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=========== NumPy C-API =========== :: unsigned int PyArray_GetNDArrayCVersion(void ) Included at the very first so not auto-grabbed and thus not labeled. :: int PyArray_SetNumericOps(PyObject *dict) Set internal structure with number functions that all arrays will use :: PyObject * PyArray_GetNumericOps(void ) Get dictionary showing number functions that all arrays will use :: int PyArray_INCREF(PyArrayObject *mp) For object arrays, increment all internal references. :: int PyArray_XDECREF(PyArrayObject *mp) Decrement all internal references for object arrays. (or arrays with object fields) :: void PyArray_SetStringFunction(PyObject *op, int repr) Set the array print function to be a Python function. :: PyArray_Descr * PyArray_DescrFromType(int type) Get the PyArray_Descr structure for a type. :: PyObject * PyArray_TypeObjectFromType(int type) Get a typeobject from a type-number -- can return NULL. New reference :: char * PyArray_Zero(PyArrayObject *arr) Get pointer to zero of correct type for array. :: char * PyArray_One(PyArrayObject *arr) Get pointer to one of correct type for array :: PyObject * PyArray_CastToType(PyArrayObject *arr, PyArray_Descr *dtype, int is_f_order) For backward compatibility Cast an array using typecode structure. steals reference to dtype --- cannot be NULL This function always makes a copy of arr, even if the dtype doesn't change. :: int PyArray_CastTo(PyArrayObject *out, PyArrayObject *mp) Cast to an already created array. :: int PyArray_CastAnyTo(PyArrayObject *out, PyArrayObject *mp) Cast to an already created array. Arrays don't have to be "broadcastable" Only requirement is they have the same number of elements. :: int PyArray_CanCastSafely(int fromtype, int totype) Check the type coercion rules. :: npy_bool PyArray_CanCastTo(PyArray_Descr *from, PyArray_Descr *to) leaves reference count alone --- cannot be NULL PyArray_CanCastTypeTo is equivalent to this, but adds a 'casting' parameter. :: int PyArray_ObjectType(PyObject *op, int minimum_type) Return the typecode of the array a Python object would be converted to Returns the type number the result should have, or NPY_NOTYPE on error. :: PyArray_Descr * PyArray_DescrFromObject(PyObject *op, PyArray_Descr *mintype) new reference -- accepts NULL for mintype :: PyArrayObject ** PyArray_ConvertToCommonType(PyObject *op, int *retn) This function is only used in one place within NumPy and should generally be avoided. It is provided mainly for backward compatibility. The user of the function has to free the returned array. :: PyArray_Descr * PyArray_DescrFromScalar(PyObject *sc) Return descr object from array scalar. New reference :: PyArray_Descr * PyArray_DescrFromTypeObject(PyObject *type) :: npy_intp PyArray_Size(PyObject *op) Compute the size of an array (in number of items) :: PyObject * PyArray_Scalar(void *data, PyArray_Descr *descr, PyObject *base) Get scalar-equivalent to a region of memory described by a descriptor. :: PyObject * PyArray_FromScalar(PyObject *scalar, PyArray_Descr *outcode) Get 0-dim array from scalar 0-dim array from array-scalar object always contains a copy of the data unless outcode is NULL, it is of void type and the referrer does not own it either. steals reference to outcode :: void PyArray_ScalarAsCtype(PyObject *scalar, void *ctypeptr) Convert to c-type no error checking is performed -- ctypeptr must be same type as scalar in case of flexible type, the data is not copied into ctypeptr which is expected to be a pointer to pointer :: int PyArray_CastScalarToCtype(PyObject *scalar, void *ctypeptr, PyArray_Descr *outcode) Cast Scalar to c-type The output buffer must be large-enough to receive the value Even for flexible types which is different from ScalarAsCtype where only a reference for flexible types is returned This may not work right on narrow builds for NumPy unicode scalars. :: int PyArray_CastScalarDirect(PyObject *scalar, PyArray_Descr *indescr, void *ctypeptr, int outtype) Cast Scalar to c-type :: PyObject * PyArray_ScalarFromObject(PyObject *object) Get an Array Scalar From a Python Object Returns NULL if unsuccessful but error is only set if another error occurred. Currently only Numeric-like object supported. :: PyArray_VectorUnaryFunc * PyArray_GetCastFunc(PyArray_Descr *descr, int type_num) Get a cast function to cast from the input descriptor to the output type_number (must be a registered data-type). Returns NULL if un-successful. :: PyObject * PyArray_FromDims(int NPY_UNUSED(nd) , int *NPY_UNUSED(d) , int NPY_UNUSED(type) ) Deprecated, use PyArray_SimpleNew instead. :: PyObject * PyArray_FromDimsAndDataAndDescr(int NPY_UNUSED(nd) , int *NPY_UNUSED(d) , PyArray_Descr *descr, char *NPY_UNUSED(data) ) Deprecated, use PyArray_NewFromDescr instead. :: PyObject * PyArray_FromAny(PyObject *op, PyArray_Descr *newtype, int min_depth, int max_depth, int flags, PyObject *context) Does not check for NPY_ARRAY_ENSURECOPY and NPY_ARRAY_NOTSWAPPED in flags Steals a reference to newtype --- which can be NULL :: PyObject * PyArray_EnsureArray(PyObject *op) This is a quick wrapper around PyArray_FromAny(op, NULL, 0, 0, NPY_ARRAY_ENSUREARRAY, NULL) that special cases Arrays and PyArray_Scalars up front It *steals a reference* to the object It also guarantees that the result is PyArray_Type Because it decrefs op if any conversion needs to take place so it can be used like PyArray_EnsureArray(some_function(...)) :: PyObject * PyArray_EnsureAnyArray(PyObject *op) :: PyObject * PyArray_FromFile(FILE *fp, PyArray_Descr *dtype, npy_intp num, char *sep) Given a ``FILE *`` pointer ``fp``, and a ``PyArray_Descr``, return an array corresponding to the data encoded in that file. The reference to `dtype` is stolen (it is possible that the passed in dtype is not held on to). The number of elements to read is given as ``num``; if it is < 0, then then as many as possible are read. If ``sep`` is NULL or empty, then binary data is assumed, else text data, with ``sep`` as the separator between elements. Whitespace in the separator matches any length of whitespace in the text, and a match for whitespace around the separator is added. For memory-mapped files, use the buffer interface. No more data than necessary is read by this routine. :: PyObject * PyArray_FromString(char *data, npy_intp slen, PyArray_Descr *dtype, npy_intp num, char *sep) Given a pointer to a string ``data``, a string length ``slen``, and a ``PyArray_Descr``, return an array corresponding to the data encoded in that string. If the dtype is NULL, the default array type is used (double). If non-null, the reference is stolen. If ``slen`` is < 0, then the end of string is used for text data. It is an error for ``slen`` to be < 0 for binary data (since embedded NULLs would be the norm). The number of elements to read is given as ``num``; if it is < 0, then then as many as possible are read. If ``sep`` is NULL or empty, then binary data is assumed, else text data, with ``sep`` as the separator between elements. Whitespace in the separator matches any length of whitespace in the text, and a match for whitespace around the separator is added. :: PyObject * PyArray_FromBuffer(PyObject *buf, PyArray_Descr *type, npy_intp count, npy_intp offset) :: PyObject * PyArray_FromIter(PyObject *obj, PyArray_Descr *dtype, npy_intp count) steals a reference to dtype (which cannot be NULL) :: PyObject * PyArray_Return(PyArrayObject *mp) Return either an array or the app