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

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Revision 1384 - (hide annotations)
Fri Jan 11 02:29:38 2008 UTC (11 years, 9 months ago) by phornby
Original Path: temp_trunk_copy/escript/src/Data.cpp
File size: 75852 byte(s)
Make a temp copy of the trunk before checking in the windows changes


1 jgs 480
2 ksteube 1312 /* $Id$ */
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 jgs 474 #include "Data.h"
17 jgs 94
18 jgs 480 #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 ksteube 1312 extern "C" {
27     #include "escript/blocktimer.h"
28     }
29 jgs 480
30 jgs 119 #include <fstream>
31 jgs 94 #include <algorithm>
32     #include <vector>
33     #include <functional>
34    
35 jgs 153 #include <boost/python/dict.hpp>
36 jgs 94 #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 jgs 102 shared_ptr<DataAbstract> temp_data(temp);
50     m_data=temp_data;
51 gross 783 m_protected=false;
52 jgs 94 }
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 matt 1319
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 gross 783 m_protected=false;
71 jgs 94 }
72    
73     Data::Data(double value,
74     const DataArrayView::ShapeType& dataPointShape,
75     const FunctionSpace& what,
76     bool expanded)
77     {
78 matt 1319 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 gross 783 m_protected=false;
86 jgs 94 }
87    
88 jgs 102 Data::Data(const Data& inData)
89 jgs 94 {
90 jgs 102 m_data=inData.m_data;
91 gross 783 m_protected=inData.isProtected();
92 jgs 94 }
93    
94     Data::Data(const Data& inData,
95     const DataArrayView::RegionType& region)
96     {
97     //
98 jgs 102 // 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 gross 783 m_protected=false;
103 jgs 94 }
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 jgs 123 // Note: Must use a reference or pointer to a derived object
113 jgs 94 // in order to get polymorphic behaviour. Shouldn't really
114     // be able to create an instance of AbstractDomain but that was done
115 jgs 123 // as a boost:python work around which may no longer be required.
116 jgs 94 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 gross 783 m_protected=false;
125 jgs 94 }
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 jgs 102 shared_ptr<DataAbstract> temp_data(temp);
135     m_data=temp_data;
136 gross 783 m_protected=false;
137 jgs 94 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 gross 783 m_protected=false;
148 jgs 94 }
149    
150     Data::Data(const DataArrayView& value,
151     const FunctionSpace& what,
152     bool expanded)
153     {
154     initialise(value,what,expanded);
155 gross 783 m_protected=false;
156 jgs 94 }
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 gross 783 m_protected=false;
165 jgs 94 }
166    
167 matt 1319
168 jgs 94 Data::Data(const object& value,
169     const Data& other)
170     {
171 matt 1319
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 jgs 94 //
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 matt 1319
191     if (temp_dataView.getRank()==0) {
192     int len = DataArrayView::noValues(other.getPointDataView().getShape());
193    
194     DataVector temp2_data(len, temp_dataView(), len);
195 matt 1328 DataArrayView temp2_dataView(temp2_data, other.getPointDataView().getShape());
196 matt 1319 initialise(temp2_dataView, other.getFunctionSpace(), false);
197    
198 jgs 94 } else {
199     //
200     // Create a DataConstant with the same sample shape as other
201 matt 1319 initialise(temp_dataView, other.getFunctionSpace(), false);
202 jgs 94 }
203 gross 783 m_protected=false;
204 jgs 94 }
205    
206 jgs 151 Data::~Data()
207     {
208    
209     }
210    
211 jgs 94 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 jgs 121 const boost::python::tuple
228 jgs 94 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 jgs 102 shared_ptr<DataAbstract> temp_data(newData);
258     m_data=temp_data;
259 jgs 94 return;
260     }
261     }
262     {
263     DataTagged* temp=dynamic_cast<DataTagged*>(other.m_data.get());
264     if (temp!=0) {
265     //
266 jgs 102 // Construct a DataTagged copy
267 jgs 94 DataAbstract* newData=new DataTagged(*temp);
268 jgs 102 shared_ptr<DataAbstract> temp_data(newData);
269     m_data=temp_data;
270 jgs 94 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 jgs 102 shared_ptr<DataAbstract> temp_data(newData);
280     m_data=temp_data;
281 jgs 94 return;
282     }
283     }
284 jgs 102 {
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 jgs 94 throw DataException("Error - Copy not implemented for this Data type.");
296     }
297    
298 gross 1118
299 jgs 94 void
300 gross 1118 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 jgs 94 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 ksteube 1312 Data::setProtection()
373     {
374 gross 783 m_protected=true;
375     }
376    
377     bool
378 ksteube 1312 Data::isProtected() const
379     {
380 gross 783 return m_protected;
381     }
382    
383    
384    
385     void
386 jgs 94 Data::expand()
387     {
388     if (isConstant()) {
389     DataConstant* tempDataConst=dynamic_cast<DataConstant*>(m_data.get());
390     DataAbstract* temp=new DataExpanded(*tempDataConst);
391 jgs 102 shared_ptr<DataAbstract> temp_data(temp);
392     m_data=temp_data;
393 jgs 94 } else if (isTagged()) {
394     DataTagged* tempDataTag=dynamic_cast<DataTagged*>(m_data.get());
395     DataAbstract* temp=new DataExpanded(*tempDataTag);
396 jgs 102 shared_ptr<DataAbstract> temp_data(temp);
397     m_data=temp_data;
398 jgs 94 } 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 jgs 102 shared_ptr<DataAbstract> temp_data(temp);
415     m_data=temp_data;
416 jgs 94 } 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 gross 854 Data
428     Data::oneOver() const
429 jgs 102 {
430 matt 1334 return C_TensorUnaryOperation(*this, bind1st(divides<double>(),1.));
431 jgs 102 }
432    
433 jgs 94 Data
434 gross 698 Data::wherePositive() const
435 jgs 94 {
436 matt 1334 return C_TensorUnaryOperation(*this, bind2nd(greater<double>(),0.0));
437 jgs 94 }
438    
439     Data
440 gross 698 Data::whereNegative() const
441 jgs 102 {
442 matt 1334 return C_TensorUnaryOperation(*this, bind2nd(less<double>(),0.0));
443 jgs 102 }
444    
445     Data
446 gross 698 Data::whereNonNegative() const
447 jgs 94 {
448 matt 1334 return C_TensorUnaryOperation(*this, bind2nd(greater_equal<double>(),0.0));
449 jgs 94 }
450    
451     Data
452 gross 698 Data::whereNonPositive() const
453 jgs 94 {
454 matt 1334 return C_TensorUnaryOperation(*this, bind2nd(less_equal<double>(),0.0));
455 jgs 94 }
456    
457     Data
458 jgs 571 Data::whereZero(double tol) const
459 jgs 94 {
460 jgs 571 Data dataAbs=abs();
461 matt 1334 return C_TensorUnaryOperation(dataAbs, bind2nd(less_equal<double>(),tol));
462 jgs 94 }
463    
464     Data
465 jgs 571 Data::whereNonZero(double tol) const
466 jgs 102 {
467 jgs 571 Data dataAbs=abs();
468 matt 1334 return C_TensorUnaryOperation(dataAbs, bind2nd(greater<double>(),tol));
469 jgs 102 }
470    
471     Data
472 jgs 94 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 matt 1353 double blocktimer_start = blocktimer_time();
496 jgs 94 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 matt 1353 blocktimer_increment("grad()", blocktimer_start);
503 jgs 94 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 gross 921
531    
532 ksteube 1312 const
533 jgs 121 boost::python::numeric::array
534 ksteube 1312 Data:: getValueOfDataPoint(int dataPointNo)
535 jgs 121 {
536 gross 921 size_t length=0;
537     int i, j, k, l;
538 jgs 121 //
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 gross 921 // 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 jgs 121
553     //
554     // resize the numeric array to the shape just calculated
555 gross 921 if (arrayRank==0) {
556     numArray.resize(1);
557     }
558 jgs 121 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 gross 921 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 trankine 924 if ((sampleNo >= getNumSamples()) || (sampleNo < 0 )) {
577 gross 921 throw DataException("Error - Data::convertToNumArray: invalid sampleNo.");
578     }
579 ksteube 1312
580 gross 921 //
581     // Check a valid data point number has been supplied
582 trankine 924 if ((dataPointNoInSample >= getNumDataPointsPerSample()) || (dataPointNoInSample < 0)) {
583 gross 921 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 ksteube 1312
589 gross 921 switch( dataPointRank ){
590     case 0 :
591     numArray[0] = dataPointView();
592     break;
593 ksteube 1312 case 1 :
594 gross 921 for( i=0; i<dataPointShape[0]; i++ )
595     numArray[i]=dataPointView(i);
596     break;
597 ksteube 1312 case 2 :
598 gross 921 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 ksteube 1312 case 3 :
603 gross 921 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 jgs 117 }
617     //
618 gross 921 // return the array
619 jgs 117 return numArray;
620 gross 921
621 jgs 117 }
622 gross 921 void
623 ksteube 1312 Data::setValueOfDataPointToPyObject(int dataPointNo, const boost::python::object& py_object)
624 jgs 121 {
625 gross 1034 // 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 gross 921 if (isProtected()) {
636     throw DataException("Error - attempt to update protected Data object.");
637     }
638     //
639     // check rank
640 ksteube 1312 if (num_array.getrank()<getDataPointRank())
641 gross 921 throw DataException("Rank of numarray does not match Data object rank");
642 bcumming 790
643 jgs 121 //
644 gross 921 // 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 jgs 121 }
649     //
650 gross 921 // make sure data is expanded:
651     if (!isExpanded()) {
652     expand();
653 jgs 121 }
654 gross 921 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 jgs 121
663 gross 922 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 ksteube 1312 const
684 gross 921 boost::python::numeric::array
685 ksteube 1312 Data::getValueOfGlobalDataPoint(int procNo, int dataPointNo)
686 gross 921 {
687     size_t length=0;
688     int i, j, k, l, pos;
689 jgs 121 //
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 gross 921 // 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 bcumming 790
727 jgs 121 //
728     // load the values for the data point into the numeric array.
729 bcumming 790
730     // updated for the MPI case
731     if( get_MPIRank()==procNo ){
732 gross 921 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 trankine 924 if ((sampleNo >= getNumSamples()) || (sampleNo < 0 )) {
738 gross 921 throw DataException("Error - Data::convertToNumArray: invalid sampleNo.");
739     }
740 ksteube 1312
741 gross 921 //
742     // Check a valid data point number has been supplied
743 trankine 924 if ((dataPointNoInSample >= getNumDataPointsPerSample()) || (dataPointNoInSample < 0)) {
744 gross 921 throw DataException("Error - Data::convertToNumArray: invalid dataPointNoInSample.");
745     }
746     // TODO: global error handling
747 bcumming 790 // create a view of the data if it is stored locally
748 gross 921 DataArrayView dataPointView = getDataPoint(sampleNo, dataPointNoInSample);
749 ksteube 1312
750 bcumming 790 // 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 ksteube 1312 case 1 :
757 bcumming 790 for( i=0; i<dataPointShape[0]; i++ )
758     tmpData[i]=dataPointView(i);
759     break;
760 ksteube 1312 case 2 :
761 bcumming 790 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 ksteube 1312 case 3 :
766 bcumming 790 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 gross 921 }
780 bcumming 790 }
781 ksteube 1312 #ifdef PASO_MPI
782 gross 921 // broadcast the data to all other processes
783     MPI_Bcast( tmpData, length, MPI_DOUBLE, procNo, get_MPIComm() );
784     #endif
785 bcumming 790
786     // unpack the data
787     switch( dataPointRank ){
788     case 0 :
789 gross 921 numArray[0]=tmpData[0];
790 bcumming 790 break;
791 ksteube 1312 case 1 :
792 bcumming 790 for( i=0; i<dataPointShape[0]; i++ )
793     numArray[i]=tmpData[i];
794     break;
795 ksteube 1312 case 2 :
796 bcumming 790 for( i=0; i<dataPointShape[0]; i++ )
797     for( j=0; j<dataPointShape[1]; j++ )
798 gross 921 numArray[make_tuple(i,j)]=tmpData[i+j*dataPointShape[0]];
799 bcumming 790 break;
800 ksteube 1312 case 3 :
801 bcumming 790 for( i=0; i<dataPointShape[0]; i++ )
802     for( j=0; j<dataPointShape[1]; j++ )
803     for( k=0; k<dataPointShape[2]; k++ )
804 gross 921 numArray[make_tuple(i,j,k)]=tmpData[i+dataPointShape[0]*(j*+k*dataPointShape[1])];
805 bcumming 790 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 gross 921 numArray[make_tuple(i,j,k,l)]=tmpData[i+dataPointShape[0]*(j*+dataPointShape[1]*(k+l*dataPointShape[2]))];
812 bcumming 790 break;
813     }
814    
815 ksteube 1312 delete [] tmpData;
816 jgs 121 //
817     // return the loaded array
818     return numArray;
819     }
820    
821 gross 921
822    
823 jgs 121 boost::python::numeric::array
824 jgs 94 Data::integrate() const
825     {
826     int index;
827     int rank = getDataPointRank();
828     DataArrayView::ShapeType shape = getDataPointShape();
829 ksteube 1312 int dataPointSize = getDataPointSize();
830 jgs 94
831     //
832     // calculate the integral values
833 ksteube 1312 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 jgs 94 AbstractContinuousDomain::asAbstractContinuousDomain(getDomain()).setToIntegrals(integrals,*this);
847 ksteube 1312 #endif
848 jgs 94
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 jgs 108 bp_array.resize(1);
855 jgs 94 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 gross 436 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 jgs 94 }
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 gross 436 bp_array[make_tuple(i,j,k)] = integrals[index];
881 jgs 94 }
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 gross 436 bp_array[make_tuple(i,j,k,l)] = integrals[index];
893 jgs 94 }
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 matt 1349 return C_TensorUnaryOperation<double (*)(double)>(*this, ::sin);
908 jgs 94 }
909    
910     Data
911     Data::cos() const
912     {
913 matt 1349 return C_TensorUnaryOperation<double (*)(double)>(*this, ::cos);
914 jgs 94 }
915    
916     Data
917     Data::tan() const
918     {
919 matt 1349 return C_TensorUnaryOperation<double (*)(double)>(*this, ::tan);
920 jgs 94 }
921    
922     Data
923 jgs 150 Data::asin() const
924     {
925 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::asin);
926 jgs 150 }
927    
928     Data
929     Data::acos() const
930     {
931 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::acos);
932 jgs 150 }
933    
934 phornby 1026
935 jgs 150 Data
936     Data::atan() const
937     {
938 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::atan);
939 jgs 150 }
940    
941     Data
942     Data::sinh() const
943     {
944 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::sinh);
945 matt 1334
946 jgs 150 }
947    
948     Data
949     Data::cosh() const
950     {
951 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::cosh);
952 jgs 150 }
953    
954     Data
955     Data::tanh() const
956     {
957 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::tanh);
958 jgs 150 }
959    
960 phornby 1026
961 jgs 150 Data
962 phornby 1026 Data::erf() const
963     {
964 gross 1028 #ifdef _WIN32
965     throw DataException("Error - Data:: erf function is not supported on _WIN32 platforms.");
966     #else
967 matt 1334 return C_TensorUnaryOperation(*this, ::erf);
968 phornby 1026 #endif
969     }
970    
971     Data
972 jgs 150 Data::asinh() const
973     {
974 phornby 1032 #ifdef _WIN32
975 matt 1334 return C_TensorUnaryOperation(*this, escript::asinh_substitute);
976 phornby 1032 #else
977 matt 1334 return C_TensorUnaryOperation(*this, ::asinh);
978 phornby 1032 #endif
979 jgs 150 }
980    
981     Data
982     Data::acosh() const
983     {
984 phornby 1032 #ifdef _WIN32
985 matt 1334 return C_TensorUnaryOperation(*this, escript::acosh_substitute);
986 phornby 1032 #else
987 matt 1334 return C_TensorUnaryOperation(*this, ::acosh);
988 phornby 1032 #endif
989 jgs 150 }
990    
991     Data
992     Data::atanh() const
993     {
994 phornby 1032 #ifdef _WIN32
995 matt 1334 return C_TensorUnaryOperation(*this, escript::atanh_substitute);
996 phornby 1032 #else
997 matt 1334 return C_TensorUnaryOperation(*this, ::atanh);
998 phornby 1032 #endif
999 jgs 150 }
1000    
1001     Data
1002 gross 286 Data::log10() const
1003 jgs 94 {
1004 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::log10);
1005 jgs 94 }
1006    
1007     Data
1008 gross 286 Data::log() const
1009 jgs 94 {
1010 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::log);
1011 jgs 94 }
1012    
1013 jgs 106 Data
1014     Data::sign() const
1015 jgs 94 {
1016 matt 1334 return C_TensorUnaryOperation(*this, escript::fsign);
1017 jgs 94 }
1018    
1019 jgs 106 Data
1020     Data::abs() const
1021 jgs 94 {
1022 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::fabs);
1023 jgs 94 }
1024    
1025 jgs 106 Data
1026     Data::neg() const
1027 jgs 94 {
1028 matt 1334 return C_TensorUnaryOperation(*this, negate<double>());
1029 jgs 94 }
1030    
1031 jgs 102 Data
1032 jgs 106 Data::pos() const
1033 jgs 94 {
1034 jgs 148 Data result;
1035     // perform a deep copy
1036     result.copy(*this);
1037     return result;
1038 jgs 102 }
1039    
1040     Data
1041 jgs 106 Data::exp() const
1042 jgs 102 {
1043 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::exp);
1044 jgs 102 }
1045    
1046     Data
1047 jgs 106 Data::sqrt() const
1048 jgs 102 {
1049 matt 1350 return C_TensorUnaryOperation<double (*)(double)>(*this, ::sqrt);
1050 jgs 102 }
1051    
1052 jgs 106 double
1053     Data::Lsup() const
1054 jgs 102 {
1055 bcumming 751 double localValue, globalValue;
1056 jgs 106 //
1057     // set the initial absolute maximum value to zero
1058 bcumming 751
1059 jgs 147 AbsMax abs_max_func;
1060 bcumming 751 localValue = algorithm(abs_max_func,0);
1061     #ifdef PASO_MPI
1062     MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MAX, MPI_COMM_WORLD );
1063     return globalValue;
1064     #else
1065     return localValue;
1066     #endif
1067 jgs 117 }
1068    
1069     double
1070 jgs 106 Data::sup() const
1071 jgs 102 {
1072 bcumming 751 double localValue, globalValue;
1073 jgs 106 //
1074     // set the initial maximum value to min possible double
1075 jgs 147 FMax fmax_func;
1076 bcumming 751 localValue = algorithm(fmax_func,numeric_limits<double>::max()*-1);
1077     #ifdef PASO_MPI
1078     MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MAX, MPI_COMM_WORLD );
1079     return globalValue;
1080     #else
1081     return localValue;
1082     #endif
1083 jgs 102 }
1084    
1085 jgs 106 double
1086     Data::inf() const
1087 jgs 102 {
1088 bcumming 751 double localValue, globalValue;
1089 jgs 106 //
1090     // set the initial minimum value to max possible double
1091 jgs 147 FMin fmin_func;
1092 bcumming 751 localValue = algorithm(fmin_func,numeric_limits<double>::max());
1093     #ifdef PASO_MPI
1094     MPI_Allreduce( &localValue, &globalValue, 1, MPI_DOUBLE, MPI_MIN, MPI_COMM_WORLD );
1095     return globalValue;
1096     #else
1097     return localValue;
1098     #endif
1099 jgs 102 }
1100    
1101 bcumming 751 /* TODO */
1102     /* global reduction */
1103 jgs 102 Data
1104 jgs 106 Data::maxval() const
1105 jgs 102 {
1106 jgs 113 //
1107     // set the initial maximum value to min possible double
1108 jgs 147 FMax fmax_func;
1109     return dp_algorithm(fmax_func,numeric_limits<double>::max()*-1);
1110 jgs 102 }
1111    
1112     Data
1113 jgs 106 Data::minval() const
1114 jgs 102 {
1115 jgs 113 //
1116     // set the initial minimum value to max possible double
1117 jgs 147 FMin fmin_func;
1118     return dp_algorithm(fmin_func,numeric_limits<double>::max());
1119 jgs 102 }
1120    
1121 jgs 123 Data
1122 gross 804 Data::swapaxes(const int axis0, const int axis1) const
1123 jgs 123 {
1124 gross 804 int axis0_tmp,axis1_tmp;
1125 gross 800 DataArrayView::ShapeType s=getDataPointShape();
1126     DataArrayView::ShapeType ev_shape;
1127     // Here's the equivalent of python s_out=s[axis_offset:]+s[:axis_offset]
1128     // which goes thru all shape vector elements starting with axis_offset (at index=rank wrap around to 0)
1129     int rank=getDataPointRank();
1130 gross 804 if (rank<2) {
1131     throw DataException("Error - Data::swapaxes argument must have at least rank 2.");
1132 gross 800 }
1133 gross 804 if (axis0<0 || axis0>rank-1) {
1134     throw DataException("Error - Data::swapaxes: axis0 must be between 0 and rank-1=" + rank-1);
1135     }
1136     if (axis1<0 || axis1>rank-1) {
1137     throw DataException("Error - Data::swapaxes: axis1 must be between 0 and rank-1=" + rank-1);
1138     }
1139     if (axis0 == axis1) {
1140     throw DataException("Error - Data::swapaxes: axis indices must be different.");
1141     }
1142     if (axis0 > axis1) {
1143     axis0_tmp=axis1;
1144     axis1_tmp=axis0;
1145     } else {
1146     axis0_tmp=axis0;
1147     axis1_tmp=axis1;
1148     }
1149 gross 800 for (int i=0; i<rank; i++) {
1150 gross 804 if (i == axis0_tmp) {
1151 ksteube 1312 ev_shape.push_back(s[axis1_tmp]);
1152 gross 804 } else if (i == axis1_tmp) {
1153 ksteube 1312 ev_shape.push_back(s[axis0_tmp]);
1154 gross 800 } else {
1155 ksteube 1312 ev_shape.push_back(s[i]);
1156 gross 800 }
1157     }
1158     Data ev(0.,ev_shape,getFunctionSpace());
1159     ev.typeMatchRight(*this);
1160 gross 804 m_data->swapaxes(ev.m_data.get(), axis0_tmp, axis1_tmp);
1161 gross 800 return ev;
1162    
1163 jgs 123 }
1164    
1165     Data
1166 ksteube 775 Data::symmetric() const
1167 jgs 123 {
1168 ksteube 775 // check input
1169     DataArrayView::ShapeType s=getDataPointShape();
1170     if (getDataPointRank()==2) {
1171 ksteube 1312 if(s[0] != s[1])
1172 ksteube 775 throw DataException("Error - Data::symmetric can only be calculated for rank 2 object with equal first and second dimension.");
1173     }
1174     else if (getDataPointRank()==4) {
1175     if(!(s[0] == s[2] && s[1] == s[3]))
1176     throw DataException("Error - Data::symmetric can only be calculated for rank 4 object with dim0==dim2 and dim1==dim3.");
1177     }
1178     else {
1179     throw DataException("Error - Data::symmetric can only be calculated for rank 2 or 4 object.");
1180     }
1181     Data ev(0.,getDataPointShape(),getFunctionSpace());
1182     ev.typeMatchRight(*this);
1183     m_data->symmetric(ev.m_data.get());
1184     return ev;
1185     }
1186    
1187     Data
1188     Data::nonsymmetric() const
1189     {
1190     // check input
1191     DataArrayView::ShapeType s=getDataPointShape();
1192     if (getDataPointRank()==2) {
1193 ksteube 1312 if(s[0] != s[1])
1194 ksteube 775 throw DataException("Error - Data::nonsymmetric can only be calculated for rank 2 object with equal first and second dimension.");
1195     DataArrayView::ShapeType ev_shape;
1196     ev_shape.push_back(s[0]);
1197     ev_shape.push_back(s[1]);
1198     Data ev(0.,ev_shape,getFunctionSpace());
1199     ev.typeMatchRight(*this);
1200     m_data->nonsymmetric(ev.m_data.get());
1201     return ev;
1202     }
1203     else if (getDataPointRank()==4) {
1204     if(!(s[0] == s[2] && s[1] == s[3]))
1205     throw DataException("Error - Data::nonsymmetric can only be calculated for rank 4 object with dim0==dim2 and dim1==dim3.");
1206     DataArrayView::ShapeType ev_shape;
1207     ev_shape.push_back(s[0]);
1208     ev_shape.push_back(s[1]);
1209     ev_shape.push_back(s[2]);
1210     ev_shape.push_back(s[3]);
1211     Data ev(0.,ev_shape,getFunctionSpace());
1212     ev.typeMatchRight(*this);
1213     m_data->nonsymmetric(ev.m_data.get());
1214     return ev;
1215     }
1216     else {
1217     throw DataException("Error - Data::nonsymmetric can only be calculated for rank 2 or 4 object.");
1218     }
1219     }
1220    
1221     Data
1222 gross 800 Data::trace(int axis_offset) const
1223 ksteube 775 {
1224     DataArrayView::ShapeType s=getDataPointShape();
1225     if (getDataPointRank()==2) {
1226     DataArrayView::ShapeType ev_shape;
1227     Data ev(0.,ev_shape,getFunctionSpace());
1228     ev.typeMatchRight(*this);
1229 gross 800 m_data->trace(ev.m_data.get(), axis_offset);
1230 ksteube 775 return ev;
1231     }
1232     if (getDataPointRank()==3) {
1233     DataArrayView::ShapeType ev_shape;
1234     if (axis_offset==0) {
1235     int s2=s[2];
1236     ev_shape.push_back(s2);
1237     }
1238     else if (axis_offset==1) {
1239     int s0=s[0];
1240     ev_shape.push_back(s0);
1241     }
1242     Data ev(0.,ev_shape,getFunctionSpace());
1243     ev.typeMatchRight(*this);
1244 gross 800 m_data->trace(ev.m_data.get(), axis_offset);
1245 ksteube 775 return ev;
1246     }
1247     if (getDataPointRank()==4) {
1248     DataArrayView::ShapeType ev_shape;
1249     if (axis_offset==0) {
1250     ev_shape.push_back(s[2]);
1251     ev_shape.push_back(s[3]);
1252     }
1253     else if (axis_offset==1) {
1254     ev_shape.push_back(s[0]);
1255     ev_shape.push_back(s[3]);
1256     }
1257     else if (axis_offset==2) {
1258     ev_shape.push_back(s[0]);
1259     ev_shape.push_back(s[1]);
1260     }
1261     Data ev(0.,ev_shape,getFunctionSpace());
1262     ev.typeMatchRight(*this);
1263 gross 800 m_data->trace(ev.m_data.get(), axis_offset);
1264 ksteube 775 return ev;
1265     }
1266     else {
1267 gross 800 throw DataException("Error - Data::trace can only be calculated for rank 2, 3 or 4 object.");
1268 ksteube 775 }
1269     }
1270    
1271     Data
1272     Data::transpose(int axis_offset) const
1273     {
1274     DataArrayView::ShapeType s=getDataPointShape();
1275     DataArrayView::ShapeType ev_shape;
1276     // Here's the equivalent of python s_out=s[axis_offset:]+s[:axis_offset]
1277     // which goes thru all shape vector elements starting with axis_offset (at index=rank wrap around to 0)
1278     int rank=getDataPointRank();
1279     if (axis_offset<0 || axis_offset>rank) {
1280     throw DataException("Error - Data::transpose must have 0 <= axis_offset <= rank=" + rank);
1281     }
1282     for (int i=0; i<rank; i++) {
1283     int index = (axis_offset+i)%rank;
1284     ev_shape.push_back(s[index]); // Append to new shape
1285     }
1286     Data ev(0.,ev_shape,getFunctionSpace());
1287     ev.typeMatchRight(*this);
1288     m_data->transpose(ev.m_data.get(), axis_offset);
1289     return ev;
1290 jgs 123 }
1291    
1292 gross 576 Data
1293     Data::eigenvalues() const
1294     {
1295     // check input
1296     DataArrayView::ShapeType s=getDataPointShape();
1297 ksteube 1312 if (getDataPointRank()!=2)
1298 gross 576 throw DataException("Error - Data::eigenvalues can only be calculated for rank 2 object.");
1299 ksteube 1312 if(s[0] != s[1])
1300 gross 576 throw DataException("Error - Data::eigenvalues can only be calculated for object with equal first and second dimension.");
1301     // create return
1302     DataArrayView::ShapeType ev_shape(1,s[0]);
1303     Data ev(0.,ev_shape,getFunctionSpace());
1304     ev.typeMatchRight(*this);
1305     m_data->eigenvalues(ev.m_data.get());
1306     return ev;
1307     }
1308    
1309 jgs 121 const boost::python::tuple
1310 gross 576 Data::eigenvalues_and_eigenvectors(const double tol) const
1311     {
1312     DataArrayView::ShapeType s=getDataPointShape();
1313 ksteube 1312 if (getDataPointRank()!=2)
1314 gross 576 throw DataException("Error - Data::eigenvalues and eigenvectors can only be calculated for rank 2 object.");
1315 ksteube 1312 if(s[0] != s[1])
1316 gross 576 throw DataException("Error - Data::eigenvalues and eigenvectors can only be calculated for object with equal first and second dimension.");
1317     // create return
1318     DataArrayView::ShapeType ev_shape(1,s[0]);
1319     Data ev(0.,ev_shape,getFunctionSpace());
1320     ev.typeMatchRight(*this);
1321     DataArrayView::ShapeType V_shape(2,s[0]);
1322     Data V(0.,V_shape,getFunctionSpace());
1323     V.typeMatchRight(*this);
1324     m_data->eigenvalues_and_eigenvectors(ev.m_data.get(),V.m_data.get(),tol);
1325     return make_tuple(boost::python::object(ev),boost::python::object(V));
1326     }
1327    
1328     const boost::python::tuple
1329 gross 921 Data::minGlobalDataPoint() const
1330 jgs 121 {
1331 gross 921 // NB: calc_minGlobalDataPoint( had to be split off from minGlobalDataPoint( as boost::make_tuple causes an
1332 jgs 148 // abort (for unknown reasons) if there are openmp directives with it in the
1333     // surrounding function
1334    
1335     int DataPointNo;
1336 gross 921 int ProcNo;
1337     calc_minGlobalDataPoint(ProcNo,DataPointNo);
1338     return make_tuple(ProcNo,DataPointNo);
1339 jgs 148 }
1340    
1341     void
1342 gross 921 Data::calc_minGlobalDataPoint(int& ProcNo,
1343     int& DataPointNo) const
1344 jgs 148 {
1345     int i,j;
1346     int lowi=0,lowj=0;
1347     double min=numeric_limits<double>::max();
1348    
1349 jgs 121 Data temp=minval();
1350    
1351     int numSamples=temp.getNumSamples();
1352     int numDPPSample=temp.getNumDataPointsPerSample();
1353    
1354 jgs 148 double next,local_min;
1355     int local_lowi,local_lowj;
1356 jgs 121
1357 jgs 148 #pragma omp parallel private(next,local_min,local_lowi,local_lowj)
1358     {
1359     local_min=min;
1360     #pragma omp for private(i,j) schedule(static)
1361     for (i=0; i<numSamples; i++) {
1362     for (j=0; j<numDPPSample; j++) {
1363     next=temp.getDataPoint(i,j)();
1364     if (next<local_min) {
1365     local_min=next;
1366     local_lowi=i;
1367     local_lowj=j;
1368     }
1369 jgs 121 }
1370     }
1371 jgs 148 #pragma omp critical
1372     if (local_min<min) {
1373     min=local_min;
1374     lowi=local_lowi;
1375     lowj=local_lowj;
1376     }
1377 jgs 121 }
1378    
1379 bcumming 782 #ifdef PASO_MPI
1380     // determine the processor on which the minimum occurs
1381     next = temp.getDataPoint(lowi,lowj)();
1382     int lowProc = 0;
1383     double *globalMins = new double[get_MPISize()+1];
1384     int error = MPI_Gather ( &next, 1, MPI_DOUBLE, globalMins, 1, MPI_DOUBLE, 0, get_MPIComm() );
1385 ksteube 1312
1386 bcumming 782 if( get_MPIRank()==0 ){
1387     next = globalMins[lowProc];
1388     for( i=1; i<get_MPISize(); i++ )
1389     if( next>globalMins[i] ){
1390     lowProc = i;
1391     next = globalMins[i];
1392     }
1393     }
1394     MPI_Bcast( &lowProc, 1, MPI_DOUBLE, 0, get_MPIComm() );
1395    
1396     delete [] globalMins;
1397     ProcNo = lowProc;
1398 bcumming 790 #else
1399     ProcNo = 0;
1400 bcumming 782 #endif
1401 gross 921 DataPointNo = lowj + lowi * numDPPSample;
1402 jgs 121 }
1403    
1404 jgs 104 void
1405     Data::saveDX(std::string fileName) const
1406     {
1407 jgs 153 boost::python::dict args;
1408     args["data"]=boost::python::object(this);
1409     getDomain().saveDX(fileName,args);
1410 jgs 104 return;
1411     }
1412    
1413 jgs 110 void
1414     Data::saveVTK(std::string fileName) const
1415     {
1416 jgs 153 boost::python::dict args;
1417     args["data"]=boost::python::object(this);
1418     getDomain().saveVTK(fileName,args);
1419 jgs 110 return;
1420     }
1421    
1422 jgs 102 Data&
1423     Data::operator+=(const Data& right)
1424     {
1425 gross 783 if (isProtected()) {
1426     throw DataException("Error - attempt to update protected Data object.");
1427     }
1428 jgs 94 binaryOp(right,plus<double>());
1429     return (*this);
1430     }
1431    
1432 jgs 102 Data&
1433     Data::operator+=(const boost::python::object& right)
1434 jgs 94 {
1435 gross 854 Data tmp(right,getFunctionSpace(),false);
1436     binaryOp(tmp,plus<double>());
1437 jgs 94 return (*this);
1438     }
1439 ksteube 1312 Data&
1440     Data::operator=(const Data& other)
1441     {
1442     copy(other);
1443     return (*this);
1444     }
1445 jgs 94
1446 jgs 102 Data&
1447     Data::operator-=(const Data& right)
1448 jgs 94 {
1449 gross 783 if (isProtected()) {
1450     throw DataException("Error - attempt to update protected Data object.");
1451     }
1452 jgs 94 binaryOp(right,minus<double>());
1453     return (*this);
1454     }
1455    
1456 jgs 102 Data&
1457     Data::operator-=(const boost::python::object& right)
1458 jgs 94 {
1459 gross 854 Data tmp(right,getFunctionSpace(),false);
1460     binaryOp(tmp,minus<double>());
1461 jgs 94 return (*this);
1462     }
1463    
1464 jgs 102 Data&
1465     Data::operator*=(const Data& right)
1466 jgs 94 {
1467 gross 783 if (isProtected()) {
1468     throw DataException("Error - attempt to update protected Data object.");
1469     }
1470 jgs 94 binaryOp(right,multiplies<double>());
1471     return (*this);
1472     }
1473    
1474 jgs 102 Data&
1475     Data::operator*=(const boost::python::object& right)
1476 jgs 94 {
1477 gross 854 Data tmp(right,getFunctionSpace(),false);
1478     binaryOp(tmp,multiplies<double>());
1479 jgs 94 return (*this);
1480     }
1481    
1482 jgs 102 Data&
1483     Data::operator/=(const Data& right)
1484 jgs 94 {
1485 gross 783 if (isProtected()) {
1486     throw DataException("Error - attempt to update protected Data object.");
1487     }
1488 jgs 94 binaryOp(right,divides<double>());
1489     return (*this);
1490     }
1491    
1492 jgs 102 Data&
1493     Data::operator/=(const boost::python::object& right)
1494 jgs 94 {
1495 gross 854 Data tmp(right,getFunctionSpace(),false);
1496     binaryOp(tmp,divides<double>());
1497 jgs 94 return (*this);
1498     }
1499    
1500 jgs 102 Data
1501 gross 699 Data::rpowO(const boost::python::object& left) const
1502     {
1503     Data left_d(left,*this);
1504     return left_d.powD(*this);
1505     }
1506    
1507     Data
1508 jgs 102 Data::powO(const boost::python::object& right) const
1509 jgs 94 {
1510 gross 854 Data tmp(right,getFunctionSpace(),false);
1511     return powD(tmp);
1512 jgs 94 }
1513    
1514 jgs 102 Data
1515     Data::powD(const Data& right) const
1516 jgs 94 {
1517 matt 1350 return C_TensorBinaryOperation<double (*)(double, double)>(*this, right, ::pow);
1518 jgs 94 }
1519    
1520     //
1521 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1522 jgs 102 Data
1523     escript::operator+(const Data& left, const Data& right)
1524 jgs 94 {
1525 matt 1327 return C_TensorBinaryOperation(left, right, plus<double>());
1526 jgs 94 }
1527    
1528     //
1529 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1530 jgs 102 Data
1531     escript::operator-(const Data& left, const Data& right)
1532 jgs 94 {
1533 matt 1327 return C_TensorBinaryOperation(left, right, minus<double>());
1534 jgs 94 }
1535    
1536     //
1537 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1538 jgs 102 Data
1539     escript::operator*(const Data& left, const Data& right)
1540 jgs 94 {
1541 matt 1327 return C_TensorBinaryOperation(left, right, multiplies<double>());
1542 jgs 94 }
1543    
1544     //
1545 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1546 jgs 102 Data
1547     escript::operator/(const Data& left, const Data& right)
1548 jgs 94 {
1549 matt 1327 return C_TensorBinaryOperation(left, right, divides<double>());
1550 jgs 94 }
1551    
1552     //
1553 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1554 jgs 102 Data
1555     escript::operator+(const Data& left, const boost::python::object& right)
1556 jgs 94 {
1557 gross 854 return left+Data(right,left.getFunctionSpace(),false);
1558 jgs 94 }
1559    
1560     //
1561 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1562 jgs 102 Data
1563     escript::operator-(const Data& left, const boost::python::object& right)
1564 jgs 94 {
1565 gross 854 return left-Data(right,left.getFunctionSpace(),false);
1566 jgs 94 }
1567    
1568     //
1569 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1570 jgs 102 Data
1571     escript::operator*(const Data& left, const boost::python::object& right)
1572 jgs 94 {
1573 gross 854 return left*Data(right,left.getFunctionSpace(),false);
1574 jgs 94 }
1575    
1576     //
1577 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1578 jgs 102 Data
1579     escript::operator/(const Data& left, const boost::python::object& right)
1580 jgs 94 {
1581 gross 854 return left/Data(right,left.getFunctionSpace(),false);
1582 jgs 94 }
1583    
1584     //
1585 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1586 jgs 102 Data
1587     escript::operator+(const boost::python::object& left, const Data& right)
1588 jgs 94 {
1589 gross 854 return Data(left,right.getFunctionSpace(),false)+right;
1590 jgs 94 }
1591    
1592     //
1593 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1594 jgs 102 Data
1595     escript::operator-(const boost::python::object& left, const Data& right)
1596 jgs 94 {
1597 gross 854 return Data(left,right.getFunctionSpace(),false)-right;
1598 jgs 94 }
1599    
1600     //
1601 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1602 jgs 102 Data
1603     escript::operator*(const boost::python::object& left, const Data& right)
1604 jgs 94 {
1605 gross 854 return Data(left,right.getFunctionSpace(),false)*right;
1606 jgs 94 }
1607    
1608     //
1609 jgs 123 // NOTE: It is essential to specify the namespace this operator belongs to
1610 jgs 102 Data
1611     escript::operator/(const boost::python::object& left, const Data& right)
1612 jgs 94 {
1613 gross 854 return Data(left,right.getFunctionSpace(),false)/right;
1614 jgs 94 }
1615    
1616     //
1617 jgs 102 //bool escript::operator==(const Data& left, const Data& right)
1618     //{
1619     // /*
1620     // NB: this operator does very little at this point, and isn't to
1621     // be relied on. Requires further implementation.
1622     // */
1623     //
1624     // bool ret;
1625     //
1626     // if (left.isEmpty()) {
1627     // if(!right.isEmpty()) {
1628     // ret = false;
1629     // } else {
1630     // ret = true;
1631     // }
1632     // }
1633     //
1634     // if (left.isConstant()) {
1635     // if(!right.isConstant()) {
1636     // ret = false;
1637     // } else {
1638     // ret = true;
1639     // }
1640     // }
1641     //
1642     // if (left.isTagged()) {
1643     // if(!right.isTagged()) {
1644     // ret = false;
1645     // } else {
1646     // ret = true;
1647     // }
1648     // }
1649     //
1650     // if (left.isExpanded()) {
1651     // if(!right.isExpanded()) {
1652     // ret = false;
1653     // } else {
1654     // ret = true;
1655     // }
1656     // }
1657     //
1658     // return ret;
1659     //}
1660    
1661 bcumming 751 /* TODO */
1662     /* global reduction */
1663 jgs 102 Data
1664 ksteube 1312 Data::getItem(const boost::python::object& key) const
1665 jgs 94 {
1666 jgs 102 const DataArrayView& view=getPointDataView();
1667 jgs 94
1668 jgs 102 DataArrayView::RegionType slice_region=view.getSliceRegion(key);
1669 jgs 94
1670 jgs 102 if (slice_region.size()!=view.getRank()) {
1671     throw DataException("Error - slice size does not match Data rank.");
1672 jgs 94 }
1673    
1674 jgs 102 return getSlice(slice_region);
1675 jgs 94 }
1676    
1677 bcumming 751 /* TODO */
1678     /* global reduction */
1679 jgs 94 Data
1680 jgs 102 Data::getSlice(const DataArrayView::RegionType& region) const
1681 jgs 94 {
1682 jgs 102 return Data(*this,region);
1683 jgs 94 }
1684    
1685 bcumming 751 /* TODO */
1686     /* global reduction */
1687 jgs 94 void
1688 jgs 102 Data::setItemO(const boost::python::object& key,
1689     const boost::python::object& value)
1690 jgs 94 {
1691 jgs 102 Data tempData(value,getFunctionSpace());
1692     setItemD(key,tempData);
1693     }
1694    
1695     void
1696     Data::setItemD(const boost::python::object& key,
1697     const Data& value)
1698     {
1699 jgs 94 const DataArrayView& view=getPointDataView();
1700 jgs 123
1701 jgs 94 DataArrayView::RegionType slice_region=view.getSliceRegion(key);
1702     if (slice_region.size()!=view.getRank()) {
1703     throw DataException("Error - slice size does not match Data rank.");
1704     }
1705 jgs 108 if (getFunctionSpace()!=value.getFunctionSpace()) {
1706     setSlice(Data(value,getFunctionSpace()),slice_region);
1707     } else {
1708     setSlice(value,slice_region);
1709     }
1710 jgs 94 }
1711    
1712     void
1713 jgs 102 Data::setSlice(const Data& value,
1714     const DataArrayView::RegionType& region)
1715 jgs 94 {
1716 gross 783 if (isProtected()) {
1717     throw DataException("Error - attempt to update protected Data object.");
1718     }
1719 jgs 102 Data tempValue(value);
1720     typeMatchLeft(tempValue);
1721     typeMatchRight(tempValue);
1722     m_data->setSlice(tempValue.m_data.get(),region);
1723     }
1724    
1725     void
1726     Data::typeMatchLeft(Data& right) const
1727     {
1728     if (isExpanded()){
1729     right.expand();
1730     } else if (isTagged()) {
1731     if (right.isConstant()) {
1732     right.tag();
1733     }
1734     }
1735     }
1736    
1737     void
1738     Data::typeMatchRight(const Data& right)
1739     {
1740 jgs 94 if (isTagged()) {
1741     if (right.isExpanded()) {
1742     expand();
1743     }
1744     } else if (isConstant()) {
1745     if (right.isExpanded()) {
1746     expand();
1747     } else if (right.isTagged()) {
1748     tag();
1749     }
1750     }
1751     }
1752    
1753     void
1754 gross 1044 Data::setTaggedValueByName(std::string name,
1755 ksteube 1312 const boost::python::object& value)
1756 gross 1044 {
1757     if (getFunctionSpace().getDomain().isValidTagName(name)) {
1758     int tagKey=getFunctionSpace().getDomain().getTag(name);
1759     setTaggedValue(tagKey,value);
1760     }
1761     }
1762     void
1763 jgs 94 Data::setTaggedValue(int tagKey,
1764     const boost::python::object& value)
1765     {
1766 gross 783 if (isProtected()) {
1767     throw DataException("Error - attempt to update protected Data object.");
1768     }
1769 jgs 94 //
1770     // Ensure underlying data object is of type DataTagged
1771 gross 1358 if (isConstant()) tag();
1772 jgs 94
1773 matt 1319 numeric::array asNumArray(value);
1774 jgs 94
1775 matt 1319
1776     // extract the shape of the numarray
1777     DataArrayView::ShapeType tempShape;
1778     for (int i=0; i < asNumArray.getrank(); i++) {
1779     tempShape.push_back(extract<int>(asNumArray.getshape()[i]));
1780     }
1781    
1782     // get the space for the data vector
1783     int len = DataArrayView::noValues(tempShape);
1784     DataVector temp_data(len, 0.0, len);
1785     DataArrayView temp_dataView(temp_data, tempShape);
1786     temp_dataView.copy(asNumArray);
1787    
1788 jgs 94 //
1789     // Call DataAbstract::setTaggedValue
1790 matt 1319 m_data->setTaggedValue(tagKey,temp_dataView);
1791 jgs 94 }
1792    
1793 jgs 110 void
1794 jgs 121 Data::setTaggedValueFromCPP(int tagKey,
1795     const DataArrayView& value)
1796     {
1797 gross 783 if (isProtected()) {
1798     throw DataException("Error - attempt to update protected Data object.");
1799     }
1800 jgs 121 //
1801     // Ensure underlying data object is of type DataTagged
1802 gross 1358 if (isConstant()) tag();
1803 jgs 121
1804     //
1805     // Call DataAbstract::setTaggedValue
1806     m_data->setTaggedValue(tagKey,value);
1807     }
1808    
1809 jgs 149 int
1810     Data::getTagNumber(int dpno)
1811     {
1812 gross 1358 return getFunctionSpace().getTagFromSampleNo(dpno);
1813 jgs 149 }
1814    
1815 jgs 121 void
1816 jgs 119 Data::archiveData(const std::string fileName)
1817     {
1818     cout << "Archiving Data object to: " << fileName << endl;
1819    
1820     //
1821     // Determine type of this Data object
1822     int dataType = -1;
1823    
1824     if (isEmpty()) {
1825     dataType = 0;
1826     cout << "\tdataType: DataEmpty" << endl;
1827     }
1828     if (isConstant()) {
1829     dataType = 1;
1830     cout << "\tdataType: DataConstant" << endl;
1831     }
1832     if (isTagged()) {
1833     dataType = 2;
1834     cout << "\tdataType: DataTagged" << endl;
1835     }
1836     if (isExpanded()) {
1837     dataType = 3;
1838     cout << "\tdataType: DataExpanded" << endl;
1839     }
1840 jgs 123
1841 jgs 119 if (dataType == -1) {
1842     throw DataException("archiveData Error: undefined dataType");
1843     }
1844    
1845     //
1846     // Collect data items common to all Data types
1847     int noSamples = getNumSamples();
1848     int noDPPSample = getNumDataPointsPerSample();
1849     int functionSpaceType = getFunctionSpace().getTypeCode();
1850     int dataPointRank = getDataPointRank();
1851     int dataPointSize = getDataPointSize();
1852     int dataLength = getLength();
1853     DataArrayView::ShapeType dataPointShape = getDataPointShape();
1854 woo409 757 vector<int> referenceNumbers(noSamples);
1855 jgs 119 for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
1856 gross 964 referenceNumbers[sampleNo] = getFunctionSpace().getReferenceIDOfSample(sampleNo);
1857 jgs 119 }
1858 woo409 757 vector<int> tagNumbers(noSamples);
1859 jgs 119 if (isTagged()) {
1860     for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
1861     tagNumbers[sampleNo] = getFunctionSpace().getTagFromSampleNo(sampleNo);
1862     }
1863     }
1864    
1865     cout << "\tnoSamples: " << noSamples << " noDPPSample: " << noDPPSample << endl;
1866     cout << "\tfunctionSpaceType: " << functionSpaceType << endl;
1867     cout << "\trank: " << dataPointRank << " size: " << dataPointSize << " length: " << dataLength << endl;
1868    
1869     //
1870     // Flatten Shape to an array of integers suitable for writing to file
1871     int flatShape[4] = {0,0,0,0};
1872     cout << "\tshape: < ";
1873     for (int dim=0; dim<dataPointRank; dim++) {
1874     flatShape[dim] = dataPointShape[dim];
1875     cout << dataPointShape[dim] << " ";
1876     }
1877     cout << ">" << endl;
1878    
1879     //
1880 jgs 123 // Open archive file
1881 jgs 119 ofstream archiveFile;
1882     archiveFile.open(fileName.data(), ios::out);
1883    
1884     if (!archiveFile.good()) {
1885     throw DataException("archiveData Error: problem opening archive file");
1886     }
1887    
1888 jgs 123 //
1889     // Write common data items to archive file
1890 jgs 119 archiveFile.write(reinterpret_cast<char *>(&dataType),sizeof(int));
1891     archiveFile.write(reinterpret_cast<char *>(&noSamples),sizeof(int));
1892     archiveFile.write(reinterpret_cast<char *>(&noDPPSample),sizeof(int));
1893     archiveFile.write(reinterpret_cast<char *>(&functionSpaceType),sizeof(int));
1894     archiveFile.write(reinterpret_cast<char *>(&dataPointRank),sizeof(int));
1895     archiveFile.write(reinterpret_cast<char *>(&dataPointSize),sizeof(int));
1896     archiveFile.write(reinterpret_cast<char *>(&dataLength),sizeof(int));
1897     for (int dim = 0; dim < 4; dim++) {
1898     archiveFile.write(reinterpret_cast<char *>(&flatShape[dim]),sizeof(int));
1899     }
1900     for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
1901     archiveFile.write(reinterpret_cast<char *>(&referenceNumbers[sampleNo]),sizeof(int));
1902     }
1903     if (isTagged()) {
1904     for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
1905     archiveFile.write(reinterpret_cast<char *>(&tagNumbers[sampleNo]),sizeof(int));
1906     }
1907     }
1908    
1909     if (!archiveFile.good()) {
1910     throw DataException("archiveData Error: problem writing to archive file");
1911     }
1912    
1913     //
1914 jgs 123 // Archive underlying data values for each Data type
1915     int noValues;
1916 jgs 119 switch (dataType) {
1917     case 0:
1918     // DataEmpty
1919 jgs 123 noValues = 0;
1920     archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));
1921     cout << "\tnoValues: " << noValues << endl;
1922 jgs 119 break;
1923     case 1:
1924     // DataConstant
1925 jgs 123 noValues = m_data->getLength();
1926     archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));
1927     cout << "\tnoValues: " << noValues << endl;
1928     if (m_data->archiveData(archiveFile,noValues)) {
1929     throw DataException("archiveData Error: problem writing data to archive file");
1930     }
1931 jgs 119 break;
1932     case 2:
1933     // DataTagged
1934 jgs 123 noValues = m_data->getLength();
1935     archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));
1936     cout << "\tnoValues: " << noValues << endl;
1937     if (m_data->archiveData(archiveFile,noValues)) {
1938     throw DataException("archiveData Error: problem writing data to archive file");
1939     }
1940 jgs 119 break;
1941     case 3:
1942     // DataExpanded
1943 jgs 123 noValues = m_data->getLength();
1944     archiveFile.write(reinterpret_cast<char *>(&noValues),sizeof(int));
1945     cout << "\tnoValues: " << noValues << endl;
1946     if (m_data->archiveData(archiveFile,noValues)) {
1947     throw DataException("archiveData Error: problem writing data to archive file");
1948     }
1949 jgs 119 break;
1950     }
1951    
1952 jgs 123 if (!archiveFile.good()) {
1953     throw DataException("archiveData Error: problem writing data to archive file");
1954     }
1955    
1956     //
1957     // Close archive file
1958     archiveFile.close();
1959    
1960     if (!archiveFile.good()) {
1961     throw DataException("archiveData Error: problem closing archive file");
1962     }
1963    
1964 jgs 119 }
1965    
1966     void
1967     Data::extractData(const std::string fileName,
1968     const FunctionSpace& fspace)
1969     {
1970     //
1971     // Can only extract Data to an object which is initially DataEmpty
1972     if (!isEmpty()) {
1973     throw DataException("extractData Error: can only extract to DataEmpty object");
1974     }
1975    
1976     cout << "Extracting Data object from: " << fileName << endl;
1977    
1978     int dataType;
1979     int noSamples;
1980     int noDPPSample;
1981     int functionSpaceType;
1982     int dataPointRank;
1983     int dataPointSize;
1984     int dataLength;
1985     DataArrayView::ShapeType dataPointShape;
1986     int flatShape[4];
1987    
1988     //
1989 jgs 123 // Open the archive file
1990 jgs 119 ifstream archiveFile;
1991     archiveFile.open(fileName.data(), ios::in);
1992    
1993     if (!archiveFile.good()) {
1994     throw DataException("extractData Error: problem opening archive file");
1995     }
1996    
1997 jgs 123 //
1998     // Read common data items from archive file
1999 jgs 119 archiveFile.read(reinterpret_cast<char *>(&dataType),sizeof(int));
2000     archiveFile.read(reinterpret_cast<char *>(&noSamples),sizeof(int));
2001     archiveFile.read(reinterpret_cast<char *>(&noDPPSample),sizeof(int));
2002     archiveFile.read(reinterpret_cast<char *>(&functionSpaceType),sizeof(int));
2003     archiveFile.read(reinterpret_cast<char *>(&dataPointRank),sizeof(int));
2004     archiveFile.read(reinterpret_cast<char *>(&dataPointSize),sizeof(int));
2005     archiveFile.read(reinterpret_cast<char *>(&dataLength),sizeof(int));
2006     for (int dim = 0; dim < 4; dim++) {
2007     archiveFile.read(reinterpret_cast<char *>(&flatShape[dim]),sizeof(int));
2008     if (flatShape[dim]>0) {
2009     dataPointShape.push_back(flatShape[dim]);
2010     }
2011     }
2012 woo409 757 vector<int> referenceNumbers(noSamples);
2013 jgs 119 for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
2014     archiveFile.read(reinterpret_cast<char *>(&referenceNumbers[sampleNo]),sizeof(int));
2015     }
2016 woo409 757 vector<int> tagNumbers(noSamples);
2017 jgs 119 if (dataType==2) {
2018     for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
2019     archiveFile.read(reinterpret_cast<char *>(&tagNumbers[sampleNo]),sizeof(int));
2020     }
2021     }
2022    
2023     if (!archiveFile.good()) {
2024     throw DataException("extractData Error: problem reading from archive file");
2025     }
2026    
2027 jgs 123 //
2028     // Verify the values just read from the archive file
2029 jgs 119 switch (dataType) {
2030     case 0:
2031     cout << "\tdataType: DataEmpty" << endl;
2032     break;
2033     case 1:
2034     cout << "\tdataType: DataConstant" << endl;
2035     break;
2036     case 2:
2037     cout << "\tdataType: DataTagged" << endl;
2038     break;
2039     case 3:
2040     cout << "\tdataType: DataExpanded" << endl;
2041     break;
2042     default:
2043     throw DataException("extractData Error: undefined dataType read from archive file");
2044     break;
2045     }
2046    
2047     cout << "\tnoSamples: " << noSamples << " noDPPSample: " << noDPPSample << endl;
2048     cout << "\tfunctionSpaceType: " << functionSpaceType << endl;
2049     cout << "\trank: " << dataPointRank << " size: " << dataPointSize << " length: " << dataLength << endl;
2050     cout << "\tshape: < ";
2051     for (int dim = 0; dim < dataPointRank; dim++) {
2052     cout << dataPointShape[dim] << " ";
2053     }
2054     cout << ">" << endl;
2055    
2056     //
2057     // Verify that supplied FunctionSpace object is compatible with this Data object.
2058     if ( (fspace.getTypeCode()!=functionSpaceType) ||
2059     (fspace.getNumSamples()!=noSamples) ||
2060     (fspace.getNumDPPSample()!=noDPPSample)
2061     ) {
2062     throw DataException("extractData Error: incompatible FunctionSpace");
2063     }
2064     for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
2065 gross 964 if (referenceNumbers[sampleNo] != fspace.getReferenceIDOfSample(sampleNo)) {
2066 jgs 119 throw DataException("extractData Error: incompatible FunctionSpace");
2067     }
2068     }
2069     if (dataType==2) {
2070     for (int sampleNo=0; sampleNo<noSamples; sampleNo++) {
2071     if (tagNumbers[sampleNo] != fspace.getTagFromSampleNo(sampleNo)) {
2072     throw DataException("extractData Error: incompatible FunctionSpace");
2073     }
2074     }
2075     }
2076    
2077     //
2078     // Construct a DataVector to hold underlying data values
2079     DataVector dataVec(dataLength);
2080    
2081     //
2082     // Load this DataVector with the appropriate values
2083 jgs 123 int noValues;
2084     archiveFile.read(reinterpret_cast<char *>(&noValues),sizeof(int));
2085     cout << "\tnoValues: " << noValues << endl;
2086 jgs 119 switch (dataType) {
2087     case 0:
2088     // DataEmpty
2089 jgs 123 if (noValues != 0) {
2090     throw DataException("extractData Error: problem reading data from archive file");
2091     }
2092 jgs 119 break;
2093     case 1:
2094     // DataConstant
2095 jgs 123 if (dataVec.extractData(archiveFile,noValues)) {
2096     throw DataException("extractData Error: problem reading data from archive file");
2097     }
2098 jgs 119 break;
2099     case 2:
2100     // DataTagged
2101 jgs 123 if (dataVec.extractData(archiveFile,noValues)) {
2102     throw DataException("extractData Error: problem reading data from archive file");
2103     }
2104 jgs 119 break;
2105     case 3:
2106     // DataExpanded
2107 jgs 123 if (dataVec.extractData(archiveFile,noValues)) {
2108     throw DataException("extractData Error: problem reading data from archive file");
2109     }
2110 jgs 119 break;
2111     }
2112    
2113 jgs 123 if (!archiveFile.good()) {
2114     throw DataException("extractData Error: problem reading from archive file");
2115     }
2116    
2117 jgs 119 //
2118 jgs 123 // Close archive file
2119     archiveFile.close();
2120    
2121     if (!archiveFile.good()) {
2122     throw DataException("extractData Error: problem closing archive file");
2123     }
2124    
2125     //
2126 jgs 119 // Construct an appropriate Data object
2127     DataAbstract* tempData;
2128     switch (dataType) {
2129     case 0:
2130     // DataEmpty
2131     tempData=new DataEmpty();
2132     break;
2133     case 1:
2134     // DataConstant
2135     tempData=new DataConstant(fspace,dataPointShape,dataVec);
2136     break;
2137     case 2:
2138     // DataTagged
2139     tempData=new DataTagged(fspace,dataPointShape,tagNumbers,dataVec);
2140     break;
2141     case 3:
2142     // DataExpanded
2143     tempData=new DataExpanded(fspace,dataPointShape,dataVec);
2144     break;
2145     }
2146     shared_ptr<DataAbstract> temp_data(tempData);
2147     m_data=temp_data;
2148     }
2149    
2150 jgs 94 ostream& escript::operator<<(ostream& o, const Data& data)
2151     {
2152     o << data.toString();
2153     return o;
2154     }
2155 bcumming 782
2156 ksteube 813 Data
2157     escript::C_GeneralTensorProduct(Data& arg_0,
2158     Data& arg_1,
2159     int axis_offset,
2160     int transpose)
2161     {
2162 gross 826 // General tensor product: res(SL x SR) = arg_0(SL x SM) * arg_1(SM x SR)
2163 ksteube 813 // SM is the product of the last axis_offset entries in arg_0.getShape().
2164    
2165     // Interpolate if necessary and find an appropriate function space
2166 gross 826 Data arg_0_Z, arg_1_Z;
2167 ksteube 813 if (arg_0.getFunctionSpace()!=arg_1.getFunctionSpace()) {
2168     if (arg_0.probeInterpolation(arg_1.getFunctionSpace())) {
2169 gross 826 arg_0_Z = arg_0.interpolate(arg_1.getFunctionSpace());
2170     arg_1_Z = Data(arg_1);
2171 ksteube 813 }
2172     else if (arg_1.probeInterpolation(arg_0.getFunctionSpace())) {
2173 gross 826 arg_1_Z=arg_1.interpolate(arg_0.getFunctionSpace());
2174     arg_0_Z =Data(arg_0);
2175 ksteube 813 }
2176     else {
2177     throw DataException("Error - C_GeneralTensorProduct: arguments have incompatible function spaces.");
2178     }
2179 gross 826 } else {
2180     arg_0_Z = Data(arg_0);
2181     arg_1_Z = Data(arg_1);
2182 ksteube 813 }
2183     // Get rank and shape of inputs
2184 gross 826 int rank0 = arg_0_Z.getDataPointRank();
2185     int rank1 = arg_1_Z.getDataPointRank();
2186     DataArrayView::ShapeType shape0 = arg_0_Z.getDataPointShape();
2187     DataArrayView::ShapeType shape1 = arg_1_Z.getDataPointShape();
2188 ksteube 813
2189     // Prepare for the loops of the product and verify compatibility of shapes
2190     int start0=0, start1=0;
2191     if (transpose == 0) {}
2192     else if (transpose == 1) { start0 = axis_offset; }
2193     else if (transpose == 2) { start1 = rank1-axis_offset; }
2194     else { throw DataException("C_GeneralTensorProduct: Error - transpose should be 0, 1 or 2"); }
2195    
2196     // Adjust the shapes for transpose
2197     DataArrayView::ShapeType tmpShape0;
2198     DataArrayView::ShapeType tmpShape1;
2199     for (int i=0; i<rank0; i++) { tmpShape0.push_back( shape0[(i+start0)%rank0] ); }
2200     for (int i=0; i<rank1; i++) { tmpShape1.push_back( shape1[(i+start1)%rank1] ); }
2201    
2202     #if 0
2203     // For debugging: show shape after transpose
2204     char tmp[100];
2205     std::string shapeStr;
2206     shapeStr = "(";
2207     for (int i=0; i<rank0; i++) { sprintf(tmp, "%d,", tmpShape0[i]); shapeStr += tmp; }
2208     shapeStr += ")";
2209     cout << "C_GeneralTensorProduct: Shape of arg0 is " << shapeStr << endl;
2210     shapeStr = "(";
2211     for (int i=0; i<rank1; i++) { sprintf(tmp, "%d,", tmpShape1[i]); shapeStr += tmp; }
2212     shapeStr += ")";
2213     cout << "C_GeneralTensorProduct: Shape of arg1 is " << shapeStr << endl;
2214     #endif
2215    
2216     // Prepare for the loops of the product
2217     int SL=1, SM=1, SR=1;
2218     for (int i=0; i<rank0-axis_offset; i++) {
2219     SL *= tmpShape0[i];
2220     }
2221     for (int i=rank0-axis_offset; i<rank0; i++) {
2222     if (tmpShape0[i] != tmpShape1[i-(rank0-axis_offset)]) {
2223     throw DataException("C_GeneralTensorProduct: Error - incompatible shapes");
2224     }
2225     SM *= tmpShape0[i];
2226     }
2227     for (int i=axis_offset; i<rank1; i++) {
2228     SR *= tmpShape1[i];
2229     }
2230    
2231     // Define the shape of the output
2232     DataArrayView::ShapeType shape2;
2233 gross 826 for (int i=0; i<rank0-axis_offset; i++) { shape2.push_back(tmpShape0[i]); } // First part of arg_0_Z
2234     for (int i=axis_offset; i<rank1; i++) { shape2.push_back(tmpShape1[i]); } // Last part of arg_1_Z
2235 ksteube 813
2236     // Declare output Data object
2237 gross 826 Data res;
2238 ksteube 813
2239 gross 826 if (arg_0_Z.isConstant() && arg_1_Z.isConstant()) {
2240     res = Data(0.0, shape2, arg_1_Z.getFunctionSpace()); // DataConstant output
2241     double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[0]);
2242     double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[0]);
2243     double *ptr_2 = &((res.getPointDataView().getData())[0]);
2244 ksteube 813 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2245     }
2246 gross 826 else if (arg_0_Z.isConstant() && arg_1_Z.isTagged()) {
2247 ksteube 813
2248     // Prepare the DataConstant input
2249 gross 826 DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());
2250 ksteube 813 if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
2251    
2252     // Borrow DataTagged input from Data object
2253 gross 826 DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData());
2254 ksteube 813 if (tmp_1==0) { throw DataException("GTP_1 Programming error - casting to DataTagged."); }
2255    
2256     // Prepare a DataTagged output 2
2257 gross 826 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace()); // DataTagged output
2258     res.tag();
2259     DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2260 ksteube 813 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2261    
2262     // Prepare offset into DataConstant
2263     int offset_0 = tmp_0->getPointOffset(0,0);
2264 gross 826 double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);
2265 ksteube 813 // Get the views
2266     DataArrayView view_1 = tmp_1->getDefaultValue();
2267     DataArrayView view_2 = tmp_2->getDefaultValue();
2268     // Get the pointers to the actual data
2269     double *ptr_1 = &((view_1.getData())[0]);
2270     double *ptr_2 = &((view_2.getData())[0]);
2271     // Compute an MVP for the default
2272     matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2273     // Compute an MVP for each tag
2274     const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2275     DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2276     for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2277     tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());
2278     DataArrayView view_1 = tmp_1->getDataPointByTag(i->first);
2279     DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);
2280     double *ptr_1 = &view_1.getData(0);
2281     double *ptr_2 = &view_2.getData(0);
2282     matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2283     }
2284    
2285     }
2286 gross 826 else if (arg_0_Z.isConstant() && arg_1_Z.isExpanded()) {
2287 ksteube 813
2288 gross 826 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace(),true); // DataExpanded output
2289     DataConstant* tmp_0=dynamic_cast<DataConstant*>(arg_0_Z.borrowData());
2290     DataExpanded* tmp_1=dynamic_cast<DataExpanded*>(arg_1_Z.borrowData());
2291     DataExpanded* tmp_2=dynamic_cast<DataExpanded*>(res.borrowData());
2292 ksteube 813 if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
2293     if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2294     if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataExpanded."); }
2295     int sampleNo_1,dataPointNo_1;
2296 gross 826 int numSamples_1 = arg_1_Z.getNumSamples();
2297     int numDataPointsPerSample_1 = arg_1_Z.getNumDataPointsPerSample();
2298 ksteube 813 int offset_0 = tmp_0->getPointOffset(0,0);
2299     #pragma omp parallel for private(sampleNo_1,dataPointNo_1) schedule(static)
2300     for (sampleNo_1 = 0; sampleNo_1 < numSamples_1; sampleNo_1++) {
2301     for (dataPointNo_1 = 0; dataPointNo_1 < numDataPointsPerSample_1; dataPointNo_1++) {
2302     int offset_1 = tmp_1->getPointOffset(sampleNo_1,dataPointNo_1);
2303     int offset_2 = tmp_2->getPointOffset(sampleNo_1,dataPointNo_1);
2304 gross 826 double *ptr_0 = &((arg_0_Z.getPointDataView().getData())[offset_0]);
2305     double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);
2306     double *ptr_2 = &((res.getPointDataView().getData())[offset_2]);
2307 ksteube 813 matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2308     }
2309     }
2310    
2311     }
2312 gross 826 else if (arg_0_Z.isTagged() && arg_1_Z.isConstant()) {
2313 ksteube 813
2314     // Borrow DataTagged input from Data object
2315 gross 826 DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2316 ksteube 813 if (tmp_0==0) { throw DataException("GTP_0 Programming error - casting to DataTagged."); }
2317    
2318     // Prepare the DataConstant input
2319 gross 826 DataConstant* tmp_1=dynamic_cast<DataConstant*>(arg_1_Z.borrowData());
2320 ksteube 813 if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataConstant."); }
2321    
2322     // Prepare a DataTagged output 2
2323 gross 826 res = Data(0.0, shape2, arg_0_Z.getFunctionSpace()); // DataTagged output
2324     res.tag();
2325     DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2326 ksteube 813 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2327    
2328     // Prepare offset into DataConstant
2329     int offset_1 = tmp_1->getPointOffset(0,0);
2330 gross 826 double *ptr_1 = &((arg_1_Z.getPointDataView().getData())[offset_1]);
2331 ksteube 813 // Get the views
2332     DataArrayView view_0 = tmp_0->getDefaultValue();
2333     DataArrayView view_2 = tmp_2->getDefaultValue();
2334     // Get the pointers to the actual data
2335     double *ptr_0 = &((view_0.getData())[0]);
2336     double *ptr_2 = &((view_2.getData())[0]);
2337     // Compute an MVP for the default
2338     matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2339     // Compute an MVP for each tag
2340     const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2341     DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2342     for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2343     tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());
2344     DataArrayView view_0 = tmp_0->getDataPointByTag(i->first);
2345     DataArrayView view_2 = tmp_2->getDataPointByTag(i->first);
2346     double *ptr_0 = &view_0.getData(0);
2347     double *ptr_2 = &view_2.getData(0);
2348     matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2349     }
2350    
2351     }
2352 gross 826 else if (arg_0_Z.isTagged() && arg_1_Z.isTagged()) {
2353 ksteube 813
2354     // Borrow DataTagged input from Data object
2355 gross 826 DataTagged* tmp_0=dynamic_cast<DataTagged*>(arg_0_Z.borrowData());
2356 ksteube 813 if (tmp_0==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2357    
2358     // Borrow DataTagged input from Data object
2359 gross 826 DataTagged* tmp_1=dynamic_cast<DataTagged*>(arg_1_Z.borrowData());
2360 ksteube 813 if (tmp_1==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2361    
2362     // Prepare a DataTagged output 2
2363 gross 826 res = Data(0.0, shape2, arg_1_Z.getFunctionSpace());
2364     res.tag(); // DataTagged output
2365     DataTagged* tmp_2=dynamic_cast<DataTagged*>(res.borrowData());
2366 ksteube 813 if (tmp_2==0) { throw DataException("GTP Programming error - casting to DataTagged."); }
2367    
2368     // Get the views
2369     DataArrayView view_0 = tmp_0->getDefaultValue();
2370     DataArrayView view_1 = tmp_1->getDefaultValue();
2371     DataArrayView view_2 = tmp_2->getDefaultValue();
2372     // Get the pointers to the actual data
2373     double *ptr_0 = &((view_0.getData())[0]);
2374     double *ptr_1 = &((view_1.getData())[0]);
2375     double *ptr_2 = &((view_2.getData())[0]);
2376     // Compute an MVP for the default
2377     matrix_matrix_product(SL, SM, SR, ptr_0, ptr_1, ptr_2, transpose);
2378     // Merge the tags
2379     DataTagged::DataMapType::const_iterator i; // i->first is a tag, i->second is an offset into memory
2380     const DataTagged::DataMapType& lookup_0=tmp_0->getTagLookup();
2381     const DataTagged::DataMapType& lookup_1=tmp_1->getTagLookup();
2382     for (i=lookup_0.begin();i!=lookup_0.end();i++) {
2383     tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue()); // use tmp_2 to get correct shape
2384     }
2385     for (i=lookup_1.begin();i!=lookup_1.end();i++) {
2386     tmp_2->addTaggedValue(i->first,tmp_2->getDefaultValue());
2387     }
2388     // Compute an MVP for each tag
2389     const DataTagged::DataMapType& lookup_2=tmp_2->getTagLookup();
2390     for (i=lookup_2.begin();i!=lookup_2.end();i++) {
2391     DataArrayView view_0