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temp/escript/src/Data.h revision 1387 by trankine, Fri Jan 11 07:45:26 2008 UTC trunk/escript/src/Data.h revision 2646 by jfenwick, Fri Sep 4 00:13:00 2009 UTC
# Line 1  Line 1 
1    
 /* $Id$ */  
   
2  /*******************************************************  /*******************************************************
3   *  *
4   *           Copyright 2003-2007 by ACceSS MNRF  * Copyright (c) 2003-2009 by University of Queensland
5   *       Copyright 2007 by University of Queensland  * Earth Systems Science Computational Center (ESSCC)
6   *  * http://www.uq.edu.au/esscc
7   *                http://esscc.uq.edu.au  *
8   *        Primary Business: Queensland, Australia  * Primary Business: Queensland, Australia
9   *  Licensed under the Open Software License version 3.0  * Licensed under the Open Software License version 3.0
10   *     http://www.opensource.org/licenses/osl-3.0.php  * http://www.opensource.org/licenses/osl-3.0.php
11   *  *
12   *******************************************************/  *******************************************************/
13    
14    
15  /** \file Data.h */  /** \file Data.h */
16    
# Line 19  Line 18 
18  #define DATA_H  #define DATA_H
19  #include "system_dep.h"  #include "system_dep.h"
20    
21    #include "DataTypes.h"
22  #include "DataAbstract.h"  #include "DataAbstract.h"
23  #include "DataAlgorithm.h"  #include "DataAlgorithm.h"
24  #include "FunctionSpace.h"  #include "FunctionSpace.h"
# Line 26  Line 26 
26  #include "UnaryOp.h"  #include "UnaryOp.h"
27  #include "DataException.h"  #include "DataException.h"
28    
29    
30  extern "C" {  extern "C" {
31  #include "DataC.h"  #include "DataC.h"
32  /* #include "paso/Paso.h" doesn't belong in this file...causes trouble for BruceFactory.cpp */  //#include <omp.h>
33  }  }
34    
35  #include "esysmpi.h"  #include "esysmpi.h"
36  #include <string>  #include <string>
37  #include <algorithm>  #include <algorithm>
38    #include <sstream>
39    
40  #include <boost/shared_ptr.hpp>  #include <boost/shared_ptr.hpp>
41  #include <boost/python/object.hpp>  #include <boost/python/object.hpp>
42  #include <boost/python/tuple.hpp>  #include <boost/python/tuple.hpp>
43  #include <boost/python/numeric.hpp>  
44    #include "BufferGroup.h"
45    
46  namespace escript {  namespace escript {
47    
# Line 47  namespace escript { Line 50  namespace escript {
50  class DataConstant;  class DataConstant;
51  class DataTagged;  class DataTagged;
52  class DataExpanded;  class DataExpanded;
53    class DataLazy;
54    
55  /**  /**
56     \brief     \brief
57     Data creates the appropriate Data object for the given construction     Data represents a collection of datapoints.
    arguments.  
58    
59     Description:     Description:
60     Data is essentially a factory class which creates the appropriate Data     Internally, the datapoints are actually stored by a DataAbstract object.
61     object for the given construction arguments. It retains control over     The specific instance of DataAbstract used may vary over the lifetime
62     the object created for the lifetime of the object.     of the Data object.
63     The type of Data object referred to may change during the lifetime of     Some methods on this class return references (eg getShape()).
64     the Data object.     These references should not be used after an operation which changes the underlying DataAbstract object.
65       Doing so will lead to invalid memory access.
66       This should not affect any methods exposed via boost::python.
67  */  */
68  class Data {  class Data {
69    
# Line 101  class Data { Line 106  class Data {
106         const FunctionSpace& what);         const FunctionSpace& what);
107    
108    /**    /**
109       \brief      \brief Copy Data from an existing vector
110       Constructor which copies data from a DataArrayView.    */
111    
      \param value - Input - Data value for a single point.  
      \param what - Input - A description of what this data represents.  
      \param expanded - Input - Flag, if true fill the entire container with  
                        the value. Otherwise a more efficient storage  
                        mechanism will be used.  
   */  
112    ESCRIPT_DLL_API    ESCRIPT_DLL_API
113    Data(const DataArrayView& value,    Data(const DataTypes::ValueType& value,
114         const FunctionSpace& what=FunctionSpace(),           const DataTypes::ShapeType& shape,
115         bool expanded=false);                   const FunctionSpace& what=FunctionSpace(),
116                     bool expanded=false);
117    
118    /**    /**
119       \brief       \brief
120       Constructor which creates a Data from a DataArrayView shape.       Constructor which creates a Data with points having the specified shape.
121    
122       \param value - Input - Single value applied to all Data.       \param value - Input - Single value applied to all Data.
123       \param dataPointShape - Input - The shape of each data point.       \param dataPointShape - Input - The shape of each data point.
# Line 128  class Data { Line 128  class Data {
128    */    */
129    ESCRIPT_DLL_API    ESCRIPT_DLL_API
130    Data(double value,    Data(double value,
131         const DataArrayView::ShapeType& dataPointShape=DataArrayView::ShapeType(),         const DataTypes::ShapeType& dataPointShape=DataTypes::ShapeType(),
132         const FunctionSpace& what=FunctionSpace(),         const FunctionSpace& what=FunctionSpace(),
133         bool expanded=false);         bool expanded=false);
134    
# Line 141  class Data { Line 141  class Data {
141    */    */
142    ESCRIPT_DLL_API    ESCRIPT_DLL_API
143    Data(const Data& inData,    Data(const Data& inData,
144         const DataArrayView::RegionType& region);         const DataTypes::RegionType& region);
   
   /**  
      \brief  
      Constructor which will create Tagged data if expanded is false.  
      No attempt is made to ensure the tag keys match the tag keys  
      within the function space.  
   
      \param tagKeys - Input - List of tag values.  
      \param values - Input - List of values, one for each tag.  
      \param defaultValue - Input - A default value, used if tag doesn't exist.  
      \param what - Input - A description of what this data represents.  
      \param expanded - Input - Flag, if true fill the entire container with  
                        the appropriate values.  
     ==>*  
   */  
   ESCRIPT_DLL_API  
   Data(const DataTagged::TagListType& tagKeys,  
        const DataTagged::ValueListType& values,  
        const DataArrayView& defaultValue,  
        const FunctionSpace& what=FunctionSpace(),  
        bool expanded=false);  
   
   /**  
      \brief  
      Constructor which copies data from a python numarray.  
   
      \param value - Input - Data value for a single point.  
      \param what - Input - A description of what this data represents.  
      \param expanded - Input - Flag, if true fill the entire container with  
                        the value. Otherwise a more efficient storage  
                        mechanism will be used.  
   */  
   ESCRIPT_DLL_API  
   Data(const boost::python::numeric::array& value,  
        const FunctionSpace& what=FunctionSpace(),  
        bool expanded=false);  
145    
146    /**    /**
147       \brief       \brief
148       Constructor which copies data from any object that can be converted into       Constructor which copies data from any object that can be treated like a python array/sequence.
      a python numarray.  
149    
150       \param value - Input - Input data.       \param value - Input - Input data.
151       \param what - Input - A description of what this data represents.       \param what - Input - A description of what this data represents.
# Line 198  class Data { Line 161  class Data {
161    /**    /**
162       \brief       \brief
163       Constructor which creates a DataConstant.       Constructor which creates a DataConstant.
164       Copies data from any object that can be converted       Copies data from any object that can be treated like a python array/sequence.
165       into a numarray. All other parameters are copied from other.       All other parameters are copied from other.
166    
167       \param value - Input - Input data.       \param value - Input - Input data.
168       \param other - Input - contains all other parameters.       \param other - Input - contains all other parameters.
# Line 217  class Data { Line 180  class Data {
180         const boost::python::tuple& shape=boost::python::make_tuple(),         const boost::python::tuple& shape=boost::python::make_tuple(),
181         const FunctionSpace& what=FunctionSpace(),         const FunctionSpace& what=FunctionSpace(),
182         bool expanded=false);         bool expanded=false);
183    
184    
185    
186      /**
187        \brief Create a Data using an existing DataAbstract. Warning: The new object assumes ownership of the pointer!
188        Once you have passed the pointer, do not delete it.
189      */
190      ESCRIPT_DLL_API
191      explicit Data(DataAbstract* underlyingdata);
192    
193      /**
194        \brief Create a Data based on the supplied DataAbstract
195      */
196      ESCRIPT_DLL_API
197      explicit Data(DataAbstract_ptr underlyingdata);
198    
199    /**    /**
200       \brief       \brief
201       Destructor       Destructor
# Line 225  class Data { Line 204  class Data {
204    ~Data();    ~Data();
205    
206    /**    /**
207       \brief       \brief Make this object a deep copy of "other".
      Perform a deep copy.  
208    */    */
209    ESCRIPT_DLL_API    ESCRIPT_DLL_API
210    void    void
211    copy(const Data& other);    copy(const Data& other);
212    
213    /**    /**
214         \brief Return a pointer to a deep copy of this object.
215      */
216      ESCRIPT_DLL_API
217      Data
218      copySelf();
219    
220    
221      /**
222         \brief produce a delayed evaluation version of this Data.
223      */
224      ESCRIPT_DLL_API
225      Data
226      delay();
227    
228      /**
229         \brief convert the current data into lazy data.
230      */
231      ESCRIPT_DLL_API
232      void
233      delaySelf();
234    
235    
236      /**
237       Member access methods.       Member access methods.
238    */    */
239    
# Line 247  class Data { Line 248  class Data {
248    
249    /**    /**
250       \brief       \brief
251       Returns trueif the data object is protected against update       Returns true, if the data object is protected against update
252    
253    */    */
254    ESCRIPT_DLL_API    ESCRIPT_DLL_API
255    bool    bool
256    isProtected() const;    isProtected() const;
257    
258    /**  
259       \brief  /**
260       Return the values of a data point on this process     \brief
261    */     Return the value of a data point as a python tuple.
262    */
263    ESCRIPT_DLL_API    ESCRIPT_DLL_API
264    const boost::python::numeric::array    const boost::python::object
265    getValueOfDataPoint(int dataPointNo);    getValueOfDataPointAsTuple(int dataPointNo);
266    
267    /**    /**
268       \brief       \brief
# Line 272  class Data { Line 274  class Data {
274    
275    /**    /**
276       \brief       \brief
277       sets the values of a data-point from a numarray object on this process       sets the values of a data-point from a array-like object on this process
278    */    */
279    ESCRIPT_DLL_API    ESCRIPT_DLL_API
280    void    void
281    setValueOfDataPointToArray(int dataPointNo, const boost::python::numeric::array&);    setValueOfDataPointToArray(int dataPointNo, const boost::python::object&);
282    
283    /**    /**
284       \brief       \brief
# Line 287  class Data { Line 289  class Data {
289    setValueOfDataPoint(int dataPointNo, const double);    setValueOfDataPoint(int dataPointNo, const double);
290    
291    /**    /**
292       \brief       \brief Return a data point across all processors as a python tuple.
      Return the value of the specified data-point across all processors  
293    */    */
294    ESCRIPT_DLL_API    ESCRIPT_DLL_API
295    const boost::python::numeric::array    const boost::python::object
296    getValueOfGlobalDataPoint(int procNo, int dataPointNo);    getValueOfGlobalDataPointAsTuple(int procNo, int dataPointNo);
297    
298    /**    /**
299       \brief       \brief
300       Return the tag number associated with the given data-point.       Return the tag number associated with the given data-point.
301    
      The data-point number here corresponds to the data-point number in the  
      numarray returned by convertToNumArray.  
302    */    */
303    ESCRIPT_DLL_API    ESCRIPT_DLL_API
304    int    int
# Line 313  class Data { Line 312  class Data {
312    escriptDataC    escriptDataC
313    getDataC();    getDataC();
314    
315    
316    
317    /**    /**
318       \brief       \brief
319       Return the C wrapper for the Data object - const version.       Return the C wrapper for the Data object - const version.
# Line 322  class Data { Line 323  class Data {
323    getDataC() const;    getDataC() const;
324    
325    /**    /**
326       \brief      \brief How much space is required to evaulate a sample of the Data.
      Write the data as a string.  
327    */    */
328    ESCRIPT_DLL_API    ESCRIPT_DLL_API
329    inline    size_t
330    std::string    getSampleBufferSize() const;
331    toString() const  
332    {  
     return m_data->toString();  
   }  
333    
334    /**    /**
335       \brief       \brief
336       Return the DataArrayView of the point data. This essentially contains       Write the data as a string. For large amounts of data, a summary is printed.
      the shape information for each data point although it also may be used  
      to manipulate the point data.  
337    */    */
338    ESCRIPT_DLL_API    ESCRIPT_DLL_API
339    inline    std::string
340    const DataArrayView&    toString() const;
   getPointDataView() const  
   {  
      return m_data->getPointDataView();  
   }  
341    
342    /**    /**
343       \brief       \brief
# Line 360  class Data { Line 352  class Data {
352       If possible convert this Data to DataTagged. This will only allow       If possible convert this Data to DataTagged. This will only allow
353       Constant data to be converted to tagged. An attempt to convert       Constant data to be converted to tagged. An attempt to convert
354       Expanded data to tagged will throw an exception.       Expanded data to tagged will throw an exception.
     ==>*  
355    */    */
356    ESCRIPT_DLL_API    ESCRIPT_DLL_API
357    void    void
358    tag();    tag();
359    
360    /**    /**
361        \brief If this data is lazy, then convert it to ready data.
362        What type of ready data depends on the expression. For example, Constant+Tagged==Tagged.
363      */
364      ESCRIPT_DLL_API
365      void
366      resolve();
367    
368    
369      /**
370       \brief Ensures data is ready for write access.
371      This means that the data will be resolved if lazy and will be copied if shared with another Data object.
372      \warning This method should only be called in single threaded sections of code. (It modifies m_data).
373      Do not create any Data objects from this one between calling requireWrite and getSampleDataRW.
374      Doing so might introduce additional sharing.
375      */
376      ESCRIPT_DLL_API
377      void
378      requireWrite();
379    
380      /**
381       \brief       \brief
382       Return true if this Data is expanded.       Return true if this Data is expanded.
383         \note To determine if a sample will contain separate values for each datapoint. Use actsExpanded instead.
384    */    */
385    ESCRIPT_DLL_API    ESCRIPT_DLL_API
386    bool    bool
# Line 376  class Data { Line 388  class Data {
388    
389    /**    /**
390       \brief       \brief
391         Return true if this Data is expanded or resolves to expanded.
392         That is, if it has a separate value for each datapoint in the sample.
393      */
394      ESCRIPT_DLL_API
395      bool
396      actsExpanded() const;
397      
398    
399      /**
400         \brief
401       Return true if this Data is tagged.       Return true if this Data is tagged.
402    */    */
403    ESCRIPT_DLL_API    ESCRIPT_DLL_API
# Line 391  class Data { Line 413  class Data {
413    isConstant() const;    isConstant() const;
414    
415    /**    /**
416         \brief Return true if this Data is lazy.
417      */
418      ESCRIPT_DLL_API
419      bool
420      isLazy() const;
421    
422      /**
423         \brief Return true if this data is ready.
424      */
425      ESCRIPT_DLL_API
426      bool
427      isReady() const;
428    
429      /**
430       \brief       \brief
431       Return true if this Data is empty.       Return true if this Data holds an instance of DataEmpty. This is _not_ the same as asking if the object
432    contains datapoints.
433    */    */
434    ESCRIPT_DLL_API    ESCRIPT_DLL_API
435    bool    bool
# Line 424  class Data { Line 461  class Data {
461    */    */
462    ESCRIPT_DLL_API    ESCRIPT_DLL_API
463    inline    inline
464    const AbstractDomain&  //   const AbstractDomain&
465      const_Domain_ptr
466    getDomain() const    getDomain() const
467    {    {
468       return getFunctionSpace().getDomain();       return getFunctionSpace().getDomain();
469    }    }
470    
471    
472      /**
473         \brief
474         Return the domain.
475         TODO: For internal use only.   This should be removed.
476      */
477      ESCRIPT_DLL_API
478      inline
479    //   const AbstractDomain&
480      Domain_ptr
481      getDomainPython() const
482      {
483         return getFunctionSpace().getDomainPython();
484      }
485    
486    /**    /**
487       \brief       \brief
488       Return a copy of the domain.       Return a copy of the domain.
# Line 444  class Data { Line 497  class Data {
497    */    */
498    ESCRIPT_DLL_API    ESCRIPT_DLL_API
499    inline    inline
500    int    unsigned int
501    getDataPointRank() const    getDataPointRank() const
502    {    {
503      return m_data->getPointDataView().getRank();      return m_data->getRank();
504    }    }
505    
506    /**    /**
# Line 484  class Data { Line 537  class Data {
537    {    {
538      return m_data->getNumDPPSample();      return m_data->getNumDPPSample();
539    }    }
540    
541    
542      /**
543        \brief
544        Return the number of values in the shape for this object.
545      */
546      ESCRIPT_DLL_API
547      int
548      getNoValues() const
549      {
550        return m_data->getNoValues();
551      }
552    
553    
554    /**    /**
555       \brief       \brief
556       dumps the object into a netCDF file       dumps the object into a netCDF file
# Line 491  class Data { Line 558  class Data {
558    ESCRIPT_DLL_API    ESCRIPT_DLL_API
559    void    void
560    dump(const std::string fileName) const;    dump(const std::string fileName) const;
561    
562     /**
563      \brief returns the values of the object as a list of tuples (one for each datapoint).
564    
565      \param scalarastuple If true, scalar data will produce single valued tuples [(1,) (2,) ...]
566    If false, the result is a list of scalars [1, 2, ...]
567     */
568      ESCRIPT_DLL_API
569      const boost::python::object
570      toListOfTuples(bool scalarastuple=true);
571    
572    
573     /**
574        \brief
575        Return the sample data for the given sample no. This is not the
576        preferred interface but is provided for use by C code.
577        The bufferg parameter is only required for LazyData.
578        \param sampleNo - Input - the given sample no.
579        \param bufferg - A buffer to compute (and store) sample data in will be selected from this group.
580        \return pointer to the sample data.
581    */
582      ESCRIPT_DLL_API
583      inline
584      const DataAbstract::ValueType::value_type*
585      getSampleDataRO(DataAbstract::ValueType::size_type sampleNo, BufferGroup* bufferg=0);
586    
587    
588    /**    /**
589       \brief       \brief
590       Return the sample data for the given sample no. This is not the       Return the sample data for the given sample no. This is not the
591       preferred interface but is provided for use by C code.       preferred interface but is provided for use by C code.
592       \param sampleNo - Input - the given sample no.       \param sampleNo - Input - the given sample no.
593         \return pointer to the sample data.
594    */    */
595    ESCRIPT_DLL_API    ESCRIPT_DLL_API
596    inline    inline
597    DataAbstract::ValueType::value_type*    DataAbstract::ValueType::value_type*
598    getSampleData(DataAbstract::ValueType::size_type sampleNo)    getSampleDataRW(DataAbstract::ValueType::size_type sampleNo);
599    {  
     return m_data->getSampleData(sampleNo);  
   }  
600    
601    /**    /**
602       \brief       \brief
# Line 521  class Data { Line 614  class Data {
614    
615    /**    /**
616       \brief       \brief
617       Return a view into the data for the data point specified.       Return a reference into the DataVector which points to the specified data point.
618       NOTE: Construction of the DataArrayView is a relatively expensive       \param sampleNo - Input -
619       operation.       \param dataPointNo - Input -
620      */
621      ESCRIPT_DLL_API
622      DataTypes::ValueType::const_reference
623      getDataPointRO(int sampleNo, int dataPointNo);
624    
625      /**
626         \brief
627         Return a reference into the DataVector which points to the specified data point.
628       \param sampleNo - Input -       \param sampleNo - Input -
629       \param dataPointNo - Input -       \param dataPointNo - Input -
630    */    */
631    ESCRIPT_DLL_API    ESCRIPT_DLL_API
632      DataTypes::ValueType::reference
633      getDataPointRW(int sampleNo, int dataPointNo);
634    
635    
636    
637      /**
638         \brief
639         Return the offset for the given sample and point within the sample
640      */
641      ESCRIPT_DLL_API
642    inline    inline
643    DataArrayView    DataTypes::ValueType::size_type
644    getDataPoint(int sampleNo,    getDataOffset(int sampleNo,
645                 int dataPointNo)                 int dataPointNo)
646    {    {
647                  return m_data->getDataPoint(sampleNo,dataPointNo);        return m_data->getPointOffset(sampleNo,dataPointNo);
648    }    }
649    
650    /**    /**
# Line 541  class Data { Line 652  class Data {
652       Return a reference to the data point shape.       Return a reference to the data point shape.
653    */    */
654    ESCRIPT_DLL_API    ESCRIPT_DLL_API
655    const DataArrayView::ShapeType&    inline
656    getDataPointShape() const;    const DataTypes::ShapeType&
657      getDataPointShape() const
658      {
659        return m_data->getShape();
660      }
661    
662    /**    /**
663       \brief       \brief
# Line 566  class Data { Line 681  class Data {
681       Return the number of doubles stored for this Data.       Return the number of doubles stored for this Data.
682    */    */
683    ESCRIPT_DLL_API    ESCRIPT_DLL_API
684    DataArrayView::ValueType::size_type    DataTypes::ValueType::size_type
685    getLength() const;    getLength() const;
686    
687      /**
688      \brief Return true if this object contains no samples.
689      This is not the same as isEmpty()
690      */
691      ESCRIPT_DLL_API
692      bool
693      hasNoSamples() const
694      {
695        return getLength()==0;
696      }
697    
698    /**    /**
699       \brief       \brief
700       Assign the given value to the tag assocciated with name. Implicitly converts this       Assign the given value to the tag assocciated with name. Implicitly converts this
701       object to type DataTagged. Throws an exception if this object       object to type DataTagged. Throws an exception if this object
702       cannot be converted to a DataTagged object or name cannot be mapped onto a tag key.       cannot be converted to a DataTagged object or name cannot be mapped onto a tag key.
703       \param tagKey - Input - Integer key.       \param name - Input - name of tag.
704       \param value - Input - Value to associate with given key.       \param value - Input - Value to associate with given key.
     ==>*  
705    */    */
706    ESCRIPT_DLL_API    ESCRIPT_DLL_API
707    void    void
# Line 605  class Data { Line 728  class Data {
728       object to type DataTagged if it is constant.       object to type DataTagged if it is constant.
729    
730       \param tagKey - Input - Integer key.       \param tagKey - Input - Integer key.
731         \param pointshape - Input - The shape of the value parameter
732       \param value - Input - Value to associate with given key.       \param value - Input - Value to associate with given key.
733      ==>*       \param dataOffset - Input - Offset of the begining of the point within the value parameter
734    */    */
735    ESCRIPT_DLL_API    ESCRIPT_DLL_API
736    void    void
737    setTaggedValueFromCPP(int tagKey,    setTaggedValueFromCPP(int tagKey,
738                          const DataArrayView& value);              const DataTypes::ShapeType& pointshape,
739                            const DataTypes::ValueType& value,
740                int dataOffset=0);
741    
742    
743    
744    /**    /**
745      \brief      \brief
# Line 644  class Data { Line 772  class Data {
772    ESCRIPT_DLL_API    ESCRIPT_DLL_API
773    Data    Data
774    interpolate(const FunctionSpace& functionspace) const;    interpolate(const FunctionSpace& functionspace) const;
775    
776    
777      ESCRIPT_DLL_API
778      Data
779      interpolateFromTable2D(const WrappedArray& table, double Amin, double Astep,
780                           double undef, Data& B, double Bmin, double Bstep);
781    
782      ESCRIPT_DLL_API
783      Data
784      interpolateFromTable1D(const WrappedArray& table, double Amin, double Astep,
785                           double undef);
786    
787    
788    
789    
790      ESCRIPT_DLL_API
791      Data
792      interpolateFromTable2DP(boost::python::object table, double Amin, double Astep,
793                            Data& B, double Bmin, double Bstep, double undef);
794    
795      ESCRIPT_DLL_API
796      Data
797      interpolateFromTable1DP(boost::python::object table, double Amin, double Astep,
798                            double undef);
799    
800    /**    /**
801       \brief       \brief
802       Calculates the gradient of the data at the data points of functionspace.       Calculates the gradient of the data at the data points of functionspace.
# Line 659  class Data { Line 812  class Data {
812    grad() const;    grad() const;
813    
814    /**    /**
815       \brief      \brief
816       Calculate the integral over the function space domain.       Calculate the integral over the function space domain as a python tuple.
      *  
817    */    */
818    ESCRIPT_DLL_API    ESCRIPT_DLL_API
819    boost::python::numeric::array    boost::python::object
820    integrate() const;    integrateToTuple_const() const;
821    
822    
823      /**
824        \brief
825         Calculate the integral over the function space domain as a python tuple.
826      */
827      ESCRIPT_DLL_API
828      boost::python::object
829      integrateToTuple();
830    
831    
832    
833    /**    /**
834       \brief       \brief
# Line 732  class Data { Line 895  class Data {
895    /**    /**
896       \brief       \brief
897       Return the maximum absolute value of this Data object.       Return the maximum absolute value of this Data object.
898       *  
899         The method is not const because lazy data needs to be expanded before Lsup can be computed.
900         The _const form can be used when the Data object is const, however this will only work for
901         Data which is not Lazy.
902    
903         For Data which contain no samples (or tagged Data for which no tags in use have a value)
904         zero is returned.
905    */    */
906    ESCRIPT_DLL_API    ESCRIPT_DLL_API
907    double    double
908    Lsup() const;    Lsup();
909    
910      ESCRIPT_DLL_API
911      double
912      Lsup_const() const;
913    
914    
915    /**    /**
916       \brief       \brief
917       Return the maximum value of this Data object.       Return the maximum value of this Data object.
918       *  
919         The method is not const because lazy data needs to be expanded before sup can be computed.
920         The _const form can be used when the Data object is const, however this will only work for
921         Data which is not Lazy.
922    
923         For Data which contain no samples (or tagged Data for which no tags in use have a value)
924         a large negative value is returned.
925    */    */
926    ESCRIPT_DLL_API    ESCRIPT_DLL_API
927    double    double
928    sup() const;    sup();
929    
930      ESCRIPT_DLL_API
931      double
932      sup_const() const;
933    
934    
935    /**    /**
936       \brief       \brief
937       Return the minimum value of this Data object.       Return the minimum value of this Data object.
938       *  
939         The method is not const because lazy data needs to be expanded before inf can be computed.
940         The _const form can be used when the Data object is const, however this will only work for
941         Data which is not Lazy.
942    
943         For Data which contain no samples (or tagged Data for which no tags in use have a value)
944         a large positive value is returned.
945    */    */
946    ESCRIPT_DLL_API    ESCRIPT_DLL_API
947    double    double
948    inf() const;    inf();
949    
950      ESCRIPT_DLL_API
951      double
952      inf_const() const;
953    
954    
955    
956    /**    /**
957       \brief       \brief
# Line 786  class Data { Line 983  class Data {
983    /**    /**
984       \brief       \brief
985       Return the (sample number, data-point number) of the data point with       Return the (sample number, data-point number) of the data point with
986       the minimum value in this Data object.       the minimum component value in this Data object.
987         \note If you are working in python, please consider using Locator
988    instead of manually manipulating process and point IDs.
989    */    */
990    ESCRIPT_DLL_API    ESCRIPT_DLL_API
991    const boost::python::tuple    const boost::python::tuple
992    minGlobalDataPoint() const;    minGlobalDataPoint() const;
993    
994      /**
995         \brief
996         Return the (sample number, data-point number) of the data point with
997         the minimum component value in this Data object.
998         \note If you are working in python, please consider using Locator
999    instead of manually manipulating process and point IDs.
1000      */
1001    ESCRIPT_DLL_API    ESCRIPT_DLL_API
1002    void    const boost::python::tuple
1003    calc_minGlobalDataPoint(int& ProcNo,  int& DataPointNo) const;    maxGlobalDataPoint() const;
1004    
1005    
1006    
1007    /**    /**
1008       \brief       \brief
1009       Return the sign of each data point of this Data object.       Return the sign of each data point of this Data object.
# Line 1095  class Data { Line 1304  class Data {
1304    void    void
1305    saveVTK(std::string fileName) const;    saveVTK(std::string fileName) const;
1306    
1307    
1308    
1309    /**    /**
1310       \brief       \brief
1311       Overloaded operator +=       Overloaded operator +=
# Line 1212  class Data { Line 1423  class Data {
1423    */    */
1424    ESCRIPT_DLL_API    ESCRIPT_DLL_API
1425    Data    Data
1426    getSlice(const DataArrayView::RegionType& region) const;    getSlice(const DataTypes::RegionType& region) const;
1427    
1428    /**    /**
1429       \brief       \brief
# Line 1225  class Data { Line 1436  class Data {
1436    ESCRIPT_DLL_API    ESCRIPT_DLL_API
1437    void    void
1438    setSlice(const Data& value,    setSlice(const Data& value,
1439             const DataArrayView::RegionType& region);             const DataTypes::RegionType& region);
   
   /**  
      \brief  
      Archive the current Data object to the given file.  
      \param fileName - Input - file to archive to.  
   */  
   ESCRIPT_DLL_API  
   void  
   archiveData(const std::string fileName);  
   
   /**  
      \brief  
      Extract the Data object archived in the given file, overwriting  
      the current Data object.  
      Note - the current object must be of type DataEmpty.  
      \param fileName - Input - file to extract from.  
      \param fspace - Input - a suitable FunctionSpace descibing the data.  
   */  
   ESCRIPT_DLL_API  
   void  
   extractData(const std::string fileName,  
               const FunctionSpace& fspace);  
   
1440    
1441    /**    /**
1442       \brief       \brief
# Line 1290  class Data { Line 1478  class Data {
1478    /**    /**
1479       \brief       \brief
1480       return the object produced by the factory, which is a DataConstant or DataExpanded       return the object produced by the factory, which is a DataConstant or DataExpanded
1481        TODO Ownership of this object should be explained in doco.
1482    */    */
1483    ESCRIPT_DLL_API    ESCRIPT_DLL_API
1484          DataAbstract*          DataAbstract*
1485          borrowData(void) const;          borrowData(void) const;
1486    
1487      ESCRIPT_DLL_API
1488            DataAbstract_ptr
1489            borrowDataPtr(void) const;
1490    
1491      ESCRIPT_DLL_API
1492            DataReady_ptr
1493            borrowReadyPtr(void) const;
1494    
1495    
1496    
1497      /**
1498         \brief
1499         Return a pointer to the beginning of the datapoint at the specified offset.
1500         TODO Eventually these should be inlined.
1501         \param i - position(offset) in the underlying datastructure
1502      */
1503    
1504      ESCRIPT_DLL_API
1505            DataTypes::ValueType::const_reference
1506            getDataAtOffsetRO(DataTypes::ValueType::size_type i);
1507    
1508    
1509      ESCRIPT_DLL_API
1510            DataTypes::ValueType::reference
1511            getDataAtOffsetRW(DataTypes::ValueType::size_type i);
1512    
1513    
1514    
1515    /**
1516       \brief Create a buffer for use by getSample
1517       Allocates a DataVector large enough for DataLazy::resolveSample to operate on for the current Data.
1518       Do not use this buffer for other Data instances (unless you are sure they will be the same size).
1519      
1520       In multi-threaded sections, this needs to be called on each thread.
1521    
1522       \return A BufferGroup* if Data is lazy, NULL otherwise.
1523       \warning This pointer must be deallocated using freeSampleBuffer to avoid cross library memory issues.
1524    */
1525      ESCRIPT_DLL_API
1526      BufferGroup*
1527      allocSampleBuffer() const;
1528    
1529    /**
1530       \brief Free a buffer allocated with allocSampleBuffer.
1531       \param buffer Input - pointer to the buffer to deallocate.
1532    */
1533    ESCRIPT_DLL_API void freeSampleBuffer(BufferGroup* buffer);
1534    
1535   protected:   protected:
1536    
1537   private:   private:
1538    
1539      double
1540      LsupWorker() const;
1541    
1542      double
1543      supWorker() const;
1544    
1545      double
1546      infWorker() const;
1547    
1548      boost::python::object
1549      integrateWorker() const;
1550    
1551      void
1552      calc_minGlobalDataPoint(int& ProcNo,  int& DataPointNo) const;
1553    
1554      void
1555      calc_maxGlobalDataPoint(int& ProcNo,  int& DataPointNo) const;
1556    
1557    
1558    /**    /**
1559       \brief       \brief
1560       Check *this and the right operand are compatible. Throws       Check *this and the right operand are compatible. Throws
# Line 1370  class Data { Line 1626  class Data {
1626       \brief       \brief
1627       Construct a Data object of the appropriate type.       Construct a Data object of the appropriate type.
1628    */    */
1629    template <class IValueType>  
1630    void    void
1631    initialise(const IValueType& value,    initialise(const DataTypes::ValueType& value,
1632             const DataTypes::ShapeType& shape,
1633               const FunctionSpace& what,               const FunctionSpace& what,
1634               bool expanded);               bool expanded);
1635    
1636      void
1637      initialise(const WrappedArray& value,
1638                     const FunctionSpace& what,
1639                     bool expanded);
1640    
1641    //    //
1642    // flag to protect the data object against any update    // flag to protect the data object against any update
1643    bool m_protected;    bool m_protected;
1644      mutable bool m_shared;
1645      bool m_lazy;
1646    
1647    //    //
1648    // pointer to the actual data object    // pointer to the actual data object
1649    boost::shared_ptr<DataAbstract> m_data;  //   boost::shared_ptr<DataAbstract> m_data;
1650      DataAbstract_ptr m_data;
1651    
1652  };  // If possible please use getReadyPtr instead.
1653    // But see warning below.
1654      const DataReady*
1655      getReady() const;
1656    
1657  template <class IValueType>    DataReady*
1658  void    getReady();
1659  Data::initialise(const IValueType& value,  
1660                   const FunctionSpace& what,  
1661                   bool expanded)  // Be wary of using this for local operations since it (temporarily) increases reference count.
1662  {  // If you are just using this to call a method on DataReady instead of DataAbstract consider using
1663    // getReady() instead
1664      DataReady_ptr
1665      getReadyPtr();
1666    
1667      const_DataReady_ptr
1668      getReadyPtr() const;
1669    
1670    
1671      /**
1672       \brief Update the Data's shared flag
1673       This indicates that the DataAbstract used by this object is now shared (or no longer shared).
1674       For internal use only.
1675      */
1676      void updateShareStatus(bool nowshared) const
1677      {
1678        m_shared=nowshared;     // m_shared is mutable
1679      }
1680    
1681      // In the isShared() method below:
1682      // A problem would occur if m_data (the address pointed to) were being modified
1683      // while the call m_data->is_shared is being executed.
1684      //
1685      // Q: So why do I think this code can be thread safe/correct?
1686      // A: We need to make some assumptions.
1687      // 1. We assume it is acceptable to return true under some conditions when we aren't shared.
1688      // 2. We assume that no constructions or assignments which will share previously unshared
1689      //    will occur while this call is executing. This is consistent with the way Data:: and C are written.
1690    //    //
1691    // Construct a Data object of the appropriate type.    // This means that the only transition we need to consider, is when a previously shared object is
1692    // Construct the object first as there seems to be a bug which causes    // not shared anymore. ie. the other objects have been destroyed or a deep copy has been made.
1693    // undefined behaviour if an exception is thrown during construction    // In those cases the m_shared flag changes to false after m_data has completed changing.
1694    // within the shared_ptr constructor.    // For any threads executing before the flag switches they will assume the object is still shared.
1695    if (expanded) {    bool isShared() const
1696      DataAbstract* temp=new DataExpanded(value,what);    {
1697      boost::shared_ptr<DataAbstract> temp_data(temp);      return m_shared;
1698      m_data=temp_data;  /*  if (m_shared) return true;
1699    } else {      if (m_data->isShared())        
1700      DataAbstract* temp=new DataConstant(value,what);      {                  
1701      boost::shared_ptr<DataAbstract> temp_data(temp);          updateShareStatus(true);
1702      m_data=temp_data;          return true;
1703        }
1704        return false;*/
1705      }
1706    
1707      void forceResolve()
1708      {
1709        if (isLazy())
1710        {
1711            #ifdef _OPENMP
1712            if (omp_in_parallel())
1713            {   // Yes this is throwing an exception out of an omp thread which is forbidden.
1714            throw DataException("Please do not call forceResolve() in a parallel region.");
1715            }
1716            #endif
1717            resolve();
1718        }
1719      }
1720    
1721      /**
1722      \brief if another object is sharing out member data make a copy to work with instead.
1723      This code should only be called from single threaded sections of code.
1724      */
1725      void exclusiveWrite()
1726      {
1727    #ifdef _OPENMP
1728      if (omp_in_parallel())
1729      {
1730    // *((int*)0)=17;
1731        throw DataException("Programming error. Please do not run exclusiveWrite() in multi-threaded sections.");
1732    }    }
1733    #endif
1734        forceResolve();
1735        if (isShared())
1736        {
1737            DataAbstract* t=m_data->deepCopy();
1738            set_m_data(DataAbstract_ptr(t));
1739        }
1740      }
1741    
1742      /**
1743      \brief checks if caller can have exclusive write to the object
1744      */
1745      void checkExclusiveWrite()
1746      {
1747        if  (isLazy() || isShared())
1748        {
1749            throw DataException("Programming error. ExclusiveWrite required - please call requireWrite()");
1750        }
1751      }
1752    
1753      /**
1754      \brief Modify the data abstract hosted by this Data object
1755      For internal use only.
1756      Passing a pointer to null is permitted (do this in the destructor)
1757      \warning Only to be called in single threaded code or inside a single/critical section. This method needs to be atomic.
1758      */
1759      void set_m_data(DataAbstract_ptr p);
1760    
1761      friend class DataAbstract;        // To allow calls to updateShareStatus
1762    
1763    };
1764    
1765    }   // end namespace escript
1766    
1767    
1768    // No, this is not supposed to be at the top of the file
1769    // DataAbstact needs to be declared first, then DataReady needs to be fully declared
1770    // so that I can dynamic cast between them below.
1771    #include "DataReady.h"
1772    #include "DataLazy.h"
1773    
1774    namespace escript
1775    {
1776    
1777    inline
1778    const DataReady*
1779    Data::getReady() const
1780    {
1781       const DataReady* dr=dynamic_cast<const DataReady*>(m_data.get());
1782       EsysAssert((dr!=0), "Error - casting to DataReady.");
1783       return dr;
1784    }
1785    
1786    inline
1787    DataReady*
1788    Data::getReady()
1789    {
1790       DataReady* dr=dynamic_cast<DataReady*>(m_data.get());
1791       EsysAssert((dr!=0), "Error - casting to DataReady.");
1792       return dr;
1793    }
1794    
1795    // Be wary of using this for local operations since it (temporarily) increases reference count.
1796    // If you are just using this to call a method on DataReady instead of DataAbstract consider using
1797    // getReady() instead
1798    inline
1799    DataReady_ptr
1800    Data::getReadyPtr()
1801    {
1802       DataReady_ptr dr=boost::dynamic_pointer_cast<DataReady>(m_data);
1803       EsysAssert((dr.get()!=0), "Error - casting to DataReady.");
1804       return dr;
1805    }
1806    
1807    
1808    inline
1809    const_DataReady_ptr
1810    Data::getReadyPtr() const
1811    {
1812       const_DataReady_ptr dr=boost::dynamic_pointer_cast<const DataReady>(m_data);
1813       EsysAssert((dr.get()!=0), "Error - casting to DataReady.");
1814       return dr;
1815    }
1816    
1817    inline
1818    DataAbstract::ValueType::value_type*
1819    Data::getSampleDataRW(DataAbstract::ValueType::size_type sampleNo)
1820    {
1821       if (isLazy())
1822       {
1823        throw DataException("Error, attempt to acquire RW access to lazy data. Please call requireWrite() first.");
1824       }
1825       return getReady()->getSampleDataRW(sampleNo);
1826  }  }
1827    
1828    inline
1829    const DataAbstract::ValueType::value_type*
1830    Data::getSampleDataRO(DataAbstract::ValueType::size_type sampleNo, BufferGroup* bufferg)
1831    {
1832       DataLazy* l=dynamic_cast<DataLazy*>(m_data.get());
1833       if (l!=0)
1834       {
1835        size_t offset=0;
1836        if (bufferg==NULL)
1837        {
1838            throw DataException("Error, attempt to getSampleDataRO for lazy Data with buffer==NULL");
1839        }
1840        const DataTypes::ValueType* res=l->resolveSample(*bufferg,sampleNo,offset);
1841        return &((*res)[offset]);
1842       }
1843       return getReady()->getSampleDataRO(sampleNo);
1844    }
1845    
1846    
1847    
1848    /**
1849       Modify a filename for MPI parallel output to multiple files
1850    */
1851    char *Escript_MPI_appendRankToFileName(const char *, int, int);
1852    
1853  /**  /**
1854     Binary Data object operators.     Binary Data object operators.
1855  */  */
# Line 1519  ESCRIPT_DLL_API std::ostream& operator<< Line 1961  ESCRIPT_DLL_API std::ostream& operator<<
1961  /**  /**
1962    \brief    \brief
1963    Compute a tensor product of two Data objects    Compute a tensor product of two Data objects
1964    \param arg0 - Input - Data object    \param arg_0 - Input - Data object
1965    \param arg1 - Input - Data object    \param arg_1 - Input - Data object
1966    \param axis_offset - Input - axis offset    \param axis_offset - Input - axis offset
1967    \param transpose - Input - 0: transpose neither, 1: transpose arg0, 2: transpose arg1    \param transpose - Input - 0: transpose neither, 1: transpose arg0, 2: transpose arg1
1968  */  */
1969  ESCRIPT_DLL_API  ESCRIPT_DLL_API
1970  Data  Data
1971  C_GeneralTensorProduct(Data& arg0,  C_GeneralTensorProduct(Data& arg_0,
1972                       Data& arg1,                       Data& arg_1,
1973                       int axis_offset=0,                       int axis_offset=0,
1974                       int transpose=0);                       int transpose=0);
1975    
   
 /**  
   \brief  
   Compute a tensor operation with two Data objects  
   \param arg0 - Input - Data object  
   \param arg1 - Input - Data object  
   \param operation - Input - Binary op functor  
 */  
 template <typename BinaryFunction>  
 ESCRIPT_DLL_API  
 Data  
 C_TensorBinaryOperation(Data const &arg0,  
                         Data const &arg1,  
                         BinaryFunction operation);  
   
 /**  
   \brief  
   Return true if operands are equivalent, else return false.  
   NB: this operator does very little at this point, and isn't to  
   be relied on. Requires further implementation.  
 */  
 // ESCRIPT_DLL_API bool operator==(const Data& left, const Data& right);  
   
1976  /**  /**
1977    \brief    \brief
1978    Perform the given binary operation with this and right as operands.    Perform the given binary operation with this and right as operands.
# Line 1567  Data::binaryOp(const Data& right, Line 1986  Data::binaryOp(const Data& right,
1986  {  {
1987     //     //
1988     // if this has a rank of zero promote it to the rank of the RHS     // if this has a rank of zero promote it to the rank of the RHS
1989     if (getPointDataView().getRank()==0 && right.getPointDataView().getRank()!=0) {     if (getDataPointRank()==0 && right.getDataPointRank()!=0) {
1990       throw DataException("Error - attempt to update rank zero object with object with rank bigger than zero.");       throw DataException("Error - attempt to update rank zero object with object with rank bigger than zero.");
1991     }     }
1992    
1993       if (isLazy() || right.isLazy())
1994       {
1995         throw DataException("Programmer error - attempt to call binaryOp with Lazy Data.");
1996       }
1997     //     //
1998     // initially make the temporary a shallow copy     // initially make the temporary a shallow copy
1999     Data tempRight(right);     Data tempRight(right);
2000    
2001     if (getFunctionSpace()!=right.getFunctionSpace()) {     if (getFunctionSpace()!=right.getFunctionSpace()) {
2002       if (right.probeInterpolation(getFunctionSpace())) {       if (right.probeInterpolation(getFunctionSpace())) {
2003         //         //
# Line 1582  Data::binaryOp(const Data& right, Line 2007  Data::binaryOp(const Data& right,
2007         //         //
2008         // interpolate onto the RHS function space         // interpolate onto the RHS function space
2009         Data tempLeft(*this,right.getFunctionSpace());         Data tempLeft(*this,right.getFunctionSpace());
2010         m_data=tempLeft.m_data;  //        m_data=tempLeft.m_data;
2011           set_m_data(tempLeft.m_data);
2012       }       }
2013     }     }
2014     operandCheck(tempRight);     operandCheck(tempRight);
# Line 1598  Data::binaryOp(const Data& right, Line 2024  Data::binaryOp(const Data& right,
2024       // of any data type       // of any data type
2025       DataExpanded* leftC=dynamic_cast<DataExpanded*>(m_data.get());       DataExpanded* leftC=dynamic_cast<DataExpanded*>(m_data.get());
2026       EsysAssert((leftC!=0), "Programming error - casting to DataExpanded.");       EsysAssert((leftC!=0), "Programming error - casting to DataExpanded.");
2027       escript::binaryOp(*leftC,*(tempRight.m_data.get()),operation);       escript::binaryOp(*leftC,*(tempRight.getReady()),operation);
2028     } else if (isTagged()) {     } else if (isTagged()) {
2029       //       //
2030       // Tagged data is operated on serially, the right hand side can be       // Tagged data is operated on serially, the right hand side can be
# Line 1646  Data::algorithm(BinaryFunction operation Line 2072  Data::algorithm(BinaryFunction operation
2072      DataConstant* leftC=dynamic_cast<DataConstant*>(m_data.get());      DataConstant* leftC=dynamic_cast<DataConstant*>(m_data.get());
2073      EsysAssert((leftC!=0), "Programming error - casting to DataConstant.");      EsysAssert((leftC!=0), "Programming error - casting to DataConstant.");
2074      return escript::algorithm(*leftC,operation,initial_value);      return escript::algorithm(*leftC,operation,initial_value);
2075      } else if (isEmpty()) {
2076        throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2077      } else if (isLazy()) {
2078        throw DataException("Error - Operations not permitted on instances of DataLazy.");
2079      } else {
2080        throw DataException("Error - Data encapsulates an unknown type.");
2081    }    }
   return 0;  
2082  }  }
2083    
2084  /**  /**
# Line 1663  inline Line 2094  inline
2094  Data  Data
2095  Data::dp_algorithm(BinaryFunction operation, double initial_value) const  Data::dp_algorithm(BinaryFunction operation, double initial_value) const
2096  {  {
2097    if (isExpanded()) {    if (isEmpty()) {
2098      Data result(0,DataArrayView::ShapeType(),getFunctionSpace(),isExpanded());      throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2099      }
2100      else if (isExpanded()) {
2101        Data result(0,DataTypes::ShapeType(),getFunctionSpace(),isExpanded());
2102      DataExpanded* dataE=dynamic_cast<DataExpanded*>(m_data.get());      DataExpanded* dataE=dynamic_cast<DataExpanded*>(m_data.get());
2103      DataExpanded* resultE=dynamic_cast<DataExpanded*>(result.m_data.get());      DataExpanded* resultE=dynamic_cast<DataExpanded*>(result.m_data.get());
2104      EsysAssert((dataE!=0), "Programming error - casting data to DataExpanded.");      EsysAssert((dataE!=0), "Programming error - casting data to DataExpanded.");
2105      EsysAssert((resultE!=0), "Programming error - casting result to DataExpanded.");      EsysAssert((resultE!=0), "Programming error - casting result to DataExpanded.");
2106      escript::dp_algorithm(*dataE,*resultE,operation,initial_value);      escript::dp_algorithm(*dataE,*resultE,operation,initial_value);
2107      return result;      return result;
2108    } else if (isTagged()) {    }
2109      else if (isTagged()) {
2110      DataTagged* dataT=dynamic_cast<DataTagged*>(m_data.get());      DataTagged* dataT=dynamic_cast<DataTagged*>(m_data.get());
     DataArrayView::ShapeType viewShape;  
     DataArrayView::ValueType viewData(1);  
     viewData[0]=0;  
     DataArrayView defaultValue(viewData,viewShape);  
     DataTagged::TagListType keys;  
     DataTagged::ValueListType values;  
     DataTagged::DataMapType::const_iterator i;  
     for (i=dataT->getTagLookup().begin();i!=dataT->getTagLookup().end();i++) {  
       keys.push_back(i->first);  
       values.push_back(defaultValue);  
     }  
     Data result(keys,values,defaultValue,getFunctionSpace());  
     DataTagged* resultT=dynamic_cast<DataTagged*>(result.m_data.get());  
2111      EsysAssert((dataT!=0), "Programming error - casting data to DataTagged.");      EsysAssert((dataT!=0), "Programming error - casting data to DataTagged.");
2112      EsysAssert((resultT!=0), "Programming error - casting result to DataTagged.");      DataTypes::ValueType defval(1);
2113        defval[0]=0;
2114        DataTagged* resultT=new DataTagged(getFunctionSpace(), DataTypes::scalarShape, defval, dataT);
2115      escript::dp_algorithm(*dataT,*resultT,operation,initial_value);      escript::dp_algorithm(*dataT,*resultT,operation,initial_value);
2116      return result;      return Data(resultT);   // note: the Data object now owns the resultT pointer
2117    } else if (isConstant()) {    }
2118      Data result(0,DataArrayView::ShapeType(),getFunctionSpace(),isExpanded());    else if (isConstant()) {
2119        Data result(0,DataTypes::ShapeType(),getFunctionSpace(),isExpanded());
2120      DataConstant* dataC=dynamic_cast<DataConstant*>(m_data.get());      DataConstant* dataC=dynamic_cast<DataConstant*>(m_data.get());
2121      DataConstant* resultC=dynamic_cast<DataConstant*>(result.m_data.get());      DataConstant* resultC=dynamic_cast<DataConstant*>(result.m_data.get());
2122      EsysAssert((dataC!=0), "Programming error - casting data to DataConstant.");      EsysAssert((dataC!=0), "Programming error - casting data to DataConstant.");
2123      EsysAssert((resultC!=0), "Programming error - casting result to DataConstant.");      EsysAssert((resultC!=0), "Programming error - casting result to DataConstant.");
2124      escript::dp_algorithm(*dataC,*resultC,operation,initial_value);      escript::dp_algorithm(*dataC,*resultC,operation,initial_value);
2125      return result;      return result;
2126      } else if (isLazy()) {
2127        throw DataException("Error - Operations not permitted on instances of DataLazy.");
2128      } else {
2129        throw DataException("Error - Data encapsulates an unknown type.");
2130    }    }
   Data falseRetVal; // to keep compiler quiet  
   return falseRetVal;  
2131  }  }
2132    
2133    /**
2134      \brief
2135      Compute a tensor operation with two Data objects
2136      \param arg_0 - Input - Data object
2137      \param arg_1 - Input - Data object
2138      \param operation - Input - Binary op functor
2139    */
2140  template <typename BinaryFunction>  template <typename BinaryFunction>
2141    inline
2142  Data  Data
2143  C_TensorBinaryOperation(Data const &arg_0,  C_TensorBinaryOperation(Data const &arg_0,
2144                          Data const &arg_1,                          Data const &arg_1,
2145                          BinaryFunction operation)                          BinaryFunction operation)
2146  {  {
2147      if (arg_0.isEmpty() || arg_1.isEmpty())
2148      {
2149         throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2150      }
2151      if (arg_0.isLazy() || arg_1.isLazy())
2152      {
2153         throw DataException("Error - Operations not permitted on lazy data.");
2154      }
2155    // Interpolate if necessary and find an appropriate function space    // Interpolate if necessary and find an appropriate function space
2156    Data arg_0_Z, arg_1_Z;    Data arg_0_Z, arg_1_Z;
2157    if (arg_0.getFunctionSpace()!=arg_1.getFunctionSpace()) {    if (arg_0.getFunctionSpace()!=arg_1.getFunctionSpace()) {
# Line 1730  C_TensorBinaryOperation(Data const &arg_ Line 2173  C_TensorBinaryOperation(Data const &arg_
2173    // Get rank and shape of inputs    // Get rank and shape of inputs
2174    int rank0 = arg_0_Z.getDataPointRank();    int rank0 = arg_0_Z.getDataPointRank();
2175    int rank1 = arg_1_Z.getDataPointRank();    int rank1 = arg_1_Z.getDataPointRank();
2176    DataArrayView::ShapeType shape0 = arg_0_Z.getDataPointShape();    DataTypes::ShapeType shape0 = arg_0_Z.getDataPointShape();
2177    DataArrayView::ShapeType shape1 = arg_1_Z.getDataPointShape();    DataTypes::ShapeType shape1 = arg_1_Z.getDataPointShape();
2178    int size0 = arg_0_Z.getDataPointSize();    int size0 = arg_0_Z.getDataPointSize();
2179    int size1 = arg_1_Z.getDataPointSize();    int size1 = arg_1_Z.getDataPointSize();
   
2180    // Declare output Data object    // Declare output Data object
2181    Data res;    Data res;
2182    
2183    if (shape0 == shape1) {    if (shape0 == shape1) {
   
2184      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2185        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output
2186        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2187        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2188        double *ptr_2 = &((res.getPointDataView().getData())[0]);        double *ptr_2 = &(res.getDataAtOffsetRW(0));
2189    
2190        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2191      }      }
2192      else if (arg_0_Z.isConstant()   && arg_1_Z.isTagged()) {      else if (arg_0_Z.isConstant()   && arg_1_Z.isTagged()) {
# Line 1762  C_TensorBinaryOperation(Data const &arg_ Line 2204  C_TensorBinaryOperation(Data const &arg_
2204    
2205        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2206        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2207        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2208        // Get the views  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2209        // Get the pointers to the actual data        // Get the pointers to the actual data
2210        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2211        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2212    
2213        // Compute a result for the default        // Compute a result for the default
2214        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2215        // Compute a result for each tag        // Compute a result for each tag
2216        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2217        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
2218        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2219          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2220          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2221          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2222          double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2223          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2224        }        }
2225    
2226      }      }
2227      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {
   
2228        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2229        DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());        DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());
2230        DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData());        DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData());
# Line 1795  C_TensorBinaryOperation(Data const &arg_ Line 2234  C_TensorBinaryOperation(Data const &arg_
2234        int numSamples_1 = arg_1_Z.getNumSamples();        int numSamples_1 = arg_1_Z.getNumSamples();
2235        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2236        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2237          res.requireWrite();
2238        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2239        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2240          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2241            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2242            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2243            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2244            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2245            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2246            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2247          }          }
2248        }        }
2249    
2250      }      }
2251      else if (arg_0_Z.isTagged()     && arg_1_Z.isConstant()) {      else if (arg_0_Z.isTagged()     && arg_1_Z.isConstant()) {
   
2252        // Borrow DataTagged input from Data object        // Borrow DataTagged input from Data object
2253        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2254    
# Line 1823  C_TensorBinaryOperation(Data const &arg_ Line 2262  C_TensorBinaryOperation(Data const &arg_
2262    
2263        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2264        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2265        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);  
2266        // Get the views        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2267        // Get the pointers to the actual data        // Get the pointers to the actual data
2268        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2269        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2270        // Compute a result for the default        // Compute a result for the default
2271        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2272        // Compute a result for each tag        // Compute a result for each tag
2273        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2274        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
2275        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2276          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2277          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2278          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_2 = &view_2.getData(0);  
2279          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2280        }        }
2281    
2282      }      }
2283      else if (arg_0_Z.isTagged()     && arg_1_Z.isTagged()) {      else if (arg_0_Z.isTagged()     && arg_1_Z.isTagged()) {
   
2284        // Borrow DataTagged input from Data object        // Borrow DataTagged input from Data object
2285        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2286    
# Line 1858  C_TensorBinaryOperation(Data const &arg_ Line 2292  C_TensorBinaryOperation(Data const &arg_
2292        res.tag();        // DataTagged output        res.tag();        // DataTagged output
2293        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2294    
       // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2295        // Get the pointers to the actual data        // Get the pointers to the actual data
2296        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2297        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2298        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2299    
2300        // Compute a result for the default        // Compute a result for the default
2301        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2302        // Merge the tags        // Merge the tags
# Line 1873  C_TensorBinaryOperation(Data const &arg_ Line 2304  C_TensorBinaryOperation(Data const &arg_
2304        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2305        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2306        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2307          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue()); // use tmp_2 to get correct shape          tmp_2->addTag(i->first); // use tmp_2 to get correct shape
2308        }        }
2309        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2310          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2311        }        }
2312        // Compute a result for each tag        // Compute a result for each tag
2313        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2314        for (i=lookup_2.begin();i!=lookup_2.end();i++) {        for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2315          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);  
2316          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2317          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2318          double *ptr_0 = &view_0.getData(0);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2319          double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2320          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2321        }        }
2322    
2323      }      }
2324      else if (arg_0_Z.isTagged()     && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isTagged()     && arg_1_Z.isExpanded()) {
   
2325        // After finding a common function space above the two inputs have the same numSamples and num DPPS        // After finding a common function space above the two inputs have the same numSamples and num DPPS
2326        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2327        DataTagged*   tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());        DataTagged*   tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
# Line 1902  C_TensorBinaryOperation(Data const &arg_ Line 2331  C_TensorBinaryOperation(Data const &arg_
2331        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2332        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2333        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2334          res.requireWrite();
2335        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2336        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2337          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
2338          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2339          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2340            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2341            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2342            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2343            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2344            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2345          }          }
2346        }        }
2347    
2348      }      }
2349      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {
   
2350        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2351        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2352        DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());        DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());
# Line 1927  C_TensorBinaryOperation(Data const &arg_ Line 2356  C_TensorBinaryOperation(Data const &arg_
2356        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2357        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2358        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2359          res.requireWrite();
2360        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2361        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2362          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2363            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2364            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2365            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);  
2366            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2367            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2368              double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2369    
2370    
2371            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2372          }          }
2373        }        }
2374    
2375      }      }
2376      else if (arg_0_Z.isExpanded()   && arg_1_Z.isTagged()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isTagged()) {
   
2377        // After finding a common function space above the two inputs have the same numSamples and num DPPS        // After finding a common function space above the two inputs have the same numSamples and num DPPS
2378        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2379        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
# Line 1951  C_TensorBinaryOperation(Data const &arg_ Line 2383  C_TensorBinaryOperation(Data const &arg_
2383        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2384        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2385        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2386          res.requireWrite();
2387        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2388        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2389          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2390          double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2391          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2392            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2393            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2394            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2395            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2396            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2397          }          }
2398        }        }
2399    
2400      }      }
2401      else if (arg_0_Z.isExpanded()   && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isExpanded()) {
   
2402        // After finding a common function space above the two inputs have the same numSamples and num DPPS        // After finding a common function space above the two inputs have the same numSamples and num DPPS
2403        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2404        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
# Line 1976  C_TensorBinaryOperation(Data const &arg_ Line 2408  C_TensorBinaryOperation(Data const &arg_
2408        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2409        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2410        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2411          res.requireWrite();
2412        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2413        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2414          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2415            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2416            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2417            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2418            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2419            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2420            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2421            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2422          }          }
2423        }        }
# Line 1995  C_TensorBinaryOperation(Data const &arg_ Line 2428  C_TensorBinaryOperation(Data const &arg_
2428      }      }
2429    
2430    } else if (0 == rank0) {    } else if (0 == rank0) {
   
2431      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2432        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace());      // DataConstant output        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace());      // DataConstant output
2433        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2434        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2435        double *ptr_2 = &((res.getPointDataView().getData())[0]);        double *ptr_2 = &(res.getDataAtOffsetRW(0));
2436        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2437      }      }
2438      else if (arg_0_Z.isConstant()   && arg_1_Z.isTagged()) {      else if (arg_0_Z.isConstant()   && arg_1_Z.isTagged()) {
# Line 2018  C_TensorBinaryOperation(Data const &arg_ Line 2450  C_TensorBinaryOperation(Data const &arg_
2450    
2451        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2452        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2453        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2454        // Get the views  
2455        DataArrayView view_1 = tmp_1->getDefaultValue();        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2456        DataArrayView view_2 = tmp_2->getDefaultValue();        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2457        // Get the pointers to the actual data  
       double *ptr_1 = &((view_1.getData())[0]);  
       double *ptr_2 = &((view_2.getData())[0]);  
2458        // Compute a result for the default        // Compute a result for the default
2459        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2460        // Compute a result for each tag        // Compute a result for each tag
2461        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2462        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
2463        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2464          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2465          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2466          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
         double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2467          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2468        }        }
2469    
# Line 2051  C_TensorBinaryOperation(Data const &arg_ Line 2479  C_TensorBinaryOperation(Data const &arg_
2479        int numSamples_1 = arg_1_Z.getNumSamples();        int numSamples_1 = arg_1_Z.getNumSamples();
2480        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2481        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2482          res.requireWrite();
2483        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2484        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2485          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2486            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2487            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2488            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2489            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2490            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2491            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2492    
2493          }          }
# Line 2080  C_TensorBinaryOperation(Data const &arg_ Line 2509  C_TensorBinaryOperation(Data const &arg_
2509    
2510        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2511        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2512        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2513        // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2514        // Get the pointers to the actual data        // Get the pointers to the actual data
2515        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2516        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2517    
2518    
2519        // Compute a result for the default        // Compute a result for the default
2520        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2521        // Compute a result for each tag        // Compute a result for each tag
2522        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2523        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
2524        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2525          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2526          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2527          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2528          double *ptr_0 = &view_0.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2529          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2530        }        }
2531    
# Line 2115  C_TensorBinaryOperation(Data const &arg_ Line 2543  C_TensorBinaryOperation(Data const &arg_
2543        res.tag();        // DataTagged output        res.tag();        // DataTagged output
2544        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2545    
       // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2546        // Get the pointers to the actual data        // Get the pointers to the actual data
2547        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2548        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2549        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2550    
2551        // Compute a result for the default        // Compute a result for the default
2552        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2553        // Merge the tags        // Merge the tags
# Line 2130  C_TensorBinaryOperation(Data const &arg_ Line 2555  C_TensorBinaryOperation(Data const &arg_
2555        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2556        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2557        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2558          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue()); // use tmp_2 to get correct shape          tmp_2->addTag(i->first); // use tmp_2 to get correct shape
2559        }        }
2560        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2561          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2562        }        }
2563        // Compute a result for each tag        // Compute a result for each tag
2564        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2565        for (i=lookup_2.begin();i!=lookup_2.end();i++) {        for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2566          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2567          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2568          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2569          double *ptr_0 = &view_0.getData(0);  
         double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2570          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2571        }        }
2572    
# Line 2159  C_TensorBinaryOperation(Data const &arg_ Line 2582  C_TensorBinaryOperation(Data const &arg_
2582        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2583        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2584        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2585          res.requireWrite();
2586        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2587        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2588          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
2589          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2590          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2591            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2592            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2593            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2594            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2595            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2596          }          }
2597        }        }
2598    
2599      }      }
2600      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {
   
2601        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2602        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2603        DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());        DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());
# Line 2184  C_TensorBinaryOperation(Data const &arg_ Line 2607  C_TensorBinaryOperation(Data const &arg_
2607        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2608        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2609        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2610          res.requireWrite();
2611        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2612        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2613          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2614            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2615            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2616            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2617            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2618            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2619            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2620          }          }
2621        }        }
# Line 2209  C_TensorBinaryOperation(Data const &arg_ Line 2633  C_TensorBinaryOperation(Data const &arg_
2633        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2634        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2635        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2636          res.requireWrite();
2637        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2638        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2639          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2640          double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2641          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2642            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2643            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2644            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2645            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2646            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2647          }          }
2648        }        }
# Line 2234  C_TensorBinaryOperation(Data const &arg_ Line 2659  C_TensorBinaryOperation(Data const &arg_
2659        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2660        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2661        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2662          res.requireWrite();
2663        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2664        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2665          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2666            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2667            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2668            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2669            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2670            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2671            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2672            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2673          }          }
2674        }        }
# Line 2253  C_TensorBinaryOperation(Data const &arg_ Line 2679  C_TensorBinaryOperation(Data const &arg_
2679      }      }
2680    
2681    } else if (0 == rank1) {    } else if (0 == rank1) {
   
2682      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2683        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output
2684        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2685        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2686        double *ptr_2 = &((res.getPointDataView().getData())[0]);        double *ptr_2 = &(res.getDataAtOffsetRW(0));
2687        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2688      }      }
2689      else if (arg_0_Z.isConstant()   && arg_1_Z.isTagged()) {      else if (arg_0_Z.isConstant()   && arg_1_Z.isTagged()) {
# Line 2276  C_TensorBinaryOperation(Data const &arg_ Line 2701  C_TensorBinaryOperation(Data const &arg_
2701    
2702        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2703        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2704        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2705        // Get the views  
2706        DataArrayView view_1 = tmp_1->getDefaultValue();        //Get the pointers to the actual data
2707        DataArrayView view_2 = tmp_2->getDefaultValue();        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2708        // Get the pointers to the actual data        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2709        double *ptr_1 = &((view_1.getData())[0]);  
       double *ptr_2 = &((view_2.getData())[0]);  
2710        // Compute a result for the default        // Compute a result for the default
2711        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2712        // Compute a result for each tag        // Compute a result for each tag
2713        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2714        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
2715        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2716          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2717          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2718          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
         double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2719          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2720        }        }
   
2721      }      }
2722      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {
2723    
# Line 2309  C_TensorBinaryOperation(Data const &arg_ Line 2730  C_TensorBinaryOperation(Data const &arg_
2730        int numSamples_1 = arg_1_Z.getNumSamples();        int numSamples_1 = arg_1_Z.getNumSamples();
2731        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2732        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2733          res.requireWrite();
2734        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2735        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2736          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2737            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2738            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2739            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2740            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2741            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2742            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2743          }          }
2744        }        }
# Line 2337  C_TensorBinaryOperation(Data const &arg_ Line 2759  C_TensorBinaryOperation(Data const &arg_
2759    
2760        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2761        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2762        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
       // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2763        // Get the pointers to the actual data        // Get the pointers to the actual data
2764        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2765        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2766        // Compute a result for the default        // Compute a result for the default
2767        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2768        // Compute a result for each tag        // Compute a result for each tag
2769        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2770        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
2771        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2772          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2773          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2774          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_2 = &view_2.getData(0);  
2775          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2776        }        }
2777    
# Line 2372  C_TensorBinaryOperation(Data const &arg_ Line 2789  C_TensorBinaryOperation(Data const &arg_
2789        res.tag();        // DataTagged output        res.tag();        // DataTagged output
2790        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2791    
       // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2792        // Get the pointers to the actual data        // Get the pointers to the actual data
2793        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2794        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2795        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2796    
2797        // Compute a result for the default        // Compute a result for the default
2798        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2799        // Merge the tags        // Merge the tags
# Line 2387  C_TensorBinaryOperation(Data const &arg_ Line 2801  C_TensorBinaryOperation(Data const &arg_
2801        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2802        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2803        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2804          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue()); // use tmp_2 to get correct shape          tmp_2->addTag(i->first); // use tmp_2 to get correct shape
2805        }        }
2806        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2807          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2808        }        }
2809        // Compute a result for each tag        // Compute a result for each tag
2810        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2811        for (i=lookup_2.begin();i!=lookup_2.end();i++) {        for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2812          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2813          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2814          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);  
2815          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2816        }        }
2817    
# Line 2416  C_TensorBinaryOperation(Data const &arg_ Line 2827  C_TensorBinaryOperation(Data const &arg_
2827        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2828        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2829        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2830          res.requireWrite();
2831        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2832        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2833          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
2834          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2835          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2836            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2837            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2838            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2839            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2840            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2841          }          }
2842        }        }
2843    
2844      }      }
2845      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {
   
2846        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2847        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2848        DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());        DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());
# Line 2441  C_TensorBinaryOperation(Data const &arg_ Line 2852  C_TensorBinaryOperation(Data const &arg_
2852        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2853        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2854        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2855          res.requireWrite();
2856        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2857        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2858          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2859            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2860            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2861            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2862            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2863            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2864            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2865          }          }
2866        }        }
# Line 2466  C_TensorBinaryOperation(Data const &arg_ Line 2878  C_TensorBinaryOperation(Data const &arg_
2878        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2879        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2880        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2881          res.requireWrite();
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_1 = tmp_1->getPointOffset(sampleNo_0,0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2885          double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2886          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2887            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->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_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2890            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2891            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2892          }          }
2893        }        }
# Line 2491  C_TensorBinaryOperation(Data const &arg_ Line 2904  C_TensorBinaryOperation(Data const &arg_
2904        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2905        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2906        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2907          res.requireWrite();
2908        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2909        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2910          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2911            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2912            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->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.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2915            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2916            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2917            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2918          }          }
2919        }        }
# Line 2521  Data Line 2935  Data
2935  C_TensorUnaryOperation(Data const &arg_0,  C_TensorUnaryOperation(Data const &arg_0,
2936                         UnaryFunction operation)                         UnaryFunction operation)
2937  {  {
2938      if (arg_0.isEmpty())  // do this before we attempt to interpolate
2939      {
2940         throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2941      }
2942      if (arg_0.isLazy())
2943      {
2944         throw DataException("Error - Operations not permitted on lazy data.");
2945      }
2946    // Interpolate if necessary and find an appropriate function space    // Interpolate if necessary and find an appropriate function space
2947    Data arg_0_Z = Data(arg_0);    Data arg_0_Z = Data(arg_0);
2948    
2949    // Get rank and shape of inputs    // Get rank and shape of inputs
2950    int rank0 = arg_0_Z.getDataPointRank();    const DataTypes::ShapeType& shape0 = arg_0_Z.getDataPointShape();
   DataArrayView::ShapeType shape0 = arg_0_Z.getDataPointShape();  
2951    int size0 = arg_0_Z.getDataPointSize();    int size0 = arg_0_Z.getDataPointSize();
2952    
2953    // Declare output Data object    // Declare output Data object
# Line 2534  C_TensorUnaryOperation(Data const &arg_0 Line 2955  C_TensorUnaryOperation(Data const &arg_0
2955    
2956    if (arg_0_Z.isConstant()) {    if (arg_0_Z.isConstant()) {
2957      res = Data(0.0, shape0, arg_0_Z.getFunctionSpace());      // DataConstant output      res = Data(0.0, shape0, arg_0_Z.getFunctionSpace());      // DataConstant output
2958      double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);      const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2959      double *ptr_2 = &((res.getPointDataView().getData())[0]);      double *ptr_2 = &(res.getDataAtOffsetRW(0));
2960      tensor_unary_operation(size0, ptr_0, ptr_2, operation);      tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2961    }    }
2962    else if (arg_0_Z.isTagged()) {    else if (arg_0_Z.isTagged()) {
# Line 2548  C_TensorUnaryOperation(Data const &arg_0 Line 2969  C_TensorUnaryOperation(Data const &arg_0
2969      res.tag();      res.tag();
2970      DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());      DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2971    
     // Get the views  
     DataArrayView view_0 = tmp_0->getDefaultValue();  
     DataArrayView view_2 = tmp_2->getDefaultValue();  
2972      // Get the pointers to the actual data      // Get the pointers to the actual data
2973      double *ptr_0 = &((view_0.getData())[0]);      const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2974      double *ptr_2 = &((view_2.getData())[0]);      double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2975      // Compute a result for the default      // Compute a result for the default
2976      tensor_unary_operation(size0, ptr_0, ptr_2, operation);      tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2977      // Compute a result for each tag      // Compute a result for each tag
2978      const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();      const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2979      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
2980      for (i=lookup_0.begin();i!=lookup_0.end();i++) {      for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2981        tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());        tmp_2->addTag(i->first);
2982        DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);        const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2983        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_2 = &view_2.getData(0);  
2984        tensor_unary_operation(size0, ptr_0, ptr_2, operation);        tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2985      }      }
2986    
# Line 2583  C_TensorUnaryOperation(Data const &arg_0 Line 2999  C_TensorUnaryOperation(Data const &arg_0
2999        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
3000          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
3001          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
3002          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
3003          double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);          double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
3004          tensor_unary_operation(size0, ptr_0, ptr_2, operation);          tensor_unary_operation(size0, ptr_0, ptr_2, operation);
3005        }        }
3006      }      }
   
3007    }    }
3008    else {    else {
3009      throw DataException("Error - C_TensorUnaryOperation: unknown combination of inputs");      throw DataException("Error - C_TensorUnaryOperation: unknown combination of inputs");

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