 2)  { start1 = rank1-axis_offset; }
2600      else              { throw DataException("C_GeneralTensorProduct: Error - transpose should be 0, 1 or 2"); }
2601    
2602    
2603      // Adjust the shapes for transpose
2604      DataTypes::ShapeType tmpShape0(rank0);    // pre-sizing the vectors rather
2605      DataTypes::ShapeType tmpShape1(rank1);    // than using push_back
2606      for (int i=0; i<rank0; i++)   { tmpShape0[i]=shape0[(i+start0)%rank0]; }
2607      for (int i=0; i<rank1; i++)   { tmpShape1[i]=shape1[(i+start1)%rank1]; }
2608    
2609    #if 0
2610      // For debugging: show shape after transpose
2611      char tmp[100];
2612      std::string shapeStr;
2613      shapeStr = "(";
2614      for (int i=0; i<rank0; i++)   { sprintf(tmp, "%d,", tmpShape0[i]); shapeStr += tmp; }
2615      shapeStr += ")";
2616      cout << "C_GeneralTensorProduct: Shape of arg0 is " << shapeStr << endl;
2617      shapeStr = "(";
2618      for (int i=0; i<rank1; i++)   { sprintf(tmp, "%d,", tmpShape1[i]); shapeStr += tmp; }
2619      shapeStr += ")";
2620      cout << "C_GeneralTensorProduct: Shape of arg1 is " << shapeStr << endl;
2621    #endif
2622    
2623      // Prepare for the loops of the product
2624      int SL=1, SM=1, SR=1;
2625      for (int i=0; i<rank0-axis_offset; i++)   {
2626        SL *= tmpShape0[i];
2627      }
2628      for (int i=rank0-axis_offset; i<rank0; i++)   {
2629        if (tmpShape0[i] != tmpShape1[i-(rank0-axis_offset)]) {
2630          throw DataException("C_GeneralTensorProduct: Error - incompatible shapes");
2631        }
2632        SM *= tmpShape0[i];
2633      }
2634      for (int i=axis_offset; i<rank1; i++)     {
2635        SR *= tmpShape1[i];
2636      }
2637    
2638      // Define the shape of the output (rank of shape is the sum of the loop ranges below)
2639      DataTypes::ShapeType shape2(rank0+rank1-2*axis_offset);  
2640      {         // block to limit the scope of out_index
2641         int out_index=0;
2642         for (int i=0; i<rank0-axis_offset; i++, ++out_index) { shape2[out_index]=tmpShape0[i]; } // First part of arg_0_Z
2643         for (int i=axis_offset; i<rank1; i++, ++out_index)   { shape2[out_index]=tmpShape1[i]; } // Last part of arg_1_Z
2644      }
2645    
2646      if (shape2.size()>ESCRIPT_MAX_DATA_RANK)
2647      {
2648         ostringstream os;
2649         os << "C_GeneralTensorProduct: Error - Attempt to create a rank " << shape2.size() << " object. The maximum rank is " << ESCRIPT_MAX_DATA_RANK << ".";
2650         throw DataException(os.str());
2651      }
2652    
2653      // Declare output Data object
2654      Data res;
2655    
2656      if      (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2657        res = Data(0.0, shape2, arg_1_Z.getFunctionSpace());    // DataConstant output
2658        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2659        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2660        double *ptr_2 = &(res.getDataAtOffsetRW(0));
2661        matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2662      }
2663      else if (arg_0_Z.isConstant()   && arg_1_Z.isTagged()) {
2664    
2665        // Prepare the DataConstant input
2666        DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());
2667        if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
2668    
2669        // Borrow DataTagged input from Data object
2670        DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData());
2671        if (tmp_1==0) { throw DataException("GTP_1 Programming error - casting to DataTagged."); }
2672    
2673        // Prepare a DataTagged output 2
2674        res = Data(0.0, shape2, arg_1_Z.getFunctionSpace());    // DataTagged output
2675        res.tag();
2676        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2677        if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2678    
2679        // Prepare offset into DataConstant
2680        int offset_0 = tmp_0->getPointOffset(0,0);
2681        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2682    
2683        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2684        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2685    
2686        // Compute an MVP for the default
2687        matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2688        // Compute an MVP for each tag
2689        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2690        DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2691        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2692          tmp_2->addTag(i->first);
2693    
2694          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2695          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2696        
2697          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2698      }      }
2699    
2700    }    }
2701    if (rank==4) {    else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {
2702      for (int i=0; i < shape[0]; i++) {  
2703        for (int j=0; j < shape[1]; j++) {      res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2704          for (int k=0; k < shape[2]; k++) {      DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());
2705            for (int l=0; l < shape[3]; l++) {      DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData());
2706              value[i][j][k][l] = valueView(i,j,k,l);      DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2707            }      if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
2708          }      if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2709        if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2710        int sampleNo_1,dataPointNo_1;
2711        int numSamples_1 = arg_1_Z.getNumSamples();
2712        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2713        int offset_0 = tmp_0->getPointOffset(0,0);
2714        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2715        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2716          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2717            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2718            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2719            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2720            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2721            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2722            matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2723        }        }
2724      }      }
2725    
2726    }    }
2727      else if (arg_0_Z.isTagged()     && arg_1_Z.isConstant()) {
2728    
2729  }      // Borrow DataTagged input from Data object
2730        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2731        if (tmp_0==0) { throw DataException("GTP_0 Programming error - casting to DataTagged."); }
2732    
2733  void      // Prepare the DataConstant input
2734  Data::archiveData(const std::string fileName)      DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());
2735  {      if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
   cout << "Archiving Data object to: " << fileName << endl;  
2736    
2737    //      // Prepare a DataTagged output 2
2738    // Determine type of this Data object      res = Data(0.0, shape2, arg_0_Z.getFunctionSpace());    // DataTagged output
2739    int dataType = -1;      res.tag();
2740        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2741        if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2742    
2743    if (isEmpty()) {      // Prepare offset into DataConstant
2744      dataType = 0;      int offset_1 = tmp_1->getPointOffset(0,0);
2745      cout << "\tdataType: DataEmpty" << endl;      const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2746    }      const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2747    if (isConstant()) {      double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
     dataType = 1;  
     cout << "\tdataType: DataConstant" << endl;  
   }  
   if (isTagged()) {  
     dataType = 2;  
     cout << "\tdataType: DataTagged" << endl;  
   }  
   if (isExpanded()) {  
     dataType = 3;  
     cout << "\tdataType: DataExpanded" << endl;  
   }  
2748    
2749    if (dataType == -1) {      // Compute an MVP for the default
2750      throw DataException("archiveData Error: undefined dataType");      matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2751    }      // Compute an MVP for each tag
2752        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2753        DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2754        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2755    
2756    //        tmp_2->addTag(i->first);
2757    // Collect data items common to all Data types        const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2758    int noSamples = getNumSamples();        double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2759    int noDPPSample = getNumDataPointsPerSample();        matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
   int functionSpaceType = getFunctionSpace().getTypeCode();  
   int dataPointRank = getDataPointRank();  
   int dataPointSize = getDataPointSize();  
   int dataLength = getLength();  
   DataArrayView::ShapeType dataPointShape = getDataPointShape();  
   vector<int> referenceNumbers(noSamples);  
   for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {  
     referenceNumbers[sampleNo] = getFunctionSpace().getReferenceNoFromSampleNo(sampleNo);  
   }  
   vector<int> tagNumbers(noSamples);  
   if (isTagged()) {  
     for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {  
       tagNumbers[sampleNo] = getFunctionSpace().getTagFromSampleNo(sampleNo);  
2760      }      }
2761    
2762    }    }
2763      else if (arg_0_Z.isTagged()     && arg_1_Z.isTagged()) {
2764    
2765    cout << "\tnoSamples: " << noSamples << " noDPPSample: " << noDPPSample << endl;      // Borrow DataTagged input from Data object
2766    cout << "\tfunctionSpaceType: " << functionSpaceType << endl;      DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2767    cout << "\trank: " << dataPointRank << " size: " << dataPointSize << " length: " << dataLength << endl;      if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2768    
2769    //      // Borrow DataTagged input from Data object
2770    // Flatten Shape to an array of integers suitable for writing to file      DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData());
2771    int flatShape[4] = {0,0,0,0};      if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
   cout << "\tshape: < ";  
   for (int dim=0; dim<dataPointRank; dim++) {  
     flatShape[dim] = dataPointShape[dim];  
     cout << dataPointShape[dim] << " ";  
   }  
   cout << ">" << endl;  
2772    
2773    //      // Prepare a DataTagged output 2
2774    // Open archive file      res = Data(0.0, shape2, arg_1_Z.getFunctionSpace());
2775    ofstream archiveFile;      res.tag();  // DataTagged output
2776    archiveFile.open(fileName.data(), ios::out);      DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2777        if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2778    
2779    if (!archiveFile.good()) {      const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2780      throw DataException("archiveData Error: problem opening archive file");      const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2781    }      double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2782    
2783    //      // Compute an MVP for the default
2784    // Write common data items to archive file      matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2785    archiveFile.write(reinterpret_cast<char *>(&dataType),sizeof(int));      // Merge the tags
2786    archiveFile.write(reinterpret_cast<char *>(&noSamples),sizeof(int));      DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2787    archiveFile.write(reinterpret_cast<char *>(&noDPPSample),sizeof(int));      const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2788    archiveFile.write(reinterpret_cast<char *>(&functionSpaceType),sizeof(int));      const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2789    archiveFile.write(reinterpret_cast<char *>(&dataPointRank),sizeof(int));      for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2790    archiveFile.write(reinterpret_cast<char *>(&dataPointSize),sizeof(int));        tmp_2->addTag(i->first); // use tmp_2 to get correct shape
2791    archiveFile.write(reinterpret_cast<char *>(&dataLength),sizeof(int));      }
2792    for (int dim = 0; dim < 4; dim++) {      for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2793      archiveFile.write(reinterpret_cast<char *>(&flatShape[dim]),sizeof(int));        tmp_2->addTag(i->first);
2794    }      }
2795    for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {      // Compute an MVP for each tag
2796      archiveFile.write(reinterpret_cast<char *>(&referenceNumbers[sampleNo]),sizeof(int));      const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2797    }      for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2798    if (isTagged()) {        const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2799      for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {        const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2800        archiveFile.write(reinterpret_cast<char *>(&tagNumbers[sampleNo]),sizeof(int));        double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2801    
2802          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2803      }      }
   }  
2804    
   if (!archiveFile.good()) {  
     throw DataException("archiveData Error: problem writing to archive file");  
2805    }    }
2806      else if (arg_0_Z.isTagged()     && arg_1_Z.isExpanded()) {
2807    
2808    //      // After finding a common function space above the two inputs have the same numSamples and num DPPS
2809    // Archive underlying data values for each Data type      res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2810    int noValues;      DataTagged*   tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2811    switch (dataType) {      DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData());
2812      case 0:      DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2813        // DataEmpty      if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2814        noValues = 0;      if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2815        archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));      if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2816        cout << "\tnoValues: " << noValues << endl;      int sampleNo_0,dataPointNo_0;
2817        break;      int numSamples_0 = arg_0_Z.getNumSamples();
2818      case 1:      int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2819        // DataConstant      #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2820        noValues = m_data->getLength();      for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2821        archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));        int offset_0 = tmp_0->getPointOffset(sampleNo_0,0); // They're all the same, so just use #0
2822        cout << "\tnoValues: " << noValues << endl;        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2823        if (m_data->archiveData(archiveFile,noValues)) {        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2824          throw DataException("archiveData Error: problem writing data to archive file");          int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2825        }          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2826        break;          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2827      case 2:          double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2828        // DataTagged          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
       noValues = m_data->getLength();  
       archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));  
       cout << "\tnoValues: " << noValues << endl;  
       if (m_data->archiveData(archiveFile,noValues)) {  
         throw DataException("archiveData Error: problem writing data to archive file");  
2829        }        }
2830        break;      }
2831      case 3:  
2832        // DataExpanded    }
2833        noValues = m_data->getLength();    else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {
2834        archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));  
2835        cout << "\tnoValues: " << noValues << endl;      res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2836        if (m_data->archiveData(archiveFile,noValues)) {      DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2837          throw DataException("archiveData Error: problem writing data to archive file");      DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());
2838        DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2839        if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2840        if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
2841        if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2842        int sampleNo_0,dataPointNo_0;
2843        int numSamples_0 = arg_0_Z.getNumSamples();
2844        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2845        int offset_1 = tmp_1->getPointOffset(0,0);
2846        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2847        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2848          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2849            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2850            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2851            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2852            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2853            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2854            matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2855        }        }
2856        break;      }
2857    
2858    
2859    }    }
2860      else if (arg_0_Z.isExpanded()   && arg_1_Z.isTagged()) {
2861    
2862        // After finding a common function space above the two inputs have the same numSamples and num DPPS
2863        res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2864        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2865        DataTagged*   tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData());
2866        DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2867        if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2868        if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2869        if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2870        int sampleNo_0,dataPointNo_0;
2871        int numSamples_0 = arg_0_Z.getNumSamples();
2872        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2873        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2874        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2875          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2876          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2877          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2878            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2879            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2880            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2881            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2882            matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2883          }
2884        }
2885    
   if (!archiveFile.good()) {  
     throw DataException("archiveData Error: problem writing data to archive file");  
2886    }    }
2887      else if (arg_0_Z.isExpanded()   && arg_1_Z.isExpanded()) {
2888    
2889    //      // After finding a common function space above the two inputs have the same numSamples and num DPPS
2890    // Close archive file      res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2891    archiveFile.close();      DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2892        DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData());
2893        DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2894        if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2895        if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2896        if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2897        int sampleNo_0,dataPointNo_0;
2898        int numSamples_0 = arg_0_Z.getNumSamples();
2899        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2900        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2901        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2902          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2903            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2904            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2905            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2906            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2907            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2908            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2909            matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2910          }
2911        }
2912    
2913    if (!archiveFile.good()) {    }
2914      throw DataException("archiveData Error: problem closing archive file");    else {
2915        throw DataException("Error - C_GeneralTensorProduct: unknown combination of inputs");
2916    }    }
2917    
2918      return res;
2919  }  }
2920    
2921  void  DataAbstract*
2922  Data::extractData(const std::string fileName,  Data::borrowData() const
                   const FunctionSpace& fspace)  
2923  {  {
2924    //    return m_data.get();
2925    // Can only extract Data to an object which is initially DataEmpty  }
   if (!isEmpty()) {  
     throw DataException("extractData Error: can only extract to DataEmpty object");  
   }  
   
   cout << "Extracting Data object from: " << fileName << endl;  
   
   int dataType;  
   int noSamples;  
   int noDPPSample;  
&n