xtensor-python/include/xtensor-python/pycontainer.hpp at master · BenJamesbabala/xtensor-python · GitHub

Repository navigation

History

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

/***************************************************************************

* *

* Distributed under the terms of the BSD 3-Clause License. *

* *

* The full license is in the file LICENSE, distributed with this software. *

****************************************************************************/

#ifndef PY_CONTAINER_HPP

#define PY_CONTAINER_HPP

#include <functional>

#include <numeric>

#include <cmath>

#include "pybind11/pybind11.h"

#include "pybind11/common.h"

#include "pybind11/complex.h"

// Because of layout, otherwise xiterator and xtensor_forward are sufficient

#include "xtensor/xcontainer.hpp"

namespace xt

{

template <class D>

class pycontainer : public pybind11::object,

public xcontainer<D>

{

public:

using derived_type = D;

using base_type = xcontainer<D>;

using inner_types = xcontainer_inner_types<D>;

using container_type = typename inner_types::container_type;

using value_type = typename container_type::value_type;

using reference = typename container_type::reference;

using const_reference = typename container_type::const_reference;

using pointer = typename container_type::pointer;

using const_pointer = typename container_type::const_pointer;

using size_type = typename container_type::size_type;

using difference_type = typename container_type::difference_type;

using shape_type = typename inner_types::shape_type;

using strides_type = typename inner_types::strides_type;

using backstrides_type = typename inner_types::backstrides_type;

using inner_shape_type = typename inner_types::inner_shape_type;

using inner_strides_type = typename inner_types::inner_strides_type;

using iterable_base = xiterable<D>;

using iterator = typename iterable_base::iterator;

using const_iterator = typename iterable_base::const_iterator;

using stepper = typename iterable_base::stepper;

using const_stepper = typename iterable_base::const_stepper;

using broadcast_iterator = typename iterable_base::broadcast_iterator;

using const_broadcast_iterator = typename iterable_base::broadcast_iterator;

void reshape(const shape_type& shape);

void reshape(const shape_type& shape, layout l);

void reshape(const shape_type& shape, const strides_type& strides);

using base_type::operator();

using base_type::begin;

using base_type::end;

protected:

pycontainer() = default;

~pycontainer() = default;

pycontainer(pybind11::handle h, borrowed_t);

pycontainer(pybind11::handle h, stolen_t);

pycontainer(const pybind11::object& o);

pycontainer(const pycontainer&) = default;

pycontainer& operator=(const pycontainer&) = default;

pycontainer(pycontainer&&) = default;

pycontainer& operator=(pycontainer&&) = default;

static derived_type ensure(pybind11::handle h);

static bool check_(pybind11::handle h);

static PyObject* raw_array_t(PyObject* ptr);

PyArrayObject* python_array();

};

namespace detail

{

// TODO : switch on pybind11::is_fmt_numeric when it is available

template <typename T, typename SFINAE = void>

struct is_fmt_numeric

{

static constexpr bool value = false;

};

constexpr int log2(size_t n, int k = 0)

{

return (n <= 1) ? k : log2(n >> 1, k + 1);

}

template <typename T>

struct is_fmt_numeric<T, std::enable_if_t<std::is_arithmetic<T>::value>>

{

static constexpr bool value = true;

static constexpr int index = std::is_same<T, bool>::value ? 0 : 1 + (

std::is_integral<T>::value ? log2(sizeof(T)) * 2 + std::is_unsigned<T>::value : 8 + (

std::is_same<T, double>::value ? 1 : std::is_same<T, long double>::value ? 2 : 0));

};

template <class T>

struct is_fmt_numeric<std::complex<T>>

{

static constexpr bool value = true;

static constexpr int index = is_fmt_numeric<T>::index + 3;

};

template <class T>

struct numpy_traits

{

private:

constexpr static const int value_list[15] = {

NPY_BOOL,

NPY_BYTE, NPY_UBYTE, NPY_SHORT, NPY_USHORT,

NPY_INT, NPY_UINT, NPY_LONGLONG, NPY_ULONGLONG,

NPY_FLOAT, NPY_DOUBLE, NPY_LONGDOUBLE,

NPY_CFLOAT, NPY_CDOUBLE, NPY_CLONGDOUBLE

};

public:

using value_type = std::remove_const_t<T>;

static constexpr int type_num = value_list[is_fmt_numeric<value_type>::index];

};

}

/******************************

* pycontainer implementation *

******************************/

template <class D>

inline pycontainer<D>::pycontainer(pybind11::handle h, borrowed_t)

: pybind11::object(h, borrowed)

{

}

template <class D>

inline pycontainer<D>::pycontainer(pybind11::handle h, stolen_t)

: pybind11::object(h, stolen)

{

}

template <class D>

inline pycontainer<D>::pycontainer(const pybind11::object& o)

: pybind11::object(raw_array_t(o.ptr()), pybind11::object::stolen)

{

if(!this->m_ptr)

throw pybind11::error_already_set();

}

template <class D>

inline auto pycontainer<D>::ensure(pybind11::handle h) -> derived_type

{

auto result = pybind11::reinterpret_steal<derived_type>(raw_array_t(h.ptr()));

if(result.ptr() == nullptr)

PyErr_Clear();

return result;

}

template <class D>

inline bool pycontainer<D>::check_(pybind11::handle h)

{

int type_num = detail::numpy_traits<value_type>::type_num;

return PyArray_Check(h.ptr()) &&

PyArray_EquivTypenums(PyArray_TYPE(reinterpret_cast<PyArrayObject*>(h.ptr())), type_num);

}

template <class D>

inline PyObject* pycontainer<D>::raw_array_t(PyObject* ptr)

{

if(ptr == nullptr)

return nullptr;

int type_num = detail::numpy_traits<value_type>::type_num;

auto res = PyArray_FromAny(ptr, PyArray_DescrFromType(type_num), 0, 0,

NPY_ARRAY_ENSUREARRAY | NPY_ARRAY_FORCECAST, nullptr);

return res;

}

template <class D>

inline PyArrayObject* pycontainer<D>::python_array()

{

return reinterpret_cast<PyArrayObject*>(this->m_ptr);

}

template <class D>

inline void pycontainer<D>::reshape(const shape_type& shape)

{

if(shape.size() != this->dimension() || !std::equal(shape.begin(), shape.end(), this->shape().begin()))

{

reshape(shape, layout::row_major);

}

template <class D>

inline void pycontainer<D>::reshape(const shape_type& shape, layout l)

{

strides_type strides = make_sequence<strides_type>(shape.size(), size_type(1));

compute_strides(shape, l, strides);

reshape(shape, strides);

}

template <class D>

inline void pycontainer<D>::reshape(const shape_type& shape, const strides_type& strides)

{

derived_type tmp(shape, strides);

*static_cast<derived_type*>(this) = std::move(tmp);

}

#endif

xtensor-python/include/xtensor-python/pycontainer.hpp at master · BenJamesbabala/xtensor-python · GitHub

Repository navigation

Expand file tree

Breadcrumbs

pycontainer.hpp

Latest commit

History

Breadcrumbs

pycontainer.hpp

File metadata and controls