/[escript]/trunk/escript/src/Data.cpp
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revision 2037 by jfenwick, Thu Nov 13 06:17:12 2008 UTC revision 2721 by jfenwick, Fri Oct 16 05:40:12 2009 UTC
# Line 1  Line 1 
1    
2  /*******************************************************  /*******************************************************
3  *  *
4  * Copyright (c) 2003-2008 by University of Queensland  * Copyright (c) 2003-2009 by University of Queensland
5  * Earth Systems Science Computational Center (ESSCC)  * Earth Systems Science Computational Center (ESSCC)
6  * http://www.uq.edu.au/esscc  * http://www.uq.edu.au/esscc
7  *  *
# Line 26  Line 26 
26  #include "EscriptParams.h"  #include "EscriptParams.h"
27    
28  extern "C" {  extern "C" {
29  #include "escript/blocktimer.h"  #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;
# Line 45  using namespace escript; Line 47  using namespace escript;
47    
48  // ensure the current object is not a DataLazy  // ensure the current object is not a DataLazy
49  // The idea was that we could add an optional warning whenever a resolve is forced  // The idea was that we could add an optional warning whenever a resolve is forced
50  #define FORCERESOLVE if (isLazy()) {resolve();}  // #define forceResolve() if (isLazy()) {#resolve();}
51    
52    #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    #define CHECK_DO_CRES escriptParams.getRESOLVE_COLLECTIVE()
91    
92    namespace
93    {
94    
95    template <class ARR>
96    inline
97    boost::python::tuple
98    pointToTuple1(const DataTypes::ShapeType& shape, ARR v, unsigned long offset)
99    {
100        using namespace boost::python;
101        using boost::python::tuple;
102        using boost::python::list;
103    
104        list l;
105        unsigned int dim=shape[0];
106        for (size_t i=0;i<dim;++i)
107        {
108        l.append(v[i+offset]);
109        }
110        return tuple(l);
111    }
112    
113    template <class ARR>
114    inline
115    boost::python::tuple
116    pointToTuple2(const DataTypes::ShapeType& shape, ARR v, unsigned long offset)
117    {
118        using namespace boost::python;
119        using boost::python::tuple;
120        using boost::python::list;
121    
122        unsigned int shape0=shape[0];
123        unsigned int shape1=shape[1];
124        list lj;
125        for (size_t j=0;j<shape0;++j)
126        {
127            list li;
128        for (size_t i=0;i<shape1;++i)
129        {
130            li.append(v[offset+DataTypes::getRelIndex(shape,j,i)]);
131        }
132        lj.append(tuple(li));
133        }
134        return tuple(lj);
135    }
136    
137    template <class ARR>
138    inline
139    boost::python::tuple
140    pointToTuple3(const DataTypes::ShapeType& shape, ARR v, unsigned long offset)
141    {
142        using namespace boost::python;
143        using boost::python::tuple;
144        using boost::python::list;
145    
146        unsigned int shape0=shape[0];
147        unsigned int shape1=shape[1];
148        unsigned int shape2=shape[2];
149    
150        list lk;
151        for (size_t k=0;k<shape0;++k)
152        {
153            list lj;
154        for (size_t j=0;j<shape1;++j)
155        {
156            list li;
157            for (size_t i=0;i<shape2;++i)
158            {
159                    li.append(v[offset+DataTypes::getRelIndex(shape,k,j,i)]);
160                }
161            lj.append(tuple(li));
162            }
163            lk.append(tuple(lj));
164        }
165        return tuple(lk);
166    }
167    
168    template <class ARR>
169    inline
170    boost::python::tuple
171    pointToTuple4(const DataTypes::ShapeType& shape, ARR v, unsigned long offset)
172    {
173        using namespace boost::python;
174        using boost::python::tuple;
175        using boost::python::list;
176    
177        unsigned int shape0=shape[0];
178        unsigned int shape1=shape[1];
179        unsigned int shape2=shape[2];
180        unsigned int shape3=shape[3];
181    
182        list ll;
183        for (size_t l=0;l<shape0;++l)
184        {
185            list lk;
186        for (size_t k=0;k<shape1;++k)
187        {
188                list lj;
189                for (size_t j=0;j<shape2;++j)
190                {
191                    list li;
192                    for (size_t i=0;i<shape3;++i)
193                    {
194                        li.append(v[offset+DataTypes::getRelIndex(shape,l,k,j,i)]);
195                    }
196                    lj.append(tuple(li));
197                }
198                lk.append(tuple(lj));
199        }
200            ll.append(tuple(lk));
201        }
202        return tuple(ll);
203    }
204    
205    
206    // This should be safer once the DataC RO changes have been brought in
207    template <class ARR>
208    boost::python::tuple
209    pointToTuple( const DataTypes::ShapeType& shape,ARR v)
210    {
211       using namespace boost::python;
212       using boost::python::list;
213       int rank=shape.size();
214       if (rank==0)
215       {
216        return make_tuple(v[0]);
217       }
218       else if (rank==1)
219       {
220            return pointToTuple1(shape,v,0);
221       }
222       else if (rank==2)
223       {
224        return pointToTuple2(shape,v,0);
225       }
226       else if (rank==3)
227       {
228        return pointToTuple3(shape,v,0);
229       }
230       else if (rank==4)
231       {
232        return pointToTuple4(shape,v,0);
233       }
234       else
235         throw DataException("Unknown rank in pointToTuple.");
236    }
237    
238    }  // anonymous namespace
239    
240  Data::Data()  Data::Data()
241        : m_shared(false), m_lazy(false)
242  {  {
243    //    //
244    // Default data is type DataEmpty    // Default data is type DataEmpty
245    DataAbstract* temp=new DataEmpty();    DataAbstract* temp=new DataEmpty();
246    m_data=temp->getPtr();  //   m_data=temp->getPtr();
247      set_m_data(temp->getPtr());
248    m_protected=false;    m_protected=false;
249  }  }
250    
# Line 60  Data::Data(double value, Line 252  Data::Data(double value,
252             const tuple& shape,             const tuple& shape,
253             const FunctionSpace& what,             const FunctionSpace& what,
254             bool expanded)             bool expanded)
255        : m_shared(false), m_lazy(false)
256  {  {
257    DataTypes::ShapeType dataPointShape;    DataTypes::ShapeType dataPointShape;
258    for (int i = 0; i < shape.attr("__len__")(); ++i) {    for (int i = 0; i < shape.attr("__len__")(); ++i) {
# Line 76  Data::Data(double value, Line 269  Data::Data(double value,
269         const DataTypes::ShapeType& dataPointShape,         const DataTypes::ShapeType& dataPointShape,
270         const FunctionSpace& what,         const FunctionSpace& what,
271             bool expanded)             bool expanded)
272        : m_shared(false), m_lazy(false)
273  {  {
274    int len = DataTypes::noValues(dataPointShape);    int len = DataTypes::noValues(dataPointShape);
   
275    DataVector temp_data(len,value,len);    DataVector temp_data(len,value,len);
 //   DataArrayView temp_dataView(temp_data, dataPointShape);  
   
 //   initialise(temp_dataView, what, expanded);  
276    initialise(temp_data, dataPointShape, what, expanded);    initialise(temp_data, dataPointShape, what, expanded);
   
277    m_protected=false;    m_protected=false;
278  }  }
279    
280  Data::Data(const Data& inData)  Data::Data(const Data& inData)
281        : m_shared(false), m_lazy(false)
282  {  {
283    m_data=inData.m_data;    set_m_data(inData.m_data);
284    m_protected=inData.isProtected();    m_protected=inData.isProtected();
285  }  }
286    
287    
288  Data::Data(const Data& inData,  Data::Data(const Data& inData,
289             const DataTypes::RegionType& region)             const DataTypes::RegionType& region)
290        : m_shared(false), m_lazy(false)
291  {  {
292    DataAbstract_ptr dat=inData.m_data;    DataAbstract_ptr dat=inData.m_data;
293    if (inData.isLazy())    if (inData.isLazy())
# Line 110  Data::Data(const Data& inData, Line 301  Data::Data(const Data& inData,
301    //    //
302    // Create Data which is a slice of another Data    // Create Data which is a slice of another Data
303    DataAbstract* tmp = dat->getSlice(region);    DataAbstract* tmp = dat->getSlice(region);
304    m_data=DataAbstract_ptr(tmp);    set_m_data(DataAbstract_ptr(tmp));
305    m_protected=false;    m_protected=false;
306    
307  }  }
308    
309  Data::Data(const Data& inData,  Data::Data(const Data& inData,
310             const FunctionSpace& functionspace)             const FunctionSpace& functionspace)
311        : m_shared(false), m_lazy(false)
312  {  {
313    if (inData.isEmpty())    if (inData.isEmpty())
314    {    {
315      throw DataException("Error - will not interpolate for instances of DataEmpty.");      throw DataException("Error - will not interpolate for instances of DataEmpty.");
316    }    }
317    if (inData.getFunctionSpace()==functionspace) {    if (inData.getFunctionSpace()==functionspace) {
318      m_data=inData.m_data;      set_m_data(inData.m_data);
319    }    }
320    else    else
321    {    {
# Line 130  Data::Data(const Data& inData, Line 323  Data::Data(const Data& inData,
323      if (inData.isConstant()) {  // for a constant function, we just need to use the new function space      if (inData.isConstant()) {  // for a constant function, we just need to use the new function space
324        if (!inData.probeInterpolation(functionspace))        if (!inData.probeInterpolation(functionspace))
325        {           // Even though this is constant, we still need to check whether interpolation is allowed        {           // Even though this is constant, we still need to check whether interpolation is allowed
326      throw FunctionSpaceException("Call to probeInterpolation returned false for DataConstant.");      throw FunctionSpaceException("Cannot interpolate across to the domain of the specified FunctionSpace. (DataConstant)");
327        }        }
328        // if the data is not lazy, this will just be a cast to DataReady        // if the data is not lazy, this will just be a cast to DataReady
329        DataReady_ptr dr=inData.m_data->resolve();        DataReady_ptr dr=inData.m_data->resolve();
330        DataConstant* dc=new DataConstant(functionspace,inData.m_data->getShape(),dr->getVector());          DataConstant* dc=new DataConstant(functionspace,inData.m_data->getShape(),dr->getVectorRO());
331        m_data=DataAbstract_ptr(dc);  //       m_data=DataAbstract_ptr(dc);
332          set_m_data(DataAbstract_ptr(dc));
333      } else {      } else {
334        Data tmp(0,inData.getDataPointShape(),functionspace,true);        Data tmp(0,inData.getDataPointShape(),functionspace,true);
335        // Note: Must use a reference or pointer to a derived object        // Note: Must use a reference or pointer to a derived object
# Line 149  Data::Data(const Data& inData, Line 343  Data::Data(const Data& inData,
343        } else {        } else {
344          inDataDomain->interpolateACross(tmp,inData);          inDataDomain->interpolateACross(tmp,inData);
345        }        }
346        m_data=tmp.m_data;  //       m_data=tmp.m_data;
347          set_m_data(tmp.m_data);
348      }      }
349    }    }
350    m_protected=false;    m_protected=false;
351  }  }
352    
353  Data::Data(DataAbstract* underlyingdata)  Data::Data(DataAbstract* underlyingdata)
354        : m_shared(false), m_lazy(false)
355  {  {
356  //  m_data=shared_ptr<DataAbstract>(underlyingdata);      set_m_data(underlyingdata->getPtr());
     m_data=underlyingdata->getPtr();  
357      m_protected=false;      m_protected=false;
358  }  }
359    
360  Data::Data(DataAbstract_ptr underlyingdata)  Data::Data(DataAbstract_ptr underlyingdata)
361        : m_shared(false), m_lazy(false)
362  {  {
363      m_data=underlyingdata;      set_m_data(underlyingdata);
364      m_protected=false;      m_protected=false;
365  }  }
366    
   
 Data::Data(const numeric::array& value,  
        const FunctionSpace& what,  
            bool expanded)  
 {  
   initialise(value,what,expanded);  
   m_protected=false;  
 }  
 /*  
 Data::Data(const DataArrayView& value,  
        const FunctionSpace& what,  
            bool expanded)  
 {  
   initialise(value,what,expanded);  
   m_protected=false;  
 }*/  
   
367  Data::Data(const DataTypes::ValueType& value,  Data::Data(const DataTypes::ValueType& value,
368           const DataTypes::ShapeType& shape,           const DataTypes::ShapeType& shape,
369                   const FunctionSpace& what,                   const FunctionSpace& what,
370                   bool expanded)                   bool expanded)
371        : m_shared(false), m_lazy(false)
372  {  {
373     initialise(value,shape,what,expanded);     initialise(value,shape,what,expanded);
374     m_protected=false;     m_protected=false;
# Line 198  Data::Data(const DataTypes::ValueType& v Line 378  Data::Data(const DataTypes::ValueType& v
378  Data::Data(const object& value,  Data::Data(const object& value,
379         const FunctionSpace& what,         const FunctionSpace& what,
380             bool expanded)             bool expanded)
381        : m_shared(false), m_lazy(false)
382  {  {
383    numeric::array asNumArray(value);    WrappedArray w(value);
384    initialise(asNumArray,what,expanded);    initialise(w,what,expanded);
385    m_protected=false;    m_protected=false;
386  }  }
387    
388    
389  Data::Data(const object& value,  Data::Data(const object& value,
390             const Data& other)             const Data& other)
391        : m_shared(false), m_lazy(false)
392  {  {
393    numeric::array asNumArray(value);    WrappedArray w(value);
   
   // extract the shape of the numarray  
   DataTypes::ShapeType tempShape=DataTypes::shapeFromNumArray(asNumArray);  
 // /*  for (int i=0; i < asNumArray.getrank(); i++) {  
 //     tempShape.push_back(extract<int>(asNumArray.getshape()[i]));  
 //   }*/  
 //   // get the space for the data vector  
 //   int len = DataTypes::noValues(tempShape);  
 //   DataVector temp_data(len, 0.0, len);  
 // /*  DataArrayView temp_dataView(temp_data, tempShape);  
 //   temp_dataView.copy(asNumArray);*/  
 //   temp_data.copyFromNumArray(asNumArray);  
394    
395    //    // extract the shape of the array
396    // Create DataConstant using the given value and all other parameters    const DataTypes::ShapeType& tempShape=w.getShape();
397    // copied from other. If value is a rank 0 object this Data    if (w.getRank()==0) {
   // will assume the point data shape of other.  
   
   if (DataTypes::getRank(tempShape)/*temp_dataView.getRank()*/==0) {  
398    
399    
400      // get the space for the data vector      // get the space for the data vector
401      int len1 = DataTypes::noValues(tempShape);      int len1 = DataTypes::noValues(tempShape);
402      DataVector temp_data(len1, 0.0, len1);      DataVector temp_data(len1, 0.0, len1);
403      temp_data.copyFromNumArray(asNumArray);      temp_data.copyFromArray(w,1);
404    
405      int len = DataTypes::noValues(other.getDataPointShape());      int len = DataTypes::noValues(other.getDataPointShape());
406    
407      DataVector temp2_data(len, temp_data[0]/*temp_dataView()*/, len);      DataVector temp2_data(len, temp_data[0], len);
     //DataArrayView temp2_dataView(temp2_data, other.getPointDataView().getShape());  
 //     initialise(temp2_dataView, other.getFunctionSpace(), false);  
   
408      DataConstant* t=new DataConstant(other.getFunctionSpace(),other.getDataPointShape(),temp2_data);      DataConstant* t=new DataConstant(other.getFunctionSpace(),other.getDataPointShape(),temp2_data);
409  //     boost::shared_ptr<DataAbstract> sp(t);  //     m_data=DataAbstract_ptr(t);
410  //     m_data=sp;      set_m_data(DataAbstract_ptr(t));
     m_data=DataAbstract_ptr(t);  
411    
412    } else {    } else {
413      //      //
414      // Create a DataConstant with the same sample shape as other      // Create a DataConstant with the same sample shape as other
415  //     initialise(temp_dataView, other.getFunctionSpace(), false);      DataConstant* t=new DataConstant(w,other.getFunctionSpace());
416      DataConstant* t=new DataConstant(asNumArray,other.getFunctionSpace());  //     m_data=DataAbstract_ptr(t);
417  //     boost::shared_ptr<DataAbstract> sp(t);      set_m_data(DataAbstract_ptr(t));
 //     m_data=sp;  
     m_data=DataAbstract_ptr(t);  
418    }    }
419    m_protected=false;    m_protected=false;
420  }  }
421    
422  Data::~Data()  Data::~Data()
423  {  {
424      set_m_data(DataAbstract_ptr());
425  }  }
426    
427    
428    // only call in thread safe contexts.
429    // This method should be atomic
430    void Data::set_m_data(DataAbstract_ptr p)
431    {
432      if (m_data.get()!=0)  // release old ownership
433      {
434        m_data->removeOwner(this);
435      }
436      if (p.get()!=0)
437      {
438        m_data=p;
439        m_data->addOwner(this);
440        m_shared=m_data->isShared();
441        m_lazy=m_data->isLazy();
442      }
443    }
444    
445  void  void Data::initialise(const WrappedArray& value,
 Data::initialise(const boost::python::numeric::array& value,  
446                   const FunctionSpace& what,                   const FunctionSpace& what,
447                   bool expanded)                   bool expanded)
448  {  {
# Line 277  Data::initialise(const boost::python::nu Line 453  Data::initialise(const boost::python::nu
453    // within the shared_ptr constructor.    // within the shared_ptr constructor.
454    if (expanded) {    if (expanded) {
455      DataAbstract* temp=new DataExpanded(value, what);      DataAbstract* temp=new DataExpanded(value, what);
456  //     boost::shared_ptr<DataAbstract> temp_data(temp);  //     m_data=temp->getPtr();
457  //     m_data=temp_data;      set_m_data(temp->getPtr());
     m_data=temp->getPtr();  
458    } else {    } else {
459      DataAbstract* temp=new DataConstant(value, what);      DataAbstract* temp=new DataConstant(value, what);
460  //     boost::shared_ptr<DataAbstract> temp_data(temp);  //     m_data=temp->getPtr();
461  //     m_data=temp_data;      set_m_data(temp->getPtr());
     m_data=temp->getPtr();  
462    }    }
463  }  }
464    
# Line 302  Data::initialise(const DataTypes::ValueT Line 476  Data::initialise(const DataTypes::ValueT
476    // within the shared_ptr constructor.    // within the shared_ptr constructor.
477    if (expanded) {    if (expanded) {
478      DataAbstract* temp=new DataExpanded(what, shape, value);      DataAbstract* temp=new DataExpanded(what, shape, value);
479  //     boost::shared_ptr<DataAbstract> temp_data(temp);  //     m_data=temp->getPtr();
480  //     m_data=temp_data;      set_m_data(temp->getPtr());
     m_data=temp->getPtr();  
481    } else {    } else {
482      DataAbstract* temp=new DataConstant(what, shape, value);      DataAbstract* temp=new DataConstant(what, shape, value);
483  //     boost::shared_ptr<DataAbstract> temp_data(temp);  //     m_data=temp->getPtr();
484  //     m_data=temp_data;      set_m_data(temp->getPtr());
     m_data=temp->getPtr();  
485    }    }
486  }  }
487    
488    
 // void  
 // Data::CompareDebug(const Data& rd)  
 // {  
 //  using namespace std;  
 //  bool mismatch=false;  
 //  std::cout << "Comparing left and right" << endl;  
 //  const DataTagged* left=dynamic_cast<DataTagged*>(m_data.get());  
 //  const DataTagged* right=dynamic_cast<DataTagged*>(rd.m_data.get());  
 //    
 //  if (left==0)  
 //  {  
 //      cout << "left arg is not a DataTagged\n";  
 //      return;  
 //  }  
 //    
 //  if (right==0)  
 //  {  
 //      cout << "right arg is not a DataTagged\n";  
 //      return;  
 //  }  
 //  cout << "Num elements=" << left->getVector().size() << ":" << right->getVector().size() << std::endl;  
 //  cout << "Shapes ";  
 //  if (left->getShape()==right->getShape())  
 //  {  
 //      cout << "ok\n";  
 //  }  
 //  else  
 //  {  
 //      cout << "Problem: shapes do not match\n";  
 //      mismatch=true;  
 //  }  
 //  int lim=left->getVector().size();  
 //  if (right->getVector().size()) lim=right->getVector().size();  
 //  for (int i=0;i<lim;++i)  
 //  {  
 //      if (left->getVector()[i]!=right->getVector()[i])  
 //      {  
 //          cout << "[" << i << "] value mismatch " << left->getVector()[i] << ":" << right->getVector()[i] << endl;  
 //          mismatch=true;  
 //      }  
 //  }  
 //  
 //  // still need to check the tag map  
 //  // also need to watch what is happening to function spaces, are they copied or what?  
 //  
 //  const DataTagged::DataMapType& mapleft=left->getTagLookup();  
 //  const DataTagged::DataMapType& mapright=right->getTagLookup();  
 //  
 //  if (mapleft.size()!=mapright.size())  
 //  {  
 //      cout << "Maps are different sizes " << mapleft.size() << ":" << mapright.size() << endl;  
 //      mismatch=true;  
 //      cout << "Left map\n";  
 //      DataTagged::DataMapType::const_iterator i,j;  
 //      for (i=mapleft.begin();i!=mapleft.end();++i) {  
 //          cout << "(" << i->first << "=>" << i->second << ")\n";  
 //      }  
 //      cout << "Right map\n";  
 //      for (i=mapright.begin();i!=mapright.end();++i) {  
 //          cout << "(" << i->first << "=>" << i->second << ")\n";  
 //      }  
 //      cout << "End map\n";  
 //  
 //  }  
 //  
 //  DataTagged::DataMapType::const_iterator i,j;  
 //  for (i=mapleft.begin(),j=mapright.begin();i!=mapleft.end() && j!=mapright.end();++i,++j) {  
 //     if ((i->first!=j->first) || (i->second!=j->second))  
 //     {  
 //      cout << "(" << i->first << "=>" << i->second << ")";  
 //      cout << ":(" << j->first << "=>" << j->second << ") ";  
 //      mismatch=true;  
 //            }  
 //  }  
 //  if (mismatch)  
 //  {  
 //      cout << "#Mismatch\n";  
 //  }  
 // }  
   
489  escriptDataC  escriptDataC
490  Data::getDataC()  Data::getDataC()
491  {  {
# Line 410  Data::getDataC() const Line 502  Data::getDataC() const
502    return temp;    return temp;
503  }  }
504    
505    size_t
506    Data::getSampleBufferSize() const
507    {
508      return m_data->getSampleBufferSize();
509    }
510    
511    
512  const boost::python::tuple  const boost::python::tuple
513  Data::getShapeTuple() const  Data::getShapeTuple() const
514  {  {
# Line 435  Data::getShapeTuple() const Line 534  Data::getShapeTuple() const
534  // It can't work out what type the function is based soley on its name.  // It can't work out what type the function is based soley on its name.
535  // There are ways to fix this involving creating function pointer variables for each form  // There are ways to fix this involving creating function pointer variables for each form
536  // but there doesn't seem to be a need given that the methods have the same name from the python point of view  // but there doesn't seem to be a need given that the methods have the same name from the python point of view
537  Data*  Data
538  Data::copySelf()  Data::copySelf()
539  {  {
540     DataAbstract* temp=m_data->deepCopy();     DataAbstract* temp=m_data->deepCopy();
541     return new Data(temp);     return Data(temp);
542  }  }
543    
544  void  void
# Line 447  Data::copy(const Data& other) Line 546  Data::copy(const Data& other)
546  {  {
547    DataAbstract* temp=other.m_data->deepCopy();    DataAbstract* temp=other.m_data->deepCopy();
548    DataAbstract_ptr p=temp->getPtr();    DataAbstract_ptr p=temp->getPtr();
549    m_data=p;  //   m_data=p;
550      set_m_data(p);
551  }  }
552    
553    
554  Data  Data
555  Data::delay()  Data::delay()
556  {  {
557    DataLazy* dl=new DataLazy(m_data);    if (!isLazy())
558    return Data(dl);    {
559          DataLazy* dl=new DataLazy(m_data);
560          return Data(dl);
561      }
562      return *this;
563  }  }
564    
565  void  void
# Line 463  Data::delaySelf() Line 567  Data::delaySelf()
567  {  {
568    if (!isLazy())    if (!isLazy())
569    {    {
570      m_data=(new DataLazy(m_data))->getPtr();  //  m_data=(new DataLazy(m_data))->getPtr();
571        set_m_data((new DataLazy(m_data))->getPtr());
572    }    }
573  }  }
574    
575    
576    // For lazy data, it would seem that DataTagged will need to be treated differently since even after setting all tags
577    // to zero, all the tags from all the DataTags would be in the result.
578    // However since they all have the same value (0) whether they are there or not should not matter.
579    // So I have decided that for all types this method will create a constant 0.
580    // It can be promoted up as required.
581    // A possible efficiency concern might be expanded->constant->expanded which has an extra memory management
582    // but we can deal with that if it arises.
583    //
584  void  void
585  Data::setToZero()  Data::setToZero()
586  {  {
# Line 474  Data::setToZero() Line 588  Data::setToZero()
588    {    {
589       throw DataException("Error - Operations not permitted on instances of DataEmpty.");       throw DataException("Error - Operations not permitted on instances of DataEmpty.");
590    }    }
591    m_data->setToZero();    if (isLazy())
592      {
593         DataTypes::ValueType v(getNoValues(),0);
594         DataConstant* dc=new DataConstant(getFunctionSpace(),getDataPointShape(),v);
595         DataLazy* dl=new DataLazy(dc->getPtr());
596         set_m_data(dl->getPtr());
597      }
598      else
599      {
600         exclusiveWrite();
601         m_data->setToZero();
602      }
603  }  }
604    
605    
606  void  void
607  Data::copyWithMask(const Data& other,  Data::copyWithMask(const Data& other,
608                     const Data& mask)                     const Data& mask)
# Line 538  Data::copyWithMask(const Data& other, Line 664  Data::copyWithMask(const Data& other,
664    {    {
665      throw DataException("Error - Unknown DataAbstract passed to copyWithMask.");      throw DataException("Error - Unknown DataAbstract passed to copyWithMask.");
666    }    }
667      unsigned int selfrank=getDataPointRank();
668      unsigned int otherrank=other2.getDataPointRank();
669      unsigned int maskrank=mask2.getDataPointRank();
670      if ((selfrank==0) && (otherrank>0 || maskrank>0))
671      {
672        // to get here we must be copying from a large object into a scalar
673        // I am not allowing this.
674        // If you are calling copyWithMask then you are considering keeping some existing values
675        // and so I'm going to assume that you don't want your data objects getting a new shape.
676        throw DataException("Attempt to copyWithMask into a scalar from an object or mask with rank>0.");
677      }
678      exclusiveWrite();
679    // Now we iterate over the elements    // Now we iterate over the elements
680    DataVector& self=getReadyPtr()->getVector();    DataVector& self=getReady()->getVectorRW();;
681    const DataVector& ovec=other2.getReadyPtr()->getVector();    const DataVector& ovec=other2.getReadyPtr()->getVectorRO();
682    const DataVector& mvec=mask2.getReadyPtr()->getVector();    const DataVector& mvec=mask2.getReadyPtr()->getVectorRO();
683    if ((self.size()!=ovec.size()) || (self.size()!=mvec.size()))  
684      if ((selfrank>0) && (otherrank==0) &&(maskrank==0))
685    {    {
686      throw DataException("Error - size mismatch in arguments to copyWithMask.");      // Not allowing this combination.
687        // it is not clear what the rank of the target should be.
688        // Should it be filled with the scalar (rank stays the same);
689        // or should the target object be reshaped to be a scalar as well.
690        throw DataException("Attempt to copyWithMask from scalar mask and data into non-scalar target.");
691      }
692      if ((selfrank>0) && (otherrank>0) &&(maskrank==0))
693      {
694        if (mvec[0]>0)      // copy whole object if scalar is >0
695        {
696            copy(other);
697        }
698        return;
699      }
700      if (isTagged())       // so all objects involved will also be tagged
701      {
702        // note the !
703        if (!((getDataPointShape()==mask2.getDataPointShape()) &&
704            ((other2.getDataPointShape()==mask2.getDataPointShape()) || (otherrank==0))))
705        {
706            throw DataException("copyWithMask, shape mismatch.");
707        }
708    
709        // We need to consider the possibility that tags are missing or in the wrong order
710        // My guiding assumption here is: All tagged Datas are assumed to have the default value for
711        // all tags which are not explicitly defined
712    
713        const DataTagged* mptr=dynamic_cast<const DataTagged*>(mask2.m_data.get());
714        const DataTagged* optr=dynamic_cast<const DataTagged*>(other2.m_data.get());
715        DataTagged* tptr=dynamic_cast<DataTagged*>(m_data.get());
716    
717        // first, add any tags missing from other or mask
718        const DataTagged::DataMapType& olookup=optr->getTagLookup();
719            const DataTagged::DataMapType& mlookup=mptr->getTagLookup();
720        const DataTagged::DataMapType& tlookup=tptr->getTagLookup();
721        DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
722        for (i=olookup.begin();i!=olookup.end();i++)
723        {
724               tptr->addTag(i->first);
725            }
726            for (i=mlookup.begin();i!=mlookup.end();i++) {
727               tptr->addTag(i->first);
728            }
729        // now we know that *this has all the required tags but they aren't guaranteed to be in
730        // the same order
731    
732        // There are two possibilities: 1. all objects have the same rank. 2. other is a scalar
733        if ((selfrank==otherrank) && (otherrank==maskrank))
734        {
735            for (i=tlookup.begin();i!=tlookup.end();i++)
736            {
737                // get the target offset
738                DataTypes::ValueType::size_type toff=tptr->getOffsetForTag(i->first);
739                    DataTypes::ValueType::size_type moff=mptr->getOffsetForTag(i->first);
740                DataTypes::ValueType::size_type ooff=optr->getOffsetForTag(i->first);
741                for (int j=0;j<getDataPointSize();++j)
742                {
743                    if (mvec[j+moff]>0)
744                    {
745                        self[j+toff]=ovec[j+ooff];
746                    }
747                }
748                }
749            // now for the default value
750            for (int j=0;j<getDataPointSize();++j)
751            {
752                if (mvec[j+mptr->getDefaultOffset()]>0)
753                {
754                    self[j+tptr->getDefaultOffset()]=ovec[j+optr->getDefaultOffset()];
755                }
756            }
757        }
758        else    // other is a scalar
759        {
760            for (i=tlookup.begin();i!=tlookup.end();i++)
761            {
762                // get the target offset
763                DataTypes::ValueType::size_type toff=tptr->getOffsetForTag(i->first);
764                    DataTypes::ValueType::size_type moff=mptr->getOffsetForTag(i->first);
765                DataTypes::ValueType::size_type ooff=optr->getOffsetForTag(i->first);
766                for (int j=0;j<getDataPointSize();++j)
767                {
768                    if (mvec[j+moff]>0)
769                    {
770                        self[j+toff]=ovec[ooff];
771                    }
772                }
773                }
774            // now for the default value
775            for (int j=0;j<getDataPointSize();++j)
776            {
777                if (mvec[j+mptr->getDefaultOffset()]>0)
778                {
779                    self[j+tptr->getDefaultOffset()]=ovec[0];
780                }
781            }
782        }
783    
784        return;         // ugly
785      }
786      // mixed scalar and non-scalar operation
787      if ((selfrank>0) && (otherrank==0) && (mask2.getDataPointShape()==getDataPointShape()))
788      {
789            size_t num_points=self.size();
790        // OPENMP 3.0 allows unsigned loop vars.
791        #if defined(_OPENMP) && (_OPENMP < 200805)
792        long i;
793        #else
794        size_t i;
795        #endif  
796        size_t psize=getDataPointSize();    
797        #pragma omp parallel for private(i) schedule(static)
798        for (i=0;i<num_points;++i)
799        {
800            if (mvec[i]>0)
801            {
802                self[i]=ovec[i/psize];      // since this is expanded there is one scalar
803            }                   // dest point
804        }
805        return;         // ugly!
806      }
807      // tagged data is already taken care of so we only need to worry about shapes
808      // special cases with scalars are already dealt with so all we need to worry about is shape
809      if ((getDataPointShape()!=other2.getDataPointShape()) || getDataPointShape()!=mask2.getDataPointShape())
810      {
811        ostringstream oss;
812        oss <<"Error - size mismatch in arguments to copyWithMask.";
813        oss << "\nself_shape=" << DataTypes::shapeToString(getDataPointShape());
814        oss << " other2_shape=" << DataTypes::shapeToString(other2.getDataPointShape());
815        oss << " mask2_shape=" << DataTypes::shapeToString(mask2.getDataPointShape());
816        throw DataException(oss.str());
817    }    }
818    size_t num_points=self.size();    size_t num_points=self.size();
819    
# Line 564  Data::copyWithMask(const Data& other, Line 833  Data::copyWithMask(const Data& other,
833    }    }
834  }  }
835    
   
   
836  bool  bool
837  Data::isExpanded() const  Data::isExpanded() const
838  {  {
# Line 574  Data::isExpanded() const Line 841  Data::isExpanded() const
841  }  }
842    
843  bool  bool
844    Data::actsExpanded() const
845    {
846      return m_data->actsExpanded();
847    
848    }
849    
850    
851    bool
852  Data::isTagged() const  Data::isTagged() const
853  {  {
854    DataTagged* temp=dynamic_cast<DataTagged*>(m_data.get());    DataTagged* temp=dynamic_cast<DataTagged*>(m_data.get());
# Line 597  Data::isConstant() const Line 872  Data::isConstant() const
872  bool  bool
873  Data::isLazy() const  Data::isLazy() const
874  {  {
875    return m_data->isLazy();    return m_lazy;    // not asking m_data because we need to be able to ask this while m_data is changing
876  }  }
877    
878  // at the moment this is synonymous with !isLazy() but that could change  // at the moment this is synonymous with !isLazy() but that could change
# Line 628  Data::expand() Line 903  Data::expand()
903    if (isConstant()) {    if (isConstant()) {
904      DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());      DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());
905      DataAbstract* temp=new DataExpanded(*tempDataConst);      DataAbstract* temp=new DataExpanded(*tempDataConst);
906  //     shared_ptr<DataAbstract> temp_data(temp);  //     m_data=temp->getPtr();
907  //     m_data=temp_data;      set_m_data(temp->getPtr());
     m_data=temp->getPtr();  
908    } else if (isTagged()) {    } else if (isTagged()) {
909      DataTagged* tempDataTag=dynamic_cast<DataTagged*>(m_data.get());      DataTagged* tempDataTag=dynamic_cast<DataTagged*>(m_data.get());
910      DataAbstract* temp=new DataExpanded(*tempDataTag);      DataAbstract* temp=new DataExpanded(*tempDataTag);
911  //     shared_ptr<DataAbstract> temp_data(temp);  //     m_data=temp->getPtr();
912  //     m_data=temp_data;      set_m_data(temp->getPtr());
     m_data=temp->getPtr();  
913    } else if (isExpanded()) {    } else if (isExpanded()) {
914      //      //
915      // do nothing      // do nothing
# Line 656  Data::tag() Line 929  Data::tag()
929    if (isConstant()) {    if (isConstant()) {
930      DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());      DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());
931      DataAbstract* temp=new DataTagged(*tempDataConst);      DataAbstract* temp=new DataTagged(*tempDataConst);
932  //     shared_ptr<DataAbstract> temp_data(temp);  //     m_data=temp->getPtr();
933  //     m_data=temp_data;      set_m_data(temp->getPtr());
     m_data=temp->getPtr();  
934    } else if (isTagged()) {    } else if (isTagged()) {
935      // do nothing      // do nothing
936    } else if (isExpanded()) {    } else if (isExpanded()) {
# Line 671  Data::tag() Line 943  Data::tag()
943       {       {
944      throw DataException("Error - data would resolve to DataExpanded, tagging is not possible.");      throw DataException("Error - data would resolve to DataExpanded, tagging is not possible.");
945       }       }
946       m_data=res;      //      m_data=res;
947         set_m_data(res);
948       tag();       tag();
949    } else {    } else {
950      throw DataException("Error - Tagging not implemented for this Data type.");      throw DataException("Error - Tagging not implemented for this Data type.");
# Line 683  Data::resolve() Line 956  Data::resolve()
956  {  {
957    if (isLazy())    if (isLazy())
958    {    {
959       m_data=m_data->resolve();  //      m_data=m_data->resolve();
960        set_m_data(m_data->resolve());
961    }    }
962  }  }
963    
964    void
965    Data::requireWrite()
966    {
967      resolve();
968      exclusiveWrite();
969    }
970    
971  Data  Data
972  Data::oneOver() const  Data::oneOver() const
973  {  {
974    if (isLazy())    MAKELAZYOP(RECIP)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),RECIP);  
     return Data(c);  
   }  
975    return C_TensorUnaryOperation(*this, bind1st(divides<double>(),1.));    return C_TensorUnaryOperation(*this, bind1st(divides<double>(),1.));
976  }  }
977    
978  Data  Data
979  Data::wherePositive() const  Data::wherePositive() const
980  {  {
981    if (isLazy())    MAKELAZYOP(GZ)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),GZ);  
     return Data(c);  
   }  
982    return C_TensorUnaryOperation(*this, bind2nd(greater<double>(),0.0));    return C_TensorUnaryOperation(*this, bind2nd(greater<double>(),0.0));
983  }  }
984    
985  Data  Data
986  Data::whereNegative() const  Data::whereNegative() const
987  {  {
988    if (isLazy())    MAKELAZYOP(LZ)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),LZ);  
     return Data(c);  
   }  
989    return C_TensorUnaryOperation(*this, bind2nd(less<double>(),0.0));    return C_TensorUnaryOperation(*this, bind2nd(less<double>(),0.0));
990  }  }
991    
992  Data  Data
993  Data::whereNonNegative() const  Data::whereNonNegative() const
994  {  {
995    if (isLazy())    MAKELAZYOP(GEZ)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),GEZ);  
     return Data(c);  
   }  
996    return C_TensorUnaryOperation(*this, bind2nd(greater_equal<double>(),0.0));    return C_TensorUnaryOperation(*this, bind2nd(greater_equal<double>(),0.0));
997  }  }
998    
999  Data  Data
1000  Data::whereNonPositive() const  Data::whereNonPositive() const
1001  {  {
1002    if (isLazy())    MAKELAZYOP(LEZ)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),LEZ);  
     return Data(c);  
   }  
1003    return C_TensorUnaryOperation(*this, bind2nd(less_equal<double>(),0.0));    return C_TensorUnaryOperation(*this, bind2nd(less_equal<double>(),0.0));
1004  }  }
1005    
1006  Data  Data
1007  Data::whereZero(double tol) const  Data::whereZero(double tol) const
1008  {  {
1009    Data dataAbs=abs();  //   Data dataAbs=abs();
1010    return C_TensorUnaryOperation(dataAbs, bind2nd(less_equal<double>(),tol));  //   return C_TensorUnaryOperation(dataAbs, bind2nd(less_equal<double>(),tol));
1011       MAKELAZYOPOFF(EZ,tol)
1012       return C_TensorUnaryOperation(*this, bind2nd(AbsLTE(),tol));
1013    
1014  }  }
1015    
1016  Data  Data
1017  Data::whereNonZero(double tol) const  Data::whereNonZero(double tol) const
1018  {  {
1019    Data dataAbs=abs();  //   Data dataAbs=abs();
1020    return C_TensorUnaryOperation(dataAbs, bind2nd(greater<double>(),tol));  //   return C_TensorUnaryOperation(dataAbs, bind2nd(greater<double>(),tol));
1021      MAKELAZYOPOFF(NEZ,tol)
1022      return C_TensorUnaryOperation(*this, bind2nd(AbsGT(),tol));
1023    
1024  }  }
1025    
1026  Data  Data
# Line 767  bool Line 1033  bool
1033  Data::probeInterpolation(const FunctionSpace& functionspace) const  Data::probeInterpolation(const FunctionSpace& functionspace) const
1034  {  {
1035    return getFunctionSpace().probeInterpolation(functionspace);    return getFunctionSpace().probeInterpolation(functionspace);
 //   if (getFunctionSpace()==functionspace) {  
 //     return true;  
 //   } else {  
 //     const_Domain_ptr domain=getDomain();  
 //     if  (*domain==*functionspace.getDomain()) {  
 //       return domain->probeInterpolationOnDomain(getFunctionSpace().getTypeCode(),functionspace.getTypeCode());  
 //     } else {  
 //       return domain->probeInterpolationACross(getFunctionSpace().getTypeCode(),*(functionspace.getDomain()),functionspace.getTypeCode());  
 //     }  
 //   }  
1036  }  }
1037    
1038  Data  Data
# Line 813  Data::getDataPointSize() const Line 1069  Data::getDataPointSize() const
1069    return m_data->getNoValues();    return m_data->getNoValues();
1070  }  }
1071    
1072    
1073  DataTypes::ValueType::size_type  DataTypes::ValueType::size_type
1074  Data::getLength() const  Data::getLength() const
1075  {  {
1076    return m_data->getLength();    return m_data->getLength();
1077  }  }
1078    
 const  
 boost::python::numeric::array  
 Data:: getValueOfDataPoint(int dataPointNo)  
 {  
   int i, j, k, l;  
1079    
1080    FORCERESOLVE;  // There is no parallelism here ... elements need to be added in the correct order.
1081    //   If we could presize the list and then fill in the elements it might work
1082    //  //   This would need setting elements to be threadsafe.
1083    // determine the rank and shape of each data point  //   Having mulitple C threads calling into one interpreter is aparently a no-no.
1084    int dataPointRank = getDataPointRank();  const boost::python::object
1085    const DataTypes::ShapeType& dataPointShape = getDataPointShape();  Data::toListOfTuples(bool scalarastuple)
1086    {
1087    //      using namespace boost::python;
1088    // create the numeric array to be returned      using boost::python::list;
1089    boost::python::numeric::array numArray(0.0);      if (get_MPISize()>1)
1090        {
1091    //          throw DataException("::toListOfTuples is not available for MPI with more than one process.");
1092    // the shape of the returned numeric array will be the same      }
1093    // as that of the data point      unsigned int rank=getDataPointRank();
1094    int arrayRank = dataPointRank;      unsigned int size=getDataPointSize();
   const DataTypes::ShapeType& arrayShape = dataPointShape;  
1095    
1096    //      int npoints=getNumDataPoints();
1097    // resize the numeric array to the shape just calculated      expand();           // This will also resolve if required
1098    if (arrayRank==0) {      const DataTypes::ValueType& vec=getReady()->getVectorRO();
1099      numArray.resize(1);      boost::python::list temp;
1100    }      temp.append(object());
1101    if (arrayRank==1) {      boost::python::list res(temp*npoints);// presize the list by the "[None] * npoints"  trick
1102      numArray.resize(arrayShape[0]);      if (rank==0)
1103    }      {
1104    if (arrayRank==2) {          long count;
1105      numArray.resize(arrayShape[0],arrayShape[1]);          if (scalarastuple)
1106    }          {
1107    if (arrayRank==3) {              for (count=0;count<npoints;++count)
1108      numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2]);              {
1109    }          res[count]=make_tuple(vec[count]);
1110    if (arrayRank==4) {              }
1111      numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2],arrayShape[3]);          }
1112    }          else
1113            {
1114                for (count=0;count<npoints;++count)
1115                {
1116                    res[count]=vec[count];
1117                }
1118            }
1119        }
1120        else if (rank==1)
1121        {
1122            size_t count;
1123            size_t offset=0;
1124            for (count=0;count<npoints;++count,offset+=size)
1125            {
1126                res[count]=pointToTuple1(getDataPointShape(), vec, offset);
1127            }
1128        }
1129        else if (rank==2)
1130        {
1131            size_t count;
1132            size_t offset=0;
1133            for (count=0;count<npoints;++count,offset+=size)
1134            {
1135            res[count]=pointToTuple2(getDataPointShape(), vec, offset);
1136            }
1137        }
1138        else if (rank==3)
1139        {
1140            size_t count;
1141            size_t offset=0;
1142            for (count=0;count<npoints;++count,offset+=size)
1143            {
1144                res[count]=pointToTuple3(getDataPointShape(), vec, offset);
1145            }
1146        }
1147        else if (rank==4)
1148        {
1149            size_t count;
1150            size_t offset=0;
1151            for (count=0;count<npoints;++count,offset+=size)
1152            {
1153                res[count]=pointToTuple4(getDataPointShape(), vec, offset);
1154            }
1155        }
1156        else
1157        {
1158            throw DataException("Unknown rank in ::toListOfTuples()");
1159        }
1160        return res;
1161    }
1162    
1163    if (getNumDataPointsPerSample()>0) {  const boost::python::object
1164    Data::getValueOfDataPointAsTuple(int dataPointNo)
1165    {
1166       forceResolve();
1167       if (getNumDataPointsPerSample()>0) {
1168         int sampleNo = dataPointNo/getNumDataPointsPerSample();         int sampleNo = dataPointNo/getNumDataPointsPerSample();
1169         int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();         int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
1170         //         //
1171         // Check a valid sample number has been supplied         // Check a valid sample number has been supplied
1172         if ((sampleNo >= getNumSamples()) || (sampleNo < 0 )) {         if ((sampleNo >= getNumSamples()) || (sampleNo < 0 )) {
1173             throw DataException("Error - Data::convertToNumArray: invalid sampleNo.");             throw DataException("Error - Data::getValueOfDataPointAsTuple: invalid sampleNo.");
1174         }         }
1175    
1176         //         //
1177         // Check a valid data point number has been supplied         // Check a valid data point number has been supplied
1178         if ((dataPointNoInSample >= getNumDataPointsPerSample()) || (dataPointNoInSample < 0)) {         if ((dataPointNoInSample >= getNumDataPointsPerSample()) || (dataPointNoInSample < 0)) {
1179             throw DataException("Error - Data::convertToNumArray: invalid dataPointNoInSample.");             throw DataException("Error - Data::getValueOfDataPointAsTuple: invalid dataPointNoInSample.");
1180         }         }
1181         // TODO: global error handling         // TODO: global error handling
        // create a view of the data if it is stored locally  
 //       DataArrayView dataPointView = getDataPoint(sampleNo, dataPointNoInSample);  
1182         DataTypes::ValueType::size_type offset=getDataOffset(sampleNo, dataPointNoInSample);         DataTypes::ValueType::size_type offset=getDataOffset(sampleNo, dataPointNoInSample);
1183           return pointToTuple(getDataPointShape(),&(getDataAtOffsetRO(offset)));
1184      }
1185         switch( dataPointRank ){    else
1186              case 0 :    {
1187                  numArray[0] = getDataAtOffset(offset);      // The pre-numpy method would return an empty array of the given shape
1188                  break;      // I'm going to throw an exception because if we have zero points per sample we have problems
1189              case 1 :      throw DataException("Error - need at least 1 datapoint per sample.");
                 for( i=0; i<dataPointShape[0]; i++ )  
                     numArray[i]=getDataAtOffset(offset+DataTypes::getRelIndex(dataPointShape, i));  
                 break;  
             case 2 :  
                 for( i=0; i<dataPointShape[0]; i++ )  
                     for( j=0; j<dataPointShape[1]; j++)  
                         numArray[make_tuple(i,j)]=getDataAtOffset(offset+DataTypes::getRelIndex(dataPointShape, 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++)  
                             numArray[make_tuple(i,j,k)]=getDataAtOffset(offset+DataTypes::getRelIndex(dataPointShape, 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++)  
                                 numArray[make_tuple(i,j,k,l)]=getDataAtOffset(offset+DataTypes::getRelIndex(dataPointShape, i,j,k,l));  
                 break;  
     }  
1190    }    }
   //  
   // return the array  
   return numArray;  
1191    
1192  }  }
1193    
1194    
1195  void  void
1196  Data::setValueOfDataPointToPyObject(int dataPointNo, const boost::python::object& py_object)  Data::setValueOfDataPointToPyObject(int dataPointNo, const boost::python::object& py_object)
1197  {  {
1198      // this will throw if the value cannot be represented      // this will throw if the value cannot be represented
1199      boost::python::numeric::array num_array(py_object);      setValueOfDataPointToArray(dataPointNo,py_object);
     setValueOfDataPointToArray(dataPointNo,num_array);  
1200  }  }
1201    
1202  void  void
1203  Data::setValueOfDataPointToArray(int dataPointNo, const boost::python::numeric::array& num_array)  Data::setValueOfDataPointToArray(int dataPointNo, const boost::python::object& obj)
1204  {  {
1205    if (isProtected()) {    if (isProtected()) {
1206          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
1207    }    }
1208    FORCERESOLVE;  
1209      WrappedArray w(obj);
1210    //    //
1211    // check rank    // check rank
1212    if (static_cast<unsigned int>(num_array.getrank())<getDataPointRank())    if (static_cast<unsigned int>(w.getRank())<getDataPointRank())
1213        throw DataException("Rank of numarray does not match Data object rank");        throw DataException("Rank of array does not match Data object rank");
1214    
1215    //    //
1216    // check shape of num_array    // check shape of array
1217    for (unsigned int i=0; i<getDataPointRank(); i++) {    for (unsigned int i=0; i<getDataPointRank(); i++) {
1218      if (extract<int>(num_array.getshape()[i])!=getDataPointShape()[i])      if (w.getShape()[i]!=getDataPointShape()[i])
1219         throw DataException("Shape of numarray does not match Data object rank");         throw DataException("Shape of array does not match Data object rank");
1220    }    }
1221    
1222      exclusiveWrite();
1223    
1224    //    //
1225    // make sure data is expanded:    // make sure data is expanded:
1226    //    //
# Line 949  Data::setValueOfDataPointToArray(int dat Line 1230  Data::setValueOfDataPointToArray(int dat
1230    if (getNumDataPointsPerSample()>0) {    if (getNumDataPointsPerSample()>0) {
1231         int sampleNo = dataPointNo/getNumDataPointsPerSample();         int sampleNo = dataPointNo/getNumDataPointsPerSample();
1232         int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();         int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
1233         m_data->copyToDataPoint(sampleNo, dataPointNoInSample,num_array);         m_data->copyToDataPoint(sampleNo, dataPointNoInSample,w);
1234    } else {    } else {
1235         m_data->copyToDataPoint(-1, 0,num_array);         m_data->copyToDataPoint(-1, 0,w);
1236    }    }
1237  }  }
1238    
# Line 963  Data::setValueOfDataPoint(int dataPointN Line 1244  Data::setValueOfDataPoint(int dataPointN
1244    }    }
1245    //    //
1246    // make sure data is expanded:    // make sure data is expanded:
1247    FORCERESOLVE;    exclusiveWrite();
1248    if (!isExpanded()) {    if (!isExpanded()) {
1249      expand();      expand();
1250    }    }
# Line 977  Data::setValueOfDataPoint(int dataPointN Line 1258  Data::setValueOfDataPoint(int dataPointN
1258  }  }
1259    
1260  const  const
1261  boost::python::numeric::array  boost::python::object
1262  Data::getValueOfGlobalDataPoint(int procNo, int dataPointNo)  Data::getValueOfGlobalDataPointAsTuple(int procNo, int dataPointNo)
1263  {  {
1264    size_t length=0;    // This could be lazier than it is now
1265    int i, j, k, l, pos;    forceResolve();
   FORCERESOLVE;  
   //  
   // determine the rank and shape of each data point  
   int dataPointRank = getDataPointRank();  
   const DataTypes::ShapeType& dataPointShape = getDataPointShape();  
   
   //  
   // create the numeric array to be returned  
   boost::python::numeric::array numArray(0.0);  
1266    
1267    //    // copy datapoint into a buffer
1268    // the shape of the returned numeric array will be the same    // broadcast buffer to all nodes
1269    // as that of the data point    // convert buffer to tuple
1270    int arrayRank = dataPointRank;    // return tuple
   const DataTypes::ShapeType& arrayShape = dataPointShape;  
1271    
1272    //    const DataTypes::ShapeType& dataPointShape = getDataPointShape();
1273    // resize the numeric array to the shape just calculated    size_t length=DataTypes::noValues(dataPointShape);
   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]);  
   }  
1274    
1275    // added for the MPI communication    // added for the MPI communication
   length=1;  
   for( i=0; i<arrayRank; i++ ) length *= arrayShape[i];  
1276    double *tmpData = new double[length];    double *tmpData = new double[length];
1277    
1278    //    // updated for the MPI case
1279    // load the values for the data point into the numeric array.    if( get_MPIRank()==procNo ){
1280          if (getNumDataPointsPerSample()>0) {
1281      // updated for the MPI case      int sampleNo = dataPointNo/getNumDataPointsPerSample();
1282      if( get_MPIRank()==procNo ){      int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
1283               if (getNumDataPointsPerSample()>0) {      //
1284                  int sampleNo = dataPointNo/getNumDataPointsPerSample();      // Check a valid sample number has been supplied
1285                  int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();      if ((sampleNo >= getNumSamples()) || (sampleNo < 0 )) {
1286                  //          throw DataException("Error - Data::getValueOfGlobalDataPointAsTuple: invalid sampleNo.");
                 // Check a valid sample number has been supplied  
                 if ((sampleNo >= getNumSamples()) || (sampleNo < 0 )) {  
                   throw DataException("Error - Data::convertToNumArray: invalid sampleNo.");  
                 }  
   
                 //  
                 // Check a valid data point number has been supplied  
                 if ((dataPointNoInSample >= getNumDataPointsPerSample()) || (dataPointNoInSample < 0)) {  
                   throw DataException("Error - Data::convertToNumArray: invalid dataPointNoInSample.");  
                 }  
                 // TODO: global error handling  
         // create a view of the data if it is stored locally  
         //DataArrayView dataPointView = getDataPoint(sampleNo, dataPointNoInSample);  
         DataTypes::ValueType::size_type offset=getDataOffset(sampleNo, dataPointNoInSample);  
   
         // pack the data from the view into tmpData for MPI communication  
         pos=0;  
         switch( dataPointRank ){  
             case 0 :  
                 tmpData[0] = getDataAtOffset(offset);  
                 break;  
             case 1 :  
                 for( i=0; i<dataPointShape[0]; i++ )  
                     tmpData[i]=getDataAtOffset(offset+DataTypes::getRelIndex(dataPointShape, i));  
                 break;  
             case 2 :  
                 for( i=0; i<dataPointShape[0]; i++ )  
                     for( j=0; j<dataPointShape[1]; j++, pos++ )  
                         tmpData[pos]=getDataAtOffset(offset+DataTypes::getRelIndex(dataPointShape, 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]=getDataAtOffset(offset+DataTypes::getRelIndex(dataPointShape, 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]=getDataAtOffset(offset+DataTypes::getRelIndex(dataPointShape, i,j,k,l));  
                 break;  
         }  
             }  
1287      }      }
1288          #ifdef PASO_MPI  
1289          // broadcast the data to all other processes      //
1290      MPI_Bcast( tmpData, length, MPI_DOUBLE, procNo, get_MPIComm() );      // Check a valid data point number has been supplied
1291          #endif      if ((dataPointNoInSample >= getNumDataPointsPerSample()) || (dataPointNoInSample < 0)) {
1292            throw DataException("Error - Data::getValueOfGlobalDataPointAsTuple: invalid dataPointNoInSample.");
     // unpack the data  
     switch( dataPointRank ){  
         case 0 :  
             numArray[0]=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++ )  
                    numArray[make_tuple(i,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++ )  
                         numArray[make_tuple(i,j,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++ )  
                                 numArray[make_tuple(i,j,k,l)]=tmpData[i+dataPointShape[0]*(j*+dataPointShape[1]*(k+l*dataPointShape[2]))];  
             break;  
1293      }      }
1294        // TODO: global error handling
1295        DataTypes::ValueType::size_type offset=getDataOffset(sampleNo, dataPointNoInSample);
1296    
1297        memcpy(tmpData,&(getDataAtOffsetRO(offset)),length*sizeof(double));
1298         }
1299      }
1300    #ifdef PASO_MPI
1301      // broadcast the data to all other processes
1302      MPI_Bcast( tmpData, length, MPI_DOUBLE, procNo, get_MPIComm() );
1303    #endif
1304    
1305      delete [] tmpData;    boost::python::tuple t=pointToTuple(dataPointShape,tmpData);
1306      delete [] tmpData;
1307    //    //
1308    // return the loaded array    // return the loaded array
1309    return numArray;    return t;
1310    
1311  }  }
1312    
1313    
1314  boost::python::numeric::array  boost::python::object
1315  Data::integrate_const() const  Data::integrateToTuple_const() const
1316  {  {
1317    if (isLazy())    if (isLazy())
1318    {    {
# Line 1127  Data::integrate_const() const Line 1321  Data::integrate_const() const
1321    return integrateWorker();    return integrateWorker();
1322  }  }
1323    
1324  boost::python::numeric::array  boost::python::object
1325  Data::integrate()  Data::integrateToTuple()
1326  {  {
1327    if (isLazy())    if (isLazy())
1328    {    {
1329      expand();      expand();   // Can't do a non-resolving version of this without changing the domain object
1330    }    }         // see the dom->setToIntegrals call. Not saying it can't be done, just not doing it yet.
1331    return integrateWorker();    return integrateWorker();
 }  
   
1332    
1333    }
1334    
1335  boost::python::numeric::array  boost::python::object
1336  Data::integrateWorker() const  Data::integrateWorker() const
1337  {  {
   int index;  
   int rank = getDataPointRank();  
1338    DataTypes::ShapeType shape = getDataPointShape();    DataTypes::ShapeType shape = getDataPointShape();
1339    int dataPointSize = getDataPointSize();    int dataPointSize = getDataPointSize();
1340    
# Line 1151  Data::integrateWorker() const Line 1342  Data::integrateWorker() const
1342    // calculate the integral values    // calculate the integral values
1343    vector<double> integrals(dataPointSize);    vector<double> integrals(dataPointSize);
1344    vector<double> integrals_local(dataPointSize);    vector<double> integrals_local(dataPointSize);
1345      const AbstractContinuousDomain* dom=dynamic_cast<const AbstractContinuousDomain*>(getDomain().get());
1346      if (dom==0)
1347      {            
1348        throw DataException("Can not integrate over non-continuous domains.");
1349      }
1350  #ifdef PASO_MPI  #ifdef PASO_MPI
1351    AbstractContinuousDomain::asAbstractContinuousDomain(*getDomain()).setToIntegrals(integrals_local,*this);    dom->setToIntegrals(integrals_local,*this);
1352    // Global sum: use an array instead of a vector because elements of array are guaranteed to be contiguous in memory    // Global sum: use an array instead of a vector because elements of array are guaranteed to be contiguous in memory
1353    double *tmp = new double[dataPointSize];    double *tmp = new double[dataPointSize];
1354    double *tmp_local = new double[dataPointSize];    double *tmp_local = new double[dataPointSize];
1355    for (int i=0; i<dataPointSize; i++) { tmp_local[i] = integrals_local[i]; }    for (int i=0; i<dataPointSize; i++) { tmp_local[i] = integrals_local[i]; }
1356    MPI_Allreduce( &tmp_local[0], &tmp[0], dataPointSize, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD );    MPI_Allreduce( &tmp_local[0], &tmp[0], dataPointSize, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD );
1357    for (int i=0; i<dataPointSize; i++) { integrals[i] = tmp[i]; }    for (int i=0; i<dataPointSize; i++) { integrals[i] = tmp[i]; }
1358      tuple result=pointToTuple(shape,tmp);
1359    delete[] tmp;    delete[] tmp;
1360    delete[] tmp_local;    delete[] tmp_local;
1361  #else  #else
1362    AbstractContinuousDomain::asAbstractContinuousDomain(*getDomain()).setToIntegrals(integrals,*this);    dom->setToIntegrals(integrals,*this);
1363    /*  double *tmp = new double[dataPointSize];
1364      for (int i=0; i<dataPointSize; i++) { tmp[i]=integrals[i]; }*/
1365      tuple result=pointToTuple(shape,integrals);
1366    //   delete tmp;
1367  #endif  #endif
1368    
   //  
   // create the numeric array to be returned  
   // and load the array with the integral values  
   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];  
           }  
         }  
       }  
     }  
   }  
1369    
1370    //    return result;
   // return the loaded array  
   return bp_array;  
1371  }  }
1372    
1373  Data  Data
1374  Data::sin() const  Data::sin() const
1375  {  {
1376    if (isLazy())    MAKELAZYOP(SIN)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),SIN);  
     return Data(c);  
   }  
1377    return C_TensorUnaryOperation<double (*)(double)>(*this, ::sin);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::sin);
1378  }  }
1379    
1380  Data  Data
1381  Data::cos() const  Data::cos() const
1382  {  {
1383    if (isLazy())    MAKELAZYOP(COS)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),COS);  
     return Data(c);  
   }  
1384    return C_TensorUnaryOperation<double (*)(double)>(*this, ::cos);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::cos);
1385  }  }
1386    
1387  Data  Data
1388  Data::tan() const  Data::tan() const
1389  {  {
1390    if (isLazy())    MAKELAZYOP(TAN)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),TAN);  
     return Data(c);  
   }  
1391    return C_TensorUnaryOperation<double (*)(double)>(*this, ::tan);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::tan);
1392  }  }
1393    
1394  Data  Data
1395  Data::asin() const  Data::asin() const
1396  {  {
1397    if (isLazy())    MAKELAZYOP(ASIN)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),ASIN);  
     return Data(c);  
   }  
1398    return C_TensorUnaryOperation<double (*)(double)>(*this, ::asin);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::asin);
1399  }  }
1400    
1401  Data  Data
1402  Data::acos() const  Data::acos() const
1403  {  {
1404    if (isLazy())    MAKELAZYOP(ACOS)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),ACOS);  
     return Data(c);  
   }  
1405    return C_TensorUnaryOperation<double (*)(double)>(*this, ::acos);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::acos);
1406  }  }
1407    
# Line 1279  Data::acos() const Line 1409  Data::acos() const
1409  Data  Data
1410  Data::atan() const  Data::atan() const
1411  {  {
1412    if (isLazy())    MAKELAZYOP(ATAN)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),ATAN);  
     return Data(c);  
   }  
1413    return C_TensorUnaryOperation<double (*)(double)>(*this, ::atan);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::atan);
1414  }  }
1415    
1416  Data  Data
1417  Data::sinh() const  Data::sinh() const
1418  {  {
1419    if (isLazy())    MAKELAZYOP(SINH)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),SINH);  
     return Data(c);  
   }  
1420    return C_TensorUnaryOperation<double (*)(double)>(*this, ::sinh);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::sinh);
1421  }  }
1422    
1423  Data  Data
1424  Data::cosh() const  Data::cosh() const
1425  {  {
1426    if (isLazy())    MAKELAZYOP(COSH)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),COSH);  
     return Data(c);  
   }  
1427    return C_TensorUnaryOperation<double (*)(double)>(*this, ::cosh);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::cosh);
1428  }  }
1429    
1430  Data  Data
1431  Data::tanh() const  Data::tanh() const
1432  {  {
1433    if (isLazy())    MAKELAZYOP(TANH)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),TANH);  
     return Data(c);  
   }  
1434    return C_TensorUnaryOperation<double (*)(double)>(*this, ::tanh);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::tanh);
1435  }  }
1436    
# Line 1324  Data::tanh() const Line 1438  Data::tanh() const
1438  Data  Data
1439  Data::erf() const  Data::erf() const
1440  {  {
1441  #ifdef _WIN32  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1442    throw DataException("Error - Data:: erf function is not supported on _WIN32 platforms.");    throw DataException("Error - Data:: erf function is not supported on _WIN32 platforms.");
1443  #else  #else
1444    if (isLazy())    MAKELAZYOP(ERF)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),ERF);  
     return Data(c);  
   }  
1445    return C_TensorUnaryOperation(*this, ::erf);    return C_TensorUnaryOperation(*this, ::erf);
1446  #endif  #endif
1447  }  }
# Line 1339  Data::erf() const Line 1449  Data::erf() const
1449  Data  Data
1450  Data::asinh() const  Data::asinh() const
1451  {  {
1452    if (isLazy())    MAKELAZYOP(ASINH)
1453    {  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
     DataLazy* c=new DataLazy(borrowDataPtr(),ASINH);  
     return Data(c);  
   }  
 #ifdef _WIN32  
1454    return C_TensorUnaryOperation(*this, escript::asinh_substitute);    return C_TensorUnaryOperation(*this, escript::asinh_substitute);
1455  #else  #else
1456    return C_TensorUnaryOperation(*this, ::asinh);    return C_TensorUnaryOperation(*this, ::asinh);
# Line 1354  Data::asinh() const Line 1460  Data::asinh() const
1460  Data  Data
1461  Data::acosh() const  Data::acosh() const
1462  {  {
1463    if (isLazy())    MAKELAZYOP(ACOSH)
1464    {  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
     DataLazy* c=new DataLazy(borrowDataPtr(),ACOSH);  
     return Data(c);  
   }  
 #ifdef _WIN32  
1465    return C_TensorUnaryOperation(*this, escript::acosh_substitute);    return C_TensorUnaryOperation(*this, escript::acosh_substitute);
1466  #else  #else
1467    return C_TensorUnaryOperation(*this, ::acosh);    return C_TensorUnaryOperation(*this, ::acosh);
# Line 1369  Data::acosh() const Line 1471  Data::acosh() const
1471  Data  Data
1472  Data::atanh() const  Data::atanh() const
1473  {  {
1474    if (isLazy())    MAKELAZYOP(ATANH)
1475    {  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
     DataLazy* c=new DataLazy(borrowDataPtr(),ATANH);  
     return Data(c);  
   }  
 #ifdef _WIN32  
1476    return C_TensorUnaryOperation(*this, escript::atanh_substitute);    return C_TensorUnaryOperation(*this, escript::atanh_substitute);
1477  #else  #else
1478    return C_TensorUnaryOperation(*this, ::atanh);    return C_TensorUnaryOperation(*this, ::atanh);
# Line 1383  Data::atanh() const Line 1481  Data::atanh() const
1481    
1482  Data  Data
1483  Data::log10() const  Data::log10() const
1484  {  if (isLazy())  {
1485    {    MAKELAZYOP(LOG10)
     DataLazy* c=new DataLazy(borrowDataPtr(),LOG10);  
     return Data(c);  
   }  
1486    return C_TensorUnaryOperation<double (*)(double)>(*this, ::log10);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::log10);
1487  }  }
1488    
1489  Data  Data
1490  Data::log() const  Data::log() const
1491  {  {
1492    if (isLazy())    MAKELAZYOP(LOG)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),LOG);  
     return Data(c);  
   }  
1493    return C_TensorUnaryOperation<double (*)(double)>(*this, ::log);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::log);
1494  }  }
1495    
1496  Data  Data
1497  Data::sign() const  Data::sign() const
1498  {  {
1499    if (isLazy())    MAKELAZYOP(SIGN)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),SIGN);  
     return Data(c);  
   }  
1500    return C_TensorUnaryOperation(*this, escript::fsign);    return C_TensorUnaryOperation(*this, escript::fsign);
1501  }  }
1502    
1503  Data  Data
1504  Data::abs() const  Data::abs() const
1505  {  {
1506    if (isLazy())    MAKELAZYOP(ABS)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),ABS);  
     return Data(c);  
   }  
1507    return C_TensorUnaryOperation<double (*)(double)>(*this, ::fabs);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::fabs);
1508  }  }
1509    
1510  Data  Data
1511  Data::neg() const  Data::neg() const
1512  {  {
1513    if (isLazy())    MAKELAZYOP(NEG)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),NEG);  
     return Data(c);  
   }  
1514    return C_TensorUnaryOperation(*this, negate<double>());    return C_TensorUnaryOperation(*this, negate<double>());
1515  }  }
1516    
# Line 1448  Data::pos() const Line 1527  Data::pos() const
1527    
1528  Data  Data
1529  Data::exp() const  Data::exp() const
1530  {    {
1531    if (isLazy())    MAKELAZYOP(EXP)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),EXP);  
     return Data(c);  
   }  
1532    return C_TensorUnaryOperation<double (*)(double)>(*this, ::exp);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::exp);
1533  }  }
1534    
1535  Data  Data
1536  Data::sqrt() const  Data::sqrt() const
1537  {  {
1538    if (isLazy())    MAKELAZYOP(SQRT)
   {  
     DataLazy* c=new DataLazy(borrowDataPtr(),SQRT);  
     return Data(c);  
   }  
1539    return C_TensorUnaryOperation<double (*)(double)>(*this, ::sqrt);    return C_TensorUnaryOperation<double (*)(double)>(*this, ::sqrt);
1540  }  }
1541    
# Line 1483  Data::Lsup() Line 1554  Data::Lsup()
1554  {  {
1555     if (isLazy())     if (isLazy())
1556     {     {
1557      expand();      if (!actsExpanded() || CHECK_DO_CRES)
1558        {
1559            resolve();
1560        }
1561        else
1562        {
1563    #ifdef PASO_MPI
1564            return lazyAlgWorker<AbsMax>(0,MPI_MAX);
1565    #else
1566            return lazyAlgWorker<AbsMax>(0,0);
1567    #endif
1568        }
1569     }     }
1570     return LsupWorker();     return LsupWorker();
1571  }  }
# Line 1503  Data::sup() Line 1585  Data::sup()
1585  {  {
1586     if (isLazy())     if (isLazy())
1587     {     {
1588      expand();      if (!actsExpanded() || CHECK_DO_CRES)
1589        {
1590            resolve();
1591        }
1592        else
1593        {
1594    #ifdef PASO_MPI
1595            return lazyAlgWorker<FMax>(numeric_limits<double>::max()*-1, MPI_MAX);
1596    #else
1597            return lazyAlgWorker<FMax>(numeric_limits<double>::max()*-1, 0);
1598    #endif
1599        }
1600     }     }
1601     return supWorker();     return supWorker();
1602  }  }
# Line 1523  Data::inf() Line 1616  Data::inf()
1616  {  {
1617     if (isLazy())     if (isLazy())
1618     {     {
1619      expand();      if (!actsExpanded() || CHECK_DO_CRES)
1620        {
1621            resolve();
1622        }
1623        else
1624        {
1625    #ifdef PASO_MPI
1626            return lazyAlgWorker<FMin>(numeric_limits<double>::max(), MPI_MIN);
1627    #else
1628            return lazyAlgWorker<FMin>(numeric_limits<double>::max(), 0);
1629    #endif
1630        }
1631     }     }
1632     return infWorker();     return infWorker();
1633  }  }
1634    
1635    template <class BinaryOp>
1636    double
1637    Data::lazyAlgWorker(double init, int mpiop_type)
1638    {
1639       if (!isLazy() || !m_data->actsExpanded())
1640       {
1641        throw DataException("Error - lazyAlgWorker can only be called on lazy(expanded) data.");
1642       }
1643       DataLazy* dl=dynamic_cast<DataLazy*>(m_data.get());
1644       EsysAssert((dl!=0), "Programming error - casting to DataLazy.");
1645       BufferGroup* bg=allocSampleBuffer();
1646       double val=init;
1647       int i=0;
1648       const size_t numsamples=getNumSamples();
1649       const size_t samplesize=getNoValues()*getNumDataPointsPerSample();
1650       BinaryOp operation;
1651       #pragma omp parallel private(i)
1652       {
1653        double localtot=init;
1654        #pragma omp for schedule(static) private(i)
1655        for (i=0;i<numsamples;++i)
1656        {
1657            size_t roffset=0;
1658            const DataTypes::ValueType* v=dl->resolveSample(*bg, i, roffset);
1659            // Now we have the sample, run operation on all points
1660            for (size_t j=0;j<samplesize;++j)
1661            {
1662            localtot=operation(localtot,(*v)[j+roffset]);
1663            }
1664        }
1665        #pragma omp critical
1666        val=operation(val,localtot);
1667       }
1668       freeSampleBuffer(bg);
1669    #ifdef PASO_MPI
1670       double globalValue;
1671       MPI_Allreduce( &val, &globalValue, 1, MPI_DOUBLE, mpiop_type, MPI_COMM_WORLD );
1672       return globalValue;
1673    #else
1674       return val;
1675    #endif
1676    }
1677    
1678  double  double
1679  Data::LsupWorker() const  Data::LsupWorker() const
1680  {  {
# Line 1585  Data::infWorker() const Line 1732  Data::infWorker() const
1732  Data  Data
1733  Data::maxval() const  Data::maxval() const
1734  {  {
1735    if (isLazy())     MAKELAZYOP(MAXVAL)
   {  
     Data temp(*this);   // to get around the fact that you can't resolve a const Data  
     temp.resolve();  
     return temp.maxval();  
   }  
1736    //    //
1737    // set the initial maximum value to min possible double    // set the initial maximum value to min possible double
1738    FMax fmax_func;    FMax fmax_func;
# Line 1600  Data::maxval() const Line 1742  Data::maxval() const
1742  Data  Data
1743  Data::minval() const  Data::minval() const
1744  {  {
1745    if (isLazy())    MAKELAZYOP(MINVAL)
   {  
     Data temp(*this);   // to get around the fact that you can't resolve a const Data  
     temp.resolve();  
     return temp.minval();  
   }  
1746    //    //
1747    // set the initial minimum value to max possible double    // set the initial minimum value to max possible double
1748    FMin fmin_func;    FMin fmin_func;
# Line 1633  Data::swapaxes(const int axis0, const in Line 1770  Data::swapaxes(const int axis0, const in
1770       if (axis0 == axis1) {       if (axis0 == axis1) {
1771           throw DataException("Error - Data::swapaxes: axis indices must be different.");           throw DataException("Error - Data::swapaxes: axis indices must be different.");
1772       }       }
1773       if (axis0 > axis1) {       MAKELAZYOP2(SWAP,axis0,axis1)
1774           axis0_tmp=axis1;       if (axis0 > axis1)
1775           axis1_tmp=axis0;       {
1776       } else {      axis0_tmp=axis1;
1777           axis0_tmp=axis0;      axis1_tmp=axis0;
          axis1_tmp=axis1;  
1778       }       }
1779       for (int i=0; i<rank; i++) {       else
1780         if (i == axis0_tmp) {       {
1781            ev_shape.push_back(s[axis1_tmp]);      axis0_tmp=axis0;
1782         } else if (i == axis1_tmp) {      axis1_tmp=axis1;
1783            ev_shape.push_back(s[axis0_tmp]);       }
1784         } else {       for (int i=0; i<rank; i++)
1785            ev_shape.push_back(s[i]);       {
1786         }      if (i == axis0_tmp)
1787        {
1788            ev_shape.push_back(s[axis1_tmp]);
1789        }
1790        else if (i == axis1_tmp)
1791        {
1792            ev_shape.push_back(s[axis0_tmp]);
1793        }
1794        else
1795        {
1796            ev_shape.push_back(s[i]);
1797        }
1798       }       }
1799       Data ev(0.,ev_shape,getFunctionSpace());       Data ev(0.,ev_shape,getFunctionSpace());
1800       ev.typeMatchRight(*this);       ev.typeMatchRight(*this);
1801       m_data->swapaxes(ev.m_data.get(), axis0_tmp, axis1_tmp);       m_data->swapaxes(ev.m_data.get(), axis0_tmp, axis1_tmp);
1802       return ev;       return ev;
   
1803  }  }
1804    
1805  Data  Data
# Line 1672  Data::symmetric() const Line 1818  Data::symmetric() const
1818       else {       else {
1819          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.");
1820       }       }
1821       if (isLazy())       MAKELAZYOP(SYM)
      {  
     DataLazy* c=new DataLazy(borrowDataPtr(),SYM);  
     return Data(c);  
      }  
1822       Data ev(0.,getDataPointShape(),getFunctionSpace());       Data ev(0.,getDataPointShape(),getFunctionSpace());
1823       ev.typeMatchRight(*this);       ev.typeMatchRight(*this);
1824       m_data->symmetric(ev.m_data.get());       m_data->symmetric(ev.m_data.get());
# Line 1686  Data::symmetric() const Line 1828  Data::symmetric() const
1828  Data  Data
1829  Data::nonsymmetric() const  Data::nonsymmetric() const
1830  {  {
1831       if (isLazy())       MAKELAZYOP(NSYM)
      {  
     DataLazy* c=new DataLazy(borrowDataPtr(),NSYM);  
     return Data(c);  
      }  
1832       // check input       // check input
1833       DataTypes::ShapeType s=getDataPointShape();       DataTypes::ShapeType s=getDataPointShape();
1834       if (getDataPointRank()==2) {       if (getDataPointRank()==2) {
# Line 1722  Data::nonsymmetric() const Line 1860  Data::nonsymmetric() const
1860       }       }
1861  }  }
1862    
   
 // Doing a lazy version of this would require some thought.  
 // First it needs a parameter (which DataLazy doesn't support at the moment).  
 // (secondly although it does not apply to trace) we can't handle operations which return  
 // multiple results (like eigenvectors_values) or return values of different shapes to their input  
 // (like eigenvalues).  
1863  Data  Data
1864  Data::trace(int axis_offset) const  Data::trace(int axis_offset) const
1865  {  {    
1866       if (isLazy())       MAKELAZYOPOFF(TRACE,axis_offset)
1867         if ((axis_offset<0) || (axis_offset>getDataPointRank()))
1868       {       {
1869      Data temp(*this);   // to get around the fact that you can't resolve a const Data      throw DataException("Error - Data::trace, axis_offset must be between 0 and rank-2 inclusive.");
     temp.resolve();  
     return temp.trace(axis_offset);  
1870       }       }
1871       DataTypes::ShapeType s=getDataPointShape();       DataTypes::ShapeType s=getDataPointShape();
1872       if (getDataPointRank()==2) {       if (getDataPointRank()==2) {
# Line 1787  Data::trace(int axis_offset) const Line 1918  Data::trace(int axis_offset) const
1918  Data  Data
1919  Data::transpose(int axis_offset) const  Data::transpose(int axis_offset) const
1920  {      {    
1921       if (isLazy())       MAKELAZYOPOFF(TRANS,axis_offset)
      {  
     Data temp(*this);   // to get around the fact that you can't resolve a const Data  
     temp.resolve();  
     return temp.transpose(axis_offset);  
      }  
1922       DataTypes::ShapeType s=getDataPointShape();       DataTypes::ShapeType s=getDataPointShape();
1923       DataTypes::ShapeType ev_shape;       DataTypes::ShapeType ev_shape;
1924       // 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]
# Line 1802  Data::transpose(int axis_offset) const Line 1928  Data::transpose(int axis_offset) const
1928          throw DataException("Error - Data::transpose must have 0 <= axis_offset <= rank=" + rank);          throw DataException("Error - Data::transpose must have 0 <= axis_offset <= rank=" + rank);
1929       }       }
1930       for (int i=0; i<rank; i++) {       for (int i=0; i<rank; i++) {
1931    
1932         int index = (axis_offset+i)%rank;         int index = (axis_offset+i)%rank;
1933         ev_shape.push_back(s[index]); // Append to new shape         ev_shape.push_back(s[index]); // Append to new shape
1934       }       }
# Line 1894  Data::calc_minGlobalDataPoint(int& ProcN Line 2021  Data::calc_minGlobalDataPoint(int& ProcN
2021    double next,local_min;    double next,local_min;
2022    int local_lowi=0,local_lowj=0;        int local_lowi=0,local_lowj=0;    
2023    
2024    #pragma omp parallel private(next,local_min,local_lowi,local_lowj)    #pragma omp parallel firstprivate(local_lowi,local_lowj) private(next,local_min)
2025    {    {
2026      local_min=min;      local_min=min;
2027      #pragma omp for private(i,j) schedule(static)      #pragma omp for private(i,j) schedule(static)
2028      for (i=0; i<numSamples; i++) {      for (i=0; i<numSamples; i++) {
2029        for (j=0; j<numDPPSample; j++) {        for (j=0; j<numDPPSample; j++) {
2030          next=temp.getDataAtOffset(temp.getDataOffset(i,j));          next=temp.getDataAtOffsetRO(temp.getDataOffset(i,j));
2031          if (next<local_min) {          if (next<local_min) {
2032            local_min=next;            local_min=next;
2033            local_lowi=i;            local_lowi=i;
# Line 1909  Data::calc_minGlobalDataPoint(int& ProcN Line 2036  Data::calc_minGlobalDataPoint(int& ProcN
2036        }        }
2037      }      }
2038      #pragma omp critical      #pragma omp critical
2039      if (local_min<min) {      if (local_min<min) {    // If we found a smaller value than our sentinel
2040        min=local_min;        min=local_min;
2041        lowi=local_lowi;        lowi=local_lowi;
2042        lowj=local_lowj;        lowj=local_lowj;
# Line 1917  Data::calc_minGlobalDataPoint(int& ProcN Line 2044  Data::calc_minGlobalDataPoint(int& ProcN
2044    }    }
2045    
2046  #ifdef PASO_MPI  #ifdef PASO_MPI
2047      // determine the processor on which the minimum occurs    // determine the processor on which the minimum occurs
2048      next = temp.getDataPoint(lowi,lowj);    next = temp.getDataPointRO(lowi,lowj);
2049      int lowProc = 0;    int lowProc = 0;
2050      double *globalMins = new double[get_MPISize()+1];    double *globalMins = new double[get_MPISize()+1];
2051      int error = MPI_Gather ( &next, 1, MPI_DOUBLE, globalMins, 1, MPI_DOUBLE, 0, get_MPIComm() );    int error;
2052      error = MPI_Gather ( &next, 1, MPI_DOUBLE, globalMins, 1, MPI_DOUBLE, 0, get_MPIComm() );
2053      if( get_MPIRank()==0 ){  
2054          next = globalMins[lowProc];    if( get_MPIRank()==0 ){
2055          for( i=1; i<get_MPISize(); i++ )      next = globalMins[lowProc];
2056              if( next>globalMins[i] ){      for( i=1; i<get_MPISize(); i++ )
2057                  lowProc = i;          if( next>globalMins[i] ){
2058                  next = globalMins[i];              lowProc = i;
2059              }              next = globalMins[i];
2060            }
2061      }
2062      MPI_Bcast( &lowProc, 1, MPI_INT, 0, get_MPIComm() );
2063      DataPointNo = lowj + lowi * numDPPSample;
2064      MPI_Bcast(&DataPointNo, 1, MPI_INT, lowProc, get_MPIComm() );
2065      delete [] globalMins;
2066      ProcNo = lowProc;
2067    #else
2068      ProcNo = 0;
2069      DataPointNo = lowj + lowi * numDPPSample;
2070    #endif
2071    }
2072    
2073    
2074    const boost::python::tuple
2075    Data::maxGlobalDataPoint() const
2076    {
2077      int DataPointNo;
2078      int ProcNo;
2079      calc_maxGlobalDataPoint(ProcNo,DataPointNo);
2080      return make_tuple(ProcNo,DataPointNo);
2081    }
2082    
2083    void
2084    Data::calc_maxGlobalDataPoint(int& ProcNo,
2085                            int& DataPointNo) const
2086    {
2087      if (isLazy())
2088      {
2089        Data temp(*this);   // to get around the fact that you can't resolve a const Data
2090        temp.resolve();
2091        return temp.calc_maxGlobalDataPoint(ProcNo,DataPointNo);
2092      }
2093      int i,j;
2094      int highi=0,highj=0;
2095    //-------------
2096      double max= -numeric_limits<double>::max();
2097    
2098      Data temp=maxval();
2099    
2100      int numSamples=temp.getNumSamples();
2101      int numDPPSample=temp.getNumDataPointsPerSample();
2102    
2103      double next,local_max;
2104      int local_highi=0,local_highj=0;  
2105    
2106      #pragma omp parallel firstprivate(local_highi,local_highj) private(next,local_max)
2107      {
2108        local_max=max;
2109        #pragma omp for private(i,j) schedule(static)
2110        for (i=0; i<numSamples; i++) {
2111          for (j=0; j<numDPPSample; j++) {
2112            next=temp.getDataAtOffsetRO(temp.getDataOffset(i,j));
2113            if (next>local_max) {
2114              local_max=next;
2115              local_highi=i;
2116              local_highj=j;
2117            }
2118          }
2119        }
2120        #pragma omp critical
2121        if (local_max>max) {    // If we found a larger value than our sentinel
2122          max=local_max;
2123          highi=local_highi;
2124          highj=local_highj;
2125        }
2126      }
2127    #ifdef PASO_MPI
2128      // determine the processor on which the maximum occurs
2129      next = temp.getDataPointRO(highi,highj);
2130      int highProc = 0;
2131      double *globalMaxs = new double[get_MPISize()+1];
2132      int error;
2133      error = MPI_Gather ( &next, 1, MPI_DOUBLE, globalMaxs, 1, MPI_DOUBLE, 0, get_MPIComm() );
2134      if( get_MPIRank()==0 ){
2135        next = globalMaxs[highProc];
2136        for( i=1; i<get_MPISize(); i++ )
2137        {
2138        if( next<globalMaxs[i] )
2139        {
2140            highProc = i;
2141            next = globalMaxs[i];
2142      }      }
2143      MPI_Bcast( &lowProc, 1, MPI_DOUBLE, 0, get_MPIComm() );      }
2144      }
2145      MPI_Bcast( &highProc, 1, MPI_INT, 0, get_MPIComm() );
2146      DataPointNo = highj + highi * numDPPSample;  
2147      MPI_Bcast(&DataPointNo, 1, MPI_INT, highProc, get_MPIComm() );
2148    
2149      delete [] globalMins;    delete [] globalMaxs;
2150      ProcNo = lowProc;    ProcNo = highProc;
2151  #else  #else
2152      ProcNo = 0;    ProcNo = 0;
2153      DataPointNo = highj + highi * numDPPSample;
2154  #endif  #endif
   DataPointNo = lowj + lowi * numDPPSample;  
2155  }  }
2156    
2157  void  void
# Line 1977  Data::saveVTK(std::string fileName) cons Line 2190  Data::saveVTK(std::string fileName) cons
2190    }    }
2191    boost::python::dict args;    boost::python::dict args;
2192    args["data"]=boost::python::object(this);    args["data"]=boost::python::object(this);
2193    getDomain()->saveVTK(fileName,args);    getDomain()->saveVTK(fileName,args,"","");
2194    return;    return;
2195  }  }
2196    
2197    
2198    
2199  Data&  Data&
2200  Data::operator+=(const Data& right)  Data::operator+=(const Data& right)
2201  {  {
2202    if (isProtected()) {    if (isProtected()) {
2203          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2204    }    }
2205    if (isLazy() || right.isLazy())    MAKELAZYBINSELF(right,ADD)    // for lazy + is equivalent to +=
2206    {    exclusiveWrite();         // Since Lazy data does not modify its leaves we only need to worry here
2207      DataLazy* c=new DataLazy(m_data,right.borrowDataPtr(),ADD); // for lazy + is equivalent to +=    binaryOp(right,plus<double>());
2208          m_data=c->getPtr();    return (*this);
     return (*this);  
   }  
   else  
   {  
     binaryOp(right,plus<double>());  
     return (*this);  
   }  
2209  }  }
2210    
2211  Data&  Data&
# Line 2007  Data::operator+=(const boost::python::ob Line 2215  Data::operator+=(const boost::python::ob
2215          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2216    }    }
2217    Data tmp(right,getFunctionSpace(),false);    Data tmp(right,getFunctionSpace(),false);
2218    if (isLazy())    (*this)+=tmp;
2219    {    return *this;
     DataLazy* c=new DataLazy(m_data,tmp.borrowDataPtr(),ADD);   // for lazy + is equivalent to +=  
         m_data=c->getPtr();  
     return (*this);  
   }  
   else  
   {  
     binaryOp(tmp,plus<double>());  
     return (*this);  
   }  
2220  }  }
2221    
2222  // Hmmm, operator= makes a deep copy but the copy constructor does not?  // Hmmm, operator= makes a deep copy but the copy constructor does not?
2223  Data&  Data&
2224  Data::operator=(const Data& other)  Data::operator=(const Data& other)
2225  {  {
2226    copy(other);    m_protected=false;        // since any changes should be caught by exclusiveWrite();
2227    //   m_data=other.m_data;
2228      set_m_data(other.m_data);
2229    return (*this);    return (*this);
2230  }  }
2231    
# Line 2034  Data::operator-=(const Data& right) Line 2235  Data::operator-=(const Data& right)
2235    if (isProtected()) {    if (isProtected()) {
2236          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2237    }    }
2238    if (isLazy() || right.isLazy())    MAKELAZYBINSELF(right,SUB)
2239    {    exclusiveWrite();
2240      DataLazy* c=new DataLazy(m_data,right.borrowDataPtr(),SUB); // for lazy - is equivalent to -=    binaryOp(right,minus<double>());
2241          m_data=c->getPtr();    return (*this);
     return (*this);  
   }  
   else  
   {  
     binaryOp(right,minus<double>());  
     return (*this);  
   }  
2242  }  }
2243    
2244  Data&  Data&
# Line 2054  Data::operator-=(const boost::python::ob Line 2248  Data::operator-=(const boost::python::ob
2248          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2249    }    }
2250    Data tmp(right,getFunctionSpace(),false);    Data tmp(right,getFunctionSpace(),false);
2251    if (isLazy())    (*this)-=tmp;
2252    {    return (*this);
     DataLazy* c=new DataLazy(m_data,tmp.borrowDataPtr(),SUB);   // for lazy - is equivalent to -=  
         m_data=c->getPtr();  
     return (*this);  
   }  
   else  
   {  
     binaryOp(tmp,minus<double>());  
     return (*this);  
   }  
2253  }  }
2254    
2255  Data&  Data&
# Line 2073  Data::operator*=(const Data& right) Line 2258  Data::operator*=(const Data& right)
2258    if (isProtected()) {    if (isProtected()) {
2259          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2260    }    }
2261    if (isLazy() || right.isLazy())    MAKELAZYBINSELF(right,MUL)
2262    {    exclusiveWrite();
2263      DataLazy* c=new DataLazy(m_data,right.borrowDataPtr(),MUL); // for lazy * is equivalent to *=    binaryOp(right,multiplies<double>());
2264          m_data=c->getPtr();    return (*this);
     return (*this);  
   }  
   else  
   {  
     binaryOp(right,multiplies<double>());  
     return (*this);  
   }  
2265  }  }
2266    
2267  Data&  Data&
# Line 2093  Data::operator*=(const boost::python::ob Line 2271  Data::operator*=(const boost::python::ob
2271          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2272    }    }
2273    Data tmp(right,getFunctionSpace(),false);    Data tmp(right,getFunctionSpace(),false);
2274    if (isLazy())    (*this)*=tmp;
2275    {    return (*this);
     DataLazy* c=new DataLazy(m_data,tmp.borrowDataPtr(),MUL);   // for lazy * is equivalent to *=  
         m_data=c->getPtr();  
     return (*this);  
   }  
   else  
   {  
     binaryOp(tmp,multiplies<double>());  
     return (*this);  
   }  
2276  }  }
2277    
2278  Data&  Data&
# Line 2112  Data::operator/=(const Data& right) Line 2281  Data::operator/=(const Data& right)
2281    if (isProtected()) {    if (isProtected()) {
2282          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2283    }    }
2284    if (isLazy() || right.isLazy())    MAKELAZYBINSELF(right,DIV)
2285    {    exclusiveWrite();
2286      DataLazy* c=new DataLazy(m_data,right.borrowDataPtr(),DIV); // for lazy / is equivalent to /=    binaryOp(right,divides<double>());
2287          m_data=c->getPtr();    return (*this);
     return (*this);  
   }  
   else  
   {  
     binaryOp(right,divides<double>());  
     return (*this);  
   }  
2288  }  }
2289    
2290  Data&  Data&
# Line 2132  Data::operator/=(const boost::python::ob Line 2294  Data::operator/=(const boost::python::ob
2294          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2295    }    }
2296    Data tmp(right,getFunctionSpace(),false);    Data tmp(right,getFunctionSpace(),false);
2297    if (isLazy())    (*this)/=tmp;
2298    {    return (*this);
     DataLazy* c=new DataLazy(m_data,tmp.borrowDataPtr(),DIV);   // for lazy / is equivalent to /=  
         m_data=c->getPtr();  
     return (*this);  
   }  
   else  
   {  
     binaryOp(tmp,divides<double>());  
     return (*this);  
   }  
2299  }  }
2300    
2301  Data  Data
# Line 2162  Data::powO(const boost::python::object& Line 2315  Data::powO(const boost::python::object&
2315  Data  Data
2316  Data::powD(const Data& right) const  Data::powD(const Data& right) const
2317  {  {
2318    if (isLazy() || right.isLazy())    MAKELAZYBIN(right,POW)
   {  
     DataLazy* c=new DataLazy(m_data,right.borrowDataPtr(),POW);  
     return Data(c);  
   }  
2319    return C_TensorBinaryOperation<double (*)(double, double)>(*this, right, ::pow);    return C_TensorBinaryOperation<double (*)(double, double)>(*this, right, ::pow);
2320  }  }
2321    
# Line 2175  Data::powD(const Data& right) const Line 2324  Data::powD(const Data& right) const
2324  Data  Data
2325  escript::operator+(const Data& left, const Data& right)  escript::operator+(const Data& left, const Data& right)
2326  {  {
2327    if (left.isLazy() || right.isLazy())    MAKELAZYBIN2(left,right,ADD)
   {  
     DataLazy* c=new DataLazy(left.borrowDataPtr(),right.borrowDataPtr(),ADD);  
     return Data(c);  
   }  
2328    return C_TensorBinaryOperation(left, right, plus<double>());    return C_TensorBinaryOperation(left, right, plus<double>());
2329  }  }
2330    
# Line 2188  escript::operator+(const Data& left, con Line 2333  escript::operator+(const Data& left, con
2333  Data  Data
2334  escript::operator-(const Data& left, const Data& right)  escript::operator-(const Data& left, const Data& right)
2335  {  {
2336    if (left.isLazy() || right.isLazy())    MAKELAZYBIN2(left,right,SUB)
   {  
     DataLazy* c=new DataLazy(left.borrowDataPtr(),right.borrowDataPtr(),SUB);  
     return Data(c);  
   }  
2337    return C_TensorBinaryOperation(left, right, minus<double>());    return C_TensorBinaryOperation(left, right, minus<double>());
2338  }  }
2339    
# Line 2201  escript::operator-(const Data& left, con Line 2342  escript::operator-(const Data& left, con
2342  Data  Data
2343  escript::operator*(const Data& left, const Data& right)  escript::operator*(const Data& left, const Data& right)
2344  {  {
2345    if (left.isLazy() || right.isLazy())    MAKELAZYBIN2(left,right,MUL)
   {  
     DataLazy* c=new DataLazy(left.borrowDataPtr(),right.borrowDataPtr(),MUL);  
     return Data(c);  
   }  
2346    return C_TensorBinaryOperation(left, right, multiplies<double>());    return C_TensorBinaryOperation(left, right, multiplies<double>());
2347  }  }
2348    
# Line 2214  escript::operator*(const Data& left, con Line 2351  escript::operator*(const Data& left, con
2351  Data  Data
2352  escript::operator/(const Data& left, const Data& right)  escript::operator/(const Data& left, const Data& right)
2353  {  {
2354    if (left.isLazy() || right.isLazy())    MAKELAZYBIN2(left,right,DIV)
   {  
     DataLazy* c=new DataLazy(left.borrowDataPtr(),right.borrowDataPtr(),DIV);  
     return Data(c);  
   }  
2355    return C_TensorBinaryOperation(left, right, divides<double>());    return C_TensorBinaryOperation(left, right, divides<double>());
2356  }  }
2357    
# Line 2227  escript::operator/(const Data& left, con Line 2360  escript::operator/(const Data& left, con
2360  Data  Data
2361  escript::operator+(const Data& left, const boost::python::object& right)  escript::operator+(const Data& left, const boost::python::object& right)
2362  {  {
2363    if (left.isLazy())    Data tmp(right,left.getFunctionSpace(),false);
2364    {    MAKELAZYBIN2(left,tmp,ADD)
2365      DataLazy* c=new DataLazy(left.borrowDataPtr(),Data(right,left.getFunctionSpace(),false).borrowDataPtr(),ADD);    return left+tmp;
     return Data(c);  
   }  
   return left+Data(right,left.getFunctionSpace(),false);  
2366  }  }
2367    
2368  //  //
# Line 2240  escript::operator+(const Data& left, con Line 2370  escript::operator+(const Data& left, con
2370  Data  Data
2371  escript::operator-(const Data& left, const boost::python::object& right)  escript::operator-(const Data& left, const boost::python::object& right)
2372  {  {
2373    if (left.isLazy())    Data tmp(right,left.getFunctionSpace(),false);
2374    {    MAKELAZYBIN2(left,tmp,SUB)
2375      DataLazy* c=new DataLazy(left.borrowDataPtr(),Data(right,left.getFunctionSpace(),false).borrowDataPtr(),SUB);    return left-tmp;
     return Data(c);  
   }  
   return left-Data(right,left.getFunctionSpace(),false);  
2376  }  }
2377    
2378  //  //
# Line 2253  escript::operator-(const Data& left, con Line 2380  escript::operator-(const Data& left, con
2380  Data  Data
2381  escript::operator*(const Data& left, const boost::python::object& right)  escript::operator*(const Data& left, const boost::python::object& right)
2382  {  {
2383    if (left.isLazy())    Data tmp(right,left.getFunctionSpace(),false);
2384    {    MAKELAZYBIN2(left,tmp,MUL)
2385      DataLazy* c=new DataLazy(left.borrowDataPtr(),Data(right,left.getFunctionSpace(),false).borrowDataPtr(),MUL);    return left*tmp;
     return Data(c);  
   }  
   return left*Data(right,left.getFunctionSpace(),false);  
2386  }  }
2387    
2388  //  //
# Line 2266  escript::operator*(const Data& left, con Line 2390  escript::operator*(const Data& left, con
2390  Data  Data
2391  escript::operator/(const Data& left, const boost::python::object& right)  escript::operator/(const Data& left, const boost::python::object& right)
2392  {  {
2393    if (left.isLazy())    Data tmp(right,left.getFunctionSpace(),false);
2394    {    MAKELAZYBIN2(left,tmp,DIV)
2395      DataLazy* c=new DataLazy(left.borrowDataPtr(),Data(right,left.getFunctionSpace(),false).borrowDataPtr(),DIV);    return left/tmp;
     return Data(c);  
   }  
   return left/Data(right,left.getFunctionSpace(),false);  
2396  }  }
2397    
2398  //  //
# Line 2279  escript::operator/(const Data& left, con Line 2400  escript::operator/(const Data& left, con
2400  Data  Data
2401  escript::operator+(const boost::python::object& left, const Data& right)  escript::operator+(const boost::python::object& left, const Data& right)
2402  {  {
2403    if (right.isLazy())    Data tmp(left,right.getFunctionSpace(),false);
2404    {    MAKELAZYBIN2(tmp,right,ADD)
2405      DataLazy* c=new DataLazy(Data(left,right.getFunctionSpace(),false).borrowDataPtr(),right.borrowDataPtr(),ADD);    return tmp+right;
     return Data(c);  
   }  
   return Data(left,right.getFunctionSpace(),false)+right;  
2406  }  }
2407    
2408  //  //
# Line 2292  escript::operator+(const boost::python:: Line 2410  escript::operator+(const boost::python::
2410  Data  Data
2411  escript::operator-(const boost::python::object& left, const Data& right)  escript::operator-(const boost::python::object& left, const Data& right)
2412  {  {
2413    if (right.isLazy())    Data tmp(left,right.getFunctionSpace(),false);
2414    {    MAKELAZYBIN2(tmp,right,SUB)
2415      DataLazy* c=new DataLazy(Data(left,right.getFunctionSpace(),false).borrowDataPtr(),right.borrowDataPtr(),SUB);    return tmp-right;
     return Data(c);  
   }  
   return Data(left,right.getFunctionSpace(),false)-right;  
2416  }  }
2417    
2418  //  //
# Line 2305  escript::operator-(const boost::python:: Line 2420  escript::operator-(const boost::python::
2420  Data  Data
2421  escript::operator*(const boost::python::object& left, const Data& right)  escript::operator*(const boost::python::object& left, const Data& right)
2422  {  {
2423    if (right.isLazy())    Data tmp(left,right.getFunctionSpace(),false);
2424    {    MAKELAZYBIN2(tmp,right,MUL)
2425      DataLazy* c=new DataLazy(Data(left,right.getFunctionSpace(),false).borrowDataPtr(),right.borrowDataPtr(),MUL);    return tmp*right;
     return Data(c);  
   }  
   return Data(left,right.getFunctionSpace(),false)*right;  
2426  }  }
2427    
2428  //  //
# Line 2318  escript::operator*(const boost::python:: Line 2430  escript::operator*(const boost::python::
2430  Data  Data
2431  escript::operator/(const boost::python::object& left, const Data& right)  escript::operator/(const boost::python::object& left, const Data& right)
2432  {  {
2433    if (right.isLazy())    Data tmp(left,right.getFunctionSpace(),false);
2434    {    MAKELAZYBIN2(tmp,right,DIV)
2435      DataLazy* c=new DataLazy(Data(left,right.getFunctionSpace(),false).borrowDataPtr(),right.borrowDataPtr(),DIV);    return tmp/right;
     return Data(c);  
   }  
   return Data(left,right.getFunctionSpace(),false)/right;  
2436  }  }
2437    
2438    
# Line 2364  void Line 2473  void
2473  Data::setItemD(const boost::python::object& key,  Data::setItemD(const boost::python::object& key,
2474                 const Data& value)                 const Data& value)
2475  {  {
 //  const DataArrayView& view=getPointDataView();  
   
2476    DataTypes::RegionType slice_region=DataTypes::getSliceRegion(getDataPointShape(),key);    DataTypes::RegionType slice_region=DataTypes::getSliceRegion(getDataPointShape(),key);
2477    if (slice_region.size()!=getDataPointRank()) {    if (slice_region.size()!=getDataPointRank()) {
2478      throw DataException("Error - slice size does not match Data rank.");      throw DataException("Error - slice size does not match Data rank.");
2479    }    }
2480      exclusiveWrite();
2481    if (getFunctionSpace()!=value.getFunctionSpace()) {    if (getFunctionSpace()!=value.getFunctionSpace()) {
2482       setSlice(Data(value,getFunctionSpace()),slice_region);       setSlice(Data(value,getFunctionSpace()),slice_region);
2483    } else {    } else {
# Line 2384  Data::setSlice(const Data& value, Line 2492  Data::setSlice(const Data& value,
2492    if (isProtected()) {    if (isProtected()) {
2493          throw DataException("Error - attempt to update protected Data object.");          throw DataException("Error - attempt to update protected Data object.");
2494    }    }
2495    FORCERESOLVE;    forceResolve();
2496  /*  if (isLazy())    exclusiveWrite();     // In case someone finds a way to call this without going through setItemD
   {  
     throw DataException("Error - setSlice not permitted on lazy data.");  
   }*/  
2497    Data tempValue(value);    Data tempValue(value);
2498    typeMatchLeft(tempValue);    typeMatchLeft(tempValue);
2499    typeMatchRight(tempValue);    typeMatchRight(tempValue);
# Line 2431  Data::typeMatchRight(const Data& right) Line 2536  Data::typeMatchRight(const Data& right)
2536    }    }
2537  }  }
2538    
2539    // The normal TaggedValue adds the tag if it is not already present
2540    // This form does not. It throws instead.
2541    // This is because the names are maintained by the domain and cannot be added
2542    // without knowing the tag number to map it to.
2543  void  void
2544  Data::setTaggedValueByName(std::string name,  Data::setTaggedValueByName(std::string name,
2545                             const boost::python::object& value)                             const boost::python::object& value)
2546  {  {
2547       if (getFunctionSpace().getDomain()->isValidTagName(name)) {       if (getFunctionSpace().getDomain()->isValidTagName(name)) {
2548      FORCERESOLVE;      forceResolve();
2549        exclusiveWrite();
2550          int tagKey=getFunctionSpace().getDomain()->getTag(name);          int tagKey=getFunctionSpace().getDomain()->getTag(name);
2551          setTaggedValue(tagKey,value);          setTaggedValue(tagKey,value);
2552       }       }
2553         else
2554         {                  // The
2555        throw DataException("Error - unknown tag in setTaggedValueByName.");
2556         }
2557  }  }
2558    
2559  void  void
2560  Data::setTaggedValue(int tagKey,  Data::setTaggedValue(int tagKey,
2561                       const boost::python::object& value)                       const boost::python::object& value)
# Line 2450  Data::setTaggedValue(int tagKey, Line 2565  Data::setTaggedValue(int tagKey,
2565    }    }
2566    //    //
2567    // Ensure underlying data object is of type DataTagged    // Ensure underlying data object is of type DataTagged
2568    FORCERESOLVE;    forceResolve();
2569      exclusiveWrite();
2570    if (isConstant()) tag();    if (isConstant()) tag();
2571    numeric::array asNumArray(value);    WrappedArray w(value);
   
   // extract the shape of the numarray  
   DataTypes::ShapeType tempShape;  
   for (int i=0; i < asNumArray.getrank(); i++) {  
     tempShape.push_back(extract<int>(asNumArray.getshape()[i]));  
   }  
2572    
2573    DataVector temp_data2;    DataVector temp_data2;
2574    temp_data2.copyFromNumArray(asNumArray);    temp_data2.copyFromArray(w,1);
2575    
2576    m_data->setTaggedValue(tagKey,tempShape, temp_data2);    m_data->setTaggedValue(tagKey,w.getShape(), temp_data2);
2577  }  }
2578    
2579    
# Line 2478  Data::setTaggedValueFromCPP(int tagKey, Line 2588  Data::setTaggedValueFromCPP(int tagKey,
2588    }    }
2589    //    //
2590    // Ensure underlying data object is of type DataTagged    // Ensure underlying data object is of type DataTagged
2591    FORCERESOLVE;    forceResolve();
2592    if (isConstant()) tag();    if (isConstant()) tag();
2593      exclusiveWrite();
2594    //    //
2595    // Call DataAbstract::setTaggedValue    // Call DataAbstract::setTaggedValue
2596    m_data->setTaggedValue(tagKey,pointshape, value, dataOffset);    m_data->setTaggedValue(tagKey,pointshape, value, dataOffset);
# Line 2512  escript::C_GeneralTensorProduct(Data& ar Line 2623  escript::C_GeneralTensorProduct(Data& ar
2623    // SM is the product of the last axis_offset entries in arg_0.getShape().    // SM is the product of the last axis_offset entries in arg_0.getShape().
2624    
2625    // deal with any lazy data    // deal with any lazy data
2626    if (arg_0.isLazy()) {arg_0.resolve();}  //   if (arg_0.isLazy()) {arg_0.resolve();}
2627    if (arg_1.isLazy()) {arg_1.resolve();}  //   if (arg_1.isLazy()) {arg_1.resolve();}
2628      if (arg_0.isLazy() || arg_1.isLazy() || (AUTOLAZYON && (arg_0.isExpanded() || arg_1.isExpanded())))
2629      {
2630        DataLazy* c=new DataLazy(arg_0.borrowDataPtr(), arg_1.borrowDataPtr(), PROD, axis_offset,transpose);
2631        return Data(c);
2632      }
2633    
2634    // Interpolate if necessary and find an appropriate function space    // Interpolate if necessary and find an appropriate function space
2635    Data arg_0_Z, arg_1_Z;    Data arg_0_Z, arg_1_Z;
# Line 2590  escript::C_GeneralTensorProduct(Data& ar Line 2706  escript::C_GeneralTensorProduct(Data& ar
2706       for (int i=axis_offset; i<rank1; i++, ++out_index)   { shape2[out_index]=tmpShape1[i]; } // Last part of arg_1_Z       for (int i=axis_offset; i<rank1; i++, ++out_index)   { shape2[out_index]=tmpShape1[i]; } // Last part of arg_1_Z
2707    }    }
2708    
2709      if (shape2.size()>ESCRIPT_MAX_DATA_RANK)
2710      {
2711         ostringstream os;
2712         os << "C_GeneralTensorProduct: Error - Attempt to create a rank " << shape2.size() << " object. The maximum rank is " << ESCRIPT_MAX_DATA_RANK << ".";
2713         throw DataException(os.str());
2714      }
2715    
2716    // Declare output Data object    // Declare output Data object
2717    Data res;    Data res;
2718    
2719    if      (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {    if      (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2720      res = Data(0.0, shape2, arg_1_Z.getFunctionSpace());    // DataConstant output      res = Data(0.0, shape2, arg_1_Z.getFunctionSpace());    // DataConstant output
2721      double *ptr_0 = &(arg_0_Z.getDataAtOffset(0));      const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2722      double *ptr_1 = &(arg_1_Z.getDataAtOffset(0));      const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2723      double *ptr_2 = &(res.getDataAtOffset(0));      double *ptr_2 = &(res.getDataAtOffsetRW(0));
2724      matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);      matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2725    }    }
2726    else if (arg_0_Z.isConstant()   && arg_1_Z.isTagged()) {    else if (arg_0_Z.isConstant()   && arg_1_Z.isTagged()) {
# Line 2618  escript::C_GeneralTensorProduct(Data& ar Line 2741  escript::C_GeneralTensorProduct(Data& ar
2741    
2742      // Prepare offset into DataConstant      // Prepare offset into DataConstant
2743      int offset_0 = tmp_0->getPointOffset(0,0);      int offset_0 = tmp_0->getPointOffset(0,0);
2744      double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0));      const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
     // Get the views  
 //     DataArrayView view_1 = tmp_1->getDefaultValue();  
 //     DataArrayView view_2 = tmp_2->getDefaultValue();  
 //     // Get the pointers to the actual data  
 //     double *ptr_1 = &((view_1.getData())[0]);  
 //     double *ptr_2 = &((view_2.getData())[0]);  
   
     double *ptr_1 = &(tmp_1->getDefaultValue(0));  
     double *ptr_2 = &(tmp_2->getDefaultValue(0));  
2745    
2746        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2747        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2748    
2749      // Compute an MVP for the default      // Compute an MVP for the default
2750      matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);      matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
# Line 2637  escript::C_GeneralTensorProduct(Data& ar Line 2753  escript::C_GeneralTensorProduct(Data& ar
2753      DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory      DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2754      for (i=lookup_1.begin();i!=lookup_1.end();i++) {      for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2755        tmp_2->addTag(i->first);        tmp_2->addTag(i->first);
 //       DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);  
 //       DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);  
 //       double *ptr_1 = &view_1.getData(0);  
 //       double *ptr_2 = &view_2.getData(0);  
2756    
2757        double *ptr_1 = &(tmp_1->getDataByTag(i->first,0));        const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2758        double *ptr_2 = &(tmp_2->getDataByTag(i->first,0));        double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2759            
2760        matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);        matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2761      }      }
# Line 2667  escript::C_GeneralTensorProduct(Data& ar Line 2779  escript::C_GeneralTensorProduct(Data& ar
2779        for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {        for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2780          int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);          int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2781          int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);          int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2782          double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0));          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2783          double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1));          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2784          double *ptr_2 = &(res.getDataAtOffset(offset_2));          double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2785          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2786        }        }
2787      }      }
# Line 2693  escript::C_GeneralTensorProduct(Data& ar Line 2805  escript::C_GeneralTensorProduct(Data& ar
2805    
2806      // Prepare offset into DataConstant      // Prepare offset into DataConstant
2807      int offset_1 = tmp_1->getPointOffset(0,0);      int offset_1 = tmp_1->getPointOffset(0,0);
2808      double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1));      const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2809      // Get the views      const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2810  //     DataArrayView view_0 = tmp_0->getDefaultValue();      double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
 //     DataArrayView view_2 = tmp_2->getDefaultValue();  
 //     // Get the pointers to the actual data  
 //     double *ptr_0 = &((view_0.getData())[0]);  
 //     double *ptr_2 = &((view_2.getData())[0]);  
   
     double *ptr_0 = &(tmp_0->getDefaultValue(0));  
     double *ptr_2 = &(tmp_2->getDefaultValue(0));  
2811    
2812      // Compute an MVP for the default      // Compute an MVP for the default
2813      matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);      matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
# Line 2710  escript::C_GeneralTensorProduct(Data& ar Line 2815  escript::C_GeneralTensorProduct(Data& ar
2815      const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();      const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2816      DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory      DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2817      for (i=lookup_0.begin();i!=lookup_0.end();i++) {      for (i=lookup_0.begin();i!=lookup_0.end();i++) {
 //      tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());  
 //       DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);  
 //       DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);  
 //       double *ptr_0 = &view_0.getData(0);  
 //       double *ptr_2 = &view_2.getData(0);  
2818    
2819        tmp_2->addTag(i->first);        tmp_2->addTag(i->first);
2820        double *ptr_0 = &(tmp_0->getDataByTag(i->first,0));        const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2821        double *ptr_2 = &(tmp_2->getDataByTag(i->first,0));        double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2822        matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);        matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2823      }      }
2824    
# Line 2739  escript::C_GeneralTensorProduct(Data& ar Line 2839  escript::C_GeneralTensorProduct(Data& ar
2839      DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());      DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2840      if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }      if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2841    
2842  //     // Get the views      const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2843  //     DataArrayView view_0 = tmp_0->getDefaultValue();      const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2844  //     DataArrayView view_1 = tmp_1->getDefaultValue();      double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
 //     DataArrayView view_2 = tmp_2->getDefaultValue();  
 //     // Get the pointers to the actual data  
 //     double *ptr_0 = &((view_0.getData())[0]);  
 //     double *ptr_1 = &((view_1.getData())[0]);  
 //     double *ptr_2 = &((view_2.getData())[0]);  
   
     double *ptr_0 = &(tmp_0->getDefaultValue(0));  
     double *ptr_1 = &(tmp_1->getDefaultValue(0));  
     double *ptr_2 = &(tmp_2->getDefaultValue(0));  
   
2845    
2846      // Compute an MVP for the default      // Compute an MVP for the default
2847      matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);      matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
# Line 2768  escript::C_GeneralTensorProduct(Data& ar Line 2858  escript::C_GeneralTensorProduct(Data& ar
2858      // Compute an MVP for each tag      // Compute an MVP for each tag
2859      const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();      const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2860      for (i=lookup_2.begin();i!=lookup_2.end();i++) {      for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2861  //       DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);        const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2862  //       DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);        const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2863  //       DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);        double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
 //       double *ptr_0 = &view_0.getData(0);  
 //       double *ptr_1 = &view_1.getData(0);  
 //       double *ptr_2 = &view_2.getData(0);  
   
       double *ptr_0 = &(tmp_0->getDataByTag(i->first,0));  
       double *ptr_1 = &(tmp_1->getDataByTag(i->first,0));  
       double *ptr_2 = &(tmp_2->getDataByTag(i->first,0));  
2864    
2865        matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);        matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2866      }      }
# Line 2799  escript::C_GeneralTensorProduct(Data& ar Line 2882  escript::C_GeneralTensorProduct(Data& ar
2882      #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)      #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2883      for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {      for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2884        int offset_0 = tmp_0->getPointOffset(sampleNo_0,0); // They're all the same, so just use #0        int offset_0 = tmp_0->getPointOffset(sampleNo_0,0); // They're all the same, so just use #0
2885        double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0));        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2886        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2887          int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2888          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2889          double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1));          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2890          double *ptr_2 = &(res.getDataAtOffset(offset_2));          double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2891          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2892        }        }
2893      }      }
# Line 2828  escript::C_GeneralTensorProduct(Data& ar Line 2911  escript::C_GeneralTensorProduct(Data& ar
2911        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2912          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2913          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2914          double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0));          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2915          double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1));          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2916          double *ptr_2 = &(res.getDataAtOffset(offset_2));          double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2917          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2918        }        }
2919      }      }
# Line 2853  escript::C_GeneralTensorProduct(Data& ar Line 2936  escript::C_GeneralTensorProduct(Data& ar
2936      #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)      #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2937      for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {      for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2938        int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);        int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2939        double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1));        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2940        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2941          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2942          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2943          double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0));          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2944          double *ptr_2 = &(res.getDataAtOffset(offset_2));          double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2945          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2946        }        }
2947      }      }
# Line 2883  escript::C_GeneralTensorProduct(Data& ar Line 2966  escript::C_GeneralTensorProduct(Data& ar
2966          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2967          int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2968          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2969          double *ptr_0 = &(arg_0_Z.getDataAtOffset(offset_0));          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2970          double *ptr_1 = &(arg_1_Z.getDataAtOffset(offset_1));          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2971          double *ptr_2 = &(res.getDataAtOffset(offset_2));          double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2972          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);          matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2973        }        }
2974      }      }
# Line 2923  Data::borrowReadyPtr() const Line 3006  Data::borrowReadyPtr() const
3006  std::string  std::string
3007  Data::toString() const  Data::toString() const
3008  {  {
3009      if (!m_data->isEmpty() &&      if (!m_data->isEmpty() &&
3010      getNumDataPoints()*getDataPointSize()>escriptParams.getInt("TOO_MANY_LINES"))      !m_data->isLazy() &&
3011        getLength()>escriptParams.getInt("TOO_MANY_LINES"))
3012      {      {
3013      stringstream temp;      stringstream temp;
3014      temp << "Summary: inf="<< inf_const() << " sup=" << sup_const() << " data points=" << getNumDataPoints();      temp << "Summary: inf="<< inf_const() << " sup=" << sup_const() << " data points=" << getNumDataPoints();
# Line 2934  Data::toString() const Line 3018  Data::toString() const
3018  }  }
3019    
3020    
3021    // This method is not thread-safe
3022    DataTypes::ValueType::reference
3023    Data::getDataAtOffsetRW(DataTypes::ValueType::size_type i)
3024    {
3025        checkExclusiveWrite();
3026        return getReady()->getDataAtOffsetRW(i);
3027    }
3028    
3029    // This method is not thread-safe
3030  DataTypes::ValueType::const_reference  DataTypes::ValueType::const_reference
3031  Data::getDataAtOffset(DataTypes::ValueType::size_type i) const  Data::getDataAtOffsetRO(DataTypes::ValueType::size_type i)
3032  {  {
3033      if (isLazy())      forceResolve();
3034      {      return getReady()->getDataAtOffsetRO(i);
     throw DataException("Programmer error - getDataAtOffset not permitted on lazy data (object is const which prevents resolving).");  
     }  
     return getReady()->getDataAtOffset(i);  
3035  }  }
3036    
3037    
3038  DataTypes::ValueType::reference  // DataTypes::ValueType::const_reference
3039  Data::getDataAtOffset(DataTypes::ValueType::size_type i)  // Data::getDataAtOffsetRO(DataTypes::ValueType::size_type i) const
3040  {  // {
3041  //     if (isLazy())  //     if (isLazy())
3042  //     {  //     {
3043  //  throw DataException("getDataAtOffset not permitted on lazy data.");  //  throw DataException("Programmer error - getDataAtOffsetRO() not permitted on Lazy Data (object is const which prevents resolving).");
3044  //     }  //     }
3045      FORCERESOLVE;  //     return getReady()->getDataAtOffsetRO(i);
3046      return getReady()->getDataAtOffset(i);  // }
3047  }  
3048    
3049  DataTypes::ValueType::const_reference  DataTypes::ValueType::const_reference
3050  Data::getDataPoint(int sampleNo, int dataPointNo) const  Data::getDataPointRO(int sampleNo, int dataPointNo)
3051  {  {
3052      forceResolve();
3053    if (!isReady())    if (!isReady())
3054    {    {
3055      throw DataException("Programmer error - getDataPoint() not permitted on Lazy Data (object is const which prevents resolving).");      throw DataException("Programmer error -getDataPointRO() not permitted on Lazy Data.");
3056    }    }
3057    else    else
3058    {    {
3059      const DataReady* dr=getReady();      const DataReady* dr=getReady();
3060      return dr->getDataAtOffset(dr->getPointOffset(sampleNo, dataPointNo));      return dr->getDataAtOffsetRO(dr->getPointOffset(sampleNo, dataPointNo));
3061    }    }
3062  }  }
3063    
3064    
3065    
3066    
3067  DataTypes::ValueType::reference  DataTypes::ValueType::reference
3068  Data::getDataPoint(int sampleNo, int dataPointNo)  Data::getDataPointRW(int sampleNo, int dataPointNo)
3069  {  {
3070    FORCERESOLVE;    checkExclusiveWrite();
3071    if (!isReady())    DataReady* dr=getReady();
3072    {    return dr->getDataAtOffsetRW(dr->getPointOffset(sampleNo, dataPointNo));
3073      throw DataException("Programmer error - getDataPoint() not permitted on Lazy Data.");  }
3074    }  
3075    else  BufferGroup*
3076    {  Data::allocSampleBuffer() const
3077      DataReady* dr=getReady();  {
3078      return dr->getDataAtOffset(dr->getPointOffset(sampleNo, dataPointNo));       if (isLazy())
3079    }       {
3080        #ifdef _OPENMP
3081        int tnum=omp_get_max_threads();
3082        #else
3083        int tnum=1;
3084        #endif
3085        return new BufferGroup(getSampleBufferSize(),tnum);
3086         }
3087         else
3088         {
3089        return NULL;
3090         }
3091    }
3092    
3093    void
3094    Data::freeSampleBuffer(BufferGroup* bufferg)
3095    {
3096         if (bufferg!=0)
3097         {
3098        delete bufferg;
3099         }
3100    }
3101    
3102    
3103    Data
3104    Data::interpolateFromTable2DP(boost::python::object table, double Amin, double Astep,
3105            Data& B, double Bmin, double Bstep, double undef, bool check_boundaries)
3106    {
3107        WrappedArray t(table);
3108        return interpolateFromTable2D(t, Amin, Astep, undef, B, Bmin, Bstep,check_boundaries);
3109    }
3110    
3111    Data
3112    Data::interpolateFromTable1DP(boost::python::object table, double Amin, double Astep,
3113                              double undef,bool check_boundaries)
3114    {
3115        WrappedArray t(table);
3116        return interpolateFromTable1D(t, Amin, Astep, undef, check_boundaries);
3117    }
3118    
3119    
3120    Data
3121    Data::interpolateFromTable1D(const WrappedArray& table, double Amin, double Astep,
3122                     double undef, bool check_boundaries)
3123    {
3124        table.convertArray();       // critical!  Calling getElt on an unconverted array is not thread safe
3125        int error=0;
3126        if ((getDataPointRank()!=0))
3127        {
3128            throw DataException("Input to 1D interpolation must be scalar");
3129        }
3130        if (table.getRank()!=1)
3131        {
3132            throw DataException("Table for 1D interpolation must be 1D");
3133        }
3134        if (Astep<=0)
3135        {
3136            throw DataException("Astep must be positive");
3137        }
3138        if (!isExpanded())
3139        {
3140            expand();
3141        }
3142        Data res(0, DataTypes::scalarShape, getFunctionSpace(), true);
3143        try
3144        {
3145            int numpts=getNumDataPoints();
3146            const DataVector& adat=getReady()->getVectorRO();
3147            DataVector& rdat=res.getReady()->getVectorRW();
3148            int twidth=table.getShape()[0]-1;
3149            bool haserror=false;
3150            int l=0;
3151            #pragma omp parallel for private(l) schedule(static)
3152            for (l=0;l<numpts; ++l)
3153            {
3154              #pragma omp flush(haserror)       // In case haserror was in register
3155              if (!haserror)        
3156              {
3157               int lerror=0;
3158               try
3159               {
3160                 do         // so we can use break
3161                 {
3162                double a=adat[l];
3163                int x=static_cast<int>(((a-Amin)/Astep));
3164                if (check_boundaries) {
3165                    if ((a<Amin) || (x<0))
3166                    {
3167                        lerror=1;
3168                        break;  
3169                    }
3170                    if (a>Amin+Astep*twidth)
3171                    {
3172                            lerror=4;
3173                        break;
3174                    }
3175                }
3176                if (x<0) x=0;
3177                if (x>twidth) x=twidth;
3178    
3179                if (x==twidth)          // value is on the far end of the table
3180                {
3181                    double e=table.getElt(x);
3182                    if (e>undef)
3183                    {
3184                        lerror=2;
3185                        break;
3186                    }
3187                    rdat[l]=e;
3188                }
3189                else        // x and y are in bounds
3190                {
3191                    double e=table.getElt(x);
3192                    double w=table.getElt(x+1);
3193                    if ((e>undef) || (w>undef))
3194                    {
3195                        lerror=2;
3196                        break;
3197                    }
3198            // map x*Astep <= a << (x+1)*Astep to [-1,1]
3199                    double la = 2.0*(a-Amin-(x*Astep))/Astep-1;
3200                    rdat[l]=((1-la)*e + (1+la)*w)/2;
3201                }  
3202                  } while (false);
3203                } catch (DataException d)
3204                {
3205                    lerror=3;
3206                }
3207                if (lerror!=0)
3208                {
3209                #pragma omp critical    // Doco says there is a flush associated with critical
3210                {
3211                    haserror=true;  // We only care that one error is recorded. We don't care which
3212                    error=lerror;   // one
3213                }
3214                }
3215              } // if (!error)
3216            }   // parallelised for
3217        } catch (DataException d)
3218        {
3219            error=3;        // this is outside the parallel region so assign directly
3220        }
3221    #ifdef PASO_MPI
3222        int rerror=0;
3223        MPI_Allreduce( &error, &rerror, 1, MPI_INT, MPI_MAX, get_MPIComm() );
3224        error=rerror;
3225    #endif
3226        if (error)
3227        {
3228            switch (error)
3229            {
3230                case 1: throw DataException("Value below lower table range.");
3231                case 2: throw DataException("Interpolated value too large");
3232                case 4: throw DataException("Value greater than upper table range.");
3233                default:
3234                    throw DataException("Unknown error in interpolation");      
3235            }
3236        }
3237        return res;
3238    }
3239    
3240            
3241    Data
3242    Data::interpolateFromTable2D(const WrappedArray& table, double Amin, double Astep,
3243                           double undef, Data& B, double Bmin, double Bstep, bool check_boundaries)
3244    {
3245        table.convertArray();       // critical!   Calling getElt on an unconverted array is not thread safe
3246        int error=0;
3247        if ((getDataPointRank()!=0) || (B.getDataPointRank()!=0))
3248        {
3249            throw DataException("Inputs to 2D interpolation must be scalar");
3250        }
3251        if (table.getRank()!=2)
3252        {
3253        throw DataException("Table for 2D interpolation must be 2D");
3254        }
3255        if ((Astep<=0) || (Bstep<=0))
3256        {
3257        throw DataException("Astep and Bstep must be postive");
3258        }
3259        if (getFunctionSpace()!=B.getFunctionSpace())
3260        {
3261        Data n=B.interpolate(getFunctionSpace());
3262        return interpolateFromTable2D(table, Amin, Astep, undef,
3263            n , Bmin, Bstep, check_boundaries);
3264        }
3265        if (!isExpanded())
3266        {
3267        expand();
3268        }
3269        if (!B.isExpanded())
3270        {
3271        B.expand();
3272        }
3273        Data res(0, DataTypes::scalarShape, getFunctionSpace(), true);
3274        try
3275        {
3276        int numpts=getNumDataPoints();
3277        const DataVector& adat=getReady()->getVectorRO();
3278        const DataVector& bdat=B.getReady()->getVectorRO();
3279        DataVector& rdat=res.getReady()->getVectorRW();
3280        const DataTypes::ShapeType& ts=table.getShape();
3281        int twx=ts[0]-1;    // table width x
3282        int twy=ts[1]-1;    // table width y
3283        bool haserror=false;
3284        int l=0;
3285        #pragma omp parallel for private(l) schedule(static)
3286        for (l=0; l<numpts; ++l)
3287        {
3288           #pragma omp flush(haserror)      // In case haserror was in register
3289           if (!haserror)      
3290           {
3291             int lerror=0;
3292             try
3293             {
3294               do
3295               {
3296            double a=adat[l];
3297            double b=bdat[l];
3298            int x=static_cast<int>(((a-Amin)/Astep));
3299            int y=static_cast<int>(((b-Bmin)/Bstep));
3300                    if (check_boundaries) {
3301                    if ( (a<Amin) || (b<Bmin) || (x<0) || (y<0) )
3302                    {
3303                    #pragma omp critical
3304                    {
3305                        lerror=1;
3306                    }
3307                    break;  
3308                    }
3309                    if ( (a>Amin+Astep*twx) || (b>Bmin+Bstep*twy) )
3310                    {
3311                    #pragma omp critical
3312                    {
3313                        lerror=4;
3314                    }
3315                    break;
3316                    }
3317                    }
3318                    if (x<0) x=0;
3319                    if (y<0) y=0;
3320                    if (x>twx) x=twx;
3321                    if (y>twx) y=twy;
3322    
3323                    if (x == twx ) {
3324                         if (y == twy ) {
3325                     double sw=table.getElt(x,y);
3326                     if ((sw>undef))
3327                     {
3328                     #pragma omp critical
3329                     {
3330                         lerror=2;
3331                     }
3332                     break;
3333                     }
3334                     rdat[l]=sw;
3335    
3336                         } else {
3337                     double sw=table.getElt(x,y);
3338                     double nw=table.getElt(x,y+1);
3339                     if ((sw>undef) || (nw>undef))
3340                     {
3341                     #pragma omp critical
3342                     {
3343                        lerror=2;
3344                     }
3345                     break;
3346                     }
3347                     double lb = 2.0*(b-Bmin-(y*Bstep))/Bstep-1;
3348                     rdat[l]=((1-lb)*sw + (1+lb)*nw )/2.;
3349    
3350                         }
3351                    } else {
3352                         if (y == twy ) {
3353                     double sw=table.getElt(x,y);
3354                     double se=table.getElt(x+1,y);
3355                     if ((sw>undef) || (se>undef) )
3356                     {
3357                     #pragma omp critical
3358                     {
3359                        lerror=2;
3360                     }
3361                     break;
3362                     }
3363                     double la = 2.0*(a-Amin-(x*Astep))/Astep-1;
3364                     rdat[l]=((1-la)*sw + (1+la)*se )/2;
3365    
3366                         } else {
3367                     double sw=table.getElt(x,y);
3368                     double nw=table.getElt(x,y+1);
3369                     double se=table.getElt(x+1,y);
3370                     double ne=table.getElt(x+1,y+1);
3371                     if ((sw>undef) || (nw>undef) || (se>undef) || (ne>undef))
3372                     {
3373                    #pragma omp critical
3374                    {
3375                         lerror=2;
3376                    }
3377                    break;
3378                     }
3379                     // map x*Astep <= a << (x+1)*Astep to [-1,1]
3380                     // same with b
3381                     double la = 2.0*(a-Amin-(x*Astep))/Astep-1;
3382                     double lb = 2.0*(b-Bmin-(y*Bstep))/Bstep-1;
3383                     rdat[l]=((1-la)*(1-lb)*sw + (1-la)*(1+lb)*nw +
3384                          (1+la)*(1-lb)*se + (1+la)*(1+lb)*ne)/4;
3385                         }
3386                    }
3387               } while (false);
3388              } catch (DataException d)
3389              {
3390            lerror=3;
3391              }
3392              if (lerror!=0)
3393              {
3394                #pragma omp critical    // Doco says there is a flush associated with critical
3395                {
3396                    haserror=true;  // We only care that one error is recorded. We don't care which
3397                    error=lerror;   // one
3398                }      
3399              }
3400            }  // if (!error)
3401        }   // parallel for
3402        } catch (DataException d)
3403        {
3404            error=3;
3405        }
3406    #ifdef PASO_MPI
3407        int rerror=0;
3408        MPI_Allreduce( &error, &rerror, 1, MPI_INT, MPI_MAX, get_MPIComm() );
3409        error=rerror;
3410    #endif
3411        if (error)
3412        {
3413        switch (error)
3414        {
3415                case 1: throw DataException("Value below lower table range.");
3416                case 2: throw DataException("Interpolated value too large");
3417                case 4: throw DataException("Value greater than upper table range.");
3418                        default:
3419                          throw DataException("Unknown error in interpolation");        
3420        }
3421        }
3422        return res;
3423  }  }
3424    
3425    
# Line 3000  Data::print() Line 3435  Data::print()
3435    {    {
3436      printf( "[%6d]", i );      printf( "[%6d]", i );
3437      for( j=0; j<getNumDataPointsPerSample(); j++ )      for( j=0; j<getNumDataPointsPerSample(); j++ )
3438        printf( "\t%10.7g", (getSampleData(i))[j] );        printf( "\t%10.7g", (getSampleDataRW(i))[j] );    // doesn't really need RW access
3439      printf( "\n" );      printf( "\n" );
3440    }    }
3441  }  }
# Line 3020  Data::dump(const std::string fileName) c Line 3455  Data::dump(const std::string fileName) c
3455            return m_data->dump(fileName);            return m_data->dump(fileName);
3456      }      }
3457    }    }
3458    catch (exception& e)    catch (std::exception& e)
3459    {    {
3460          cout << e.what() << endl;          cout << e.what() << endl;
3461    }    }
# Line 3062  Data::get_MPIComm() const Line 3497  Data::get_MPIComm() const
3497  #endif  #endif
3498  }  }
3499    
   

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