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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 2644 by jfenwick, Wed Sep 2 04:14:03 2009 UTC
# Line 1  Line 1 
1    
 /* $Id$ */  
   
2  /*******************************************************  /*******************************************************
3   *  *
4   *           Copyright 2003-2007 by ACceSS MNRF  * Copyright (c) 2003-2009 by University of Queensland
5   *       Copyright 2007 by University of Queensland  * Earth Systems Science Computational Center (ESSCC)
6   *  * http://www.uq.edu.au/esscc
7   *                http://esscc.uq.edu.au  *
8   *        Primary Business: Queensland, Australia  * Primary Business: Queensland, Australia
9   *  Licensed under the Open Software License version 3.0  * Licensed under the Open Software License version 3.0
10   *     http://www.opensource.org/licenses/osl-3.0.php  * http://www.opensource.org/licenses/osl-3.0.php
11   *  *
12   *******************************************************/  *******************************************************/
13    
14    
15  /** \file Data.h */  /** \file Data.h */
16    
# Line 19  Line 18 
18  #define DATA_H  #define DATA_H
19  #include "system_dep.h"  #include "system_dep.h"
20    
21    #include "DataTypes.h"
22  #include "DataAbstract.h"  #include "DataAbstract.h"
23  #include "DataAlgorithm.h"  #include "DataAlgorithm.h"
24  #include "FunctionSpace.h"  #include "FunctionSpace.h"
# Line 26  Line 26 
26  #include "UnaryOp.h"  #include "UnaryOp.h"
27  #include "DataException.h"  #include "DataException.h"
28    
29    
30  extern "C" {  extern "C" {
31  #include "DataC.h"  #include "DataC.h"
32  /* #include "paso/Paso.h" doesn't belong in this file...causes trouble for BruceFactory.cpp */  //#include <omp.h>
33  }  }
34    
35  #include "esysmpi.h"  #include "esysmpi.h"
36  #include <string>  #include <string>
37  #include <algorithm>  #include <algorithm>
38    #include <sstream>
39    
40  #include <boost/shared_ptr.hpp>  #include <boost/shared_ptr.hpp>
41  #include <boost/python/object.hpp>  #include <boost/python/object.hpp>
42  #include <boost/python/tuple.hpp>  #include <boost/python/tuple.hpp>
43  #include <boost/python/numeric.hpp>  
44    #include "BufferGroup.h"
45    
46  namespace escript {  namespace escript {
47    
# Line 47  namespace escript { Line 50  namespace escript {
50  class DataConstant;  class DataConstant;
51  class DataTagged;  class DataTagged;
52  class DataExpanded;  class DataExpanded;
53    class DataLazy;
54    
55  /**  /**
56     \brief     \brief
57     Data creates the appropriate Data object for the given construction     Data represents a collection of datapoints.
    arguments.  
58    
59     Description:     Description:
60     Data is essentially a factory class which creates the appropriate Data     Internally, the datapoints are actually stored by a DataAbstract object.
61     object for the given construction arguments. It retains control over     The specific instance of DataAbstract used may vary over the lifetime
62     the object created for the lifetime of the object.     of the Data object.
63     The type of Data object referred to may change during the lifetime of     Some methods on this class return references (eg getShape()).
64     the Data object.     These references should not be used after an operation which changes the underlying DataAbstract object.
65       Doing so will lead to invalid memory access.
66       This should not affect any methods exposed via boost::python.
67  */  */
68  class Data {  class Data {
69    
# Line 101  class Data { Line 106  class Data {
106         const FunctionSpace& what);         const FunctionSpace& what);
107    
108    /**    /**
109       \brief      \brief Copy Data from an existing vector
110       Constructor which copies data from a DataArrayView.    */
111    
      \param value - Input - Data value for a single point.  
      \param what - Input - A description of what this data represents.  
      \param expanded - Input - Flag, if true fill the entire container with  
                        the value. Otherwise a more efficient storage  
                        mechanism will be used.  
   */  
112    ESCRIPT_DLL_API    ESCRIPT_DLL_API
113    Data(const DataArrayView& value,    Data(const DataTypes::ValueType& value,
114         const FunctionSpace& what=FunctionSpace(),           const DataTypes::ShapeType& shape,
115         bool expanded=false);                   const FunctionSpace& what=FunctionSpace(),
116                     bool expanded=false);
117    
118    /**    /**
119       \brief       \brief
120       Constructor which creates a Data from a DataArrayView shape.       Constructor which creates a Data with points having the specified shape.
121    
122       \param value - Input - Single value applied to all Data.       \param value - Input - Single value applied to all Data.
123       \param dataPointShape - Input - The shape of each data point.       \param dataPointShape - Input - The shape of each data point.
# Line 128  class Data { Line 128  class Data {
128    */    */
129    ESCRIPT_DLL_API    ESCRIPT_DLL_API
130    Data(double value,    Data(double value,
131         const DataArrayView::ShapeType& dataPointShape=DataArrayView::ShapeType(),         const DataTypes::ShapeType& dataPointShape=DataTypes::ShapeType(),
132         const FunctionSpace& what=FunctionSpace(),         const FunctionSpace& what=FunctionSpace(),
133         bool expanded=false);         bool expanded=false);
134    
# Line 141  class Data { Line 141  class Data {
141    */    */
142    ESCRIPT_DLL_API    ESCRIPT_DLL_API
143    Data(const Data& inData,    Data(const Data& inData,
144         const DataArrayView::RegionType& region);         const DataTypes::RegionType& region);
   
   /**  
      \brief  
      Constructor which will create Tagged data if expanded is false.  
      No attempt is made to ensure the tag keys match the tag keys  
      within the function space.  
   
      \param tagKeys - Input - List of tag values.  
      \param values - Input - List of values, one for each tag.  
      \param defaultValue - Input - A default value, used if tag doesn't exist.  
      \param what - Input - A description of what this data represents.  
      \param expanded - Input - Flag, if true fill the entire container with  
                        the appropriate values.  
     ==>*  
   */  
   ESCRIPT_DLL_API  
   Data(const DataTagged::TagListType& tagKeys,  
        const DataTagged::ValueListType& values,  
        const DataArrayView& defaultValue,  
        const FunctionSpace& what=FunctionSpace(),  
        bool expanded=false);  
   
   /**  
      \brief  
      Constructor which copies data from a python numarray.  
   
      \param value - Input - Data value for a single point.  
      \param what - Input - A description of what this data represents.  
      \param expanded - Input - Flag, if true fill the entire container with  
                        the value. Otherwise a more efficient storage  
                        mechanism will be used.  
   */  
   ESCRIPT_DLL_API  
   Data(const boost::python::numeric::array& value,  
        const FunctionSpace& what=FunctionSpace(),  
        bool expanded=false);  
145    
146    /**    /**
147       \brief       \brief
148       Constructor which copies data from any object that can be converted into       Constructor which copies data from any object that can be treated like a python array/sequence.
      a python numarray.  
149    
150       \param value - Input - Input data.       \param value - Input - Input data.
151       \param what - Input - A description of what this data represents.       \param what - Input - A description of what this data represents.
# Line 198  class Data { Line 161  class Data {
161    /**    /**
162       \brief       \brief
163       Constructor which creates a DataConstant.       Constructor which creates a DataConstant.
164       Copies data from any object that can be converted       Copies data from any object that can be treated like a python array/sequence.
165       into a numarray. All other parameters are copied from other.       All other parameters are copied from other.
166    
167       \param value - Input - Input data.       \param value - Input - Input data.
168       \param other - Input - contains all other parameters.       \param other - Input - contains all other parameters.
# Line 217  class Data { Line 180  class Data {
180         const boost::python::tuple& shape=boost::python::make_tuple(),         const boost::python::tuple& shape=boost::python::make_tuple(),
181         const FunctionSpace& what=FunctionSpace(),         const FunctionSpace& what=FunctionSpace(),
182         bool expanded=false);         bool expanded=false);
183    
184    
185    
186      /**
187        \brief Create a Data using an existing DataAbstract. Warning: The new object assumes ownership of the pointer!
188        Once you have passed the pointer, do not delete it.
189      */
190      ESCRIPT_DLL_API
191      explicit Data(DataAbstract* underlyingdata);
192    
193      /**
194        \brief Create a Data based on the supplied DataAbstract
195      */
196      ESCRIPT_DLL_API
197      explicit Data(DataAbstract_ptr underlyingdata);
198    
199    /**    /**
200       \brief       \brief
201       Destructor       Destructor
# Line 225  class Data { Line 204  class Data {
204    ~Data();    ~Data();
205    
206    /**    /**
207       \brief       \brief Make this object a deep copy of "other".
      Perform a deep copy.  
208    */    */
209    ESCRIPT_DLL_API    ESCRIPT_DLL_API
210    void    void
211    copy(const Data& other);    copy(const Data& other);
212    
213    /**    /**
214         \brief Return a pointer to a deep copy of this object.
215      */
216      ESCRIPT_DLL_API
217      Data
218      copySelf();
219    
220    
221      /**
222         \brief produce a delayed evaluation version of this Data.
223      */
224      ESCRIPT_DLL_API
225      Data
226      delay();
227    
228      /**
229         \brief convert the current data into lazy data.
230      */
231      ESCRIPT_DLL_API
232      void
233      delaySelf();
234    
235    
236      /**
237       Member access methods.       Member access methods.
238    */    */
239    
# Line 247  class Data { Line 248  class Data {
248    
249    /**    /**
250       \brief       \brief
251       Returns trueif the data object is protected against update       Returns true, if the data object is protected against update
252    
253    */    */
254    ESCRIPT_DLL_API    ESCRIPT_DLL_API
255    bool    bool
256    isProtected() const;    isProtected() const;
257    
258    /**  
259       \brief  /**
260       Return the values of a data point on this process     \brief
261    */     Return the value of a data point as a python tuple.
262    */
263    ESCRIPT_DLL_API    ESCRIPT_DLL_API
264    const boost::python::numeric::array    const boost::python::object
265    getValueOfDataPoint(int dataPointNo);    getValueOfDataPointAsTuple(int dataPointNo);
266    
267    /**    /**
268       \brief       \brief
# Line 272  class Data { Line 274  class Data {
274    
275    /**    /**
276       \brief       \brief
277       sets the values of a data-point from a numarray object on this process       sets the values of a data-point from a array-like object on this process
278    */    */
279    ESCRIPT_DLL_API    ESCRIPT_DLL_API
280    void    void
281    setValueOfDataPointToArray(int dataPointNo, const boost::python::numeric::array&);    setValueOfDataPointToArray(int dataPointNo, const boost::python::object&);
282    
283    /**    /**
284       \brief       \brief
# Line 287  class Data { Line 289  class Data {
289    setValueOfDataPoint(int dataPointNo, const double);    setValueOfDataPoint(int dataPointNo, const double);
290    
291    /**    /**
292       \brief       \brief Return a data point across all processors as a python tuple.
      Return the value of the specified data-point across all processors  
293    */    */
294    ESCRIPT_DLL_API    ESCRIPT_DLL_API
295    const boost::python::numeric::array    const boost::python::object
296    getValueOfGlobalDataPoint(int procNo, int dataPointNo);    getValueOfGlobalDataPointAsTuple(int procNo, int dataPointNo);
297    
298    /**    /**
299       \brief       \brief
300       Return the tag number associated with the given data-point.       Return the tag number associated with the given data-point.
301    
      The data-point number here corresponds to the data-point number in the  
      numarray returned by convertToNumArray.  
302    */    */
303    ESCRIPT_DLL_API    ESCRIPT_DLL_API
304    int    int
# Line 313  class Data { Line 312  class Data {
312    escriptDataC    escriptDataC
313    getDataC();    getDataC();
314    
315    
316    
317    /**    /**
318       \brief       \brief
319       Return the C wrapper for the Data object - const version.       Return the C wrapper for the Data object - const version.
# Line 322  class Data { Line 323  class Data {
323    getDataC() const;    getDataC() const;
324    
325    /**    /**
326       \brief      \brief How much space is required to evaulate a sample of the Data.
      Write the data as a string.  
327    */    */
328    ESCRIPT_DLL_API    ESCRIPT_DLL_API
329    inline    size_t
330    std::string    getSampleBufferSize() const;
331    toString() const  
332    {  
     return m_data->toString();  
   }  
333    
334    /**    /**
335       \brief       \brief
336       Return the DataArrayView of the point data. This essentially contains       Write the data as a string. For large amounts of data, a summary is printed.
      the shape information for each data point although it also may be used  
      to manipulate the point data.  
337    */    */
338    ESCRIPT_DLL_API    ESCRIPT_DLL_API
339    inline    std::string
340    const DataArrayView&    toString() const;
   getPointDataView() const  
   {  
      return m_data->getPointDataView();  
   }  
341    
342    /**    /**
343       \brief       \brief
# Line 360  class Data { Line 352  class Data {
352       If possible convert this Data to DataTagged. This will only allow       If possible convert this Data to DataTagged. This will only allow
353       Constant data to be converted to tagged. An attempt to convert       Constant data to be converted to tagged. An attempt to convert
354       Expanded data to tagged will throw an exception.       Expanded data to tagged will throw an exception.
     ==>*  
355    */    */
356    ESCRIPT_DLL_API    ESCRIPT_DLL_API
357    void    void
358    tag();    tag();
359    
360    /**    /**
361        \brief If this data is lazy, then convert it to ready data.
362        What type of ready data depends on the expression. For example, Constant+Tagged==Tagged.
363      */
364      ESCRIPT_DLL_API
365      void
366      resolve();
367    
368    
369      /**
370       \brief Ensures data is ready for write access.
371      This means that the data will be resolved if lazy and will be copied if shared with another Data object.
372      \warning This method should only be called in single threaded sections of code. (It modifies m_data).
373      Do not create any Data objects from this one between calling requireWrite and getSampleDataRW.
374      Doing so might introduce additional sharing.
375      */
376      ESCRIPT_DLL_API
377      void
378      requireWrite();
379    
380      /**
381       \brief       \brief
382       Return true if this Data is expanded.       Return true if this Data is expanded.
383         \note To determine if a sample will contain separate values for each datapoint. Use actsExpanded instead.
384    */    */
385    ESCRIPT_DLL_API    ESCRIPT_DLL_API
386    bool    bool
# Line 376  class Data { Line 388  class Data {
388    
389    /**    /**
390       \brief       \brief
391         Return true if this Data is expanded or resolves to expanded.
392         That is, if it has a separate value for each datapoint in the sample.
393      */
394      ESCRIPT_DLL_API
395      bool
396      actsExpanded() const;
397      
398    
399      /**
400         \brief
401       Return true if this Data is tagged.       Return true if this Data is tagged.
402    */    */
403    ESCRIPT_DLL_API    ESCRIPT_DLL_API
# Line 391  class Data { Line 413  class Data {
413    isConstant() const;    isConstant() const;
414    
415    /**    /**
416         \brief Return true if this Data is lazy.
417      */
418      ESCRIPT_DLL_API
419      bool
420      isLazy() const;
421    
422      /**
423         \brief Return true if this data is ready.
424      */
425      ESCRIPT_DLL_API
426      bool
427      isReady() const;
428    
429      /**
430       \brief       \brief
431       Return true if this Data is empty.       Return true if this Data holds an instance of DataEmpty. This is _not_ the same as asking if the object
432    contains datapoints.
433    */    */
434    ESCRIPT_DLL_API    ESCRIPT_DLL_API
435    bool    bool
# Line 424  class Data { Line 461  class Data {
461    */    */
462    ESCRIPT_DLL_API    ESCRIPT_DLL_API
463    inline    inline
464    const AbstractDomain&  //   const AbstractDomain&
465      const_Domain_ptr
466    getDomain() const    getDomain() const
467    {    {
468       return getFunctionSpace().getDomain();       return getFunctionSpace().getDomain();
469    }    }
470    
471    
472      /**
473         \brief
474         Return the domain.
475         TODO: For internal use only.   This should be removed.
476      */
477      ESCRIPT_DLL_API
478      inline
479    //   const AbstractDomain&
480      Domain_ptr
481      getDomainPython() const
482      {
483         return getFunctionSpace().getDomainPython();
484      }
485    
486    /**    /**
487       \brief       \brief
488       Return a copy of the domain.       Return a copy of the domain.
# Line 444  class Data { Line 497  class Data {
497    */    */
498    ESCRIPT_DLL_API    ESCRIPT_DLL_API
499    inline    inline
500    int    unsigned int
501    getDataPointRank() const    getDataPointRank() const
502    {    {
503      return m_data->getPointDataView().getRank();      return m_data->getRank();
504    }    }
505    
506    /**    /**
# Line 484  class Data { Line 537  class Data {
537    {    {
538      return m_data->getNumDPPSample();      return m_data->getNumDPPSample();
539    }    }
540    
541    
542      /**
543        \brief
544        Return the number of values in the shape for this object.
545      */
546      ESCRIPT_DLL_API
547      int
548      getNoValues() const
549      {
550        return m_data->getNoValues();
551      }
552    
553    
554    /**    /**
555       \brief       \brief
556       dumps the object into a netCDF file       dumps the object into a netCDF file
# Line 491  class Data { Line 558  class Data {
558    ESCRIPT_DLL_API    ESCRIPT_DLL_API
559    void    void
560    dump(const std::string fileName) const;    dump(const std::string fileName) const;
561    
562     /**
563      \brief returns the values of the object as a list of tuples (one for each datapoint).
564    
565      \param scalarastuple If true, scalar data will produce single valued tuples [(1,) (2,) ...]
566    If false, the result is a list of scalars [1, 2, ...]
567     */
568      ESCRIPT_DLL_API
569      const boost::python::object
570      toListOfTuples(bool scalarastuple=true);
571    
572    
573     /**
574        \brief
575        Return the sample data for the given sample no. This is not the
576        preferred interface but is provided for use by C code.
577        The bufferg parameter is only required for LazyData.
578        \param sampleNo - Input - the given sample no.
579        \param bufferg - A buffer to compute (and store) sample data in will be selected from this group.
580        \return pointer to the sample data.
581    */
582      ESCRIPT_DLL_API
583      inline
584      const DataAbstract::ValueType::value_type*
585      getSampleDataRO(DataAbstract::ValueType::size_type sampleNo, BufferGroup* bufferg=0);
586    
587    
588    /**    /**
589       \brief       \brief
590       Return the sample data for the given sample no. This is not the       Return the sample data for the given sample no. This is not the
591       preferred interface but is provided for use by C code.       preferred interface but is provided for use by C code.
592       \param sampleNo - Input - the given sample no.       \param sampleNo - Input - the given sample no.
593         \return pointer to the sample data.
594    */    */
595    ESCRIPT_DLL_API    ESCRIPT_DLL_API
596    inline    inline
597    DataAbstract::ValueType::value_type*    DataAbstract::ValueType::value_type*
598    getSampleData(DataAbstract::ValueType::size_type sampleNo)    getSampleDataRW(DataAbstract::ValueType::size_type sampleNo);
599    {  
     return m_data->getSampleData(sampleNo);  
   }  
600    
601    /**    /**
602       \brief       \brief
# Line 521  class Data { Line 614  class Data {
614    
615    /**    /**
616       \brief       \brief
617       Return a view into the data for the data point specified.       Return a reference into the DataVector which points to the specified data point.
      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 644  class Data { Line 763  class Data {
763    ESCRIPT_DLL_API    ESCRIPT_DLL_API
764    Data    Data
765    interpolate(const FunctionSpace& functionspace) const;    interpolate(const FunctionSpace& functionspace) const;
766    
767    
768      ESCRIPT_DLL_API
769      Data
770      interpolateFromTable2D(const WrappedArray& table, double Amin, double Astep,
771                           double undef, Data& B, double Bmin, double Bstep);
772    
773    
774      // This signature needs to be tuned
775      ESCRIPT_DLL_API
776      Data
777      interpolateFromTable(boost::python::object table, double Amin, double Astep,
778                           double undef, Data& B, double Bmin, double Bstep);
779    
780    /**    /**
781       \brief       \brief
782       Calculates the gradient of the data at the data points of functionspace.       Calculates the gradient of the data at the data points of functionspace.
# Line 659  class Data { Line 792  class Data {
792    grad() const;    grad() const;
793    
794    /**    /**
795       \brief      \brief
796       Calculate the integral over the function space domain.       Calculate the integral over the function space domain as a python tuple.
      *  
797    */    */
798    ESCRIPT_DLL_API    ESCRIPT_DLL_API
799    boost::python::numeric::array    boost::python::object
800    integrate() const;    integrateToTuple_const() const;
801    
802    
803      /**
804        \brief
805         Calculate the integral over the function space domain as a python tuple.
806      */
807      ESCRIPT_DLL_API
808      boost::python::object
809      integrateToTuple();
810    
811    
812    
813    /**    /**
814       \brief       \brief
# Line 732  class Data { Line 875  class Data {
875    /**    /**
876       \brief       \brief
877       Return the maximum absolute value of this Data object.       Return the maximum absolute value of this Data object.
878       *  
879         The method is not const because lazy data needs to be expanded before Lsup can be computed.
880         The _const form can be used when the Data object is const, however this will only work for
881         Data which is not Lazy.
882    
883         For Data which contain no samples (or tagged Data for which no tags in use have a value)
884         zero is returned.
885    */    */
886    ESCRIPT_DLL_API    ESCRIPT_DLL_API
887    double    double
888    Lsup() const;    Lsup();
889    
890      ESCRIPT_DLL_API
891      double
892      Lsup_const() const;
893    
894    
895    /**    /**
896       \brief       \brief
897       Return the maximum value of this Data object.       Return the maximum value of this Data object.
898       *  
899         The method is not const because lazy data needs to be expanded before sup can be computed.
900         The _const form can be used when the Data object is const, however this will only work for
901         Data which is not Lazy.
902    
903         For Data which contain no samples (or tagged Data for which no tags in use have a value)
904         a large negative value is returned.
905    */    */
906    ESCRIPT_DLL_API    ESCRIPT_DLL_API
907    double    double
908    sup() const;    sup();
909    
910      ESCRIPT_DLL_API
911      double
912      sup_const() const;
913    
914    
915    /**    /**
916       \brief       \brief
917       Return the minimum value of this Data object.       Return the minimum value of this Data object.
918       *  
919         The method is not const because lazy data needs to be expanded before inf can be computed.
920         The _const form can be used when the Data object is const, however this will only work for
921         Data which is not Lazy.
922    
923         For Data which contain no samples (or tagged Data for which no tags in use have a value)
924         a large positive value is returned.
925    */    */
926    ESCRIPT_DLL_API    ESCRIPT_DLL_API
927    double    double
928    inf() const;    inf();
929    
930      ESCRIPT_DLL_API
931      double
932      inf_const() const;
933    
934    
935    
936    /**    /**
937       \brief       \brief
# Line 786  class Data { Line 963  class Data {
963    /**    /**
964       \brief       \brief
965       Return the (sample number, data-point number) of the data point with       Return the (sample number, data-point number) of the data point with
966       the minimum value in this Data object.       the minimum component value in this Data object.
967         \note If you are working in python, please consider using Locator
968    instead of manually manipulating process and point IDs.
969    */    */
970    ESCRIPT_DLL_API    ESCRIPT_DLL_API
971    const boost::python::tuple    const boost::python::tuple
972    minGlobalDataPoint() const;    minGlobalDataPoint() const;
973    
974      /**
975         \brief
976         Return the (sample number, data-point number) of the data point with
977         the minimum component value in this Data object.
978         \note If you are working in python, please consider using Locator
979    instead of manually manipulating process and point IDs.
980      */
981    ESCRIPT_DLL_API    ESCRIPT_DLL_API
982    void    const boost::python::tuple
983    calc_minGlobalDataPoint(int& ProcNo,  int& DataPointNo) const;    maxGlobalDataPoint() const;
984    
985    
986    
987    /**    /**
988       \brief       \brief
989       Return the sign of each data point of this Data object.       Return the sign of each data point of this Data object.
# Line 1095  class Data { Line 1284  class Data {
1284    void    void
1285    saveVTK(std::string fileName) const;    saveVTK(std::string fileName) const;
1286    
1287    
1288    
1289    /**    /**
1290       \brief       \brief
1291       Overloaded operator +=       Overloaded operator +=
# Line 1212  class Data { Line 1403  class Data {
1403    */    */
1404    ESCRIPT_DLL_API    ESCRIPT_DLL_API
1405    Data    Data
1406    getSlice(const DataArrayView::RegionType& region) const;    getSlice(const DataTypes::RegionType& region) const;
1407    
1408    /**    /**
1409       \brief       \brief
# Line 1225  class Data { Line 1416  class Data {
1416    ESCRIPT_DLL_API    ESCRIPT_DLL_API
1417    void    void
1418    setSlice(const Data& value,    setSlice(const Data& value,
1419             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);  
   
1420    
1421    /**    /**
1422       \brief       \brief
# Line 1290  class Data { Line 1458  class Data {
1458    /**    /**
1459       \brief       \brief
1460       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
1461        TODO Ownership of this object should be explained in doco.
1462    */    */
1463    ESCRIPT_DLL_API    ESCRIPT_DLL_API
1464          DataAbstract*          DataAbstract*
1465          borrowData(void) const;          borrowData(void) const;
1466    
1467      ESCRIPT_DLL_API
1468            DataAbstract_ptr
1469            borrowDataPtr(void) const;
1470    
1471      ESCRIPT_DLL_API
1472            DataReady_ptr
1473            borrowReadyPtr(void) const;
1474    
1475    
1476    
1477      /**
1478         \brief
1479         Return a pointer to the beginning of the datapoint at the specified offset.
1480         TODO Eventually these should be inlined.
1481         \param i - position(offset) in the underlying datastructure
1482      */
1483    
1484      ESCRIPT_DLL_API
1485            DataTypes::ValueType::const_reference
1486            getDataAtOffsetRO(DataTypes::ValueType::size_type i);
1487    
1488    
1489      ESCRIPT_DLL_API
1490            DataTypes::ValueType::reference
1491            getDataAtOffsetRW(DataTypes::ValueType::size_type i);
1492    
1493    
1494    
1495    /**
1496       \brief Create a buffer for use by getSample
1497       Allocates a DataVector large enough for DataLazy::resolveSample to operate on for the current Data.
1498       Do not use this buffer for other Data instances (unless you are sure they will be the same size).
1499      
1500       In multi-threaded sections, this needs to be called on each thread.
1501    
1502       \return A BufferGroup* if Data is lazy, NULL otherwise.
1503       \warning This pointer must be deallocated using freeSampleBuffer to avoid cross library memory issues.
1504    */
1505      ESCRIPT_DLL_API
1506      BufferGroup*
1507      allocSampleBuffer() const;
1508    
1509    /**
1510       \brief Free a buffer allocated with allocSampleBuffer.
1511       \param buffer Input - pointer to the buffer to deallocate.
1512    */
1513    ESCRIPT_DLL_API void freeSampleBuffer(BufferGroup* buffer);
1514    
1515   protected:   protected:
1516    
1517   private:   private:
1518    
1519      double
1520      LsupWorker() const;
1521    
1522      double
1523      supWorker() const;
1524    
1525      double
1526      infWorker() const;
1527    
1528      boost::python::object
1529      integrateWorker() const;
1530    
1531      void
1532      calc_minGlobalDataPoint(int& ProcNo,  int& DataPointNo) const;
1533    
1534      void
1535      calc_maxGlobalDataPoint(int& ProcNo,  int& DataPointNo) const;
1536    
1537    
1538    /**    /**
1539       \brief       \brief
1540       Check *this and the right operand are compatible. Throws       Check *this and the right operand are compatible. Throws
# Line 1370  class Data { Line 1606  class Data {
1606       \brief       \brief
1607       Construct a Data object of the appropriate type.       Construct a Data object of the appropriate type.
1608    */    */
1609    template <class IValueType>  
1610    void    void
1611    initialise(const IValueType& value,    initialise(const DataTypes::ValueType& value,
1612             const DataTypes::ShapeType& shape,
1613               const FunctionSpace& what,               const FunctionSpace& what,
1614               bool expanded);               bool expanded);
1615    
1616      void
1617      initialise(const WrappedArray& value,
1618                     const FunctionSpace& what,
1619                     bool expanded);
1620    
1621    //    //
1622    // flag to protect the data object against any update    // flag to protect the data object against any update
1623    bool m_protected;    bool m_protected;
1624      mutable bool m_shared;
1625      bool m_lazy;
1626    
1627    //    //
1628    // pointer to the actual data object    // pointer to the actual data object
1629    boost::shared_ptr<DataAbstract> m_data;  //   boost::shared_ptr<DataAbstract> m_data;
1630      DataAbstract_ptr m_data;
1631    
1632  };  // If possible please use getReadyPtr instead.
1633    // But see warning below.
1634      const DataReady*
1635      getReady() const;
1636    
1637  template <class IValueType>    DataReady*
1638  void    getReady();
1639  Data::initialise(const IValueType& value,  
1640                   const FunctionSpace& what,  
1641                   bool expanded)  // Be wary of using this for local operations since it (temporarily) increases reference count.
1642  {  // If you are just using this to call a method on DataReady instead of DataAbstract consider using
1643    // getReady() instead
1644      DataReady_ptr
1645      getReadyPtr();
1646    
1647      const_DataReady_ptr
1648      getReadyPtr() const;
1649    
1650    
1651      /**
1652       \brief Update the Data's shared flag
1653       This indicates that the DataAbstract used by this object is now shared (or no longer shared).
1654       For internal use only.
1655      */
1656      void updateShareStatus(bool nowshared) const
1657      {
1658        m_shared=nowshared;     // m_shared is mutable
1659      }
1660    
1661      // In the isShared() method below:
1662      // A problem would occur if m_data (the address pointed to) were being modified
1663      // while the call m_data->is_shared is being executed.
1664      //
1665      // Q: So why do I think this code can be thread safe/correct?
1666      // A: We need to make some assumptions.
1667      // 1. We assume it is acceptable to return true under some conditions when we aren't shared.
1668      // 2. We assume that no constructions or assignments which will share previously unshared
1669      //    will occur while this call is executing. This is consistent with the way Data:: and C are written.
1670    //    //
1671    // 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
1672    // 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.
1673    // 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.
1674    // within the shared_ptr constructor.    // For any threads executing before the flag switches they will assume the object is still shared.
1675    if (expanded) {    bool isShared() const
1676      DataAbstract* temp=new DataExpanded(value,what);    {
1677      boost::shared_ptr<DataAbstract> temp_data(temp);      return m_shared;
1678      m_data=temp_data;  /*  if (m_shared) return true;
1679    } else {      if (m_data->isShared())        
1680      DataAbstract* temp=new DataConstant(value,what);      {                  
1681      boost::shared_ptr<DataAbstract> temp_data(temp);          updateShareStatus(true);
1682      m_data=temp_data;          return true;
1683        }
1684        return false;*/
1685      }
1686    
1687      void forceResolve()
1688      {
1689        if (isLazy())
1690        {
1691            #ifdef _OPENMP
1692            if (omp_in_parallel())
1693            {   // Yes this is throwing an exception out of an omp thread which is forbidden.
1694            throw DataException("Please do not call forceResolve() in a parallel region.");
1695            }
1696            #endif
1697            resolve();
1698        }
1699      }
1700    
1701      /**
1702      \brief if another object is sharing out member data make a copy to work with instead.
1703      This code should only be called from single threaded sections of code.
1704      */
1705      void exclusiveWrite()
1706      {
1707    #ifdef _OPENMP
1708      if (omp_in_parallel())
1709      {
1710    // *((int*)0)=17;
1711        throw DataException("Programming error. Please do not run exclusiveWrite() in multi-threaded sections.");
1712    }    }
1713    #endif
1714        forceResolve();
1715        if (isShared())
1716        {
1717            DataAbstract* t=m_data->deepCopy();
1718            set_m_data(DataAbstract_ptr(t));
1719        }
1720      }
1721    
1722      /**
1723      \brief checks if caller can have exclusive write to the object
1724      */
1725      void checkExclusiveWrite()
1726      {
1727        if  (isLazy() || isShared())
1728        {
1729            throw DataException("Programming error. ExclusiveWrite required - please call requireWrite()");
1730        }
1731      }
1732    
1733      /**
1734      \brief Modify the data abstract hosted by this Data object
1735      For internal use only.
1736      Passing a pointer to null is permitted (do this in the destructor)
1737      \warning Only to be called in single threaded code or inside a single/critical section. This method needs to be atomic.
1738      */
1739      void set_m_data(DataAbstract_ptr p);
1740    
1741      friend class DataAbstract;        // To allow calls to updateShareStatus
1742    
1743    };
1744    
1745    }   // end namespace escript
1746    
1747    
1748    // No, this is not supposed to be at the top of the file
1749    // DataAbstact needs to be declared first, then DataReady needs to be fully declared
1750    // so that I can dynamic cast between them below.
1751    #include "DataReady.h"
1752    #include "DataLazy.h"
1753    
1754    namespace escript
1755    {
1756    
1757    inline
1758    const DataReady*
1759    Data::getReady() const
1760    {
1761       const DataReady* dr=dynamic_cast<const DataReady*>(m_data.get());
1762       EsysAssert((dr!=0), "Error - casting to DataReady.");
1763       return dr;
1764  }  }
1765    
1766    inline
1767    DataReady*
1768    Data::getReady()
1769    {
1770       DataReady* dr=dynamic_cast<DataReady*>(m_data.get());
1771       EsysAssert((dr!=0), "Error - casting to DataReady.");
1772       return dr;
1773    }
1774    
1775    // Be wary of using this for local operations since it (temporarily) increases reference count.
1776    // If you are just using this to call a method on DataReady instead of DataAbstract consider using
1777    // getReady() instead
1778    inline
1779    DataReady_ptr
1780    Data::getReadyPtr()
1781    {
1782       DataReady_ptr dr=boost::dynamic_pointer_cast<DataReady>(m_data);
1783       EsysAssert((dr.get()!=0), "Error - casting to DataReady.");
1784       return dr;
1785    }
1786    
1787    
1788    inline
1789    const_DataReady_ptr
1790    Data::getReadyPtr() const
1791    {
1792       const_DataReady_ptr dr=boost::dynamic_pointer_cast<const DataReady>(m_data);
1793       EsysAssert((dr.get()!=0), "Error - casting to DataReady.");
1794       return dr;
1795    }
1796    
1797    inline
1798    DataAbstract::ValueType::value_type*
1799    Data::getSampleDataRW(DataAbstract::ValueType::size_type sampleNo)
1800    {
1801       if (isLazy())
1802       {
1803        throw DataException("Error, attempt to acquire RW access to lazy data. Please call requireWrite() first.");
1804       }
1805       return getReady()->getSampleDataRW(sampleNo);
1806    }
1807    
1808    inline
1809    const DataAbstract::ValueType::value_type*
1810    Data::getSampleDataRO(DataAbstract::ValueType::size_type sampleNo, BufferGroup* bufferg)
1811    {
1812       DataLazy* l=dynamic_cast<DataLazy*>(m_data.get());
1813       if (l!=0)
1814       {
1815        size_t offset=0;
1816        if (bufferg==NULL)
1817        {
1818            throw DataException("Error, attempt to getSampleDataRO for lazy Data with buffer==NULL");
1819        }
1820        const DataTypes::ValueType* res=l->resolveSample(*bufferg,sampleNo,offset);
1821        return &((*res)[offset]);
1822       }
1823       return getReady()->getSampleDataRO(sampleNo);
1824    }
1825    
1826    
1827    
1828    /**
1829       Modify a filename for MPI parallel output to multiple files
1830    */
1831    char *Escript_MPI_appendRankToFileName(const char *, int, int);
1832    
1833  /**  /**
1834     Binary Data object operators.     Binary Data object operators.
1835  */  */
# Line 1519  ESCRIPT_DLL_API std::ostream& operator<< Line 1941  ESCRIPT_DLL_API std::ostream& operator<<
1941  /**  /**
1942    \brief    \brief
1943    Compute a tensor product of two Data objects    Compute a tensor product of two Data objects
1944    \param arg0 - Input - Data object    \param arg_0 - Input - Data object
1945    \param arg1 - Input - Data object    \param arg_1 - Input - Data object
1946    \param axis_offset - Input - axis offset    \param axis_offset - Input - axis offset
1947    \param transpose - Input - 0: transpose neither, 1: transpose arg0, 2: transpose arg1    \param transpose - Input - 0: transpose neither, 1: transpose arg0, 2: transpose arg1
1948  */  */
1949  ESCRIPT_DLL_API  ESCRIPT_DLL_API
1950  Data  Data
1951  C_GeneralTensorProduct(Data& arg0,  C_GeneralTensorProduct(Data& arg_0,
1952                       Data& arg1,                       Data& arg_1,
1953                       int axis_offset=0,                       int axis_offset=0,
1954                       int transpose=0);                       int transpose=0);
1955    
   
 /**  
   \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);  
   
1956  /**  /**
1957    \brief    \brief
1958    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 1966  Data::binaryOp(const Data& right,
1966  {  {
1967     //     //
1968     // 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
1969     if (getPointDataView().getRank()==0 && right.getPointDataView().getRank()!=0) {     if (getDataPointRank()==0 && right.getDataPointRank()!=0) {
1970       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.");
1971     }     }
1972    
1973       if (isLazy() || right.isLazy())
1974       {
1975         throw DataException("Programmer error - attempt to call binaryOp with Lazy Data.");
1976       }
1977     //     //
1978     // initially make the temporary a shallow copy     // initially make the temporary a shallow copy
1979     Data tempRight(right);     Data tempRight(right);
1980    
1981     if (getFunctionSpace()!=right.getFunctionSpace()) {     if (getFunctionSpace()!=right.getFunctionSpace()) {
1982       if (right.probeInterpolation(getFunctionSpace())) {       if (right.probeInterpolation(getFunctionSpace())) {
1983         //         //
# Line 1582  Data::binaryOp(const Data& right, Line 1987  Data::binaryOp(const Data& right,
1987         //         //
1988         // interpolate onto the RHS function space         // interpolate onto the RHS function space
1989         Data tempLeft(*this,right.getFunctionSpace());         Data tempLeft(*this,right.getFunctionSpace());
1990         m_data=tempLeft.m_data;  //        m_data=tempLeft.m_data;
1991           set_m_data(tempLeft.m_data);
1992       }       }
1993     }     }
1994     operandCheck(tempRight);     operandCheck(tempRight);
# Line 1598  Data::binaryOp(const Data& right, Line 2004  Data::binaryOp(const Data& right,
2004       // of any data type       // of any data type
2005       DataExpanded* leftC=dynamic_cast<DataExpanded*>(m_data.get());       DataExpanded* leftC=dynamic_cast<DataExpanded*>(m_data.get());
2006       EsysAssert((leftC!=0), "Programming error - casting to DataExpanded.");       EsysAssert((leftC!=0), "Programming error - casting to DataExpanded.");
2007       escript::binaryOp(*leftC,*(tempRight.m_data.get()),operation);       escript::binaryOp(*leftC,*(tempRight.getReady()),operation);
2008     } else if (isTagged()) {     } else if (isTagged()) {
2009       //       //
2010       // 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 2052  Data::algorithm(BinaryFunction operation
2052      DataConstant* leftC=dynamic_cast<DataConstant*>(m_data.get());      DataConstant* leftC=dynamic_cast<DataConstant*>(m_data.get());
2053      EsysAssert((leftC!=0), "Programming error - casting to DataConstant.");      EsysAssert((leftC!=0), "Programming error - casting to DataConstant.");
2054      return escript::algorithm(*leftC,operation,initial_value);      return escript::algorithm(*leftC,operation,initial_value);
2055      } else if (isEmpty()) {
2056        throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2057      } else if (isLazy()) {
2058        throw DataException("Error - Operations not permitted on instances of DataLazy.");
2059      } else {
2060        throw DataException("Error - Data encapsulates an unknown type.");
2061    }    }
   return 0;  
2062  }  }
2063    
2064  /**  /**
# Line 1663  inline Line 2074  inline
2074  Data  Data
2075  Data::dp_algorithm(BinaryFunction operation, double initial_value) const  Data::dp_algorithm(BinaryFunction operation, double initial_value) const
2076  {  {
2077    if (isExpanded()) {    if (isEmpty()) {
2078      Data result(0,DataArrayView::ShapeType(),getFunctionSpace(),isExpanded());      throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2079      }
2080      else if (isExpanded()) {
2081        Data result(0,DataTypes::ShapeType(),getFunctionSpace(),isExpanded());
2082      DataExpanded* dataE=dynamic_cast<DataExpanded*>(m_data.get());      DataExpanded* dataE=dynamic_cast<DataExpanded*>(m_data.get());
2083      DataExpanded* resultE=dynamic_cast<DataExpanded*>(result.m_data.get());      DataExpanded* resultE=dynamic_cast<DataExpanded*>(result.m_data.get());
2084      EsysAssert((dataE!=0), "Programming error - casting data to DataExpanded.");      EsysAssert((dataE!=0), "Programming error - casting data to DataExpanded.");
2085      EsysAssert((resultE!=0), "Programming error - casting result to DataExpanded.");      EsysAssert((resultE!=0), "Programming error - casting result to DataExpanded.");
2086      escript::dp_algorithm(*dataE,*resultE,operation,initial_value);      escript::dp_algorithm(*dataE,*resultE,operation,initial_value);
2087      return result;      return result;
2088    } else if (isTagged()) {    }
2089      else if (isTagged()) {
2090      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());  
2091      EsysAssert((dataT!=0), "Programming error - casting data to DataTagged.");      EsysAssert((dataT!=0), "Programming error - casting data to DataTagged.");
2092      EsysAssert((resultT!=0), "Programming error - casting result to DataTagged.");      DataTypes::ValueType defval(1);
2093        defval[0]=0;
2094        DataTagged* resultT=new DataTagged(getFunctionSpace(), DataTypes::scalarShape, defval, dataT);
2095      escript::dp_algorithm(*dataT,*resultT,operation,initial_value);      escript::dp_algorithm(*dataT,*resultT,operation,initial_value);
2096      return result;      return Data(resultT);   // note: the Data object now owns the resultT pointer
2097    } else if (isConstant()) {    }
2098      Data result(0,DataArrayView::ShapeType(),getFunctionSpace(),isExpanded());    else if (isConstant()) {
2099        Data result(0,DataTypes::ShapeType(),getFunctionSpace(),isExpanded());
2100      DataConstant* dataC=dynamic_cast<DataConstant*>(m_data.get());      DataConstant* dataC=dynamic_cast<DataConstant*>(m_data.get());
2101      DataConstant* resultC=dynamic_cast<DataConstant*>(result.m_data.get());      DataConstant* resultC=dynamic_cast<DataConstant*>(result.m_data.get());
2102      EsysAssert((dataC!=0), "Programming error - casting data to DataConstant.");      EsysAssert((dataC!=0), "Programming error - casting data to DataConstant.");
2103      EsysAssert((resultC!=0), "Programming error - casting result to DataConstant.");      EsysAssert((resultC!=0), "Programming error - casting result to DataConstant.");
2104      escript::dp_algorithm(*dataC,*resultC,operation,initial_value);      escript::dp_algorithm(*dataC,*resultC,operation,initial_value);
2105      return result;      return result;
2106      } else if (isLazy()) {
2107        throw DataException("Error - Operations not permitted on instances of DataLazy.");
2108      } else {
2109        throw DataException("Error - Data encapsulates an unknown type.");
2110    }    }
   Data falseRetVal; // to keep compiler quiet  
   return falseRetVal;  
2111  }  }
2112    
2113    /**
2114      \brief
2115      Compute a tensor operation with two Data objects
2116      \param arg_0 - Input - Data object
2117      \param arg_1 - Input - Data object
2118      \param operation - Input - Binary op functor
2119    */
2120  template <typename BinaryFunction>  template <typename BinaryFunction>
2121    inline
2122  Data  Data
2123  C_TensorBinaryOperation(Data const &arg_0,  C_TensorBinaryOperation(Data const &arg_0,
2124                          Data const &arg_1,                          Data const &arg_1,
2125                          BinaryFunction operation)                          BinaryFunction operation)
2126  {  {
2127      if (arg_0.isEmpty() || arg_1.isEmpty())
2128      {
2129         throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2130      }
2131      if (arg_0.isLazy() || arg_1.isLazy())
2132      {
2133         throw DataException("Error - Operations not permitted on lazy data.");
2134      }
2135    // Interpolate if necessary and find an appropriate function space    // Interpolate if necessary and find an appropriate function space
2136    Data arg_0_Z, arg_1_Z;    Data arg_0_Z, arg_1_Z;
2137    if (arg_0.getFunctionSpace()!=arg_1.getFunctionSpace()) {    if (arg_0.getFunctionSpace()!=arg_1.getFunctionSpace()) {
# Line 1730  C_TensorBinaryOperation(Data const &arg_ Line 2153  C_TensorBinaryOperation(Data const &arg_
2153    // Get rank and shape of inputs    // Get rank and shape of inputs
2154    int rank0 = arg_0_Z.getDataPointRank();    int rank0 = arg_0_Z.getDataPointRank();
2155    int rank1 = arg_1_Z.getDataPointRank();    int rank1 = arg_1_Z.getDataPointRank();
2156    DataArrayView::ShapeType shape0 = arg_0_Z.getDataPointShape();    DataTypes::ShapeType shape0 = arg_0_Z.getDataPointShape();
2157    DataArrayView::ShapeType shape1 = arg_1_Z.getDataPointShape();    DataTypes::ShapeType shape1 = arg_1_Z.getDataPointShape();
2158    int size0 = arg_0_Z.getDataPointSize();    int size0 = arg_0_Z.getDataPointSize();
2159    int size1 = arg_1_Z.getDataPointSize();    int size1 = arg_1_Z.getDataPointSize();
   
2160    // Declare output Data object    // Declare output Data object
2161    Data res;    Data res;
2162    
2163    if (shape0 == shape1) {    if (shape0 == shape1) {
   
2164      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2165        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output
2166        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2167        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2168        double *ptr_2 = &((res.getPointDataView().getData())[0]);        double *ptr_2 = &(res.getDataAtOffsetRW(0));
2169    
2170        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2171      }      }
2172      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 2184  C_TensorBinaryOperation(Data const &arg_
2184    
2185        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2186        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2187        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2188        // Get the views  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2189        // Get the pointers to the actual data        // Get the pointers to the actual data
2190        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2191        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2192    
2193        // Compute a result for the default        // Compute a result for the default
2194        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2195        // Compute a result for each tag        // Compute a result for each tag
2196        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2197        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
2198        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2199          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2200          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2201          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2202          double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2203          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2204        }        }
2205    
2206      }      }
2207      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {
   
2208        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2209        DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());        DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());
2210        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 2214  C_TensorBinaryOperation(Data const &arg_
2214        int numSamples_1 = arg_1_Z.getNumSamples();        int numSamples_1 = arg_1_Z.getNumSamples();
2215        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2216        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2217          res.requireWrite();
2218        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2219        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2220          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2221            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2222            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2223            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2224            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2225            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2226            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2227          }          }
2228        }        }
2229    
2230      }      }
2231      else if (arg_0_Z.isTagged()     && arg_1_Z.isConstant()) {      else if (arg_0_Z.isTagged()     && arg_1_Z.isConstant()) {
   
2232        // Borrow DataTagged input from Data object        // Borrow DataTagged input from Data object
2233        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2234    
# Line 1823  C_TensorBinaryOperation(Data const &arg_ Line 2242  C_TensorBinaryOperation(Data const &arg_
2242    
2243        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2244        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2245        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);  
2246        // 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();  
2247        // Get the pointers to the actual data        // Get the pointers to the actual data
2248        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2249        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2250        // Compute a result for the default        // Compute a result for the default
2251        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2252        // Compute a result for each tag        // Compute a result for each tag
2253        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2254        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
2255        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2256          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2257          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2258          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);  
2259          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2260        }        }
2261    
2262      }      }
2263      else if (arg_0_Z.isTagged()     && arg_1_Z.isTagged()) {      else if (arg_0_Z.isTagged()     && arg_1_Z.isTagged()) {
   
2264        // Borrow DataTagged input from Data object        // Borrow DataTagged input from Data object
2265        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());        DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2266    
# Line 1858  C_TensorBinaryOperation(Data const &arg_ Line 2272  C_TensorBinaryOperation(Data const &arg_
2272        res.tag();        // DataTagged output        res.tag();        // DataTagged output
2273        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2274    
       // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2275        // Get the pointers to the actual data        // Get the pointers to the actual data
2276        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2277        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2278        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2279    
2280        // Compute a result for the default        // Compute a result for the default
2281        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2282        // Merge the tags        // Merge the tags
# Line 1873  C_TensorBinaryOperation(Data const &arg_ Line 2284  C_TensorBinaryOperation(Data const &arg_
2284        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2285        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2286        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2287          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
2288        }        }
2289        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2290          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2291        }        }
2292        // Compute a result for each tag        // Compute a result for each tag
2293        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2294        for (i=lookup_2.begin();i!=lookup_2.end();i++) {        for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2295          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);  
2296          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2297          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2298          double *ptr_0 = &view_0.getData(0);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2299          double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2300          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2301        }        }
2302    
2303      }      }
2304      else if (arg_0_Z.isTagged()     && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isTagged()     && arg_1_Z.isExpanded()) {
   
2305        // 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
2306        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2307        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 2311  C_TensorBinaryOperation(Data const &arg_
2311        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2312        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2313        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2314          res.requireWrite();
2315        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2316        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2317          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
2318          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2319          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2320            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2321            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2322            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2323            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2324            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2325          }          }
2326        }        }
2327    
2328      }      }
2329      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {
   
2330        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2331        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2332        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 2336  C_TensorBinaryOperation(Data const &arg_
2336        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2337        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2338        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2339          res.requireWrite();
2340        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2341        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2342          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2343            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2344            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2345            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);  
2346            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2347            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2348              double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2349    
2350    
2351            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2352          }          }
2353        }        }
2354    
2355      }      }
2356      else if (arg_0_Z.isExpanded()   && arg_1_Z.isTagged()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isTagged()) {
   
2357        // 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
2358        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2359        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 2363  C_TensorBinaryOperation(Data const &arg_
2363        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2364        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2365        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2366          res.requireWrite();
2367        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2368        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2369          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2370          double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2371          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2372            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2373            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2374            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2375            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2376            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2377          }          }
2378        }        }
2379    
2380      }      }
2381      else if (arg_0_Z.isExpanded()   && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isExpanded()) {
   
2382        // 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
2383        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2384        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 2388  C_TensorBinaryOperation(Data const &arg_
2388        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2389        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2390        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2391          res.requireWrite();
2392        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2393        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2394          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2395            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2396            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2397            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2398            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2399            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2400            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2401            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1, ptr_2, operation);
2402          }          }
2403        }        }
# Line 1995  C_TensorBinaryOperation(Data const &arg_ Line 2408  C_TensorBinaryOperation(Data const &arg_
2408      }      }
2409    
2410    } else if (0 == rank0) {    } else if (0 == rank0) {
   
2411      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2412        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace());      // DataConstant output        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace());      // DataConstant output
2413        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2414        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2415        double *ptr_2 = &((res.getPointDataView().getData())[0]);        double *ptr_2 = &(res.getDataAtOffsetRW(0));
2416        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2417      }      }
2418      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 2430  C_TensorBinaryOperation(Data const &arg_
2430    
2431        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2432        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2433        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2434        // Get the views  
2435        DataArrayView view_1 = tmp_1->getDefaultValue();        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2436        DataArrayView view_2 = tmp_2->getDefaultValue();        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2437        // Get the pointers to the actual data  
       double *ptr_1 = &((view_1.getData())[0]);  
       double *ptr_2 = &((view_2.getData())[0]);  
2438        // Compute a result for the default        // Compute a result for the default
2439        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2440        // Compute a result for each tag        // Compute a result for each tag
2441        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2442        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
2443        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2444          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2445          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2446          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);  
2447          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2448        }        }
2449    
# Line 2051  C_TensorBinaryOperation(Data const &arg_ Line 2459  C_TensorBinaryOperation(Data const &arg_
2459        int numSamples_1 = arg_1_Z.getNumSamples();        int numSamples_1 = arg_1_Z.getNumSamples();
2460        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2461        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2462          res.requireWrite();
2463        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2464        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2465          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2466            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2467            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2468            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2469            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2470            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2471            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2472    
2473          }          }
# Line 2080  C_TensorBinaryOperation(Data const &arg_ Line 2489  C_TensorBinaryOperation(Data const &arg_
2489    
2490        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2491        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2492        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2493        // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2494        // Get the pointers to the actual data        // Get the pointers to the actual data
2495        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2496        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2497    
2498    
2499        // Compute a result for the default        // Compute a result for the default
2500        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2501        // Compute a result for each tag        // Compute a result for each tag
2502        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2503        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
2504        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2505          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2506          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2507          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2508          double *ptr_0 = &view_0.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2509          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2510        }        }
2511    
# Line 2115  C_TensorBinaryOperation(Data const &arg_ Line 2523  C_TensorBinaryOperation(Data const &arg_
2523        res.tag();        // DataTagged output        res.tag();        // DataTagged output
2524        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2525    
       // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2526        // Get the pointers to the actual data        // Get the pointers to the actual data
2527        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2528        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2529        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2530    
2531        // Compute a result for the default        // Compute a result for the default
2532        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);        tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2533        // Merge the tags        // Merge the tags
# Line 2130  C_TensorBinaryOperation(Data const &arg_ Line 2535  C_TensorBinaryOperation(Data const &arg_
2535        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2536        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2537        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2538          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
2539        }        }
2540        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2541          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2542        }        }
2543        // Compute a result for each tag        // Compute a result for each tag
2544        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2545        for (i=lookup_2.begin();i!=lookup_2.end();i++) {        for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2546          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2547          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2548          DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);          double *ptr_2 = &(tmp_2->getDataByTagRW(i->first,0));
2549          double *ptr_0 = &view_0.getData(0);  
         double *ptr_1 = &view_1.getData(0);  
         double *ptr_2 = &view_2.getData(0);  
2550          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);          tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2551        }        }
2552    
# Line 2159  C_TensorBinaryOperation(Data const &arg_ Line 2562  C_TensorBinaryOperation(Data const &arg_
2562        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2563        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2564        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2565          res.requireWrite();
2566        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2567        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2568          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
2569          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2570          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2571            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2572            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2573            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2574            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2575            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2576          }          }
2577        }        }
2578    
2579      }      }
2580      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {
   
2581        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape1, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2582        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2583        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 2587  C_TensorBinaryOperation(Data const &arg_
2587        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2588        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2589        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2590          res.requireWrite();
2591        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2592        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2593          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2594            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2595            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2596            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2597            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2598            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2599            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2600          }          }
2601        }        }
# Line 2209  C_TensorBinaryOperation(Data const &arg_ Line 2613  C_TensorBinaryOperation(Data const &arg_
2613        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2614        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2615        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2616          res.requireWrite();
2617        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2618        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2619          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2620          double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2621          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2622            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2623            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2624            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2625            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2626            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2627          }          }
2628        }        }
# Line 2234  C_TensorBinaryOperation(Data const &arg_ Line 2639  C_TensorBinaryOperation(Data const &arg_
2639        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2640        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2641        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2642          res.requireWrite();
2643        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2644        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2645          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2646            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2647            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2648            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2649            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2650            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2651            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2652            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);            tensor_binary_operation(size1, ptr_0[0], ptr_1, ptr_2, operation);
2653          }          }
2654        }        }
# Line 2253  C_TensorBinaryOperation(Data const &arg_ Line 2659  C_TensorBinaryOperation(Data const &arg_
2659      }      }
2660    
2661    } else if (0 == rank1) {    } else if (0 == rank1) {
   
2662      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {      if (arg_0_Z.isConstant()   && arg_1_Z.isConstant()) {
2663        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace());      // DataConstant output
2664        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2665        double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);        const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(0));
2666        double *ptr_2 = &((res.getPointDataView().getData())[0]);        double *ptr_2 = &(res.getDataAtOffsetRW(0));
2667        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2668      }      }
2669      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 2681  C_TensorBinaryOperation(Data const &arg_
2681    
2682        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2683        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2684        double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);        const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2685        // Get the views  
2686        DataArrayView view_1 = tmp_1->getDefaultValue();        //Get the pointers to the actual data
2687        DataArrayView view_2 = tmp_2->getDefaultValue();        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2688        // Get the pointers to the actual data        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2689        double *ptr_1 = &((view_1.getData())[0]);  
       double *ptr_2 = &((view_2.getData())[0]);  
2690        // Compute a result for the default        // Compute a result for the default
2691        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2692        // Compute a result for each tag        // Compute a result for each tag
2693        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2694        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
2695        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2696          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2697          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2698          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);  
2699          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2700        }        }
   
2701      }      }
2702      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {      else if (arg_0_Z.isConstant()   && arg_1_Z.isExpanded()) {
2703    
# Line 2309  C_TensorBinaryOperation(Data const &arg_ Line 2710  C_TensorBinaryOperation(Data const &arg_
2710        int numSamples_1 = arg_1_Z.getNumSamples();        int numSamples_1 = arg_1_Z.getNumSamples();
2711        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2712        int offset_0 = tmp_0->getPointOffset(0,0);        int offset_0 = tmp_0->getPointOffset(0,0);
2713          res.requireWrite();
2714        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)        #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2715        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {        for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2716          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {          for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2717            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2718            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);            int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2719            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2720            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2721            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2722            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2723          }          }
2724        }        }
# Line 2337  C_TensorBinaryOperation(Data const &arg_ Line 2739  C_TensorBinaryOperation(Data const &arg_
2739    
2740        // Prepare offset into DataConstant        // Prepare offset into DataConstant
2741        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2742        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();  
2743        // Get the pointers to the actual data        // Get the pointers to the actual data
2744        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2745        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2746        // Compute a result for the default        // Compute a result for the default
2747        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2748        // Compute a result for each tag        // Compute a result for each tag
2749        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2750        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
2751        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2752          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2753          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2754          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);  
2755          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2756        }        }
2757    
# Line 2372  C_TensorBinaryOperation(Data const &arg_ Line 2769  C_TensorBinaryOperation(Data const &arg_
2769        res.tag();        // DataTagged output        res.tag();        // DataTagged output
2770        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());        DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2771    
       // Get the views  
       DataArrayView view_0 = tmp_0->getDefaultValue();  
       DataArrayView view_1 = tmp_1->getDefaultValue();  
       DataArrayView view_2 = tmp_2->getDefaultValue();  
2772        // Get the pointers to the actual data        // Get the pointers to the actual data
2773        double *ptr_0 = &((view_0.getData())[0]);        const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2774        double *ptr_1 = &((view_1.getData())[0]);        const double *ptr_1 = &(tmp_1->getDefaultValueRO(0));
2775        double *ptr_2 = &((view_2.getData())[0]);        double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2776    
2777        // Compute a result for the default        // Compute a result for the default
2778        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);        tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2779        // Merge the tags        // Merge the tags
# Line 2387  C_TensorBinaryOperation(Data const &arg_ Line 2781  C_TensorBinaryOperation(Data const &arg_
2781        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();        const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2782        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();        const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2783        for (i=lookup_0.begin();i!=lookup_0.end();i++) {        for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2784          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
2785        }        }
2786        for (i=lookup_1.begin();i!=lookup_1.end();i++) {        for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2787          tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());          tmp_2->addTag(i->first);
2788        }        }
2789        // Compute a result for each tag        // Compute a result for each tag
2790        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();        const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2791        for (i=lookup_2.begin();i!=lookup_2.end();i++) {        for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2792          DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);          const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2793          DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);          const double *ptr_1 = &(tmp_1->getDataByTagRO(i->first,0));
2794          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);  
2795          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);          tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2796        }        }
2797    
# Line 2416  C_TensorBinaryOperation(Data const &arg_ Line 2807  C_TensorBinaryOperation(Data const &arg_
2807        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2808        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2809        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2810          res.requireWrite();
2811        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2812        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2813          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
2814          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2815          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2816            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2817            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2818            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2819            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2820            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2821          }          }
2822        }        }
2823    
2824      }      }
2825      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {      else if (arg_0_Z.isExpanded()   && arg_1_Z.isConstant()) {
   
2826        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output        res = Data(0.0, shape0, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2827        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());        DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2828        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 2832  C_TensorBinaryOperation(Data const &arg_
2832        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2833        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2834        int offset_1 = tmp_1->getPointOffset(0,0);        int offset_1 = tmp_1->getPointOffset(0,0);
2835          res.requireWrite();
2836        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2837        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2838          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2839            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2840            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2841            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2842            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2843            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2844            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2845          }          }
2846        }        }
# Line 2466  C_TensorBinaryOperation(Data const &arg_ Line 2858  C_TensorBinaryOperation(Data const &arg_
2858        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2859        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2860        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2861          res.requireWrite();
2862        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2863        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2864          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);          int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2865          double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);          const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2866          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2867            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2868            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2869            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2870            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2871            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2872          }          }
2873        }        }
# Line 2491  C_TensorBinaryOperation(Data const &arg_ Line 2884  C_TensorBinaryOperation(Data const &arg_
2884        int sampleNo_0,dataPointNo_0;        int sampleNo_0,dataPointNo_0;
2885        int numSamples_0 = arg_0_Z.getNumSamples();        int numSamples_0 = arg_0_Z.getNumSamples();
2886        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();        int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2887          res.requireWrite();
2888        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)        #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2889        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {        for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2890          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {          for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2891            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2892            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2893            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);            int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2894            double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);            const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2895            double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);            const double *ptr_1 = &(arg_1_Z.getDataAtOffsetRO(offset_1));
2896            double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);            double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2897            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);            tensor_binary_operation(size0, ptr_0, ptr_1[0], ptr_2, operation);
2898          }          }
2899        }        }
# Line 2521  Data Line 2915  Data
2915  C_TensorUnaryOperation(Data const &arg_0,  C_TensorUnaryOperation(Data const &arg_0,
2916                         UnaryFunction operation)                         UnaryFunction operation)
2917  {  {
2918      if (arg_0.isEmpty())  // do this before we attempt to interpolate
2919      {
2920         throw DataException("Error - Operations not permitted on instances of DataEmpty.");
2921      }
2922      if (arg_0.isLazy())
2923      {
2924         throw DataException("Error - Operations not permitted on lazy data.");
2925      }
2926    // Interpolate if necessary and find an appropriate function space    // Interpolate if necessary and find an appropriate function space
2927    Data arg_0_Z = Data(arg_0);    Data arg_0_Z = Data(arg_0);
2928    
2929    // Get rank and shape of inputs    // Get rank and shape of inputs
2930    int rank0 = arg_0_Z.getDataPointRank();    const DataTypes::ShapeType& shape0 = arg_0_Z.getDataPointShape();
   DataArrayView::ShapeType shape0 = arg_0_Z.getDataPointShape();  
2931    int size0 = arg_0_Z.getDataPointSize();    int size0 = arg_0_Z.getDataPointSize();
2932    
2933    // Declare output Data object    // Declare output Data object
# Line 2534  C_TensorUnaryOperation(Data const &arg_0 Line 2935  C_TensorUnaryOperation(Data const &arg_0
2935    
2936    if (arg_0_Z.isConstant()) {    if (arg_0_Z.isConstant()) {
2937      res = Data(0.0, shape0, arg_0_Z.getFunctionSpace());      // DataConstant output      res = Data(0.0, shape0, arg_0_Z.getFunctionSpace());      // DataConstant output
2938      double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);      const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(0));
2939      double *ptr_2 = &((res.getPointDataView().getData())[0]);      double *ptr_2 = &(res.getDataAtOffsetRW(0));
2940      tensor_unary_operation(size0, ptr_0, ptr_2, operation);      tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2941    }    }
2942    else if (arg_0_Z.isTagged()) {    else if (arg_0_Z.isTagged()) {
# Line 2548  C_TensorUnaryOperation(Data const &arg_0 Line 2949  C_TensorUnaryOperation(Data const &arg_0
2949      res.tag();      res.tag();
2950      DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());      DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2951    
     // Get the views  
     DataArrayView view_0 = tmp_0->getDefaultValue();  
     DataArrayView view_2 = tmp_2->getDefaultValue();  
2952      // Get the pointers to the actual data      // Get the pointers to the actual data
2953      double *ptr_0 = &((view_0.getData())[0]);      const double *ptr_0 = &(tmp_0->getDefaultValueRO(0));
2954      double *ptr_2 = &((view_2.getData())[0]);      double *ptr_2 = &(tmp_2->getDefaultValueRW(0));
2955      // Compute a result for the default      // Compute a result for the default
2956      tensor_unary_operation(size0, ptr_0, ptr_2, operation);      tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2957      // Compute a result for each tag      // Compute a result for each tag
2958      const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();      const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2959      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
2960      for (i=lookup_0.begin();i!=lookup_0.end();i++) {      for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2961        tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());        tmp_2->addTag(i->first);
2962        DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);        const double *ptr_0 = &(tmp_0->getDataByTagRO(i->first,0));
2963        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);  
2964        tensor_unary_operation(size0, ptr_0, ptr_2, operation);        tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2965      }      }
2966    
# Line 2583  C_TensorUnaryOperation(Data const &arg_0 Line 2979  C_TensorUnaryOperation(Data const &arg_0
2979        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {        for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2980          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2981          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);          int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2982          double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);          const double *ptr_0 = &(arg_0_Z.getDataAtOffsetRO(offset_0));
2983          double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);          double *ptr_2 = &(res.getDataAtOffsetRW(offset_2));
2984          tensor_unary_operation(size0, ptr_0, ptr_2, operation);          tensor_unary_operation(size0, ptr_0, ptr_2, operation);
2985        }        }
2986      }      }
   
2987    }    }
2988    else {    else {
2989      throw DataException("Error - C_TensorUnaryOperation: unknown combination of inputs");      throw DataException("Error - C_TensorUnaryOperation: unknown combination of inputs");

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