1 cimport python_buffer as pybuf

2 cimport stdlib

3

4 cdef extern from "Python.h":

5 ctypedef int Py_intptr_t

6

7 cdef extern from "numpy/arrayobject.h":

8 ctypedef Py_intptr_t npy_intp

9

10 cdef enum:

11 NPY_BOOL,

12 NPY_BYTE, NPY_UBYTE,

13 NPY_SHORT, NPY_USHORT,

14 NPY_INT, NPY_UINT,

15 NPY_LONG, NPY_ULONG,

16 NPY_LONGLONG, NPY_ULONGLONG,

17 NPY_FLOAT, NPY_DOUBLE, NPY_LONGDOUBLE,

18 NPY_CFLOAT, NPY_CDOUBLE, NPY_CLONGDOUBLE,

19 NPY_OBJECT,

20 NPY_STRING, NPY_UNICODE,

21 NPY_VOID,

22 NPY_NTYPES,

23 NPY_NOTYPE,

24 NPY_CHAR,

25 NPY_USERDEF,

26

27 NPY_C_CONTIGUOUS,

28 NPY_F_CONTIGUOUS

29

30 ctypedef class numpy.dtype [object PyArray_Descr]:

31 cdef int type_num

32 cdef object fields

33 cdef object names

34

35

36 ctypedef class numpy.ndarray [object PyArrayObject]:

37 cdef __cythonbufferdefaults__ = {"mode": "strided"}

38

39 cdef:

40 char *data

41 int ndim "nd"

42 npy_intp *shape "dimensions"

43 npy_intp *strides

44 int flags

45 dtype descr

46

47 # Note: This syntax (function definition in pxd files) is an

48 # experimental exception made for __getbuffer__ and __releasebuffer__

49 # -- the details of this may change.

50 def __getbuffer__(ndarray self, Py_buffer* info, int flags):

51 # This implementation of getbuffer is geared towards Cython

52 # requirements, and does not yet fullfill the PEP.

53 # In particular strided access is always provided regardless

54 # of flags

55 cdef int copy_shape, i, ndim

56 ndim = PyArray_NDIM(self)

57

58 if sizeof(npy_intp) != sizeof(Py_ssize_t):

59 copy_shape = 1

60 else:

61 copy_shape = 0

62

63 if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS)

64 and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)):

65 raise ValueError("ndarray is not C contiguous")

66

67 if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS)

68 and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)):

69 raise ValueError("ndarray is not Fortran contiguous")

70

71 info.buf = PyArray_DATA(self)

72 info.ndim = ndim

73 if copy_shape:

74 # Allocate new buffer for strides and shape info. This is allocated

75 # as one block, strides first.

76 info.strides = <Py_ssize_t*>stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2)

77 info.shape = info.strides + ndim

78 for i in range(ndim):

79 info.strides[i] = PyArray_STRIDES(self)[i]

80 info.shape[i] = PyArray_DIMS(self)[i]

81 else:

82 info.strides = <Py_ssize_t*>PyArray_STRIDES(self)

83 info.shape = <Py_ssize_t*>PyArray_DIMS(self)

84 info.suboffsets = NULL

85 info.itemsize = PyArray_ITEMSIZE(self)

86 info.readonly = not PyArray_ISWRITEABLE(self)

87

88 cdef int t

89 cdef char* f = NULL

90 cdef dtype descr = self.descr

91 cdef list stack

92

93 cdef bint hasfields = PyDataType_HASFIELDS(descr)

94

95 # Ugly hack warning:

96 # Cython currently will not support helper functions in

97 # pxd files -- so we must keep our own, manual stack!

98 # In addition, avoid allocation of the stack in the common

99 # case that we are dealing with a single non-nested datatype...

100 # (this would look much prettier if we could use utility

101 # functions).

102

103 if not hasfields and not copy_shape:

104 # do not call releasebuffer

105 info.obj = None

106 else:

107 # need to call releasebuffer

108 info.obj = self

109

110 if not hasfields:

111 t = descr.type_num

112 if t == NPY_BYTE: f = "b"

113 elif t == NPY_UBYTE: f = "B"

114 elif t == NPY_SHORT: f = "h"

115 elif t == NPY_USHORT: f = "H"

116 elif t == NPY_INT: f = "i"

117 elif t == NPY_UINT: f = "I"

118 elif t == NPY_LONG: f = "l"

119 elif t == NPY_ULONG: f = "L"

120 elif t == NPY_LONGLONG: f = "q"

121 elif t == NPY_ULONGLONG: f = "Q"

122 elif t == NPY_FLOAT: f = "f"

123 elif t == NPY_DOUBLE: f = "d"

124 elif t == NPY_LONGDOUBLE: f = "g"

125 elif t == NPY_CFLOAT: f = "Zf"

126 elif t == NPY_CDOUBLE: f = "Zd"

127 elif t == NPY_CLONGDOUBLE: f = "Zg"

128 elif t == NPY_OBJECT: f = "O"

129 else:

130 raise ValueError("unknown dtype code in numpy.pxd (%d)" % t)

131 info.format = f

132 return

133 else:

134 info.format = <char*>stdlib.malloc(255) # static size

135 f = info.format

136 stack = [iter(descr.fields.iteritems())]

137

138 while True:

139 iterator = stack[-1]

140 descr = None

141 while descr is None:

142 try:

143 descr = iterator.next()[1][0]

144 except StopIteration:

145 stack.pop()

146 if len(stack) > 0:

147 f[0] = 125 #"}"

148 f += 1

149 iterator = stack[-1]

150 else:

151 f[0] = 0 # Terminate string!

152 return

153

154 hasfields = PyDataType_HASFIELDS(descr)

155 if not hasfields:

156 t = descr.type_num

157 if f - info.format > 240: # this should leave room for "T{" and "}" as well

158 raise RuntimeError("Format string allocated too short.")

159

160 # Until ticket #99 is fixed, use integers to avoid warnings

161 if t == NPY_BYTE: f[0] = 98 #"b"

162 elif t == NPY_UBYTE: f[0] = 66 #"B"

163 elif t == NPY_SHORT: f[0] = 104 #"h"

164 elif t == NPY_USHORT: f[0] = 72 #"H"

165 elif t == NPY_INT: f[0] = 105 #"i"

166 elif t == NPY_UINT: f[0] = 73 #"I"

167 elif t == NPY_LONG: f[0] = 108 #"l"

168 elif t == NPY_ULONG: f[0] = 76 #"L"

169 elif t == NPY_LONGLONG: f[0] = 113 #"q"

170 elif t == NPY_ULONGLONG: f[0] = 81 #"Q"

171 elif t == NPY_FLOAT: f[0] = 102 #"f"

172 elif t == NPY_DOUBLE: f[0] = 100 #"d"

173 elif t == NPY_LONGDOUBLE: f[0] = 103 #"g"

174 elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1

175 elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1

176 elif t == NPY_CLONGDOUBLE: f[0] = 90; f[1] = 103; f += 1

177 elif t == NPY_OBJECT: f[0] = 79 #"O"

178 else:

179 raise ValueError("unknown dtype code in numpy.pxd (%d)" % t)

180 f += 1

181 else:

182 f[0] = 84 #"T"

183 f[1] = 123 #"{"

184 f += 2

185 stack.append(iter(descr.fields.iteritems()))

186

187 def __releasebuffer__(ndarray self, Py_buffer* info):

188 # This can not be called unless format needs to be freed (as

189 # obj is set to NULL in those case)

190 if PyArray_HASFIELDS(self):

191 stdlib.free(info.format)

192 if sizeof(npy_intp) != sizeof(Py_ssize_t):

193 stdlib.free(info.strides)

194 # info.shape was stored after info.strides in the same block

195

196

197 cdef void* PyArray_DATA(ndarray arr)

198 cdef int PyArray_TYPE(ndarray arr)

199 cdef int PyArray_NDIM(ndarray arr)

200 cdef int PyArray_ISWRITEABLE(ndarray arr)

201 cdef npy_intp* PyArray_STRIDES(ndarray arr)

202 cdef npy_intp* PyArray_DIMS(ndarray arr)

203 cdef int PyArray_ITEMSIZE(ndarray arr)

204 cdef int PyArray_CHKFLAGS(ndarray arr, int flags)

205 cdef int PyArray_HASFIELDS(ndarray arr)

206

207 cdef int PyDataType_HASFIELDS(dtype obj)

208

209 ctypedef signed int npy_byte

210 ctypedef signed int npy_short

211 ctypedef signed int npy_int

212 ctypedef signed int npy_long

213 ctypedef signed int npy_longlong

214

215 ctypedef unsigned int npy_ubyte

216 ctypedef unsigned int npy_ushort

217 ctypedef unsigned int npy_uint

218 ctypedef unsigned int npy_ulong

219 ctypedef unsigned int npy_ulonglong

220

221 ctypedef float npy_float

222 ctypedef float npy_double

223 ctypedef float npy_longdouble

224

225 ctypedef signed int npy_int8

226 ctypedef signed int npy_int16

227 ctypedef signed int npy_int32

228 ctypedef signed int npy_int64

229 ctypedef signed int npy_int96

230 ctypedef signed int npy_int128

231

232 ctypedef unsigned int npy_uint8

233 ctypedef unsigned int npy_uint16

234 ctypedef unsigned int npy_uint32

235 ctypedef unsigned int npy_uint64

236 ctypedef unsigned int npy_uint96

237 ctypedef unsigned int npy_uint128

238

239 ctypedef float npy_float32

240 ctypedef float npy_float64

241 ctypedef float npy_float80

242 ctypedef float npy_float96

243 ctypedef float npy_float128

244

245 ctypedef struct npy_cfloat:

246 float real

247 float imag

248

249 ctypedef struct npy_cdouble:

250 double real

251 double imag

252

253 ctypedef struct npy_clongdouble:

254 long double real

255 long double imag

256

257 # Typedefs that matches the runtime dtype objects in

258 # the numpy module.

259

260 # The ones that are commented out needs an IFDEF function

261 # in Cython to enable them only on the right systems.

262

263 ctypedef npy_int8 int8_t

264 ctypedef npy_int16 int16_t

265 ctypedef npy_int32 int32_t

266 ctypedef npy_int64 int64_t

267 #ctypedef npy_int96 int96_t

268 #ctypedef npy_int128 int128_t

269

270 ctypedef npy_uint8 uint8_t

271 ctypedef npy_uint16 uint16_t

272 ctypedef npy_uint32 uint32_t

273 ctypedef npy_uint64 uint64_t

274 #ctypedef npy_uint96 uint96_t

275 #ctypedef npy_uint128 uint128_t

276

277 ctypedef npy_float32 float32_t

278 ctypedef npy_float64 float64_t

279 #ctypedef npy_float80 float80_t

280 #ctypedef npy_float128 float128_t

281

282 # The int types are mapped a bit surprising --

283 # numpy.int corresponds to 'l' and numpy.long to 'q'

284 ctypedef npy_long int_t

285 ctypedef npy_longlong long_t

286

287 ctypedef npy_ulong uint_t

288 ctypedef npy_ulonglong ulong_t

289

290 ctypedef npy_double float_t

291 ctypedef npy_double double_t

292 ctypedef npy_longdouble longdouble_t

293

294 ctypedef npy_cfloat cfloat_t

295 ctypedef npy_cdouble cdouble_t

296 ctypedef npy_clongdouble clongdouble_t