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Diffstat (limited to 'doc/source/reference/c-api.array.rst')
| -rw-r--r-- | doc/source/reference/c-api.array.rst | 44 |
1 files changed, 30 insertions, 14 deletions
diff --git a/doc/source/reference/c-api.array.rst b/doc/source/reference/c-api.array.rst index 85cf3c317..cef400fad 100644 --- a/doc/source/reference/c-api.array.rst +++ b/doc/source/reference/c-api.array.rst @@ -165,13 +165,13 @@ with misaligned data. at least *aobj* ->nd in size). You may want to typecast the returned pointer to the data type of the ndarray. -.. cfunction:: void* PyArray_GETPTR1(PyObject* obj, <npy_intp> i) +.. cfunction:: void* PyArray_GETPTR1(PyArrayObject* obj, npy_intp i) -.. cfunction:: void* PyArray_GETPTR2(PyObject* obj, <npy_intp> i, <npy_intp> j) +.. cfunction:: void* PyArray_GETPTR2(PyArrayObject* obj, npy_intp i, npy_intp j) -.. cfunction:: void* PyArray_GETPTR3(PyObject* obj, <npy_intp> i, <npy_intp> j, <npy_intp> k) +.. cfunction:: void* PyArray_GETPTR3(PyArrayObject* obj, npy_intp i, npy_intp j, npy_intp k) -.. cfunction:: void* PyArray_GETPTR4(PyObject* obj, <npy_intp> i, <npy_intp> j, <npy_intp> k, <npy_intp> l) +.. cfunction:: void* PyArray_GETPTR4(PyArrayObject* obj, npy_intp i, npy_intp j, npy_intp k, npy_intp l) Quick, inline access to the element at the given coordinates in the ndarray, *obj*, which must have respectively 1, 2, 3, or 4 @@ -1062,7 +1062,7 @@ Converting data types *arr* is an array scalar (has 0 dimensions), it finds the data type of smallest size to which the value may be converted without overflow or truncation to an integer. - + This function will not demote complex to float or anything to boolean, but will demote a signed integer to an unsigned integer when the scalar value is positive. @@ -1088,7 +1088,7 @@ Converting data types Categories are determined by first checking which of boolean, integer (int/uint), or floating point (float/complex) the maximum kind of all the arrays and the scalars are. - + If there are only scalars or the maximum category of the scalars is higher than the maximum category of the arrays, the data types are combined with :cfunc:`PyArray_PromoteTypes` @@ -1310,11 +1310,21 @@ of the constant names is deprecated in 1.7. The data area is in Fortran-style contiguous order (first index varies the fastest). -Notice that contiguous 1-d arrays are always both Fortran contiguous -and C contiguous. Both of these flags can be checked and are convenience -flags only as whether or not an array is :cdata:`NPY_ARRAY_C_CONTIGUOUS` -or :cdata:`NPY_ARRAY_F_CONTIGUOUS` can be determined by the ``strides``, -``dimensions``, and ``itemsize`` attributes. +.. note:: + + Arrays can be both C-style and Fortran-style contiguous simultaneously. + This is clear for 1-dimensional arrays, but can also be true for higher + dimensional arrays. + + Even for contiguous arrays a stride for a given dimension + ``arr.strides[dim]`` may be *arbitrary* if ``arr.shape[dim] == 1`` + or the array has no elements. + It does *not* generally hold that ``self.strides[-1] == self.itemsize`` + for C-style contiguous arrays or ``self.strides[0] == self.itemsize`` for + Fortran-style contiguous arrays is true. The correct way to access the + ``itemsize`` of an array from the C API is ``PyArray_ITEMSIZE(arr)``. + + .. seealso:: :ref:`Internal memory layout of an ndarray <arrays.ndarray>` .. cvar:: NPY_ARRAY_OWNDATA @@ -1322,7 +1332,7 @@ or :cdata:`NPY_ARRAY_F_CONTIGUOUS` can be determined by the ``strides``, .. cvar:: NPY_ARRAY_ALIGNED - The data area is aligned appropriately (for all strides). + The data area and all array elements are aligned appropriately. .. cvar:: NPY_ARRAY_WRITEABLE @@ -1432,14 +1442,20 @@ For all of these macros *arr* must be an instance of a (subclass of) :cdata:`NPY_ARRAY_OWNDATA`, :cdata:`NPY_ARRAY_ALIGNED`, :cdata:`NPY_ARRAY_WRITEABLE`, :cdata:`NPY_ARRAY_UPDATEIFCOPY`. -.. cfunction:: PyArray_ISCONTIGUOUS(arr) +.. cfunction:: PyArray_IS_C_CONTIGUOUS(arr) Evaluates true if *arr* is C-style contiguous. -.. cfunction:: PyArray_ISFORTRAN(arr) +.. cfunction:: PyArray_IS_F_CONTIGUOUS(arr) Evaluates true if *arr* is Fortran-style contiguous. +.. cfunction:: PyArray_ISFORTRAN(arr) + + Evaluates true if *arr* is Fortran-style contiguous and *not* + C-style contiguous. :cfunc:`PyArray_IS_F_CONTIGUOUS` + is the correct way to test for Fortran-style contiguity. + .. cfunction:: PyArray_ISWRITEABLE(arr) Evaluates true if the data area of *arr* can be written to |