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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 2521 by jfenwick, Tue Jul 7 00:08:58 2009 UTC
# Line 1  Line 1 
1    
 /* $Id$ */  
   
2  /*******************************************************  /*******************************************************
3   *  *
4   *           Copyright 2003-2007 by ACceSS MNRF  * Copyright (c) 2003-2008 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);
145    
146    /**    /**
147       \brief       \brief
148       Constructor which will create Tagged data if expanded is false.       Constructor which copies data from any object that can be treated like a python array/sequence.
      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);  
   
   /**  
      \brief  
      Constructor which copies data from any object that can be converted into  
      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.
      NOTE: Construction of the DataArrayView is a relatively expensive  
      operation.  
618       \param sampleNo - Input -       \param sampleNo - Input -
619       \param dataPointNo - Input -       \param dataPointNo - Input -
620    */    */
621    ESCRIPT_DLL_API    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 -
629         \param dataPointNo - Input -
630      */
631      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    
# Line 576  class Data { Line 691  class Data {
691       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
692       object to type DataTagged. Throws an exception if this object       object to type DataTagged. Throws an exception if this object
693       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.
694       \param tagKey - Input - Integer key.       \param name - Input - name of tag.
695       \param value - Input - Value to associate with given key.       \param value - Input - Value to associate with given key.
     ==>*  
696    */    */
697    ESCRIPT_DLL_API    ESCRIPT_DLL_API
698    void    void
# Line 605  class Data { Line 719  class Data {
719       object to type DataTagged if it is constant.       object to type DataTagged if it is constant.
720    
721       \param tagKey - Input - Integer key.       \param tagKey - Input - Integer key.
722         \param pointshape - Input - The shape of the value parameter
723       \param value - Input - Value to associate with given key.       \param value - Input - Value to associate with given key.
724      ==>*       \param dataOffset - Input - Offset of the begining of the point within the value parameter
725    */    */
726    ESCRIPT_DLL_API    ESCRIPT_DLL_API
727    void    void
728    setTaggedValueFromCPP(int tagKey,    setTaggedValueFromCPP(int tagKey,
729                          const DataArrayView& value);              const DataTypes::ShapeType& pointshape,
730                            const DataTypes::ValueType& value,
731                int dataOffset=0);
732    
733    
734    
735    /**    /**
736      \brief      \brief
# Line 659  class Data { Line 778  class Data {
778    grad() const;    grad() const;
779    
780    /**    /**
781       \brief      \brief
782       Calculate the integral over the function space domain.       Calculate the integral over the function space domain as a python tuple.
      *  
783    */    */
784    ESCRIPT_DLL_API    ESCRIPT_DLL_API
785    boost::python::numeric::array    boost::python::object
786    integrate() const;    integrateToTuple_const() const;
787    
788    
789      /**
790        \brief
791         Calculate the integral over the function space domain as a python tuple.
792      */
793      ESCRIPT_DLL_API
794      boost::python::object
795      integrateToTuple();
796    
797    
798    
799    /**    /**
800       \brief       \brief
# Line 732  class Data { Line 861  class Data {
861    /**    /**
862       \brief       \brief
863       Return the maximum absolute value of this Data object.       Return the maximum absolute value of this Data object.
864       *  
865         The method is not const because lazy data needs to be expanded before Lsup can be computed.
866         The _const form can be used when the Data object is const, however this will only work for
867         Data which is not Lazy.
868    
869         For Data which contain no samples (or tagged Data for which no tags in use have a value)
870         zero is returned.
871    */    */
872    ESCRIPT_DLL_API    ESCRIPT_DLL_API
873    double    double
874    Lsup() const;    Lsup();
875    
876      ESCRIPT_DLL_API
877      double
878      Lsup_const() const;
879    
880    
881    /**    /**
882       \brief       \brief
883       Return the maximum value of this Data object.       Return the maximum value of this Data object.
884       *  
885         The method is not const because lazy data needs to be expanded before sup can be computed.
886         The _const form can be used when the Data object is const, however this will only work for
887         Data which is not Lazy.
888    
889         For Data which contain no samples (or tagged Data for which no tags in use have a value)
890         a large negative value is returned.
891    */    */
892    ESCRIPT_DLL_API    ESCRIPT_DLL_API
893    double    double
894    sup() const;    sup();
895    
896      ESCRIPT_DLL_API
897      double
898      sup_const() const;
899    
900    
901    /**    /**
902       \brief       \brief
903       Return the minimum value of this Data object.       Return the minimum value of this Data object.
904       *  
905         The method is not const because lazy data needs to be expanded before inf can be computed.
906         The _const form can be used when the Data object is const, however this will only work for
907         Data which is not Lazy.
908    
909         For Data which contain no samples (or tagged Data for which no tags in use have a value)
910         a large positive value is returned.
911    */    */
912    ESCRIPT_DLL_API    ESCRIPT_DLL_API
913    double    double
914    inf() const;    inf();
915    
916      ESCRIPT_DLL_API
917      double
918      inf_const() const;
919    
920    
921    
922    /**    /**
923       \brief       \brief
# Line 786  class Data { Line 949  class Data {
949    /**    /**
950       \brief       \brief
951       Return the (sample number, data-point number) of the data point with       Return the (sample number, data-point number) of the data point with
952       the minimum value in this Data object.       the minimum component value in this Data object.
953         \note If you are working in python, please consider using Locator
954    instead of manually manipulating process and point IDs.
955    */    */
956    ESCRIPT_DLL_API    ESCRIPT_DLL_API
957    const boost::python::tuple    const boost::python::tuple
958    minGlobalDataPoint() const;    minGlobalDataPoint() const;
959    
960      /**
961         \brief
962         Return the (sample number, data-point number) of the data point with
963         the minimum component value in this Data object.
964         \note If you are working in python, please consider using Locator
965    instead of manually manipulating process and point IDs.
966      */
967    ESCRIPT_DLL_API    ESCRIPT_DLL_API
968    void    const boost::python::tuple
969    calc_minGlobalDataPoint(int& ProcNo,  int& DataPointNo) const;    maxGlobalDataPoint() const;
970    
971    
972    
973    /**    /**
974       \brief       \brief
975       Return the sign of each data point of this Data object.       Return the sign of each data point of this Data object.
# Line 1212  class Data { Line 1387  class Data {
1387    */    */
1388    ESCRIPT_DLL_API    ESCRIPT_DLL_API
1389    Data    Data
1390    getSlice(const DataArrayView::RegionType& region) const;    getSlice(const DataTypes::RegionType& region) const;
1391    
1392    /**    /**
1393       \brief       \brief
# Line 1225  class Data { Line 1400  class Data {
1400    ESCRIPT_DLL_API    ESCRIPT_DLL_API
1401    void    void
1402    setSlice(const Data& value,    setSlice(const Data& value,
1403             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);  
   
1404    
1405    /**    /**
1406       \brief       \brief
# Line 1290  class Data { Line 1442  class Data {
1442    /**    /**
1443       \brief       \brief
1444       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
1445        TODO Ownership of this object should be explained in doco.
1446    */    */
1447    ESCRIPT_DLL_API    ESCRIPT_DLL_API
1448          DataAbstract*          DataAbstract*
1449          borrowData(void) const;          borrowData(void) const;
1450    
1451      ESCRIPT_DLL_API
1452            DataAbstract_ptr
1453            borrowDataPtr(void) const;
1454    
1455      ESCRIPT_DLL_API
1456            DataReady_ptr
1457            borrowReadyPtr(void) const;
1458    
1459    
1460    
1461      /**
1462         \brief
1463         Return a pointer to the beginning of the datapoint at the specified offset.
1464         TODO Eventually these should be inlined.
1465         \param i - position(offset) in the underlying datastructure
1466      */
1467    
1468      ESCRIPT_DLL_API
1469            DataTypes::ValueType::const_reference
1470            getDataAtOffsetRO(DataTypes::ValueType::size_type i);
1471    
1472    
1473      ESCRIPT_DLL_API
1474            DataTypes::ValueType::reference
1475            getDataAtOffsetRW(DataTypes::ValueType::size_type i);
1476    
1477    
1478    
1479    /**
1480       \brief Create a buffer for use by getSample
1481       Allocates a DataVector large enough for DataLazy::resolveSample to operate on for the current Data.
1482       Do not use this buffer for other Data instances (unless you are sure they will be the same size).
1483      
1484       In multi-threaded sections, this needs to be called on each thread.
1485    
1486       \return A BufferGroup* if Data is lazy, NULL otherwise.
1487       \warning This pointer must be deallocated using freeSampleBuffer to avoid cross library memory issues.
1488    */
1489      ESCRIPT_DLL_API
1490      BufferGroup*
1491      allocSampleBuffer() const;
1492    
1493    /**
1494       \brief Free a buffer allocated with allocSampleBuffer.
1495       \param buffer Input - pointer to the buffer to deallocate.
1496    */
1497    ESCRIPT_DLL_API void freeSampleBuffer(BufferGroup* buffer);
1498    
1499   protected:   protected:
1500    
1501   private:   private:
1502    
1503      double
1504      LsupWorker() const;
1505    
1506      double
1507      supWorker() const;
1508    
1509      double
1510      infWorker() const;
1511    
1512      boost::python::object
1513      integrateWorker() const;
1514    
1515      void
1516      calc_minGlobalDataPoint(int& ProcNo,  int& DataPointNo) const;
1517    
1518      void
1519      calc_maxGlobalDataPoint(int& ProcNo,  int& DataPointNo) const;
1520    
1521    
1522    /**    /**
1523       \brief       \brief
1524       Check *this and the right operand are compatible. Throws       Check *this and the right operand are compatible. Throws
# Line 1370  class Data { Line 1590  class Data {
1590       \brief       \brief
1591       Construct a Data object of the appropriate type.       Construct a Data object of the appropriate type.
1592    */    */
1593    template <class IValueType>  
1594    void    void
1595    initialise(const IValueType& value,    initialise(const DataTypes::ValueType& value,
1596             const DataTypes::ShapeType& shape,
1597               const FunctionSpace& what,               const FunctionSpace& what,
1598               bool expanded);               bool expanded);
1599    
1600      void
1601      initialise(const WrappedArray& value,
1602                     const FunctionSpace& what,
1603                     bool expanded);
1604    
1605    //    //
1606    // flag to protect the data object against any update    // flag to protect the data object against any update
1607    bool m_protected;    bool m_protected;
1608      mutable bool m_shared;
1609      bool m_lazy;
1610    
1611    //    //
1612    // pointer to the actual data object    // pointer to the actual data object
1613    boost::shared_ptr<DataAbstract> m_data;  //   boost::shared_ptr<DataAbstract> m_data;
1614      DataAbstract_ptr m_data;
1615    
1616  };  // If possible please use getReadyPtr instead.
1617    // But see warning below.
1618      const DataReady*
1619      getReady() const;
1620    
1621  template <class IValueType>    DataReady*
1622  void    getReady();
1623  Data::initialise(const IValueType& value,  
1624                   const FunctionSpace& what,  
1625                   bool expanded)  // Be wary of using this for local operations since it (temporarily) increases reference count.
1626  {  // If you are just using this to call a method on DataReady instead of DataAbstract consider using
1627    // getReady() instead
1628      DataReady_ptr
1629      getReadyPtr();
1630    
1631      const_DataReady_ptr
1632      getReadyPtr() const;
1633    
1634    
1635      /**
1636       \brief Update the Data's shared flag
1637       This indicates that the DataAbstract used by this object is now shared (or no longer shared).
1638       For internal use only.
1639      */
1640      void updateShareStatus(bool nowshared) const
1641      {
1642        m_shared=nowshared;     // m_shared is mutable
1643      }
1644    
1645      // In the isShared() method below:
1646      // A problem would occur if m_data (the address pointed to) were being modified
1647      // while the call m_data->is_shared is being executed.
1648      //
1649      // Q: So why do I think this code can be thread safe/correct?
1650      // A: We need to make some assumptions.
1651      // 1. We assume it is acceptable to return true under some conditions when we aren't shared.
1652      // 2. We assume that no constructions or assignments which will share previously unshared
1653      //    will occur while this call is executing. This is consistent with the way Data:: and C are written.
1654    //    //
1655    // 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
1656    // 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.
1657    // 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.
1658    // within the shared_ptr constructor.    // For any threads executing before the flag switches they will assume the object is still shared.
1659    if (expanded) {    bool isShared() const
1660      DataAbstract* temp=new DataExpanded(value,what);    {
1661      boost::shared_ptr<DataAbstract> temp_data(temp);      return m_shared;
1662      m_data=temp_data;  /*  if (m_shared) return true;
1663    } else {      if (m_data->isShared())        
1664      DataAbstract* temp=new DataConstant(value,what);      {                  
1665      boost::shared_ptr<DataAbstract> temp_data(temp);          updateShareStatus(true);
1666      m_data=temp_data;          return true;
1667        }
1668        return false;*/
1669      }
1670    
1671      void forceResolve()
1672      {
1673        if (isLazy())
1674        {
1675            #ifdef _OPENMP
1676            if (omp_in_parallel())
1677            {   // Yes this is throwing an exception out of an omp thread which is forbidden.
1678            throw DataException("Please do not call forceResolve() in a parallel region.");
1679            }
1680            #endif
1681            resolve();
1682        }
1683      }
1684    
1685      /**
1686      \brief if another object is sharing out member data make a copy to work with instead.
1687      This code should only be called from single threaded sections of code.
1688      */
1689      void exclusiveWrite()
1690      {
1691    #ifdef _OPENMP
1692      if (omp_in_parallel())
1693      {
1694    // *((int*)0)=17;
1695        throw DataException("Programming error. Please do not run exclusiveWrite() in multi-threaded sections.");
1696      }
1697    #endif
1698        forceResolve();
1699        if (isShared())
1700        {
1701            DataAbstract* t=m_data->deepCopy();
1702            set_m_data(DataAbstract_ptr(t));
1703        }
1704    }    }
1705    
1706      /**
1707      \brief checks if caller can have exclusive write to the object
1708      */
1709      void checkExclusiveWrite()
1710      {
1711        if  (isLazy() || isShared())
1712        {
1713            throw DataException("Programming error. ExclusiveWrite required - please call requireWrite()");
1714        }
1715      }
1716    
1717      /**
1718      \brief Modify the data abstract hosted by this Data object
1719      For internal use only.
1720      Passing a pointer to null is permitted (do this in the destructor)
1721      \warning Only to be called in single threaded code or inside a single/critical section. This method needs to be atomic.
1722      */
1723      void set_m_data(DataAbstract_ptr p);
1724    
1725      friend class DataAbstract;        // To allow calls to updateShareStatus
1726    
1727    };
1728    
1729    }   // end namespace escript
1730    
1731    
1732    // No, this is not supposed to be at the top of the file
1733    // DataAbstact needs to be declared first, then DataReady needs to be fully declared
1734    // so that I can dynamic cast between them below.
1735    #include "DataReady.h"
1736    #include "DataLazy.h"
1737    
1738    namespace escript
1739    {
1740    
1741    inline
1742    const DataReady*
1743    Data::getReady() const
1744    {
1745       const DataReady* dr=dynamic_cast<const DataReady*>(m_data.get());
1746       EsysAssert((dr!=0), "Error - casting to DataReady.");
1747       return dr;
1748  }  }
1749    
1750    inline
1751    DataReady*
1752    Data::getReady()
1753    {
1754       DataReady* dr=dynamic_cast<DataReady*>(m_data.get());
1755       EsysAssert((dr!=0), "Error - casting to DataReady.");
1756       return dr;
1757    }
1758    
1759    // Be wary of using this for local operations since it (temporarily) increases reference count.
1760    // If you are just using this to call a method on DataReady instead of DataAbstract consider using
1761    // getReady() instead
1762    inline
1763    DataReady_ptr
1764    Data::getReadyPtr()
1765    {
1766       DataReady_ptr dr=boost::dynamic_pointer_cast<DataReady>(m_data);
1767       EsysAssert((dr.get()!=0), "Error - casting to DataReady.");
1768       return dr;
1769    }
1770    
1771    
1772    inline
1773    const_DataReady_ptr
1774    Data::getReadyPtr() const
1775    {
1776       const_DataReady_ptr dr=boost::dynamic_pointer_cast<const DataReady>(m_data);
1777       EsysAssert((dr.get()!=0), "Error - casting to DataReady.");
1778       return dr;
1779    }
1780    
1781    inline
1782    DataAbstract::ValueType::value_type*
1783    Data::getSampleDataRW(DataAbstract::ValueType::size_type sampleNo)
1784    {
1785       if (isLazy())
1786       {
1787        throw DataException("Error, attempt to acquire RW access to lazy data. Please call requireWrite() first.");
1788       }
1789       return getReady()->getSampleDataRW(sampleNo);
1790    }
1791    
1792    inline
1793    const DataAbstract::ValueType::value_type*
1794    Data::getSampleDataRO(DataAbstract::ValueType::size_type sampleNo, BufferGroup* bufferg)
1795    {
1796       DataLazy* l=dynamic_cast<DataLazy*>(m_data.get());
1797       if (l!=0)
1798       {
1799        size_t offset=0;
1800        if (bufferg==NULL)
1801        {
1802            throw DataException("Error, attempt to getSampleDataRO for lazy Data with buffer==NULL");
1803        }
1804        const DataTypes::ValueType* res=l->resolveSample(*bufferg,sampleNo,offset);
1805        return &((*res)[offset]);
1806       }
1807       return getReady()->getSampleDataRO(sampleNo);
1808    }
1809    
1810    
1811    
1812    /**
1813       Modify a filename for MPI parallel output to multiple files
1814    */
1815    char *Escript_MPI_appendRankToFileName(const char *, int, int);
1816    
1817  /**  /**
1818     Binary Data object operators.     Binary Data object operators.
1819  */  */
# Line 1519  ESCRIPT_DLL_API std::ostream& operator<< Line 1925  ESCRIPT_DLL_API std::ostream& operator<<
1925  /**  /**
1926    \brief    \brief
1927    Compute a tensor product of two Data objects    Compute a tensor product of two Data objects
1928    \param arg0 - Input - Data object    \param arg_0 - Input - Data object
1929    \param arg1 - Input - Data object    \param arg_1 - Input - Data object
1930    \param axis_offset - Input - axis offset    \param axis_offset - Input - axis offset
1931    \param transpose - Input - 0: transpose neither, 1: transpose arg0, 2: transpose arg1    \param transpose - Input - 0: transpose neither, 1: transpose arg0, 2: transpose arg1
1932  */  */
1933  ESCRIPT_DLL_API  ESCRIPT_DLL_API
1934  Data  Data
1935  C_GeneralTensorProduct(Data& arg0,  C_GeneralTensorProduct(Data& arg_0,
1936                       Data& arg1,                       Data& arg_1,
1937                       int axis_offset=0,                       int axis_offset=0,
1938                       int transpose=0);                       int transpose=0);
1939    
   
 /**  
   \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);  
   
1940  /**  /**
1941    \brief    \brief
1942    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 1950  Data::binaryOp(const Data& right,
1950  {  {
1951     //     //
1952     // 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
1953     if (getPointDataView().getRank()==0 && right.getPointDataView().getRank()!=0) {     if (getDataPointRank()==0 && right.getDataPointRank()!=0) {
1954       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.");
1955     }     }
1956    
1957       if (isLazy() || right.isLazy())
1958       {
1959         throw DataException("Programmer error - attempt to call binaryOp with Lazy Data.");
1960       }
1961     //     //
1962     // initially make the temporary a shallow copy     // initially make the temporary a shallow copy
1963     Data tempRight(right);     Data tempRight(right);
1964    
1965     if (getFunctionSpace()!=right.getFunctionSpace()) {     if (getFunctionSpace()!=right.getFunctionSpace()) {
1966       if (right.probeInterpolation(getFunctionSpace())) {       if (right.probeInterpolation(getFunctionSpace())) {
1967         //         //
# Line 1582  Data::binaryOp(const Data& right, Line 1971  Data::binaryOp(const Data& right,
1971         //         //
1972         // interpolate onto the RHS function space         // interpolate onto the RHS function space
1973         Data tempLeft(*this,right.getFunctionSpace());         Data tempLeft(*this,right.getFunctionSpace());
1974         m_data=tempLeft.m_data;  //        m_data=tempLeft.m_data;
1975           set_m_data(tempLeft.m_data);
1976       }       }
1977     }     }
1978     operandCheck(tempRight);     operandCheck(tempRight);
# Line 1598  Data::binaryOp(const Data& right, Line 1988  Data::binaryOp(const Data& right,
1988       // of any data type       // of any data type
1989       DataExpanded* leftC=dynamic_cast<DataExpanded*>(m_data.get());       DataExpanded* leftC=dynamic_cast<DataExpanded*>(m_data.get());
1990       EsysAssert((leftC!=0), "Programming error - casting to DataExpanded.");       EsysAssert((leftC!=0), "Programming error - casting to DataExpanded.");
1991       escript::binaryOp(*leftC,*(tempRight.m_data.get()),operation);       escript::binaryOp(*leftC,*(tempRight.getReady()),operation);
1992     } else if (isTagged()) {     } else if (isTagged()) {
1993       //       //
1994       // 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 2036  Data::algorithm(BinaryFunction operation
2036      DataConstant* leftC=dynamic_cast<DataConstant*>(m_data.get());      DataConstant* leftC=dynamic_cast<DataConstant*>(m_data.get());
2037      EsysAssert((leftC!=0), "Programming error - casting to DataConstant.");      EsysAssert((leftC!=0), "Programming error - casting to DataConstant.");
2038      return escript::algorithm(*leftC,operation,initial_value);      return escript::algorithm(*leftC,operation,initial_value);
2039      } else if (isEmpty()) {
2040        throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2041      } else if (isLazy()) {
2042        throw DataException("Error - Operations not permitted on instances of DataLazy.");
2043      } else {
2044        throw DataException("Error - Data encapsulates an unknown type.");
2045    }    }
   return 0;  
2046  }  }
2047    
2048  /**  /**
# Line 1663  inline Line 2058  inline
2058  Data  Data
2059  Data::dp_algorithm(BinaryFunction operation, double initial_value) const  Data::dp_algorithm(BinaryFunction operation, double initial_value) const
2060  {  {
2061    if (isExpanded()) {    if (isEmpty()) {
2062      Data result(0,DataArrayView::ShapeType(),getFunctionSpace(),isExpanded());      throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2063      }
2064      else if (isExpanded()) {
2065        Data result(0,DataTypes::ShapeType(),getFunctionSpace(),isExpanded());
2066      DataExpanded* dataE=dynamic_cast<DataExpanded*>(m_data.get());      DataExpanded* dataE=dynamic_cast<DataExpanded*>(m_data.get());
2067      DataExpanded* resultE=dynamic_cast<DataExpanded*>(result.m_data.get());      DataExpanded* resultE=dynamic_cast<DataExpanded*>(result.m_data.get());
2068      EsysAssert((dataE!=0), "Programming error - casting data to DataExpanded.");      EsysAssert((dataE!=0), "Programming error - casting data to DataExpanded.");
2069      EsysAssert((resultE!=0), "Programming error - casting result to DataExpanded.");      EsysAssert((resultE!=0), "Programming error - casting result to DataExpanded.");
2070      escript::dp_algorithm(*dataE,*resultE,operation,initial_value);      escript::dp_algorithm(*dataE,*resultE,operation,initial_value);
2071      return result;      return result;
2072    } else if (isTagged()) {    }
2073      else if (isTagged()) {
2074      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());  
2075      EsysAssert((dataT!=0), "Programming error - casting data to DataTagged.");      EsysAssert((dataT!=0), "Programming error - casting data to DataTagged.");
2076      EsysAssert((resultT!=0), "Programming error - casting result to DataTagged.");      DataTypes::ValueType defval(1);
2077        defval[0]=0;
2078        DataTagged* resultT=new DataTagged(getFunctionSpace(), DataTypes::scalarShape, defval, dataT);
2079      escript::dp_algorithm(*dataT,*resultT,operation,initial_value);      escript::dp_algorithm(*dataT,*resultT,operation,initial_value);
2080      return result;      return Data(resultT);   // note: the Data object now owns the resultT pointer
2081    } else if (isConstant()) {    }
2082      Data result(0,DataArrayView::ShapeType(),getFunctionSpace(),isExpanded());    else if (isConstant()) {
2083        Data result(0,DataTypes::ShapeType(),getFunctionSpace(),isExpanded());
2084      DataConstant* dataC=dynamic_cast<DataConstant*>(m_data.get());      DataConstant* dataC=dynamic_cast<DataConstant*>(m_data.get());
2085      DataConstant* resultC=dynamic_cast<DataConstant*>(result.m_data.get());      DataConstant* resultC=dynamic_cast<DataConstant*>(result.m_data.get());
2086      EsysAssert((dataC!=0), "Programming error - casting data to DataConstant.");      EsysAssert((dataC!=0), "Programming error - casting data to DataConstant.");
2087      EsysAssert((resultC!=0), "Programming error - casting result to DataConstant.");      EsysAssert((resultC!=0), "Programming error - casting result to DataConstant.");
2088      escript::dp_algorithm(*dataC,*resultC,operation,initial_value);      escript::dp_algorithm(*dataC,*resultC,operation,initial_value);
2089      return result;      return result;
2090      } else if (isLazy()) {
2091        throw DataException("Error - Operations not permitted on instances of DataLazy.");
2092      } else {
2093        throw DataException("Error - Data encapsulates an unknown type.");
2094    }    }
   Data falseRetVal; // to keep compiler quiet  
   return falseRetVal;  
2095  }  }
2096    
2097    /**
2098      \brief
2099      Compute a tensor operation with two Data objects
2100      \param arg_0 - Input - Data object
2101      \param arg_1 - Input - Data object
2102      \param operation - Input - Binary op functor
2103    */
2104  template <typename BinaryFunction>  template <typename BinaryFunction>
2105    inline
2106  Data  Data
2107  C_TensorBinaryOperation(Data const &arg_0,  C_TensorBinaryOperation(Data const &arg_0,
2108                          Data const &arg_1,                          Data const &arg_1,
2109                          BinaryFunction operation)                          BinaryFunction operation)
2110  {  {
2111      if (arg_0.isEmpty() || arg_1.isEmpty())
2112      {
2113         throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2114      }
2115      if (arg_0.isLazy() || arg_1.isLazy())
2116      {
2117         throw DataException("Error - Operations not permitted on lazy data.");
2118      }
2119    // Interpolate if necessary and find an appropriate function space    // Interpolate if necessary and find an appropriate function space
2120    Data arg_0_Z, arg_1_Z;    Data arg_0_Z, arg_1_Z;
2121    if (arg_0.getFunctionSpace()!=arg_1.getFunctionSpace()) {    if (arg_0.getFunctionSpace()!=arg_1.getFunctionSpace()) {
# Line 1730  C_TensorBinaryOperation(Data const &arg_ Line 2137  C_TensorBinaryOperation(Data const &arg_
2137    // Get rank and shape of inputs    // Get rank and shape of inputs
2138    int rank0 = arg_0_Z.getDataPointRank();    int rank0 = arg_0_Z.getDataPointRank();
2139    int rank1 = arg_1_Z.getDataPointRank();    int rank1 = arg_1_Z.getDataPointRank();
2140    DataArrayView::ShapeType shape0 = arg_0_Z.getDataPointShape();    DataTypes::ShapeType shape0 = arg_0_Z.getDataPointShape();
2141    DataArrayView::ShapeType shape1 = arg_1_Z.getDataPointShape();    DataTypes::ShapeType shape1 = arg_1_Z.getDataPointShape();
2142    int size0 = arg_0_Z.getDataPointSize();    int size0 = arg_0_Z.getDataPointSize();
2143    int size1 = arg_1_Z.getDataPointSize();    int size1 = arg_1_Z.getDataPointSize();
   
2144    // Declare output Data object    // Declare output Data object
2145    Data res;    Data res;
2146    
2147    if (shape0 == shape1) {    if (shape0 == shape1) {
   
2148      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2149        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output
2150        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2151        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2152        double *ptr_2 = &((res.getPointDataView().getData())[0]);        double *ptr_2 = &(res.getDataAtOffsetRW(0));
2153    
2154        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2155      }      }
2156      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 2168  C_TensorBinaryOperation(Data const &arg_
2168    
2169        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2170        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2171        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2172        // Get the views  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2173        // Get the pointers to the actual data        // Get the pointers to the actual data
2174        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2175        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2176    
2177        // Compute a result for the default        // Compute a result for the default
2178        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2179        // Compute a result for each tag        // Compute a result for each tag
2180        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2181        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
2182        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2183          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2184          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2185          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2186          double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2187          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2188        }        }
2189    
2190      }      }
2191      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {
   
2192        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2193        DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());        DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());
2194        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 2198  C_TensorBinaryOperation(Data const &arg_
2198        int numSamples_1 = arg_1_Z.getNumSamples();        int numSamples_1 = arg_1_Z.getNumSamples();
2199        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2200        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2201          res.requireWrite();
2202        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2203        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2204          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2205            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2206            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2207            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2208            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2209            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2210            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2211          }          }
2212        }        }
2213    
2214      }      }
2215      else if (arg_0_Z.isTagged()     && arg_1_Z.isConstant()) {      else if (arg_0_Z.isTagged()     && arg_1_Z.isConstant()) {
   
2216        // Borrow DataTagged input from Data object        // Borrow DataTagged input from Data object
2217        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2218    
# Line 1823  C_TensorBinaryOperation(Data const &arg_ Line 2226  C_TensorBinaryOperation(Data const &arg_
2226    
2227        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2228        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2229        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);  
2230        // 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();  
2231        // Get the pointers to the actual data        // Get the pointers to the actual data
2232        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2233        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2234        // Compute a result for the default        // Compute a result for the default
2235        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2236        // Compute a result for each tag        // Compute a result for each tag
2237        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2238        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
2239        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2240          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2241          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2242          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);  
2243          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2244        }        }
2245    
2246      }      }
2247      else if (arg_0_Z.isTagged()     && arg_1_Z.isTagged()) {      else if (arg_0_Z.isTagged()     && arg_1_Z.isTagged()) {
   
2248        // Borrow DataTagged input from Data object        // Borrow DataTagged input from Data object
2249        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2250    
# Line 1858  C_TensorBinaryOperation(Data const &arg_ Line 2256  C_TensorBinaryOperation(Data const &arg_
2256        res.tag();        // DataTagged output        res.tag();        // DataTagged output
2257        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2258    
       // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2259        // Get the pointers to the actual data        // Get the pointers to the actual data
2260        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2261        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2262        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2263    
2264        // Compute a result for the default        // Compute a result for the default
2265        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2266        // Merge the tags        // Merge the tags
# Line 1873  C_TensorBinaryOperation(Data const &arg_ Line 2268  C_TensorBinaryOperation(Data const &arg_
2268        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2269        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2270        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2271          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
2272        }        }
2273        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2274          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2275        }        }
2276        // Compute a result for each tag        // Compute a result for each tag
2277        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2278        for (i=lookup_2.begin();i!=lookup_2.end();i++) {        for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2279          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);  
2280          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2281          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2282          double *ptr_0 = &view_0.getData(0);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2283          double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2284          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2285        }        }
2286    
2287      }      }
2288      else if (arg_0_Z.isTagged()     && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isTagged()     && arg_1_Z.isExpanded()) {
   
2289        // 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
2290        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2291        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 2295  C_TensorBinaryOperation(Data const &arg_
2295        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2296        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2297        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2298          res.requireWrite();
2299        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2300        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2301          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
2302          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2303          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2304            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2305            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2306            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2307            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2308            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2309          }          }
2310        }        }
2311    
2312      }      }
2313      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {
   
2314        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2315        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2316        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 2320  C_TensorBinaryOperation(Data const &arg_
2320        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2321        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2322        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2323          res.requireWrite();
2324        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2325        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2326          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2327            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2328            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2329            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);  
2330            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2331            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2332              double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2333    
2334    
2335            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2336          }          }
2337        }        }
2338    
2339      }      }
2340      else if (arg_0_Z.isExpanded()   && arg_1_Z.isTagged()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isTagged()) {
   
2341        // 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
2342        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2343        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 2347  C_TensorBinaryOperation(Data const &arg_
2347        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2348        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2349        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2350          res.requireWrite();
2351        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2352        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2353          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2354          double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2355          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2356            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2357            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2358            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2359            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2360            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2361          }          }
2362        }        }
2363    
2364      }      }
2365      else if (arg_0_Z.isExpanded()   && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isExpanded()) {
   
2366        // 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
2367        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2368        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 2372  C_TensorBinaryOperation(Data const &arg_
2372        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2373        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2374        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2375          res.requireWrite();
2376        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2377        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2378          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2379            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2380            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2381            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2382            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2383            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2384            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2385            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2386          }          }
2387        }        }
# Line 1995  C_TensorBinaryOperation(Data const &arg_ Line 2392  C_TensorBinaryOperation(Data const &arg_
2392      }      }
2393    
2394    } else if (0 == rank0) {    } else if (0 == rank0) {
   
2395      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2396        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace());      // DataConstant output        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace());      // DataConstant output
2397        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2398        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2399        double *ptr_2 = &((res.getPointDataView().getData())[0]);        double *ptr_2 = &(res.getDataAtOffsetRW(0));
2400        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2401      }      }
2402      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 2414  C_TensorBinaryOperation(Data const &arg_
2414    
2415        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2416        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2417        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2418        // Get the views  
2419        DataArrayView view_1 = tmp_1->getDefaultValue();        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2420        DataArrayView view_2 = tmp_2->getDefaultValue();        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2421        // Get the pointers to the actual data  
       double *ptr_1 = &((view_1.getData())[0]);  
       double *ptr_2 = &((view_2.getData())[0]);  
2422        // Compute a result for the default        // Compute a result for the default
2423        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2424        // Compute a result for each tag        // Compute a result for each tag
2425        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2426        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
2427        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2428          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2429          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2430          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);  
2431          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2432        }        }
2433    
# Line 2051  C_TensorBinaryOperation(Data const &arg_ Line 2443  C_TensorBinaryOperation(Data const &arg_
2443        int numSamples_1 = arg_1_Z.getNumSamples();        int numSamples_1 = arg_1_Z.getNumSamples();
2444        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2445        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2446          res.requireWrite();
2447        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2448        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2449          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2450            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2451            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2452            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2453            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2454            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2455            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2456    
2457          }          }
# Line 2080  C_TensorBinaryOperation(Data const &arg_ Line 2473  C_TensorBinaryOperation(Data const &arg_
2473    
2474        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2475        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2476        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2477        // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2478        // Get the pointers to the actual data        // Get the pointers to the actual data
2479        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2480        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2481    
2482    
2483        // Compute a result for the default        // Compute a result for the default
2484        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2485        // Compute a result for each tag        // Compute a result for each tag
2486        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2487        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
2488        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2489          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2490          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2491          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2492          double *ptr_0 = &view_0.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2493          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2494        }        }
2495    
# Line 2115  C_TensorBinaryOperation(Data const &arg_ Line 2507  C_TensorBinaryOperation(Data const &arg_
2507        res.tag();        // DataTagged output        res.tag();        // DataTagged output
2508        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2509    
       // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2510        // Get the pointers to the actual data        // Get the pointers to the actual data
2511        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2512        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2513        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2514    
2515        // Compute a result for the default        // Compute a result for the default
2516        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2517        // Merge the tags        // Merge the tags
# Line 2130  C_TensorBinaryOperation(Data const &arg_ Line 2519  C_TensorBinaryOperation(Data const &arg_
2519        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2520        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2521        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2522          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
2523        }        }
2524        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2525          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2526        }        }
2527        // Compute a result for each tag        // Compute a result for each tag
2528        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2529        for (i=lookup_2.begin();i!=lookup_2.end();i++) {        for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2530          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2531          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2532          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2533          double *ptr_0 = &view_0.getData(0);  
         double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2534          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2535        }        }
2536    
# Line 2159  C_TensorBinaryOperation(Data const &arg_ Line 2546  C_TensorBinaryOperation(Data const &arg_
2546        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2547        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2548        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2549          res.requireWrite();
2550        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2551        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2552          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
2553          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2554          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2555            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2556            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2557            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2558            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2559            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2560          }          }
2561        }        }
2562    
2563      }      }
2564      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {
   
2565        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2566        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2567        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 2571  C_TensorBinaryOperation(Data const &arg_
2571        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2572        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2573        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2574          res.requireWrite();
2575        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2576        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2577          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2578            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2579            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2580            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2581            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2582            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2583            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2584          }          }
2585        }        }
# Line 2209  C_TensorBinaryOperation(Data const &arg_ Line 2597  C_TensorBinaryOperation(Data const &arg_
2597        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2598        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2599        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2600          res.requireWrite();
2601        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2602        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2603          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2604          double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2605          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2606            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2607            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2608            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2609            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2610            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2611          }          }
2612        }        }
# Line 2234  C_TensorBinaryOperation(Data const &arg_ Line 2623  C_TensorBinaryOperation(Data const &arg_
2623        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2624        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2625        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2626          res.requireWrite();
2627        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2628        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2629          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2630            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2631            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2632            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2633            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2634            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2635            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2636            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2637          }          }
2638        }        }
# Line 2253  C_TensorBinaryOperation(Data const &arg_ Line 2643  C_TensorBinaryOperation(Data const &arg_
2643      }      }
2644    
2645    } else if (0 == rank1) {    } else if (0 == rank1) {
   
2646      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2647        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output
2648        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2649        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2650        double *ptr_2 = &((res.getPointDataView().getData())[0]);        double *ptr_2 = &(res.getDataAtOffsetRW(0));
2651        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2652      }      }
2653      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 2665  C_TensorBinaryOperation(Data const &arg_
2665    
2666        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2667        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2668        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2669        // Get the views  
2670        DataArrayView view_1 = tmp_1->getDefaultValue();        //Get the pointers to the actual data
2671        DataArrayView view_2 = tmp_2->getDefaultValue();        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2672        // Get the pointers to the actual data        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2673        double *ptr_1 = &((view_1.getData())[0]);  
       double *ptr_2 = &((view_2.getData())[0]);  
2674        // Compute a result for the default        // Compute a result for the default
2675        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2676        // Compute a result for each tag        // Compute a result for each tag
2677        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2678        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
2679        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2680          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2681          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2682          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);  
2683          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2684        }        }
   
2685      }      }
2686      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {
2687    
# Line 2309  C_TensorBinaryOperation(Data const &arg_ Line 2694  C_TensorBinaryOperation(Data const &arg_
2694        int numSamples_1 = arg_1_Z.getNumSamples();        int numSamples_1 = arg_1_Z.getNumSamples();
2695        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2696        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2697          res.requireWrite();
2698        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2699        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2700          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2701            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2702            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2703            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2704            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2705            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2706            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2707          }          }
2708        }        }
# Line 2337  C_TensorBinaryOperation(Data const &arg_ Line 2723  C_TensorBinaryOperation(Data const &arg_
2723    
2724        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2725        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2726        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();  
2727        // Get the pointers to the actual data        // Get the pointers to the actual data
2728        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2729        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2730        // Compute a result for the default        // Compute a result for the default
2731        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2732        // Compute a result for each tag        // Compute a result for each tag
2733        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2734        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
2735        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2736          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2737          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2738          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);  
2739          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2740        }        }
2741    
# Line 2372  C_TensorBinaryOperation(Data const &arg_ Line 2753  C_TensorBinaryOperation(Data const &arg_
2753        res.tag();        // DataTagged output        res.tag();        // DataTagged output
2754        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2755    
       // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2756        // Get the pointers to the actual data        // Get the pointers to the actual data
2757        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2758        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2759        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2760    
2761        // Compute a result for the default        // Compute a result for the default
2762        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2763        // Merge the tags        // Merge the tags
# Line 2387  C_TensorBinaryOperation(Data const &arg_ Line 2765  C_TensorBinaryOperation(Data const &arg_
2765        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2766        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2767        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2768          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
2769        }        }
2770        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2771          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2772        }        }
2773        // Compute a result for each tag        // Compute a result for each tag
2774        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2775        for (i=lookup_2.begin();i!=lookup_2.end();i++) {        for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2776          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2777          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2778          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);  
2779          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2780        }        }
2781    
# Line 2416  C_TensorBinaryOperation(Data const &arg_ Line 2791  C_TensorBinaryOperation(Data const &arg_
2791        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2792        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2793        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2794          res.requireWrite();
2795        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2796        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2797          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
2798          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2799          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2800            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2801            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2802            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2803            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2804            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2805          }          }
2806        }        }
2807    
2808      }      }
2809      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {
   
2810        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2811        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2812        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 2816  C_TensorBinaryOperation(Data const &arg_
2816        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2817        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2818        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2819          res.requireWrite();
2820        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2821        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2822          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2823            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2824            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2825            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2826            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2827            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2828            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2829          }          }
2830        }        }
# Line 2466  C_TensorBinaryOperation(Data const &arg_ Line 2842  C_TensorBinaryOperation(Data const &arg_
2842        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2843        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2844        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2845          res.requireWrite();
2846        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2847        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2848          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2849          double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2850          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2851            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2852            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2853            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2854            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2855            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2856          }          }
2857        }        }
# Line 2491  C_TensorBinaryOperation(Data const &arg_ Line 2868  C_TensorBinaryOperation(Data const &arg_
2868        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2869        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2870        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2871          res.requireWrite();
2872        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2873        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2874          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2875            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2876            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2877            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2878            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2879            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2880            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2881            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2882          }          }
2883        }        }
# Line 2521  Data Line 2899  Data
2899  C_TensorUnaryOperation(Data const &arg_0,  C_TensorUnaryOperation(Data const &arg_0,
2900                         UnaryFunction operation)                         UnaryFunction operation)
2901  {  {
2902      if (arg_0.isEmpty())  // do this before we attempt to interpolate
2903      {
2904         throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2905      }
2906      if (arg_0.isLazy())
2907      {
2908         throw DataException("Error - Operations not permitted on lazy data.");
2909      }
2910    // Interpolate if necessary and find an appropriate function space    // Interpolate if necessary and find an appropriate function space
2911    Data arg_0_Z = Data(arg_0);    Data arg_0_Z = Data(arg_0);
2912    
2913    // Get rank and shape of inputs    // Get rank and shape of inputs
2914    int rank0 = arg_0_Z.getDataPointRank();    const DataTypes::ShapeType& shape0 = arg_0_Z.getDataPointShape();
   DataArrayView::ShapeType shape0 = arg_0_Z.getDataPointShape();  
2915    int size0 = arg_0_Z.getDataPointSize();    int size0 = arg_0_Z.getDataPointSize();
2916    
2917    // Declare output Data object    // Declare output Data object
# Line 2534  C_TensorUnaryOperation(Data const &arg_0 Line 2919  C_TensorUnaryOperation(Data const &arg_0
2919    
2920    if (arg_0_Z.isConstant()) {    if (arg_0_Z.isConstant()) {
2921      res = Data(0.0, shape0, arg_0_Z.getFunctionSpace());      // DataConstant output      res = Data(0.0, shape0, arg_0_Z.getFunctionSpace());      // DataConstant output
2922      double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);      const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2923      double *ptr_2 = &((res.getPointDataView().getData())[0]);      double *ptr_2 = &(res.getDataAtOffsetRW(0));
2924      tensor_unary_operation(size0, ptr_0, ptr_2, operation);      tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2925    }    }
2926    else if (arg_0_Z.isTagged()) {    else if (arg_0_Z.isTagged()) {
# Line 2548  C_TensorUnaryOperation(Data const &arg_0 Line 2933  C_TensorUnaryOperation(Data const &arg_0
2933      res.tag();      res.tag();
2934      DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());      DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2935    
     // Get the views  
     DataArrayView view_0 = tmp_0->getDefaultValue();  
     DataArrayView view_2 = tmp_2->getDefaultValue();  
2936      // Get the pointers to the actual data      // Get the pointers to the actual data
2937      double *ptr_0 = &((view_0.getData())[0]);      const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2938      double *ptr_2 = &((view_2.getData())[0]);      double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2939      // Compute a result for the default      // Compute a result for the default
2940      tensor_unary_operation(size0, ptr_0, ptr_2, operation);      tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2941      // Compute a result for each tag      // Compute a result for each tag
2942      const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();      const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2943      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
2944      for (i=lookup_0.begin();i!=lookup_0.end();i++) {      for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2945        tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());        tmp_2->addTag(i->first);
2946        DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);        const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2947        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);  
2948        tensor_unary_operation(size0, ptr_0, ptr_2, operation);        tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2949      }      }
2950    
# Line 2583  C_TensorUnaryOperation(Data const &arg_0 Line 2963  C_TensorUnaryOperation(Data const &arg_0
2963        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2964          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2965          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2966          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2967          double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);          double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2968          tensor_unary_operation(size0, ptr_0, ptr_2, operation);          tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2969        }        }
2970      }      }
   
2971    }    }
2972    else {    else {
2973      throw DataException("Error - C_TensorUnaryOperation: unknown combination of inputs");      throw DataException("Error - C_TensorUnaryOperation: unknown combination of inputs");

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