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trunk/escript/src/DataLazy.cpp revision 4264 by jfenwick, Thu Feb 28 11:32:57 2013 UTC trunk/escriptcore/src/DataLazy.cpp revision 6042 by jfenwick, Wed Mar 9 04:30:36 2016 UTC
# Line 1  Line 1 
1    
2  /*****************************************************************************  /*****************************************************************************
3  *  *
4  * Copyright (c) 2003-2013 by University of Queensland  * Copyright (c) 2003-2016 by The University of Queensland
5  * http://www.uq.edu.au  * http://www.uq.edu.au
6  *  *
7  * Primary Business: Queensland, Australia  * Primary Business: Queensland, Australia
# Line 9  Line 9 
9  * http://www.opensource.org/licenses/osl-3.0.php  * http://www.opensource.org/licenses/osl-3.0.php
10  *  *
11  * Development until 2012 by Earth Systems Science Computational Center (ESSCC)  * Development until 2012 by Earth Systems Science Computational Center (ESSCC)
12  * Development since 2012 by School of Earth Sciences  * Development 2012-2013 by School of Earth Sciences
13    * Development from 2014 by Centre for Geoscience Computing (GeoComp)
14  *  *
15  *****************************************************************************/  *****************************************************************************/
16    
   
17  #include "DataLazy.h"  #include "DataLazy.h"
 #include "esysUtils/Esys_MPI.h"  
 #ifdef _OPENMP  
 #include <omp.h>  
 #endif  
 #include "FunctionSpace.h"  
 #include "DataTypes.h"  
18  #include "Data.h"  #include "Data.h"
19  #include "UnaryFuncs.h"     // for escript::fsign  #include "DataTypes.h"
 #include "Utils.h"  
   
20  #include "EscriptParams.h"  #include "EscriptParams.h"
21    #include "FunctionSpace.h"
22    #include "UnaryFuncs.h"    // for escript::fsign
23    #include "Utils.h"
24    #include "DataMaths.h"
25    
26  #ifdef USE_NETCDF  #ifdef USE_NETCDF
27  #include <netcdfcpp.h>  #include <netcdfcpp.h>
28  #endif  #endif
29    
30  #include <iomanip>      // for some fancy formatting in debug  #include <iomanip> // for some fancy formatting in debug
31    
32    using namespace escript::DataTypes;
33    
34    #define NO_ARG
35    
36  // #define LAZYDEBUG(X) if (privdebug){X;}  // #define LAZYDEBUG(X) if (privdebug){X;}
37  #define LAZYDEBUG(X)  #define LAZYDEBUG(X)
# Line 61  A special operation, IDENTITY, stores an Line 61  A special operation, IDENTITY, stores an
61  This means that all "internal" nodes in the structure are instances of DataLazy.  This means that all "internal" nodes in the structure are instances of DataLazy.
62    
63  Each operation has a string representation as well as an opgroup - eg G_IDENTITY, G_BINARY, ...  Each operation has a string representation as well as an opgroup - eg G_IDENTITY, G_BINARY, ...
64  Note that IDENITY is not considered a unary operation.  Note that IDENTITY is not considered a unary operation.
65    
66  I am avoiding calling the structure formed a tree because it is not guaranteed to be one (eg c=a+a).  I am avoiding calling the structure formed a tree because it is not guaranteed to be one (eg c=a+a).
67  It must however form a DAG (directed acyclic graph).  It must however form a DAG (directed acyclic graph).
# Line 69  I will refer to individual DataLazy obje Line 69  I will refer to individual DataLazy obje
69    
70  Each node also stores:  Each node also stores:
71  - m_readytype \in {'E','T','C','?'} ~ indicates what sort of DataReady would be produced if the expression was  - m_readytype \in {'E','T','C','?'} ~ indicates what sort of DataReady would be produced if the expression was
72      evaluated.          evaluated.
73  - m_buffsrequired ~ the larged number of samples which would need to be kept simultaneously in order to  - m_buffsrequired ~ the large number of samples which would need to be kept simultaneously in order to
74      evaluate the expression.          evaluate the expression.
75  - m_samplesize ~ the number of doubles stored in a sample.  - m_samplesize ~ the number of doubles stored in a sample.
76    
77  When a new node is created, the above values are computed based on the values in the child nodes.  When a new node is created, the above values are computed based on the values in the child nodes.
# Line 136  enum ES_opgroup Line 136  enum ES_opgroup
136  {  {
137     G_UNKNOWN,     G_UNKNOWN,
138     G_IDENTITY,     G_IDENTITY,
139     G_BINARY,        // pointwise operations with two arguments     G_BINARY,            // pointwise operations with two arguments
140     G_UNARY,     // pointwise operations with one argument     G_UNARY,             // pointwise operations with one argument
141     G_UNARY_P,       // pointwise operations with one argument, requiring a parameter     G_UNARY_P,           // pointwise operations with one argument, requiring a parameter
142     G_NP1OUT,        // non-pointwise op with one output     G_NP1OUT,            // non-pointwise op with one output
143     G_NP1OUT_P,      // non-pointwise op with one output requiring a parameter     G_NP1OUT_P,          // non-pointwise op with one output requiring a parameter
144     G_TENSORPROD,    // general tensor product     G_TENSORPROD,        // general tensor product
145     G_NP1OUT_2P,     // non-pointwise op with one output requiring two params     G_NP1OUT_2P,         // non-pointwise op with one output requiring two params
146     G_REDUCTION,     // non-pointwise unary op with a scalar output     G_REDUCTION,         // non-pointwise unary op with a scalar output
147     G_CONDEVAL     G_CONDEVAL
148  };  };
149    
# Line 151  enum ES_opgroup Line 151  enum ES_opgroup
151    
152    
153  string ES_opstrings[]={"UNKNOWN","IDENTITY","+","-","*","/","^",  string ES_opstrings[]={"UNKNOWN","IDENTITY","+","-","*","/","^",
154              "sin","cos","tan",                          "sin","cos","tan",
155              "asin","acos","atan","sinh","cosh","tanh","erf",                          "asin","acos","atan","sinh","cosh","tanh","erf",
156              "asinh","acosh","atanh",                          "asinh","acosh","atanh",
157              "log10","log","sign","abs","neg","pos","exp","sqrt",                          "log10","log","sign","abs","neg","pos","exp","sqrt",
158              "1/","where>0","where<0","where>=0","where<=0", "where<>0","where=0",                          "1/","where>0","where<0","where>=0","where<=0", "where<>0","where=0",
159              "symmetric","nonsymmetric",                          "symmetric","nonsymmetric",
160              "prod",                          "prod",
161              "transpose", "trace",                          "transpose", "trace",
162              "swapaxes",                          "swapaxes",
163              "minval", "maxval",                          "minval", "maxval",
164              "condEval"};                          "condEval"};
165  int ES_opcount=44;  int ES_opcount=44;
166  ES_opgroup opgroups[]={G_UNKNOWN,G_IDENTITY,G_BINARY,G_BINARY,G_BINARY,G_BINARY, G_BINARY,  ES_opgroup opgroups[]={G_UNKNOWN,G_IDENTITY,G_BINARY,G_BINARY,G_BINARY,G_BINARY, G_BINARY,
167              G_UNARY,G_UNARY,G_UNARY, //10                          G_UNARY,G_UNARY,G_UNARY, //10
168              G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,    // 17                          G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,        // 17
169              G_UNARY,G_UNARY,G_UNARY,                    // 20                          G_UNARY,G_UNARY,G_UNARY,                                        // 20
170              G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,    // 28                          G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,        // 28
171              G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY, G_UNARY_P, G_UNARY_P,      // 35                          G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY, G_UNARY_P, G_UNARY_P,          // 35
172              G_NP1OUT,G_NP1OUT,                          G_NP1OUT,G_NP1OUT,
173              G_TENSORPROD,                          G_TENSORPROD,
174              G_NP1OUT_P, G_NP1OUT_P,                          G_NP1OUT_P, G_NP1OUT_P,
175              G_NP1OUT_2P,                          G_NP1OUT_2P,
176              G_REDUCTION, G_REDUCTION,                          G_REDUCTION, G_REDUCTION,
177              G_CONDEVAL};                          G_CONDEVAL};
178  inline  inline
179  ES_opgroup  ES_opgroup
180  getOpgroup(ES_optype op)  getOpgroup(ES_optype op)
# Line 186  getOpgroup(ES_optype op) Line 186  getOpgroup(ES_optype op)
186  FunctionSpace  FunctionSpace
187  resultFS(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op)  resultFS(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op)
188  {  {
189      // perhaps this should call interpolate and throw or something?          // perhaps this should call interpolate and throw or something?
190      // maybe we need an interpolate node -          // maybe we need an interpolate node -
191      // that way, if interpolate is required in any other op we can just throw a          // that way, if interpolate is required in any other op we can just throw a
192      // programming error exception.          // programming error exception.
193    
194    FunctionSpace l=left->getFunctionSpace();    FunctionSpace l=left->getFunctionSpace();
195    FunctionSpace r=right->getFunctionSpace();    FunctionSpace r=right->getFunctionSpace();
# Line 198  resultFS(DataAbstract_ptr left, DataAbst Line 198  resultFS(DataAbstract_ptr left, DataAbst
198      signed char res=r.getDomain()->preferredInterpolationOnDomain(r.getTypeCode(), l.getTypeCode());      signed char res=r.getDomain()->preferredInterpolationOnDomain(r.getTypeCode(), l.getTypeCode());
199      if (res==1)      if (res==1)
200      {      {
201      return l;          return l;
202      }      }
203      if (res==-1)      if (res==-1)
204      {      {
205      return r;          return r;
206      }      }
207      throw DataException("Cannot interpolate between the FunctionSpaces given for operation "+opToString(op)+".");      throw DataException("Cannot interpolate between the FunctionSpaces given for operation "+opToString(op)+".");
208    }    }
# Line 214  resultFS(DataAbstract_ptr left, DataAbst Line 214  resultFS(DataAbstract_ptr left, DataAbst
214  DataTypes::ShapeType  DataTypes::ShapeType
215  resultShape(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op)  resultShape(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op)
216  {  {
217      if (left->getShape()!=right->getShape())          if (left->getShape()!=right->getShape())
218      {          {
219        if ((getOpgroup(op)!=G_BINARY) && (getOpgroup(op)!=G_NP1OUT))            if ((getOpgroup(op)!=G_BINARY) && (getOpgroup(op)!=G_NP1OUT))
220        {            {
221          throw DataException("Shapes not the name - shapes must match for (point)binary operations.");                  throw DataException("Shapes not the name - shapes must match for (point)binary operations.");
222        }            }
223    
224        if (left->getRank()==0)   // we need to allow scalar * anything            if (left->getRank()==0)       // we need to allow scalar * anything
225        {            {
226          return right->getShape();                  return right->getShape();
227        }            }
228        if (right->getRank()==0)            if (right->getRank()==0)
229        {            {
230          return left->getShape();                  return left->getShape();
231        }            }
232        throw DataException("Shapes not the same - arguments must have matching shapes (or be scalars) for (point)binary operations on lazy data.");            throw DataException("Shapes not the same - arguments must have matching shapes (or be scalars) for (point)binary operations on lazy data.");
233      }          }
234      return left->getShape();          return left->getShape();
235  }  }
236    
237  // return the shape for "op left"  // return the shape for "op left"
# Line 239  resultShape(DataAbstract_ptr left, DataA Line 239  resultShape(DataAbstract_ptr left, DataA
239  DataTypes::ShapeType  DataTypes::ShapeType
240  resultShape(DataAbstract_ptr left, ES_optype op, int axis_offset)  resultShape(DataAbstract_ptr left, ES_optype op, int axis_offset)
241  {  {
242      switch(op)          switch(op)
243      {          {
244          case TRANS:          case TRANS:
245         {            // for the scoping of variables             {                    // for the scoping of variables
246          const DataTypes::ShapeType& s=left->getShape();                  const DataTypes::ShapeType& s=left->getShape();
247          DataTypes::ShapeType sh;                  DataTypes::ShapeType sh;
248          int rank=left->getRank();                  int rank=left->getRank();
249          if (axis_offset<0 || axis_offset>rank)                  if (axis_offset<0 || axis_offset>rank)
250          {                  {
251              stringstream e;              stringstream e;
252              e << "Error - Data::transpose must have 0 <= axis_offset <= rank=" << rank;              e << "Error - Data::transpose must have 0 <= axis_offset <= rank=" << rank;
253              throw DataException(e.str());              throw DataException(e.str());
254          }          }
255          for (int i=0; i<rank; i++)          for (int i=0; i<rank; i++)
256          {                  {
257             int index = (axis_offset+i)%rank;                     int index = (axis_offset+i)%rank;
258             sh.push_back(s[index]); // Append to new shape             sh.push_back(s[index]); // Append to new shape
259          }          }
260          return sh;                  return sh;
261         }             }
262      break;          break;
263      case TRACE:          case TRACE:
264         {             {
265          int rank=left->getRank();                  int rank=left->getRank();
266          if (rank<2)                  if (rank<2)
267          {                  {
268             throw DataException("Trace can only be computed for objects with rank 2 or greater.");                     throw DataException("Trace can only be computed for objects with rank 2 or greater.");
269          }                  }
270          if ((axis_offset>rank-2) || (axis_offset<0))                  if ((axis_offset>rank-2) || (axis_offset<0))
271          {                  {
272             throw DataException("Trace: axis offset must lie between 0 and rank-2 inclusive.");                     throw DataException("Trace: axis offset must lie between 0 and rank-2 inclusive.");
273          }                  }
274          if (rank==2)                  if (rank==2)
275          {                  {
276             return DataTypes::scalarShape;                     return DataTypes::scalarShape;
277          }                  }
278          else if (rank==3)                  else if (rank==3)
279          {                  {
280             DataTypes::ShapeType sh;                     DataTypes::ShapeType sh;
281                 if (axis_offset==0)                     if (axis_offset==0)
282             {                     {
283                  sh.push_back(left->getShape()[2]);                          sh.push_back(left->getShape()[2]);
284                 }                     }
285                 else     // offset==1                     else         // offset==1
286             {                     {
287              sh.push_back(left->getShape()[0]);                          sh.push_back(left->getShape()[0]);
288                 }                     }
289             return sh;                     return sh;
290          }                  }
291          else if (rank==4)                  else if (rank==4)
292          {                  {
293             DataTypes::ShapeType sh;                     DataTypes::ShapeType sh;
294             const DataTypes::ShapeType& s=left->getShape();                     const DataTypes::ShapeType& s=left->getShape();
295                 if (axis_offset==0)                     if (axis_offset==0)
296             {                     {
297                  sh.push_back(s[2]);                          sh.push_back(s[2]);
298                  sh.push_back(s[3]);                          sh.push_back(s[3]);
299                 }                     }
300                 else if (axis_offset==1)                     else if (axis_offset==1)
301             {                     {
302                  sh.push_back(s[0]);                          sh.push_back(s[0]);
303                  sh.push_back(s[3]);                          sh.push_back(s[3]);
304                 }                     }
305             else     // offset==2                     else         // offset==2
306             {                     {
307              sh.push_back(s[0]);                          sh.push_back(s[0]);
308              sh.push_back(s[1]);                          sh.push_back(s[1]);
309             }                     }
310             return sh;                     return sh;
311          }                  }
312          else        // unknown rank                  else            // unknown rank
313          {                  {
314             throw DataException("Error - Data::trace can only be calculated for rank 2, 3 or 4 object.");                     throw DataException("Error - Data::trace can only be calculated for rank 2, 3 or 4 object.");
315          }                  }
316         }             }
317      break;          break;
318          default:          default:
319      throw DataException("Programmer error - resultShape(left,op) can't compute shapes for operator "+opToString(op)+".");          throw DataException("Programmer error - resultShape(left,op) can't compute shapes for operator "+opToString(op)+".");
320      }          }
321  }  }
322    
323  DataTypes::ShapeType  DataTypes::ShapeType
# Line 373  SwapShape(DataAbstract_ptr left, const i Line 373  SwapShape(DataAbstract_ptr left, const i
373  DataTypes::ShapeType  DataTypes::ShapeType
374  GTPShape(DataAbstract_ptr left, DataAbstract_ptr right, int axis_offset, int transpose, int& SL, int& SM, int& SR)  GTPShape(DataAbstract_ptr left, DataAbstract_ptr right, int axis_offset, int transpose, int& SL, int& SM, int& SR)
375  {  {
376                
377    // Get rank and shape of inputs    // Get rank and shape of inputs
378    int rank0 = left->getRank();    int rank0 = left->getRank();
379    int rank1 = right->getRank();    int rank1 = right->getRank();
# Line 382  GTPShape(DataAbstract_ptr left, DataAbst Line 382  GTPShape(DataAbstract_ptr left, DataAbst
382    
383    // Prepare for the loops of the product and verify compatibility of shapes    // Prepare for the loops of the product and verify compatibility of shapes
384    int start0=0, start1=0;    int start0=0, start1=0;
385    if (transpose == 0)       {}    if (transpose == 0)           {}
386    else if (transpose == 1)  { start0 = axis_offset; }    else if (transpose == 1)      { start0 = axis_offset; }
387    else if (transpose == 2)  { start1 = rank1-axis_offset; }    else if (transpose == 2)      { start1 = rank1-axis_offset; }
388    else              { throw DataException("DataLazy GeneralTensorProduct Constructor: Error - transpose should be 0, 1 or 2"); }    else                          { throw DataException("DataLazy GeneralTensorProduct Constructor: Error - transpose should be 0, 1 or 2"); }
389    
390    if (rank0<axis_offset)    if (rank0<axis_offset)
391    {    {
392      throw DataException("DataLazy GeneralTensorProduct Constructor: Error - rank of left < axisoffset");          throw DataException("DataLazy GeneralTensorProduct Constructor: Error - rank of left < axisoffset");
393    }    }
394    
395    // Adjust the shapes for transpose    // Adjust the shapes for transpose
396    DataTypes::ShapeType tmpShape0(rank0);    // pre-sizing the vectors rather    DataTypes::ShapeType tmpShape0(rank0);        // pre-sizing the vectors rather
397    DataTypes::ShapeType tmpShape1(rank1);    // than using push_back    DataTypes::ShapeType tmpShape1(rank1);        // than using push_back
398    for (int i=0; i<rank0; i++)   { tmpShape0[i]=shape0[(i+start0)%rank0]; }    for (int i=0; i<rank0; i++)   { tmpShape0[i]=shape0[(i+start0)%rank0]; }
399    for (int i=0; i<rank1; i++)   { tmpShape1[i]=shape1[(i+start1)%rank1]; }    for (int i=0; i<rank1; i++)   { tmpShape1[i]=shape1[(i+start1)%rank1]; }
400    
401    // Prepare for the loops of the product    // Prepare for the loops of the product
402    SL=1, SM=1, SR=1;    SL=1, SM=1, SR=1;
403    for (int i=0; i<rank0-axis_offset; i++)   {    for (int i=0; i<rank0-axis_offset; i++)       {
404      SL *= tmpShape0[i];      SL *= tmpShape0[i];
405    }    }
406    for (int i=rank0-axis_offset; i<rank0; i++)   {    for (int i=rank0-axis_offset; i<rank0; i++)   {
407      if (tmpShape0[i] != tmpShape1[i-(rank0-axis_offset)]) {      if (tmpShape0[i] != tmpShape1[i-(rank0-axis_offset)]) {
408        throw DataException("C_GeneralTensorProduct: Error - incompatible shapes");        throw DataException("C_GeneralTensorProduct: Error - incompatible shapes");
409      }      }
410      SM *= tmpShape0[i];      SM *= tmpShape0[i];
411    }    }
412    for (int i=axis_offset; i<rank1; i++)     {    for (int i=axis_offset; i<rank1; i++)         {
413      SR *= tmpShape1[i];      SR *= tmpShape1[i];
414    }    }
415    
416    // Define the shape of the output (rank of shape is the sum of the loop ranges below)    // Define the shape of the output (rank of shape is the sum of the loop ranges below)
417    DataTypes::ShapeType shape2(rank0+rank1-2*axis_offset);      DataTypes::ShapeType shape2(rank0+rank1-2*axis_offset);      
418    {         // block to limit the scope of out_index    {                     // block to limit the scope of out_index
419       int out_index=0;       int out_index=0;
420       for (int i=0; i<rank0-axis_offset; i++, ++out_index) { shape2[out_index]=tmpShape0[i]; } // First part of arg_0_Z       for (int i=0; i<rank0-axis_offset; i++, ++out_index) { shape2[out_index]=tmpShape0[i]; } // First part of arg_0_Z
421       for (int i=axis_offset; i<rank1; i++, ++out_index)   { shape2[out_index]=tmpShape1[i]; } // Last part of arg_1_Z       for (int i=axis_offset; i<rank1; i++, ++out_index)   { shape2[out_index]=tmpShape1[i]; } // Last part of arg_1_Z
# Line 431  GTPShape(DataAbstract_ptr left, DataAbst Line 431  GTPShape(DataAbstract_ptr left, DataAbst
431    return shape2;    return shape2;
432  }  }
433    
434  }   // end anonymous namespace  }       // end anonymous namespace
435    
436    
437    
# Line 466  void DataLazy::LazyNodeSetup() Line 466  void DataLazy::LazyNodeSetup()
466    
467  // Creates an identity node  // Creates an identity node
468  DataLazy::DataLazy(DataAbstract_ptr p)  DataLazy::DataLazy(DataAbstract_ptr p)
469      : parent(p->getFunctionSpace(),p->getShape())          : parent(p->getFunctionSpace(),p->getShape())
470      ,m_sampleids(0),          ,m_sampleids(0),
471      m_samples(1)          m_samples(1)
472  {  {
473     if (p->isLazy())     if (p->isLazy())
474     {     {
475      // I don't want identity of Lazy.          // I don't want identity of Lazy.
476      // Question: Why would that be so bad?          // Question: Why would that be so bad?
477      // Answer: We assume that the child of ID is something we can call getVector on          // Answer: We assume that the child of ID is something we can call getVector on
478      throw DataException("Programmer error - attempt to create identity from a DataLazy.");          throw DataException("Programmer error - attempt to create identity from a DataLazy.");
479     }     }
480     else     else
481     {     {
482      p->makeLazyShared();          p->makeLazyShared();
483      DataReady_ptr dr=dynamic_pointer_cast<DataReady>(p);          DataReady_ptr dr=dynamic_pointer_cast<DataReady>(p);
484      makeIdentity(dr);          makeIdentity(dr);
485  LAZYDEBUG(cout << "Wrapping " << dr.get() << " id=" << m_id.get() << endl;)  LAZYDEBUG(cout << "Wrapping " << dr.get() << " id=" << m_id.get() << endl;)
486     }     }
487  LAZYDEBUG(cout << "(1)Lazy created with " << m_samplesize << endl;)  LAZYDEBUG(cout << "(1)Lazy created with " << m_samplesize << endl;)
488  }  }
489    
490  DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op)  DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op)
491      : parent(left->getFunctionSpace(),(getOpgroup(op)!=G_REDUCTION)?left->getShape():DataTypes::scalarShape),          : parent(left->getFunctionSpace(),(getOpgroup(op)!=G_REDUCTION)?left->getShape():DataTypes::scalarShape),
492      m_op(op),          m_op(op),
493      m_axis_offset(0),          m_axis_offset(0),
494      m_transpose(0),          m_transpose(0),
495      m_SL(0), m_SM(0), m_SR(0)          m_SL(0), m_SM(0), m_SR(0)
496  {  {
497     if ((getOpgroup(op)!=G_UNARY) && (getOpgroup(op)!=G_NP1OUT) && (getOpgroup(op)!=G_REDUCTION))     if ((getOpgroup(op)!=G_UNARY) && (getOpgroup(op)!=G_NP1OUT) && (getOpgroup(op)!=G_REDUCTION))
498     {     {
499      throw DataException("Programmer error - constructor DataLazy(left, op) will only process UNARY operations.");          throw DataException("Programmer error - constructor DataLazy(left, op) will only process UNARY operations.");
500     }     }
501    
502     DataLazy_ptr lleft;     DataLazy_ptr lleft;
503     if (!left->isLazy())     if (!left->isLazy())
504     {     {
505      lleft=DataLazy_ptr(new DataLazy(left));          lleft=DataLazy_ptr(new DataLazy(left));
506     }     }
507     else     else
508     {     {
509      lleft=dynamic_pointer_cast<DataLazy>(left);          lleft=dynamic_pointer_cast<DataLazy>(left);
510     }     }
511     m_readytype=lleft->m_readytype;     m_readytype=lleft->m_readytype;
512     m_left=lleft;     m_left=lleft;
# Line 520  DataLazy::DataLazy(DataAbstract_ptr left Line 520  DataLazy::DataLazy(DataAbstract_ptr left
520    
521  // In this constructor we need to consider interpolation  // In this constructor we need to consider interpolation
522  DataLazy::DataLazy(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op)  DataLazy::DataLazy(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op)
523      : parent(resultFS(left,right,op), resultShape(left,right,op)),          : parent(resultFS(left,right,op), resultShape(left,right,op)),
524      m_op(op),          m_op(op),
525      m_SL(0), m_SM(0), m_SR(0)          m_SL(0), m_SM(0), m_SR(0)
526  {  {
527  LAZYDEBUG(cout << "Forming operator with " << left.get() << " " << right.get() << endl;)  LAZYDEBUG(cout << "Forming operator with " << left.get() << " " << right.get() << endl;)
528     if ((getOpgroup(op)!=G_BINARY))     if ((getOpgroup(op)!=G_BINARY))
529     {     {
530      throw DataException("Programmer error - constructor DataLazy(left, right, op) will only process BINARY operations.");          throw DataException("Programmer error - constructor DataLazy(left, right, op) will only process BINARY operations.");
531     }     }
532    
533     if (getFunctionSpace()!=left->getFunctionSpace())    // left needs to be interpolated     if (getFunctionSpace()!=left->getFunctionSpace())    // left needs to be interpolated
534     {     {
535      FunctionSpace fs=getFunctionSpace();          FunctionSpace fs=getFunctionSpace();
536      Data ltemp(left);          Data ltemp(left);
537      Data tmp(ltemp,fs);          Data tmp(ltemp,fs);
538      left=tmp.borrowDataPtr();          left=tmp.borrowDataPtr();
539     }     }
540     if (getFunctionSpace()!=right->getFunctionSpace())   // right needs to be interpolated     if (getFunctionSpace()!=right->getFunctionSpace())   // right needs to be interpolated
541     {     {
542      Data tmp(Data(right),getFunctionSpace());          Data tmp(Data(right),getFunctionSpace());
543      right=tmp.borrowDataPtr();          right=tmp.borrowDataPtr();
544  LAZYDEBUG(cout << "Right interpolation required " << right.get() << endl;)  LAZYDEBUG(cout << "Right interpolation required " << right.get() << endl;)
545     }     }
546     left->operandCheck(*right);     left->operandCheck(*right);
547    
548     if (left->isLazy())          // the children need to be DataLazy. Wrap them in IDENTITY if required     if (left->isLazy())                  // the children need to be DataLazy. Wrap them in IDENTITY if required
549     {     {
550      m_left=dynamic_pointer_cast<DataLazy>(left);          m_left=dynamic_pointer_cast<DataLazy>(left);
551  LAZYDEBUG(cout << "Left is " << m_left->toString() << endl;)  LAZYDEBUG(cout << "Left is " << m_left->toString() << endl;)
552     }     }
553     else     else
554     {     {
555      m_left=DataLazy_ptr(new DataLazy(left));          m_left=DataLazy_ptr(new DataLazy(left));
556  LAZYDEBUG(cout << "Left " << left.get() << " wrapped " << m_left->m_id.get() << endl;)  LAZYDEBUG(cout << "Left " << left.get() << " wrapped " << m_left->m_id.get() << endl;)
557     }     }
558     if (right->isLazy())     if (right->isLazy())
559     {     {
560      m_right=dynamic_pointer_cast<DataLazy>(right);          m_right=dynamic_pointer_cast<DataLazy>(right);
561  LAZYDEBUG(cout << "Right is " << m_right->toString() << endl;)  LAZYDEBUG(cout << "Right is " << m_right->toString() << endl;)
562     }     }
563     else     else
564     {     {
565      m_right=DataLazy_ptr(new DataLazy(right));          m_right=DataLazy_ptr(new DataLazy(right));
566  LAZYDEBUG(cout << "Right " << right.get() << " wrapped " << m_right->m_id.get() << endl;)  LAZYDEBUG(cout << "Right " << right.get() << " wrapped " << m_right->m_id.get() << endl;)
567     }     }
568     char lt=m_left->m_readytype;     char lt=m_left->m_readytype;
569     char rt=m_right->m_readytype;     char rt=m_right->m_readytype;
570     if (lt=='E' || rt=='E')     if (lt=='E' || rt=='E')
571     {     {
572      m_readytype='E';          m_readytype='E';
573     }     }
574     else if (lt=='T' || rt=='T')     else if (lt=='T' || rt=='T')
575     {     {
576      m_readytype='T';          m_readytype='T';
577     }     }
578     else     else
579     {     {
580      m_readytype='C';          m_readytype='C';
581     }     }
582     m_samplesize=getNumDPPSample()*getNoValues();     m_samplesize=getNumDPPSample()*getNoValues();
583     m_children=m_left->m_children+m_right->m_children+2;     m_children=m_left->m_children+m_right->m_children+2;
# Line 588  LAZYDEBUG(cout << "(3)Lazy created with Line 588  LAZYDEBUG(cout << "(3)Lazy created with
588  }  }
589    
590  DataLazy::DataLazy(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op, int axis_offset, int transpose)  DataLazy::DataLazy(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op, int axis_offset, int transpose)
591      : parent(resultFS(left,right,op), GTPShape(left,right, axis_offset, transpose, m_SL,m_SM, m_SR)),          : parent(resultFS(left,right,op), GTPShape(left,right, axis_offset, transpose, m_SL,m_SM, m_SR)),
592      m_op(op),          m_op(op),
593      m_axis_offset(axis_offset),          m_axis_offset(axis_offset),
594      m_transpose(transpose)          m_transpose(transpose)
595  {  {
596     if ((getOpgroup(op)!=G_TENSORPROD))     if ((getOpgroup(op)!=G_TENSORPROD))
597     {     {
598      throw DataException("Programmer error - constructor DataLazy(left, right, op, ax, tr) will only process BINARY operations which require parameters.");          throw DataException("Programmer error - constructor DataLazy(left, right, op, ax, tr) will only process BINARY operations which require parameters.");
599     }     }
600     if ((transpose>2) || (transpose<0))     if ((transpose>2) || (transpose<0))
601     {     {
602      throw DataException("DataLazy GeneralTensorProduct constructor: Error - transpose should be 0, 1 or 2");          throw DataException("DataLazy GeneralTensorProduct constructor: Error - transpose should be 0, 1 or 2");
603     }     }
604     if (getFunctionSpace()!=left->getFunctionSpace())    // left needs to be interpolated     if (getFunctionSpace()!=left->getFunctionSpace())    // left needs to be interpolated
605     {     {
606      FunctionSpace fs=getFunctionSpace();          FunctionSpace fs=getFunctionSpace();
607      Data ltemp(left);          Data ltemp(left);
608      Data tmp(ltemp,fs);          Data tmp(ltemp,fs);
609      left=tmp.borrowDataPtr();          left=tmp.borrowDataPtr();
610     }     }
611     if (getFunctionSpace()!=right->getFunctionSpace())   // right needs to be interpolated     if (getFunctionSpace()!=right->getFunctionSpace())   // right needs to be interpolated
612     {     {
613      Data tmp(Data(right),getFunctionSpace());          Data tmp(Data(right),getFunctionSpace());
614      right=tmp.borrowDataPtr();          right=tmp.borrowDataPtr();
615     }     }
616  //    left->operandCheck(*right);  //    left->operandCheck(*right);
617    
618     if (left->isLazy())          // the children need to be DataLazy. Wrap them in IDENTITY if required     if (left->isLazy())                  // the children need to be DataLazy. Wrap them in IDENTITY if required
619     {     {
620      m_left=dynamic_pointer_cast<DataLazy>(left);          m_left=dynamic_pointer_cast<DataLazy>(left);
621     }     }
622     else     else
623     {     {
624      m_left=DataLazy_ptr(new DataLazy(left));          m_left=DataLazy_ptr(new DataLazy(left));
625     }     }
626     if (right->isLazy())     if (right->isLazy())
627     {     {
628      m_right=dynamic_pointer_cast<DataLazy>(right);          m_right=dynamic_pointer_cast<DataLazy>(right);
629     }     }
630     else     else
631     {     {
632      m_right=DataLazy_ptr(new DataLazy(right));          m_right=DataLazy_ptr(new DataLazy(right));
633     }     }
634     char lt=m_left->m_readytype;     char lt=m_left->m_readytype;
635     char rt=m_right->m_readytype;     char rt=m_right->m_readytype;
636     if (lt=='E' || rt=='E')     if (lt=='E' || rt=='E')
637     {     {
638      m_readytype='E';          m_readytype='E';
639     }     }
640     else if (lt=='T' || rt=='T')     else if (lt=='T' || rt=='T')
641     {     {
642      m_readytype='T';          m_readytype='T';
643     }     }
644     else     else
645     {     {
646      m_readytype='C';          m_readytype='C';
647     }     }
648     m_samplesize=getNumDPPSample()*getNoValues();     m_samplesize=getNumDPPSample()*getNoValues();
649     m_children=m_left->m_children+m_right->m_children+2;     m_children=m_left->m_children+m_right->m_children+2;
# Line 655  LAZYDEBUG(cout << "(4)Lazy created with Line 655  LAZYDEBUG(cout << "(4)Lazy created with
655    
656    
657  DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op, int axis_offset)  DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op, int axis_offset)
658      : parent(left->getFunctionSpace(), resultShape(left,op, axis_offset)),          : parent(left->getFunctionSpace(), resultShape(left,op, axis_offset)),
659      m_op(op),          m_op(op),
660      m_axis_offset(axis_offset),          m_axis_offset(axis_offset),
661      m_transpose(0),          m_transpose(0),
662      m_tol(0)          m_tol(0)
663  {  {
664     if ((getOpgroup(op)!=G_NP1OUT_P))     if ((getOpgroup(op)!=G_NP1OUT_P))
665     {     {
666      throw DataException("Programmer error - constructor DataLazy(left, op, ax) will only process UNARY operations which require parameters.");          throw DataException("Programmer error - constructor DataLazy(left, op, ax) will only process UNARY operations which require parameters.");
667     }     }
668     DataLazy_ptr lleft;     DataLazy_ptr lleft;
669     if (!left->isLazy())     if (!left->isLazy())
670     {     {
671      lleft=DataLazy_ptr(new DataLazy(left));          lleft=DataLazy_ptr(new DataLazy(left));
672     }     }
673     else     else
674     {     {
675      lleft=dynamic_pointer_cast<DataLazy>(left);          lleft=dynamic_pointer_cast<DataLazy>(left);
676     }     }
677     m_readytype=lleft->m_readytype;     m_readytype=lleft->m_readytype;
678     m_left=lleft;     m_left=lleft;
# Line 685  LAZYDEBUG(cout << "(5)Lazy created with Line 685  LAZYDEBUG(cout << "(5)Lazy created with
685  }  }
686    
687  DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op, double tol)  DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op, double tol)
688      : parent(left->getFunctionSpace(), left->getShape()),          : parent(left->getFunctionSpace(), left->getShape()),
689      m_op(op),          m_op(op),
690      m_axis_offset(0),          m_axis_offset(0),
691      m_transpose(0),          m_transpose(0),
692      m_tol(tol)          m_tol(tol)
693  {  {
694     if ((getOpgroup(op)!=G_UNARY_P))     if ((getOpgroup(op)!=G_UNARY_P))
695     {     {
696      throw DataException("Programmer error - constructor DataLazy(left, op, tol) will only process UNARY operations which require parameters.");          throw DataException("Programmer error - constructor DataLazy(left, op, tol) will only process UNARY operations which require parameters.");
697     }     }
698     DataLazy_ptr lleft;     DataLazy_ptr lleft;
699     if (!left->isLazy())     if (!left->isLazy())
700     {     {
701      lleft=DataLazy_ptr(new DataLazy(left));          lleft=DataLazy_ptr(new DataLazy(left));
702     }     }
703     else     else
704     {     {
705      lleft=dynamic_pointer_cast<DataLazy>(left);          lleft=dynamic_pointer_cast<DataLazy>(left);
706     }     }
707     m_readytype=lleft->m_readytype;     m_readytype=lleft->m_readytype;
708     m_left=lleft;     m_left=lleft;
# Line 716  LAZYDEBUG(cout << "(6)Lazy created with Line 716  LAZYDEBUG(cout << "(6)Lazy created with
716    
717    
718  DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op, const int axis0, const int axis1)  DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op, const int axis0, const int axis1)
719      : parent(left->getFunctionSpace(), SwapShape(left,axis0,axis1)),          : parent(left->getFunctionSpace(), SwapShape(left,axis0,axis1)),
720      m_op(op),          m_op(op),
721      m_axis_offset(axis0),          m_axis_offset(axis0),
722      m_transpose(axis1),          m_transpose(axis1),
723      m_tol(0)          m_tol(0)
724  {  {
725     if ((getOpgroup(op)!=G_NP1OUT_2P))     if ((getOpgroup(op)!=G_NP1OUT_2P))
726     {     {
727      throw DataException("Programmer error - constructor DataLazy(left, op, tol) will only process UNARY operations which require two integer parameters.");          throw DataException("Programmer error - constructor DataLazy(left, op, tol) will only process UNARY operations which require two integer parameters.");
728     }     }
729     DataLazy_ptr lleft;     DataLazy_ptr lleft;
730     if (!left->isLazy())     if (!left->isLazy())
731     {     {
732      lleft=DataLazy_ptr(new DataLazy(left));          lleft=DataLazy_ptr(new DataLazy(left));
733     }     }
734     else     else
735     {     {
736      lleft=dynamic_pointer_cast<DataLazy>(left);          lleft=dynamic_pointer_cast<DataLazy>(left);
737     }     }
738     m_readytype=lleft->m_readytype;     m_readytype=lleft->m_readytype;
739     m_left=lleft;     m_left=lleft;
# Line 751  namespace Line 751  namespace
751    
752      inline int max3(int a, int b, int c)      inline int max3(int a, int b, int c)
753      {      {
754      int t=(a>b?a:b);          int t=(a>b?a:b);
755      return (t>c?t:c);          return (t>c?t:c);
756    
757      }      }
758  }  }
759    
760  DataLazy::DataLazy(DataAbstract_ptr mask, DataAbstract_ptr left, DataAbstract_ptr right/*, double tol*/)  DataLazy::DataLazy(DataAbstract_ptr mask, DataAbstract_ptr left, DataAbstract_ptr right/*, double tol*/)
761      : parent(left->getFunctionSpace(), left->getShape()),          : parent(left->getFunctionSpace(), left->getShape()),
762      m_op(CONDEVAL),          m_op(CONDEVAL),
763      m_axis_offset(0),          m_axis_offset(0),
764      m_transpose(0),          m_transpose(0),
765      m_tol(0)          m_tol(0)
766  {  {
767    
768     DataLazy_ptr lmask;     DataLazy_ptr lmask;
# Line 770  DataLazy::DataLazy(DataAbstract_ptr mask Line 770  DataLazy::DataLazy(DataAbstract_ptr mask
770     DataLazy_ptr lright;     DataLazy_ptr lright;
771     if (!mask->isLazy())     if (!mask->isLazy())
772     {     {
773      lmask=DataLazy_ptr(new DataLazy(mask));          lmask=DataLazy_ptr(new DataLazy(mask));
774     }     }
775     else     else
776     {     {
777      lmask=dynamic_pointer_cast<DataLazy>(mask);          lmask=dynamic_pointer_cast<DataLazy>(mask);
778     }     }
779     if (!left->isLazy())     if (!left->isLazy())
780     {     {
781      lleft=DataLazy_ptr(new DataLazy(left));          lleft=DataLazy_ptr(new DataLazy(left));
782     }     }
783     else     else
784     {     {
785      lleft=dynamic_pointer_cast<DataLazy>(left);          lleft=dynamic_pointer_cast<DataLazy>(left);
786     }     }
787     if (!right->isLazy())     if (!right->isLazy())
788     {     {
789      lright=DataLazy_ptr(new DataLazy(right));          lright=DataLazy_ptr(new DataLazy(right));
790     }     }
791     else     else
792     {     {
793      lright=dynamic_pointer_cast<DataLazy>(right);          lright=dynamic_pointer_cast<DataLazy>(right);
794     }     }
795     m_readytype=lmask->m_readytype;     m_readytype=lmask->m_readytype;
796     if ((lleft->m_readytype!=lright->m_readytype) || (lmask->m_readytype!=lleft->m_readytype))     if ((lleft->m_readytype!=lright->m_readytype) || (lmask->m_readytype!=lleft->m_readytype))
797     {     {
798      throw DataException("Programmer Error - condEval arguments must have the same readytype");          throw DataException("Programmer Error - condEval arguments must have the same readytype");
799     }     }
800     m_left=lleft;     m_left=lleft;
801     m_right=lright;     m_right=lright;
# Line 822  DataLazy::~DataLazy() Line 822  DataLazy::~DataLazy()
822    For reasons of efficiency do not call this method on DataExpanded nodes.    For reasons of efficiency do not call this method on DataExpanded nodes.
823  */  */
824  DataReady_ptr  DataReady_ptr
825  DataLazy::collapseToReady()  DataLazy::collapseToReady() const
826  {  {
827    if (m_readytype=='E')    if (m_readytype=='E')
828    { // this is more an efficiency concern than anything else    {     // this is more an efficiency concern than anything else
829      throw DataException("Programmer Error - do not use collapse on Expanded data.");      throw DataException("Programmer Error - do not use collapse on Expanded data.");
830    }    }
831    if (m_op==IDENTITY)    if (m_op==IDENTITY)
# Line 843  DataLazy::collapseToReady() Line 843  DataLazy::collapseToReady()
843    switch(m_op)    switch(m_op)
844    {    {
845      case ADD:      case ADD:
846      result=left+right;          result=left+right;
847      break;          break;
848      case SUB:            case SUB:          
849      result=left-right;          result=left-right;
850      break;          break;
851      case MUL:            case MUL:          
852      result=left*right;          result=left*right;
853      break;          break;
854      case DIV:            case DIV:          
855      result=left/right;          result=left/right;
856      break;          break;
857      case SIN:      case SIN:
858      result=left.sin();            result=left.sin();      
859      break;          break;
860      case COS:      case COS:
861      result=left.cos();          result=left.cos();
862      break;          break;
863      case TAN:      case TAN:
864      result=left.tan();          result=left.tan();
865      break;          break;
866      case ASIN:      case ASIN:
867      result=left.asin();          result=left.asin();
868      break;          break;
869      case ACOS:      case ACOS:
870      result=left.acos();          result=left.acos();
871      break;          break;
872      case ATAN:      case ATAN:
873      result=left.atan();          result=left.atan();
874      break;          break;
875      case SINH:      case SINH:
876      result=left.sinh();          result=left.sinh();
877      break;          break;
878      case COSH:      case COSH:
879      result=left.cosh();          result=left.cosh();
880      break;          break;
881      case TANH:      case TANH:
882      result=left.tanh();          result=left.tanh();
883      break;          break;
884      case ERF:      case ERF:
885      result=left.erf();          result=left.erf();
886      break;          break;
887     case ASINH:     case ASINH:
888      result=left.asinh();          result=left.asinh();
889      break;          break;
890     case ACOSH:     case ACOSH:
891      result=left.acosh();          result=left.acosh();
892      break;          break;
893     case ATANH:     case ATANH:
894      result=left.atanh();          result=left.atanh();
895      break;          break;
896      case LOG10:      case LOG10:
897      result=left.log10();          result=left.log10();
898      break;          break;
899      case LOG:      case LOG:
900      result=left.log();          result=left.log();
901      break;          break;
902      case SIGN:      case SIGN:
903      result=left.sign();          result=left.sign();
904      break;          break;
905      case ABS:      case ABS:
906      result=left.abs();          result=left.abs();
907      break;          break;
908      case NEG:      case NEG:
909      result=left.neg();          result=left.neg();
910      break;          break;
911      case POS:      case POS:
912      // it doesn't mean anything for delayed.          // it doesn't mean anything for delayed.
913      // it will just trigger a deep copy of the lazy object          // it will just trigger a deep copy of the lazy object
914      throw DataException("Programmer error - POS not supported for lazy data.");          throw DataException("Programmer error - POS not supported for lazy data.");
915      break;          break;
916      case EXP:      case EXP:
917      result=left.exp();          result=left.exp();
918      break;          break;
919      case SQRT:      case SQRT:
920      result=left.sqrt();          result=left.sqrt();
921      break;          break;
922      case RECIP:      case RECIP:
923      result=left.oneOver();          result=left.oneOver();
924      break;          break;
925      case GZ:      case GZ:
926      result=left.wherePositive();          result=left.wherePositive();
927      break;          break;
928      case LZ:      case LZ:
929      result=left.whereNegative();          result=left.whereNegative();
930      break;          break;
931      case GEZ:      case GEZ:
932      result=left.whereNonNegative();          result=left.whereNonNegative();
933      break;          break;
934      case LEZ:      case LEZ:
935      result=left.whereNonPositive();          result=left.whereNonPositive();
936      break;          break;
937      case NEZ:      case NEZ:
938      result=left.whereNonZero(m_tol);          result=left.whereNonZero(m_tol);
939      break;          break;
940      case EZ:      case EZ:
941      result=left.whereZero(m_tol);          result=left.whereZero(m_tol);
942      break;          break;
943      case SYM:      case SYM:
944      result=left.symmetric();          result=left.symmetric();
945      break;          break;
946      case NSYM:      case NSYM:
947      result=left.nonsymmetric();          result=left.nonsymmetric();
948      break;          break;
949      case PROD:      case PROD:
950      result=C_GeneralTensorProduct(left,right,m_axis_offset, m_transpose);          result=C_GeneralTensorProduct(left,right,m_axis_offset, m_transpose);
951      break;          break;
952      case TRANS:      case TRANS:
953      result=left.transpose(m_axis_offset);          result=left.transpose(m_axis_offset);
954      break;          break;
955      case TRACE:      case TRACE:
956      result=left.trace(m_axis_offset);          result=left.trace(m_axis_offset);
957      break;          break;
958      case SWAP:      case SWAP:
959      result=left.swapaxes(m_axis_offset, m_transpose);          result=left.swapaxes(m_axis_offset, m_transpose);
960      break;          break;
961      case MINVAL:      case MINVAL:
962      result=left.minval();          result=left.minval();
963      break;          break;
964      case MAXVAL:      case MAXVAL:
965      result=left.minval();          result=left.minval();
966      break;          break;
967      default:      default:
968      throw DataException("Programmer error - collapseToReady does not know how to resolve operator "+opToString(m_op)+".");          throw DataException("Programmer error - collapseToReady does not know how to resolve operator "+opToString(m_op)+".");
969    }    }
970    return result.borrowReadyPtr();    return result.borrowReadyPtr();
971  }  }
# Line 977  DataLazy::collapseToReady() Line 977  DataLazy::collapseToReady()
977     the purpose of using DataLazy in the first place).     the purpose of using DataLazy in the first place).
978  */  */
979  void  void
980  DataLazy::collapse()  DataLazy::collapse() const
981  {  {
982    if (m_op==IDENTITY)    if (m_op==IDENTITY)
983    {    {
984      return;          return;
985    }    }
986    if (m_readytype=='E')    if (m_readytype=='E')
987    { // this is more an efficiency concern than anything else    {     // this is more an efficiency concern than anything else
988      throw DataException("Programmer Error - do not use collapse on Expanded data.");      throw DataException("Programmer Error - do not use collapse on Expanded data.");
989    }    }
990    m_id=collapseToReady();    m_id=collapseToReady();
# Line 997  DataLazy::collapse() Line 997  DataLazy::collapse()
997    
998    
999  #define PROC_OP(TYPE,X)                               \  #define PROC_OP(TYPE,X)                               \
1000      for (int j=0;j<onumsteps;++j)\          for (int j=0;j<onumsteps;++j)\
1001      {\          {\
1002        for (int i=0;i<numsteps;++i,resultp+=resultStep) \            for (int i=0;i<numsteps;++i,resultp+=resultStep) \
1003        { \            { \
1004  LAZYDEBUG(cout << "[left,right]=[" << lroffset << "," << rroffset << "]" << endl;)\  LAZYDEBUG(cout << "[left,right]=[" << lroffset << "," << rroffset << "]" << endl;)\
1005  LAZYDEBUG(cout << "{left,right}={" << (*left)[lroffset] << "," << (*right)[rroffset] << "}\n";)\  LAZYDEBUG(cout << "{left,right}={" << (*left)[lroffset] << "," << (*right)[rroffset] << "}\n";)\
1006           tensor_binary_operation< TYPE >(chunksize, &((*left)[lroffset]), &((*right)[rroffset]), resultp, X); \               tensor_binary_operation< TYPE >(chunksize, &((*left)[lroffset]), &((*right)[rroffset]), resultp, X); \
1007  LAZYDEBUG(cout << " result=      " << resultp[0] << endl;) \  LAZYDEBUG(cout << " result=      " << resultp[0] << endl;) \
1008           lroffset+=leftstep; \               lroffset+=leftstep; \
1009           rroffset+=rightstep; \               rroffset+=rightstep; \
1010        }\            }\
1011        lroffset+=oleftstep;\            lroffset+=oleftstep;\
1012        rroffset+=orightstep;\            rroffset+=orightstep;\
1013      }          }
1014    
1015    
1016  // The result will be stored in m_samples  // The result will be stored in m_samples
1017  // The return value is a pointer to the DataVector, offset is the offset within the return value  // The return value is a pointer to the DataVector, offset is the offset within the return value
1018  const DataTypes::ValueType*  const DataTypes::RealVectorType*
1019  DataLazy::resolveNodeSample(int tid, int sampleNo, size_t& roffset)  DataLazy::resolveNodeSample(int tid, int sampleNo, size_t& roffset) const
1020  {  {
1021  LAZYDEBUG(cout << "Resolve sample " << toString() << endl;)  LAZYDEBUG(cout << "Resolve sample " << toString() << endl;)
1022      // collapse so we have a 'E' node or an IDENTITY for some other type          // collapse so we have a 'E' node or an IDENTITY for some other type
1023    if (m_readytype!='E' && m_op!=IDENTITY)    if (m_readytype!='E' && m_op!=IDENTITY)
1024    {    {
1025      collapse();          collapse();
1026    }    }
1027    if (m_op==IDENTITY)      if (m_op==IDENTITY)  
1028    {    {
1029      const ValueType& vec=m_id->getVectorRO();      const RealVectorType& vec=m_id->getVectorRO();
1030      roffset=m_id->getPointOffset(sampleNo, 0);      roffset=m_id->getPointOffset(sampleNo, 0);
1031  #ifdef LAZY_STACK_PROF  #ifdef LAZY_STACK_PROF
1032  int x;  int x;
# Line 1043  if (&x<stackend[omp_get_thread_num()]) Line 1043  if (&x<stackend[omp_get_thread_num()])
1043    }    }
1044    if (m_sampleids[tid]==sampleNo)    if (m_sampleids[tid]==sampleNo)
1045    {    {
1046      roffset=tid*m_samplesize;          roffset=tid*m_samplesize;
1047      return &(m_samples);        // sample is already resolved          return &(m_samples);            // sample is already resolved
1048    }    }
1049    m_sampleids[tid]=sampleNo;    m_sampleids[tid]=sampleNo;
1050    
# Line 1064  if (&x<stackend[omp_get_thread_num()]) Line 1064  if (&x<stackend[omp_get_thread_num()])
1064    }    }
1065  }  }
1066    
1067  const DataTypes::ValueType*  const DataTypes::RealVectorType*
1068  DataLazy::resolveNodeUnary(int tid, int sampleNo, size_t& roffset)  DataLazy::resolveNodeUnary(int tid, int sampleNo, size_t& roffset) const
1069  {  {
1070      // we assume that any collapsing has been done before we get here          // we assume that any collapsing has been done before we get here
1071      // since we only have one argument we don't need to think about only          // since we only have one argument we don't need to think about only
1072      // processing single points.          // processing single points.
1073      // we will also know we won't get identity nodes          // we will also know we won't get identity nodes
1074    if (m_readytype!='E')    if (m_readytype!='E')
1075    {    {
1076      throw DataException("Programmer error - resolveUnary should only be called on expanded Data.");      throw DataException("Programmer error - resolveUnary should only be called on expanded Data.");
# Line 1079  DataLazy::resolveNodeUnary(int tid, int Line 1079  DataLazy::resolveNodeUnary(int tid, int
1079    {    {
1080      throw DataException("Programmer error - resolveNodeUnary should not be called on identity nodes.");      throw DataException("Programmer error - resolveNodeUnary should not be called on identity nodes.");
1081    }    }
1082    const DataTypes::ValueType* leftres=m_left->resolveNodeSample(tid, sampleNo, roffset);    const DataTypes::RealVectorType* leftres=m_left->resolveNodeSample(tid, sampleNo, roffset);
1083    const double* left=&((*leftres)[roffset]);    const double* left=&((*leftres)[roffset]);
1084    roffset=m_samplesize*tid;    roffset=m_samplesize*tid;
1085    double* result=&(m_samples[roffset]);    double* result=&(m_samples[roffset]);
1086    switch (m_op)    switch (m_op)
1087    {    {
1088      case SIN:        case SIN:  
1089      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::sin);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::sin);
1090      break;          break;
1091      case COS:      case COS:
1092      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::cos);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::cos);
1093      break;          break;
1094      case TAN:      case TAN:
1095      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::tan);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::tan);
1096      break;          break;
1097      case ASIN:      case ASIN:
1098      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::asin);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::asin);
1099      break;          break;
1100      case ACOS:      case ACOS:
1101      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::acos);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::acos);
1102      break;          break;
1103      case ATAN:      case ATAN:
1104      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::atan);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::atan);
1105      break;          break;
1106      case SINH:      case SINH:
1107      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::sinh);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::sinh);
1108      break;          break;
1109      case COSH:      case COSH:
1110      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::cosh);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::cosh);
1111      break;          break;
1112      case TANH:      case TANH:
1113      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::tanh);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::tanh);
1114      break;          break;
1115      case ERF:      case ERF:
1116  #if defined (_WIN32) && !defined(__INTEL_COMPILER)  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1117      throw DataException("Error - Data:: erf function is not supported on _WIN32 platforms.");          throw DataException("Error - Data:: erf function is not supported on _WIN32 platforms.");
1118  #else  #else
1119      tensor_unary_operation(m_samplesize, left, result, ::erf);          tensor_unary_operation(m_samplesize, left, result, ::erf);
1120      break;          break;
1121  #endif  #endif
1122     case ASINH:     case ASINH:
1123  #if defined (_WIN32) && !defined(__INTEL_COMPILER)  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1124      tensor_unary_operation(m_samplesize, left, result, escript::asinh_substitute);          tensor_unary_operation(m_samplesize, left, result, escript::asinh_substitute);
1125  #else  #else
1126      tensor_unary_operation(m_samplesize, left, result, ::asinh);          tensor_unary_operation(m_samplesize, left, result, ::asinh);
1127  #endif    #endif  
1128      break;          break;
1129     case ACOSH:     case ACOSH:
1130  #if defined (_WIN32) && !defined(__INTEL_COMPILER)  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1131      tensor_unary_operation(m_samplesize, left, result, escript::acosh_substitute);          tensor_unary_operation(m_samplesize, left, result, escript::acosh_substitute);
1132  #else  #else
1133      tensor_unary_operation(m_samplesize, left, result, ::acosh);          tensor_unary_operation(m_samplesize, left, result, ::acosh);
1134  #endif    #endif  
1135      break;          break;
1136     case ATANH:     case ATANH:
1137  #if defined (_WIN32) && !defined(__INTEL_COMPILER)  #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1138      tensor_unary_operation(m_samplesize, left, result, escript::atanh_substitute);          tensor_unary_operation(m_samplesize, left, result, escript::atanh_substitute);
1139  #else  #else
1140      tensor_unary_operation(m_samplesize, left, result, ::atanh);          tensor_unary_operation(m_samplesize, left, result, ::atanh);
1141  #endif    #endif  
1142      break;          break;
1143      case LOG10:      case LOG10:
1144      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::log10);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::log10);
1145      break;          break;
1146      case LOG:      case LOG:
1147      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::log);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::log);
1148      break;          break;
1149      case SIGN:      case SIGN:
1150      tensor_unary_operation(m_samplesize, left, result, escript::fsign);          tensor_unary_operation(m_samplesize, left, result, escript::fsign);
1151      break;          break;
1152      case ABS:      case ABS:
1153      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::fabs);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::fabs);
1154      break;          break;
1155      case NEG:      case NEG:
1156      tensor_unary_operation(m_samplesize, left, result, negate<double>());          tensor_unary_operation(m_samplesize, left, result, negate<double>());
1157      break;          break;
1158      case POS:      case POS:
1159      // it doesn't mean anything for delayed.          // it doesn't mean anything for delayed.
1160      // it will just trigger a deep copy of the lazy object          // it will just trigger a deep copy of the lazy object
1161      throw DataException("Programmer error - POS not supported for lazy data.");          throw DataException("Programmer error - POS not supported for lazy data.");
1162      break;          break;
1163      case EXP:      case EXP:
1164      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::exp);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::exp);
1165      break;          break;
1166      case SQRT:      case SQRT:
1167      tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::sqrt);          tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::sqrt);
1168      break;          break;
1169      case RECIP:      case RECIP:
1170      tensor_unary_operation(m_samplesize, left, result, bind1st(divides<double>(),1.));          tensor_unary_operation(m_samplesize, left, result, bind1st(divides<double>(),1.));
1171      break;          break;
1172      case GZ:      case GZ:
1173      tensor_unary_operation(m_samplesize, left, result, bind2nd(greater<double>(),0.0));          tensor_unary_operation(m_samplesize, left, result, bind2nd(greater<double>(),0.0));
1174      break;          break;
1175      case LZ:      case LZ:
1176      tensor_unary_operation(m_samplesize, left, result, bind2nd(less<double>(),0.0));          tensor_unary_operation(m_samplesize, left, result, bind2nd(less<double>(),0.0));
1177      break;          break;
1178      case GEZ:      case GEZ:
1179      tensor_unary_operation(m_samplesize, left, result, bind2nd(greater_equal<double>(),0.0));          tensor_unary_operation(m_samplesize, left, result, bind2nd(greater_equal<double>(),0.0));
1180      break;          break;
1181      case LEZ:      case LEZ:
1182      tensor_unary_operation(m_samplesize, left, result, bind2nd(less_equal<double>(),0.0));          tensor_unary_operation(m_samplesize, left, result, bind2nd(less_equal<double>(),0.0));
1183      break;          break;
1184  // There are actually G_UNARY_P but I don't see a compelling reason to treat them differently  // There are actually G_UNARY_P but I don't see a compelling reason to treat them differently
1185      case NEZ:      case NEZ:
1186      tensor_unary_operation(m_samplesize, left, result, bind2nd(AbsGT(),m_tol));          tensor_unary_operation(m_samplesize, left, result, bind2nd(AbsGT(),m_tol));
1187      break;          break;
1188      case EZ:      case EZ:
1189      tensor_unary_operation(m_samplesize, left, result, bind2nd(AbsLTE(),m_tol));          tensor_unary_operation(m_samplesize, left, result, bind2nd(AbsLTE(),m_tol));
1190      break;          break;
1191    
1192      default:      default:
1193      throw DataException("Programmer error - resolveUnary can not resolve operator "+opToString(m_op)+".");          throw DataException("Programmer error - resolveUnary can not resolve operator "+opToString(m_op)+".");
1194    }    }
1195    return &(m_samples);    return &(m_samples);
1196  }  }
1197    
1198    
1199  const DataTypes::ValueType*  const DataTypes::RealVectorType*
1200  DataLazy::resolveNodeReduction(int tid, int sampleNo, size_t& roffset)  DataLazy::resolveNodeReduction(int tid, int sampleNo, size_t& roffset) const
1201  {  {
1202      // we assume that any collapsing has been done before we get here          // we assume that any collapsing has been done before we get here
1203      // since we only have one argument we don't need to think about only          // since we only have one argument we don't need to think about only
1204      // processing single points.          // processing single points.
1205      // we will also know we won't get identity nodes          // we will also know we won't get identity nodes
1206    if (m_readytype!='E')    if (m_readytype!='E')
1207    {    {
1208      throw DataException("Programmer error - resolveUnary should only be called on expanded Data.");      throw DataException("Programmer error - resolveUnary should only be called on expanded Data.");
# Line 1212  DataLazy::resolveNodeReduction(int tid, Line 1212  DataLazy::resolveNodeReduction(int tid,
1212      throw DataException("Programmer error - resolveNodeUnary should not be called on identity nodes.");      throw DataException("Programmer error - resolveNodeUnary should not be called on identity nodes.");
1213    }    }
1214    size_t loffset=0;    size_t loffset=0;
1215    const DataTypes::ValueType* leftres=m_left->resolveNodeSample(tid, sampleNo, loffset);    const DataTypes::RealVectorType* leftres=m_left->resolveNodeSample(tid, sampleNo, loffset);
1216    
1217    roffset=m_samplesize*tid;    roffset=m_samplesize*tid;
1218    unsigned int ndpps=getNumDPPSample();    unsigned int ndpps=getNumDPPSample();
# Line 1221  DataLazy::resolveNodeReduction(int tid, Line 1221  DataLazy::resolveNodeReduction(int tid,
1221    switch (m_op)    switch (m_op)
1222    {    {
1223      case MINVAL:      case MINVAL:
1224      {          {
1225        for (unsigned int z=0;z<ndpps;++z)            for (unsigned int z=0;z<ndpps;++z)
1226        {            {
1227          FMin op;              FMin op;
1228          *result=DataMaths::reductionOp(*leftres, m_left->getShape(), loffset, op, numeric_limits<double>::max());              *result=DataMaths::reductionOp(*leftres, m_left->getShape(), loffset, op, numeric_limits<double>::max());
1229          loffset+=psize;              loffset+=psize;
1230          result++;              result++;
1231        }            }
1232      }          }
1233      break;          break;
1234      case MAXVAL:      case MAXVAL:
1235      {          {
1236        for (unsigned int z=0;z<ndpps;++z)            for (unsigned int z=0;z<ndpps;++z)
1237        {            {
1238        FMax op;            FMax op;
1239        *result=DataMaths::reductionOp(*leftres, m_left->getShape(), loffset, op, numeric_limits<double>::max()*-1);            *result=DataMaths::reductionOp(*leftres, m_left->getShape(), loffset, op, numeric_limits<double>::max()*-1);
1240        loffset+=psize;            loffset+=psize;
1241        result++;            result++;
1242        }            }
1243      }          }
1244      break;          break;
1245      default:      default:
1246      throw DataException("Programmer error - resolveUnary can not resolve operator "+opToString(m_op)+".");          throw DataException("Programmer error - resolveUnary can not resolve operator "+opToString(m_op)+".");
1247    }    }
1248    return &(m_samples);    return &(m_samples);
1249  }  }
1250    
1251  const DataTypes::ValueType*  const DataTypes::RealVectorType*
1252  DataLazy::resolveNodeNP1OUT(int tid, int sampleNo, size_t& roffset)  DataLazy::resolveNodeNP1OUT(int tid, int sampleNo, size_t& roffset) const
1253  {  {
1254      // we assume that any collapsing has been done before we get here          // we assume that any collapsing has been done before we get here
1255      // since we only have one argument we don't need to think about only          // since we only have one argument we don't need to think about only
1256      // processing single points.          // processing single points.
1257    if (m_readytype!='E')    if (m_readytype!='E')
1258    {    {
1259      throw DataException("Programmer error - resolveNodeNP1OUT should only be called on expanded Data.");      throw DataException("Programmer error - resolveNodeNP1OUT should only be called on expanded Data.");
# Line 1263  DataLazy::resolveNodeNP1OUT(int tid, int Line 1263  DataLazy::resolveNodeNP1OUT(int tid, int
1263      throw DataException("Programmer error - resolveNodeNP1OUT should not be called on identity nodes.");      throw DataException("Programmer error - resolveNodeNP1OUT should not be called on identity nodes.");
1264    }    }
1265    size_t subroffset;    size_t subroffset;
1266    const ValueType* leftres=m_left->resolveNodeSample(tid, sampleNo, subroffset);    const RealVectorType* leftres=m_left->resolveNodeSample(tid, sampleNo, subroffset);
1267    roffset=m_samplesize*tid;    roffset=m_samplesize*tid;
1268    size_t loop=0;    size_t loop=0;
1269    size_t numsteps=(m_readytype=='E')?getNumDPPSample():1;    size_t numsteps=(m_readytype=='E')?getNumDPPSample():1;
# Line 1272  DataLazy::resolveNodeNP1OUT(int tid, int Line 1272  DataLazy::resolveNodeNP1OUT(int tid, int
1272    switch (m_op)    switch (m_op)
1273    {    {
1274      case SYM:      case SYM:
1275      for (loop=0;loop<numsteps;++loop)          for (loop=0;loop<numsteps;++loop)
1276      {          {
1277          DataMaths::symmetric(*leftres,m_left->getShape(),subroffset, m_samples, getShape(), offset);              DataMaths::symmetric(*leftres,m_left->getShape(),subroffset, m_samples, getShape(), offset);
1278          subroffset+=step;              subroffset+=step;
1279          offset+=step;              offset+=step;
1280      }          }
1281      break;          break;
1282      case NSYM:      case NSYM:
1283      for (loop=0;loop<numsteps;++loop)          for (loop=0;loop<numsteps;++loop)
1284      {          {
1285          DataMaths::nonsymmetric(*leftres,m_left->getShape(),subroffset, m_samples, getShape(), offset);              DataMaths::nonsymmetric(*leftres,m_left->getShape(),subroffset, m_samples, getShape(), offset);
1286          subroffset+=step;              subroffset+=step;
1287          offset+=step;              offset+=step;
1288      }          }
1289      break;          break;
1290      default:      default:
1291      throw DataException("Programmer error - resolveNP1OUT can not resolve operator "+opToString(m_op)+".");          throw DataException("Programmer error - resolveNP1OUT can not resolve operator "+opToString(m_op)+".");
1292    }    }
1293    return &m_samples;    return &m_samples;
1294  }  }
1295    
1296  const DataTypes::ValueType*  const DataTypes::RealVectorType*
1297  DataLazy::resolveNodeNP1OUT_P(int tid, int sampleNo, size_t& roffset)  DataLazy::resolveNodeNP1OUT_P(int tid, int sampleNo, size_t& roffset) const
1298  {  {
1299      // we assume that any collapsing has been done before we get here          // we assume that any collapsing has been done before we get here
1300      // since we only have one argument we don't need to think about only          // since we only have one argument we don't need to think about only
1301      // processing single points.          // processing single points.
1302    if (m_readytype!='E')    if (m_readytype!='E')
1303    {    {
1304      throw DataException("Programmer error - resolveNodeNP1OUT_P should only be called on expanded Data.");      throw DataException("Programmer error - resolveNodeNP1OUT_P should only be called on expanded Data.");
# Line 1309  DataLazy::resolveNodeNP1OUT_P(int tid, i Line 1309  DataLazy::resolveNodeNP1OUT_P(int tid, i
1309    }    }
1310    size_t subroffset;    size_t subroffset;
1311    size_t offset;    size_t offset;
1312    const ValueType* leftres=m_left->resolveNodeSample(tid, sampleNo, subroffset);    const RealVectorType* leftres=m_left->resolveNodeSample(tid, sampleNo, subroffset);
1313    roffset=m_samplesize*tid;    roffset=m_samplesize*tid;
1314    offset=roffset;    offset=roffset;
1315    size_t loop=0;    size_t loop=0;
# Line 1319  DataLazy::resolveNodeNP1OUT_P(int tid, i Line 1319  DataLazy::resolveNodeNP1OUT_P(int tid, i
1319    switch (m_op)    switch (m_op)
1320    {    {
1321      case TRACE:      case TRACE:
1322      for (loop=0;loop<numsteps;++loop)          for (loop=0;loop<numsteps;++loop)
1323      {          {
1324              DataMaths::trace(*leftres,m_left->getShape(),subroffset, m_samples ,getShape(),offset,m_axis_offset);              DataMaths::trace(*leftres,m_left->getShape(),subroffset, m_samples ,getShape(),offset,m_axis_offset);
1325          subroffset+=instep;              subroffset+=instep;
1326          offset+=outstep;              offset+=outstep;
1327      }          }
1328      break;          break;
1329      case TRANS:      case TRANS:
1330      for (loop=0;loop<numsteps;++loop)          for (loop=0;loop<numsteps;++loop)
1331      {          {
1332              DataMaths::transpose(*leftres,m_left->getShape(),subroffset, m_samples, getShape(),offset,m_axis_offset);              DataMaths::transpose(*leftres,m_left->getShape(),subroffset, m_samples, getShape(),offset,m_axis_offset);
1333          subroffset+=instep;              subroffset+=instep;
1334          offset+=outstep;              offset+=outstep;
1335      }          }
1336      break;          break;
1337      default:      default:
1338      throw DataException("Programmer error - resolveNP1OUTP can not resolve operator "+opToString(m_op)+".");          throw DataException("Programmer error - resolveNP1OUTP can not resolve operator "+opToString(m_op)+".");
1339    }    }
1340    return &m_samples;    return &m_samples;
1341  }  }
1342    
1343    
1344  const DataTypes::ValueType*  const DataTypes::RealVectorType*
1345  DataLazy::resolveNodeNP1OUT_2P(int tid, int sampleNo, size_t& roffset)  DataLazy::resolveNodeNP1OUT_2P(int tid, int sampleNo, size_t& roffset) const
1346  {  {
1347    if (m_readytype!='E')    if (m_readytype!='E')
1348    {    {
# Line 1354  DataLazy::resolveNodeNP1OUT_2P(int tid, Line 1354  DataLazy::resolveNodeNP1OUT_2P(int tid,
1354    }    }
1355    size_t subroffset;    size_t subroffset;
1356    size_t offset;    size_t offset;
1357    const ValueType* leftres=m_left->resolveNodeSample(tid, sampleNo, subroffset);    const RealVectorType* leftres=m_left->resolveNodeSample(tid, sampleNo, subroffset);
1358    roffset=m_samplesize*tid;    roffset=m_samplesize*tid;
1359    offset=roffset;    offset=roffset;
1360    size_t loop=0;    size_t loop=0;
# Line 1364  DataLazy::resolveNodeNP1OUT_2P(int tid, Line 1364  DataLazy::resolveNodeNP1OUT_2P(int tid,
1364    switch (m_op)    switch (m_op)
1365    {    {
1366      case SWAP:      case SWAP:
1367      for (loop=0;loop<numsteps;++loop)          for (loop=0;loop<numsteps;++loop)
1368      {          {
1369              DataMaths::swapaxes(*leftres,m_left->getShape(),subroffset, m_samples, getShape(),offset, m_axis_offset, m_transpose);              DataMaths::swapaxes(*leftres,m_left->getShape(),subroffset, m_samples, getShape(),offset, m_axis_offset, m_transpose);
1370          subroffset+=instep;              subroffset+=instep;
1371          offset+=outstep;              offset+=outstep;
1372      }          }
1373      break;          break;
1374      default:      default:
1375      throw DataException("Programmer error - resolveNodeNP1OUT2P can not resolve operator "+opToString(m_op)+".");          throw DataException("Programmer error - resolveNodeNP1OUT2P can not resolve operator "+opToString(m_op)+".");
1376    }    }
1377    return &m_samples;    return &m_samples;
1378  }  }
1379    
1380  const DataTypes::ValueType*  const DataTypes::RealVectorType*
1381  DataLazy::resolveNodeCondEval(int tid, int sampleNo, size_t& roffset)  DataLazy::resolveNodeCondEval(int tid, int sampleNo, size_t& roffset) const
1382  {  {
1383    if (m_readytype!='E')    if (m_readytype!='E')
1384    {    {
# Line 1390  DataLazy::resolveNodeCondEval(int tid, i Line 1390  DataLazy::resolveNodeCondEval(int tid, i
1390    }    }
1391    size_t subroffset;    size_t subroffset;
1392    
1393    const ValueType* maskres=m_mask->resolveNodeSample(tid, sampleNo, subroffset);    const RealVectorType* maskres=m_mask->resolveNodeSample(tid, sampleNo, subroffset);
1394    const ValueType* srcres=0;    const RealVectorType* srcres=0;
1395    if ((*maskres)[subroffset]>0)    if ((*maskres)[subroffset]>0)
1396    {    {
1397      srcres=m_left->resolveNodeSample(tid, sampleNo, subroffset);          srcres=m_left->resolveNodeSample(tid, sampleNo, subroffset);
1398    }    }
1399    else    else
1400    {    {
1401      srcres=m_right->resolveNodeSample(tid, sampleNo, subroffset);          srcres=m_right->resolveNodeSample(tid, sampleNo, subroffset);
1402    }    }
1403    
1404    // Now we need to copy the result    // Now we need to copy the result
# Line 1406  DataLazy::resolveNodeCondEval(int tid, i Line 1406  DataLazy::resolveNodeCondEval(int tid, i
1406    roffset=m_samplesize*tid;    roffset=m_samplesize*tid;
1407    for (int i=0;i<m_samplesize;++i)    for (int i=0;i<m_samplesize;++i)
1408    {    {
1409      m_samples[roffset+i]=(*srcres)[subroffset+i];            m_samples[roffset+i]=(*srcres)[subroffset+i];  
1410    }    }
1411    
1412    return &m_samples;    return &m_samples;
# Line 1421  DataLazy::resolveNodeCondEval(int tid, i Line 1421  DataLazy::resolveNodeCondEval(int tid, i
1421  // There is an additional complication when scalar operations are considered.  // There is an additional complication when scalar operations are considered.
1422  // For example, 2+Vector.  // For example, 2+Vector.
1423  // In this case each double within the point is treated individually  // In this case each double within the point is treated individually
1424  const DataTypes::ValueType*  const DataTypes::RealVectorType*
1425  DataLazy::resolveNodeBinary(int tid, int sampleNo, size_t& roffset)  DataLazy::resolveNodeBinary(int tid, int sampleNo, size_t& roffset) const
1426  {  {
1427  LAZYDEBUG(cout << "Resolve binary: " << toString() << endl;)  LAZYDEBUG(cout << "Resolve binary: " << toString() << endl;)
1428    
1429    size_t lroffset=0, rroffset=0;    // offsets in the left and right result vectors    size_t lroffset=0, rroffset=0;        // offsets in the left and right result vectors
1430      // first work out which of the children are expanded          // first work out which of the children are expanded
1431    bool leftExp=(m_left->m_readytype=='E');    bool leftExp=(m_left->m_readytype=='E');
1432    bool rightExp=(m_right->m_readytype=='E');    bool rightExp=(m_right->m_readytype=='E');
1433    if (!leftExp && !rightExp)    if (!leftExp && !rightExp)
1434    {    {
1435      throw DataException("Programmer Error - please use collapse if neither argument has type 'E'.");          throw DataException("Programmer Error - please use collapse if neither argument has type 'E'.");
1436    }    }
1437    bool leftScalar=(m_left->getRank()==0);    bool leftScalar=(m_left->getRank()==0);
1438    bool rightScalar=(m_right->getRank()==0);    bool rightScalar=(m_right->getRank()==0);
1439    if ((m_left->getRank()!=m_right->getRank()) && (!leftScalar && !rightScalar))    if ((m_left->getRank()!=m_right->getRank()) && (!leftScalar && !rightScalar))
1440    {    {
1441      throw DataException("resolveBinary - ranks of arguments must match unless one of them is scalar.");          throw DataException("resolveBinary - ranks of arguments must match unless one of them is scalar.");
1442    }    }
1443    size_t leftsize=m_left->getNoValues();    size_t leftsize=m_left->getNoValues();
1444    size_t rightsize=m_right->getNoValues();    size_t rightsize=m_right->getNoValues();
1445    size_t chunksize=1;           // how many doubles will be processed in one go    size_t chunksize=1;                   // how many doubles will be processed in one go
1446    int leftstep=0;       // how far should the left offset advance after each step    int leftstep=0;               // how far should the left offset advance after each step
1447    int rightstep=0;    int rightstep=0;
1448    int numsteps=0;       // total number of steps for the inner loop    int numsteps=0;               // total number of steps for the inner loop
1449    int oleftstep=0;  // the o variables refer to the outer loop    int oleftstep=0;      // the o variables refer to the outer loop
1450    int orightstep=0; // The outer loop is only required in cases where there is an extended scalar    int orightstep=0;     // The outer loop is only required in cases where there is an extended scalar
1451    int onumsteps=1;    int onumsteps=1;
1452        
1453    bool LES=(leftExp && leftScalar); // Left is an expanded scalar    bool LES=(leftExp && leftScalar);     // Left is an expanded scalar
1454    bool RES=(rightExp && rightScalar);    bool RES=(rightExp && rightScalar);
1455    bool LS=(!leftExp && leftScalar); // left is a single scalar    bool LS=(!leftExp && leftScalar);     // left is a single scalar
1456    bool RS=(!rightExp && rightScalar);    bool RS=(!rightExp && rightScalar);
1457    bool LN=(!leftExp && !leftScalar);    // left is a single non-scalar    bool LN=(!leftExp && !leftScalar);    // left is a single non-scalar
1458    bool RN=(!rightExp && !rightScalar);    bool RN=(!rightExp && !rightScalar);
1459    bool LEN=(leftExp && !leftScalar);    // left is an expanded non-scalar    bool LEN=(leftExp && !leftScalar);    // left is an expanded non-scalar
1460    bool REN=(rightExp && !rightScalar);    bool REN=(rightExp && !rightScalar);
1461    
1462    if ((LES && RES) || (LEN && REN)) // both are Expanded scalars or both are expanded non-scalars    if ((LES && RES) || (LEN && REN))     // both are Expanded scalars or both are expanded non-scalars
1463    {    {
1464      chunksize=m_left->getNumDPPSample()*leftsize;          chunksize=m_left->getNumDPPSample()*leftsize;
1465      leftstep=0;          leftstep=0;
1466      rightstep=0;          rightstep=0;
1467      numsteps=1;          numsteps=1;
1468    }    }
1469    else if (LES || RES)    else if (LES || RES)
1470    {    {
1471      chunksize=1;          chunksize=1;
1472      if (LES)        // left is an expanded scalar          if (LES)                // left is an expanded scalar
1473      {          {
1474          if (RS)                  if (RS)
1475          {                  {
1476             leftstep=1;                     leftstep=1;
1477             rightstep=0;                     rightstep=0;
1478             numsteps=m_left->getNumDPPSample();                     numsteps=m_left->getNumDPPSample();
1479          }                  }
1480          else        // RN or REN                  else            // RN or REN
1481          {                  {
1482             leftstep=0;                     leftstep=0;
1483             oleftstep=1;                     oleftstep=1;
1484             rightstep=1;                     rightstep=1;
1485             orightstep=(RN ? -(int)rightsize : 0);                     orightstep=(RN ? -(int)rightsize : 0);
1486             numsteps=rightsize;                     numsteps=rightsize;
1487             onumsteps=m_left->getNumDPPSample();                     onumsteps=m_left->getNumDPPSample();
1488          }                  }
1489      }          }
1490      else        // right is an expanded scalar          else            // right is an expanded scalar
1491      {          {
1492          if (LS)                  if (LS)
1493          {                  {
1494             rightstep=1;                     rightstep=1;
1495             leftstep=0;                     leftstep=0;
1496             numsteps=m_right->getNumDPPSample();                     numsteps=m_right->getNumDPPSample();
1497          }                  }
1498          else                  else
1499          {                  {
1500             rightstep=0;                     rightstep=0;
1501             orightstep=1;                     orightstep=1;
1502             leftstep=1;                     leftstep=1;
1503             oleftstep=(LN ? -(int)leftsize : 0);                     oleftstep=(LN ? -(int)leftsize : 0);
1504             numsteps=leftsize;                     numsteps=leftsize;
1505             onumsteps=m_right->getNumDPPSample();                     onumsteps=m_right->getNumDPPSample();
1506          }                  }
1507      }          }
1508    }    }
1509    else  // this leaves (LEN, RS), (LEN, RN) and their transposes    else  // this leaves (LEN, RS), (LEN, RN) and their transposes
1510    {    {
1511      if (LEN)    // and Right will be a single value          if (LEN)        // and Right will be a single value
1512      {          {
1513          chunksize=rightsize;                  chunksize=rightsize;
1514          leftstep=rightsize;                  leftstep=rightsize;
1515          rightstep=0;                  rightstep=0;
1516          numsteps=m_left->getNumDPPSample();                  numsteps=m_left->getNumDPPSample();
1517          if (RS)                  if (RS)
1518          {                  {
1519             numsteps*=leftsize;                     numsteps*=leftsize;
1520          }                  }
1521      }          }
1522      else    // REN          else    // REN
1523      {          {
1524          chunksize=leftsize;                  chunksize=leftsize;
1525          rightstep=leftsize;                  rightstep=leftsize;
1526          leftstep=0;                  leftstep=0;
1527          numsteps=m_right->getNumDPPSample();                  numsteps=m_right->getNumDPPSample();
1528          if (LS)                  if (LS)
1529          {                  {
1530             numsteps*=rightsize;                     numsteps*=rightsize;
1531          }                  }
1532      }          }
1533    }    }
1534    
1535    int resultStep=max(leftstep,rightstep);   // only one (at most) should be !=0    int resultStep=max(leftstep,rightstep);       // only one (at most) should be !=0
1536      // Get the values of sub-expressions          // Get the values of sub-expressions
1537    const ValueType* left=m_left->resolveNodeSample(tid,sampleNo,lroffset);      const RealVectorType* left=m_left->resolveNodeSample(tid,sampleNo,lroffset);      
1538    const ValueType* right=m_right->resolveNodeSample(tid,sampleNo,rroffset);    const RealVectorType* right=m_right->resolveNodeSample(tid,sampleNo,rroffset);
1539  LAZYDEBUG(cout << "Post sub calls in " << toString() << endl;)  LAZYDEBUG(cout << "Post sub calls in " << toString() << endl;)
1540  LAZYDEBUG(cout << "shapes=" << DataTypes::shapeToString(m_left->getShape()) << "," << DataTypes::shapeToString(m_right->getShape()) << endl;)  LAZYDEBUG(cout << "shapes=" << DataTypes::shapeToString(m_left->getShape()) << "," << DataTypes::shapeToString(m_right->getShape()) << endl;)
1541  LAZYDEBUG(cout << "chunksize=" << chunksize << endl << "leftstep=" << leftstep << " rightstep=" << rightstep;)  LAZYDEBUG(cout << "chunksize=" << chunksize << endl << "leftstep=" << leftstep << " rightstep=" << rightstep;)
# Line 1549  LAZYDEBUG(cout << "Right res["<< rroffse Line 1549  LAZYDEBUG(cout << "Right res["<< rroffse
1549    
1550    
1551    roffset=m_samplesize*tid;    roffset=m_samplesize*tid;
1552    double* resultp=&(m_samples[roffset]);        // results are stored at the vector offset we recieved    double* resultp=&(m_samples[roffset]);                // results are stored at the vector offset we received
1553    switch(m_op)    switch(m_op)
1554    {    {
1555      case ADD:      case ADD:
1556          PROC_OP(NO_ARG,plus<double>());          //PROC_OP(NO_ARG,plus<double>());
1557      break;        DataMaths::binaryOpVectorLazyHelper<real_t, real_t, real_t>(resultp,
1558                 &(*left)[0],
1559                 &(*right)[0],
1560                 chunksize,
1561                 onumsteps,
1562                 numsteps,
1563                 resultStep,
1564                 leftstep,
1565                 rightstep,
1566                 oleftstep,
1567                 orightstep,
1568                 escript::ESFunction::PLUSF);  
1569            break;
1570      case SUB:      case SUB:
1571      PROC_OP(NO_ARG,minus<double>());          PROC_OP(NO_ARG,minus<double>());
1572      break;          break;
1573      case MUL:      case MUL:
1574      PROC_OP(NO_ARG,multiplies<double>());          PROC_OP(NO_ARG,multiplies<double>());
1575      break;          break;
1576      case DIV:      case DIV:
1577      PROC_OP(NO_ARG,divides<double>());          PROC_OP(NO_ARG,divides<double>());
1578      break;          break;
1579      case POW:      case POW:
1580         PROC_OP(double (double,double),::pow);         PROC_OP(double (double,double),::pow);
1581      break;          break;
1582      default:      default:
1583      throw DataException("Programmer error - resolveBinary can not resolve operator "+opToString(m_op)+".");          throw DataException("Programmer error - resolveBinary can not resolve operator "+opToString(m_op)+".");
1584    }    }
1585  LAZYDEBUG(cout << "Result res[" << roffset<< "]" << m_samples[roffset] << endl;)  LAZYDEBUG(cout << "Result res[" << roffset<< "]" << m_samples[roffset] << endl;)
1586    return &m_samples;    return &m_samples;
# Line 1578  LAZYDEBUG(cout << "Result res[" << roffs Line 1590  LAZYDEBUG(cout << "Result res[" << roffs
1590  // This method assumes that any subexpressions which evaluate to Constant or Tagged Data  // This method assumes that any subexpressions which evaluate to Constant or Tagged Data
1591  // have already been collapsed to IDENTITY. So we must have at least one expanded child.  // have already been collapsed to IDENTITY. So we must have at least one expanded child.
1592  // unlike the other resolve helpers, we must treat these datapoints separately.  // unlike the other resolve helpers, we must treat these datapoints separately.
1593  const DataTypes::ValueType*  const DataTypes::RealVectorType*
1594  DataLazy::resolveNodeTProd(int tid, int sampleNo, size_t& roffset)  DataLazy::resolveNodeTProd(int tid, int sampleNo, size_t& roffset) const
1595  {  {
1596  LAZYDEBUG(cout << "Resolve TensorProduct: " << toString() << endl;)  LAZYDEBUG(cout << "Resolve TensorProduct: " << toString() << endl;)
1597    
1598    size_t lroffset=0, rroffset=0;    // offsets in the left and right result vectors    size_t lroffset=0, rroffset=0;        // offsets in the left and right result vectors
1599      // first work out which of the children are expanded          // first work out which of the children are expanded
1600    bool leftExp=(m_left->m_readytype=='E');    bool leftExp=(m_left->m_readytype=='E');
1601    bool rightExp=(m_right->m_readytype=='E');    bool rightExp=(m_right->m_readytype=='E');
1602    int steps=getNumDPPSample();    int steps=getNumDPPSample();
1603    int leftStep=(leftExp? m_left->getNoValues() : 0);        // do not have scalars as input to this method    int leftStep=(leftExp? m_left->getNoValues() : 0);            // do not have scalars as input to this method
1604    int rightStep=(rightExp?m_right->getNoValues() : 0);    int rightStep=(rightExp?m_right->getNoValues() : 0);
1605    
1606    int resultStep=getNoValues();    int resultStep=getNoValues();
1607    roffset=m_samplesize*tid;    roffset=m_samplesize*tid;
1608    size_t offset=roffset;    size_t offset=roffset;
1609    
1610    const ValueType* left=m_left->resolveNodeSample(tid, sampleNo, lroffset);    const RealVectorType* left=m_left->resolveNodeSample(tid, sampleNo, lroffset);
1611    
1612    const ValueType* right=m_right->resolveNodeSample(tid, sampleNo, rroffset);    const RealVectorType* right=m_right->resolveNodeSample(tid, sampleNo, rroffset);
1613    
1614  LAZYDEBUG(cerr << "[Left shape]=" << DataTypes::shapeToString(m_left->getShape()) << "\n[Right shape]=" << DataTypes::shapeToString(m_right->getShape()) << " result=" <<DataTypes::shapeToString(getShape()) <<  endl;  LAZYDEBUG(cerr << "[Left shape]=" << DataTypes::shapeToString(m_left->getShape()) << "\n[Right shape]=" << DataTypes::shapeToString(m_right->getShape()) << " result=" <<DataTypes::shapeToString(getShape()) <<  endl;
1615  cout << getNoValues() << endl;)  cout << getNoValues() << endl;)
# Line 1611  LAZYDEBUG(cout << "m_samplesize=" << m_s Line 1623  LAZYDEBUG(cout << "m_samplesize=" << m_s
1623  LAZYDEBUG(cout << "outputshape=" << DataTypes::shapeToString(getShape()) << endl;)  LAZYDEBUG(cout << "outputshape=" << DataTypes::shapeToString(getShape()) << endl;)
1624  LAZYDEBUG(cout << "DPPS=" << m_right->getNumDPPSample() <<"."<<endl;)  LAZYDEBUG(cout << "DPPS=" << m_right->getNumDPPSample() <<"."<<endl;)
1625    
1626    double* resultp=&(m_samples[offset]);     // results are stored at the vector offset we recieved    double* resultp=&(m_samples[offset]);         // results are stored at the vector offset we received
1627    switch(m_op)    switch(m_op)
1628    {    {
1629      case PROD:      case PROD:
1630      for (int i=0;i<steps;++i,resultp+=resultStep)          for (int i=0;i<steps;++i,resultp+=resultStep)
1631      {          {
1632            const double *ptr_0 = &((*left)[lroffset]);            const double *ptr_0 = &((*left)[lroffset]);
1633            const double *ptr_1 = &((*right)[rroffset]);            const double *ptr_1 = &((*right)[rroffset]);
1634    
1635  LAZYDEBUG(cout << DataTypes::pointToString(*left, m_left->getShape(),lroffset,"LEFT") << endl;)  LAZYDEBUG(cout << DataTypes::pointToString(*left, m_left->getShape(),lroffset,"LEFT") << endl;)
1636  LAZYDEBUG(cout << DataTypes::pointToString(*right,m_right->getShape(),rroffset, "RIGHT") << endl;)  LAZYDEBUG(cout << DataTypes::pointToString(*right,m_right->getShape(),rroffset, "RIGHT") << endl;)
1637    
1638            matrix_matrix_product(m_SL, m_SM, m_SR, ptr_0, ptr_1, resultp, m_transpose);            matrix_matrix_product(m_SL, m_SM, m_SR, ptr_0, ptr_1, resultp, m_transpose);
1639    
1640        lroffset+=leftStep;            lroffset+=leftStep;
1641        rroffset+=rightStep;            rroffset+=rightStep;
1642      }          }
1643      break;          break;
1644      default:      default:
1645      throw DataException("Programmer error - resolveTProduct can not resolve operator "+opToString(m_op)+".");          throw DataException("Programmer error - resolveTProduct can not resolve operator "+opToString(m_op)+".");
1646    }    }
1647    roffset=offset;    roffset=offset;
1648    return &m_samples;    return &m_samples;
1649  }  }
1650    
1651    
1652  const DataTypes::ValueType*  const DataTypes::RealVectorType*
1653  DataLazy::resolveSample(int sampleNo, size_t& roffset)  DataLazy::resolveSample(int sampleNo, size_t& roffset) const
1654  {  {
1655  #ifdef _OPENMP  #ifdef _OPENMP
1656      int tid=omp_get_thread_num();          int tid=omp_get_thread_num();
1657  #else  #else
1658      int tid=0;          int tid=0;
1659  #endif  #endif
1660    
1661  #ifdef LAZY_STACK_PROF  #ifdef LAZY_STACK_PROF
1662      stackstart[tid]=&tid;          stackstart[tid]=&tid;
1663      stackend[tid]=&tid;          stackend[tid]=&tid;
1664      const DataTypes::ValueType* r=resolveNodeSample(tid, sampleNo, roffset);          const DataTypes::RealVectorType* r=resolveNodeSample(tid, sampleNo, roffset);
1665      size_t d=(size_t)stackstart[tid]-(size_t)stackend[tid];          size_t d=(size_t)stackstart[tid]-(size_t)stackend[tid];
1666      #pragma omp critical          #pragma omp critical
1667      if (d>maxstackuse)          if (d>maxstackuse)
1668      {          {
1669  cout << "Max resolve Stack use " << d << endl;  cout << "Max resolve Stack use " << d << endl;
1670          maxstackuse=d;                  maxstackuse=d;
1671      }          }
1672      return r;          return r;
1673  #else  #else
1674      return resolveNodeSample(tid, sampleNo, roffset);          return resolveNodeSample(tid, sampleNo, roffset);
1675  #endif  #endif
1676  }  }
1677    
# Line 1669  void Line 1681  void
1681  DataLazy::resolveToIdentity()  DataLazy::resolveToIdentity()
1682  {  {
1683     if (m_op==IDENTITY)     if (m_op==IDENTITY)
1684      return;          return;
1685     DataReady_ptr p=resolveNodeWorker();     DataReady_ptr p=resolveNodeWorker();
1686     makeIdentity(p);     makeIdentity(p);
1687  }  }
# Line 1706  DataLazy::resolveGroupWorker(std::vector Line 1718  DataLazy::resolveGroupWorker(std::vector
1718  {  {
1719    if (dats.empty())    if (dats.empty())
1720    {    {
1721      return;          return;
1722    }    }
1723    vector<DataLazy*> work;    vector<DataLazy*> work;
1724    FunctionSpace fs=dats[0]->getFunctionSpace();    FunctionSpace fs=dats[0]->getFunctionSpace();
1725    bool match=true;    bool match=true;
1726    for (int i=dats.size()-1;i>=0;--i)    for (int i=dats.size()-1;i>=0;--i)
1727    {    {
1728      if (dats[i]->m_readytype!='E')          if (dats[i]->m_readytype!='E')
1729      {          {
1730          dats[i]->collapse();                  dats[i]->collapse();
1731      }          }
1732      if (dats[i]->m_op!=IDENTITY)          if (dats[i]->m_op!=IDENTITY)
1733      {          {
1734          work.push_back(dats[i]);                  work.push_back(dats[i]);
1735          if (fs!=dats[i]->getFunctionSpace())                  if (fs!=dats[i]->getFunctionSpace())
1736          {                  {
1737              match=false;                          match=false;
1738          }                  }
1739      }          }
1740    }    }
1741    if (work.empty())    if (work.empty())
1742    {    {
1743      return;     // no work to do          return;         // no work to do
1744    }    }
1745    if (match)    // all functionspaces match.  Yes I realise this is overly strict    if (match)    // all functionspaces match.  Yes I realise this is overly strict
1746    {     // it is possible that dats[0] is one of the objects which we discarded and    {             // it is possible that dats[0] is one of the objects which we discarded and
1747          // all the other functionspaces match.                  // all the other functionspaces match.
1748      vector<DataExpanded*> dep;          vector<DataExpanded*> dep;
1749      vector<ValueType*> vecs;          vector<RealVectorType*> vecs;
1750      for (int i=0;i<work.size();++i)          for (int i=0;i<work.size();++i)
1751      {          {
1752          dep.push_back(new DataExpanded(fs,work[i]->getShape(), ValueType(work[i]->getNoValues())));                  dep.push_back(new DataExpanded(fs,work[i]->getShape(), RealVectorType(work[i]->getNoValues())));
1753          vecs.push_back(&(dep[i]->getVectorRW()));                  vecs.push_back(&(dep[i]->getVectorRW()));
1754      }          }
1755      int totalsamples=work[0]->getNumSamples();          int totalsamples=work[0]->getNumSamples();
1756      const ValueType* res=0; // Storage for answer          const RealVectorType* res=0; // Storage for answer
1757      int sample;          int sample;
1758      #pragma omp parallel private(sample, res)          #pragma omp parallel private(sample, res)
1759      {          {
1760          size_t roffset=0;              size_t roffset=0;
1761          #pragma omp for schedule(static)              #pragma omp for schedule(static)
1762          for (sample=0;sample<totalsamples;++sample)              for (sample=0;sample<totalsamples;++sample)
1763          {              {
1764          roffset=0;                  roffset=0;
1765          int j;                  int j;
1766          for (j=work.size()-1;j>=0;--j)                  for (j=work.size()-1;j>=0;--j)
1767          {                  {
1768  #ifdef _OPENMP  #ifdef _OPENMP
1769                  res=work[j]->resolveNodeSample(omp_get_thread_num(),sample,roffset);                      res=work[j]->resolveNodeSample(omp_get_thread_num(),sample,roffset);
1770  #else  #else
1771                  res=work[j]->resolveNodeSample(0,sample,roffset);                      res=work[j]->resolveNodeSample(0,sample,roffset);
1772  #endif  #endif
1773                  DataVector::size_type outoffset=dep[j]->getPointOffset(sample,0);                      RealVectorType::size_type outoffset=dep[j]->getPointOffset(sample,0);
1774                  memcpy(&((*vecs[j])[outoffset]),&((*res)[roffset]),work[j]->m_samplesize*sizeof(DataVector::ElementType));                      memcpy(&((*vecs[j])[outoffset]),&((*res)[roffset]),work[j]->m_samplesize*sizeof(RealVectorType::ElementType));
1775          }                  }
1776          }              }
1777      }          }
1778      // Now we need to load the new results as identity ops into the lazy nodes          // Now we need to load the new results as identity ops into the lazy nodes
1779      for (int i=work.size()-1;i>=0;--i)          for (int i=work.size()-1;i>=0;--i)
1780      {          {
1781          work[i]->makeIdentity(boost::dynamic_pointer_cast<DataReady>(dep[i]->getPtr()));              work[i]->makeIdentity(REFCOUNTNS::dynamic_pointer_cast<DataReady>(dep[i]->getPtr()));
1782      }          }
1783    }    }
1784    else  // functionspaces do not match    else  // functionspaces do not match
1785    {    {
1786      for (int i=0;i<work.size();++i)          for (int i=0;i<work.size();++i)
1787      {          {
1788          work[i]->resolveToIdentity();                  work[i]->resolveToIdentity();
1789      }          }
1790    }    }
1791  }  }
1792    
# Line 1784  DataLazy::resolveGroupWorker(std::vector Line 1796  DataLazy::resolveGroupWorker(std::vector
1796  DataReady_ptr  DataReady_ptr
1797  DataLazy::resolveNodeWorker()  DataLazy::resolveNodeWorker()
1798  {  {
1799    if (m_readytype!='E')     // if the whole sub-expression is Constant or Tagged, then evaluate it normally    if (m_readytype!='E')         // if the whole sub-expression is Constant or Tagged, then evaluate it normally
1800    {    {
1801      collapse();      collapse();
1802    }    }
1803    if (m_op==IDENTITY)       // So a lazy expression of Constant or Tagged data will be returned here.    if (m_op==IDENTITY)           // So a lazy expression of Constant or Tagged data will be returned here.
1804    {    {
1805      return m_id;      return m_id;
1806    }    }
1807      // from this point on we must have m_op!=IDENTITY and m_readytype=='E'          // from this point on we must have m_op!=IDENTITY and m_readytype=='E'
1808    DataExpanded* result=new DataExpanded(getFunctionSpace(),getShape(),  ValueType(getNoValues()));    DataExpanded* result=new DataExpanded(getFunctionSpace(),getShape(),  RealVectorType(getNoValues()));
1809    ValueType& resvec=result->getVectorRW();    RealVectorType& resvec=result->getVectorRW();
1810    DataReady_ptr resptr=DataReady_ptr(result);    DataReady_ptr resptr=DataReady_ptr(result);
1811    
1812    int sample;    int sample;
1813    int totalsamples=getNumSamples();    int totalsamples=getNumSamples();
1814    const ValueType* res=0;   // Storage for answer    const RealVectorType* res=0;       // Storage for answer
1815  LAZYDEBUG(cout << "Total number of samples=" <<totalsamples << endl;)  LAZYDEBUG(cout << "Total number of samples=" <<totalsamples << endl;)
1816    #pragma omp parallel private(sample,res)    #pragma omp parallel private(sample,res)
1817    {    {
1818      size_t roffset=0;          size_t roffset=0;
1819  #ifdef LAZY_STACK_PROF  #ifdef LAZY_STACK_PROF
1820      stackstart[omp_get_thread_num()]=&roffset;          stackstart[omp_get_thread_num()]=&roffset;
1821      stackend[omp_get_thread_num()]=&roffset;          stackend[omp_get_thread_num()]=&roffset;
1822  #endif  #endif
1823      #pragma omp for schedule(static)          #pragma omp for schedule(static)
1824      for (sample=0;sample<totalsamples;++sample)          for (sample=0;sample<totalsamples;++sample)
1825      {          {
1826          roffset=0;                  roffset=0;
1827  #ifdef _OPENMP  #ifdef _OPENMP
1828              res=resolveNodeSample(omp_get_thread_num(),sample,roffset);                  res=resolveNodeSample(omp_get_thread_num(),sample,roffset);
1829  #else  #else
1830              res=resolveNodeSample(0,sample,roffset);                  res=resolveNodeSample(0,sample,roffset);
1831  #endif  #endif
1832  LAZYDEBUG(cout << "Sample #" << sample << endl;)  LAZYDEBUG(cout << "Sample #" << sample << endl;)
1833  LAZYDEBUG(cout << "Final res[" << roffset<< "]=" << (*res)[roffset] << (*res)[roffset]<< endl; )  LAZYDEBUG(cout << "Final res[" << roffset<< "]=" << (*res)[roffset] << (*res)[roffset]<< endl; )
1834              DataVector::size_type outoffset=result->getPointOffset(sample,0);                  RealVectorType::size_type outoffset=result->getPointOffset(sample,0);
1835              memcpy(&(resvec[outoffset]),&((*res)[roffset]),m_samplesize*sizeof(DataVector::ElementType));                  memcpy(&(resvec[outoffset]),&((*res)[roffset]),m_samplesize*sizeof(RealVectorType::ElementType));
1836      }          }
1837    }    }
1838  #ifdef LAZY_STACK_PROF  #ifdef LAZY_STACK_PROF
1839    for (int i=0;i<getNumberOfThreads();++i)    for (int i=0;i<getNumberOfThreads();++i)
1840    {    {
1841      size_t r=((size_t)stackstart[i] - (size_t)stackend[i]);          size_t r=((size_t)stackstart[i] - (size_t)stackend[i]);
1842  //  cout << i << " " << stackstart[i] << " .. " << stackend[i] << " = " <<  r << endl;  //      cout << i << " " << stackstart[i] << " .. " << stackend[i] << " = " <<  r << endl;
1843      if (r>maxstackuse)          if (r>maxstackuse)
1844      {          {
1845          maxstackuse=r;                  maxstackuse=r;
1846      }          }
1847    }    }
1848    cout << "Max resolve Stack use=" << maxstackuse << endl;    cout << "Max resolve Stack use=" << maxstackuse << endl;
1849  #endif  #endif
# Line 1845  DataLazy::toString() const Line 1857  DataLazy::toString() const
1857    oss << "Lazy Data: [depth=" << m_height<< "] ";    oss << "Lazy Data: [depth=" << m_height<< "] ";
1858    switch (escriptParams.getLAZY_STR_FMT())    switch (escriptParams.getLAZY_STR_FMT())
1859    {    {
1860    case 1:   // tree format    case 1:       // tree format
1861      oss << endl;          oss << endl;
1862      intoTreeString(oss,"");          intoTreeString(oss,"");
1863      break;          break;
1864    case 2:   // just the depth    case 2:       // just the depth
1865      break;          break;
1866    default:    default:
1867      intoString(oss);          intoString(oss);
1868      break;          break;
1869    }    }
1870    return oss.str();    return oss.str();
1871  }  }
# Line 1866  DataLazy::intoString(ostringstream& oss) Line 1878  DataLazy::intoString(ostringstream& oss)
1878    switch (getOpgroup(m_op))    switch (getOpgroup(m_op))
1879    {    {
1880    case G_IDENTITY:    case G_IDENTITY:
1881      if (m_id->isExpanded())          if (m_id->isExpanded())
1882      {          {
1883         oss << "E";             oss << "E";
1884      }          }
1885      else if (m_id->isTagged())          else if (m_id->isTagged())
1886      {          {
1887        oss << "T";            oss << "T";
1888      }          }
1889      else if (m_id->isConstant())          else if (m_id->isConstant())
1890      {          {
1891        oss << "C";            oss << "C";
1892      }          }
1893      else          else
1894      {          {
1895        oss << "?";            oss << "?";
1896      }          }
1897      oss << '@' << m_id.get();          oss << '@' << m_id.get();
1898      break;          break;
1899    case G_BINARY:    case G_BINARY:
1900      oss << '(';          oss << '(';
1901      m_left->intoString(oss);          m_left->intoString(oss);
1902      oss << ' ' << opToString(m_op) << ' ';          oss << ' ' << opToString(m_op) << ' ';
1903      m_right->intoString(oss);          m_right->intoString(oss);
1904      oss << ')';          oss << ')';
1905      break;          break;
1906    case G_UNARY:    case G_UNARY:
1907    case G_UNARY_P:    case G_UNARY_P:
1908    case G_NP1OUT:    case G_NP1OUT:
1909    case G_NP1OUT_P:    case G_NP1OUT_P:
1910    case G_REDUCTION:    case G_REDUCTION:
1911      oss << opToString(m_op) << '(';          oss << opToString(m_op) << '(';
1912      m_left->intoString(oss);          m_left->intoString(oss);
1913      oss << ')';          oss << ')';
1914      break;          break;
1915    case G_TENSORPROD:    case G_TENSORPROD:
1916      oss << opToString(m_op) << '(';          oss << opToString(m_op) << '(';
1917      m_left->intoString(oss);          m_left->intoString(oss);
1918      oss << ", ";          oss << ", ";
1919      m_right->intoString(oss);          m_right->intoString(oss);
1920      oss << ')';          oss << ')';
1921      break;          break;
1922    case G_NP1OUT_2P:    case G_NP1OUT_2P:
1923      oss << opToString(m_op) << '(';          oss << opToString(m_op) << '(';
1924      m_left->intoString(oss);          m_left->intoString(oss);
1925      oss << ", " << m_axis_offset << ", " << m_transpose;          oss << ", " << m_axis_offset << ", " << m_transpose;
1926      oss << ')';          oss << ')';
1927      break;          break;
1928    case G_CONDEVAL:    case G_CONDEVAL:
1929      oss << opToString(m_op)<< '(' ;          oss << opToString(m_op)<< '(' ;
1930      m_mask->intoString(oss);          m_mask->intoString(oss);
1931      oss << " ? ";          oss << " ? ";
1932      m_left->intoString(oss);          m_left->intoString(oss);
1933      oss << " : ";          oss << " : ";
1934      m_right->intoString(oss);          m_right->intoString(oss);
1935      oss << ')';          oss << ')';
1936      break;          break;
1937    default:    default:
1938      oss << "UNKNOWN";          oss << "UNKNOWN";
1939    }    }
1940  }  }
1941    
# Line 1935  DataLazy::intoTreeString(ostringstream& Line 1947  DataLazy::intoTreeString(ostringstream&
1947    switch (getOpgroup(m_op))    switch (getOpgroup(m_op))
1948    {    {
1949    case G_IDENTITY:    case G_IDENTITY:
1950      if (m_id->isExpanded())          if (m_id->isExpanded())
1951      {          {
1952         oss << "E";             oss << "E";
1953      }          }
1954      else if (m_id->isTagged())          else if (m_id->isTagged())
1955      {          {
1956        oss << "T";            oss << "T";
1957      }          }
1958      else if (m_id->isConstant())          else if (m_id->isConstant())
1959      {          {
1960        oss << "C";            oss << "C";
1961      }          }
1962      else          else
1963      {          {
1964        oss << "?";            oss << "?";
1965      }          }
1966      oss << '@' << m_id.get() << endl;          oss << '@' << m_id.get() << endl;
1967      break;          break;
1968    case G_BINARY:    case G_BINARY:
1969      oss << opToString(m_op) << endl;          oss << opToString(m_op) << endl;
1970      indent+='.';          indent+='.';
1971      m_left->intoTreeString(oss, indent);          m_left->intoTreeString(oss, indent);
1972      m_right->intoTreeString(oss, indent);          m_right->intoTreeString(oss, indent);
1973      break;          break;
1974    case G_UNARY:    case G_UNARY:
1975    case G_UNARY_P:    case G_UNARY_P:
1976    case G_NP1OUT:    case G_NP1OUT:
1977    case G_NP1OUT_P:    case G_NP1OUT_P:
1978    case G_REDUCTION:    case G_REDUCTION:
1979      oss << opToString(m_op) << endl;          oss << opToString(m_op) << endl;
1980      indent+='.';          indent+='.';
1981      m_left->intoTreeString(oss, indent);          m_left->intoTreeString(oss, indent);
1982      break;          break;
1983    case G_TENSORPROD:    case G_TENSORPROD:
1984      oss << opToString(m_op) << endl;          oss << opToString(m_op) << endl;
1985      indent+='.';          indent+='.';
1986      m_left->intoTreeString(oss, indent);          m_left->intoTreeString(oss, indent);
1987      m_right->intoTreeString(oss, indent);          m_right->intoTreeString(oss, indent);
1988      break;          break;
1989    case G_NP1OUT_2P:    case G_NP1OUT_2P:
1990      oss << opToString(m_op) << ", " << m_axis_offset << ", " << m_transpose<< endl;          oss << opToString(m_op) << ", " << m_axis_offset << ", " << m_transpose<< endl;
1991      indent+='.';          indent+='.';
1992      m_left->intoTreeString(oss, indent);          m_left->intoTreeString(oss, indent);
1993      break;          break;
1994    default:    default:
1995      oss << "UNKNOWN";          oss << "UNKNOWN";
1996    }    }
1997  }  }
1998    
1999    
2000  DataAbstract*  DataAbstract*
2001  DataLazy::deepCopy()  DataLazy::deepCopy() const
2002  {  {
2003    switch (getOpgroup(m_op))    switch (getOpgroup(m_op))
2004    {    {
2005    case G_IDENTITY:  return new DataLazy(m_id->deepCopy()->getPtr());    case G_IDENTITY:  return new DataLazy(m_id->deepCopy()->getPtr());
2006    case G_UNARY:    case G_UNARY:
2007    case G_REDUCTION:      return new DataLazy(m_left->deepCopy()->getPtr(),m_op);    case G_REDUCTION:      return new DataLazy(m_left->deepCopy()->getPtr(),m_op);
2008    case G_UNARY_P:   return new DataLazy(m_left->deepCopy()->getPtr(), m_op, m_tol);    case G_UNARY_P:       return new DataLazy(m_left->deepCopy()->getPtr(), m_op, m_tol);
2009    case G_BINARY:    return new DataLazy(m_left->deepCopy()->getPtr(),m_right->deepCopy()->getPtr(),m_op);    case G_BINARY:        return new DataLazy(m_left->deepCopy()->getPtr(),m_right->deepCopy()->getPtr(),m_op);
2010    case G_NP1OUT: return new DataLazy(m_left->deepCopy()->getPtr(), m_right->deepCopy()->getPtr(),m_op);    case G_NP1OUT: return new DataLazy(m_left->deepCopy()->getPtr(), m_right->deepCopy()->getPtr(),m_op);
2011    case G_TENSORPROD: return new DataLazy(m_left->deepCopy()->getPtr(), m_right->deepCopy()->getPtr(), m_op, m_axis_offset, m_transpose);    case G_TENSORPROD: return new DataLazy(m_left->deepCopy()->getPtr(), m_right->deepCopy()->getPtr(), m_op, m_axis_offset, m_transpose);
2012    case G_NP1OUT_P:   return new DataLazy(m_left->deepCopy()->getPtr(),m_op,  m_axis_offset);    case G_NP1OUT_P:   return new DataLazy(m_left->deepCopy()->getPtr(),m_op,  m_axis_offset);
2013    case G_NP1OUT_2P:  return new DataLazy(m_left->deepCopy()->getPtr(), m_op, m_axis_offset, m_transpose);    case G_NP1OUT_2P:  return new DataLazy(m_left->deepCopy()->getPtr(), m_op, m_axis_offset, m_transpose);
2014    default:    default:
2015      throw DataException("Programmer error - do not know how to deepcopy operator "+opToString(m_op)+".");          throw DataException("Programmer error - do not know how to deepcopy operator "+opToString(m_op)+".");
2016    }    }
2017  }  }
2018    
# Line 2012  DataLazy::deepCopy() Line 2024  DataLazy::deepCopy()
2024  // or it could be some function of the lengths of the DataReady instances which  // or it could be some function of the lengths of the DataReady instances which
2025  // form part of the expression.  // form part of the expression.
2026  // Rather than have people making assumptions, I have disabled the method.  // Rather than have people making assumptions, I have disabled the method.
2027  DataTypes::ValueType::size_type  DataTypes::RealVectorType::size_type
2028  DataLazy::getLength() const  DataLazy::getLength() const
2029  {  {
2030    throw DataException("getLength() does not make sense for lazy data.");    throw DataException("getLength() does not make sense for lazy data.");
# Line 2027  DataLazy::getSlice(const DataTypes::Regi Line 2039  DataLazy::getSlice(const DataTypes::Regi
2039    
2040    
2041  // To do this we need to rely on our child nodes  // To do this we need to rely on our child nodes
2042  DataTypes::ValueType::size_type  DataTypes::RealVectorType::size_type
2043  DataLazy::getPointOffset(int sampleNo,  DataLazy::getPointOffset(int sampleNo,
2044                   int dataPointNo)                   int dataPointNo)
2045  {  {
2046    if (m_op==IDENTITY)    if (m_op==IDENTITY)
2047    {    {
2048      return m_id->getPointOffset(sampleNo,dataPointNo);          return m_id->getPointOffset(sampleNo,dataPointNo);
2049    }    }
2050    if (m_readytype!='E')    if (m_readytype!='E')
2051    {    {
2052      collapse();          collapse();
2053      return m_id->getPointOffset(sampleNo,dataPointNo);          return m_id->getPointOffset(sampleNo,dataPointNo);
2054    }    }
2055    // at this point we do not have an identity node and the expression will be Expanded    // at this point we do not have an identity node and the expression will be Expanded
2056    // so we only need to know which child to ask    // so we only need to know which child to ask
2057    if (m_left->m_readytype=='E')    if (m_left->m_readytype=='E')
2058    {    {
2059      return m_left->getPointOffset(sampleNo,dataPointNo);          return m_left->getPointOffset(sampleNo,dataPointNo);
2060    }    }
2061    else    else
2062    {    {
2063      return m_right->getPointOffset(sampleNo,dataPointNo);          return m_right->getPointOffset(sampleNo,dataPointNo);
2064    }    }
2065  }  }
2066    
2067  // To do this we need to rely on our child nodes  // To do this we need to rely on our child nodes
2068  DataTypes::ValueType::size_type  DataTypes::RealVectorType::size_type
2069  DataLazy::getPointOffset(int sampleNo,  DataLazy::getPointOffset(int sampleNo,
2070                   int dataPointNo) const                   int dataPointNo) const
2071  {  {
2072    if (m_op==IDENTITY)    if (m_op==IDENTITY)
2073    {    {
2074      return m_id->getPointOffset(sampleNo,dataPointNo);          return m_id->getPointOffset(sampleNo,dataPointNo);
2075    }    }
2076    if (m_readytype=='E')    if (m_readytype=='E')
2077    {    {
# Line 2067  DataLazy::getPointOffset(int sampleNo, Line 2079  DataLazy::getPointOffset(int sampleNo,
2079      // so we only need to know which child to ask      // so we only need to know which child to ask
2080      if (m_left->m_readytype=='E')      if (m_left->m_readytype=='E')
2081      {      {
2082      return m_left->getPointOffset(sampleNo,dataPointNo);          return m_left->getPointOffset(sampleNo,dataPointNo);
2083      }      }
2084      else      else
2085      {      {
2086      return m_right->getPointOffset(sampleNo,dataPointNo);          return m_right->getPointOffset(sampleNo,dataPointNo);
2087      }      }
2088    }    }
2089    if (m_readytype=='C')    if (m_readytype=='C')
2090    {    {
2091      return m_left->getPointOffset(sampleNo,dataPointNo); // which child doesn't matter          return m_left->getPointOffset(sampleNo,dataPointNo); // which child doesn't matter
2092    }    }
2093    throw DataException("Programmer error - getPointOffset on lazy data may require collapsing (but this object is marked const).");    throw DataException("Programmer error - getPointOffset on lazy data may require collapsing (but this object is marked const).");
2094  }  }
# Line 2086  DataLazy::getPointOffset(int sampleNo, Line 2098  DataLazy::getPointOffset(int sampleNo,
2098  void  void
2099  DataLazy::setToZero()  DataLazy::setToZero()
2100  {  {
2101  //   DataTypes::ValueType v(getNoValues(),0);  //   DataTypes::RealVectorType v(getNoValues(),0);
2102  //   m_id=DataReady_ptr(new DataConstant(getFunctionSpace(),getShape(),v));  //   m_id=DataReady_ptr(new DataConstant(getFunctionSpace(),getShape(),v));
2103  //   m_op=IDENTITY;  //   m_op=IDENTITY;
2104  //   m_right.reset();    //   m_right.reset();  
# Line 2094  DataLazy::setToZero() Line 2106  DataLazy::setToZero()
2106  //   m_readytype='C';  //   m_readytype='C';
2107  //   m_buffsRequired=1;  //   m_buffsRequired=1;
2108    
2109    privdebug=privdebug;  // to stop the compiler complaining about unused privdebug    (void)privdebug;  // to stop the compiler complaining about unused privdebug
2110    throw DataException("Programmer error - setToZero not supported for DataLazy (DataLazy objects should be read only).");    throw DataException("Programmer error - setToZero not supported for DataLazy (DataLazy objects should be read only).");
2111  }  }
2112    
2113  bool  bool
2114  DataLazy::actsExpanded() const  DataLazy::actsExpanded() const
2115  {  {
2116      return (m_readytype=='E');          return (m_readytype=='E');
2117  }  }
2118    
2119  }   // end namespace  } // end namespace
2120    

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