eigen-allocator.hpp
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1 //
2 // Copyright (c) 2014-2023 CNRS INRIA
3 //
4 
5 #ifndef __eigenpy_eigen_allocator_hpp__
6 #define __eigenpy_eigen_allocator_hpp__
7 
8 #include "eigenpy/fwd.hpp"
9 #include "eigenpy/numpy-map.hpp"
10 #include "eigenpy/register.hpp"
11 #include "eigenpy/scalar-conversion.hpp"
12 #include "eigenpy/utils/is-aligned.hpp"
13 
14 namespace eigenpy {
15 
16 namespace details {
17 template <typename MatType,
18  bool IsVectorAtCompileTime = MatType::IsVectorAtCompileTime>
19 struct init_matrix_or_array {
20  static MatType *run(int rows, int cols, void *storage) {
21  if (storage)
22  return new (storage) MatType(rows, cols);
23  else
24  return new MatType(rows, cols);
25  }
26 
27  static MatType *run(PyArrayObject *pyArray, void *storage = NULL) {
28  assert(PyArray_NDIM(pyArray) == 1 || PyArray_NDIM(pyArray) == 2);
29 
30  int rows = -1, cols = -1;
31  const int ndim = PyArray_NDIM(pyArray);
32  if (ndim == 2) {
33  rows = (int)PyArray_DIMS(pyArray)[0];
34  cols = (int)PyArray_DIMS(pyArray)[1];
35  } else if (ndim == 1) {
36  rows = (int)PyArray_DIMS(pyArray)[0];
37  cols = 1;
38  }
39 
40  return run(rows, cols, storage);
41  }
42 };
43 
44 template <typename MatType>
45 struct init_matrix_or_array<MatType, true> {
46  static MatType *run(int rows, int cols, void *storage) {
47  if (storage)
48  return new (storage) MatType(rows, cols);
49  else
50  return new MatType(rows, cols);
51  }
52 
53  static MatType *run(int size, void *storage) {
54  if (storage)
55  return new (storage) MatType(size);
56  else
57  return new MatType(size);
58  }
59 
60  static MatType *run(PyArrayObject *pyArray, void *storage = NULL) {
61  const int ndim = PyArray_NDIM(pyArray);
62  if (ndim == 1) {
63  const int size = (int)PyArray_DIMS(pyArray)[0];
64  return run(size, storage);
65  } else {
66  const int rows = (int)PyArray_DIMS(pyArray)[0];
67  const int cols = (int)PyArray_DIMS(pyArray)[1];
68  return run(rows, cols, storage);
69  }
70  }
71 };
72 
73 #ifdef EIGENPY_WITH_TENSOR_SUPPORT
74 template <typename Tensor>
75 struct init_tensor {
76  static Tensor *run(PyArrayObject *pyArray, void *storage = NULL) {
77  enum { Rank = Tensor::NumDimensions };
78  assert(PyArray_NDIM(pyArray) == Rank);
79  typedef typename Tensor::Index Index;
80 
81  Eigen::array<Index, Rank> dimensions;
82  for (int k = 0; k < PyArray_NDIM(pyArray); ++k)
83  dimensions[k] = PyArray_DIMS(pyArray)[k];
84 
85  if (storage)
86  return new (storage) Tensor(dimensions);
87  else
88  return new Tensor(dimensions);
89  }
90 };
91 #endif
92 
93 template <typename MatType>
94 struct check_swap_impl_matrix;
95 
96 template <typename EigenType,
97  typename BaseType = typename get_eigen_base_type<EigenType>::type>
98 struct check_swap_impl;
99 
100 template <typename MatType>
101 struct check_swap_impl<MatType, Eigen::MatrixBase<MatType> >
102  : check_swap_impl_matrix<MatType> {};
103 
104 template <typename MatType>
105 struct check_swap_impl_matrix {
106  static bool run(PyArrayObject *pyArray,
107  const Eigen::MatrixBase<MatType> &mat) {
108  if (PyArray_NDIM(pyArray) == 0) return false;
109  if (mat.rows() == PyArray_DIMS(pyArray)[0])
110  return false;
111  else
112  return true;
113  }
114 };
115 
116 template <typename EigenType>
117 bool check_swap(PyArrayObject *pyArray, const EigenType &mat) {
118  return check_swap_impl<EigenType>::run(pyArray, mat);
119 }
120 
121 #ifdef EIGENPY_WITH_TENSOR_SUPPORT
122 template <typename TensorType>
123 struct check_swap_impl_tensor {
124  static bool run(PyArrayObject * /*pyArray*/, const TensorType & /*tensor*/) {
125  return false;
126  }
127 };
128 
129 template <typename TensorType>
130 struct check_swap_impl<TensorType, Eigen::TensorBase<TensorType> >
131  : check_swap_impl_tensor<TensorType> {};
132 #endif
133 
134 // template <typename MatType>
135 // struct cast_impl_matrix;
136 //
137 // template <typename EigenType,
138 // typename BaseType = typename get_eigen_base_type<EigenType>::type>
139 // struct cast_impl;
140 //
141 // template <typename MatType>
142 // struct cast_impl<MatType, Eigen::MatrixBase<MatType> >
143 // : cast_impl_matrix<MatType> {};
144 //
145 // template <typename MatType>
146 // struct cast_impl_matrix
147 //{
148 // template <typename NewScalar, typename MatrixIn, typename MatrixOut>
149 // static void run(const Eigen::MatrixBase<MatrixIn> &input,
150 // const Eigen::MatrixBase<MatrixOut> &dest) {
151 // dest.const_cast_derived() = input.template cast<NewScalar>();
152 // }
153 // };
154 
155 template <typename Scalar, typename NewScalar,
156  template <typename D> class EigenBase = Eigen::MatrixBase,
157  bool cast_is_valid = FromTypeToType<Scalar, NewScalar>::value>
158 struct cast {
159  template <typename MatrixIn, typename MatrixOut>
160  static void run(const Eigen::MatrixBase<MatrixIn> &input,
161  const Eigen::MatrixBase<MatrixOut> &dest) {
162  dest.const_cast_derived() = input.template cast<NewScalar>();
163  }
164 };
165 
166 #ifdef EIGENPY_WITH_TENSOR_SUPPORT
167 template <typename Scalar, typename NewScalar>
168 struct cast<Scalar, NewScalar, Eigen::TensorRef, true> {
169  template <typename TensorIn, typename TensorOut>
170  static void run(const TensorIn &input, TensorOut &dest) {
171  dest = input.template cast<NewScalar>();
172  }
173 };
174 #endif
175 
176 template <typename Scalar, typename NewScalar,
177  template <typename D> class EigenBase>
178 struct cast<Scalar, NewScalar, EigenBase, false> {
179  template <typename MatrixIn, typename MatrixOut>
180  static void run(const MatrixIn /*input*/, const MatrixOut /*dest*/) {
181  // do nothing
182  assert(false && "Must never happened");
183  }
184 };
185 
186 } // namespace details
187 
188 #define EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType, Scalar, NewScalar, \
189  pyArray, mat) \
190  details::cast<Scalar, NewScalar>::run( \
191  NumpyMap<MatType, Scalar>::map(pyArray, \
192  details::check_swap(pyArray, mat)), \
193  mat)
194 
195 #define EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType, Scalar, NewScalar, \
196  mat, pyArray) \
197  details::cast<Scalar, NewScalar>::run( \
198  mat, NumpyMap<MatType, NewScalar>::map( \
199  pyArray, details::check_swap(pyArray, mat)))
200 
201 // Define specific cast for Windows and Mac
202 #if defined _WIN32 || defined __CYGWIN__
203 // Manage NPY_INT on Windows (NPY_INT32 is NPY_LONG).
204 // See https://github.com/stack-of-tasks/eigenpy/pull/455
205 #define EIGENPY_CAST_FROM_NUMPY_TO_EIGEN_SWITCH_OS_SPECIFIC( \
206  MatType, Scalar, pyArray, mat, CAST_MACRO) \
207  case NPY_INT: \
208  CAST_MACRO(MatType, int32_t, Scalar, pyArray, mat); \
209  break; \
210  case NPY_UINT: \
211  CAST_MACRO(MatType, uint32_t, Scalar, pyArray, mat); \
212  break;
213 #elif defined __APPLE__
214 // Manage NPY_LONGLONG on Mac (NPY_INT64 is NPY_LONG).
215 // long long and long are both the same type
216 // but NPY_LONGLONG and NPY_LONG are different dtype.
217 // See https://github.com/stack-of-tasks/eigenpy/pull/455
218 #define EIGENPY_CAST_FROM_NUMPY_TO_EIGEN_SWITCH_OS_SPECIFIC( \
219  MatType, Scalar, pyArray, mat, CAST_MACRO) \
220  case NPY_LONGLONG: \
221  CAST_MACRO(MatType, int64_t, Scalar, pyArray, mat); \
222  break; \
223  case NPY_ULONGLONG: \
224  CAST_MACRO(MatType, uint64_t, Scalar, pyArray, mat); \
225  break;
226 #else
227 #define EIGENPY_CAST_FROM_NUMPY_TO_EIGEN_SWITCH_OS_SPECIFIC( \
228  MatType, Scalar, pyArray, mat, CAST_MACRO)
229 #endif
230 
232 #define EIGENPY_CAST_FROM_NUMPY_TO_EIGEN_SWITCH( \
233  pyArray_type_code, MatType, Scalar, pyArray, mat, CAST_MACRO) \
234  switch (pyArray_type_code) { \
235  case NPY_BOOL: \
236  CAST_MACRO(MatType, bool, Scalar, pyArray, mat); \
237  break; \
238  case NPY_INT8: \
239  CAST_MACRO(MatType, int8_t, Scalar, pyArray, mat); \
240  break; \
241  case NPY_INT16: \
242  CAST_MACRO(MatType, int16_t, Scalar, pyArray, mat); \
243  break; \
244  case NPY_INT32: \
245  CAST_MACRO(MatType, int32_t, Scalar, pyArray, mat); \
246  break; \
247  case NPY_INT64: \
248  CAST_MACRO(MatType, int64_t, Scalar, pyArray, mat); \
249  break; \
250  case NPY_UINT8: \
251  CAST_MACRO(MatType, uint8_t, Scalar, pyArray, mat); \
252  break; \
253  case NPY_UINT16: \
254  CAST_MACRO(MatType, uint16_t, Scalar, pyArray, mat); \
255  break; \
256  case NPY_UINT32: \
257  CAST_MACRO(MatType, uint32_t, Scalar, pyArray, mat); \
258  break; \
259  case NPY_UINT64: \
260  CAST_MACRO(MatType, uint64_t, Scalar, pyArray, mat); \
261  break; \
262  case NPY_FLOAT: \
263  CAST_MACRO(MatType, float, Scalar, pyArray, mat); \
264  break; \
265  case NPY_CFLOAT: \
266  CAST_MACRO(MatType, std::complex<float>, Scalar, pyArray, mat); \
267  break; \
268  case NPY_DOUBLE: \
269  CAST_MACRO(MatType, double, Scalar, pyArray, mat); \
270  break; \
271  case NPY_CDOUBLE: \
272  CAST_MACRO(MatType, std::complex<double>, Scalar, pyArray, mat); \
273  break; \
274  case NPY_LONGDOUBLE: \
275  CAST_MACRO(MatType, long double, Scalar, pyArray, mat); \
276  break; \
277  case NPY_CLONGDOUBLE: \
278  CAST_MACRO(MatType, std::complex<long double>, Scalar, pyArray, mat); \
279  break; \
280  EIGENPY_CAST_FROM_NUMPY_TO_EIGEN_SWITCH_OS_SPECIFIC( \
281  MatType, Scalar, pyArray, mat, CAST_MACRO) \
282  default: \
283  throw Exception("You asked for a conversion which is not implemented."); \
284  }
285 
286 template <typename EigenType>
287 struct EigenAllocator;
288 
289 template <typename EigenType,
290  typename BaseType = typename get_eigen_base_type<EigenType>::type>
291 struct eigen_allocator_impl;
292 
293 template <typename MatType>
294 struct eigen_allocator_impl_matrix;
295 
296 template <typename MatType>
297 struct eigen_allocator_impl<MatType, Eigen::MatrixBase<MatType> >
298  : eigen_allocator_impl_matrix<MatType> {};
299 
300 template <typename MatType>
301 struct eigen_allocator_impl<const MatType, const Eigen::MatrixBase<MatType> >
302  : eigen_allocator_impl_matrix<const MatType> {};
303 
304 template <typename MatType>
305 struct eigen_allocator_impl_matrix {
306  typedef MatType Type;
307  typedef typename MatType::Scalar Scalar;
308 
309  static void allocate(
310  PyArrayObject *pyArray,
311  boost::python::converter::rvalue_from_python_storage<MatType> *storage) {
312  void *raw_ptr = storage->storage.bytes;
313  assert(is_aligned(raw_ptr, EIGENPY_DEFAULT_ALIGN_BYTES) &&
314  "The pointer is not aligned.");
315 
316  Type *mat_ptr = details::init_matrix_or_array<Type>::run(pyArray, raw_ptr);
317  Type &mat = *mat_ptr;
318 
319  copy(pyArray, mat);
320  }
321 
323  template <typename MatrixDerived>
324  static void copy(PyArrayObject *pyArray,
325  const Eigen::MatrixBase<MatrixDerived> &mat_) {
326  MatrixDerived &mat = mat_.const_cast_derived();
327  const int pyArray_type_code = EIGENPY_GET_PY_ARRAY_TYPE(pyArray);
328  const int Scalar_type_code = Register::getTypeCode<Scalar>();
329 
330  if (pyArray_type_code == Scalar_type_code) {
331  mat = NumpyMap<MatType, Scalar>::map(
332  pyArray, details::check_swap(pyArray, mat)); // avoid useless cast
333  return;
334  }
335  EIGENPY_CAST_FROM_NUMPY_TO_EIGEN_SWITCH(
336  pyArray_type_code, MatType, Scalar, pyArray, mat,
337  EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX);
338  }
339 
341  template <typename MatrixDerived>
342  static void copy(const Eigen::MatrixBase<MatrixDerived> &mat_,
343  PyArrayObject *pyArray) {
344  const MatrixDerived &mat =
345  const_cast<const MatrixDerived &>(mat_.derived());
346  const int pyArray_type_code = EIGENPY_GET_PY_ARRAY_TYPE(pyArray);
347  const int Scalar_type_code = Register::getTypeCode<Scalar>();
348 
349  if (pyArray_type_code == Scalar_type_code) // no cast needed
350  {
351  NumpyMap<MatType, Scalar>::map(pyArray,
352  details::check_swap(pyArray, mat)) = mat;
353  return;
354  }
355  throw Exception(
356  "Scalar conversion from Eigen to Numpy is not implemented.");
357  }
358 };
359 
360 #ifdef EIGENPY_WITH_TENSOR_SUPPORT
361 template <typename TensorType>
362 struct eigen_allocator_impl_tensor;
363 
364 template <typename TensorType>
365 struct eigen_allocator_impl<TensorType, Eigen::TensorBase<TensorType> >
366  : eigen_allocator_impl_tensor<TensorType> {};
367 
368 template <typename TensorType>
369 struct eigen_allocator_impl<const TensorType,
370  const Eigen::TensorBase<TensorType> >
371  : eigen_allocator_impl_tensor<const TensorType> {};
372 
373 template <typename TensorType>
374 struct eigen_allocator_impl_tensor {
375  typedef typename TensorType::Scalar Scalar;
376  static void allocate(
377  PyArrayObject *pyArray,
378  boost::python::converter::rvalue_from_python_storage<TensorType>
379  *storage) {
380  void *raw_ptr = storage->storage.bytes;
381  assert(is_aligned(raw_ptr, EIGENPY_DEFAULT_ALIGN_BYTES) &&
382  "The pointer is not aligned.");
383 
384  TensorType *tensor_ptr =
385  details::init_tensor<TensorType>::run(pyArray, raw_ptr);
386  TensorType &tensor = *tensor_ptr;
387 
388  copy(pyArray, tensor);
389  }
390 
391 #define EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_TENSOR(TensorType, Scalar, \
392  NewScalar, pyArray, tensor) \
393  { \
394  typename NumpyMap<TensorType, Scalar>::EigenMap pyArray_map = \
395  NumpyMap<TensorType, Scalar>::map( \
396  pyArray, details::check_swap(pyArray, tensor)); \
397  details::cast<Scalar, NewScalar, Eigen::TensorRef>::run(pyArray_map, \
398  tensor); \
399  }
400 
402  template <typename TensorDerived>
403  static void copy(PyArrayObject *pyArray, TensorDerived &tensor) {
404  const int pyArray_type_code = EIGENPY_GET_PY_ARRAY_TYPE(pyArray);
405  const int Scalar_type_code = Register::getTypeCode<Scalar>();
406 
407  if (pyArray_type_code == Scalar_type_code) {
408  tensor = NumpyMap<TensorType, Scalar>::map(
409  pyArray, details::check_swap(pyArray, tensor)); // avoid useless cast
410  return;
411  }
412 
413  EIGENPY_CAST_FROM_NUMPY_TO_EIGEN_SWITCH(
414  pyArray_type_code, TensorType, Scalar, pyArray, tensor,
415  EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_TENSOR);
416  }
417 
418 #define EIGENPY_CAST_FROM_EIGEN_TENSOR_TO_PYARRAY(TensorType, Scalar, \
419  NewScalar, tensor, pyArray) \
420  { \
421  typename NumpyMap<TensorType, NewScalar>::EigenMap pyArray_map = \
422  NumpyMap<TensorType, NewScalar>::map( \
423  pyArray, details::check_swap(pyArray, tensor)); \
424  details::cast<Scalar, NewScalar, Eigen::TensorRef>::run(tensor, \
425  pyArray_map); \
426  }
427 
429  static void copy(const TensorType &tensor, PyArrayObject *pyArray) {
430  const int pyArray_type_code = EIGENPY_GET_PY_ARRAY_TYPE(pyArray);
431  const int Scalar_type_code = Register::getTypeCode<Scalar>();
432 
433  if (pyArray_type_code == Scalar_type_code) // no cast needed
434  {
435  NumpyMap<TensorType, Scalar>::map(
436  pyArray, details::check_swap(pyArray, tensor)) = tensor;
437  return;
438  }
439 
440  throw Exception(
441  "Scalar conversion from Eigen to Numpy is not implemented.");
442  }
443 };
444 #endif
445 
446 #if EIGEN_VERSION_AT_LEAST(3, 2, 0)
447 template <typename MatType>
455 inline bool is_arr_layout_compatible_with_mat_type(PyArrayObject *pyArray) {
456  bool is_array_C_cont = PyArray_IS_C_CONTIGUOUS(pyArray);
457  bool is_array_F_cont = PyArray_IS_F_CONTIGUOUS(pyArray);
458  return (MatType::IsRowMajor && is_array_C_cont) ||
459  (!MatType::IsRowMajor && is_array_F_cont) ||
460  (MatType::IsVectorAtCompileTime &&
461  (is_array_C_cont || is_array_F_cont));
462 }
463 
464 template <typename MatType, int Options, typename Stride>
465 struct eigen_allocator_impl_matrix<Eigen::Ref<MatType, Options, Stride> > {
466  typedef Eigen::Ref<MatType, Options, Stride> RefType;
467  typedef typename MatType::Scalar Scalar;
468 
469  typedef
470  typename ::boost::python::detail::referent_storage<RefType &>::StorageType
471  StorageType;
472 
473  static void allocate(
474  PyArrayObject *pyArray,
475  ::boost::python::converter::rvalue_from_python_storage<RefType>
476  *storage) {
477  typedef typename StrideType<
478  MatType,
479  Eigen::internal::traits<RefType>::StrideType::InnerStrideAtCompileTime,
480  Eigen::internal::traits<RefType>::StrideType::
481  OuterStrideAtCompileTime>::type NumpyMapStride;
482 
483  bool need_to_allocate = false;
484  const int pyArray_type_code = EIGENPY_GET_PY_ARRAY_TYPE(pyArray);
485  const int Scalar_type_code = Register::getTypeCode<Scalar>();
486  if (pyArray_type_code != Scalar_type_code) need_to_allocate |= true;
487  bool incompatible_layout =
488  !is_arr_layout_compatible_with_mat_type<MatType>(pyArray);
489  need_to_allocate |= incompatible_layout;
490  if (Options !=
491  Eigen::Unaligned) // we need to check whether the memory is correctly
492  // aligned and composed of a continuous segment
493  {
494  void *data_ptr = PyArray_DATA(pyArray);
495  if (!PyArray_ISONESEGMENT(pyArray) || !is_aligned(data_ptr, Options))
496  need_to_allocate |= true;
497  }
498 
499  void *raw_ptr = storage->storage.bytes;
500  if (need_to_allocate) {
501  MatType *mat_ptr;
502  mat_ptr = details::init_matrix_or_array<MatType>::run(pyArray);
503  RefType mat_ref(*mat_ptr);
504 
505  new (raw_ptr) StorageType(mat_ref, pyArray, mat_ptr);
506 
507  RefType &mat = *reinterpret_cast<RefType *>(raw_ptr);
508  EigenAllocator<MatType>::copy(pyArray, mat);
509  } else {
510  assert(pyArray_type_code == Scalar_type_code);
511  typename NumpyMap<MatType, Scalar, Options, NumpyMapStride>::EigenMap
512  numpyMap =
513  NumpyMap<MatType, Scalar, Options, NumpyMapStride>::map(pyArray);
514  RefType mat_ref(numpyMap);
515  new (raw_ptr) StorageType(mat_ref, pyArray);
516  }
517  }
518 
519  static void copy(RefType const &ref, PyArrayObject *pyArray) {
520  EigenAllocator<MatType>::copy(ref, pyArray);
521  }
522 };
523 
524 template <typename MatType, int Options, typename Stride>
525 struct eigen_allocator_impl_matrix<
526  const Eigen::Ref<const MatType, Options, Stride> > {
527  typedef const Eigen::Ref<const MatType, Options, Stride> RefType;
528  typedef typename MatType::Scalar Scalar;
529 
530  typedef
531  typename ::boost::python::detail::referent_storage<RefType &>::StorageType
532  StorageType;
533 
534  static void allocate(
535  PyArrayObject *pyArray,
536  ::boost::python::converter::rvalue_from_python_storage<RefType>
537  *storage) {
538  typedef typename StrideType<
539  MatType,
540  Eigen::internal::traits<RefType>::StrideType::InnerStrideAtCompileTime,
541  Eigen::internal::traits<RefType>::StrideType::
542  OuterStrideAtCompileTime>::type NumpyMapStride;
543 
544  bool need_to_allocate = false;
545  const int pyArray_type_code = EIGENPY_GET_PY_ARRAY_TYPE(pyArray);
546  const int Scalar_type_code = Register::getTypeCode<Scalar>();
547 
548  if (pyArray_type_code != Scalar_type_code) need_to_allocate |= true;
549  bool incompatible_layout =
550  !is_arr_layout_compatible_with_mat_type<MatType>(pyArray);
551  need_to_allocate |= incompatible_layout;
552  if (Options !=
553  Eigen::Unaligned) // we need to check whether the memory is correctly
554  // aligned and composed of a continuous segment
555  {
556  void *data_ptr = PyArray_DATA(pyArray);
557  if (!PyArray_ISONESEGMENT(pyArray) || !is_aligned(data_ptr, Options))
558  need_to_allocate |= true;
559  }
560 
561  void *raw_ptr = storage->storage.bytes;
562  if (need_to_allocate) {
563  MatType *mat_ptr;
564  mat_ptr = details::init_matrix_or_array<MatType>::run(pyArray);
565  RefType mat_ref(*mat_ptr);
566 
567  new (raw_ptr) StorageType(mat_ref, pyArray, mat_ptr);
568 
569  MatType &mat = *mat_ptr;
570  EigenAllocator<MatType>::copy(pyArray, mat);
571  } else {
572  assert(pyArray_type_code == Scalar_type_code);
573  typename NumpyMap<MatType, Scalar, Options, NumpyMapStride>::EigenMap
574  numpyMap =
575  NumpyMap<MatType, Scalar, Options, NumpyMapStride>::map(pyArray);
576  RefType mat_ref(numpyMap);
577  new (raw_ptr) StorageType(mat_ref, pyArray);
578  }
579  }
580 
581  static void copy(RefType const &ref, PyArrayObject *pyArray) {
582  EigenAllocator<MatType>::copy(ref, pyArray);
583  }
584 };
585 #endif
586 
587 #ifdef EIGENPY_WITH_TENSOR_SUPPORT
588 
589 template <typename TensorType, typename TensorRef>
590 struct eigen_allocator_impl_tensor_ref;
591 
592 template <typename TensorType>
593 struct eigen_allocator_impl_tensor<Eigen::TensorRef<TensorType> >
594  : eigen_allocator_impl_tensor_ref<TensorType,
595  Eigen::TensorRef<TensorType> > {};
596 
597 template <typename TensorType>
598 struct eigen_allocator_impl_tensor<const Eigen::TensorRef<const TensorType> >
599  : eigen_allocator_impl_tensor_ref<
600  const TensorType, const Eigen::TensorRef<const TensorType> > {};
601 
602 template <typename TensorType, typename RefType>
603 struct eigen_allocator_impl_tensor_ref {
604  typedef typename TensorType::Scalar Scalar;
605 
606  typedef
607  typename ::boost::python::detail::referent_storage<RefType &>::StorageType
608  StorageType;
609 
610  static void allocate(
611  PyArrayObject *pyArray,
612  ::boost::python::converter::rvalue_from_python_storage<RefType>
613  *storage) {
614  // typedef typename StrideType<
615  // MatType,
616  // Eigen::internal::traits<RefType>::StrideType::InnerStrideAtCompileTime,
617  // Eigen::internal::traits<RefType>::StrideType::
618  // OuterStrideAtCompileTime>::type NumpyMapStride;
619 
620  static const int Options = Eigen::internal::traits<TensorType>::Options;
621 
622  bool need_to_allocate = false;
623  const int pyArray_type_code = EIGENPY_GET_PY_ARRAY_TYPE(pyArray);
624  const int Scalar_type_code = Register::getTypeCode<Scalar>();
625  if (pyArray_type_code != Scalar_type_code) need_to_allocate |= true;
626  // bool incompatible_layout =
627  // !is_arr_layout_compatible_with_mat_type<MatType>(pyArray);
628  // need_to_allocate |= incompatible_layout;
629  // if (Options !=
630  // Eigen::Unaligned) // we need to check whether the memory is
631  // correctly
632  // // aligned and composed of a continuous segment
633  // {
634  // void *data_ptr = PyArray_DATA(pyArray);
635  // if (!PyArray_ISONESEGMENT(pyArray) || !is_aligned(data_ptr,
636  // Options))
637  // need_to_allocate |= true;
638  // }
639 
640  void *raw_ptr = storage->storage.bytes;
641  if (need_to_allocate) {
642  typedef typename boost::remove_const<TensorType>::type TensorTypeNonConst;
643  TensorTypeNonConst *tensor_ptr;
644  tensor_ptr = details::init_tensor<TensorTypeNonConst>::run(pyArray);
645  RefType tensor_ref(*tensor_ptr);
646 
647  new (raw_ptr) StorageType(tensor_ref, pyArray, tensor_ptr);
648 
649  TensorTypeNonConst &tensor = *tensor_ptr;
650  EigenAllocator<TensorTypeNonConst>::copy(pyArray, tensor);
651  } else {
652  assert(pyArray_type_code == Scalar_type_code);
653  typename NumpyMap<TensorType, Scalar, Options>::EigenMap numpyMap =
654  NumpyMap<TensorType, Scalar, Options>::map(pyArray);
655  RefType tensor_ref(numpyMap);
656  new (raw_ptr) StorageType(tensor_ref, pyArray);
657  }
658  }
659 
660  static void copy(RefType const &ref, PyArrayObject *pyArray) {
661  EigenAllocator<TensorType>::copy(ref, pyArray);
662  }
663 };
664 
665 #endif
666 
667 template <typename EigenType>
668 struct EigenAllocator : eigen_allocator_impl<EigenType> {};
669 
670 } // namespace eigenpy
671 
672 #endif // __eigenpy_eigen_allocator_hpp__
eigenpy::details::init_matrix_or_array::run
static MatType * run(PyArrayObject *pyArray, void *storage=NULL)
Definition: eigen-allocator.hpp:27
eigenpy::eigen_allocator_impl_matrix::copy
static void copy(const Eigen::MatrixBase< MatrixDerived > &mat_, PyArrayObject *pyArray)
Copy mat into the Python array using Eigen::Map.
Definition: eigen-allocator.hpp:342
eigenpy::details::cast< Scalar, NewScalar, EigenBase, false >::run
static void run(const MatrixIn, const MatrixOut)
Definition: eigen-allocator.hpp:180
Eigen
Definition: complex.cpp:7
eigenpy::details::init_matrix_or_array< MatType, true >::run
static MatType * run(PyArrayObject *pyArray, void *storage=NULL)
Definition: eigen-allocator.hpp:60
register.hpp
eigenpy::cast
Default cast algo to cast a From to To. Can be specialized for any types.
Definition: user-type.hpp:18
eigenpy::details::cast::run
static void run(const Eigen::MatrixBase< MatrixIn > &input, const Eigen::MatrixBase< MatrixOut > &dest)
Definition: eigen-allocator.hpp:160
EIGENPY_DEFAULT_ALIGN_BYTES
#define EIGENPY_DEFAULT_ALIGN_BYTES
Definition: fwd.hpp:106
eigenpy::details::init_matrix_or_array< MatType, true >::run
static MatType * run(int size, void *storage)
Definition: eigen-allocator.hpp:53
fwd.hpp
scalar-conversion.hpp
test_complex.rows
int rows
Definition: test_complex.py:4
ref
Eigen::TensorRef< Tensor > ref(Eigen::TensorRef< Tensor > tensor)
Definition: tensor.cpp:55
numpy-map.hpp
is-aligned.hpp
eigenpy::eigen_allocator_impl
Definition: eigen-allocator.hpp:291
eigenpy::get_eigen_base_type::type
boost::mpl::if_< boost::is_const< typename boost::remove_reference< EigenType >::type >, const _type, _type >::type type
Definition: fwd.hpp:165
eigenpy
Definition: alignment.hpp:14
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Definition: numpy-map.hpp:227
eigenpy::details::check_swap_impl
Definition: eigen-allocator.hpp:98
eigenpy::EigenAllocator
Definition: eigen-allocator.hpp:287
copy
ReturnMatrix copy(const Eigen::MatrixBase< Matrix > &mat)
Definition: matrix.cpp:131
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX
#define EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType, Scalar, NewScalar, pyArray, mat)
Definition: eigen-allocator.hpp:188
eigenpy::eigen_allocator_impl_matrix::Scalar
MatType::Scalar Scalar
Definition: eigen-allocator.hpp:307
eigenpy::details::init_matrix_or_array< MatType, true >::run
static MatType * run(int rows, int cols, void *storage)
Definition: eigen-allocator.hpp:46
test_eigen_ref.mat
mat
Definition: test_eigen_ref.py:137
eigenpy::is_aligned
bool is_aligned(const void *ptr, std::size_t alignment)
Definition: is-aligned.hpp:9
test_matrix.value
float value
Definition: test_matrix.py:161
eigenpy::details::init_matrix_or_array::run
static MatType * run(int rows, int cols, void *storage)
Definition: eigen-allocator.hpp:20
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Definition: eigen-allocator.hpp:94
eigenpy::Exception
Definition: exception.hpp:19
omniidl_be_python_with_docstring.run
def run(tree, args)
Definition: omniidl_be_python_with_docstring.py:140
eigenpy::details::cast
Definition: eigen-allocator.hpp:158
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static void copy(PyArrayObject *pyArray, const Eigen::MatrixBase< MatrixDerived > &mat_)
Copy Python array into the input matrix mat.
Definition: eigen-allocator.hpp:324
EIGENPY_GET_PY_ARRAY_TYPE
#define EIGENPY_GET_PY_ARRAY_TYPE(array)
Definition: numpy.hpp:55
eigenpy::eigen_allocator_impl_matrix::Type
MatType Type
Definition: eigen-allocator.hpp:306
eigenpy::details::check_swap_impl_matrix::run
static bool run(PyArrayObject *pyArray, const Eigen::MatrixBase< MatType > &mat)
Definition: eigen-allocator.hpp:106
EIGENPY_CAST_FROM_NUMPY_TO_EIGEN_SWITCH
#define EIGENPY_CAST_FROM_NUMPY_TO_EIGEN_SWITCH( pyArray_type_code, MatType, Scalar, pyArray, mat, CAST_MACRO)
Define casting between Numpy matrix type to Eigen type.
Definition: eigen-allocator.hpp:232
eigenpy::eigen_allocator_impl_matrix::allocate
static void allocate(PyArrayObject *pyArray, boost::python::converter::rvalue_from_python_storage< MatType > *storage)
Definition: eigen-allocator.hpp:309
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int cols
Definition: test_complex.py:5
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Definition: eigen-allocator.hpp:294
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bool check_swap(PyArrayObject *pyArray, const EigenType &mat)
Definition: eigen-allocator.hpp:117
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Definition: eigen-allocator.hpp:19

eigenpy
Author(s): Justin Carpentier, Nicolas Mansard
autogenerated on Sat Nov 2 2024 02:14:45