职业分析的数据交互可视化.zip

=========== 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) :: 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 appropriate Python object if the array is 0d and matches a Python type. steals reference to mp :: PyObject * PyArray_GetField(PyArrayObject *self, PyArray_Descr *typed, int