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1 | // Copyright Jim Bosch 2010-2012. |
2 | // Copyright Stefan Seefeld 2016. | |
3 | // Distributed under the Boost Software License, Version 1.0. | |
4 | // (See accompanying file LICENSE_1_0.txt or copy at | |
5 | // http://www.boost.org/LICENSE_1_0.txt) | |
6 | ||
7 | #ifndef boost_python_numpy_ndarray_hpp_ | |
8 | #define boost_python_numpy_ndarray_hpp_ | |
9 | ||
10 | /** | |
11 | * @brief Object manager and various utilities for numpy.ndarray. | |
12 | */ | |
13 | ||
14 | #include <boost/python.hpp> | |
15 | #include <boost/utility/enable_if.hpp> | |
16 | #include <boost/type_traits/is_integral.hpp> | |
17 | #include <boost/python/numpy/numpy_object_mgr_traits.hpp> | |
18 | #include <boost/python/numpy/dtype.hpp> | |
19 | #include <vector> | |
20 | ||
21 | namespace boost { namespace python { namespace numpy { | |
22 | ||
23 | /** | |
24 | * @brief A boost.python "object manager" (subclass of object) for numpy.ndarray. | |
25 | * | |
26 | * @todo This could have a lot more functionality (like boost::python::numeric::array). | |
27 | * Right now all that exists is what was needed to move raw data between C++ and Python. | |
28 | */ | |
29 | class ndarray : public object | |
30 | { | |
31 | ||
32 | /** | |
33 | * @brief An internal struct that's byte-compatible with PyArrayObject. | |
34 | * | |
35 | * This is just a hack to allow inline access to this stuff while hiding numpy/arrayobject.h | |
36 | * from the user. | |
37 | */ | |
38 | struct array_struct | |
39 | { | |
40 | PyObject_HEAD | |
41 | char * data; | |
42 | int nd; | |
43 | Py_intptr_t * shape; | |
44 | Py_intptr_t * strides; | |
45 | PyObject * base; | |
46 | PyObject * descr; | |
47 | int flags; | |
48 | PyObject * weakreflist; | |
49 | }; | |
50 | ||
51 | /// @brief Return the held Python object as an array_struct. | |
52 | array_struct * get_struct() const { return reinterpret_cast<array_struct*>(this->ptr()); } | |
53 | ||
54 | public: | |
55 | ||
56 | /** | |
57 | * @brief Enum to represent (some) of Numpy's internal flags. | |
58 | * | |
59 | * These don't match the actual Numpy flag values; we can't get those without including | |
60 | * numpy/arrayobject.h or copying them directly. That's very unfortunate. | |
61 | * | |
62 | * @todo I'm torn about whether this should be an enum. It's very convenient to not | |
63 | * make these simple integer values for overloading purposes, but the need to | |
64 | * define every possible combination and custom bitwise operators is ugly. | |
65 | */ | |
66 | enum bitflag | |
67 | { | |
68 | NONE=0x0, C_CONTIGUOUS=0x1, F_CONTIGUOUS=0x2, V_CONTIGUOUS=0x1|0x2, | |
69 | ALIGNED=0x4, WRITEABLE=0x8, BEHAVED=0x4|0x8, | |
70 | CARRAY_RO=0x1|0x4, CARRAY=0x1|0x4|0x8, CARRAY_MIS=0x1|0x8, | |
71 | FARRAY_RO=0x2|0x4, FARRAY=0x2|0x4|0x8, FARRAY_MIS=0x2|0x8, | |
72 | UPDATE_ALL=0x1|0x2|0x4, VARRAY=0x1|0x2|0x8, ALL=0x1|0x2|0x4|0x8 | |
73 | }; | |
74 | ||
75 | BOOST_PYTHON_FORWARD_OBJECT_CONSTRUCTORS(ndarray, object); | |
76 | ||
77 | /// @brief Return a view of the scalar with the given dtype. | |
78 | ndarray view(dtype const & dt) const; | |
79 | ||
80 | /// @brief Copy the array, cast to a specified type. | |
81 | ndarray astype(dtype const & dt) const; | |
82 | ||
83 | /// @brief Copy the scalar (deep for all non-object fields). | |
84 | ndarray copy() const; | |
85 | ||
86 | /// @brief Return the size of the nth dimension. | |
87 | Py_intptr_t shape(int n) const { return get_shape()[n]; } | |
88 | ||
89 | /// @brief Return the stride of the nth dimension. | |
90 | Py_intptr_t strides(int n) const { return get_strides()[n]; } | |
91 | ||
92 | /** | |
93 | * @brief Return the array's raw data pointer. | |
94 | * | |
95 | * This returns char so stride math works properly on it. It's pretty much | |
96 | * expected that the user will have to reinterpret_cast it. | |
97 | */ | |
98 | char * get_data() const { return get_struct()->data; } | |
99 | ||
100 | /// @brief Return the array's data-type descriptor object. | |
101 | dtype get_dtype() const; | |
102 | ||
103 | /// @brief Return the object that owns the array's data, or None if the array owns its own data. | |
104 | object get_base() const; | |
105 | ||
106 | /// @brief Set the object that owns the array's data. Use with care. | |
107 | void set_base(object const & base); | |
108 | ||
109 | /// @brief Return the shape of the array as an array of integers (length == get_nd()). | |
110 | Py_intptr_t const * get_shape() const { return get_struct()->shape; } | |
111 | ||
112 | /// @brief Return the stride of the array as an array of integers (length == get_nd()). | |
113 | Py_intptr_t const * get_strides() const { return get_struct()->strides; } | |
114 | ||
115 | /// @brief Return the number of array dimensions. | |
116 | int get_nd() const { return get_struct()->nd; } | |
117 | ||
118 | /// @brief Return the array flags. | |
119 | bitflag get_flags() const; | |
120 | ||
121 | /// @brief Reverse the dimensions of the array. | |
122 | ndarray transpose() const; | |
123 | ||
124 | /// @brief Eliminate any unit-sized dimensions. | |
125 | ndarray squeeze() const; | |
126 | ||
127 | /// @brief Equivalent to self.reshape(*shape) in Python. | |
128 | ndarray reshape(python::tuple const & shape) const; | |
129 | ||
130 | /** | |
131 | * @brief If the array contains only a single element, return it as an array scalar; otherwise return | |
132 | * the array. | |
133 | * | |
134 | * @internal This is simply a call to PyArray_Return(); | |
135 | */ | |
136 | object scalarize() const; | |
137 | }; | |
138 | ||
139 | /** | |
140 | * @brief Construct a new array with the given shape and data type, with data initialized to zero. | |
141 | */ | |
142 | ndarray zeros(python::tuple const & shape, dtype const & dt); | |
143 | ndarray zeros(int nd, Py_intptr_t const * shape, dtype const & dt); | |
144 | ||
145 | /** | |
146 | * @brief Construct a new array with the given shape and data type, with data left uninitialized. | |
147 | */ | |
148 | ndarray empty(python::tuple const & shape, dtype const & dt); | |
149 | ndarray empty(int nd, Py_intptr_t const * shape, dtype const & dt); | |
150 | ||
151 | /** | |
152 | * @brief Construct a new array from an arbitrary Python sequence. | |
153 | * | |
154 | * @todo This does't seem to handle ndarray subtypes the same way that "numpy.array" does in Python. | |
155 | */ | |
156 | ndarray array(object const & obj); | |
157 | ndarray array(object const & obj, dtype const & dt); | |
158 | ||
159 | namespace detail | |
160 | { | |
161 | ||
162 | ndarray from_data_impl(void * data, | |
163 | dtype const & dt, | |
164 | std::vector<Py_intptr_t> const & shape, | |
165 | std::vector<Py_intptr_t> const & strides, | |
166 | object const & owner, | |
167 | bool writeable); | |
168 | ||
169 | template <typename Container> | |
170 | ndarray from_data_impl(void * data, | |
171 | dtype const & dt, | |
172 | Container shape, | |
173 | Container strides, | |
174 | object const & owner, | |
175 | bool writeable, | |
176 | typename boost::enable_if< boost::is_integral<typename Container::value_type> >::type * enabled = NULL) | |
177 | { | |
178 | std::vector<Py_intptr_t> shape_(shape.begin(),shape.end()); | |
179 | std::vector<Py_intptr_t> strides_(strides.begin(), strides.end()); | |
180 | return from_data_impl(data, dt, shape_, strides_, owner, writeable); | |
181 | } | |
182 | ||
183 | ndarray from_data_impl(void * data, | |
184 | dtype const & dt, | |
185 | object const & shape, | |
186 | object const & strides, | |
187 | object const & owner, | |
188 | bool writeable); | |
189 | ||
190 | } // namespace boost::python::numpy::detail | |
191 | ||
192 | /** | |
193 | * @brief Construct a new ndarray object from a raw pointer. | |
194 | * | |
195 | * @param[in] data Raw pointer to the first element of the array. | |
196 | * @param[in] dt Data type descriptor. Often retrieved with dtype::get_builtin(). | |
197 | * @param[in] shape Shape of the array as STL container of integers; must have begin() and end(). | |
198 | * @param[in] strides Shape of the array as STL container of integers; must have begin() and end(). | |
199 | * @param[in] owner An arbitray Python object that owns that data pointer. The array object will | |
200 | * keep a reference to the object, and decrement it's reference count when the | |
201 | * array goes out of scope. Pass None at your own peril. | |
202 | * | |
203 | * @todo Should probably take ranges of iterators rather than actual container objects. | |
204 | */ | |
205 | template <typename Container> | |
206 | inline ndarray from_data(void * data, | |
207 | dtype const & dt, | |
208 | Container shape, | |
209 | Container strides, | |
210 | python::object const & owner) | |
211 | { | |
212 | return numpy::detail::from_data_impl(data, dt, shape, strides, owner, true); | |
213 | } | |
214 | ||
215 | /** | |
216 | * @brief Construct a new ndarray object from a raw pointer. | |
217 | * | |
218 | * @param[in] data Raw pointer to the first element of the array. | |
219 | * @param[in] dt Data type descriptor. Often retrieved with dtype::get_builtin(). | |
220 | * @param[in] shape Shape of the array as STL container of integers; must have begin() and end(). | |
221 | * @param[in] strides Shape of the array as STL container of integers; must have begin() and end(). | |
222 | * @param[in] owner An arbitray Python object that owns that data pointer. The array object will | |
223 | * keep a reference to the object, and decrement it's reference count when the | |
224 | * array goes out of scope. Pass None at your own peril. | |
225 | * | |
226 | * This overload takes a const void pointer and sets the "writeable" flag of the array to false. | |
227 | * | |
228 | * @todo Should probably take ranges of iterators rather than actual container objects. | |
229 | */ | |
230 | template <typename Container> | |
231 | inline ndarray from_data(void const * data, | |
232 | dtype const & dt, | |
233 | Container shape, | |
234 | Container strides, | |
235 | python::object const & owner) | |
236 | { | |
237 | return numpy::detail::from_data_impl(const_cast<void*>(data), dt, shape, strides, owner, false); | |
238 | } | |
239 | ||
240 | /** | |
241 | * @brief Transform an arbitrary object into a numpy array with the given requirements. | |
242 | * | |
243 | * @param[in] obj An arbitrary python object to convert. Arrays that meet the requirements | |
244 | * will be passed through directly. | |
245 | * @param[in] dt Data type descriptor. Often retrieved with dtype::get_builtin(). | |
246 | * @param[in] nd_min Minimum number of dimensions. | |
247 | * @param[in] nd_max Maximum number of dimensions. | |
248 | * @param[in] flags Bitwise OR of flags specifying additional requirements. | |
249 | */ | |
250 | ndarray from_object(object const & obj, dtype const & dt, | |
251 | int nd_min, int nd_max, ndarray::bitflag flags=ndarray::NONE); | |
252 | ||
253 | inline ndarray from_object(object const & obj, dtype const & dt, | |
254 | int nd, ndarray::bitflag flags=ndarray::NONE) | |
255 | { | |
256 | return from_object(obj, dt, nd, nd, flags); | |
257 | } | |
258 | ||
259 | inline ndarray from_object(object const & obj, dtype const & dt, ndarray::bitflag flags=ndarray::NONE) | |
260 | { | |
261 | return from_object(obj, dt, 0, 0, flags); | |
262 | } | |
263 | ||
264 | ndarray from_object(object const & obj, int nd_min, int nd_max, | |
265 | ndarray::bitflag flags=ndarray::NONE); | |
266 | ||
267 | inline ndarray from_object(object const & obj, int nd, ndarray::bitflag flags=ndarray::NONE) | |
268 | { | |
269 | return from_object(obj, nd, nd, flags); | |
270 | } | |
271 | ||
272 | inline ndarray from_object(object const & obj, ndarray::bitflag flags=ndarray::NONE) | |
273 | { | |
274 | return from_object(obj, 0, 0, flags); | |
275 | } | |
276 | ||
277 | inline ndarray::bitflag operator|(ndarray::bitflag a, ndarray::bitflag b) | |
278 | { | |
279 | return ndarray::bitflag(int(a) | int(b)); | |
280 | } | |
281 | ||
282 | inline ndarray::bitflag operator&(ndarray::bitflag a, ndarray::bitflag b) | |
283 | { | |
284 | return ndarray::bitflag(int(a) & int(b)); | |
285 | } | |
286 | ||
287 | } // namespace boost::python::numpy | |
288 | ||
289 | namespace converter | |
290 | { | |
291 | ||
292 | NUMPY_OBJECT_MANAGER_TRAITS(numpy::ndarray); | |
293 | ||
294 | }}} // namespace boost::python::converter | |
295 | ||
296 | #endif |