/[escript]/trunk/escript/src/Data.cpp
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Contents of /trunk/escript/src/Data.cpp

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Revision 1332 - (show annotations)
Tue Oct 23 03:28:51 2007 UTC (11 years, 10 months ago) by matt
File size: 76193 byte(s)
Pow now uses the new binary function interface of C_TensorBinaryOperation.

1
2 /* $Id$ */
3
4 /*******************************************************
5 *
6 * Copyright 2003-2007 by ACceSS MNRF
7 * Copyright 2007 by University of Queensland
8 *
9 * http://esscc.uq.edu.au
10 * Primary Business: Queensland, Australia
11 * Licensed under the Open Software License version 3.0
12 * http://www.opensource.org/licenses/osl-3.0.php
13 *
14 *******************************************************/
15
16 #include "Data.h"
17
18 #include "DataExpanded.h"
19 #include "DataConstant.h"
20 #include "DataTagged.h"
21 #include "DataEmpty.h"
22 #include "DataArrayView.h"
23 #include "FunctionSpaceFactory.h"
24 #include "AbstractContinuousDomain.h"
25 #include "UnaryFuncs.h"
26 extern "C" {
27 #include "escript/blocktimer.h"
28 }
29
30 #include <fstream>
31 #include <algorithm>
32 #include <vector>
33 #include <functional>
34
35 #include <boost/python/dict.hpp>
36 #include <boost/python/extract.hpp>
37 #include <boost/python/long.hpp>
38
39 using namespace std;
40 using namespace boost::python;
41 using namespace boost;
42 using namespace escript;
43
44 Data::Data()
45 {
46 //
47 // Default data is type DataEmpty
48 DataAbstract* temp=new DataEmpty();
49 shared_ptr<DataAbstract> temp_data(temp);
50 m_data=temp_data;
51 m_protected=false;
52 }
53
54 Data::Data(double value,
55 const tuple& shape,
56 const FunctionSpace& what,
57 bool expanded)
58 {
59 DataArrayView::ShapeType dataPointShape;
60 for (int i = 0; i < shape.attr("__len__")(); ++i) {
61 dataPointShape.push_back(extract<const int>(shape[i]));
62 }
63
64 int len = DataArrayView::noValues(dataPointShape);
65 DataVector temp_data(len,value,len);
66 DataArrayView temp_dataView(temp_data, dataPointShape);
67
68 initialise(temp_dataView, what, expanded);
69
70 m_protected=false;
71 }
72
73 Data::Data(double value,
74 const DataArrayView::ShapeType& dataPointShape,
75 const FunctionSpace& what,
76 bool expanded)
77 {
78 int len = DataArrayView::noValues(dataPointShape);
79
80 DataVector temp_data(len,value,len);
81 DataArrayView temp_dataView(temp_data, dataPointShape);
82
83 initialise(temp_dataView, what, expanded);
84
85 m_protected=false;
86 }
87
88 Data::Data(const Data& inData)
89 {
90 m_data=inData.m_data;
91 m_protected=inData.isProtected();
92 }
93
94 Data::Data(const Data& inData,
95 const DataArrayView::RegionType& region)
96 {
97 //
98 // Create Data which is a slice of another Data
99 DataAbstract* tmp = inData.m_data->getSlice(region);
100 shared_ptr<DataAbstract> temp_data(tmp);
101 m_data=temp_data;
102 m_protected=false;
103 }
104
105 Data::Data(const Data& inData,
106 const FunctionSpace& functionspace)
107 {
108 if (inData.getFunctionSpace()==functionspace) {
109 m_data=inData.m_data;
110 } else {
111 Data tmp(0,inData.getPointDataView().getShape(),functionspace,true);
112 // Note: Must use a reference or pointer to a derived object
113 // in order to get polymorphic behaviour. Shouldn't really
114 // be able to create an instance of AbstractDomain but that was done
115 // as a boost:python work around which may no longer be required.
116 const AbstractDomain& inDataDomain=inData.getDomain();
117 if (inDataDomain==functionspace.getDomain()) {
118 inDataDomain.interpolateOnDomain(tmp,inData);
119 } else {
120 inDataDomain.interpolateACross(tmp,inData);
121 }
122 m_data=tmp.m_data;
123 }
124 m_protected=false;
125 }
126
127 Data::Data(const DataTagged::TagListType& tagKeys,
128 const DataTagged::ValueListType & values,
129 const DataArrayView& defaultValue,
130 const FunctionSpace& what,
131 bool expanded)
132 {
133 DataAbstract* temp=new DataTagged(tagKeys,values,defaultValue,what);
134 shared_ptr<DataAbstract> temp_data(temp);
135 m_data=temp_data;
136 m_protected=false;
137 if (expanded) {
138 expand();
139 }
140 }
141
142 Data::Data(const numeric::array& value,
143 const FunctionSpace& what,
144 bool expanded)
145 {
146 initialise(value,what,expanded);
147 m_protected=false;
148 }
149
150 Data::Data(const DataArrayView& value,
151 const FunctionSpace& what,
152 bool expanded)
153 {
154 initialise(value,what,expanded);
155 m_protected=false;
156 }
157
158 Data::Data(const object& value,
159 const FunctionSpace& what,
160 bool expanded)
161 {
162 numeric::array asNumArray(value);
163 initialise(asNumArray,what,expanded);
164 m_protected=false;
165 }
166
167
168 Data::Data(const object& value,
169 const Data& other)
170 {
171
172 numeric::array asNumArray(value);
173
174
175 // extract the shape of the numarray
176 DataArrayView::ShapeType tempShape;
177 for (int i=0; i < asNumArray.getrank(); i++) {
178 tempShape.push_back(extract<int>(asNumArray.getshape()[i]));
179 }
180 // get the space for the data vector
181 int len = DataArrayView::noValues(tempShape);
182 DataVector temp_data(len, 0.0, len);
183 DataArrayView temp_dataView(temp_data, tempShape);
184 temp_dataView.copy(asNumArray);
185
186 //
187 // Create DataConstant using the given value and all other parameters
188 // copied from other. If value is a rank 0 object this Data
189 // will assume the point data shape of other.
190
191 if (temp_dataView.getRank()==0) {
192 int len = DataArrayView::noValues(other.getPointDataView().getShape());
193
194 DataVector temp2_data(len, temp_dataView(), len);
195 DataArrayView temp2_dataView(temp2_data, other.getPointDataView().getShape());
196 initialise(temp2_dataView, other.getFunctionSpace(), false);
197
198 } else {
199 //
200 // Create a DataConstant with the same sample shape as other
201 initialise(temp_dataView, other.getFunctionSpace(), false);
202 }
203 m_protected=false;
204 }
205
206 Data::~Data()
207 {
208
209 }
210
211 escriptDataC
212 Data::getDataC()
213 {
214 escriptDataC temp;
215 temp.m_dataPtr=(void*)this;
216 return temp;
217 }
218
219 escriptDataC
220 Data::getDataC() const
221 {
222 escriptDataC temp;
223 temp.m_dataPtr=(void*)this;
224 return temp;
225 }
226
227 const boost::python::tuple
228 Data::getShapeTuple() const
229 {
230 const DataArrayView::ShapeType& shape=getDataPointShape();
231 switch(getDataPointRank()) {
232 case 0:
233 return make_tuple();
234 case 1:
235 return make_tuple(long_(shape[0]));
236 case 2:
237 return make_tuple(long_(shape[0]),long_(shape[1]));
238 case 3:
239 return make_tuple(long_(shape[0]),long_(shape[1]),long_(shape[2]));
240 case 4:
241 return make_tuple(long_(shape[0]),long_(shape[1]),long_(shape[2]),long_(shape[3]));
242 default:
243 throw DataException("Error - illegal Data rank.");
244 }
245 }
246 void
247 Data::copy(const Data& other)
248 {
249 //
250 // Perform a deep copy
251 {
252 DataExpanded* temp=dynamic_cast<DataExpanded*>(other.m_data.get());
253 if (temp!=0) {
254 //
255 // Construct a DataExpanded copy
256 DataAbstract* newData=new DataExpanded(*temp);
257 shared_ptr<DataAbstract> temp_data(newData);
258 m_data=temp_data;
259 return;
260 }
261 }
262 {
263 DataTagged* temp=dynamic_cast<DataTagged*>(other.m_data.get());
264 if (temp!=0) {
265 //
266 // Construct a DataTagged copy
267 DataAbstract* newData=new DataTagged(*temp);
268 shared_ptr<DataAbstract> temp_data(newData);
269 m_data=temp_data;
270 return;
271 }
272 }
273 {
274 DataConstant* temp=dynamic_cast<DataConstant*>(other.m_data.get());
275 if (temp!=0) {
276 //
277 // Construct a DataConstant copy
278 DataAbstract* newData=new DataConstant(*temp);
279 shared_ptr<DataAbstract> temp_data(newData);
280 m_data=temp_data;
281 return;
282 }
283 }
284 {
285 DataEmpty* temp=dynamic_cast<DataEmpty*>(other.m_data.get());
286 if (temp!=0) {
287 //
288 // Construct a DataEmpty copy
289 DataAbstract* newData=new DataEmpty();
290 shared_ptr<DataAbstract> temp_data(newData);
291 m_data=temp_data;
292 return;
293 }
294 }
295 throw DataException("Error - Copy not implemented for this Data type.");
296 }
297
298
299 void
300 Data::setToZero()
301 {
302 {
303 DataExpanded* temp=dynamic_cast<DataExpanded*>(m_data.get());
304 if (temp!=0) {
305 temp->setToZero();
306 return;
307 }
308 }
309 {
310 DataTagged* temp=dynamic_cast<DataTagged*>(m_data.get());
311 if (temp!=0) {
312 temp->setToZero();
313 return;
314 }
315 }
316 {
317 DataConstant* temp=dynamic_cast<DataConstant*>(m_data.get());
318 if (temp!=0) {
319 temp->setToZero();
320 return;
321 }
322 }
323 throw DataException("Error - Data can not be set to zero.");
324 }
325
326 void
327 Data::copyWithMask(const Data& other,
328 const Data& mask)
329 {
330 Data mask1;
331 Data mask2;
332
333 mask1 = mask.wherePositive();
334 mask2.copy(mask1);
335
336 mask1 *= other;
337 mask2 *= *this;
338 mask2 = *this - mask2;
339
340 *this = mask1 + mask2;
341 }
342
343 bool
344 Data::isExpanded() const
345 {
346 DataExpanded* temp=dynamic_cast<DataExpanded*>(m_data.get());
347 return (temp!=0);
348 }
349
350 bool
351 Data::isTagged() const
352 {
353 DataTagged* temp=dynamic_cast<DataTagged*>(m_data.get());
354 return (temp!=0);
355 }
356
357 bool
358 Data::isEmpty() const
359 {
360 DataEmpty* temp=dynamic_cast<DataEmpty*>(m_data.get());
361 return (temp!=0);
362 }
363
364 bool
365 Data::isConstant() const
366 {
367 DataConstant* temp=dynamic_cast<DataConstant*>(m_data.get());
368 return (temp!=0);
369 }
370
371 void
372 Data::setProtection()
373 {
374 m_protected=true;
375 }
376
377 bool
378 Data::isProtected() const
379 {
380 return m_protected;
381 }
382
383
384
385 void
386 Data::expand()
387 {
388 if (isConstant()) {
389 DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());
390 DataAbstract* temp=new DataExpanded(*tempDataConst);
391 shared_ptr<DataAbstract> temp_data(temp);
392 m_data=temp_data;
393 } else if (isTagged()) {
394 DataTagged* tempDataTag=dynamic_cast<DataTagged*>(m_data.get());
395 DataAbstract* temp=new DataExpanded(*tempDataTag);
396 shared_ptr<DataAbstract> temp_data(temp);
397 m_data=temp_data;
398 } else if (isExpanded()) {
399 //
400 // do nothing
401 } else if (isEmpty()) {
402 throw DataException("Error - Expansion of DataEmpty not possible.");
403 } else {
404 throw DataException("Error - Expansion not implemented for this Data type.");
405 }
406 }
407
408 void
409 Data::tag()
410 {
411 if (isConstant()) {
412 DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());
413 DataAbstract* temp=new DataTagged(*tempDataConst);
414 shared_ptr<DataAbstract> temp_data(temp);
415 m_data=temp_data;
416 } else if (isTagged()) {
417 // do nothing
418 } else if (isExpanded()) {
419 throw DataException("Error - Creating tag data from DataExpanded not possible.");
420 } else if (isEmpty()) {
421 throw DataException("Error - Creating tag data from DataEmpty not possible.");
422 } else {
423 throw DataException("Error - Tagging not implemented for this Data type.");
424 }
425 }
426
427 Data
428 Data::oneOver() const
429 {
430 return escript::unaryOp(*this,bind1st(divides<double>(),1.));
431 }
432
433 Data
434 Data::wherePositive() const
435 {
436 return escript::unaryOp(*this,bind2nd(greater<double>(),0.0));
437 }
438
439 Data
440 Data::whereNegative() const
441 {
442 return escript::unaryOp(*this,bind2nd(less<double>(),0.0));
443 }
444
445 Data
446 Data::whereNonNegative() const
447 {
448 return escript::unaryOp(*this,bind2nd(greater_equal<double>(),0.0));
449 }
450
451 Data
452 Data::whereNonPositive() const
453 {
454 return escript::unaryOp(*this,bind2nd(less_equal<double>(),0.0));
455 }
456
457 Data
458 Data::whereZero(double tol) const
459 {
460 Data dataAbs=abs();
461 return escript::unaryOp(dataAbs,bind2nd(less_equal<double>(),tol));
462 }
463
464 Data
465 Data::whereNonZero(double tol) const
466 {
467 Data dataAbs=abs();
468 return escript::unaryOp(dataAbs,bind2nd(greater<double>(),tol));
469 }
470
471 Data
472 Data::interpolate(const FunctionSpace& functionspace) const
473 {
474 return Data(*this,functionspace);
475 }
476
477 bool
478 Data::probeInterpolation(const FunctionSpace& functionspace) const
479 {
480 if (getFunctionSpace()==functionspace) {
481 return true;
482 } else {
483 const AbstractDomain& domain=getDomain();
484 if (domain==functionspace.getDomain()) {
485 return domain.probeInterpolationOnDomain(getFunctionSpace().getTypeCode(),functionspace.getTypeCode());
486 } else {
487 return domain.probeInterpolationACross(getFunctionSpace().getTypeCode(),functionspace.getDomain(),functionspace.getTypeCode());
488 }
489 }
490 }
491
492 Data
493 Data::gradOn(const FunctionSpace& functionspace) const
494 {
495 double blocktimer_start = blocktimer_time();
496 if (functionspace.getDomain()!=getDomain())
497 throw DataException("Error - gradient cannot be calculated on different domains.");
498 DataArrayView::ShapeType grad_shape=getPointDataView().getShape();
499 grad_shape.push_back(functionspace.getDim());
500 Data out(0.0,grad_shape,functionspace,true);
501 getDomain().setToGradient(out,*this);
502 blocktimer_increment("grad()", blocktimer_start);
503 return out;
504 }
505
506 Data
507 Data::grad() const
508 {
509 return gradOn(escript::function(getDomain()));
510 }
511
512 int
513 Data::getDataPointSize() const
514 {
515 return getPointDataView().noValues();
516 }
517
518 DataArrayView::ValueType::size_type
519 Data::getLength() const
520 {
521 return m_data->getLength();
522 }
523
524 const DataArrayView::ShapeType&
525 Data::getDataPointShape() const
526 {
527 return getPointDataView().getShape();
528 }
529
530
531
532 const
533 boost::python::numeric::array
534 Data:: getValueOfDataPoint(int dataPointNo)
535 {
536 size_t length=0;
537 int i, j, k, l;
538 //
539 // determine the rank and shape of each data point
540 int dataPointRank = getDataPointRank();
541 DataArrayView::ShapeType dataPointShape = getDataPointShape();
542
543 //
544 // create the numeric array to be returned
545 boost::python::numeric::array numArray(0.0);
546
547 //
548 // the shape of the returned numeric array will be the same
549 // as that of the data point
550 int arrayRank = dataPointRank;
551 DataArrayView::ShapeType arrayShape = dataPointShape;
552
553 //
554 // resize the numeric array to the shape just calculated
555 if (arrayRank==0) {
556 numArray.resize(1);
557 }
558 if (arrayRank==1) {
559 numArray.resize(arrayShape[0]);
560 }
561 if (arrayRank==2) {
562 numArray.resize(arrayShape[0],arrayShape[1]);
563 }
564 if (arrayRank==3) {
565 numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2]);
566 }
567 if (arrayRank==4) {
568 numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2],arrayShape[3]);
569 }
570
571 if (getNumDataPointsPerSample()>0) {
572 int sampleNo = dataPointNo/getNumDataPointsPerSample();
573 int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
574 //
575 // Check a valid sample number has been supplied
576 if ((sampleNo >= getNumSamples()) || (sampleNo < 0 )) {
577 throw DataException("Error - Data::convertToNumArray: invalid sampleNo.");
578 }
579
580 //
581 // Check a valid data point number has been supplied
582 if ((dataPointNoInSample >= getNumDataPointsPerSample()) || (dataPointNoInSample < 0)) {
583 throw DataException("Error - Data::convertToNumArray: invalid dataPointNoInSample.");
584 }
585 // TODO: global error handling
586 // create a view of the data if it is stored locally
587 DataArrayView dataPointView = getDataPoint(sampleNo, dataPointNoInSample);
588
589 switch( dataPointRank ){
590 case 0 :
591 numArray[0] = dataPointView();
592 break;
593 case 1 :
594 for( i=0; i<dataPointShape[0]; i++ )
595 numArray[i]=dataPointView(i);
596 break;
597 case 2 :
598 for( i=0; i<dataPointShape[0]; i++ )
599 for( j=0; j<dataPointShape[1]; j++)
600 numArray[make_tuple(i,j)]=dataPointView(i,j);
601 break;
602 case 3 :
603 for( i=0; i<dataPointShape[0]; i++ )
604 for( j=0; j<dataPointShape[1]; j++ )
605 for( k=0; k<dataPointShape[2]; k++)
606 numArray[make_tuple(i,j,k)]=dataPointView(i,j,k);
607 break;
608 case 4 :
609 for( i=0; i<dataPointShape[0]; i++ )
610 for( j=0; j<dataPointShape[1]; j++ )
611 for( k=0; k<dataPointShape[2]; k++ )
612 for( l=0; l<dataPointShape[3]; l++)
613 numArray[make_tuple(i,j,k,l)]=dataPointView(i,j,k,l);
614 break;
615 }
616 }
617 //
618 // return the array
619 return numArray;
620
621 }
622 void
623 Data::setValueOfDataPointToPyObject(int dataPointNo, const boost::python::object& py_object)
624 {
625 // this will throw if the value cannot be represented
626 boost::python::numeric::array num_array(py_object);
627 setValueOfDataPointToArray(dataPointNo,num_array);
628
629
630 }
631
632 void
633 Data::setValueOfDataPointToArray(int dataPointNo, const boost::python::numeric::array& num_array)
634 {
635 if (isProtected()) {
636 throw DataException("Error - attempt to update protected Data object.");
637 }
638 //
639 // check rank
640 if (num_array.getrank()<getDataPointRank())
641 throw DataException("Rank of numarray does not match Data object rank");
642
643 //
644 // check shape of num_array
645 for (int i=0; i<getDataPointRank(); i++) {
646 if (extract<int>(num_array.getshape()[i])!=getDataPointShape()[i])
647 throw DataException("Shape of numarray does not match Data object rank");
648 }
649 //
650 // make sure data is expanded:
651 if (!isExpanded()) {
652 expand();
653 }
654 if (getNumDataPointsPerSample()>0) {
655 int sampleNo = dataPointNo/getNumDataPointsPerSample();
656 int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
657 m_data->copyToDataPoint(sampleNo, dataPointNoInSample,num_array);
658 } else {
659 m_data->copyToDataPoint(-1, 0,num_array);
660 }
661 }
662
663 void
664 Data::setValueOfDataPoint(int dataPointNo, const double value)
665 {
666 if (isProtected()) {
667 throw DataException("Error - attempt to update protected Data object.");
668 }
669 //
670 // make sure data is expanded:
671 if (!isExpanded()) {
672 expand();
673 }
674 if (getNumDataPointsPerSample()>0) {
675 int sampleNo = dataPointNo/getNumDataPointsPerSample();
676 int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
677 m_data->copyToDataPoint(sampleNo, dataPointNoInSample,value);
678 } else {
679 m_data->copyToDataPoint(-1, 0,value);
680 }
681 }
682
683 const
684 boost::python::numeric::array
685 Data::getValueOfGlobalDataPoint(int procNo, int dataPointNo)
686 {
687 size_t length=0;
688 int i, j, k, l, pos;
689 //
690 // determine the rank and shape of each data point
691 int dataPointRank = getDataPointRank();
692 DataArrayView::ShapeType dataPointShape = getDataPointShape();
693
694 //
695 // create the numeric array to be returned
696 boost::python::numeric::array numArray(0.0);
697
698 //
699 // the shape of the returned numeric array will be the same
700 // as that of the data point
701 int arrayRank = dataPointRank;
702 DataArrayView::ShapeType arrayShape = dataPointShape;
703
704 //
705 // resize the numeric array to the shape just calculated
706 if (arrayRank==0) {
707 numArray.resize(1);
708 }
709 if (arrayRank==1) {
710 numArray.resize(arrayShape[0]);
711 }
712 if (arrayRank==2) {
713 numArray.resize(arrayShape[0],arrayShape[1]);
714 }
715 if (arrayRank==3) {
716 numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2]);
717 }
718 if (arrayRank==4) {
719 numArray.resize(arrayShape[0],arrayShape[1],arrayShape[2],arrayShape[3]);
720 }
721
722 // added for the MPI communication
723 length=1;
724 for( i=0; i<arrayRank; i++ ) length *= arrayShape[i];
725 double *tmpData = new double[length];
726
727 //
728 // load the values for the data point into the numeric array.
729
730 // updated for the MPI case
731 if( get_MPIRank()==procNo ){
732 if (getNumDataPointsPerSample()>0) {
733 int sampleNo = dataPointNo/getNumDataPointsPerSample();
734 int dataPointNoInSample = dataPointNo - sampleNo * getNumDataPointsPerSample();
735 //
736 // Check a valid sample number has been supplied
737 if ((sampleNo >= getNumSamples()) || (sampleNo < 0 )) {
738 throw DataException("Error - Data::convertToNumArray: invalid sampleNo.");
739 }
740
741 //
742 // Check a valid data point number has been supplied
743 if ((dataPointNoInSample >= getNumDataPointsPerSample()) || (dataPointNoInSample < 0)) {
744 throw DataException("Error - Data::convertToNumArray: invalid dataPointNoInSample.");
745 }
746 // TODO: global error handling
747 // create a view of the data if it is stored locally
748 DataArrayView dataPointView = getDataPoint(sampleNo, dataPointNoInSample);
749
750 // pack the data from the view into tmpData for MPI communication
751 pos=0;
752 switch( dataPointRank ){
753 case 0 :
754 tmpData[0] = dataPointView();
755 break;
756 case 1 :
757 for( i=0; i<dataPointShape[0]; i++ )
758 tmpData[i]=dataPointView(i);
759 break;
760 case 2 :
761 for( i=0; i<dataPointShape[0]; i++ )
762 for( j=0; j<dataPointShape[1]; j++, pos++ )
763 tmpData[pos]=dataPointView(i,j);
764 break;
765 case 3 :
766 for( i=0; i<dataPointShape[0]; i++ )
767 for( j=0; j<dataPointShape[1]; j++ )
768 for( k=0; k<dataPointShape[2]; k++, pos++ )
769 tmpData[pos]=dataPointView(i,j,k);
770 break;
771 case 4 :
772 for( i=0; i<dataPointShape[0]; i++ )
773 for( j=0; j<dataPointShape[1]; j++ )
774 for( k=0; k<dataPointShape[2]; k++ )
775 for( l=0; l<dataPointShape[3]; l++, pos++ )
776 tmpData[pos]=dataPointView(i,j,k,l);
777 break;
778 }
779 }
780 }
781 #ifdef PASO_MPI
782 // broadcast the data to all other processes
783 MPI_Bcast( tmpData, length, MPI_DOUBLE, procNo, get_MPIComm() );
784 #endif
785
786 // unpack the data
787 switch( dataPointRank ){
788 case 0 :
789 numArray[0]=tmpData[0];
790 break;
791 case 1 :
792 for( i=0; i<dataPointShape[0]; i++ )
793 numArray[i]=tmpData[i];
794 break;
795 case 2 :
796 for( i=0; i<dataPointShape[0]; i++ )
797 for( j=0; j<dataPointShape[1]; j++ )
798 numArray[make_tuple(i,j)]=tmpData[i+j*dataPointShape[0]];
799 break;
800 case 3 :
801 for( i=0; i<dataPointShape[0]; i++ )
802 for( j=0; j<dataPointShape[1]; j++ )
803 for( k=0; k<dataPointShape[2]; k++ )
804 numArray[make_tuple(i,j,k)]=tmpData[i+dataPointShape[0]*(j*+k*dataPointShape[1])];
805 break;
806 case 4 :
807 for( i=0; i<dataPointShape[0]; i++ )
808 for( j=0; j<dataPointShape[1]; j++ )
809 for( k=0; k<dataPointShape[2]; k++ )
810 for( l=0; l<dataPointShape[3]; l++ )
811 numArray[make_tuple(i,j,k,l)]=tmpData[i+dataPointShape[0]*(j*+dataPointShape[1]*(k+l*dataPointShape[2]))];
812 break;
813 }
814
815 delete [] tmpData;
816 //
817 // return the loaded array
818 return numArray;
819 }
820
821
822
823 boost::python::numeric::array
824 Data::integrate() const
825 {
826 int index;
827 int rank = getDataPointRank();
828 DataArrayView::ShapeType shape = getDataPointShape();
829 int dataPointSize = getDataPointSize();
830
831 //
832 // calculate the integral values
833 vector<double> integrals(dataPointSize);
834 vector<double> integrals_local(dataPointSize);
835 #ifdef PASO_MPI
836 AbstractContinuousDomain::asAbstractContinuousDomain(getDomain()).setToIntegrals(integrals_local,*this);
837 // Global sum: use an array instead of a vector because elements of array are guaranteed to be contiguous in memory
838 double *tmp = new double[dataPointSize];
839 double *tmp_local = new double[dataPointSize];
840 for (int i=0; i<dataPointSize; i++) { tmp_local[i] = integrals_local[i]; }
841 MPI_Allreduce( &tmp_local[0], &tmp[0], dataPointSize, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD );
842 for (int i=0; i<dataPointSize; i++) { integrals[i] = tmp[i]; }
843 delete[] tmp;
844 delete[] tmp_local;
845 #else
846 AbstractContinuousDomain::asAbstractContinuousDomain(getDomain()).setToIntegrals(integrals,*this);
847 #endif
848
849 //
850 // create the numeric array to be returned
851 // and load the array with the integral values
852 boost::python::numeric::array bp_array(1.0);
853 if (rank==0) {
854 bp_array.resize(1);
855 index = 0;
856 bp_array[0] = integrals[index];
857 }
858 if (rank==1) {
859 bp_array.resize(shape[0]);
860 for (int i=0; i<shape[0]; i++) {
861 index = i;
862 bp_array[i] = integrals[index];
863 }
864 }
865 if (rank==2) {
866 bp_array.resize(shape[0],shape[1]);
867 for (int i=0; i<shape[0]; i++) {
868 for (int j=0; j<shape[1]; j++) {
869 index = i + shape[0] * j;
870 bp_array[make_tuple(i,j)] = integrals[index];
871 }
872 }
873 }
874 if (rank==3) {
875 bp_array.resize(shape[0],shape[1],shape[2]);
876 for (int i=0; i<shape[0]; i++) {
877 for (int j=0; j<shape[1]; j++) {
878 for (int k=0; k<shape[2]; k++) {
879 index = i + shape[0] * ( j + shape[1] * k );
880 bp_array[make_tuple(i,j,k)] = integrals[index];
881 }
882 }
883 }
884 }
885 if (rank==4) {
886 bp_array.resize(shape[0],shape[1],shape[2],shape[3]);
887 for (int i=0; i<shape[0]; i++) {
888 for (int j=0; j<shape[1]; j++) {
889 for (int k=0; k<shape[2]; k++) {
890 for (int l=0; l<shape[3]; l++) {
891 index = i + shape[0] * ( j + shape[1] * ( k + shape[2] * l ) );
892 bp_array[make_tuple(i,j,k,l)] = integrals[index];
893 }
894 }
895 }
896 }
897 }
898
899 //
900 // return the loaded array
901 return bp_array;
902 }
903
904 Data
905 Data::sin() const
906 {
907 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::sin);
908 }
909
910 Data
911 Data::cos() const
912 {
913 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::cos);
914 }
915
916 Data
917 Data::tan() const
918 {
919 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::tan);
920 }
921
922 Data
923 Data::asin() const
924 {
925 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::asin);
926 }
927
928 Data
929 Data::acos() const
930 {
931 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::acos);
932 }
933
934
935 Data
936 Data::atan() const
937 {
938 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::atan);
939 }
940
941 Data
942 Data::sinh() const
943 {
944 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::sinh);
945 }
946
947 Data
948 Data::cosh() const
949 {
950 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::cosh);
951 }
952
953 Data
954 Data::tanh() const
955 {
956 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::tanh);
957 }
958
959
960 Data
961 Data::erf() const
962 {
963 #ifdef _WIN32
964 throw DataException("Error - Data:: erf function is not supported on _WIN32 platforms.");
965 #else
966 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::erf);
967 #endif
968 }
969
970 Data
971 Data::asinh() const
972 {
973 #ifdef _WIN32
974 return escript::unaryOp(*this,escript::asinh_substitute);
975 #else
976 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::asinh);
977 #endif
978 }
979
980 Data
981 Data::acosh() const
982 {
983 #ifdef _WIN32
984 return escript::unaryOp(*this,escript::acosh_substitute);
985 #else
986 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::acosh);
987 #endif
988 }
989
990 Data
991 Data::atanh() const
992 {
993 #ifdef _WIN32
994 return escript::unaryOp(*this,escript::atanh_substitute);
995 #else
996 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::atanh);
997 #endif
998 }
999
1000 Data
1001 Data::log10() const
1002 {
1003 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::log10);
1004 }
1005
1006 Data
1007 Data::log() const
1008 {
1009 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::log);
1010 }
1011
1012 Data
1013 Data::sign() const
1014 {
1015 return escript::unaryOp(*this,escript::fsign);
1016 }
1017
1018 Data
1019 Data::abs() const
1020 {
1021 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::fabs);
1022 }
1023
1024 Data
1025 Data::neg() const
1026 {
1027 return escript::unaryOp(*this,negate<double>());
1028 }
1029
1030 Data
1031 Data::pos() const
1032 {
1033 Data result;
1034 // perform a deep copy
1035 result.copy(*this);
1036 return result;
1037 }
1038
1039 Data
1040 Data::exp() const
1041 {
1042 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::exp);
1043 }
1044
1045 Data
1046 Data::sqrt() const
1047 {
1048 return escript::unaryOp(*this,(Data::UnaryDFunPtr)::sqrt);
1049 }
1050
1051 double
1052 Data::Lsup() const
1053 {
1054 double localValue, globalValue;
1055 //
1056 // set the initial absolute maximum value to zero
1057
1058 AbsMax abs_max_func;
1059 localValue = algorithm(abs_max_func,0);
1060 #ifdef PASO_MPI
1061 MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MAX, MPI_COMM_WORLD );
1062 return globalValue;
1063 #else
1064 return localValue;
1065 #endif
1066 }
1067
1068 double
1069 Data::sup() const
1070 {
1071 double localValue, globalValue;
1072 //
1073 // set the initial maximum value to min possible double
1074 FMax fmax_func;
1075 localValue = algorithm(fmax_func,numeric_limits<double>::max()*-1);
1076 #ifdef PASO_MPI
1077 MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MAX, MPI_COMM_WORLD );
1078 return globalValue;
1079 #else
1080 return localValue;
1081 #endif
1082 }
1083
1084 double
1085 Data::inf() const
1086 {
1087 double localValue, globalValue;
1088 //
1089 // set the initial minimum value to max possible double
1090 FMin fmin_func;
1091 localValue = algorithm(fmin_func,numeric_limits<double>::max());
1092 #ifdef PASO_MPI
1093 MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MIN, MPI_COMM_WORLD );
1094 return globalValue;
1095 #else
1096 return localValue;
1097 #endif
1098 }
1099
1100 /* TODO */
1101 /* global reduction */
1102 Data
1103 Data::maxval() const
1104 {
1105 //
1106 // set the initial maximum value to min possible double
1107 FMax fmax_func;
1108 return dp_algorithm(fmax_func,numeric_limits<double>::max()*-1);
1109 }
1110
1111 Data
1112 Data::minval() const
1113 {
1114 //
1115 // set the initial minimum value to max possible double
1116 FMin fmin_func;
1117 return dp_algorithm(fmin_func,numeric_limits<double>::max());
1118 }
1119
1120 Data
1121 Data::swapaxes(const int axis0, const int axis1) const
1122 {
1123 int axis0_tmp,axis1_tmp;
1124 DataArrayView::ShapeType s=getDataPointShape();
1125 DataArrayView::ShapeType ev_shape;
1126 // Here's the equivalent of python s_out=s[axis_offset:]+s[:axis_offset]
1127 // which goes thru all shape vector elements starting with axis_offset (at index=rank wrap around to 0)
1128 int rank=getDataPointRank();
1129 if (rank<2) {
1130 throw DataException("Error - Data::swapaxes argument must have at least rank 2.");
1131 }
1132 if (axis0<0 || axis0>rank-1) {
1133 throw DataException("Error - Data::swapaxes: axis0 must be between 0 and rank-1=" + rank-1);
1134 }
1135 if (axis1<0 || axis1>rank-1) {
1136 throw DataException("Error - Data::swapaxes: axis1 must be between 0 and rank-1=" + rank-1);
1137 }
1138 if (axis0 == axis1) {
1139 throw DataException("Error - Data::swapaxes: axis indices must be different.");
1140 }
1141 if (axis0 > axis1) {
1142 axis0_tmp=axis1;
1143 axis1_tmp=axis0;
1144 } else {
1145 axis0_tmp=axis0;
1146 axis1_tmp=axis1;
1147 }
1148 for (int i=0; i<rank; i++) {
1149 if (i == axis0_tmp) {
1150 ev_shape.push_back(s[axis1_tmp]);
1151 } else if (i == axis1_tmp) {
1152 ev_shape.push_back(s[axis0_tmp]);
1153 } else {
1154 ev_shape.push_back(s[i]);
1155 }
1156 }
1157 Data ev(0.,ev_shape,getFunctionSpace());
1158 ev.typeMatchRight(*this);
1159 m_data->swapaxes(ev.m_data.get(), axis0_tmp, axis1_tmp);
1160 return ev;
1161
1162 }
1163
1164 Data
1165 Data::symmetric() const
1166 {
1167 // check input
1168 DataArrayView::ShapeType s=getDataPointShape();
1169 if (getDataPointRank()==2) {
1170 if(s[0] != s[1])
1171 throw DataException("Error - Data::symmetric can only be calculated for rank 2 object with equal first and second dimension.");
1172 }
1173 else if (getDataPointRank()==4) {
1174 if(!(s[0] == s[2] && s[1] == s[3]))
1175 throw DataException("Error - Data::symmetric can only be calculated for rank 4 object with dim0==dim2 and dim1==dim3.");
1176 }
1177 else {
1178 throw DataException("Error - Data::symmetric can only be calculated for rank 2 or 4 object.");
1179 }
1180 Data ev(0.,getDataPointShape(),getFunctionSpace());
1181 ev.typeMatchRight(*this);
1182 m_data->symmetric(ev.m_data.get());
1183 return ev;
1184 }
1185
1186 Data
1187 Data::nonsymmetric() const
1188 {
1189 // check input
1190 DataArrayView::ShapeType s=getDataPointShape();
1191 if (getDataPointRank()==2) {
1192 if(s[0] != s[1])
1193 throw DataException("Error - Data::nonsymmetric can only be calculated for rank 2 object with equal first and second dimension.");
1194 DataArrayView::ShapeType ev_shape;
1195 ev_shape.push_back(s[0]);
1196 ev_shape.push_back(s[1]);
1197 Data ev(0.,ev_shape,getFunctionSpace());
1198 ev.typeMatchRight(*this);
1199 m_data->nonsymmetric(ev.m_data.get());
1200 return ev;
1201 }
1202 else if (getDataPointRank()==4) {
1203 if(!(s[0] == s[2] && s[1] == s[3]))
1204 throw DataException("Error - Data::nonsymmetric can only be calculated for rank 4 object with dim0==dim2 and dim1==dim3.");
1205 DataArrayView::ShapeType ev_shape;
1206 ev_shape.push_back(s[0]);
1207 ev_shape.push_back(s[1]);
1208 ev_shape.push_back(s[2]);
1209 ev_shape.push_back(s[3]);
1210 Data ev(0.,ev_shape,getFunctionSpace());
1211 ev.typeMatchRight(*this);
1212 m_data->nonsymmetric(ev.m_data.get());
1213 return ev;
1214 }
1215 else {
1216 throw DataException("Error - Data::nonsymmetric can only be calculated for rank 2 or 4 object.");
1217 }
1218 }
1219
1220 Data
1221 Data::trace(int axis_offset) const
1222 {
1223 DataArrayView::ShapeType s=getDataPointShape();
1224 if (getDataPointRank()==2) {
1225 DataArrayView::ShapeType ev_shape;
1226 Data ev(0.,ev_shape,getFunctionSpace());
1227 ev.typeMatchRight(*this);
1228 m_data->trace(ev.m_data.get(), axis_offset);
1229 return ev;
1230 }
1231 if (getDataPointRank()==3) {
1232 DataArrayView::ShapeType ev_shape;
1233 if (axis_offset==0) {
1234 int s2=s[2];
1235 ev_shape.push_back(s2);
1236 }
1237 else if (axis_offset==1) {
1238 int s0=s[0];
1239 ev_shape.push_back(s0);
1240 }
1241 Data ev(0.,ev_shape,getFunctionSpace());
1242 ev.typeMatchRight(*this);
1243 m_data->trace(ev.m_data.get(), axis_offset);
1244 return ev;
1245 }
1246 if (getDataPointRank()==4) {
1247 DataArrayView::ShapeType ev_shape;
1248 if (axis_offset==0) {
1249 ev_shape.push_back(s[2]);
1250 ev_shape.push_back(s[3]);
1251 }
1252 else if (axis_offset==1) {
1253 ev_shape.push_back(s[0]);
1254 ev_shape.push_back(s[3]);
1255 }
1256 else if (axis_offset==2) {
1257 ev_shape.push_back(s[0]);
1258 ev_shape.push_back(s[1]);
1259 }
1260 Data ev(0.,ev_shape,getFunctionSpace());
1261 ev.typeMatchRight(*this);
1262 m_data->trace(ev.m_data.get(), axis_offset);
1263 return ev;
1264 }
1265 else {
1266 throw DataException("Error - Data::trace can only be calculated for rank 2, 3 or 4 object.");
1267 }
1268 }
1269
1270 Data
1271 Data::transpose(int axis_offset) const
1272 {
1273 DataArrayView::ShapeType s=getDataPointShape();
1274 DataArrayView::ShapeType ev_shape;
1275 // Here's the equivalent of python s_out=s[axis_offset:]+s[:axis_offset]
1276 // which goes thru all shape vector elements starting with axis_offset (at index=rank wrap around to 0)
1277 int rank=getDataPointRank();
1278 if (axis_offset<0 || axis_offset>rank) {
1279 throw DataException("Error - Data::transpose must have 0 <= axis_offset <= rank=" + rank);
1280 }
1281 for (int i=0; i<rank; i++) {
1282 int index = (axis_offset+i)%rank;
1283 ev_shape.push_back(s[index]); // Append to new shape
1284 }
1285 Data ev(0.,ev_shape,getFunctionSpace());
1286 ev.typeMatchRight(*this);
1287 m_data->transpose(ev.m_data.get(), axis_offset);
1288 return ev;
1289 }
1290
1291 Data
1292 Data::eigenvalues() const
1293 {
1294 // check input
1295 DataArrayView::ShapeType s=getDataPointShape();
1296 if (getDataPointRank()!=2)
1297 throw DataException("Error - Data::eigenvalues can only be calculated for rank 2 object.");
1298 if(s[0] != s[1])
1299 throw DataException("Error - Data::eigenvalues can only be calculated for object with equal first and second dimension.");
1300 // create return
1301 DataArrayView::ShapeType ev_shape(1,s[0]);
1302 Data ev(0.,ev_shape,getFunctionSpace());
1303 ev.typeMatchRight(*this);
1304 m_data->eigenvalues(ev.m_data.get());
1305 return ev;
1306 }
1307
1308 const boost::python::tuple
1309 Data::eigenvalues_and_eigenvectors(const double tol) const
1310 {
1311 DataArrayView::ShapeType s=getDataPointShape();
1312 if (getDataPointRank()!=2)
1313 throw DataException("Error - Data::eigenvalues and eigenvectors can only be calculated for rank 2 object.");
1314 if(s[0] != s[1])
1315 throw DataException("Error - Data::eigenvalues and eigenvectors can only be calculated for object with equal first and second dimension.");
1316 // create return
1317 DataArrayView::ShapeType ev_shape(1,s[0]);
1318 Data ev(0.,ev_shape,getFunctionSpace());
1319 ev.typeMatchRight(*this);
1320 DataArrayView::ShapeType V_shape(2,s[0]);
1321 Data V(0.,V_shape,getFunctionSpace());
1322 V.typeMatchRight(*this);
1323 m_data->eigenvalues_and_eigenvectors(ev.m_data.get(),V.m_data.get(),tol);
1324 return make_tuple(boost::python::object(ev),boost::python::object(V));
1325 }
1326
1327 const boost::python::tuple
1328 Data::minGlobalDataPoint() const
1329 {
1330 // NB: calc_minGlobalDataPoint( had to be split off from minGlobalDataPoint( as boost::make_tuple causes an
1331 // abort (for unknown reasons) if there are openmp directives with it in the
1332 // surrounding function
1333
1334 int DataPointNo;
1335 int ProcNo;
1336 calc_minGlobalDataPoint(ProcNo,DataPointNo);
1337 return make_tuple(ProcNo,DataPointNo);
1338 }
1339
1340 void
1341 Data::calc_minGlobalDataPoint(int& ProcNo,
1342 int& DataPointNo) const
1343 {
1344 int i,j;
1345 int lowi=0,lowj=0;
1346 double min=numeric_limits<double>::max();
1347
1348 Data temp=minval();
1349
1350 int numSamples=temp.getNumSamples();
1351 int numDPPSample=temp.getNumDataPointsPerSample();
1352
1353 double next,local_min;
1354 int local_lowi,local_lowj;
1355
1356 #pragma omp parallel private(next,local_min,local_lowi,local_lowj)
1357 {
1358 local_min=min;
1359 #pragma omp for private(i,j) schedule(static)
1360 for (i=0; i<numSamples; i++) {
1361 for (j=0; j<numDPPSample; j++) {
1362 next=temp.getDataPoint(i,j)();
1363 if (next<local_min) {
1364 local_min=next;
1365 local_lowi=i;
1366 local_lowj=j;
1367 }
1368 }
1369 }
1370 #pragma omp critical
1371 if (local_min<min) {
1372 min=local_min;
1373 lowi=local_lowi;
1374 lowj=local_lowj;
1375 }
1376 }
1377
1378 #ifdef PASO_MPI
1379 // determine the processor on which the minimum occurs
1380 next = temp.getDataPoint(lowi,lowj)();
1381 int lowProc = 0;
1382 double *globalMins = new double[get_MPISize()+1];
1383 int error = MPI_Gather ( &next, 1, MPI_DOUBLE, globalMins, 1, MPI_DOUBLE, 0, get_MPIComm() );
1384
1385 if( get_MPIRank()==0 ){
1386 next = globalMins[lowProc];
1387 for( i=1; i<get_MPISize(); i++ )
1388 if( next>globalMins[i] ){
1389 lowProc = i;
1390 next = globalMins[i];
1391 }
1392 }
1393 MPI_Bcast( &lowProc, 1, MPI_DOUBLE, 0, get_MPIComm() );
1394
1395 delete [] globalMins;
1396 ProcNo = lowProc;
1397 #else
1398 ProcNo = 0;
1399 #endif
1400 DataPointNo = lowj + lowi * numDPPSample;
1401 }
1402
1403 void
1404 Data::saveDX(std::string fileName) const
1405 {
1406 boost::python::dict args;
1407 args["data"]=boost::python::object(this);
1408 getDomain().saveDX(fileName,args);
1409 return;
1410 }
1411
1412 void
1413 Data::saveVTK(std::string fileName) const
1414 {
1415 boost::python::dict args;
1416 args["data"]=boost::python::object(this);
1417 getDomain().saveVTK(fileName,args);
1418 return;
1419 }
1420
1421 Data&
1422 Data::operator+=(const Data& right)
1423 {
1424 if (isProtected()) {
1425 throw DataException("Error - attempt to update protected Data object.");
1426 }
1427 binaryOp(right,plus<double>());
1428 return (*this);
1429 }
1430
1431 Data&
1432 Data::operator+=(const boost::python::object& right)
1433 {
1434 Data tmp(right,getFunctionSpace(),false);
1435 binaryOp(tmp,plus<double>());
1436 return (*this);
1437 }
1438 Data&
1439 Data::operator=(const Data& other)
1440 {
1441 copy(other);
1442 return (*this);
1443 }
1444
1445 Data&
1446 Data::operator-=(const Data& right)
1447 {
1448 if (isProtected()) {
1449 throw DataException("Error - attempt to update protected Data object.");
1450 }
1451 binaryOp(right,minus<double>());
1452 return (*this);
1453 }
1454
1455 Data&
1456 Data::operator-=(const boost::python::object& right)
1457 {
1458 Data tmp(right,getFunctionSpace(),false);
1459 binaryOp(tmp,minus<double>());
1460 return (*this);
1461 }
1462
1463 Data&
1464 Data::operator*=(const Data& right)
1465 {
1466 if (isProtected()) {
1467 throw DataException("Error - attempt to update protected Data object.");
1468 }
1469 binaryOp(right,multiplies<double>());
1470 return (*this);
1471 }
1472
1473 Data&
1474 Data::operator*=(const boost::python::object& right)
1475 {
1476 Data tmp(right,getFunctionSpace(),false);
1477 binaryOp(tmp,multiplies<double>());
1478 return (*this);
1479 }
1480
1481 Data&
1482 Data::operator/=(const Data& right)
1483 {
1484 if (isProtected()) {
1485 throw DataException("Error - attempt to update protected Data object.");
1486 }
1487 binaryOp(right,divides<double>());
1488 return (*this);
1489 }
1490
1491 Data&
1492 Data::operator/=(const boost::python::object& right)
1493 {
1494 Data tmp(right,getFunctionSpace(),false);
1495 binaryOp(tmp,divides<double>());
1496 return (*this);
1497 }
1498
1499 Data
1500 Data::rpowO(const boost::python::object& left) const
1501 {
1502 Data left_d(left,*this);
1503 return left_d.powD(*this);
1504 }
1505
1506 Data
1507 Data::powO(const boost::python::object& right) const
1508 {
1509 Data tmp(right,getFunctionSpace(),false);
1510 return powD(tmp);
1511 }
1512
1513 /* Data */
1514 /* Data::powD(const Data& right) const */
1515 /* { */
1516 /* Data result; */
1517 /* if (getDataPointRank()<right.getDataPointRank()) { */
1518 /* result.copy(right); */
1519 /* result.binaryOp(*this,escript::rpow); */
1520 /* } else { */
1521 /* result.copy(*this); */
1522 /* result.binaryOp(right,(Data::BinaryDFunPtr)::pow); */
1523 /* } */
1524 /* return result; */
1525 /* } */
1526
1527 Data
1528 Data::powD(const Data& right) const
1529 {
1530 return C_TensorBinaryOperation(*this, right, ::pow);
1531 }
1532
1533 //
1534 // NOTE: It is essential to specify the namespace this operator belongs to
1535 Data
1536 escript::operator+(const Data& left, const Data& right)
1537 {
1538 return C_TensorBinaryOperation(left, right, plus<double>());
1539 }
1540
1541 //
1542 // NOTE: It is essential to specify the namespace this operator belongs to
1543 Data
1544 escript::operator-(const Data& left, const Data& right)
1545 {
1546 return C_TensorBinaryOperation(left, right, minus<double>());
1547 }
1548
1549 //
1550 // NOTE: It is essential to specify the namespace this operator belongs to
1551 Data
1552 escript::operator*(const Data& left, const Data& right)
1553 {
1554 return C_TensorBinaryOperation(left, right, multiplies<double>());
1555 }
1556
1557 //
1558 // NOTE: It is essential to specify the namespace this operator belongs to
1559 Data
1560 escript::operator/(const Data& left, const Data& right)
1561 {
1562 return C_TensorBinaryOperation(left, right, divides<double>());
1563 }
1564
1565 //
1566 // NOTE: It is essential to specify the namespace this operator belongs to
1567 Data
1568 escript::operator+(const Data& left, const boost::python::object& right)
1569 {
1570 return left+Data(right,left.getFunctionSpace(),false);
1571 }
1572
1573 //
1574 // NOTE: It is essential to specify the namespace this operator belongs to
1575 Data
1576 escript::operator-(const Data& left, const boost::python::object& right)
1577 {
1578 return left-Data(right,left.getFunctionSpace(),false);
1579 }
1580
1581 //
1582 // NOTE: It is essential to specify the namespace this operator belongs to
1583 Data
1584 escript::operator*(const Data& left, const boost::python::object& right)
1585 {
1586 return left*Data(right,left.getFunctionSpace(),false);
1587 }
1588
1589 //
1590 // NOTE: It is essential to specify the namespace this operator belongs to
1591 Data
1592 escript::operator/(const Data& left, const boost::python::object& right)
1593 {
1594 return left/Data(right,left.getFunctionSpace(),false);
1595 }
1596
1597 //
1598 // NOTE: It is essential to specify the namespace this operator belongs to
1599 Data
1600 escript::operator+(const boost::python::object& left, const Data& right)
1601 {
1602 return Data(left,right.getFunctionSpace(),false)+right;
1603 }
1604
1605 //
1606 // NOTE: It is essential to specify the namespace this operator belongs to
1607 Data
1608 escript::operator-(const boost::python::object& left, const Data& right)
1609 {
1610 return Data(left,right.getFunctionSpace(),false)-right;
1611 }
1612
1613 //
1614 // NOTE: It is essential to specify the namespace this operator belongs to
1615 Data
1616 escript::operator*(const boost::python::object& left, const Data& right)
1617 {
1618 return Data(left,right.getFunctionSpace(),false)*right;
1619 }
1620
1621 //
1622 // NOTE: It is essential to specify the namespace this operator belongs to
1623 Data
1624 escript::operator/(const boost::python::object& left, const Data& right)
1625 {
1626 return Data(left,right.getFunctionSpace(),false)/right;
1627 }
1628
1629 //
1630 //bool escript::operator==(const Data& left, const Data& right)
1631 //{
1632 // /*
1633 // NB: this operator does very little at this point, and isn't to
1634 // be relied on. Requires further implementation.
1635 // */
1636 //
1637 // bool ret;
1638 //
1639 // if (left.isEmpty()) {
1640 // if(!right.isEmpty()) {
1641 // ret = false;
1642 // } else {
1643 // ret = true;
1644 // }
1645 // }
1646 //
1647 // if (left.isConstant()) {
1648 // if(!right.isConstant()) {
1649 // ret = false;
1650 // } else {
1651 // ret = true;
1652 // }
1653 // }
1654 //
1655 // if (left.isTagged()) {
1656 // if(!right.isTagged()) {
1657 // ret = false;
1658 // } else {
1659 // ret = true;
1660 // }
1661 // }
1662 //
1663 // if (left.isExpanded()) {
1664 // if(!right.isExpanded()) {
1665 // ret = false;
1666 // } else {
1667 // ret = true;
1668 // }
1669 // }
1670 //
1671 // return ret;
1672 //}
1673
1674 /* TODO */
1675 /* global reduction */
1676 Data
1677 Data::getItem(const boost::python::object& key) const
1678 {
1679 const DataArrayView& view=getPointDataView();
1680
1681 DataArrayView::RegionType slice_region=view.getSliceRegion(key);
1682
1683 if (slice_region.size()!=view.getRank()) {
1684 throw DataException("Error - slice size does not match Data rank.");
1685 }
1686
1687 return getSlice(slice_region);
1688 }
1689
1690 /* TODO */
1691 /* global reduction */
1692 Data
1693 Data::getSlice(const DataArrayView::RegionType& region) const
1694 {
1695 return Data(*this,region);
1696 }
1697
1698 /* TODO */
1699 /* global reduction */
1700 void
1701 Data::setItemO(const boost::python::object& key,
1702 const boost::python::object& value)
1703 {
1704 Data tempData(value,getFunctionSpace());
1705 setItemD(key,tempData);
1706 }
1707
1708 void
1709 Data::setItemD(const boost::python::object& key,
1710 const Data& value)
1711 {
1712 const DataArrayView& view=getPointDataView();
1713
1714 DataArrayView::RegionType slice_region=view.getSliceRegion(key);
1715 if (slice_region.size()!=view.getRank()) {
1716 throw DataException("Error - slice size does not match Data rank.");
1717 }
1718 if (getFunctionSpace()!=value.getFunctionSpace()) {
1719 setSlice(Data(value,getFunctionSpace()),slice_region);
1720 } else {
1721 setSlice(value,slice_region);
1722 }
1723 }
1724
1725 void
1726 Data::setSlice(const Data& value,
1727 const DataArrayView::RegionType& region)
1728 {
1729 if (isProtected()) {
1730 throw DataException("Error - attempt to update protected Data object.");
1731 }
1732 Data tempValue(value);
1733 typeMatchLeft(tempValue);
1734 typeMatchRight(tempValue);
1735 m_data->setSlice(tempValue.m_data.get(),region);
1736 }
1737
1738 void
1739 Data::typeMatchLeft(Data& right) const
1740 {
1741 if (isExpanded()){
1742 right.expand();
1743 } else if (isTagged()) {
1744 if (right.isConstant()) {
1745 right.tag();
1746 }
1747 }
1748 }
1749
1750 void
1751 Data::typeMatchRight(const Data& right)
1752 {
1753 if (isTagged()) {
1754 if (right.isExpanded()) {
1755 expand();
1756 }
1757 } else if (isConstant()) {
1758 if (right.isExpanded()) {
1759 expand();
1760 } else if (right.isTagged()) {
1761 tag();
1762 }
1763 }
1764 }
1765
1766 void
1767 Data::setTaggedValueByName(std::string name,
1768 const boost::python::object& value)
1769 {
1770 if (getFunctionSpace().getDomain().isValidTagName(name)) {
1771 int tagKey=getFunctionSpace().getDomain().getTag(name);
1772 setTaggedValue(tagKey,value);
1773 }
1774 }
1775 void
1776 Data::setTaggedValue(int tagKey,
1777 const boost::python::object& value)
1778 {
1779 if (isProtected()) {
1780 throw DataException("Error - attempt to update protected Data object.");
1781 }
1782 //
1783 // Ensure underlying data object is of type DataTagged
1784 tag();
1785
1786 if (!isTagged()) {
1787 throw DataException("Error - DataTagged conversion failed!!");
1788 }
1789
1790 numeric::array asNumArray(value);
1791
1792
1793 // extract the shape of the numarray
1794 DataArrayView::ShapeType tempShape;
1795 for (int i=0; i < asNumArray.getrank(); i++) {
1796 tempShape.push_back(extract<int>(asNumArray.getshape()[i]));
1797 }
1798
1799 // get the space for the data vector
1800 int len = DataArrayView::noValues(tempShape);
1801 DataVector temp_data(len, 0.0, len);
1802 DataArrayView temp_dataView(temp_data, tempShape);
1803 temp_dataView.copy(asNumArray);
1804
1805 //
1806 // Call DataAbstract::setTaggedValue
1807 m_data->setTaggedValue(tagKey,temp_dataView);
1808 }
1809
1810 void
1811 Data::setTaggedValueFromCPP(int tagKey,
1812 const DataArrayView& value)
1813 {
1814 if (isProtected()) {
1815 throw DataException("Error - attempt to update protected Data object.");
1816 }
1817 //
1818 // Ensure underlying data object is of type DataTagged
1819 tag();
1820
1821 if (!isTagged()) {
1822 throw DataException("Error - DataTagged conversion failed!!");
1823 }
1824
1825 //
1826 // Call DataAbstract::setTaggedValue
1827 m_data->setTaggedValue(tagKey,value);
1828 }
1829
1830 int
1831 Data::getTagNumber(int dpno)
1832 {
1833 return m_data->getTagNumber(dpno);
1834 }
1835
1836 void
1837 Data::archiveData(const std::string fileName)
1838 {
1839 cout << "Archiving Data object to: " << fileName << endl;
1840
1841 //
1842 // Determine type of this Data object
1843 int dataType = -1;
1844
1845 if (isEmpty()) {
1846 dataType = 0;
1847 cout << "\tdataType: DataEmpty" << endl;
1848 }
1849 if (isConstant()) {
1850 dataType = 1;
1851 cout << "\tdataType: DataConstant" << endl;
1852 }
1853 if (isTagged()) {
1854 dataType = 2;
1855 cout << "\tdataType: DataTagged" << endl;
1856 }
1857 if (isExpanded()) {
1858 dataType = 3;
1859 cout << "\tdataType: DataExpanded" << endl;
1860 }
1861
1862 if (dataType == -1) {
1863 throw DataException("archiveData Error: undefined dataType");
1864 }
1865
1866 //
1867 // Collect data items common to all Data types
1868 int noSamples = getNumSamples();
1869 int noDPPSample = getNumDataPointsPerSample();
1870 int functionSpaceType = getFunctionSpace().getTypeCode();
1871 int dataPointRank = getDataPointRank();
1872 int dataPointSize = getDataPointSize();
1873 int dataLength = getLength();
1874 DataArrayView::ShapeType dataPointShape = getDataPointShape();
1875 vector<int> referenceNumbers(noSamples);
1876 for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
1877 referenceNumbers[sampleNo] = getFunctionSpace().getReferenceIDOfSample(sampleNo);
1878 }
1879 vector<int> tagNumbers(noSamples);
1880 if (isTagged()) {
1881 for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
1882 tagNumbers[sampleNo] = getFunctionSpace().getTagFromSampleNo(sampleNo);
1883 }
1884 }
1885
1886 cout << "\tnoSamples: " << noSamples << " noDPPSample: " << noDPPSample << endl;
1887 cout << "\tfunctionSpaceType: " << functionSpaceType << endl;
1888 cout << "\trank: " << dataPointRank << " size: " << dataPointSize << " length: " << dataLength << endl;
1889
1890 //
1891 // Flatten Shape to an array of integers suitable for writing to file
1892 int flatShape[4] = {0,0,0,0};
1893 cout << "\tshape: < ";
1894 for (int dim=0; dim<dataPointRank; dim++) {
1895 flatShape[dim] = dataPointShape[dim];
1896 cout << dataPointShape[dim] << " ";
1897 }
1898 cout << ">" << endl;
1899
1900 //
1901 // Open archive file
1902 ofstream archiveFile;
1903 archiveFile.open(fileName.data(), ios::out);
1904
1905 if (!archiveFile.good()) {
1906 throw DataException("archiveData Error: problem opening archive file");
1907 }
1908
1909 //
1910 // Write common data items to archive file
1911 archiveFile.write(reinterpret_cast<char *>(&dataType),sizeof(int));
1912 archiveFile.write(reinterpret_cast<char *>(&noSamples),sizeof(int));
1913 archiveFile.write(reinterpret_cast<char *>(&noDPPSample),sizeof(int));
1914 archiveFile.write(reinterpret_cast<char *>(&functionSpaceType),sizeof(int));
1915 archiveFile.write(reinterpret_cast<char *>(&dataPointRank),sizeof(int));
1916 archiveFile.write(reinterpret_cast<char *>(&dataPointSize),sizeof(int));
1917 archiveFile.write(reinterpret_cast<char *>(&dataLength),sizeof(int));
1918 for (int dim = 0; dim < 4; dim++) {
1919 archiveFile.write(reinterpret_cast<char *>(&flatShape[dim]),sizeof(int));
1920 }
1921 for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
1922 archiveFile.write(reinterpret_cast<char *>(&referenceNumbers[sampleNo]),sizeof(int));
1923 }
1924 if (isTagged()) {
1925 for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
1926 archiveFile.write(reinterpret_cast<char *>(&tagNumbers[sampleNo]),sizeof(int));
1927 }
1928 }
1929
1930 if (!archiveFile.good()) {
1931 throw DataException("archiveData Error: problem writing to archive file");
1932 }
1933
1934 //
1935 // Archive underlying data values for each Data type
1936 int noValues;
1937 switch (dataType) {
1938 case 0:
1939 // DataEmpty
1940 noValues = 0;
1941 archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));
1942 cout << "\tnoValues: " << noValues << endl;
1943 break;
1944 case 1:
1945 // DataConstant
1946 noValues = m_data->getLength();
1947 archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));
1948 cout << "\tnoValues: " << noValues << endl;
1949 if (m_data->archiveData(archiveFile,noValues)) {
1950 throw DataException("archiveData Error: problem writing data to archive file");
1951 }
1952 break;
1953 case 2:
1954 // DataTagged
1955 noValues = m_data->getLength();
1956 archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));
1957 cout << "\tnoValues: " << noValues << endl;
1958 if (m_data->archiveData(archiveFile,noValues)) {
1959 throw DataException("archiveData Error: problem writing data to archive file");
1960 }
1961 break;
1962 case 3:
1963 // DataExpanded
1964 noValues = m_data->getLength();
1965 archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));
1966 cout << "\tnoValues: " << noValues << endl;
1967 if (m_data->archiveData(archiveFile,noValues)) {
1968 throw DataException("archiveData Error: problem writing data to archive file");
1969 }
1970 break;
1971 }
1972
1973 if (!archiveFile.good()) {
1974 throw DataException("archiveData Error: problem writing data to archive file");
1975 }
1976
1977 //
1978 // Close archive file
1979 archiveFile.close();
1980
1981 if (!archiveFile.good()) {
1982 throw DataException("archiveData Error: problem closing archive file");
1983 }
1984
1985 }
1986
1987 void
1988 Data::extractData(const std::string fileName,
1989 const FunctionSpace& fspace)
1990 {
1991 //
1992 // Can only extract Data to an object which is initially DataEmpty
1993 if (!isEmpty()) {
1994 throw DataException("extractData Error: can only extract to DataEmpty object");
1995 }
1996
1997 cout << "Extracting Data object from: " << fileName << endl;
1998
1999 int dataType;
2000 int noSamples;
2001 int noDPPSample;
2002 int functionSpaceType;
2003 int dataPointRank;
2004 int dataPointSize;
2005 int dataLength;
2006 DataArrayView::ShapeType dataPointShape;
2007 int flatShape[4];
2008
2009 //
2010 // Open the archive file
2011 ifstream archiveFile;
2012 archiveFile.open(fileName.data(), ios::in);
2013
2014 if (!archiveFile.good()) {
2015 throw DataException("extractData Error: problem opening archive file");
2016 }
2017
2018 //
2019 // Read common data items from archive file
2020 archiveFile.read(reinterpret_cast<char *>(&dataType),sizeof(int));
2021 archiveFile.read(reinterpret_cast<char *>(&noSamples),sizeof(int));
2022 archiveFile.read(reinterpret_cast<char *>(&noDPPSample),sizeof(int));
2023 archiveFile.read(reinterpret_cast<char *>(&functionSpaceType),sizeof(int));
2024 archiveFile.read(reinterpret_cast<char *>(&dataPointRank),sizeof(int));
2025 archiveFile.read(reinterpret_cast<char *>(&dataPointSize),sizeof(int));
2026 archiveFile.read(reinterpret_cast<char *>(&dataLength),sizeof(int));
2027 for (int dim = 0; dim < 4; dim++) {
2028 archiveFile.read(reinterpret_cast<char *>(&flatShape[dim]),sizeof(int));
2029 if (flatShape[dim]>0) {
2030 dataPointShape.push_back(flatShape[dim]);
2031 }
2032 }
2033 vector<int> referenceNumbers(noSamples);
2034 for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
2035 archiveFile.read(reinterpret_cast<char *>(&referenceNumbers[sampleNo]),sizeof(int));
2036 }
2037 vector<int> tagNumbers(noSamples);
2038 if (dataType==2) {
2039 for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
2040 archiveFile.read(reinterpret_cast<char *>(&tagNumbers[sampleNo]),sizeof(int));
2041 }
2042 }
2043
2044 if (!archiveFile.good()) {
2045 throw DataException("extractData Error: problem reading from archive file");
2046 }
2047
2048 //
2049 // Verify the values just read from the archive file
2050 switch (dataType) {
2051 case 0:
2052 cout << "\tdataType: DataEmpty" << endl;
2053 break;
2054 case 1:
2055 cout << "\tdataType: DataConstant" << endl;
2056 break;
2057 case 2:
2058 cout << "\tdataType: DataTagged" << endl;
2059 break;
2060 case 3:
2061 cout << "\tdataType: DataExpanded" << endl;
2062 break;
2063 default:
2064 throw DataException("extractData Error: undefined dataType read from archive file");
2065 break;
2066 }
2067
2068 cout << "\tnoSamples: " << noSamples << " noDPPSample: " << noDPPSample << endl;
2069 cout << "\tfunctionSpaceType: " << functionSpaceType << endl;
2070 cout << "\trank: " << dataPointRank << " size: " << dataPointSize << " length: " << dataLength << endl;
2071 cout << "\tshape: < ";
2072 for (int dim = 0; dim < dataPointRank; dim++) {
2073 cout << dataPointShape[dim] << " ";
2074 }
2075 cout << ">" << endl;
2076
2077 //
2078 // Verify that supplied FunctionSpace object is compatible with this Data object.
2079 if ( (fspace.getTypeCode()!=functionSpaceType) ||
2080 (fspace.getNumSamples()!=noSamples) ||
2081 (fspace.getNumDPPSample()!=noDPPSample)
2082 ) {
2083 throw DataException("extractData Error: incompatible FunctionSpace");
2084 }
2085 for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
2086 if (referenceNumbers[sampleNo] != fspace.getReferenceIDOfSample(sampleNo)) {
2087 throw DataException("extractData Error: incompatible FunctionSpace");
2088 }
2089 }
2090 if (dataType==2) {
2091 for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
2092 if (tagNumbers[sampleNo] != fspace.getTagFromSampleNo(sampleNo)) {
2093 throw DataException("extractData Error: incompatible FunctionSpace");
2094 }
2095 }
2096 }
2097
2098 //
2099 // Construct a DataVector to hold underlying data values
2100 DataVector dataVec(dataLength);
2101
2102 //
2103 // Load this DataVector with the appropriate values
2104 int noValues;
2105 archiveFile.read(reinterpret_cast<char *>(&noValues),sizeof(int));
2106 cout << "\tnoValues: " << noValues << endl;
2107 switch (dataType) {
2108 case 0:
2109 // DataEmpty
2110 if (noValues != 0) {
2111 throw DataException("extractData Error: problem reading data from archive file");
2112 }
2113 break;
2114 case 1:
2115 // DataConstant
2116 if (dataVec.extractData(archiveFile,noValues)) {
2117 throw DataException("extractData Error: problem reading data from archive file");
2118 }
2119 break;
2120 case 2:
2121 // DataTagged
2122 if (dataVec.extractData(archiveFile,noValues)) {
2123 throw DataException("extractData Error: problem reading data from archive file");
2124 }
2125 break;
2126 case 3:
2127 // DataExpanded
2128 if (dataVec.extractData(archiveFile,noValues)) {
2129 throw DataException("extractData Error: problem reading data from archive file");
2130 }
2131 break;
2132 }
2133
2134 if (!archiveFile.good()) {
2135 throw DataException("extractData Error: problem reading from archive file");
2136 }
2137
2138 //
2139 // Close archive file
2140 archiveFile.close();
2141
2142 if (!archiveFile.good()) {
2143 throw DataException("extractData Error: problem closing archive file");
2144 }
2145
2146 //
2147 // Construct an appropriate Data object
2148 DataAbstract* tempData;
2149 switch (dataType) {
2150 case 0:
2151 // DataEmpty
2152 tempData=new DataEmpty();
2153 break;
2154 case 1:
2155 // DataConstant
2156 tempData=new DataConstant(fspace,dataPointShape,dataVec);
2157 break;
2158 case 2:
2159 // DataTagged
2160 tempData=new DataTagged(fspace,dataPointShape,tagNumbers,dataVec);
2161 break;
2162 case 3:
2163 // DataExpanded
2164 tempData=new DataExpanded(fspace,dataPointShape,dataVec);
2165 break;
2166 }
2167 shared_ptr<DataAbstract> temp_data(tempData);
2168 m_data=temp_data;
2169 }
2170
2171 ostream& escript::operator<<(ostream& o, const Data& data)
2172 {
2173 o << data.toString();
2174 return o;
2175 }
2176
2177 Data
2178 escript::C_GeneralTensorProduct(Data& arg_0,
2179 Data& arg_1,
2180 int axis_offset,
2181 int transpose)
2182 {
2183 // General tensor product: res(SL x SR) = arg_0(SL x SM) * arg_1(SM x SR)
2184 // SM is the product of the last axis_offset entries in arg_0.getShape().
2185
2186 // Interpolate if necessary and find an appropriate function space
2187 Data arg_0_Z, arg_1_Z;
2188 if (arg_0.getFunctionSpace()!=arg_1.getFunctionSpace()) {
2189 if (arg_0.probeInterpolation(arg_1.getFunctionSpace())) {
2190 arg_0_Z = arg_0.interpolate(arg_1.getFunctionSpace());
2191 arg_1_Z = Data(arg_1);
2192 }
2193 else if (arg_1.probeInterpolation(arg_0.getFunctionSpace())) {
2194 arg_1_Z=arg_1.interpolate(arg_0.getFunctionSpace());
2195 arg_0_Z =Data(arg_0);
2196 }
2197 else {
2198 throw DataException("Error - C_GeneralTensorProduct: arguments have incompatible function spaces.");
2199 }
2200 } else {
2201 arg_0_Z = Data(arg_0);
2202 arg_1_Z = Data(arg_1);
2203 }
2204 // Get rank and shape of inputs
2205 int rank0 = arg_0_Z.getDataPointRank();
2206 int rank1 = arg_1_Z.getDataPointRank();
2207 DataArrayView::ShapeType shape0 = arg_0_Z.getDataPointShape();
2208 DataArrayView::ShapeType shape1 = arg_1_Z.getDataPointShape();
2209
2210 // Prepare for the loops of the product and verify compatibility of shapes
2211 int start0=0, start1=0;
2212 if (transpose == 0) {}
2213 else if (transpose == 1) { start0 = axis_offset; }
2214 else if (transpose == 2) { start1 = rank1-axis_offset; }
2215 else { throw DataException("C_GeneralTensorProduct: Error - transpose should be 0, 1 or 2"); }
2216
2217 // Adjust the shapes for transpose
2218 DataArrayView::ShapeType tmpShape0;
2219 DataArrayView::ShapeType tmpShape1;
2220 for (int i=0; i<rank0; i++) { tmpShape0.push_back( shape0[(i+start0)%rank0] ); }
2221 for (int i=0; i<rank1; i++) { tmpShape1.push_back( shape1[(i+start1)%rank1] ); }
2222
2223 #if 0
2224 // For debugging: show shape after transpose
2225 char tmp[100];
2226 std::string shapeStr;
2227 shapeStr = "(";
2228 for (int i=0; i<rank0; i++) { sprintf(tmp, "%d,", tmpShape0[i]); shapeStr += tmp; }
2229 shapeStr += ")";
2230 cout << "C_GeneralTensorProduct: Shape of arg0 is " << shapeStr << endl;
2231 shapeStr = "(";
2232 for (int i=0; i<rank1; i++) { sprintf(tmp, "%d,", tmpShape1[i]); shapeStr += tmp; }
2233 shapeStr += ")";
2234 cout << "C_GeneralTensorProduct: Shape of arg1 is " << shapeStr << endl;
2235 #endif
2236
2237 // Prepare for the loops of the product
2238 int SL=1, SM=1, SR=1;
2239 for (int i=0; i<rank0-axis_offset; i++) {
2240 SL *= tmpShape0[i];
2241 }
2242 for (int i=rank0-axis_offset; i<rank0; i++) {
2243 if (tmpShape0[i] != tmpShape1[i-(rank0-axis_offset)]) {
2244 throw DataException("C_GeneralTensorProduct: Error - incompatible shapes");
2245 }
2246 SM *= tmpShape0[i];
2247 }
2248 for (int i=axis_offset; i<rank1; i++) {
2249 SR *= tmpShape1[i];
2250 }
2251
2252 // Define the shape of the output
2253 DataArrayView::ShapeType shape2;
2254 for (int i=0; i<rank0-axis_offset; i++) { shape2.push_back(tmpShape0[i]); } // First part of arg_0_Z
2255 for (int i=axis_offset; i<rank1; i++) { shape2.push_back(tmpShape1[i]); } // Last part of arg_1_Z
2256
2257 // Declare output Data object
2258 Data res;
2259
2260 if (arg_0_Z.isConstant() && arg_1_Z.isConstant()) {
2261 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace()); // DataConstant output
2262 double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);
2263 double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);
2264 double *ptr_2 = &((res.getPointDataView().getData())[0]);
2265 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2266 }
2267 else if (arg_0_Z.isConstant() && arg_1_Z.isTagged()) {
2268
2269 // Prepare the DataConstant input
2270 DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());
2271 if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
2272
2273 // Borrow DataTagged input from Data object
2274 DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData());
2275 if (tmp_1==0) { throw DataException("GTP_1 Programming error - casting to DataTagged."); }
2276
2277 // Prepare a DataTagged output 2
2278 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace()); // DataTagged output
2279 res.tag();
2280 DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2281 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2282
2283 // Prepare offset into DataConstant
2284 int offset_0 = tmp_0->getPointOffset(0,0);
2285 double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);
2286 // Get the views
2287 DataArrayView view_1 = tmp_1->getDefaultValue();
2288 DataArrayView view_2 = tmp_2->getDefaultValue();
2289 // Get the pointers to the actual data
2290 double *ptr_1 = &((view_1.getData())[0]);
2291 double *ptr_2 = &((view_2.getData())[0]);
2292 // Compute an MVP for the default
2293 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2294 // Compute an MVP for each tag
2295 const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2296 DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2297 for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2298 tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());
2299 DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);
2300 DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);
2301 double *ptr_1 = &view_1.getData(0);
2302 double *ptr_2 = &view_2.getData(0);
2303 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2304 }
2305
2306 }
2307 else if (arg_0_Z.isConstant() && arg_1_Z.isExpanded()) {
2308
2309 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2310 DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());
2311 DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData());
2312 DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2313 if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
2314 if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2315 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2316 int sampleNo_1,dataPointNo_1;
2317 int numSamples_1 = arg_1_Z.getNumSamples();
2318 int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2319 int offset_0 = tmp_0->getPointOffset(0,0);
2320 #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2321 for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2322 for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2323 int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2324 int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2325 double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);
2326 double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);
2327 double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);
2328 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2329 }
2330 }
2331
2332 }
2333 else if (arg_0_Z.isTagged() && arg_1_Z.isConstant()) {
2334
2335 // Borrow DataTagged input from Data object
2336 DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2337 if (tmp_0==0) { throw DataException("GTP_0 Programming error - casting to DataTagged."); }
2338
2339 // Prepare the DataConstant input
2340 DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());
2341 if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
2342
2343 // Prepare a DataTagged output 2
2344 res = Data(0.0, shape2, arg_0_Z.getFunctionSpace()); // DataTagged output
2345 res.tag();
2346 DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2347 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2348
2349 // Prepare offset into DataConstant
2350 int offset_1 = tmp_1->getPointOffset(0,0);
2351 double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);
2352 // Get the views
2353 DataArrayView view_0 = tmp_0->getDefaultValue();
2354 DataArrayView view_2 = tmp_2->getDefaultValue();
2355 // Get the pointers to the actual data
2356 double *ptr_0 = &((view_0.getData())[0]);
2357 double *ptr_2 = &((view_2.getData())[0]);
2358 // Compute an MVP for the default
2359 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2360 // Compute an MVP for each tag
2361 const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2362 DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2363 for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2364 tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());
2365 DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);
2366 DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);
2367 double *ptr_0 = &view_0.getData(0);
2368 double *ptr_2 = &view_2.getData(0);
2369 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2370 }
2371
2372 }
2373 else if (arg_0_Z.isTagged() && arg_1_Z.isTagged()) {
2374
2375 // Borrow DataTagged input from Data object
2376 DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2377 if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2378
2379 // Borrow DataTagged input from Data object
2380 DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData());
2381 if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2382
2383 // Prepare a DataTagged output 2
2384 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace());
2385 res.tag(); // DataTagged output
2386 DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2387 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2388
2389 // Get the views
2390 DataArrayView view_0 = tmp_0->getDefaultValue();
2391 DataArrayView view_1 = tmp_1->getDefaultValue();
2392 DataArrayView view_2 = tmp_2->getDefaultValue();
2393 // Get the pointers to the actual data
2394 double *ptr_0 = &((view_0.getData())[0]);
2395 double *ptr_1 = &((view_1.getData())[0]);
2396 double *ptr_2 = &((view_2.getData())[0]);
2397 // Compute an MVP for the default
2398 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2399 // Merge the tags
2400 DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2401 const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2402 const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2403 for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2404 tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue()); // use tmp_2 to get correct shape
2405 }
2406 for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2407 tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());
2408 }
2409 // Compute an MVP for each tag
2410 const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2411 for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2412 DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);
2413 DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);
2414 DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);
2415 double *ptr_0 = &view_0.getData(0);
2416 double *ptr_1 = &view_1.getData(0);
2417 double *ptr_2 = &view_2.getData(0);
2418 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2419 }
2420
2421 }
2422 else if (arg_0_Z.isTagged() && arg_1_Z.isExpanded()) {
2423
2424 // After finding a common function space above the two inputs have the same numSamples and num DPPS
2425 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2426 DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2427 DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData());
2428 DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2429 if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2430 if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2431 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2432 int sampleNo_0,dataPointNo_0;
2433 int numSamples_0 = arg_0_Z.getNumSamples();
2434 int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2435 #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2436 for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2437 int offset_0 = tmp_0->getPointOffset(sampleNo_0,0); // They're all the same, so just use #0
2438 double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);
2439 for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2440 int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2441 int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2442 double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);
2443 double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);
2444 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2445 }
2446 }
2447
2448 }
2449 else if (arg_0_Z.isExpanded() && arg_1_Z.isConstant()) {
2450
2451 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2452 DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2453 DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());
2454 DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2455 if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2456 if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
2457 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2458 int sampleNo_0,dataPointNo_0;
2459 int numSamples_0 = arg_0_Z.getNumSamples();
2460 int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2461 int offset_1 = tmp_1->getPointOffset(0,0);
2462 #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2463 for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2464 for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2465 int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2466 int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2467 double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);
2468 double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);
2469 double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);
2470 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2471 }
2472 }
2473
2474
2475 }
2476 else if (arg_0_Z.isExpanded() && arg_1_Z.isTagged()) {
2477
2478 // After finding a common function space above the two inputs have the same numSamples and num DPPS
2479 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2480 DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2481 DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData());
2482 DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2483 if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2484 if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2485 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2486 int sampleNo_0,dataPointNo_0;
2487 int numSamples_0 = arg_0_Z.getNumSamples();
2488 int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2489 #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2490 for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2491 int offset_1 = tmp_1->getPointOffset(sampleNo_0,0);
2492 double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);
2493 for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2494 int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2495 int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2496 double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);
2497 double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);
2498 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2499 }
2500 }
2501
2502 }
2503 else if (arg_0_Z.isExpanded() && arg_1_Z.isExpanded()) {
2504
2505 // After finding a common function space above the two inputs have the same numSamples and num DPPS
2506 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2507 DataExpanded* tmp_0=dynamic_cast<DataExpanded*>(arg_0_Z.borrowData());
2508 DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData());
2509 DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2510 if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2511 if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2512 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2513 int sampleNo_0,dataPointNo_0;
2514 int numSamples_0 = arg_0_Z.getNumSamples();
2515 int numDataPointsPerSample_0 = arg_0_Z.getNumDataPointsPerSample();
2516 #pragma omp parallel for private(sampleNo_0,dataPointNo_0) schedule(static)
2517 for (sampleNo_0 = 0; sampleNo_0 < numSamples_0; sampleNo_0++) {
2518 for (dataPointNo_0 = 0; dataPointNo_0 < numDataPointsPerSample_0; dataPointNo_0++) {
2519 int offset_0 = tmp_0->getPointOffset(sampleNo_0,dataPointNo_0);
2520 int offset_1 = tmp_1->getPointOffset(sampleNo_0,dataPointNo_0);
2521 int offset_2 = tmp_2->getPointOffset(sampleNo_0,dataPointNo_0);
2522 double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);
2523 double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);
2524 double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);
2525 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2526 }
2527 }
2528
2529 }
2530 else {
2531 throw DataException("Error - C_GeneralTensorProduct: unknown combination of inputs");
2532 }
2533
2534 return res;
2535 }
2536
2537 DataAbstract*
2538 Data::borrowData() const
2539 {
2540 return m_data.get();
2541 }
2542
2543 /* Member functions specific to the MPI implementation */
2544
2545 void
2546 Data::print()
2547 {
2548 int i,j;
2549
2550 printf( "Data is %dX%d\n", getNumSamples(), getNumDataPointsPerSample() );
2551 for( i=0; i<getNumSamples(); i++ )
2552 {
2553 printf( "[%6d]", i );
2554 for( j=0; j<getNumDataPointsPerSample(); j++ )
2555 printf( "\t%10.7g", (getSampleData(i))[j] );
2556 printf( "\n" );
2557 }
2558 }
2559 void
2560 Data::dump(const std::string fileName) const
2561 {
2562 try
2563 {
2564 return m_data->dump(fileName);
2565 }
2566 catch (exception& e)
2567 {
2568 cout << e.what() << endl;
2569 }
2570 }
2571
2572 int
2573 Data::get_MPISize() const
2574 {
2575 int error, size;
2576 #ifdef PASO_MPI
2577 error = MPI_Comm_size( get_MPIComm(), &size );
2578 #else
2579 size = 1;
2580 #endif
2581 return size;
2582 }
2583
2584 int
2585 Data::get_MPIRank() const
2586 {
2587 int error, rank;
2588 #ifdef PASO_MPI
2589 error = MPI_Comm_rank( get_MPIComm(), &rank );
2590 #else
2591 rank = 0;
2592 #endif
2593 return rank;
2594 }
2595
2596 MPI_Comm
2597 Data::get_MPIComm() const
2598 {
2599 #ifdef PASO_MPI
2600 return MPI_COMM_WORLD;
2601 #else
2602 return -1;
2603 #endif
2604 }
2605

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