1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322
1323
1324
1325
1326
1327
1328
1329
1330
1331
1332
1333
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353
1354
1355
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
1390
1391
1392
1393
1394
1395
1396
1397
1398
1399
1400
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417
1418
1419
1420
1421
1422
1423
1424
1425
1426
1427
1428
1429
1430
1431
1432
1433
1434
1435
1436
1437
1438
1439
1440
1441
1442
1443
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
1454
1455
1456
1457
1458
1459
1460
1461
1462
1463
1464
1465
1466
1467
1468
1469
1470
1471
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483
1484
1485
1486
1487
1488
1489
1490
1491
1492
1493
1494
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
1514
1515
1516
1517
1518
1519
1520
1521
1522
1523
1524
1525
1526
1527
1528
1529
1530
1531
1532
1533
1534
1535
1536
1537
1538
1539
1540
1541
1542
|
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_TRANSFORM_H
#define EIGEN_TRANSFORM_H
namespace Eigen {
namespace internal {
template<typename Transform>
struct transform_traits
{
enum
{
Dim = Transform::Dim,
HDim = Transform::HDim,
Mode = Transform::Mode,
IsProjective = (int(Mode)==int(Projective))
};
};
template< typename TransformType,
typename MatrixType,
int Case = transform_traits<TransformType>::IsProjective ? 0
: int(MatrixType::RowsAtCompileTime) == int(transform_traits<TransformType>::HDim) ? 1
: 2,
int RhsCols = MatrixType::ColsAtCompileTime>
struct transform_right_product_impl;
template< typename Other,
int Mode,
int Options,
int Dim,
int HDim,
int OtherRows=Other::RowsAtCompileTime,
int OtherCols=Other::ColsAtCompileTime>
struct transform_left_product_impl;
template< typename Lhs,
typename Rhs,
bool AnyProjective =
transform_traits<Lhs>::IsProjective ||
transform_traits<Rhs>::IsProjective>
struct transform_transform_product_impl;
template< typename Other,
int Mode,
int Options,
int Dim,
int HDim,
int OtherRows=Other::RowsAtCompileTime,
int OtherCols=Other::ColsAtCompileTime>
struct transform_construct_from_matrix;
template<typename TransformType> struct transform_take_affine_part;
template<typename _Scalar, int _Dim, int _Mode, int _Options>
struct traits<Transform<_Scalar,_Dim,_Mode,_Options> >
{
typedef _Scalar Scalar;
typedef Eigen::Index StorageIndex;
typedef Dense StorageKind;
enum {
Dim1 = _Dim==Dynamic ? _Dim : _Dim + 1,
RowsAtCompileTime = _Mode==Projective ? Dim1 : _Dim,
ColsAtCompileTime = Dim1,
MaxRowsAtCompileTime = RowsAtCompileTime,
MaxColsAtCompileTime = ColsAtCompileTime,
Flags = 0
};
};
template<int Mode> struct transform_make_affine;
} // end namespace internal
/** \geometry_module \ingroup Geometry_Module
*
* \class Transform
*
* \brief Represents an homogeneous transformation in a N dimensional space
*
* \tparam _Scalar the scalar type, i.e., the type of the coefficients
* \tparam _Dim the dimension of the space
* \tparam _Mode the type of the transformation. Can be:
* - #Affine: the transformation is stored as a (Dim+1)^2 matrix,
* where the last row is assumed to be [0 ... 0 1].
* - #AffineCompact: the transformation is stored as a (Dim)x(Dim+1) matrix.
* - #Projective: the transformation is stored as a (Dim+1)^2 matrix
* without any assumption.
* \tparam _Options has the same meaning as in class Matrix. It allows to specify DontAlign and/or RowMajor.
* These Options are passed directly to the underlying matrix type.
*
* The homography is internally represented and stored by a matrix which
* is available through the matrix() method. To understand the behavior of
* this class you have to think a Transform object as its internal
* matrix representation. The chosen convention is right multiply:
*
* \code v' = T * v \endcode
*
* Therefore, an affine transformation matrix M is shaped like this:
*
* \f$ \left( \begin{array}{cc}
* linear & translation\\
* 0 ... 0 & 1
* \end{array} \right) \f$
*
* Note that for a projective transformation the last row can be anything,
* and then the interpretation of different parts might be sightly different.
*
* However, unlike a plain matrix, the Transform class provides many features
* simplifying both its assembly and usage. In particular, it can be composed
* with any other transformations (Transform,Translation,RotationBase,DiagonalMatrix)
* and can be directly used to transform implicit homogeneous vectors. All these
* operations are handled via the operator*. For the composition of transformations,
* its principle consists to first convert the right/left hand sides of the product
* to a compatible (Dim+1)^2 matrix and then perform a pure matrix product.
* Of course, internally, operator* tries to perform the minimal number of operations
* according to the nature of each terms. Likewise, when applying the transform
* to points, the latters are automatically promoted to homogeneous vectors
* before doing the matrix product. The conventions to homogeneous representations
* are performed as follow:
*
* \b Translation t (Dim)x(1):
* \f$ \left( \begin{array}{cc}
* I & t \\
* 0\,...\,0 & 1
* \end{array} \right) \f$
*
* \b Rotation R (Dim)x(Dim):
* \f$ \left( \begin{array}{cc}
* R & 0\\
* 0\,...\,0 & 1
* \end{array} \right) \f$
*<!--
* \b Linear \b Matrix L (Dim)x(Dim):
* \f$ \left( \begin{array}{cc}
* L & 0\\
* 0\,...\,0 & 1
* \end{array} \right) \f$
*
* \b Affine \b Matrix A (Dim)x(Dim+1):
* \f$ \left( \begin{array}{c}
* A\\
* 0\,...\,0\,1
* \end{array} \right) \f$
*-->
* \b Scaling \b DiagonalMatrix S (Dim)x(Dim):
* \f$ \left( \begin{array}{cc}
* S & 0\\
* 0\,...\,0 & 1
* \end{array} \right) \f$
*
* \b Column \b point v (Dim)x(1):
* \f$ \left( \begin{array}{c}
* v\\
* 1
* \end{array} \right) \f$
*
* \b Set \b of \b column \b points V1...Vn (Dim)x(n):
* \f$ \left( \begin{array}{ccc}
* v_1 & ... & v_n\\
* 1 & ... & 1
* \end{array} \right) \f$
*
* The concatenation of a Transform object with any kind of other transformation
* always returns a Transform object.
*
* A little exception to the "as pure matrix product" rule is the case of the
* transformation of non homogeneous vectors by an affine transformation. In
* that case the last matrix row can be ignored, and the product returns non
* homogeneous vectors.
*
* Since, for instance, a Dim x Dim matrix is interpreted as a linear transformation,
* it is not possible to directly transform Dim vectors stored in a Dim x Dim matrix.
* The solution is either to use a Dim x Dynamic matrix or explicitly request a
* vector transformation by making the vector homogeneous:
* \code
* m' = T * m.colwise().homogeneous();
* \endcode
* Note that there is zero overhead.
*
* Conversion methods from/to Qt's QMatrix and QTransform are available if the
* preprocessor token EIGEN_QT_SUPPORT is defined.
*
* This class can be extended with the help of the plugin mechanism described on the page
* \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_TRANSFORM_PLUGIN.
*
* \sa class Matrix, class Quaternion
*/
template<typename _Scalar, int _Dim, int _Mode, int _Options>
class Transform
{
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_Dim==Dynamic ? Dynamic : (_Dim+1)*(_Dim+1))
enum {
Mode = _Mode,
Options = _Options,
Dim = _Dim, ///< space dimension in which the transformation holds
HDim = _Dim+1, ///< size of a respective homogeneous vector
Rows = int(Mode)==(AffineCompact) ? Dim : HDim
};
/** the scalar type of the coefficients */
typedef _Scalar Scalar;
typedef Eigen::Index StorageIndex;
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
/** type of the matrix used to represent the transformation */
typedef typename internal::make_proper_matrix_type<Scalar,Rows,HDim,Options>::type MatrixType;
/** constified MatrixType */
typedef const MatrixType ConstMatrixType;
/** type of the matrix used to represent the linear part of the transformation */
typedef Matrix<Scalar,Dim,Dim,Options> LinearMatrixType;
/** type of read/write reference to the linear part of the transformation */
typedef Block<MatrixType,Dim,Dim,int(Mode)==(AffineCompact) && (Options&RowMajor)==0> LinearPart;
/** type of read reference to the linear part of the transformation */
typedef const Block<ConstMatrixType,Dim,Dim,int(Mode)==(AffineCompact) && (Options&RowMajor)==0> ConstLinearPart;
/** type of read/write reference to the affine part of the transformation */
typedef typename internal::conditional<int(Mode)==int(AffineCompact),
MatrixType&,
Block<MatrixType,Dim,HDim> >::type AffinePart;
/** type of read reference to the affine part of the transformation */
typedef typename internal::conditional<int(Mode)==int(AffineCompact),
const MatrixType&,
const Block<const MatrixType,Dim,HDim> >::type ConstAffinePart;
/** type of a vector */
typedef Matrix<Scalar,Dim,1> VectorType;
/** type of a read/write reference to the translation part of the rotation */
typedef Block<MatrixType,Dim,1,!(internal::traits<MatrixType>::Flags & RowMajorBit)> TranslationPart;
/** type of a read reference to the translation part of the rotation */
typedef const Block<ConstMatrixType,Dim,1,!(internal::traits<MatrixType>::Flags & RowMajorBit)> ConstTranslationPart;
/** corresponding translation type */
typedef Translation<Scalar,Dim> TranslationType;
// this intermediate enum is needed to avoid an ICE with gcc 3.4 and 4.0
enum { TransformTimeDiagonalMode = ((Mode==int(Isometry))?Affine:int(Mode)) };
/** The return type of the product between a diagonal matrix and a transform */
typedef Transform<Scalar,Dim,TransformTimeDiagonalMode> TransformTimeDiagonalReturnType;
protected:
MatrixType m_matrix;
public:
/** Default constructor without initialization of the meaningful coefficients.
* If Mode==Affine, then the last row is set to [0 ... 0 1] */
EIGEN_DEVICE_FUNC inline Transform()
{
check_template_params();
internal::transform_make_affine<(int(Mode)==Affine) ? Affine : AffineCompact>::run(m_matrix);
}
EIGEN_DEVICE_FUNC inline Transform(const Transform& other)
{
check_template_params();
m_matrix = other.m_matrix;
}
EIGEN_DEVICE_FUNC inline explicit Transform(const TranslationType& t)
{
check_template_params();
*this = t;
}
EIGEN_DEVICE_FUNC inline explicit Transform(const UniformScaling<Scalar>& s)
{
check_template_params();
*this = s;
}
template<typename Derived>
EIGEN_DEVICE_FUNC inline explicit Transform(const RotationBase<Derived, Dim>& r)
{
check_template_params();
*this = r;
}
EIGEN_DEVICE_FUNC inline Transform& operator=(const Transform& other)
{ m_matrix = other.m_matrix; return *this; }
typedef internal::transform_take_affine_part<Transform> take_affine_part;
/** Constructs and initializes a transformation from a Dim^2 or a (Dim+1)^2 matrix. */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC inline explicit Transform(const EigenBase<OtherDerived>& other)
{
EIGEN_STATIC_ASSERT((internal::is_same<Scalar,typename OtherDerived::Scalar>::value),
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY);
check_template_params();
internal::transform_construct_from_matrix<OtherDerived,Mode,Options,Dim,HDim>::run(this, other.derived());
}
/** Set \c *this from a Dim^2 or (Dim+1)^2 matrix. */
template<typename OtherDerived>
EIGEN_DEVICE_FUNC inline Transform& operator=(const EigenBase<OtherDerived>& other)
{
EIGEN_STATIC_ASSERT((internal::is_same<Scalar,typename OtherDerived::Scalar>::value),
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY);
internal::transform_construct_from_matrix<OtherDerived,Mode,Options,Dim,HDim>::run(this, other.derived());
return *this;
}
template<int OtherOptions>
EIGEN_DEVICE_FUNC inline Transform(const Transform<Scalar,Dim,Mode,OtherOptions>& other)
{
check_template_params();
// only the options change, we can directly copy the matrices
m_matrix = other.matrix();
}
template<int OtherMode,int OtherOptions>
EIGEN_DEVICE_FUNC inline Transform(const Transform<Scalar,Dim,OtherMode,OtherOptions>& other)
{
check_template_params();
// prevent conversions as:
// Affine | AffineCompact | Isometry = Projective
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(OtherMode==int(Projective), Mode==int(Projective)),
YOU_PERFORMED_AN_INVALID_TRANSFORMATION_CONVERSION)
// prevent conversions as:
// Isometry = Affine | AffineCompact
EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(OtherMode==int(Affine)||OtherMode==int(AffineCompact), Mode!=int(Isometry)),
YOU_PERFORMED_AN_INVALID_TRANSFORMATION_CONVERSION)
enum { ModeIsAffineCompact = Mode == int(AffineCompact),
OtherModeIsAffineCompact = OtherMode == int(AffineCompact)
};
if(ModeIsAffineCompact == OtherModeIsAffineCompact)
{
// We need the block expression because the code is compiled for all
// combinations of transformations and will trigger a compile time error
// if one tries to assign the matrices directly
m_matrix.template block<Dim,Dim+1>(0,0) = other.matrix().template block<Dim,Dim+1>(0,0);
makeAffine();
}
else if(OtherModeIsAffineCompact)
{
typedef typename Transform<Scalar,Dim,OtherMode,OtherOptions>::MatrixType OtherMatrixType;
internal::transform_construct_from_matrix<OtherMatrixType,Mode,Options,Dim,HDim>::run(this, other.matrix());
}
else
{
// here we know that Mode == AffineCompact and OtherMode != AffineCompact.
// if OtherMode were Projective, the static assert above would already have caught it.
// So the only possibility is that OtherMode == Affine
linear() = other.linear();
translation() = other.translation();
}
}
template<typename OtherDerived>
EIGEN_DEVICE_FUNC Transform(const ReturnByValue<OtherDerived>& other)
{
check_template_params();
other.evalTo(*this);
}
template<typename OtherDerived>
EIGEN_DEVICE_FUNC Transform& operator=(const ReturnByValue<OtherDerived>& other)
{
other.evalTo(*this);
return *this;
}
#ifdef EIGEN_QT_SUPPORT
inline Transform(const QMatrix& other);
inline Transform& operator=(const QMatrix& other);
inline QMatrix toQMatrix(void) const;
inline Transform(const QTransform& other);
inline Transform& operator=(const QTransform& other);
inline QTransform toQTransform(void) const;
#endif
EIGEN_DEVICE_FUNC Index rows() const { return int(Mode)==int(Projective) ? m_matrix.cols() : (m_matrix.cols()-1); }
EIGEN_DEVICE_FUNC Index cols() const { return m_matrix.cols(); }
/** shortcut for m_matrix(row,col);
* \sa MatrixBase::operator(Index,Index) const */
EIGEN_DEVICE_FUNC inline Scalar operator() (Index row, Index col) const { return m_matrix(row,col); }
/** shortcut for m_matrix(row,col);
* \sa MatrixBase::operator(Index,Index) */
EIGEN_DEVICE_FUNC inline Scalar& operator() (Index row, Index col) { return m_matrix(row,col); }
/** \returns a read-only expression of the transformation matrix */
EIGEN_DEVICE_FUNC inline const MatrixType& matrix() const { return m_matrix; }
/** \returns a writable expression of the transformation matrix */
EIGEN_DEVICE_FUNC inline MatrixType& matrix() { return m_matrix; }
/** \returns a read-only expression of the linear part of the transformation */
EIGEN_DEVICE_FUNC inline ConstLinearPart linear() const { return ConstLinearPart(m_matrix,0,0); }
/** \returns a writable expression of the linear part of the transformation */
EIGEN_DEVICE_FUNC inline LinearPart linear() { return LinearPart(m_matrix,0,0); }
/** \returns a read-only expression of the Dim x HDim affine part of the transformation */
EIGEN_DEVICE_FUNC inline ConstAffinePart affine() const { return take_affine_part::run(m_matrix); }
/** \returns a writable expression of the Dim x HDim affine part of the transformation */
EIGEN_DEVICE_FUNC inline AffinePart affine() { return take_affine_part::run(m_matrix); }
/** \returns a read-only expression of the translation vector of the transformation */
EIGEN_DEVICE_FUNC inline ConstTranslationPart translation() const { return ConstTranslationPart(m_matrix,0,Dim); }
/** \returns a writable expression of the translation vector of the transformation */
EIGEN_DEVICE_FUNC inline TranslationPart translation() { return TranslationPart(m_matrix,0,Dim); }
/** \returns an expression of the product between the transform \c *this and a matrix expression \a other.
*
* The right-hand-side \a other can be either:
* \li an homogeneous vector of size Dim+1,
* \li a set of homogeneous vectors of size Dim+1 x N,
* \li a transformation matrix of size Dim+1 x Dim+1.
*
* Moreover, if \c *this represents an affine transformation (i.e., Mode!=Projective), then \a other can also be:
* \li a point of size Dim (computes: \code this->linear() * other + this->translation()\endcode),
* \li a set of N points as a Dim x N matrix (computes: \code (this->linear() * other).colwise() + this->translation()\endcode),
*
* In all cases, the return type is a matrix or vector of same sizes as the right-hand-side \a other.
*
* If you want to interpret \a other as a linear or affine transformation, then first convert it to a Transform<> type,
* or do your own cooking.
*
* Finally, if you want to apply Affine transformations to vectors, then explicitly apply the linear part only:
* \code
* Affine3f A;
* Vector3f v1, v2;
* v2 = A.linear() * v1;
* \endcode
*
*/
// note: this function is defined here because some compilers cannot find the respective declaration
template<typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename internal::transform_right_product_impl<Transform, OtherDerived>::ResultType
operator * (const EigenBase<OtherDerived> &other) const
{ return internal::transform_right_product_impl<Transform, OtherDerived>::run(*this,other.derived()); }
/** \returns the product expression of a transformation matrix \a a times a transform \a b
*
* The left hand side \a other can be either:
* \li a linear transformation matrix of size Dim x Dim,
* \li an affine transformation matrix of size Dim x Dim+1,
* \li a general transformation matrix of size Dim+1 x Dim+1.
*/
template<typename OtherDerived> friend
EIGEN_DEVICE_FUNC inline const typename internal::transform_left_product_impl<OtherDerived,Mode,Options,_Dim,_Dim+1>::ResultType
operator * (const EigenBase<OtherDerived> &a, const Transform &b)
{ return internal::transform_left_product_impl<OtherDerived,Mode,Options,Dim,HDim>::run(a.derived(),b); }
/** \returns The product expression of a transform \a a times a diagonal matrix \a b
*
* The rhs diagonal matrix is interpreted as an affine scaling transformation. The
* product results in a Transform of the same type (mode) as the lhs only if the lhs
* mode is no isometry. In that case, the returned transform is an affinity.
*/
template<typename DiagonalDerived>
EIGEN_DEVICE_FUNC inline const TransformTimeDiagonalReturnType
operator * (const DiagonalBase<DiagonalDerived> &b) const
{
TransformTimeDiagonalReturnType res(*this);
res.linearExt() *= b;
return res;
}
/** \returns The product expression of a diagonal matrix \a a times a transform \a b
*
* The lhs diagonal matrix is interpreted as an affine scaling transformation. The
* product results in a Transform of the same type (mode) as the lhs only if the lhs
* mode is no isometry. In that case, the returned transform is an affinity.
*/
template<typename DiagonalDerived>
EIGEN_DEVICE_FUNC friend inline TransformTimeDiagonalReturnType
operator * (const DiagonalBase<DiagonalDerived> &a, const Transform &b)
{
TransformTimeDiagonalReturnType res;
res.linear().noalias() = a*b.linear();
res.translation().noalias() = a*b.translation();
if (Mode!=int(AffineCompact))
res.matrix().row(Dim) = b.matrix().row(Dim);
return res;
}
template<typename OtherDerived>
EIGEN_DEVICE_FUNC inline Transform& operator*=(const EigenBase<OtherDerived>& other) { return *this = *this * other; }
/** Concatenates two transformations */
EIGEN_DEVICE_FUNC inline const Transform operator * (const Transform& other) const
{
return internal::transform_transform_product_impl<Transform,Transform>::run(*this,other);
}
#if EIGEN_COMP_ICC
private:
// this intermediate structure permits to workaround a bug in ICC 11:
// error: template instantiation resulted in unexpected function type of "Eigen::Transform<double, 3, 32, 0>
// (const Eigen::Transform<double, 3, 2, 0> &) const"
// (the meaning of a name may have changed since the template declaration -- the type of the template is:
// "Eigen::internal::transform_transform_product_impl<Eigen::Transform<double, 3, 32, 0>,
// Eigen::Transform<double, 3, Mode, Options>, <expression>>::ResultType (const Eigen::Transform<double, 3, Mode, Options> &) const")
//
template<int OtherMode,int OtherOptions> struct icc_11_workaround
{
typedef internal::transform_transform_product_impl<Transform,Transform<Scalar,Dim,OtherMode,OtherOptions> > ProductType;
typedef typename ProductType::ResultType ResultType;
};
public:
/** Concatenates two different transformations */
template<int OtherMode,int OtherOptions>
inline typename icc_11_workaround<OtherMode,OtherOptions>::ResultType
operator * (const Transform<Scalar,Dim,OtherMode,OtherOptions>& other) const
{
typedef typename icc_11_workaround<OtherMode,OtherOptions>::ProductType ProductType;
return ProductType::run(*this,other);
}
#else
/** Concatenates two different transformations */
template<int OtherMode,int OtherOptions>
EIGEN_DEVICE_FUNC inline typename internal::transform_transform_product_impl<Transform,Transform<Scalar,Dim,OtherMode,OtherOptions> >::ResultType
operator * (const Transform<Scalar,Dim,OtherMode,OtherOptions>& other) const
{
return internal::transform_transform_product_impl<Transform,Transform<Scalar,Dim,OtherMode,OtherOptions> >::run(*this,other);
}
#endif
/** \sa MatrixBase::setIdentity() */
EIGEN_DEVICE_FUNC void setIdentity() { m_matrix.setIdentity(); }
/**
* \brief Returns an identity transformation.
* \todo In the future this function should be returning a Transform expression.
*/
EIGEN_DEVICE_FUNC static const Transform Identity()
{
return Transform(MatrixType::Identity());
}
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
inline Transform& scale(const MatrixBase<OtherDerived> &other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
inline Transform& prescale(const MatrixBase<OtherDerived> &other);
EIGEN_DEVICE_FUNC inline Transform& scale(const Scalar& s);
EIGEN_DEVICE_FUNC inline Transform& prescale(const Scalar& s);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
inline Transform& translate(const MatrixBase<OtherDerived> &other);
template<typename OtherDerived>
EIGEN_DEVICE_FUNC
inline Transform& pretranslate(const MatrixBase<OtherDerived> &other);
template<typename RotationType>
EIGEN_DEVICE_FUNC
inline Transform& rotate(const RotationType& rotation);
template<typename RotationType>
EIGEN_DEVICE_FUNC
inline Transform& prerotate(const RotationType& rotation);
EIGEN_DEVICE_FUNC Transform& shear(const Scalar& sx, const Scalar& sy);
EIGEN_DEVICE_FUNC Transform& preshear(const Scalar& sx, const Scalar& sy);
EIGEN_DEVICE_FUNC inline Transform& operator=(const TranslationType& t);
EIGEN_DEVICE_FUNC
inline Transform& operator*=(const TranslationType& t) { return translate(t.vector()); }
EIGEN_DEVICE_FUNC inline Transform operator*(const TranslationType& t) const;
EIGEN_DEVICE_FUNC
inline Transform& operator=(const UniformScaling<Scalar>& t);
EIGEN_DEVICE_FUNC
inline Transform& operator*=(const UniformScaling<Scalar>& s) { return scale(s.factor()); }
EIGEN_DEVICE_FUNC
inline TransformTimeDiagonalReturnType operator*(const UniformScaling<Scalar>& s) const
{
TransformTimeDiagonalReturnType res = *this;
res.scale(s.factor());
return res;
}
EIGEN_DEVICE_FUNC
inline Transform& operator*=(const DiagonalMatrix<Scalar,Dim>& s) { linearExt() *= s; return *this; }
template<typename Derived>
EIGEN_DEVICE_FUNC inline Transform& operator=(const RotationBase<Derived,Dim>& r);
template<typename Derived>
EIGEN_DEVICE_FUNC inline Transform& operator*=(const RotationBase<Derived,Dim>& r) { return rotate(r.toRotationMatrix()); }
template<typename Derived>
EIGEN_DEVICE_FUNC inline Transform operator*(const RotationBase<Derived,Dim>& r) const;
EIGEN_DEVICE_FUNC const LinearMatrixType rotation() const;
template<typename RotationMatrixType, typename ScalingMatrixType>
EIGEN_DEVICE_FUNC
void computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const;
template<typename ScalingMatrixType, typename RotationMatrixType>
EIGEN_DEVICE_FUNC
void computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const;
template<typename PositionDerived, typename OrientationType, typename ScaleDerived>
EIGEN_DEVICE_FUNC
Transform& fromPositionOrientationScale(const MatrixBase<PositionDerived> &position,
const OrientationType& orientation, const MatrixBase<ScaleDerived> &scale);
EIGEN_DEVICE_FUNC
inline Transform inverse(TransformTraits traits = (TransformTraits)Mode) const;
/** \returns a const pointer to the column major internal matrix */
EIGEN_DEVICE_FUNC const Scalar* data() const { return m_matrix.data(); }
/** \returns a non-const pointer to the column major internal matrix */
EIGEN_DEVICE_FUNC Scalar* data() { return m_matrix.data(); }
/** \returns \c *this with scalar type casted to \a NewScalarType
*
* Note that if \a NewScalarType is equal to the current scalar type of \c *this
* then this function smartly returns a const reference to \c *this.
*/
template<typename NewScalarType>
EIGEN_DEVICE_FUNC inline typename internal::cast_return_type<Transform,Transform<NewScalarType,Dim,Mode,Options> >::type cast() const
{ return typename internal::cast_return_type<Transform,Transform<NewScalarType,Dim,Mode,Options> >::type(*this); }
/** Copy constructor with scalar type conversion */
template<typename OtherScalarType>
EIGEN_DEVICE_FUNC inline explicit Transform(const Transform<OtherScalarType,Dim,Mode,Options>& other)
{
check_template_params();
m_matrix = other.matrix().template cast<Scalar>();
}
/** \returns \c true if \c *this is approximately equal to \a other, within the precision
* determined by \a prec.
*
* \sa MatrixBase::isApprox() */
EIGEN_DEVICE_FUNC bool isApprox(const Transform& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
{ return m_matrix.isApprox(other.m_matrix, prec); }
/** Sets the last row to [0 ... 0 1]
*/
EIGEN_DEVICE_FUNC void makeAffine()
{
internal::transform_make_affine<int(Mode)>::run(m_matrix);
}
/** \internal
* \returns the Dim x Dim linear part if the transformation is affine,
* and the HDim x Dim part for projective transformations.
*/
EIGEN_DEVICE_FUNC inline Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,Dim> linearExt()
{ return m_matrix.template block<int(Mode)==int(Projective)?HDim:Dim,Dim>(0,0); }
/** \internal
* \returns the Dim x Dim linear part if the transformation is affine,
* and the HDim x Dim part for projective transformations.
*/
EIGEN_DEVICE_FUNC inline const Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,Dim> linearExt() const
{ return m_matrix.template block<int(Mode)==int(Projective)?HDim:Dim,Dim>(0,0); }
/** \internal
* \returns the translation part if the transformation is affine,
* and the last column for projective transformations.
*/
EIGEN_DEVICE_FUNC inline Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,1> translationExt()
{ return m_matrix.template block<int(Mode)==int(Projective)?HDim:Dim,1>(0,Dim); }
/** \internal
* \returns the translation part if the transformation is affine,
* and the last column for projective transformations.
*/
EIGEN_DEVICE_FUNC inline const Block<MatrixType,int(Mode)==int(Projective)?HDim:Dim,1> translationExt() const
{ return m_matrix.template block<int(Mode)==int(Projective)?HDim:Dim,1>(0,Dim); }
#ifdef EIGEN_TRANSFORM_PLUGIN
#include EIGEN_TRANSFORM_PLUGIN
#endif
protected:
#ifndef EIGEN_PARSED_BY_DOXYGEN
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void check_template_params()
{
EIGEN_STATIC_ASSERT((Options & (DontAlign|RowMajor)) == Options, INVALID_MATRIX_TEMPLATE_PARAMETERS)
}
#endif
};
/** \ingroup Geometry_Module */
typedef Transform<float,2,Isometry> Isometry2f;
/** \ingroup Geometry_Module */
typedef Transform<float,3,Isometry> Isometry3f;
/** \ingroup Geometry_Module */
typedef Transform<double,2,Isometry> Isometry2d;
/** \ingroup Geometry_Module */
typedef Transform<double,3,Isometry> Isometry3d;
/** \ingroup Geometry_Module */
typedef Transform<float,2,Affine> Affine2f;
/** \ingroup Geometry_Module */
typedef Transform<float,3,Affine> Affine3f;
/** \ingroup Geometry_Module */
typedef Transform<double,2,Affine> Affine2d;
/** \ingroup Geometry_Module */
typedef Transform<double,3,Affine> Affine3d;
/** \ingroup Geometry_Module */
typedef Transform<float,2,AffineCompact> AffineCompact2f;
/** \ingroup Geometry_Module */
typedef Transform<float,3,AffineCompact> AffineCompact3f;
/** \ingroup Geometry_Module */
typedef Transform<double,2,AffineCompact> AffineCompact2d;
/** \ingroup Geometry_Module */
typedef Transform<double,3,AffineCompact> AffineCompact3d;
/** \ingroup Geometry_Module */
typedef Transform<float,2,Projective> Projective2f;
/** \ingroup Geometry_Module */
typedef Transform<float,3,Projective> Projective3f;
/** \ingroup Geometry_Module */
typedef Transform<double,2,Projective> Projective2d;
/** \ingroup Geometry_Module */
typedef Transform<double,3,Projective> Projective3d;
/**************************
*** Optional QT support ***
**************************/
#ifdef EIGEN_QT_SUPPORT
/** Initializes \c *this from a QMatrix assuming the dimension is 2.
*
* This function is available only if the token EIGEN_QT_SUPPORT is defined.
*/
template<typename Scalar, int Dim, int Mode,int Options>
Transform<Scalar,Dim,Mode,Options>::Transform(const QMatrix& other)
{
check_template_params();
*this = other;
}
/** Set \c *this from a QMatrix assuming the dimension is 2.
*
* This function is available only if the token EIGEN_QT_SUPPORT is defined.
*/
template<typename Scalar, int Dim, int Mode,int Options>
Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const QMatrix& other)
{
EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
if (Mode == int(AffineCompact))
m_matrix << other.m11(), other.m21(), other.dx(),
other.m12(), other.m22(), other.dy();
else
m_matrix << other.m11(), other.m21(), other.dx(),
other.m12(), other.m22(), other.dy(),
0, 0, 1;
return *this;
}
/** \returns a QMatrix from \c *this assuming the dimension is 2.
*
* \warning this conversion might loss data if \c *this is not affine
*
* This function is available only if the token EIGEN_QT_SUPPORT is defined.
*/
template<typename Scalar, int Dim, int Mode, int Options>
QMatrix Transform<Scalar,Dim,Mode,Options>::toQMatrix(void) const
{
check_template_params();
EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
return QMatrix(m_matrix.coeff(0,0), m_matrix.coeff(1,0),
m_matrix.coeff(0,1), m_matrix.coeff(1,1),
m_matrix.coeff(0,2), m_matrix.coeff(1,2));
}
/** Initializes \c *this from a QTransform assuming the dimension is 2.
*
* This function is available only if the token EIGEN_QT_SUPPORT is defined.
*/
template<typename Scalar, int Dim, int Mode,int Options>
Transform<Scalar,Dim,Mode,Options>::Transform(const QTransform& other)
{
check_template_params();
*this = other;
}
/** Set \c *this from a QTransform assuming the dimension is 2.
*
* This function is available only if the token EIGEN_QT_SUPPORT is defined.
*/
template<typename Scalar, int Dim, int Mode, int Options>
Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const QTransform& other)
{
check_template_params();
EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
if (Mode == int(AffineCompact))
m_matrix << other.m11(), other.m21(), other.dx(),
other.m12(), other.m22(), other.dy();
else
m_matrix << other.m11(), other.m21(), other.dx(),
other.m12(), other.m22(), other.dy(),
other.m13(), other.m23(), other.m33();
return *this;
}
/** \returns a QTransform from \c *this assuming the dimension is 2.
*
* This function is available only if the token EIGEN_QT_SUPPORT is defined.
*/
template<typename Scalar, int Dim, int Mode, int Options>
QTransform Transform<Scalar,Dim,Mode,Options>::toQTransform(void) const
{
EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
if (Mode == int(AffineCompact))
return QTransform(m_matrix.coeff(0,0), m_matrix.coeff(1,0),
m_matrix.coeff(0,1), m_matrix.coeff(1,1),
m_matrix.coeff(0,2), m_matrix.coeff(1,2));
else
return QTransform(m_matrix.coeff(0,0), m_matrix.coeff(1,0), m_matrix.coeff(2,0),
m_matrix.coeff(0,1), m_matrix.coeff(1,1), m_matrix.coeff(2,1),
m_matrix.coeff(0,2), m_matrix.coeff(1,2), m_matrix.coeff(2,2));
}
#endif
/*********************
*** Procedural API ***
*********************/
/** Applies on the right the non uniform scale transformation represented
* by the vector \a other to \c *this and returns a reference to \c *this.
* \sa prescale()
*/
template<typename Scalar, int Dim, int Mode, int Options>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
Transform<Scalar,Dim,Mode,Options>::scale(const MatrixBase<OtherDerived> &other)
{
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
linearExt().noalias() = (linearExt() * other.asDiagonal());
return *this;
}
/** Applies on the right a uniform scale of a factor \a c to \c *this
* and returns a reference to \c *this.
* \sa prescale(Scalar)
*/
template<typename Scalar, int Dim, int Mode, int Options>
EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::scale(const Scalar& s)
{
EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
linearExt() *= s;
return *this;
}
/** Applies on the left the non uniform scale transformation represented
* by the vector \a other to \c *this and returns a reference to \c *this.
* \sa scale()
*/
template<typename Scalar, int Dim, int Mode, int Options>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
Transform<Scalar,Dim,Mode,Options>::prescale(const MatrixBase<OtherDerived> &other)
{
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
affine().noalias() = (other.asDiagonal() * affine());
return *this;
}
/** Applies on the left a uniform scale of a factor \a c to \c *this
* and returns a reference to \c *this.
* \sa scale(Scalar)
*/
template<typename Scalar, int Dim, int Mode, int Options>
EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::prescale(const Scalar& s)
{
EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
m_matrix.template topRows<Dim>() *= s;
return *this;
}
/** Applies on the right the translation matrix represented by the vector \a other
* to \c *this and returns a reference to \c *this.
* \sa pretranslate()
*/
template<typename Scalar, int Dim, int Mode, int Options>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
Transform<Scalar,Dim,Mode,Options>::translate(const MatrixBase<OtherDerived> &other)
{
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
translationExt() += linearExt() * other;
return *this;
}
/** Applies on the left the translation matrix represented by the vector \a other
* to \c *this and returns a reference to \c *this.
* \sa translate()
*/
template<typename Scalar, int Dim, int Mode, int Options>
template<typename OtherDerived>
EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
Transform<Scalar,Dim,Mode,Options>::pretranslate(const MatrixBase<OtherDerived> &other)
{
EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,int(Dim))
if(int(Mode)==int(Projective))
affine() += other * m_matrix.row(Dim);
else
translation() += other;
return *this;
}
/** Applies on the right the rotation represented by the rotation \a rotation
* to \c *this and returns a reference to \c *this.
*
* The template parameter \a RotationType is the type of the rotation which
* must be known by internal::toRotationMatrix<>.
*
* Natively supported types includes:
* - any scalar (2D),
* - a Dim x Dim matrix expression,
* - a Quaternion (3D),
* - a AngleAxis (3D)
*
* This mechanism is easily extendable to support user types such as Euler angles,
* or a pair of Quaternion for 4D rotations.
*
* \sa rotate(Scalar), class Quaternion, class AngleAxis, prerotate(RotationType)
*/
template<typename Scalar, int Dim, int Mode, int Options>
template<typename RotationType>
EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
Transform<Scalar,Dim,Mode,Options>::rotate(const RotationType& rotation)
{
linearExt() *= internal::toRotationMatrix<Scalar,Dim>(rotation);
return *this;
}
/** Applies on the left the rotation represented by the rotation \a rotation
* to \c *this and returns a reference to \c *this.
*
* See rotate() for further details.
*
* \sa rotate()
*/
template<typename Scalar, int Dim, int Mode, int Options>
template<typename RotationType>
EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
Transform<Scalar,Dim,Mode,Options>::prerotate(const RotationType& rotation)
{
m_matrix.template block<Dim,HDim>(0,0) = internal::toRotationMatrix<Scalar,Dim>(rotation)
* m_matrix.template block<Dim,HDim>(0,0);
return *this;
}
/** Applies on the right the shear transformation represented
* by the vector \a other to \c *this and returns a reference to \c *this.
* \warning 2D only.
* \sa preshear()
*/
template<typename Scalar, int Dim, int Mode, int Options>
EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
Transform<Scalar,Dim,Mode,Options>::shear(const Scalar& sx, const Scalar& sy)
{
EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
VectorType tmp = linear().col(0)*sy + linear().col(1);
linear() << linear().col(0) + linear().col(1)*sx, tmp;
return *this;
}
/** Applies on the left the shear transformation represented
* by the vector \a other to \c *this and returns a reference to \c *this.
* \warning 2D only.
* \sa shear()
*/
template<typename Scalar, int Dim, int Mode, int Options>
EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
Transform<Scalar,Dim,Mode,Options>::preshear(const Scalar& sx, const Scalar& sy)
{
EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
m_matrix.template block<Dim,HDim>(0,0) = LinearMatrixType(1, sx, sy, 1) * m_matrix.template block<Dim,HDim>(0,0);
return *this;
}
/******************************************************
*** Scaling, Translation and Rotation compatibility ***
******************************************************/
template<typename Scalar, int Dim, int Mode, int Options>
EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const TranslationType& t)
{
linear().setIdentity();
translation() = t.vector();
makeAffine();
return *this;
}
template<typename Scalar, int Dim, int Mode, int Options>
EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options> Transform<Scalar,Dim,Mode,Options>::operator*(const TranslationType& t) const
{
Transform res = *this;
res.translate(t.vector());
return res;
}
template<typename Scalar, int Dim, int Mode, int Options>
EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const UniformScaling<Scalar>& s)
{
m_matrix.setZero();
linear().diagonal().fill(s.factor());
makeAffine();
return *this;
}
template<typename Scalar, int Dim, int Mode, int Options>
template<typename Derived>
EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const RotationBase<Derived,Dim>& r)
{
linear() = internal::toRotationMatrix<Scalar,Dim>(r);
translation().setZero();
makeAffine();
return *this;
}
template<typename Scalar, int Dim, int Mode, int Options>
template<typename Derived>
EIGEN_DEVICE_FUNC inline Transform<Scalar,Dim,Mode,Options> Transform<Scalar,Dim,Mode,Options>::operator*(const RotationBase<Derived,Dim>& r) const
{
Transform res = *this;
res.rotate(r.derived());
return res;
}
/************************
*** Special functions ***
************************/
/** \returns the rotation part of the transformation
*
*
* \svd_module
*
* \sa computeRotationScaling(), computeScalingRotation(), class SVD
*/
template<typename Scalar, int Dim, int Mode, int Options>
EIGEN_DEVICE_FUNC const typename Transform<Scalar,Dim,Mode,Options>::LinearMatrixType
Transform<Scalar,Dim,Mode,Options>::rotation() const
{
LinearMatrixType result;
computeRotationScaling(&result, (LinearMatrixType*)0);
return result;
}
/** decomposes the linear part of the transformation as a product rotation x scaling, the scaling being
* not necessarily positive.
*
* If either pointer is zero, the corresponding computation is skipped.
*
*
*
* \svd_module
*
* \sa computeScalingRotation(), rotation(), class SVD
*/
template<typename Scalar, int Dim, int Mode, int Options>
template<typename RotationMatrixType, typename ScalingMatrixType>
EIGEN_DEVICE_FUNC void Transform<Scalar,Dim,Mode,Options>::computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const
{
JacobiSVD<LinearMatrixType> svd(linear(), ComputeFullU | ComputeFullV);
Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1
VectorType sv(svd.singularValues());
sv.coeffRef(0) *= x;
if(scaling) scaling->lazyAssign(svd.matrixV() * sv.asDiagonal() * svd.matrixV().adjoint());
if(rotation)
{
LinearMatrixType m(svd.matrixU());
m.col(0) /= x;
rotation->lazyAssign(m * svd.matrixV().adjoint());
}
}
/** decomposes the linear part of the transformation as a product scaling x rotation, the scaling being
* not necessarily positive.
*
* If either pointer is zero, the corresponding computation is skipped.
*
*
*
* \svd_module
*
* \sa computeRotationScaling(), rotation(), class SVD
*/
template<typename Scalar, int Dim, int Mode, int Options>
template<typename ScalingMatrixType, typename RotationMatrixType>
EIGEN_DEVICE_FUNC void Transform<Scalar,Dim,Mode,Options>::computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const
{
JacobiSVD<LinearMatrixType> svd(linear(), ComputeFullU | ComputeFullV);
Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1
VectorType sv(svd.singularValues());
sv.coeffRef(0) *= x;
if(scaling) scaling->lazyAssign(svd.matrixU() * sv.asDiagonal() * svd.matrixU().adjoint());
if(rotation)
{
LinearMatrixType m(svd.matrixU());
m.col(0) /= x;
rotation->lazyAssign(m * svd.matrixV().adjoint());
}
}
/** Convenient method to set \c *this from a position, orientation and scale
* of a 3D object.
*/
template<typename Scalar, int Dim, int Mode, int Options>
template<typename PositionDerived, typename OrientationType, typename ScaleDerived>
EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>&
Transform<Scalar,Dim,Mode,Options>::fromPositionOrientationScale(const MatrixBase<PositionDerived> &position,
const OrientationType& orientation, const MatrixBase<ScaleDerived> &scale)
{
linear() = internal::toRotationMatrix<Scalar,Dim>(orientation);
linear() *= scale.asDiagonal();
translation() = position;
makeAffine();
return *this;
}
namespace internal {
template<int Mode>
struct transform_make_affine
{
template<typename MatrixType>
EIGEN_DEVICE_FUNC static void run(MatrixType &mat)
{
static const int Dim = MatrixType::ColsAtCompileTime-1;
mat.template block<1,Dim>(Dim,0).setZero();
mat.coeffRef(Dim,Dim) = typename MatrixType::Scalar(1);
}
};
template<>
struct transform_make_affine<AffineCompact>
{
template<typename MatrixType> EIGEN_DEVICE_FUNC static void run(MatrixType &) { }
};
// selector needed to avoid taking the inverse of a 3x4 matrix
template<typename TransformType, int Mode=TransformType::Mode>
struct projective_transform_inverse
{
EIGEN_DEVICE_FUNC static inline void run(const TransformType&, TransformType&)
{}
};
template<typename TransformType>
struct projective_transform_inverse<TransformType, Projective>
{
EIGEN_DEVICE_FUNC static inline void run(const TransformType& m, TransformType& res)
{
res.matrix() = m.matrix().inverse();
}
};
} // end namespace internal
/**
*
* \returns the inverse transformation according to some given knowledge
* on \c *this.
*
* \param hint allows to optimize the inversion process when the transformation
* is known to be not a general transformation (optional). The possible values are:
* - #Projective if the transformation is not necessarily affine, i.e., if the
* last row is not guaranteed to be [0 ... 0 1]
* - #Affine if the last row can be assumed to be [0 ... 0 1]
* - #Isometry if the transformation is only a concatenations of translations
* and rotations.
* The default is the template class parameter \c Mode.
*
* \warning unless \a traits is always set to NoShear or NoScaling, this function
* requires the generic inverse method of MatrixBase defined in the LU module. If
* you forget to include this module, then you will get hard to debug linking errors.
*
* \sa MatrixBase::inverse()
*/
template<typename Scalar, int Dim, int Mode, int Options>
EIGEN_DEVICE_FUNC Transform<Scalar,Dim,Mode,Options>
Transform<Scalar,Dim,Mode,Options>::inverse(TransformTraits hint) const
{
Transform res;
if (hint == Projective)
{
internal::projective_transform_inverse<Transform>::run(*this, res);
}
else
{
if (hint == Isometry)
{
res.matrix().template topLeftCorner<Dim,Dim>() = linear().transpose();
}
else if(hint&Affine)
{
res.matrix().template topLeftCorner<Dim,Dim>() = linear().inverse();
}
else
{
eigen_assert(false && "Invalid transform traits in Transform::Inverse");
}
// translation and remaining parts
res.matrix().template topRightCorner<Dim,1>()
= - res.matrix().template topLeftCorner<Dim,Dim>() * translation();
res.makeAffine(); // we do need this, because in the beginning res is uninitialized
}
return res;
}
namespace internal {
/*****************************************************
*** Specializations of take affine part ***
*****************************************************/
template<typename TransformType> struct transform_take_affine_part {
typedef typename TransformType::MatrixType MatrixType;
typedef typename TransformType::AffinePart AffinePart;
typedef typename TransformType::ConstAffinePart ConstAffinePart;
static inline AffinePart run(MatrixType& m)
{ return m.template block<TransformType::Dim,TransformType::HDim>(0,0); }
static inline ConstAffinePart run(const MatrixType& m)
{ return m.template block<TransformType::Dim,TransformType::HDim>(0,0); }
};
template<typename Scalar, int Dim, int Options>
struct transform_take_affine_part<Transform<Scalar,Dim,AffineCompact, Options> > {
typedef typename Transform<Scalar,Dim,AffineCompact,Options>::MatrixType MatrixType;
static inline MatrixType& run(MatrixType& m) { return m; }
static inline const MatrixType& run(const MatrixType& m) { return m; }
};
/*****************************************************
*** Specializations of construct from matrix ***
*****************************************************/
template<typename Other, int Mode, int Options, int Dim, int HDim>
struct transform_construct_from_matrix<Other, Mode,Options,Dim,HDim, Dim,Dim>
{
static inline void run(Transform<typename Other::Scalar,Dim,Mode,Options> *transform, const Other& other)
{
transform->linear() = other;
transform->translation().setZero();
transform->makeAffine();
}
};
template<typename Other, int Mode, int Options, int Dim, int HDim>
struct transform_construct_from_matrix<Other, Mode,Options,Dim,HDim, Dim,HDim>
{
static inline void run(Transform<typename Other::Scalar,Dim,Mode,Options> *transform, const Other& other)
{
transform->affine() = other;
transform->makeAffine();
}
};
template<typename Other, int Mode, int Options, int Dim, int HDim>
struct transform_construct_from_matrix<Other, Mode,Options,Dim,HDim, HDim,HDim>
{
static inline void run(Transform<typename Other::Scalar,Dim,Mode,Options> *transform, const Other& other)
{ transform->matrix() = other; }
};
template<typename Other, int Options, int Dim, int HDim>
struct transform_construct_from_matrix<Other, AffineCompact,Options,Dim,HDim, HDim,HDim>
{
static inline void run(Transform<typename Other::Scalar,Dim,AffineCompact,Options> *transform, const Other& other)
{ transform->matrix() = other.template block<Dim,HDim>(0,0); }
};
/**********************************************************
*** Specializations of operator* with rhs EigenBase ***
**********************************************************/
template<int LhsMode,int RhsMode>
struct transform_product_result
{
enum
{
Mode =
(LhsMode == (int)Projective || RhsMode == (int)Projective ) ? Projective :
(LhsMode == (int)Affine || RhsMode == (int)Affine ) ? Affine :
(LhsMode == (int)AffineCompact || RhsMode == (int)AffineCompact ) ? AffineCompact :
(LhsMode == (int)Isometry || RhsMode == (int)Isometry ) ? Isometry : Projective
};
};
template< typename TransformType, typename MatrixType, int RhsCols>
struct transform_right_product_impl< TransformType, MatrixType, 0, RhsCols>
{
typedef typename MatrixType::PlainObject ResultType;
static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other)
{
return T.matrix() * other;
}
};
template< typename TransformType, typename MatrixType, int RhsCols>
struct transform_right_product_impl< TransformType, MatrixType, 1, RhsCols>
{
enum {
Dim = TransformType::Dim,
HDim = TransformType::HDim,
OtherRows = MatrixType::RowsAtCompileTime,
OtherCols = MatrixType::ColsAtCompileTime
};
typedef typename MatrixType::PlainObject ResultType;
static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other)
{
EIGEN_STATIC_ASSERT(OtherRows==HDim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES);
typedef Block<ResultType, Dim, OtherCols, int(MatrixType::RowsAtCompileTime)==Dim> TopLeftLhs;
ResultType res(other.rows(),other.cols());
TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() = T.affine() * other;
res.row(OtherRows-1) = other.row(OtherRows-1);
return res;
}
};
template< typename TransformType, typename MatrixType, int RhsCols>
struct transform_right_product_impl< TransformType, MatrixType, 2, RhsCols>
{
enum {
Dim = TransformType::Dim,
HDim = TransformType::HDim,
OtherRows = MatrixType::RowsAtCompileTime,
OtherCols = MatrixType::ColsAtCompileTime
};
typedef typename MatrixType::PlainObject ResultType;
static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other)
{
EIGEN_STATIC_ASSERT(OtherRows==Dim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES);
typedef Block<ResultType, Dim, OtherCols, true> TopLeftLhs;
ResultType res(Replicate<typename TransformType::ConstTranslationPart, 1, OtherCols>(T.translation(),1,other.cols()));
TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() += T.linear() * other;
return res;
}
};
template< typename TransformType, typename MatrixType >
struct transform_right_product_impl< TransformType, MatrixType, 2, 1> // rhs is a vector of size Dim
{
typedef typename TransformType::MatrixType TransformMatrix;
enum {
Dim = TransformType::Dim,
HDim = TransformType::HDim,
OtherRows = MatrixType::RowsAtCompileTime,
WorkingRows = EIGEN_PLAIN_ENUM_MIN(TransformMatrix::RowsAtCompileTime,HDim)
};
typedef typename MatrixType::PlainObject ResultType;
static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other)
{
EIGEN_STATIC_ASSERT(OtherRows==Dim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES);
Matrix<typename ResultType::Scalar, Dim+1, 1> rhs;
rhs.template head<Dim>() = other; rhs[Dim] = typename ResultType::Scalar(1);
Matrix<typename ResultType::Scalar, WorkingRows, 1> res(T.matrix() * rhs);
return res.template head<Dim>();
}
};
/**********************************************************
*** Specializations of operator* with lhs EigenBase ***
**********************************************************/
// generic HDim x HDim matrix * T => Projective
template<typename Other,int Mode, int Options, int Dim, int HDim>
struct transform_left_product_impl<Other,Mode,Options,Dim,HDim, HDim,HDim>
{
typedef Transform<typename Other::Scalar,Dim,Mode,Options> TransformType;
typedef typename TransformType::MatrixType MatrixType;
typedef Transform<typename Other::Scalar,Dim,Projective,Options> ResultType;
static ResultType run(const Other& other,const TransformType& tr)
{ return ResultType(other * tr.matrix()); }
};
// generic HDim x HDim matrix * AffineCompact => Projective
template<typename Other, int Options, int Dim, int HDim>
struct transform_left_product_impl<Other,AffineCompact,Options,Dim,HDim, HDim,HDim>
{
typedef Transform<typename Other::Scalar,Dim,AffineCompact,Options> TransformType;
typedef typename TransformType::MatrixType MatrixType;
typedef Transform<typename Other::Scalar,Dim,Projective,Options> ResultType;
static ResultType run(const Other& other,const TransformType& tr)
{
ResultType res;
res.matrix().noalias() = other.template block<HDim,Dim>(0,0) * tr.matrix();
res.matrix().col(Dim) += other.col(Dim);
return res;
}
};
// affine matrix * T
template<typename Other,int Mode, int Options, int Dim, int HDim>
struct transform_left_product_impl<Other,Mode,Options,Dim,HDim, Dim,HDim>
{
typedef Transform<typename Other::Scalar,Dim,Mode,Options> TransformType;
typedef typename TransformType::MatrixType MatrixType;
typedef TransformType ResultType;
static ResultType run(const Other& other,const TransformType& tr)
{
ResultType res;
res.affine().noalias() = other * tr.matrix();
res.matrix().row(Dim) = tr.matrix().row(Dim);
return res;
}
};
// affine matrix * AffineCompact
template<typename Other, int Options, int Dim, int HDim>
struct transform_left_product_impl<Other,AffineCompact,Options,Dim,HDim, Dim,HDim>
{
typedef Transform<typename Other::Scalar,Dim,AffineCompact,Options> TransformType;
typedef typename TransformType::MatrixType MatrixType;
typedef TransformType ResultType;
static ResultType run(const Other& other,const TransformType& tr)
{
ResultType res;
res.matrix().noalias() = other.template block<Dim,Dim>(0,0) * tr.matrix();
res.translation() += other.col(Dim);
return res;
}
};
// linear matrix * T
template<typename Other,int Mode, int Options, int Dim, int HDim>
struct transform_left_product_impl<Other,Mode,Options,Dim,HDim, Dim,Dim>
{
typedef Transform<typename Other::Scalar,Dim,Mode,Options> TransformType;
typedef typename TransformType::MatrixType MatrixType;
typedef TransformType ResultType;
static ResultType run(const Other& other, const TransformType& tr)
{
TransformType res;
if(Mode!=int(AffineCompact))
res.matrix().row(Dim) = tr.matrix().row(Dim);
res.matrix().template topRows<Dim>().noalias()
= other * tr.matrix().template topRows<Dim>();
return res;
}
};
/**********************************************************
*** Specializations of operator* with another Transform ***
**********************************************************/
template<typename Scalar, int Dim, int LhsMode, int LhsOptions, int RhsMode, int RhsOptions>
struct transform_transform_product_impl<Transform<Scalar,Dim,LhsMode,LhsOptions>,Transform<Scalar,Dim,RhsMode,RhsOptions>,false >
{
enum { ResultMode = transform_product_result<LhsMode,RhsMode>::Mode };
typedef Transform<Scalar,Dim,LhsMode,LhsOptions> Lhs;
typedef Transform<Scalar,Dim,RhsMode,RhsOptions> Rhs;
typedef Transform<Scalar,Dim,ResultMode,LhsOptions> ResultType;
static ResultType run(const Lhs& lhs, const Rhs& rhs)
{
ResultType res;
res.linear() = lhs.linear() * rhs.linear();
res.translation() = lhs.linear() * rhs.translation() + lhs.translation();
res.makeAffine();
return res;
}
};
template<typename Scalar, int Dim, int LhsMode, int LhsOptions, int RhsMode, int RhsOptions>
struct transform_transform_product_impl<Transform<Scalar,Dim,LhsMode,LhsOptions>,Transform<Scalar,Dim,RhsMode,RhsOptions>,true >
{
typedef Transform<Scalar,Dim,LhsMode,LhsOptions> Lhs;
typedef Transform<Scalar,Dim,RhsMode,RhsOptions> Rhs;
typedef Transform<Scalar,Dim,Projective> ResultType;
static ResultType run(const Lhs& lhs, const Rhs& rhs)
{
return ResultType( lhs.matrix() * rhs.matrix() );
}
};
template<typename Scalar, int Dim, int LhsOptions, int RhsOptions>
struct transform_transform_product_impl<Transform<Scalar,Dim,AffineCompact,LhsOptions>,Transform<Scalar,Dim,Projective,RhsOptions>,true >
{
typedef Transform<Scalar,Dim,AffineCompact,LhsOptions> Lhs;
typedef Transform<Scalar,Dim,Projective,RhsOptions> Rhs;
typedef Transform<Scalar,Dim,Projective> ResultType;
static ResultType run(const Lhs& lhs, const Rhs& rhs)
{
ResultType res;
res.matrix().template topRows<Dim>() = lhs.matrix() * rhs.matrix();
res.matrix().row(Dim) = rhs.matrix().row(Dim);
return res;
}
};
template<typename Scalar, int Dim, int LhsOptions, int RhsOptions>
struct transform_transform_product_impl<Transform<Scalar,Dim,Projective,LhsOptions>,Transform<Scalar,Dim,AffineCompact,RhsOptions>,true >
{
typedef Transform<Scalar,Dim,Projective,LhsOptions> Lhs;
typedef Transform<Scalar,Dim,AffineCompact,RhsOptions> Rhs;
typedef Transform<Scalar,Dim,Projective> ResultType;
static ResultType run(const Lhs& lhs, const Rhs& rhs)
{
ResultType res(lhs.matrix().template leftCols<Dim>() * rhs.matrix());
res.matrix().col(Dim) += lhs.matrix().col(Dim);
return res;
}
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_TRANSFORM_H
|