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Revision 6042 - (hide annotations)
Wed Mar 9 04:30:36 2016 UTC (3 years ago) by jfenwick
Original Path: trunk/escriptcore/src/DataLazy.cpp
File size: 68126 byte(s)
Preliminary to lazy cleanup


Lazy is not templated for complex as yet but hopefully
we can relieve the dependency on the briarpatch of
the current methods.


1 jfenwick 1865
2 jfenwick 3981 /*****************************************************************************
3 jfenwick 1865 *
4 jfenwick 5863 * Copyright (c) 2003-2016 by The University of Queensland
5 jfenwick 3981 * http://www.uq.edu.au
6 jfenwick 1865 *
7     * Primary Business: Queensland, Australia
8     * Licensed under the Open Software License version 3.0
9     * http://www.opensource.org/licenses/osl-3.0.php
10     *
11 jfenwick 3981 * Development until 2012 by Earth Systems Science Computational Center (ESSCC)
12 jfenwick 4657 * Development 2012-2013 by School of Earth Sciences
13     * Development from 2014 by Centre for Geoscience Computing (GeoComp)
14 jfenwick 3981 *
15     *****************************************************************************/
16 jfenwick 1865
17     #include "DataLazy.h"
18 caltinay 5972 #include "Data.h"
19     #include "DataTypes.h"
20     #include "EscriptParams.h"
21     #include "FunctionSpace.h"
22     #include "UnaryFuncs.h" // for escript::fsign
23     #include "Utils.h"
24 jfenwick 6042 #include "DataMaths.h"
25 caltinay 5972
26 caltinay 3317 #ifdef USE_NETCDF
27     #include <netcdfcpp.h>
28     #endif
29    
30 caltinay 5997 #include <iomanip> // for some fancy formatting in debug
31 jfenwick 2199
32 jfenwick 5938 using namespace escript::DataTypes;
33    
34 caltinay 5972 #define NO_ARG
35    
36 jfenwick 2157 // #define LAZYDEBUG(X) if (privdebug){X;}
37 jfenwick 2092 #define LAZYDEBUG(X)
38 jfenwick 2157 namespace
39     {
40     bool privdebug=false;
41 jfenwick 2092
42 jfenwick 2157 #define ENABLEDEBUG privdebug=true;
43     #define DISABLEDEBUG privdebug=false;
44     }
45    
46 jfenwick 2501 // #define SIZELIMIT if ((m_height>escript::escriptParams.getTOO_MANY_LEVELS()) || (m_children>escript::escriptParams.getTOO_MANY_NODES())) {cerr << "\n!!!!!!! SIZE LIMIT EXCEEDED " << m_children << ";" << m_height << endl << toString() << endl;resolveToIdentity();}
47 jfenwick 2177
48 jfenwick 2795 // #define SIZELIMIT if ((m_height>escript::escriptParams.getTOO_MANY_LEVELS()) || (m_children>escript::escriptParams.getTOO_MANY_NODES())) {cerr << "SIZE LIMIT EXCEEDED " << m_height << endl;resolveToIdentity();}
49 jfenwick 2472
50 jfenwick 2501
51 jfenwick 2795 #define SIZELIMIT if (m_height>escript::escriptParams.getTOO_MANY_LEVELS()) {if (escript::escriptParams.getLAZY_VERBOSE()){cerr << "SIZE LIMIT EXCEEDED height=" << m_height << endl;}resolveToIdentity();}
52    
53 jfenwick 1899 /*
54     How does DataLazy work?
55     ~~~~~~~~~~~~~~~~~~~~~~~
56    
57     Each instance represents a single operation on one or two other DataLazy instances. These arguments are normally
58     denoted left and right.
59    
60     A special operation, IDENTITY, stores an instance of DataReady in the m_id member.
61     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, ...
64 caltinay 4286 Note that IDENTITY is not considered a unary operation.
65 jfenwick 1899
66     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).
68     I will refer to individual DataLazy objects with the structure as nodes.
69    
70     Each node also stores:
71     - m_readytype \in {'E','T','C','?'} ~ indicates what sort of DataReady would be produced if the expression was
72 caltinay 5972 evaluated.
73 caltinay 4286 - m_buffsrequired ~ the large number of samples which would need to be kept simultaneously in order to
74 caltinay 5972 evaluate the expression.
75 jfenwick 1899 - 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.
78     Eg: if left requires 4 samples and right requires 6 then left+right requires 7 samples.
79    
80     The resolve method, which produces a DataReady from a DataLazy, does the following:
81     1) Create a DataReady to hold the new result.
82     2) Allocate a vector (v) big enough to hold m_buffsrequired samples.
83     3) For each sample, call resolveSample with v, to get its values and copy them into the result object.
84    
85     (In the case of OMP, multiple samples are resolved in parallel so the vector needs to be larger.)
86    
87     resolveSample returns a Vector* and an offset within that vector where the result is stored.
88     Normally, this would be v, but for identity nodes their internal vector is returned instead.
89    
90     The convention that I use, is that the resolve methods should store their results starting at the offset they are passed.
91    
92     For expressions which evaluate to Constant or Tagged, there is a different evaluation method.
93     The collapse method invokes the (non-lazy) operations on the Data class to evaluate the expression.
94 jfenwick 2037
95 jfenwick 2147 To add a new operator you need to do the following (plus anything I might have forgotten - adding a new group for example):
96 jfenwick 2037 1) Add to the ES_optype.
97     2) determine what opgroup your operation belongs to (X)
98     3) add a string for the op to the end of ES_opstrings
99     4) increase ES_opcount
100     5) add an entry (X) to opgroups
101     6) add an entry to the switch in collapseToReady
102     7) add an entry to resolveX
103 jfenwick 1899 */
104    
105    
106 jfenwick 1865 using namespace std;
107 jfenwick 1868 using namespace boost;
108 jfenwick 1865
109     namespace escript
110     {
111    
112     namespace
113     {
114    
115 jfenwick 2777
116     // enabling this will print out when ever the maximum stacksize used by resolve increases
117     // it assumes _OPENMP is also in use
118     //#define LAZY_STACK_PROF
119    
120    
121    
122     #ifndef _OPENMP
123     #ifdef LAZY_STACK_PROF
124     #undef LAZY_STACK_PROF
125     #endif
126     #endif
127    
128    
129     #ifdef LAZY_STACK_PROF
130     std::vector<void*> stackstart(getNumberOfThreads());
131     std::vector<void*> stackend(getNumberOfThreads());
132     size_t maxstackuse=0;
133     #endif
134    
135 jfenwick 1886 enum ES_opgroup
136     {
137     G_UNKNOWN,
138     G_IDENTITY,
139 caltinay 5972 G_BINARY, // pointwise operations with two arguments
140     G_UNARY, // pointwise operations with one argument
141     G_UNARY_P, // pointwise operations with one argument, requiring a parameter
142     G_NP1OUT, // non-pointwise op with one output
143     G_NP1OUT_P, // non-pointwise op with one output requiring a parameter
144     G_TENSORPROD, // general tensor product
145     G_NP1OUT_2P, // non-pointwise op with one output requiring two params
146     G_REDUCTION, // non-pointwise unary op with a scalar output
147 jfenwick 3035 G_CONDEVAL
148 jfenwick 1886 };
149    
150    
151    
152    
153 jfenwick 1910 string ES_opstrings[]={"UNKNOWN","IDENTITY","+","-","*","/","^",
154 caltinay 5972 "sin","cos","tan",
155     "asin","acos","atan","sinh","cosh","tanh","erf",
156     "asinh","acosh","atanh",
157     "log10","log","sign","abs","neg","pos","exp","sqrt",
158     "1/","where>0","where<0","where>=0","where<=0", "where<>0","where=0",
159     "symmetric","nonsymmetric",
160     "prod",
161     "transpose", "trace",
162     "swapaxes",
163     "minval", "maxval",
164     "condEval"};
165 jfenwick 3035 int ES_opcount=44;
166 jfenwick 1910 ES_opgroup opgroups[]={G_UNKNOWN,G_IDENTITY,G_BINARY,G_BINARY,G_BINARY,G_BINARY, G_BINARY,
167 caltinay 5972 G_UNARY,G_UNARY,G_UNARY, //10
168     G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY, // 17
169     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
171     G_UNARY,G_UNARY,G_UNARY,G_UNARY,G_UNARY, G_UNARY_P, G_UNARY_P, // 35
172     G_NP1OUT,G_NP1OUT,
173     G_TENSORPROD,
174     G_NP1OUT_P, G_NP1OUT_P,
175     G_NP1OUT_2P,
176     G_REDUCTION, G_REDUCTION,
177     G_CONDEVAL};
178 jfenwick 1886 inline
179     ES_opgroup
180     getOpgroup(ES_optype op)
181     {
182     return opgroups[op];
183     }
184    
185 jfenwick 1865 // return the FunctionSpace of the result of "left op right"
186     FunctionSpace
187     resultFS(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op)
188     {
189 caltinay 5972 // perhaps this should call interpolate and throw or something?
190     // maybe we need an interpolate node -
191     // that way, if interpolate is required in any other op we can just throw a
192     // programming error exception.
193 jfenwick 1879
194 jfenwick 1943 FunctionSpace l=left->getFunctionSpace();
195     FunctionSpace r=right->getFunctionSpace();
196     if (l!=r)
197     {
198 jfenwick 4264 signed char res=r.getDomain()->preferredInterpolationOnDomain(r.getTypeCode(), l.getTypeCode());
199     if (res==1)
200 jfenwick 1943 {
201 caltinay 5972 return l;
202 jfenwick 1943 }
203 jfenwick 4264 if (res==-1)
204 jfenwick 1943 {
205 caltinay 5972 return r;
206 jfenwick 1943 }
207     throw DataException("Cannot interpolate between the FunctionSpaces given for operation "+opToString(op)+".");
208     }
209     return l;
210 jfenwick 1865 }
211    
212     // return the shape of the result of "left op right"
213 jfenwick 2066 // the shapes resulting from tensor product are more complex to compute so are worked out elsewhere
214 jfenwick 1865 DataTypes::ShapeType
215     resultShape(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op)
216     {
217 caltinay 5972 if (left->getShape()!=right->getShape())
218     {
219     if ((getOpgroup(op)!=G_BINARY) && (getOpgroup(op)!=G_NP1OUT))
220     {
221     throw DataException("Shapes not the name - shapes must match for (point)binary operations.");
222     }
223 jfenwick 2721
224 caltinay 5972 if (left->getRank()==0) // we need to allow scalar * anything
225     {
226     return right->getShape();
227     }
228     if (right->getRank()==0)
229     {
230     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.");
233     }
234     return left->getShape();
235 jfenwick 1865 }
236    
237 jfenwick 2084 // return the shape for "op left"
238    
239     DataTypes::ShapeType
240 jfenwick 2199 resultShape(DataAbstract_ptr left, ES_optype op, int axis_offset)
241 jfenwick 2084 {
242 caltinay 5972 switch(op)
243     {
244     case TRANS:
245     { // for the scoping of variables
246     const DataTypes::ShapeType& s=left->getShape();
247     DataTypes::ShapeType sh;
248     int rank=left->getRank();
249     if (axis_offset<0 || axis_offset>rank)
250     {
251 caltinay 2779 stringstream e;
252     e << "Error - Data::transpose must have 0 <= axis_offset <= rank=" << rank;
253     throw DataException(e.str());
254 caltinay 5972 }
255     for (int i=0; i<rank; i++)
256     {
257     int index = (axis_offset+i)%rank;
258     sh.push_back(s[index]); // Append to new shape
259     }
260     return sh;
261     }
262     break;
263     case TRACE:
264     {
265     int rank=left->getRank();
266     if (rank<2)
267     {
268     throw DataException("Trace can only be computed for objects with rank 2 or greater.");
269     }
270     if ((axis_offset>rank-2) || (axis_offset<0))
271     {
272     throw DataException("Trace: axis offset must lie between 0 and rank-2 inclusive.");
273     }
274     if (rank==2)
275     {
276     return DataTypes::scalarShape;
277     }
278     else if (rank==3)
279     {
280     DataTypes::ShapeType sh;
281     if (axis_offset==0)
282     {
283     sh.push_back(left->getShape()[2]);
284     }
285     else // offset==1
286     {
287     sh.push_back(left->getShape()[0]);
288     }
289     return sh;
290     }
291     else if (rank==4)
292     {
293     DataTypes::ShapeType sh;
294     const DataTypes::ShapeType& s=left->getShape();
295     if (axis_offset==0)
296     {
297     sh.push_back(s[2]);
298     sh.push_back(s[3]);
299     }
300     else if (axis_offset==1)
301     {
302     sh.push_back(s[0]);
303     sh.push_back(s[3]);
304     }
305     else // offset==2
306     {
307     sh.push_back(s[0]);
308     sh.push_back(s[1]);
309     }
310     return sh;
311     }
312     else // unknown rank
313     {
314     throw DataException("Error - Data::trace can only be calculated for rank 2, 3 or 4 object.");
315     }
316     }
317     break;
318     default:
319     throw DataException("Programmer error - resultShape(left,op) can't compute shapes for operator "+opToString(op)+".");
320     }
321 jfenwick 2084 }
322    
323 jfenwick 2496 DataTypes::ShapeType
324     SwapShape(DataAbstract_ptr left, const int axis0, const int axis1)
325     {
326     // This code taken from the Data.cpp swapaxes() method
327     // Some of the checks are probably redundant here
328     int axis0_tmp,axis1_tmp;
329     const DataTypes::ShapeType& s=left->getShape();
330     DataTypes::ShapeType out_shape;
331     // Here's the equivalent of python s_out=s[axis_offset:]+s[:axis_offset]
332     // which goes thru all shape vector elements starting with axis_offset (at index=rank wrap around to 0)
333     int rank=left->getRank();
334     if (rank<2) {
335     throw DataException("Error - Data::swapaxes argument must have at least rank 2.");
336     }
337     if (axis0<0 || axis0>rank-1) {
338 caltinay 2779 stringstream e;
339     e << "Error - Data::swapaxes: axis0 must be between 0 and rank-1=" << (rank-1);
340     throw DataException(e.str());
341 jfenwick 2496 }
342     if (axis1<0 || axis1>rank-1) {
343 caltinay 2782 stringstream e;
344 caltinay 2779 e << "Error - Data::swapaxes: axis1 must be between 0 and rank-1=" << (rank-1);
345     throw DataException(e.str());
346 jfenwick 2496 }
347     if (axis0 == axis1) {
348     throw DataException("Error - Data::swapaxes: axis indices must be different.");
349     }
350     if (axis0 > axis1) {
351     axis0_tmp=axis1;
352     axis1_tmp=axis0;
353     } else {
354     axis0_tmp=axis0;
355     axis1_tmp=axis1;
356     }
357     for (int i=0; i<rank; i++) {
358     if (i == axis0_tmp) {
359     out_shape.push_back(s[axis1_tmp]);
360     } else if (i == axis1_tmp) {
361     out_shape.push_back(s[axis0_tmp]);
362     } else {
363     out_shape.push_back(s[i]);
364     }
365     }
366     return out_shape;
367     }
368    
369    
370 jfenwick 2066 // determine the output shape for the general tensor product operation
371     // the additional parameters return information required later for the product
372     // the majority of this code is copy pasted from C_General_Tensor_Product
373     DataTypes::ShapeType
374     GTPShape(DataAbstract_ptr left, DataAbstract_ptr right, int axis_offset, int transpose, int& SL, int& SM, int& SR)
375 jfenwick 1865 {
376 caltinay 5972
377 jfenwick 2066 // Get rank and shape of inputs
378     int rank0 = left->getRank();
379     int rank1 = right->getRank();
380     const DataTypes::ShapeType& shape0 = left->getShape();
381     const DataTypes::ShapeType& shape1 = right->getShape();
382    
383     // Prepare for the loops of the product and verify compatibility of shapes
384     int start0=0, start1=0;
385 caltinay 5972 if (transpose == 0) {}
386     else if (transpose == 1) { start0 = axis_offset; }
387     else if (transpose == 2) { start1 = rank1-axis_offset; }
388     else { throw DataException("DataLazy GeneralTensorProduct Constructor: Error - transpose should be 0, 1 or 2"); }
389 jfenwick 2066
390 jfenwick 2085 if (rank0<axis_offset)
391     {
392 caltinay 5972 throw DataException("DataLazy GeneralTensorProduct Constructor: Error - rank of left < axisoffset");
393 jfenwick 2085 }
394 jfenwick 2066
395     // Adjust the shapes for transpose
396 caltinay 5972 DataTypes::ShapeType tmpShape0(rank0); // pre-sizing the vectors rather
397     DataTypes::ShapeType tmpShape1(rank1); // than using push_back
398     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]; }
400 jfenwick 2066
401     // Prepare for the loops of the product
402     SL=1, SM=1, SR=1;
403 caltinay 5972 for (int i=0; i<rank0-axis_offset; i++) {
404 jfenwick 2066 SL *= tmpShape0[i];
405     }
406 caltinay 5972 for (int i=rank0-axis_offset; i<rank0; i++) {
407 jfenwick 2066 if (tmpShape0[i] != tmpShape1[i-(rank0-axis_offset)]) {
408     throw DataException("C_GeneralTensorProduct: Error - incompatible shapes");
409     }
410     SM *= tmpShape0[i];
411     }
412 caltinay 5972 for (int i=axis_offset; i<rank1; i++) {
413 jfenwick 2066 SR *= tmpShape1[i];
414     }
415    
416     // Define the shape of the output (rank of shape is the sum of the loop ranges below)
417 caltinay 5972 DataTypes::ShapeType shape2(rank0+rank1-2*axis_offset);
418     { // block to limit the scope of out_index
419 jfenwick 2066 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
421     for (int i=axis_offset; i<rank1; i++, ++out_index) { shape2[out_index]=tmpShape1[i]; } // Last part of arg_1_Z
422     }
423 jfenwick 2086
424     if (shape2.size()>ESCRIPT_MAX_DATA_RANK)
425     {
426     ostringstream os;
427     os << "C_GeneralTensorProduct: Error - Attempt to create a rank " << shape2.size() << " object. The maximum rank is " << ESCRIPT_MAX_DATA_RANK << ".";
428     throw DataException(os.str());
429     }
430    
431 jfenwick 2066 return shape2;
432 jfenwick 1865 }
433    
434 caltinay 5972 } // end anonymous namespace
435 jfenwick 1865
436    
437 jfenwick 1899
438     // Return a string representing the operation
439 jfenwick 1865 const std::string&
440     opToString(ES_optype op)
441     {
442     if (op<0 || op>=ES_opcount)
443     {
444     op=UNKNOWNOP;
445     }
446     return ES_opstrings[op];
447     }
448    
449 jfenwick 2500 void DataLazy::LazyNodeSetup()
450     {
451     #ifdef _OPENMP
452     int numthreads=omp_get_max_threads();
453     m_samples.resize(numthreads*m_samplesize);
454     m_sampleids=new int[numthreads];
455     for (int i=0;i<numthreads;++i)
456     {
457     m_sampleids[i]=-1;
458     }
459     #else
460     m_samples.resize(m_samplesize);
461     m_sampleids=new int[1];
462     m_sampleids[0]=-1;
463     #endif // _OPENMP
464     }
465 jfenwick 1865
466 jfenwick 2500
467     // Creates an identity node
468 jfenwick 1865 DataLazy::DataLazy(DataAbstract_ptr p)
469 caltinay 5972 : parent(p->getFunctionSpace(),p->getShape())
470     ,m_sampleids(0),
471     m_samples(1)
472 jfenwick 1865 {
473 jfenwick 1879 if (p->isLazy())
474     {
475 caltinay 5972 // I don't want identity of Lazy.
476     // Question: Why would that be so bad?
477     // 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.");
479 jfenwick 1879 }
480     else
481     {
482 caltinay 5972 p->makeLazyShared();
483     DataReady_ptr dr=dynamic_pointer_cast<DataReady>(p);
484     makeIdentity(dr);
485 jfenwick 2199 LAZYDEBUG(cout << "Wrapping " << dr.get() << " id=" << m_id.get() << endl;)
486 jfenwick 1879 }
487 jfenwick 2092 LAZYDEBUG(cout << "(1)Lazy created with " << m_samplesize << endl;)
488 jfenwick 1865 }
489    
490 jfenwick 1886 DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op)
491 caltinay 5972 : parent(left->getFunctionSpace(),(getOpgroup(op)!=G_REDUCTION)?left->getShape():DataTypes::scalarShape),
492     m_op(op),
493     m_axis_offset(0),
494     m_transpose(0),
495     m_SL(0), m_SM(0), m_SR(0)
496 jfenwick 1886 {
497 jfenwick 2721 if ((getOpgroup(op)!=G_UNARY) && (getOpgroup(op)!=G_NP1OUT) && (getOpgroup(op)!=G_REDUCTION))
498 jfenwick 1886 {
499 caltinay 5972 throw DataException("Programmer error - constructor DataLazy(left, op) will only process UNARY operations.");
500 jfenwick 1886 }
501 jfenwick 2066
502 jfenwick 1886 DataLazy_ptr lleft;
503     if (!left->isLazy())
504     {
505 caltinay 5972 lleft=DataLazy_ptr(new DataLazy(left));
506 jfenwick 1886 }
507     else
508     {
509 caltinay 5972 lleft=dynamic_pointer_cast<DataLazy>(left);
510 jfenwick 1886 }
511 jfenwick 1889 m_readytype=lleft->m_readytype;
512 jfenwick 1886 m_left=lleft;
513     m_samplesize=getNumDPPSample()*getNoValues();
514 jfenwick 2177 m_children=m_left->m_children+1;
515     m_height=m_left->m_height+1;
516 jfenwick 2500 LazyNodeSetup();
517 jfenwick 2177 SIZELIMIT
518 jfenwick 1886 }
519    
520    
521 jfenwick 1943 // In this constructor we need to consider interpolation
522 jfenwick 1879 DataLazy::DataLazy(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op)
523 caltinay 5972 : parent(resultFS(left,right,op), resultShape(left,right,op)),
524     m_op(op),
525     m_SL(0), m_SM(0), m_SR(0)
526 jfenwick 1879 {
527 jfenwick 2199 LAZYDEBUG(cout << "Forming operator with " << left.get() << " " << right.get() << endl;)
528 jfenwick 2037 if ((getOpgroup(op)!=G_BINARY))
529 jfenwick 1886 {
530 caltinay 5972 throw DataException("Programmer error - constructor DataLazy(left, right, op) will only process BINARY operations.");
531 jfenwick 1886 }
532 jfenwick 1943
533 caltinay 5972 if (getFunctionSpace()!=left->getFunctionSpace()) // left needs to be interpolated
534 jfenwick 1943 {
535 caltinay 5972 FunctionSpace fs=getFunctionSpace();
536     Data ltemp(left);
537     Data tmp(ltemp,fs);
538     left=tmp.borrowDataPtr();
539 jfenwick 1943 }
540 caltinay 5972 if (getFunctionSpace()!=right->getFunctionSpace()) // right needs to be interpolated
541 jfenwick 1943 {
542 caltinay 5972 Data tmp(Data(right),getFunctionSpace());
543     right=tmp.borrowDataPtr();
544 jfenwick 2199 LAZYDEBUG(cout << "Right interpolation required " << right.get() << endl;)
545 jfenwick 1943 }
546     left->operandCheck(*right);
547    
548 caltinay 5972 if (left->isLazy()) // the children need to be DataLazy. Wrap them in IDENTITY if required
549 jfenwick 1879 {
550 caltinay 5972 m_left=dynamic_pointer_cast<DataLazy>(left);
551 jfenwick 2199 LAZYDEBUG(cout << "Left is " << m_left->toString() << endl;)
552 jfenwick 1879 }
553     else
554     {
555 caltinay 5972 m_left=DataLazy_ptr(new DataLazy(left));
556 jfenwick 2199 LAZYDEBUG(cout << "Left " << left.get() << " wrapped " << m_left->m_id.get() << endl;)
557 jfenwick 1879 }
558     if (right->isLazy())
559     {
560 caltinay 5972 m_right=dynamic_pointer_cast<DataLazy>(right);
561 jfenwick 2199 LAZYDEBUG(cout << "Right is " << m_right->toString() << endl;)
562 jfenwick 1879 }
563     else
564     {
565 caltinay 5972 m_right=DataLazy_ptr(new DataLazy(right));
566 jfenwick 2199 LAZYDEBUG(cout << "Right " << right.get() << " wrapped " << m_right->m_id.get() << endl;)
567 jfenwick 1879 }
568 jfenwick 1889 char lt=m_left->m_readytype;
569     char rt=m_right->m_readytype;
570     if (lt=='E' || rt=='E')
571     {
572 caltinay 5972 m_readytype='E';
573 jfenwick 1889 }
574     else if (lt=='T' || rt=='T')
575     {
576 caltinay 5972 m_readytype='T';
577 jfenwick 1889 }
578     else
579     {
580 caltinay 5972 m_readytype='C';
581 jfenwick 1889 }
582 jfenwick 2066 m_samplesize=getNumDPPSample()*getNoValues();
583 jfenwick 2177 m_children=m_left->m_children+m_right->m_children+2;
584     m_height=max(m_left->m_height,m_right->m_height)+1;
585 jfenwick 2500 LazyNodeSetup();
586 jfenwick 2177 SIZELIMIT
587 jfenwick 2092 LAZYDEBUG(cout << "(3)Lazy created with " << m_samplesize << endl;)
588 jfenwick 1879 }
589    
590 jfenwick 2066 DataLazy::DataLazy(DataAbstract_ptr left, DataAbstract_ptr right, ES_optype op, int axis_offset, int transpose)
591 caltinay 5972 : parent(resultFS(left,right,op), GTPShape(left,right, axis_offset, transpose, m_SL,m_SM, m_SR)),
592     m_op(op),
593     m_axis_offset(axis_offset),
594     m_transpose(transpose)
595 jfenwick 2066 {
596     if ((getOpgroup(op)!=G_TENSORPROD))
597     {
598 caltinay 5972 throw DataException("Programmer error - constructor DataLazy(left, right, op, ax, tr) will only process BINARY operations which require parameters.");
599 jfenwick 2066 }
600     if ((transpose>2) || (transpose<0))
601     {
602 caltinay 5972 throw DataException("DataLazy GeneralTensorProduct constructor: Error - transpose should be 0, 1 or 2");
603 jfenwick 2066 }
604 caltinay 5972 if (getFunctionSpace()!=left->getFunctionSpace()) // left needs to be interpolated
605 jfenwick 2066 {
606 caltinay 5972 FunctionSpace fs=getFunctionSpace();
607     Data ltemp(left);
608     Data tmp(ltemp,fs);
609     left=tmp.borrowDataPtr();
610 jfenwick 2066 }
611 caltinay 5972 if (getFunctionSpace()!=right->getFunctionSpace()) // right needs to be interpolated
612 jfenwick 2066 {
613 caltinay 5972 Data tmp(Data(right),getFunctionSpace());
614     right=tmp.borrowDataPtr();
615 jfenwick 2066 }
616 jfenwick 2195 // left->operandCheck(*right);
617 jfenwick 1879
618 caltinay 5972 if (left->isLazy()) // the children need to be DataLazy. Wrap them in IDENTITY if required
619 jfenwick 2066 {
620 caltinay 5972 m_left=dynamic_pointer_cast<DataLazy>(left);
621 jfenwick 2066 }
622     else
623     {
624 caltinay 5972 m_left=DataLazy_ptr(new DataLazy(left));
625 jfenwick 2066 }
626     if (right->isLazy())
627     {
628 caltinay 5972 m_right=dynamic_pointer_cast<DataLazy>(right);
629 jfenwick 2066 }
630     else
631     {
632 caltinay 5972 m_right=DataLazy_ptr(new DataLazy(right));
633 jfenwick 2066 }
634     char lt=m_left->m_readytype;
635     char rt=m_right->m_readytype;
636     if (lt=='E' || rt=='E')
637     {
638 caltinay 5972 m_readytype='E';
639 jfenwick 2066 }
640     else if (lt=='T' || rt=='T')
641     {
642 caltinay 5972 m_readytype='T';
643 jfenwick 2066 }
644     else
645     {
646 caltinay 5972 m_readytype='C';
647 jfenwick 2066 }
648     m_samplesize=getNumDPPSample()*getNoValues();
649 jfenwick 2177 m_children=m_left->m_children+m_right->m_children+2;
650     m_height=max(m_left->m_height,m_right->m_height)+1;
651 jfenwick 2500 LazyNodeSetup();
652 jfenwick 2177 SIZELIMIT
653 jfenwick 2092 LAZYDEBUG(cout << "(4)Lazy created with " << m_samplesize << endl;)
654 jfenwick 2066 }
655    
656    
657 jfenwick 2084 DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op, int axis_offset)
658 caltinay 5972 : parent(left->getFunctionSpace(), resultShape(left,op, axis_offset)),
659     m_op(op),
660     m_axis_offset(axis_offset),
661     m_transpose(0),
662     m_tol(0)
663 jfenwick 2084 {
664     if ((getOpgroup(op)!=G_NP1OUT_P))
665     {
666 caltinay 5972 throw DataException("Programmer error - constructor DataLazy(left, op, ax) will only process UNARY operations which require parameters.");
667 jfenwick 2084 }
668     DataLazy_ptr lleft;
669     if (!left->isLazy())
670     {
671 caltinay 5972 lleft=DataLazy_ptr(new DataLazy(left));
672 jfenwick 2084 }
673     else
674     {
675 caltinay 5972 lleft=dynamic_pointer_cast<DataLazy>(left);
676 jfenwick 2084 }
677     m_readytype=lleft->m_readytype;
678     m_left=lleft;
679     m_samplesize=getNumDPPSample()*getNoValues();
680 jfenwick 2177 m_children=m_left->m_children+1;
681     m_height=m_left->m_height+1;
682 jfenwick 2500 LazyNodeSetup();
683 jfenwick 2177 SIZELIMIT
684 jfenwick 2092 LAZYDEBUG(cout << "(5)Lazy created with " << m_samplesize << endl;)
685 jfenwick 2084 }
686    
687 jfenwick 2147 DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op, double tol)
688 caltinay 5972 : parent(left->getFunctionSpace(), left->getShape()),
689     m_op(op),
690     m_axis_offset(0),
691     m_transpose(0),
692     m_tol(tol)
693 jfenwick 2147 {
694     if ((getOpgroup(op)!=G_UNARY_P))
695     {
696 caltinay 5972 throw DataException("Programmer error - constructor DataLazy(left, op, tol) will only process UNARY operations which require parameters.");
697 jfenwick 2147 }
698     DataLazy_ptr lleft;
699     if (!left->isLazy())
700     {
701 caltinay 5972 lleft=DataLazy_ptr(new DataLazy(left));
702 jfenwick 2147 }
703     else
704     {
705 caltinay 5972 lleft=dynamic_pointer_cast<DataLazy>(left);
706 jfenwick 2147 }
707     m_readytype=lleft->m_readytype;
708     m_left=lleft;
709     m_samplesize=getNumDPPSample()*getNoValues();
710 jfenwick 2177 m_children=m_left->m_children+1;
711     m_height=m_left->m_height+1;
712 jfenwick 2500 LazyNodeSetup();
713 jfenwick 2177 SIZELIMIT
714 jfenwick 2147 LAZYDEBUG(cout << "(6)Lazy created with " << m_samplesize << endl;)
715     }
716 jfenwick 2084
717 jfenwick 2496
718     DataLazy::DataLazy(DataAbstract_ptr left, ES_optype op, const int axis0, const int axis1)
719 caltinay 5972 : parent(left->getFunctionSpace(), SwapShape(left,axis0,axis1)),
720     m_op(op),
721     m_axis_offset(axis0),
722     m_transpose(axis1),
723     m_tol(0)
724 jfenwick 2496 {
725     if ((getOpgroup(op)!=G_NP1OUT_2P))
726     {
727 caltinay 5972 throw DataException("Programmer error - constructor DataLazy(left, op, tol) will only process UNARY operations which require two integer parameters.");
728 jfenwick 2496 }
729     DataLazy_ptr lleft;
730     if (!left->isLazy())
731     {
732 caltinay 5972 lleft=DataLazy_ptr(new DataLazy(left));
733 jfenwick 2496 }
734     else
735     {
736 caltinay 5972 lleft=dynamic_pointer_cast<DataLazy>(left);
737 jfenwick 2496 }
738     m_readytype=lleft->m_readytype;
739     m_left=lleft;
740     m_samplesize=getNumDPPSample()*getNoValues();
741     m_children=m_left->m_children+1;
742     m_height=m_left->m_height+1;
743 jfenwick 2500 LazyNodeSetup();
744 jfenwick 2496 SIZELIMIT
745     LAZYDEBUG(cout << "(7)Lazy created with " << m_samplesize << endl;)
746     }
747    
748 jfenwick 3035
749     namespace
750     {
751    
752     inline int max3(int a, int b, int c)
753     {
754 caltinay 5972 int t=(a>b?a:b);
755     return (t>c?t:c);
756 jfenwick 3035
757     }
758     }
759    
760     DataLazy::DataLazy(DataAbstract_ptr mask, DataAbstract_ptr left, DataAbstract_ptr right/*, double tol*/)
761 caltinay 5972 : parent(left->getFunctionSpace(), left->getShape()),
762     m_op(CONDEVAL),
763     m_axis_offset(0),
764     m_transpose(0),
765     m_tol(0)
766 jfenwick 3035 {
767    
768     DataLazy_ptr lmask;
769     DataLazy_ptr lleft;
770     DataLazy_ptr lright;
771     if (!mask->isLazy())
772     {
773 caltinay 5972 lmask=DataLazy_ptr(new DataLazy(mask));
774 jfenwick 3035 }
775     else
776     {
777 caltinay 5972 lmask=dynamic_pointer_cast<DataLazy>(mask);
778 jfenwick 3035 }
779     if (!left->isLazy())
780     {
781 caltinay 5972 lleft=DataLazy_ptr(new DataLazy(left));
782 jfenwick 3035 }
783     else
784     {
785 caltinay 5972 lleft=dynamic_pointer_cast<DataLazy>(left);
786 jfenwick 3035 }
787     if (!right->isLazy())
788     {
789 caltinay 5972 lright=DataLazy_ptr(new DataLazy(right));
790 jfenwick 3035 }
791     else
792     {
793 caltinay 5972 lright=dynamic_pointer_cast<DataLazy>(right);
794 jfenwick 3035 }
795     m_readytype=lmask->m_readytype;
796     if ((lleft->m_readytype!=lright->m_readytype) || (lmask->m_readytype!=lleft->m_readytype))
797     {
798 caltinay 5972 throw DataException("Programmer Error - condEval arguments must have the same readytype");
799 jfenwick 3035 }
800     m_left=lleft;
801     m_right=lright;
802     m_mask=lmask;
803     m_samplesize=getNumDPPSample()*getNoValues();
804     m_children=m_left->m_children+m_right->m_children+m_mask->m_children+1;
805     m_height=max3(m_left->m_height,m_right->m_height,m_mask->m_height)+1;
806     LazyNodeSetup();
807     SIZELIMIT
808     LAZYDEBUG(cout << "(8)Lazy created with " << m_samplesize << endl;)
809     }
810    
811    
812    
813 jfenwick 1865 DataLazy::~DataLazy()
814     {
815 jfenwick 2500 delete[] m_sampleids;
816 jfenwick 1865 }
817    
818 jfenwick 1879
819 jfenwick 1899 /*
820     \brief Evaluates the expression using methods on Data.
821     This does the work for the collapse method.
822     For reasons of efficiency do not call this method on DataExpanded nodes.
823     */
824 jfenwick 1889 DataReady_ptr
825 jfenwick 4621 DataLazy::collapseToReady() const
826 jfenwick 1889 {
827     if (m_readytype=='E')
828 caltinay 5972 { // this is more an efficiency concern than anything else
829 jfenwick 1889 throw DataException("Programmer Error - do not use collapse on Expanded data.");
830     }
831     if (m_op==IDENTITY)
832     {
833     return m_id;
834     }
835     DataReady_ptr pleft=m_left->collapseToReady();
836     Data left(pleft);
837     Data right;
838 jfenwick 2066 if ((getOpgroup(m_op)==G_BINARY) || (getOpgroup(m_op)==G_TENSORPROD))
839 jfenwick 1889 {
840     right=Data(m_right->collapseToReady());
841     }
842     Data result;
843     switch(m_op)
844     {
845     case ADD:
846 caltinay 5972 result=left+right;
847     break;
848     case SUB:
849     result=left-right;
850     break;
851     case MUL:
852     result=left*right;
853     break;
854     case DIV:
855     result=left/right;
856     break;
857 jfenwick 1889 case SIN:
858 caltinay 5972 result=left.sin();
859     break;
860 jfenwick 1889 case COS:
861 caltinay 5972 result=left.cos();
862     break;
863 jfenwick 1889 case TAN:
864 caltinay 5972 result=left.tan();
865     break;
866 jfenwick 1889 case ASIN:
867 caltinay 5972 result=left.asin();
868     break;
869 jfenwick 1889 case ACOS:
870 caltinay 5972 result=left.acos();
871     break;
872 jfenwick 1889 case ATAN:
873 caltinay 5972 result=left.atan();
874     break;
875 jfenwick 1889 case SINH:
876 caltinay 5972 result=left.sinh();
877     break;
878 jfenwick 1889 case COSH:
879 caltinay 5972 result=left.cosh();
880     break;
881 jfenwick 1889 case TANH:
882 caltinay 5972 result=left.tanh();
883     break;
884 jfenwick 1889 case ERF:
885 caltinay 5972 result=left.erf();
886     break;
887 jfenwick 1889 case ASINH:
888 caltinay 5972 result=left.asinh();
889     break;
890 jfenwick 1889 case ACOSH:
891 caltinay 5972 result=left.acosh();
892     break;
893 jfenwick 1889 case ATANH:
894 caltinay 5972 result=left.atanh();
895     break;
896 jfenwick 1889 case LOG10:
897 caltinay 5972 result=left.log10();
898     break;
899 jfenwick 1889 case LOG:
900 caltinay 5972 result=left.log();
901     break;
902 jfenwick 1889 case SIGN:
903 caltinay 5972 result=left.sign();
904     break;
905 jfenwick 1889 case ABS:
906 caltinay 5972 result=left.abs();
907     break;
908 jfenwick 1889 case NEG:
909 caltinay 5972 result=left.neg();
910     break;
911 jfenwick 1889 case POS:
912 caltinay 5972 // it doesn't mean anything for delayed.
913     // it will just trigger a deep copy of the lazy object
914     throw DataException("Programmer error - POS not supported for lazy data.");
915     break;
916 jfenwick 1889 case EXP:
917 caltinay 5972 result=left.exp();
918     break;
919 jfenwick 1889 case SQRT:
920 caltinay 5972 result=left.sqrt();
921     break;
922 jfenwick 1889 case RECIP:
923 caltinay 5972 result=left.oneOver();
924     break;
925 jfenwick 1889 case GZ:
926 caltinay 5972 result=left.wherePositive();
927     break;
928 jfenwick 1889 case LZ:
929 caltinay 5972 result=left.whereNegative();
930     break;
931 jfenwick 1889 case GEZ:
932 caltinay 5972 result=left.whereNonNegative();
933     break;
934 jfenwick 1889 case LEZ:
935 caltinay 5972 result=left.whereNonPositive();
936     break;
937 jfenwick 2147 case NEZ:
938 caltinay 5972 result=left.whereNonZero(m_tol);
939     break;
940 jfenwick 2147 case EZ:
941 caltinay 5972 result=left.whereZero(m_tol);
942     break;
943 jfenwick 2037 case SYM:
944 caltinay 5972 result=left.symmetric();
945     break;
946 jfenwick 2037 case NSYM:
947 caltinay 5972 result=left.nonsymmetric();
948     break;
949 jfenwick 2066 case PROD:
950 caltinay 5972 result=C_GeneralTensorProduct(left,right,m_axis_offset, m_transpose);
951     break;
952 jfenwick 2084 case TRANS:
953 caltinay 5972 result=left.transpose(m_axis_offset);
954     break;
955 jfenwick 2084 case TRACE:
956 caltinay 5972 result=left.trace(m_axis_offset);
957     break;
958 jfenwick 2496 case SWAP:
959 caltinay 5972 result=left.swapaxes(m_axis_offset, m_transpose);
960     break;
961 jfenwick 2721 case MINVAL:
962 caltinay 5972 result=left.minval();
963     break;
964 jfenwick 2721 case MAXVAL:
965 caltinay 5972 result=left.minval();
966     break;
967 jfenwick 1889 default:
968 caltinay 5972 throw DataException("Programmer error - collapseToReady does not know how to resolve operator "+opToString(m_op)+".");
969 jfenwick 1889 }
970     return result.borrowReadyPtr();
971     }
972    
973 jfenwick 1899 /*
974     \brief Converts the DataLazy into an IDENTITY storing the value of the expression.
975     This method uses the original methods on the Data class to evaluate the expressions.
976     For this reason, it should not be used on DataExpanded instances. (To do so would defeat
977     the purpose of using DataLazy in the first place).
978     */
979 jfenwick 1889 void
980 jfenwick 4621 DataLazy::collapse() const
981 jfenwick 1889 {
982     if (m_op==IDENTITY)
983     {
984 caltinay 5972 return;
985 jfenwick 1889 }
986     if (m_readytype=='E')
987 caltinay 5972 { // this is more an efficiency concern than anything else
988 jfenwick 1889 throw DataException("Programmer Error - do not use collapse on Expanded data.");
989     }
990     m_id=collapseToReady();
991     m_op=IDENTITY;
992     }
993    
994 jfenwick 1899
995 jfenwick 1889
996    
997    
998 jfenwick 2147
999 phornby 1987 #define PROC_OP(TYPE,X) \
1000 caltinay 5972 for (int j=0;j<onumsteps;++j)\
1001     {\
1002     for (int i=0;i<numsteps;++i,resultp+=resultStep) \
1003     { \
1004 jfenwick 2152 LAZYDEBUG(cout << "[left,right]=[" << lroffset << "," << rroffset << "]" << endl;)\
1005 jfenwick 2157 LAZYDEBUG(cout << "{left,right}={" << (*left)[lroffset] << "," << (*right)[rroffset] << "}\n";)\
1006 caltinay 5972 tensor_binary_operation< TYPE >(chunksize, &((*left)[lroffset]), &((*right)[rroffset]), resultp, X); \
1007 jfenwick 2157 LAZYDEBUG(cout << " result= " << resultp[0] << endl;) \
1008 caltinay 5972 lroffset+=leftstep; \
1009     rroffset+=rightstep; \
1010     }\
1011     lroffset+=oleftstep;\
1012     rroffset+=orightstep;\
1013     }
1014 jfenwick 1889
1015 jfenwick 1899
1016 jfenwick 2500 // 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
1018 jfenwick 5938 const DataTypes::RealVectorType*
1019 jfenwick 4621 DataLazy::resolveNodeSample(int tid, int sampleNo, size_t& roffset) const
1020 jfenwick 2500 {
1021     LAZYDEBUG(cout << "Resolve sample " << toString() << endl;)
1022 caltinay 5972 // collapse so we have a 'E' node or an IDENTITY for some other type
1023 jfenwick 2500 if (m_readytype!='E' && m_op!=IDENTITY)
1024     {
1025 caltinay 5972 collapse();
1026 jfenwick 2500 }
1027 caltinay 5972 if (m_op==IDENTITY)
1028 jfenwick 2500 {
1029 jfenwick 6042 const RealVectorType& vec=m_id->getVectorRO();
1030 jfenwick 2500 roffset=m_id->getPointOffset(sampleNo, 0);
1031 jfenwick 2777 #ifdef LAZY_STACK_PROF
1032     int x;
1033     if (&x<stackend[omp_get_thread_num()])
1034     {
1035     stackend[omp_get_thread_num()]=&x;
1036     }
1037     #endif
1038 jfenwick 2500 return &(vec);
1039     }
1040     if (m_readytype!='E')
1041     {
1042     throw DataException("Programmer Error - Collapse did not produce an expanded node.");
1043     }
1044 jfenwick 2501 if (m_sampleids[tid]==sampleNo)
1045     {
1046 caltinay 5972 roffset=tid*m_samplesize;
1047     return &(m_samples); // sample is already resolved
1048 jfenwick 2501 }
1049     m_sampleids[tid]=sampleNo;
1050 jfenwick 3035
1051 jfenwick 2500 switch (getOpgroup(m_op))
1052     {
1053     case G_UNARY:
1054     case G_UNARY_P: return resolveNodeUnary(tid, sampleNo, roffset);
1055     case G_BINARY: return resolveNodeBinary(tid, sampleNo, roffset);
1056     case G_NP1OUT: return resolveNodeNP1OUT(tid, sampleNo, roffset);
1057     case G_NP1OUT_P: return resolveNodeNP1OUT_P(tid, sampleNo, roffset);
1058     case G_TENSORPROD: return resolveNodeTProd(tid, sampleNo, roffset);
1059     case G_NP1OUT_2P: return resolveNodeNP1OUT_2P(tid, sampleNo, roffset);
1060 jfenwick 2721 case G_REDUCTION: return resolveNodeReduction(tid, sampleNo, roffset);
1061 jfenwick 3035 case G_CONDEVAL: return resolveNodeCondEval(tid, sampleNo, roffset);
1062 jfenwick 2500 default:
1063     throw DataException("Programmer Error - resolveSample does not know how to process "+opToString(m_op)+".");
1064     }
1065     }
1066    
1067 jfenwick 5938 const DataTypes::RealVectorType*
1068 jfenwick 4621 DataLazy::resolveNodeUnary(int tid, int sampleNo, size_t& roffset) const
1069 jfenwick 2500 {
1070 caltinay 5972 // 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
1072     // processing single points.
1073     // we will also know we won't get identity nodes
1074 jfenwick 2500 if (m_readytype!='E')
1075     {
1076     throw DataException("Programmer error - resolveUnary should only be called on expanded Data.");
1077     }
1078     if (m_op==IDENTITY)
1079     {
1080     throw DataException("Programmer error - resolveNodeUnary should not be called on identity nodes.");
1081     }
1082 jfenwick 5938 const DataTypes::RealVectorType* leftres=m_left->resolveNodeSample(tid, sampleNo, roffset);
1083 jfenwick 2500 const double* left=&((*leftres)[roffset]);
1084     roffset=m_samplesize*tid;
1085     double* result=&(m_samples[roffset]);
1086     switch (m_op)
1087     {
1088 caltinay 5972 case SIN:
1089     tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::sin);
1090     break;
1091 jfenwick 2500 case COS:
1092 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::cos);
1093     break;
1094 jfenwick 2500 case TAN:
1095 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::tan);
1096     break;
1097 jfenwick 2500 case ASIN:
1098 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::asin);
1099     break;
1100 jfenwick 2500 case ACOS:
1101 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::acos);
1102     break;
1103 jfenwick 2500 case ATAN:
1104 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::atan);
1105     break;
1106 jfenwick 2500 case SINH:
1107 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::sinh);
1108     break;
1109 jfenwick 2500 case COSH:
1110 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::cosh);
1111     break;
1112 jfenwick 2500 case TANH:
1113 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::tanh);
1114     break;
1115 jfenwick 2500 case ERF:
1116     #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1117 caltinay 5972 throw DataException("Error - Data:: erf function is not supported on _WIN32 platforms.");
1118 jfenwick 2500 #else
1119 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, ::erf);
1120     break;
1121 jfenwick 2500 #endif
1122     case ASINH:
1123     #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1124 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, escript::asinh_substitute);
1125 jfenwick 2500 #else
1126 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, ::asinh);
1127 jfenwick 2500 #endif
1128 caltinay 5972 break;
1129 jfenwick 2500 case ACOSH:
1130     #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1131 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, escript::acosh_substitute);
1132 jfenwick 2500 #else
1133 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, ::acosh);
1134 jfenwick 2500 #endif
1135 caltinay 5972 break;
1136 jfenwick 2500 case ATANH:
1137     #if defined (_WIN32) && !defined(__INTEL_COMPILER)
1138 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, escript::atanh_substitute);
1139 jfenwick 2500 #else
1140 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, ::atanh);
1141 jfenwick 2500 #endif
1142 caltinay 5972 break;
1143 jfenwick 2500 case LOG10:
1144 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::log10);
1145     break;
1146 jfenwick 2500 case LOG:
1147 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::log);
1148     break;
1149 jfenwick 2500 case SIGN:
1150 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, escript::fsign);
1151     break;
1152 jfenwick 2500 case ABS:
1153 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::fabs);
1154     break;
1155 jfenwick 2500 case NEG:
1156 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, negate<double>());
1157     break;
1158 jfenwick 2500 case POS:
1159 caltinay 5972 // it doesn't mean anything for delayed.
1160     // it will just trigger a deep copy of the lazy object
1161     throw DataException("Programmer error - POS not supported for lazy data.");
1162     break;
1163 jfenwick 2500 case EXP:
1164 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::exp);
1165     break;
1166 jfenwick 2500 case SQRT:
1167 caltinay 5972 tensor_unary_operation<double (*)(double)>(m_samplesize, left, result, ::sqrt);
1168     break;
1169 jfenwick 2500 case RECIP:
1170 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, bind1st(divides<double>(),1.));
1171     break;
1172 jfenwick 2500 case GZ:
1173 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, bind2nd(greater<double>(),0.0));
1174     break;
1175 jfenwick 2500 case LZ:
1176 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, bind2nd(less<double>(),0.0));
1177     break;
1178 jfenwick 2500 case GEZ:
1179 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, bind2nd(greater_equal<double>(),0.0));
1180     break;
1181 jfenwick 2500 case LEZ:
1182 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, bind2nd(less_equal<double>(),0.0));
1183     break;
1184 jfenwick 2500 // There are actually G_UNARY_P but I don't see a compelling reason to treat them differently
1185     case NEZ:
1186 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, bind2nd(AbsGT(),m_tol));
1187     break;
1188 jfenwick 2500 case EZ:
1189 caltinay 5972 tensor_unary_operation(m_samplesize, left, result, bind2nd(AbsLTE(),m_tol));
1190     break;
1191 jfenwick 2500
1192     default:
1193 caltinay 5972 throw DataException("Programmer error - resolveUnary can not resolve operator "+opToString(m_op)+".");
1194 jfenwick 2500 }
1195     return &(m_samples);
1196     }
1197    
1198    
1199 jfenwick 5938 const DataTypes::RealVectorType*
1200 jfenwick 4621 DataLazy::resolveNodeReduction(int tid, int sampleNo, size_t& roffset) const
1201 jfenwick 2721 {
1202 caltinay 5972 // 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
1204     // processing single points.
1205     // we will also know we won't get identity nodes
1206 jfenwick 2721 if (m_readytype!='E')
1207     {
1208     throw DataException("Programmer error - resolveUnary should only be called on expanded Data.");
1209     }
1210     if (m_op==IDENTITY)
1211     {
1212     throw DataException("Programmer error - resolveNodeUnary should not be called on identity nodes.");
1213     }
1214     size_t loffset=0;
1215 jfenwick 5938 const DataTypes::RealVectorType* leftres=m_left->resolveNodeSample(tid, sampleNo, loffset);
1216 jfenwick 2721
1217     roffset=m_samplesize*tid;
1218 jfenwick 2734 unsigned int ndpps=getNumDPPSample();
1219 jfenwick 3917 unsigned int psize=DataTypes::noValues(m_left->getShape());
1220 jfenwick 2721 double* result=&(m_samples[roffset]);
1221     switch (m_op)
1222     {
1223     case MINVAL:
1224 caltinay 5972 {
1225     for (unsigned int z=0;z<ndpps;++z)
1226     {
1227     FMin op;
1228     *result=DataMaths::reductionOp(*leftres, m_left->getShape(), loffset, op, numeric_limits<double>::max());
1229     loffset+=psize;
1230     result++;
1231     }
1232     }
1233     break;
1234 jfenwick 2721 case MAXVAL:
1235 caltinay 5972 {
1236     for (unsigned int z=0;z<ndpps;++z)
1237     {
1238     FMax op;
1239     *result=DataMaths::reductionOp(*leftres, m_left->getShape(), loffset, op, numeric_limits<double>::max()*-1);
1240     loffset+=psize;
1241     result++;
1242     }
1243     }
1244     break;
1245 jfenwick 2721 default:
1246 caltinay 5972 throw DataException("Programmer error - resolveUnary can not resolve operator "+opToString(m_op)+".");
1247 jfenwick 2721 }
1248     return &(m_samples);
1249     }
1250    
1251 jfenwick 5938 const DataTypes::RealVectorType*
1252 jfenwick 4621 DataLazy::resolveNodeNP1OUT(int tid, int sampleNo, size_t& roffset) const
1253 jfenwick 2500 {
1254 caltinay 5972 // 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
1256     // processing single points.
1257 jfenwick 2500 if (m_readytype!='E')
1258     {
1259     throw DataException("Programmer error - resolveNodeNP1OUT should only be called on expanded Data.");
1260     }
1261     if (m_op==IDENTITY)
1262     {
1263     throw DataException("Programmer error - resolveNodeNP1OUT should not be called on identity nodes.");
1264     }
1265     size_t subroffset;
1266 jfenwick 6042 const RealVectorType* leftres=m_left->resolveNodeSample(tid, sampleNo, subroffset);
1267 jfenwick 2500 roffset=m_samplesize*tid;
1268     size_t loop=0;
1269     size_t numsteps=(m_readytype=='E')?getNumDPPSample():1;
1270     size_t step=getNoValues();
1271     size_t offset=roffset;
1272     switch (m_op)
1273     {
1274     case SYM:
1275 caltinay 5972 for (loop=0;loop<numsteps;++loop)
1276     {
1277     DataMaths::symmetric(*leftres,m_left->getShape(),subroffset, m_samples, getShape(), offset);
1278     subroffset+=step;
1279     offset+=step;
1280     }
1281     break;
1282 jfenwick 2500 case NSYM:
1283 caltinay 5972 for (loop=0;loop<numsteps;++loop)
1284     {
1285     DataMaths::nonsymmetric(*leftres,m_left->getShape(),subroffset, m_samples, getShape(), offset);
1286     subroffset+=step;
1287     offset+=step;
1288     }
1289     break;
1290 jfenwick 2500 default:
1291 caltinay 5972 throw DataException("Programmer error - resolveNP1OUT can not resolve operator "+opToString(m_op)+".");
1292 jfenwick 2500 }
1293     return &m_samples;
1294     }
1295    
1296 jfenwick 5938 const DataTypes::RealVectorType*
1297 jfenwick 4621 DataLazy::resolveNodeNP1OUT_P(int tid, int sampleNo, size_t& roffset) const
1298 jfenwick 2500 {
1299 caltinay 5972 // 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
1301     // processing single points.
1302 jfenwick 2500 if (m_readytype!='E')
1303     {
1304     throw DataException("Programmer error - resolveNodeNP1OUT_P should only be called on expanded Data.");
1305     }
1306     if (m_op==IDENTITY)
1307     {
1308     throw DataException("Programmer error - resolveNodeNP1OUT_P should not be called on identity nodes.");
1309     }
1310     size_t subroffset;
1311     size_t offset;
1312 jfenwick 6042 const RealVectorType* leftres=m_left->resolveNodeSample(tid, sampleNo, subroffset);
1313 jfenwick 2500 roffset=m_samplesize*tid;
1314     offset=roffset;
1315     size_t loop=0;
1316     size_t numsteps=(m_readytype=='E')?getNumDPPSample():1;
1317     size_t outstep=getNoValues();
1318     size_t instep=m_left->getNoValues();
1319     switch (m_op)
1320     {
1321     case TRACE:
1322 caltinay 5972 for (loop=0;loop<numsteps;++loop)
1323     {
1324 jfenwick 2500 DataMaths::trace(*leftres,m_left->getShape(),subroffset, m_samples ,getShape(),offset,m_axis_offset);
1325 caltinay 5972 subroffset+=instep;
1326     offset+=outstep;
1327     }
1328     break;
1329 jfenwick 2500 case TRANS:
1330 caltinay 5972 for (loop=0;loop<numsteps;++loop)
1331     {
1332 jfenwick 2500 DataMaths::transpose(*leftres,m_left->getShape(),subroffset, m_samples, getShape(),offset,m_axis_offset);
1333 caltinay 5972 subroffset+=instep;
1334     offset+=outstep;
1335     }
1336     break;
1337 jfenwick 2500 default:
1338 caltinay 5972 throw DataException("Programmer error - resolveNP1OUTP can not resolve operator "+opToString(m_op)+".");
1339 jfenwick 2500 }
1340     return &m_samples;
1341     }
1342    
1343    
1344 jfenwick 5938 const DataTypes::RealVectorType*
1345 jfenwick 4621 DataLazy::resolveNodeNP1OUT_2P(int tid, int sampleNo, size_t& roffset) const
1346 jfenwick 2500 {
1347     if (m_readytype!='E')
1348     {
1349     throw DataException("Programmer error - resolveNodeNP1OUT_2P should only be called on expanded Data.");
1350     }
1351     if (m_op==IDENTITY)
1352     {
1353     throw DataException("Programmer error - resolveNodeNP1OUT_2P should not be called on identity nodes.");
1354     }
1355     size_t subroffset;
1356     size_t offset;
1357 jfenwick 6042 const RealVectorType* leftres=m_left->resolveNodeSample(tid, sampleNo, subroffset);
1358 jfenwick 2500 roffset=m_samplesize*tid;
1359     offset=roffset;
1360     size_t loop=0;
1361     size_t numsteps=(m_readytype=='E')?getNumDPPSample():1;
1362     size_t outstep=getNoValues();
1363     size_t instep=m_left->getNoValues();
1364     switch (m_op)
1365     {
1366     case SWAP:
1367 caltinay 5972 for (loop=0;loop<numsteps;++loop)
1368     {
1369 jfenwick 2500 DataMaths::swapaxes(*leftres,m_left->getShape(),subroffset, m_samples, getShape(),offset, m_axis_offset, m_transpose);
1370 caltinay 5972 subroffset+=instep;
1371     offset+=outstep;
1372     }
1373     break;
1374 jfenwick 2500 default:
1375 caltinay 5972 throw DataException("Programmer error - resolveNodeNP1OUT2P can not resolve operator "+opToString(m_op)+".");
1376 jfenwick 2500 }
1377     return &m_samples;
1378     }
1379    
1380 jfenwick 5938 const DataTypes::RealVectorType*
1381 jfenwick 4621 DataLazy::resolveNodeCondEval(int tid, int sampleNo, size_t& roffset) const
1382 jfenwick 3035 {
1383     if (m_readytype!='E')
1384     {
1385     throw DataException("Programmer error - resolveNodeCondEval should only be called on expanded Data.");
1386     }
1387     if (m_op!=CONDEVAL)
1388     {
1389     throw DataException("Programmer error - resolveNodeCondEval should only be called on CONDEVAL nodes.");
1390     }
1391     size_t subroffset;
1392 jfenwick 2500
1393 jfenwick 6042 const RealVectorType* maskres=m_mask->resolveNodeSample(tid, sampleNo, subroffset);
1394     const RealVectorType* srcres=0;
1395 jfenwick 3035 if ((*maskres)[subroffset]>0)
1396     {
1397 caltinay 5972 srcres=m_left->resolveNodeSample(tid, sampleNo, subroffset);
1398 jfenwick 3035 }
1399     else
1400     {
1401 caltinay 5972 srcres=m_right->resolveNodeSample(tid, sampleNo, subroffset);
1402 jfenwick 3035 }
1403    
1404     // Now we need to copy the result
1405    
1406     roffset=m_samplesize*tid;
1407     for (int i=0;i<m_samplesize;++i)
1408     {
1409 caltinay 5972 m_samples[roffset+i]=(*srcres)[subroffset+i];
1410 jfenwick 3035 }
1411    
1412     return &m_samples;
1413     }
1414    
1415 jfenwick 2500 // This method assumes that any subexpressions which evaluate to Constant or Tagged Data
1416     // have already been collapsed to IDENTITY. So we must have at least one expanded child.
1417     // If both children are expanded, then we can process them in a single operation (we treat
1418     // the whole sample as one big datapoint.
1419     // If one of the children is not expanded, then we need to treat each point in the sample
1420     // individually.
1421     // There is an additional complication when scalar operations are considered.
1422     // For example, 2+Vector.
1423     // In this case each double within the point is treated individually
1424 jfenwick 5938 const DataTypes::RealVectorType*
1425 jfenwick 4621 DataLazy::resolveNodeBinary(int tid, int sampleNo, size_t& roffset) const
1426 jfenwick 2500 {
1427     LAZYDEBUG(cout << "Resolve binary: " << toString() << endl;)
1428    
1429 caltinay 5972 size_t lroffset=0, rroffset=0; // offsets in the left and right result vectors
1430     // first work out which of the children are expanded
1431 jfenwick 2500 bool leftExp=(m_left->m_readytype=='E');
1432     bool rightExp=(m_right->m_readytype=='E');
1433     if (!leftExp && !rightExp)
1434     {
1435 caltinay 5972 throw DataException("Programmer Error - please use collapse if neither argument has type 'E'.");
1436 jfenwick 2500 }
1437     bool leftScalar=(m_left->getRank()==0);
1438     bool rightScalar=(m_right->getRank()==0);
1439     if ((m_left->getRank()!=m_right->getRank()) && (!leftScalar && !rightScalar))
1440     {
1441 caltinay 5972 throw DataException("resolveBinary - ranks of arguments must match unless one of them is scalar.");
1442 jfenwick 2500 }
1443     size_t leftsize=m_left->getNoValues();
1444     size_t rightsize=m_right->getNoValues();
1445 caltinay 5972 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
1447 jfenwick 2500 int rightstep=0;
1448 caltinay 5972 int numsteps=0; // total number of steps for the inner loop
1449     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
1451 jfenwick 2500 int onumsteps=1;
1452    
1453 caltinay 5972 bool LES=(leftExp && leftScalar); // Left is an expanded scalar
1454 jfenwick 2500 bool RES=(rightExp && rightScalar);
1455 caltinay 5972 bool LS=(!leftExp && leftScalar); // left is a single scalar
1456 jfenwick 2500 bool RS=(!rightExp && rightScalar);
1457 caltinay 5972 bool LN=(!leftExp && !leftScalar); // left is a single non-scalar
1458 jfenwick 2500 bool RN=(!rightExp && !rightScalar);
1459 caltinay 5972 bool LEN=(leftExp && !leftScalar); // left is an expanded non-scalar
1460 jfenwick 2500 bool REN=(rightExp && !rightScalar);
1461    
1462 caltinay 5972 if ((LES && RES) || (LEN && REN)) // both are Expanded scalars or both are expanded non-scalars
1463 jfenwick 2500 {
1464 caltinay 5972 chunksize=m_left->getNumDPPSample()*leftsize;
1465     leftstep=0;
1466     rightstep=0;
1467     numsteps=1;
1468 jfenwick 2500 }
1469     else if (LES || RES)
1470     {
1471 caltinay 5972 chunksize=1;
1472     if (LES) // left is an expanded scalar
1473     {
1474     if (RS)
1475     {
1476     leftstep=1;
1477     rightstep=0;
1478     numsteps=m_left->getNumDPPSample();
1479     }
1480     else // RN or REN
1481     {
1482     leftstep=0;
1483     oleftstep=1;
1484     rightstep=1;
1485     orightstep=(RN ? -(int)rightsize : 0);
1486     numsteps=rightsize;
1487     onumsteps=m_left->getNumDPPSample();
1488     }
1489     }
1490     else // right is an expanded scalar
1491     {
1492     if (LS)
1493     {
1494     rightstep=1;
1495     leftstep=0;
1496     numsteps=m_right->getNumDPPSample();
1497     }
1498     else
1499     {
1500     rightstep=0;
1501     orightstep=1;
1502     leftstep=1;
1503     oleftstep=(LN ? -(int)leftsize : 0);
1504     numsteps=leftsize;
1505     onumsteps=m_right->getNumDPPSample();
1506     }
1507     }
1508 jfenwick 2500 }
1509 caltinay 5972 else // this leaves (LEN, RS), (LEN, RN) and their transposes
1510 jfenwick 2500 {
1511 caltinay 5972 if (LEN) // and Right will be a single value
1512     {
1513     chunksize=rightsize;
1514     leftstep=rightsize;
1515     rightstep=0;
1516     numsteps=m_left->getNumDPPSample();
1517     if (RS)
1518     {
1519     numsteps*=leftsize;
1520     }
1521     }
1522     else // REN
1523     {
1524     chunksize=leftsize;
1525     rightstep=leftsize;
1526     leftstep=0;
1527     numsteps=m_right->getNumDPPSample();
1528     if (LS)
1529     {
1530     numsteps*=rightsize;
1531     }
1532     }
1533 jfenwick 2500 }
1534    
1535 caltinay 5972 int resultStep=max(leftstep,rightstep); // only one (at most) should be !=0
1536     // Get the values of sub-expressions
1537 jfenwick 6042 const RealVectorType* left=m_left->resolveNodeSample(tid,sampleNo,lroffset);
1538     const RealVectorType* right=m_right->resolveNodeSample(tid,sampleNo,rroffset);
1539 jfenwick 2500 LAZYDEBUG(cout << "Post sub calls in " << toString() << endl;)
1540     LAZYDEBUG(cout << "shapes=" << DataTypes::shapeToString(m_left->getShape()) << "," << DataTypes::shapeToString(m_right->getShape()) << endl;)
1541     LAZYDEBUG(cout << "chunksize=" << chunksize << endl << "leftstep=" << leftstep << " rightstep=" << rightstep;)
1542     LAZYDEBUG(cout << " numsteps=" << numsteps << endl << "oleftstep=" << oleftstep << " orightstep=" << orightstep;)
1543     LAZYDEBUG(cout << "onumsteps=" << onumsteps << endl;)
1544     LAZYDEBUG(cout << " DPPS=" << m_left->getNumDPPSample() << "," <<m_right->getNumDPPSample() << endl;)
1545     LAZYDEBUG(cout << "" << LS << RS << LN << RN << LES << RES <<LEN << REN << endl;)
1546    
1547     LAZYDEBUG(cout << "Left res["<< lroffset<< "]=" << (*left)[lroffset] << endl;)
1548     LAZYDEBUG(cout << "Right res["<< rroffset<< "]=" << (*right)[rroffset] << endl;)
1549    
1550    
1551     roffset=m_samplesize*tid;
1552 caltinay 5972 double* resultp=&(m_samples[roffset]); // results are stored at the vector offset we received
1553 jfenwick 2500 switch(m_op)
1554     {
1555     case ADD:
1556 jfenwick 6042 //PROC_OP(NO_ARG,plus<double>());
1557     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 caltinay 5972 break;
1570 jfenwick 2500 case SUB:
1571 caltinay 5972 PROC_OP(NO_ARG,minus<double>());
1572     break;
1573 jfenwick 2500 case MUL:
1574 caltinay 5972 PROC_OP(NO_ARG,multiplies<double>());
1575     break;
1576 jfenwick 2500 case DIV:
1577 caltinay 5972 PROC_OP(NO_ARG,divides<double>());
1578     break;
1579 jfenwick 2500 case POW:
1580     PROC_OP(double (double,double),::pow);
1581 caltinay 5972 break;
1582 jfenwick 2500 default:
1583 caltinay 5972 throw DataException("Programmer error - resolveBinary can not resolve operator "+opToString(m_op)+".");
1584 jfenwick 2500 }
1585     LAZYDEBUG(cout << "Result res[" << roffset<< "]" << m_samples[roffset] << endl;)
1586     return &m_samples;
1587     }
1588    
1589    
1590     // 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.
1592     // unlike the other resolve helpers, we must treat these datapoints separately.
1593 jfenwick 5938 const DataTypes::RealVectorType*
1594 jfenwick 4621 DataLazy::resolveNodeTProd(int tid, int sampleNo, size_t& roffset) const
1595 jfenwick 2500 {
1596     LAZYDEBUG(cout << "Resolve TensorProduct: " << toString() << endl;)
1597    
1598 caltinay 5972 size_t lroffset=0, rroffset=0; // offsets in the left and right result vectors
1599     // first work out which of the children are expanded
1600 jfenwick 2500 bool leftExp=(m_left->m_readytype=='E');
1601     bool rightExp=(m_right->m_readytype=='E');
1602     int steps=getNumDPPSample();
1603 caltinay 5972 int leftStep=(leftExp? m_left->getNoValues() : 0); // do not have scalars as input to this method
1604 jfenwick 2500 int rightStep=(rightExp?m_right->getNoValues() : 0);
1605    
1606     int resultStep=getNoValues();
1607     roffset=m_samplesize*tid;
1608     size_t offset=roffset;
1609    
1610 jfenwick 6042 const RealVectorType* left=m_left->resolveNodeSample(tid, sampleNo, lroffset);
1611 jfenwick 2500
1612 jfenwick 6042 const RealVectorType* right=m_right->resolveNodeSample(tid, sampleNo, rroffset);
1613 jfenwick 2500
1614     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;)
1616    
1617    
1618     LAZYDEBUG(cerr << "Post sub calls: " << toString() << endl;)
1619     LAZYDEBUG(cout << "LeftExp=" << leftExp << " rightExp=" << rightExp << endl;)
1620     LAZYDEBUG(cout << "LeftR=" << m_left->getRank() << " rightExp=" << m_right->getRank() << endl;)
1621     LAZYDEBUG(cout << "LeftSize=" << m_left->getNoValues() << " RightSize=" << m_right->getNoValues() << endl;)
1622     LAZYDEBUG(cout << "m_samplesize=" << m_samplesize << endl;)
1623     LAZYDEBUG(cout << "outputshape=" << DataTypes::shapeToString(getShape()) << endl;)
1624     LAZYDEBUG(cout << "DPPS=" << m_right->getNumDPPSample() <<"."<<endl;)
1625    
1626 caltinay 5972 double* resultp=&(m_samples[offset]); // results are stored at the vector offset we received
1627 jfenwick 2500 switch(m_op)
1628     {
1629     case PROD:
1630 caltinay 5972 for (int i=0;i<steps;++i,resultp+=resultStep)
1631     {
1632     const double *ptr_0 = &((*left)[lroffset]);
1633     const double *ptr_1 = &((*right)[rroffset]);
1634 jfenwick 2500
1635     LAZYDEBUG(cout << DataTypes::pointToString(*left, m_left->getShape(),lroffset,"LEFT") << endl;)
1636     LAZYDEBUG(cout << DataTypes::pointToString(*right,m_right->getShape(),rroffset, "RIGHT") << endl;)
1637    
1638 caltinay 5972 matrix_matrix_product(m_SL, m_SM, m_SR, ptr_0, ptr_1, resultp, m_transpose);
1639 jfenwick 2500
1640 caltinay 5972 lroffset+=leftStep;
1641     rroffset+=rightStep;
1642     }
1643     break;
1644 jfenwick 2500 default:
1645 caltinay 5972 throw DataException("Programmer error - resolveTProduct can not resolve operator "+opToString(m_op)+".");
1646 jfenwick 2500 }
1647     roffset=offset;
1648     return &m_samples;
1649     }
1650    
1651 jfenwick 1898
1652 jfenwick 5938 const DataTypes::RealVectorType*
1653 jfenwick 4621 DataLazy::resolveSample(int sampleNo, size_t& roffset) const
1654 jfenwick 1879 {
1655 jfenwick 2271 #ifdef _OPENMP
1656 caltinay 5972 int tid=omp_get_thread_num();
1657 jfenwick 2271 #else
1658 caltinay 5972 int tid=0;
1659 jfenwick 2271 #endif
1660 jfenwick 2777
1661     #ifdef LAZY_STACK_PROF
1662 caltinay 5972 stackstart[tid]=&tid;
1663     stackend[tid]=&tid;
1664     const DataTypes::RealVectorType* r=resolveNodeSample(tid, sampleNo, roffset);
1665     size_t d=(size_t)stackstart[tid]-(size_t)stackend[tid];
1666     #pragma omp critical
1667     if (d>maxstackuse)
1668     {
1669 jfenwick 2777 cout << "Max resolve Stack use " << d << endl;
1670 caltinay 5972 maxstackuse=d;
1671     }
1672     return r;
1673 jfenwick 2777 #else
1674 caltinay 5972 return resolveNodeSample(tid, sampleNo, roffset);
1675 jfenwick 2777 #endif
1676 jfenwick 2271 }
1677    
1678    
1679 jfenwick 2497 // This needs to do the work of the identity constructor
1680 jfenwick 2177 void
1681     DataLazy::resolveToIdentity()
1682     {
1683     if (m_op==IDENTITY)
1684 caltinay 5972 return;
1685 jfenwick 2500 DataReady_ptr p=resolveNodeWorker();
1686 jfenwick 2177 makeIdentity(p);
1687     }
1688 jfenwick 1889
1689 jfenwick 2177 void DataLazy::makeIdentity(const DataReady_ptr& p)
1690     {
1691     m_op=IDENTITY;
1692     m_axis_offset=0;
1693     m_transpose=0;
1694     m_SL=m_SM=m_SR=0;
1695     m_children=m_height=0;
1696     m_id=p;
1697     if(p->isConstant()) {m_readytype='C';}
1698     else if(p->isExpanded()) {m_readytype='E';}
1699     else if (p->isTagged()) {m_readytype='T';}
1700     else {throw DataException("Unknown DataReady instance in convertToIdentity constructor.");}
1701     m_samplesize=p->getNumDPPSample()*p->getNoValues();
1702     m_left.reset();
1703     m_right.reset();
1704     }
1705    
1706 jfenwick 2497
1707     DataReady_ptr
1708     DataLazy::resolve()
1709     {
1710     resolveToIdentity();
1711     return m_id;
1712     }
1713    
1714 jfenwick 2799
1715     /* This is really a static method but I think that caused problems in windows */
1716     void
1717     DataLazy::resolveGroupWorker(std::vector<DataLazy*>& dats)
1718     {
1719     if (dats.empty())
1720     {
1721 caltinay 5972 return;
1722 jfenwick 2799 }
1723     vector<DataLazy*> work;
1724     FunctionSpace fs=dats[0]->getFunctionSpace();
1725     bool match=true;
1726 jfenwick 2824 for (int i=dats.size()-1;i>=0;--i)
1727 jfenwick 2799 {
1728 caltinay 5972 if (dats[i]->m_readytype!='E')
1729     {
1730     dats[i]->collapse();
1731     }
1732     if (dats[i]->m_op!=IDENTITY)
1733     {
1734     work.push_back(dats[i]);
1735     if (fs!=dats[i]->getFunctionSpace())
1736     {
1737     match=false;
1738     }
1739     }
1740 jfenwick 2799 }
1741     if (work.empty())
1742     {
1743 caltinay 5972 return; // no work to do
1744 jfenwick 2799 }
1745 caltinay 5972 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
1747     // all the other functionspaces match.
1748     vector<DataExpanded*> dep;
1749 jfenwick 6042 vector<RealVectorType*> vecs;
1750 caltinay 5972 for (int i=0;i<work.size();++i)
1751     {
1752 jfenwick 6042 dep.push_back(new DataExpanded(fs,work[i]->getShape(), RealVectorType(work[i]->getNoValues())));
1753 caltinay 5972 vecs.push_back(&(dep[i]->getVectorRW()));
1754     }
1755     int totalsamples=work[0]->getNumSamples();
1756 jfenwick 6042 const RealVectorType* res=0; // Storage for answer
1757 caltinay 5972 int sample;
1758     #pragma omp parallel private(sample, res)
1759     {
1760     size_t roffset=0;
1761     #pragma omp for schedule(static)
1762     for (sample=0;sample<totalsamples;++sample)
1763     {
1764     roffset=0;
1765     int j;
1766     for (j=work.size()-1;j>=0;--j)
1767     {
1768 jfenwick 2799 #ifdef _OPENMP
1769 caltinay 5972 res=work[j]->resolveNodeSample(omp_get_thread_num(),sample,roffset);
1770 jfenwick 2799 #else
1771 caltinay 5972 res=work[j]->resolveNodeSample(0,sample,roffset);
1772 jfenwick 2799 #endif
1773 caltinay 5972 RealVectorType::size_type outoffset=dep[j]->getPointOffset(sample,0);
1774     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
1779     for (int i=work.size()-1;i>=0;--i)
1780     {
1781 jfenwick 5985 work[i]->makeIdentity(REFCOUNTNS::dynamic_pointer_cast<DataReady>(dep[i]->getPtr()));
1782 caltinay 5972 }
1783 jfenwick 2799 }
1784 caltinay 5972 else // functionspaces do not match
1785 jfenwick 2799 {
1786 caltinay 5972 for (int i=0;i<work.size();++i)
1787     {
1788     work[i]->resolveToIdentity();
1789     }
1790 jfenwick 2799 }
1791     }
1792    
1793    
1794    
1795 jfenwick 2500 // This version of resolve uses storage in each node to hold results
1796     DataReady_ptr
1797     DataLazy::resolveNodeWorker()
1798     {
1799 caltinay 5972 if (m_readytype!='E') // if the whole sub-expression is Constant or Tagged, then evaluate it normally
1800 jfenwick 2500 {
1801     collapse();
1802     }
1803 caltinay 5972 if (m_op==IDENTITY) // So a lazy expression of Constant or Tagged data will be returned here.
1804 jfenwick 2500 {
1805     return m_id;
1806     }
1807 caltinay 5972 // from this point on we must have m_op!=IDENTITY and m_readytype=='E'
1808 jfenwick 6042 DataExpanded* result=new DataExpanded(getFunctionSpace(),getShape(), RealVectorType(getNoValues()));
1809     RealVectorType& resvec=result->getVectorRW();
1810 jfenwick 2500 DataReady_ptr resptr=DataReady_ptr(result);
1811    
1812     int sample;
1813     int totalsamples=getNumSamples();
1814 jfenwick 6042 const RealVectorType* res=0; // Storage for answer
1815 jfenwick 2500 LAZYDEBUG(cout << "Total number of samples=" <<totalsamples << endl;)
1816 jfenwick 2777 #pragma omp parallel private(sample,res)
1817 jfenwick 2500 {
1818 caltinay 5972 size_t roffset=0;
1819 jfenwick 2777 #ifdef LAZY_STACK_PROF
1820 caltinay 5972 stackstart[omp_get_thread_num()]=&roffset;
1821     stackend[omp_get_thread_num()]=&roffset;
1822 jfenwick 2777 #endif
1823 caltinay 5972 #pragma omp for schedule(static)
1824     for (sample=0;sample<totalsamples;++sample)
1825     {
1826     roffset=0;
1827 jfenwick 2500 #ifdef _OPENMP
1828 caltinay 5972 res=resolveNodeSample(omp_get_thread_num(),sample,roffset);
1829 jfenwick 2500 #else
1830 caltinay 5972 res=resolveNodeSample(0,sample,roffset);
1831 jfenwick 2500 #endif
1832     LAZYDEBUG(cout << "Sample #" << sample << endl;)
1833     LAZYDEBUG(cout << "Final res[" << roffset<< "]=" << (*res)[roffset] << (*res)[roffset]<< endl; )
1834 caltinay 5972 RealVectorType::size_type outoffset=result->getPointOffset(sample,0);
1835     memcpy(&(resvec[outoffset]),&((*res)[roffset]),m_samplesize*sizeof(RealVectorType::ElementType));
1836     }
1837 jfenwick 2500 }
1838 jfenwick 2777 #ifdef LAZY_STACK_PROF
1839     for (int i=0;i<getNumberOfThreads();++i)
1840     {
1841 caltinay 5972 size_t r=((size_t)stackstart[i] - (size_t)stackend[i]);
1842     // cout << i << " " << stackstart[i] << " .. " << stackend[i] << " = " << r << endl;
1843     if (r>maxstackuse)
1844     {
1845     maxstackuse=r;
1846     }
1847 jfenwick 2777 }
1848     cout << "Max resolve Stack use=" << maxstackuse << endl;
1849     #endif
1850 jfenwick 2500 return resptr;
1851     }
1852    
1853 jfenwick 1865 std::string
1854     DataLazy::toString() const
1855     {
1856 jfenwick 1886 ostringstream oss;
1857 jfenwick 2791 oss << "Lazy Data: [depth=" << m_height<< "] ";
1858 jfenwick 2795 switch (escriptParams.getLAZY_STR_FMT())
1859 jfenwick 2737 {
1860 caltinay 5972 case 1: // tree format
1861     oss << endl;
1862     intoTreeString(oss,"");
1863     break;
1864     case 2: // just the depth
1865     break;
1866 jfenwick 2795 default:
1867 caltinay 5972 intoString(oss);
1868     break;
1869 jfenwick 2737 }
1870 jfenwick 1886 return oss.str();
1871 jfenwick 1865 }
1872    
1873 jfenwick 1899
1874 jfenwick 1886 void
1875     DataLazy::intoString(ostringstream& oss) const
1876     {
1877 jfenwick 2271 // oss << "[" << m_children <<";"<<m_height <<"]";
1878 jfenwick 1886 switch (getOpgroup(m_op))
1879     {
1880 jfenwick 1889 case G_IDENTITY:
1881 caltinay 5972 if (m_id->isExpanded())
1882     {
1883     oss << "E";
1884     }
1885     else if (m_id->isTagged())
1886     {
1887     oss << "T";
1888     }
1889     else if (m_id->isConstant())
1890     {
1891     oss << "C";
1892     }
1893     else
1894     {
1895     oss << "?";
1896     }
1897     oss << '@' << m_id.get();
1898     break;
1899 jfenwick 1886 case G_BINARY:
1900 caltinay 5972 oss << '(';
1901     m_left->intoString(oss);
1902     oss << ' ' << opToString(m_op) << ' ';
1903     m_right->intoString(oss);
1904     oss << ')';
1905     break;
1906 jfenwick 1886 case G_UNARY:
1907 jfenwick 2147 case G_UNARY_P:
1908 jfenwick 2037 case G_NP1OUT:
1909 jfenwick 2084 case G_NP1OUT_P:
1910 jfenwick 2721 case G_REDUCTION:
1911 caltinay 5972 oss << opToString(m_op) << '(';
1912     m_left->intoString(oss);
1913     oss << ')';
1914     break;
1915 jfenwick 2066 case G_TENSORPROD:
1916 caltinay 5972 oss << opToString(m_op) << '(';
1917     m_left->intoString(oss);
1918     oss << ", ";
1919     m_right->intoString(oss);
1920     oss << ')';
1921     break;
1922 jfenwick 2496 case G_NP1OUT_2P:
1923 caltinay 5972 oss << opToString(m_op) << '(';
1924     m_left->intoString(oss);
1925     oss << ", " << m_axis_offset << ", " << m_transpose;
1926     oss << ')';
1927     break;
1928 jfenwick 3035 case G_CONDEVAL:
1929 caltinay 5972 oss << opToString(m_op)<< '(' ;
1930     m_mask->intoString(oss);
1931     oss << " ? ";
1932     m_left->intoString(oss);
1933     oss << " : ";
1934     m_right->intoString(oss);
1935     oss << ')';
1936     break;
1937 jfenwick 1886 default:
1938 caltinay 5972 oss << "UNKNOWN";
1939 jfenwick 1886 }
1940     }
1941    
1942 jfenwick 2737
1943     void
1944     DataLazy::intoTreeString(ostringstream& oss, string indent) const
1945     {
1946     oss << '[' << m_rank << ':' << setw(3) << m_samplesize << "] " << indent;
1947     switch (getOpgroup(m_op))
1948     {
1949     case G_IDENTITY:
1950 caltinay 5972 if (m_id->isExpanded())
1951     {
1952     oss << "E";
1953     }
1954     else if (m_id->isTagged())
1955     {
1956     oss << "T";
1957     }
1958     else if (m_id->isConstant())
1959     {
1960     oss << "C";
1961     }
1962     else
1963     {
1964     oss << "?";
1965     }
1966     oss << '@' << m_id.get() << endl;
1967     break;
1968 jfenwick 2737 case G_BINARY:
1969 caltinay 5972 oss << opToString(m_op) << endl;
1970     indent+='.';
1971     m_left->intoTreeString(oss, indent);
1972     m_right->intoTreeString(oss, indent);
1973     break;
1974 jfenwick 2737 case G_UNARY:
1975     case G_UNARY_P:
1976     case G_NP1OUT:
1977     case G_NP1OUT_P:
1978     case G_REDUCTION:
1979 caltinay 5972 oss << opToString(m_op) << endl;
1980     indent+='.';
1981     m_left->intoTreeString(oss, indent);
1982     break;
1983 jfenwick 2737 case G_TENSORPROD:
1984 caltinay 5972 oss << opToString(m_op) << endl;
1985     indent+='.';
1986     m_left->intoTreeString(oss, indent);
1987     m_right->intoTreeString(oss, indent);
1988     break;
1989 jfenwick 2737 case G_NP1OUT_2P:
1990 caltinay 5972 oss << opToString(m_op) << ", " << m_axis_offset << ", " << m_transpose<< endl;
1991     indent+='.';
1992     m_left->intoTreeString(oss, indent);
1993     break;
1994 jfenwick 2737 default:
1995 caltinay 5972 oss << "UNKNOWN";
1996 jfenwick 2737 }
1997     }
1998    
1999    
2000 jfenwick 1865 DataAbstract*
2001 jfenwick 5938 DataLazy::deepCopy() const
2002 jfenwick 1865 {
2003 jfenwick 1935 switch (getOpgroup(m_op))
2004 jfenwick 1865 {
2005 jfenwick 1935 case G_IDENTITY: return new DataLazy(m_id->deepCopy()->getPtr());
2006 caltinay 5972 case G_UNARY:
2007 jfenwick 2721 case G_REDUCTION: return new DataLazy(m_left->deepCopy()->getPtr(),m_op);
2008 caltinay 5972 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);
2010 jfenwick 2066 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);
2012 jfenwick 2721 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);
2014 jfenwick 1935 default:
2015 caltinay 5972 throw DataException("Programmer error - do not know how to deepcopy operator "+opToString(m_op)+".");
2016 jfenwick 1865 }
2017     }
2018    
2019    
2020 jfenwick 2721
2021 jfenwick 2066 // There is no single, natural interpretation of getLength on DataLazy.
2022     // Instances of DataReady can look at the size of their vectors.
2023     // For lazy though, it could be the size the data would be if it were resolved;
2024     // or it could be some function of the lengths of the DataReady instances which
2025     // form part of the expression.
2026     // Rather than have people making assumptions, I have disabled the method.
2027 jfenwick 5938 DataTypes::RealVectorType::size_type
2028 jfenwick 1865 DataLazy::getLength() const
2029     {
2030 jfenwick 2066 throw DataException("getLength() does not make sense for lazy data.");
2031 jfenwick 1865 }
2032    
2033    
2034     DataAbstract*
2035     DataLazy::getSlice(const DataTypes::RegionType& region) const
2036     {
2037 jfenwick 1879 throw DataException("getSlice - not implemented for Lazy objects.");
2038 jfenwick 1865 }
2039    
2040 jfenwick 1935
2041     // To do this we need to rely on our child nodes
2042 jfenwick 5938 DataTypes::RealVectorType::size_type
2043 jfenwick 1865 DataLazy::getPointOffset(int sampleNo,
2044 jfenwick 1935 int dataPointNo)
2045     {
2046     if (m_op==IDENTITY)
2047     {
2048 caltinay 5972 return m_id->getPointOffset(sampleNo,dataPointNo);
2049 jfenwick 1935 }
2050     if (m_readytype!='E')
2051     {
2052 caltinay 5972 collapse();
2053     return m_id->getPointOffset(sampleNo,dataPointNo);
2054 jfenwick 1935 }
2055     // 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
2057     if (m_left->m_readytype=='E')
2058     {
2059 caltinay 5972 return m_left->getPointOffset(sampleNo,dataPointNo);
2060 jfenwick 1935 }
2061     else
2062     {
2063 caltinay 5972 return m_right->getPointOffset(sampleNo,dataPointNo);
2064 jfenwick 1935 }
2065     }
2066    
2067     // To do this we need to rely on our child nodes
2068 jfenwick 5938 DataTypes::RealVectorType::size_type
2069 jfenwick 1935 DataLazy::getPointOffset(int sampleNo,
2070 jfenwick 1865 int dataPointNo) const
2071     {
2072 jfenwick 1935 if (m_op==IDENTITY)
2073     {
2074 caltinay 5972 return m_id->getPointOffset(sampleNo,dataPointNo);
2075 jfenwick 1935 }
2076     if (m_readytype=='E')
2077     {
2078     // at this point we do not have an identity node and the expression will be Expanded
2079     // so we only need to know which child to ask
2080     if (m_left->m_readytype=='E')
2081     {
2082 caltinay 5972 return m_left->getPointOffset(sampleNo,dataPointNo);
2083 jfenwick 1935 }
2084     else
2085     {
2086 caltinay 5972 return m_right->getPointOffset(sampleNo,dataPointNo);
2087 jfenwick 1935 }
2088     }
2089     if (m_readytype=='C')
2090     {
2091 caltinay 5972 return m_left->getPointOffset(sampleNo,dataPointNo); // which child doesn't matter
2092 jfenwick 1935 }
2093     throw DataException("Programmer error - getPointOffset on lazy data may require collapsing (but this object is marked const).");
2094 jfenwick 1865 }
2095    
2096 jfenwick 2271
2097     // I have decided to let Data:: handle this issue.
2098 jfenwick 1901 void
2099     DataLazy::setToZero()
2100     {
2101 jfenwick 5938 // DataTypes::RealVectorType v(getNoValues(),0);
2102 jfenwick 2271 // m_id=DataReady_ptr(new DataConstant(getFunctionSpace(),getShape(),v));
2103     // m_op=IDENTITY;
2104     // m_right.reset();
2105     // m_left.reset();
2106     // m_readytype='C';
2107     // m_buffsRequired=1;
2108    
2109 jfenwick 4634 (void)privdebug; // to stop the compiler complaining about unused privdebug
2110 jfenwick 2271 throw DataException("Programmer error - setToZero not supported for DataLazy (DataLazy objects should be read only).");
2111 jfenwick 1901 }
2112    
2113 jfenwick 2271 bool
2114     DataLazy::actsExpanded() const
2115     {
2116 caltinay 5972 return (m_readytype=='E');
2117 jfenwick 2271 }
2118    
2119 caltinay 5997 } // end namespace
2120 caltinay 5972

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