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diff --git a/trunk/source/reference/c-api.array.rst b/trunk/source/reference/c-api.array.rst deleted file mode 100644 index 56950a8d9..000000000 --- a/trunk/source/reference/c-api.array.rst +++ /dev/null @@ -1,2635 +0,0 @@ -Array API -========= - -.. sectionauthor:: Travis E. Oliphant - -| The test of a first-rate intelligence is the ability to hold two -| opposed ideas in the mind at the same time, and still retain the -| ability to function. -| --- *F. Scott Fitzgerald* - -| For a successful technology, reality must take precedence over public -| relations, for Nature cannot be fooled. -| --- *Richard P. Feynman* - -.. index:: - pair: ndarray; C-API - pair: C-API; array - - -Array structure and data access -------------------------------- - -These macros all access the :ctype:`PyArrayObject` structure members. The input -argument, obj, can be any :ctype:`PyObject *` that is directly interpretable -as a :ctype:`PyArrayObject *` (any instance of the :cdata:`PyArray_Type` and its -sub-types). - -.. cfunction:: void *PyArray_DATA(PyObject *obj) - -.. cfunction:: char *PyArray_BYTES(PyObject *obj) - - These two macros are similar and obtain the pointer to the - data-buffer for the array. The first macro can (and should be) - assigned to a particular pointer where the second is for generic - processing. If you have not guaranteed a contiguous and/or aligned - array then be sure you understand how to access the data in the - array to avoid memory and/or alignment problems. - -.. cfunction:: npy_intp *PyArray_DIMS(PyObject *arr) - -.. cfunction:: npy_intp *PyArray_STRIDES(PyObject* arr) - -.. cfunction:: npy_intp PyArray_DIM(PyObject* arr, int n) - - Return the shape in the *n* :math:`^{\textrm{th}}` dimension. - -.. cfunction:: npy_intp PyArray_STRIDE(PyObject* arr, int n) - - Return the stride in the *n* :math:`^{\textrm{th}}` dimension. - -.. cfunction:: PyObject *PyArray_BASE(PyObject* arr) - -.. cfunction:: PyArray_Descr *PyArray_DESCR(PyObject* arr) - -.. cfunction:: int PyArray_FLAGS(PyObject* arr) - -.. cfunction:: int PyArray_ITEMSIZE(PyObject* arr) - - Return the itemsize for the elements of this array. - -.. cfunction:: int PyArray_TYPE(PyObject* arr) - - Return the (builtin) typenumber for the elements of this array. - -.. cfunction:: PyObject *PyArray_GETITEM(PyObject* arr, void* itemptr) - - Get a Python object from the ndarray, *arr*, at the location - pointed to by itemptr. Return ``NULL`` on failure. - -.. cfunction:: int PyArray_SETITEM(PyObject* arr, void* itemptr, PyObject* obj) - - Convert obj and place it in the ndarray, *arr*, at the place - pointed to by itemptr. Return -1 if an error occurs or 0 on - success. - -.. cfunction:: npy_intp PyArray_SIZE(PyObject* arr) - - Returns the total size (in number of elements) of the array. - -.. cfunction:: npy_intp PyArray_Size(PyObject* obj) - - Returns 0 if *obj* is not a sub-class of bigndarray. Otherwise, - returns the total number of elements in the array. Safer version - of :cfunc:`PyArray_SIZE` (*obj*). - -.. cfunction:: npy_intp PyArray_NBYTES(PyObject* arr) - - Returns the total number of bytes consumed by the array. - - -Data access -^^^^^^^^^^^ - -These functions and macros provide easy access to elements of the -ndarray from C. These work for all arrays. You may need to take care -when accessing the data in the array, however, if it is not in machine -byte-order, misaligned, or not writeable. In other words, be sure to -respect the state of the flags unless you know what you are doing, or -have previously guaranteed an array that is writeable, aligned, and in -machine byte-order using :cfunc:`PyArray_FromAny`. If you wish to handle all -types of arrays, the copyswap function for each type is useful for -handling misbehaved arrays. Some platforms (e.g. Solaris) do not like -misaligned data and will crash if you de-reference a misaligned -pointer. Other platforms (e.g. x86 Linux) will just work more slowly -with misaligned data. - -.. cfunction:: void* PyArray_GetPtr(PyArrayObject* aobj, npy_intp* ind) - - Return a pointer to the data of the ndarray, *aobj*, at the - N-dimensional index given by the c-array, *ind*, (which must be - 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_GETPTR2(PyObject* 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_GETPTR4(PyObject* 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 - dimensions (this is not checked). The corresponding *i*, *j*, - *k*, and *l* coordinates can be any integer but will be - interpreted as ``npy_intp``. You may want to typecast the - returned pointer to the data type of the ndarray. - - -Creating arrays ---------------- - - -From scratch -^^^^^^^^^^^^ - -.. cfunction:: PyObject* PyArray_NewFromDescr(PyTypeObject* subtype, PyArray_Descr* descr, int nd, npy_intp* dims, npy_intp* strides, void* data, int flags, PyObject* obj) - - This is the main array creation function. Most new arrays are - created with this flexible function. The returned object is an - object of Python-type *subtype*, which must be a subtype of - :cdata:`PyArray_Type`. The array has *nd* dimensions, described by - *dims*. The data-type descriptor of the new array is *descr*. If - *subtype* is not :cdata:`&PyArray_Type` (*e.g.* a Python subclass of - the ndarray), then *obj* is the object to pass to the - :obj:`__array_finalize__` method of the subclass. If *data* is - ``NULL``, then new memory will be allocated and *flags* can be - non-zero to indicate a Fortran-style contiguous array. If *data* - is not ``NULL``, then it is assumed to point to the memory to be - used for the array and the *flags* argument is used as the new - flags for the array (except the state of :cdata:`NPY_OWNDATA` and - :cdata:`UPDATEIFCOPY` flags of the new array will be reset). In - addition, if *data* is non-NULL, then *strides* can also be - provided. If *strides* is ``NULL``, then the array strides are - computed as C-style contiguous (default) or Fortran-style - contiguous (*flags* is nonzero for *data* = ``NULL`` or *flags* & - :cdata:`NPY_F_CONTIGUOUS` is nonzero non-NULL *data*). Any provided - *dims* and *strides* are copied into newly allocated dimension and - strides arrays for the new array object. - -.. cfunction:: PyObject* PyArray_New(PyTypeObject* subtype, int nd, npy_intp* dims, int type_num, npy_intp* strides, void* data, int itemsize, int flags, PyObject* obj) - - This is similar to :cfunc:`PyArray_DescrNew` (...) except you - specify the data-type descriptor with *type_num* and *itemsize*, - where *type_num* corresponds to a builtin (or user-defined) - type. If the type always has the same number of bytes, then - itemsize is ignored. Otherwise, itemsize specifies the particular - size of this array. - - - -.. warning:: - - If data is passed to :cfunc:`PyArray_NewFromDescr` or :cfunc:`PyArray_New`, - this memory must not be deallocated until the new array is - deleted. If this data came from another Python object, this can - be accomplished using :cfunc:`Py_INCREF` on that object and setting the - base member of the new array to point to that object. If strides - are passed in they must be consistent with the dimensions, the - itemsize, and the data of the array. - -.. cfunction:: PyObject* PyArray_SimpleNew(int nd, npy_intp* dims, int typenum) - - Create a new unitialized array of type, *typenum*, whose size in - each of *nd* dimensions is given by the integer array, *dims*. - This function cannot be used to create a flexible-type array (no - itemsize given). - -.. cfunction:: PyObject* PyArray_SimpleNewFromData(int nd, npy_intp* dims, int typenum, void* data) - - Create an array wrapper around *data* pointed to by the given - pointer. The array flags will have a default that the data area is - well-behaved and C-style contiguous. The shape of the array is - given by the *dims* c-array of length *nd*. The data-type of the - array is indicated by *typenum*. - -.. cfunction:: PyObject* PyArray_SimpleNewFromDescr(int nd, npy_intp* dims, PyArray_Descr* descr) - - Create a new array with the provided data-type descriptor, *descr* - , of the shape deteremined by *nd* and *dims*. - -.. cfunction:: PyArray_FILLWBYTE(PyObject* obj, int val) - - Fill the array pointed to by *obj* ---which must be a (subclass - of) bigndarray---with the contents of *val* (evaluated as a byte). - -.. cfunction:: PyObject* PyArray_Zeros(int nd, npy_intp* dims, PyArray_Descr* dtype, int fortran) - - Construct a new *nd* -dimensional array with shape given by *dims* - and data type given by *dtype*. If *fortran* is non-zero, then a - Fortran-order array is created, otherwise a C-order array is - created. Fill the memory with zeros (or the 0 object if *dtype* - corresponds to :ctype:`PyArray_OBJECT` ). - -.. cfunction:: PyObject* PyArray_ZEROS(int nd, npy_intp* dims, int type_num, int fortran) - - Macro form of :cfunc:`PyArray_Zeros` which takes a type-number instead - of a data-type object. - -.. cfunction:: PyObject* PyArray_Empty(int nd, npy_intp* dims, PyArray_Descr* dtype, int fortran) - - Construct a new *nd* -dimensional array with shape given by *dims* - and data type given by *dtype*. If *fortran* is non-zero, then a - Fortran-order array is created, otherwise a C-order array is - created. The array is uninitialized unless the data type - corresponds to :ctype:`PyArray_OBJECT` in which case the array is - filled with :cdata:`Py_None`. - -.. cfunction:: PyObject* PyArray_EMPTY(int nd, npy_intp* dims, int typenum, int fortran) - - Macro form of :cfunc:`PyArray_Empty` which takes a type-number, - *typenum*, instead of a data-type object. - -.. cfunction:: PyObject* PyArray_Arange(double start, double stop, double step, int typenum) - - Construct a new 1-dimensional array of data-type, *typenum*, that - ranges from *start* to *stop* (exclusive) in increments of *step* - . Equivalent to **arange** (*start*, *stop*, *step*, dtype). - -.. cfunction:: PyObject* PyArray_ArangeObj(PyObject* start, PyObject* stop, PyObject* step, PyArray_Descr* descr) - - Construct a new 1-dimensional array of data-type determined by - ``descr``, that ranges from ``start`` to ``stop`` (exclusive) in - increments of ``step``. Equivalent to arange( ``start``, - ``stop``, ``step``, ``typenum`` ). - - -From other objects -^^^^^^^^^^^^^^^^^^ - -.. cfunction:: PyObject* PyArray_FromAny(PyObject* op, PyArray_Descr* dtype, int min_depth, int max_depth, int requirements, PyObject* context) - - This is the main function used to obtain an array from any nested - sequence, or object that exposes the array interface, ``op``. The - parameters allow specification of the required *type*, the - minimum (*min_depth*) and maximum (*max_depth*) number of - dimensions acceptable, and other *requirements* for the array. The - *dtype* argument needs to be a :ctype:`PyArray_Descr` structure - indicating the desired data-type (including required - byteorder). The *dtype* argument may be NULL, indicating that any - data-type (and byteorder) is acceptable. If you want to use - ``NULL`` for the *dtype* and ensure the array is notswapped then - use :cfunc:`PyArray_CheckFromAny`. A value of 0 for either of the - depth parameters causes the parameter to be ignored. Any of the - following array flags can be added (*e.g.* using \|) to get the - *requirements* argument. If your code can handle general (*e.g.* - strided, byte-swapped, or unaligned arrays) then *requirements* - may be 0. Also, if *op* is not already an array (or does not - expose the array interface), then a new array will be created (and - filled from *op* using the sequence protocol). The new array will - have :cdata:`NPY_DEFAULT` as its flags member. The *context* argument - is passed to the :obj:`__array__` method of *op* and is only used if - the array is constructed that way. - - .. cvar:: NPY_C_CONTIGUOUS - - Make sure the returned array is C-style contiguous - - .. cvar:: NPY_F_CONTIGUOUS - - Make sure the returned array is Fortran-style contiguous. - - .. cvar:: NPY_ALIGNED - - Make sure the returned array is aligned on proper boundaries for its - data type. An aligned array has the data pointer and every strides - factor as a multiple of the alignment factor for the data-type- - descriptor. - - .. cvar:: NPY_WRITEABLE - - Make sure the returned array can be written to. - - .. cvar:: NPY_ENSURECOPY - - Make sure a copy is made of *op*. If this flag is not - present, data is not copied if it can be avoided. - - .. cvar:: NPY_ENSUREARRAY - - Make sure the result is a base-class ndarray or bigndarray. By - default, if *op* is an instance of a subclass of the - bigndarray, an instance of that same subclass is returned. If - this flag is set, an ndarray object will be returned instead. - - .. cvar:: NPY_FORCECAST - - Force a cast to the output type even if it cannot be done - safely. Without this flag, a data cast will occur only if it - can be done safely, otherwise an error is reaised. - - .. cvar:: NPY_UPDATEIFCOPY - - If *op* is already an array, but does not satisfy the - requirements, then a copy is made (which will satisfy the - requirements). If this flag is present and a copy (of an - object that is already an array) must be made, then the - corresponding :cdata:`NPY_UPDATEIFCOPY` flag is set in the returned - copy and *op* is made to be read-only. When the returned copy - is deleted (presumably after your calculations are complete), - its contents will be copied back into *op* and the *op* array - will be made writeable again. If *op* is not writeable to - begin with, then an error is raised. If *op* is not already an - array, then this flag has no effect. - - .. cvar:: NPY_BEHAVED - - :cdata:`NPY_ALIGNED` \| :cdata:`NPY_WRITEABLE` - - .. cvar:: NPY_CARRAY - - :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_BEHAVED` - - .. cvar:: NPY_CARRAY_RO - - :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_ALIGNED` - - .. cvar:: NPY_FARRAY - - :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_BEHAVED` - - .. cvar:: NPY_FARRAY_RO - - :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_ALIGNED` - - .. cvar:: NPY_DEFAULT - - :cdata:`NPY_CARRAY` - - .. cvar:: NPY_IN_ARRAY - - :cdata:`NPY_CONTIGUOUS` \| :cdata:`NPY_ALIGNED` - - .. cvar:: NPY_IN_FARRAY - - :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_ALIGNED` - - .. cvar:: NPY_INOUT_ARRAY - - :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_WRITEABLE` \| - :cdata:`NPY_ALIGNED` - - .. cvar:: NPY_INOUT_FARRAY - - :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_WRITEABLE` \| - :cdata:`NPY_ALIGNED` - - .. cvar:: NPY_OUT_ARRAY - - :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_WRITEABLE` \| - :cdata:`NPY_ALIGNED` \| :cdata:`NPY_UPDATEIFCOPY` - - .. cvar:: NPY_OUT_FARRAY - - :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_WRITEABLE` \| - :cdata:`NPY_ALIGNED` \| :cdata:`UPDATEIFCOPY` - - -.. cfunction:: PyObject* PyArray_CheckFromAny(PyObject* op, PyArray_Descr* dtype, int min_depth, int max_depth, int requirements, PyObject* context) - - Nearly identical to :cfunc:`PyArray_FromAny` (...) except - *requirements* can contain :cdata:`NPY_NOTSWAPPED` (over-riding the - specification in *dtype*) and :cdata:`NPY_ELEMENTSTRIDES` which - indicates that the array should be aligned in the sense that the - strides are multiples of the element size. - -.. cvar:: NPY_NOTSWAPPED - - Make sure the returned array has a data-type descriptor that is in - machine byte-order, over-riding any specification in the *dtype* - argument. Normally, the byte-order requirement is determined by - the *dtype* argument. If this flag is set and the dtype argument - does not indicate a machine byte-order descriptor (or is NULL and - the object is already an array with a data-type descriptor that is - not in machine byte- order), then a new data-type descriptor is - created and used with its byte-order field set to native. - -.. cvar:: NPY_BEHAVED_NS - - :cdata:`NPY_ALIGNED` \| :cdata:`NPY_WRITEABLE` \| :cdata:`NPY_NOTSWAPPED` - -.. cvar:: NPY_ELEMENTSTRIDES - - Make sure the returned array has strides that are multiples of the - element size. - -.. cfunction:: PyObject* PyArray_FromArray(PyArrayObject* op, PyArray_Descr* newtype, int requirements) - - Special case of :cfunc:`PyArray_FromAny` for when *op* is already an - array but it needs to be of a specific *newtype* (including - byte-order) or has certain *requirements*. - -.. cfunction:: PyObject* PyArray_FromStructInterface(PyObject* op) - - Returns an ndarray object from a Python object that exposes the - :obj:`__array_struct__`` method and follows the array interface - protocol. If the object does not contain this method then a - borrowed reference to :cdata:`Py_NotImplemented` is returned. - -.. cfunction:: PyObject* PyArray_FromInterface(PyObject* op) - - Returns an ndarray object from a Python object that exposes the - :obj:`__array_shape__` and :obj:`__array_typestr__` - methods following - the array interface protocol. If the object does not contain one - of these method then a borrowed reference to :cdata:`Py_NotImplemented` - is returned. - -.. cfunction:: PyObject* PyArray_FromArrayAttr(PyObject* op, PyArray_Descr* dtype, PyObject* context) - - Return an ndarray object from a Python object that exposes the - :obj:`__array__` method. The :obj:`__array__` method can take 0, 1, or 2 - arguments ([dtype, context]) where *context* is used to pass - information about where the :obj:`__array__` method is being called - from (currently only used in ufuncs). - -.. cfunction:: PyObject* PyArray_ContiguousFromAny(PyObject* op, int typenum, int min_depth, int max_depth) - - This function returns a (C-style) contiguous and behaved function - array from any nested sequence or array interface exporting - object, *op*, of (non-flexible) type given by the enumerated - *typenum*, of minimum depth *min_depth*, and of maximum depth - *max_depth*. Equivalent to a call to :cfunc:`PyArray_FromAny` with - requirements set to :cdata:`NPY_DEFAULT` and the type_num member of the - type argument set to *typenum*. - -.. cfunction:: PyObject *PyArray_FromObject(PyObject *op, int typenum, int min_depth, int max_depth) - - Return an aligned and in native-byteorder array from any nested - sequence or array-interface exporting object, op, of a type given by - the enumerated typenum. The minimum number of dimensions the array can - have is given by min_depth while the maximum is max_depth. This is - equivalent to a call to :cfunc:`PyArray_FromAny` with requirements set to - BEHAVED. - -.. cfunction:: PyObject* PyArray_EnsureArray(PyObject* op) - - This function **steals a reference** to ``op`` and makes sure that - ``op`` is a base-class ndarray. It special cases array scalars, - but otherwise calls :cfunc:`PyArray_FromAny` ( ``op``, NULL, 0, 0, - :cdata:`NPY_ENSUREARRAY`). - -.. cfunction:: PyObject* PyArray_FromString(char* string, npy_intp slen, PyArray_Descr* dtype, npy_intp num, char* sep) - - Construct a one-dimensional ndarray of a single type from a binary - or (ASCII) text ``string`` of length ``slen``. The data-type of - the array to-be-created is given by ``dtype``. If num is -1, then - **copy** the entire string and return an appropriately sized - array, otherwise, ``num`` is the number of items to **copy** from - the string. If ``sep`` is NULL (or ""), then interpret the string - as bytes of binary data, otherwise convert the sub-strings - separated by ``sep`` to items of data-type ``dtype``. Some - data-types may not be readable in text mode and an error will be - raised if that occurs. All errors return NULL. - -.. cfunction:: PyObject* PyArray_FromFile(FILE* fp, PyArray_Descr* dtype, npy_intp num, char* sep) - - Construct a one-dimensional ndarray of a single type from a binary - or text file. The open file pointer is ``fp``, the data-type of - the array to be created is given by ``dtype``. This must match - the data in the file. If ``num`` is -1, then read until the end of - the file and return an appropriately sized array, otherwise, - ``num`` is the number of items to read. If ``sep`` is NULL (or - ""), then read from the file in binary mode, otherwise read from - the file in text mode with ``sep`` providing the item - separator. Some array types cannot be read in text mode in which - case an error is raised. - -.. cfunction:: PyObject* PyArray_FromBuffer(PyObject* buf, PyArray_Descr* dtype, npy_intp count, npy_intp offset) - - Construct a one-dimensional ndarray of a single type from an - object, ``buf``, that exports the (single-segment) buffer protocol - (or has an attribute __buffer\__ that returns an object that - exports the buffer protocol). A writeable buffer will be tried - first followed by a read- only buffer. The :cdata:`NPY_WRITEABLE` - flag of the returned array will reflect which one was - successful. The data is assumed to start at ``offset`` bytes from - the start of the memory location for the object. The type of the - data in the buffer will be interpreted depending on the data- type - descriptor, ``dtype.`` If ``count`` is negative then it will be - determined from the size of the buffer and the requested itemsize, - otherwise, ``count`` represents how many elements should be - converted from the buffer. - -.. cfunction:: int PyArray_CopyInto(PyArrayObject* dest, PyArrayObject* src) - - Copy from the source array, ``src``, into the destination array, - ``dest``, performing a data-type conversion if necessary. If an - error occurs return -1 (otherwise 0). The shape of ``src`` must be - broadcastable to the shape of ``dest``. The data areas of dest - and src must not overlap. - -.. cfunction:: int PyArray_MoveInto(PyArrayObject* dest, PyArrayObject* src) - - Move data from the source array, ``src``, into the destination - array, ``dest``, performing a data-type conversion if - necessary. If an error occurs return -1 (otherwise 0). The shape - of ``src`` must be broadcastable to the shape of ``dest``. The - data areas of dest and src may overlap. - -.. cfunction:: PyArrayObject* PyArray_GETCONTIGUOUS(PyObject* op) - - If ``op`` is already (C-style) contiguous and well-behaved then - just return a reference, otherwise return a (contiguous and - well-behaved) copy of the array. The parameter op must be a - (sub-class of an) ndarray and no checking for that is done. - -.. cfunction:: PyObject* PyArray_FROM_O(PyObject* obj) - - Convert ``obj`` to an ndarray. The argument can be any nested - sequence or object that exports the array interface. This is a - macro form of :cfunc:`PyArray_FromAny` using ``NULL``, 0, 0, 0 for the - other arguments. Your code must be able to handle any data-type - descriptor and any combination of data-flags to use this macro. - -.. cfunction:: PyObject* PyArray_FROM_OF(PyObject* obj, int requirements) - - Similar to :cfunc:`PyArray_FROM_O` except it can take an argument - of *requirements* indicating properties the resulting array must - have. Available requirements that can be enforced are - :cdata:`NPY_CONTIGUOUS`, :cdata:`NPY_F_CONTIGUOUS`, - :cdata:`NPY_ALIGNED`, :cdata:`NPY_WRITEABLE`, - :cdata:`NPY_NOTSWAPPED`, :cdata:`NPY_ENSURECOPY`, - :cdata:`NPY_UPDATEIFCOPY`, :cdata:`NPY_FORCECAST`, and - :cdata:`NPY_ENSUREARRAY`. Standard combinations of flags can also - be used: - -.. cfunction:: PyObject* PyArray_FROM_OT(PyObject* obj, int typenum) - - Similar to :cfunc:`PyArray_FROM_O` except it can take an argument of - *typenum* specifying the type-number the returned array. - -.. cfunction:: PyObject* PyArray_FROM_OTF(PyObject* obj, int typenum, int requirements) - - Combination of :cfunc:`PyArray_FROM_OF` and :cfunc:`PyArray_FROM_OT` - allowing both a *typenum* and a *flags* argument to be provided.. - -.. cfunction:: PyObject* PyArray_FROMANY(PyObject* obj, int typenum, int min, int max, int requirements) - - Similar to :cfunc:`PyArray_FromAny` except the data-type is - specified using a typenumber. :cfunc:`PyArray_DescrFromType` - (*typenum*) is passed directly to :cfunc:`PyArray_FromAny`. This - macro also adds :cdata:`NPY_DEFAULT` to requirements if - :cdata:`NPY_ENSURECOPY` is passed in as requirements. - -.. cfunction:: PyObject *PyArray_CheckAxis(PyObject* obj, int* axis, int requirements) - - Encapsulate the functionality of functions and methods that take - the axis= keyword and work properly with None as the axis - argument. The input array is ``obj``, while ``*axis`` is a - converted integer (so that >=MAXDIMS is the None value), and - ``requirements`` gives the needed properties of ``obj``. The - output is a converted version of the input so that requirements - are met and if needed a flattening has occurred. On output - negative values of ``*axis`` are converted and the new value is - checked to ensure consistency with the shape of ``obj``. - - -Dealing with types ------------------- - - -General check of Python Type -^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. cfunction:: PyArray_Check(op) - - Evaluates true if *op* is a Python object whose type is a sub-type - of :cdata:`PyArray_Type`. - -.. cfunction:: PyArray_CheckExact(op) - - Evaluates true if *op* is a Python object with type - :cdata:`PyArray_Type`. - -.. cfunction:: PyArray_HasArrayInterface(op, out) - - If ``op`` implements any part of the array interface, then ``out`` - will contain a new reference to the newly created ndarray using - the interface or ``out`` will contain ``NULL`` if an error during - conversion occurs. Otherwise, out will contain a borrowed - reference to :cdata:`Py_NotImplemented` and no error condition is set. - -.. cfunction:: PyArray_HasArrayInterfaceType(op, type, context, out) - - If ``op`` implements any part of the array interface, then ``out`` - will contain a new reference to the newly created ndarray using - the interface or ``out`` will contain ``NULL`` if an error during - conversion occurs. Otherwise, out will contain a borrowed - reference to Py_NotImplemented and no error condition is set. - This version allows setting of the type and context in the part of - the array interface that looks for the :obj:`__array__` attribute. - -.. cfunction:: PyArray_IsZeroDim(op) - - Evaluates true if *op* is an instance of (a subclass of) - :cdata:`PyArray_Type` and has 0 dimensions. - -.. cfunction:: PyArray_IsScalar(op, cls) - - Evaluates true if *op* is an instance of :cdata:`Py{cls}ArrType_Type`. - -.. cfunction:: PyArray_CheckScalar(op) - - Evaluates true if *op* is either an array scalar (an instance of a - sub-type of :cdata:`PyGenericArr_Type` ), or an instance of (a - sub-class of) :cdata:`PyArray_Type` whose dimensionality is 0. - -.. cfunction:: PyArray_IsPythonScalar(op) - - Evaluates true if *op* is a builtin Python "scalar" object (int, - float, complex, str, unicode, long, bool). - -.. cfunction:: PyArray_IsAnyScalar(op) - - Evaluates true if *op* is either a Python scalar or an array - scalar (an instance of a sub- type of :cdata:`PyGenericArr_Type` ). - - -Data-type checking -^^^^^^^^^^^^^^^^^^ - -For the typenum macros, the argument is an integer representing an -enumerated array data type. For the array type checking macros the -argument must be a :ctype:`PyObject *` that can be directly interpreted as a -:ctype:`PyArrayObject *`. - -.. cfunction:: PyTypeNum_ISUNSIGNED(num) - -.. cfunction:: PyDataType_ISUNSIGNED(descr) - -.. cfunction:: PyArray_ISUNSIGNED(obj) - - Type represents an unsigned integer. - -.. cfunction:: PyTypeNum_ISSIGNED(num) - -.. cfunction:: PyDataType_ISSIGNED(descr) - -.. cfunction:: PyArray_ISSIGNED(obj) - - Type represents a signed integer. - -.. cfunction:: PyTypeNum_ISINTEGER(num) - -.. cfunction:: PyDataType_ISINTEGER(descr) - -.. cfunction:: PyArray_ISINTEGER(obj) - - Type represents any integer. - -.. cfunction:: PyTypeNum_ISFLOAT(num) - -.. cfunction:: PyDataType_ISFLOAT(descr) - -.. cfunction:: PyArray_ISFLOAT(obj) - - Type represents any floating point number. - -.. cfunction:: PyTypeNum_ISCOMPLEX(num) - -.. cfunction:: PyDataType_ISCOMPLEX(descr) - -.. cfunction:: PyArray_ISCOMPLEX(obj) - - Type represents any complex floating point number. - -.. cfunction:: PyTypeNum_ISNUMBER(num) - -.. cfunction:: PyDataType_ISNUMBER(descr) - -.. cfunction:: PyArray_ISNUMBER(obj) - - Type represents any integer, floating point, or complex floating point - number. - -.. cfunction:: PyTypeNum_ISSTRING(num) - -.. cfunction:: PyDataType_ISSTRING(descr) - -.. cfunction:: PyArray_ISSTRING(obj) - - Type represents a string data type. - -.. cfunction:: PyTypeNum_ISPYTHON(num) - -.. cfunction:: PyDataType_ISPYTHON(descr) - -.. cfunction:: PyArray_ISPYTHON(obj) - - Type represents an enumerated type corresponding to one of the - standard Python scalar (bool, int, float, or complex). - -.. cfunction:: PyTypeNum_ISFLEXIBLE(num) - -.. cfunction:: PyDataType_ISFLEXIBLE(descr) - -.. cfunction:: PyArray_ISFLEXIBLE(obj) - - Type represents one of the flexible array types ( :cdata:`NPY_STRING`, - :cdata:`NPY_UNICODE`, or :cdata:`NPY_VOID` ). - -.. cfunction:: PyTypeNum_ISUSERDEF(num) - -.. cfunction:: PyDataType_ISUSERDEF(descr) - -.. cfunction:: PyArray_ISUSERDEF(obj) - - Type represents a user-defined type. - -.. cfunction:: PyTypeNum_ISEXTENDED(num) - -.. cfunction:: PyDataType_ISEXTENDED(descr) - -.. cfunction:: PyArray_ISEXTENDED(obj) - - Type is either flexible or user-defined. - -.. cfunction:: PyTypeNum_ISOBJECT(num) - -.. cfunction:: PyDataType_ISOBJECT(descr) - -.. cfunction:: PyArray_ISOBJECT(obj) - - Type represents object data type. - -.. cfunction:: PyTypeNum_ISBOOL(num) - -.. cfunction:: PyDataType_ISBOOL(descr) - -.. cfunction:: PyArray_ISBOOL(obj) - - Type represents Boolean data type. - -.. cfunction:: PyDataType_HASFIELDS(descr) - -.. cfunction:: PyArray_HASFIELDS(obj) - - Type has fields associated with it. - -.. cfunction:: PyArray_ISNOTSWAPPED(m) - - Evaluates true if the data area of the ndarray *m* is in machine - byte-order according to the array's data-type descriptor. - -.. cfunction:: PyArray_ISBYTESWAPPED(m) - - Evaluates true if the data area of the ndarray *m* is **not** in - machine byte-order according to the array's data-type descriptor. - -.. cfunction:: Bool PyArray_EquivTypes(PyArray_Descr* type1, PyArray_Descr* type2) - - Return :cdata:`NPY_TRUE` if *type1* and *type2* actually represent - equivalent types for this platform (the fortran member of each - type is ignored). For example, on 32-bit platforms, - :cdata:`NPY_LONG` and :cdata:`NPY_INT` are equivalent. Otherwise - return :cdata:`NPY_FALSE`. - -.. cfunction:: Bool PyArray_EquivArrTypes(PyArrayObject* a1, PyArrayObject * a2) - - Return :cdata:`NPY_TRUE` if *a1* and *a2* are arrays with equivalent - types for this platform. - -.. cfunction:: Bool PyArray_EquivTypenums(int typenum1, int typenum2) - - Special case of :cfunc:`PyArray_EquivTypes` (...) that does not accept - flexible data types but may be easier to call. - -.. cfunction:: int PyArray_EquivByteorders({byteorder} b1, {byteorder} b2) - - True if byteorder characters ( :cdata:`NPY_LITTLE`, - :cdata:`NPY_BIG`, :cdata:`NPY_NATIVE`, :cdata:`NPY_IGNORE` ) are - either equal or equivalent as to their specification of a native - byte order. Thus, on a little-endian machine :cdata:`NPY_LITTLE` - and :cdata:`NPY_NATIVE` are equivalent where they are not - equivalent on a big-endian machine. - - -Converting data types -^^^^^^^^^^^^^^^^^^^^^ - -.. cfunction:: PyObject* PyArray_Cast(PyArrayObject* arr, int typenum) - - Mainly for backwards compatibility to the Numeric C-API and for - simple casts to non-flexible types. Return a new array object with - the elements of *arr* cast to the data-type *typenum* which must - be one of the enumerated types and not a flexible type. - -.. cfunction:: PyObject* PyArray_CastToType(PyArrayObject* arr, PyArray_Descr* type, int fortran) - - Return a new array of the *type* specified, casting the elements - of *arr* as appropriate. The fortran argument specifies the - ordering of the output array. - -.. cfunction:: int PyArray_CastTo(PyArrayObject* out, PyArrayObject* in) - - Cast the elements of the array *in* into the array *out*. The - output array should be writeable, have an integer-multiple of the - number of elements in the input array (more than one copy can be - placed in out), and have a data type that is one of the builtin - types. Returns 0 on success and -1 if an error occurs. - -.. cfunction:: PyArray_VectorUnaryFunc* PyArray_GetCastFunc(PyArray_Descr* from, int totype) - - Return the low-level casting function to cast from the given - descriptor to the builtin type number. If no casting function - exists return ``NULL`` and set an error. Using this function - instead of direct access to *from* ->f->cast will allow support of - any user-defined casting functions added to a descriptors casting - dictionary. - -.. cfunction:: int PyArray_CanCastSafely(int fromtype, int totype) - - Returns non-zero if an array of data type *fromtype* can be cast - to an array of data type *totype* without losing information. An - exception is that 64-bit integers are allowed to be cast to 64-bit - floating point values even though this can lose precision on large - integers so as not to proliferate the use of long doubles without - explict requests. Flexible array types are not checked according - to their lengths with this function. - -.. cfunction:: int PyArray_CanCastTo(PyArray_Descr* fromtype, PyArray_Descr* totype) - - Returns non-zero if an array of data type *fromtype* (which can - include flexible types) can be cast safely to an array of data - type *totype* (which can include flexible types). This is - basically a wrapper around :cfunc:`PyArray_CanCastSafely` with - additional support for size checking if *fromtype* and *totype* - are :cdata:`NPY_STRING` or :cdata:`NPY_UNICODE`. - -.. cfunction:: int PyArray_ObjectType(PyObject* op, int mintype) - - This function is useful for determining a common type that two or - more arrays can be converted to. It only works for non-flexible - array types as no itemsize information is passed. The *mintype* - argument represents the minimum type acceptable, and *op* - represents the object that will be converted to an array. The - return value is the enumerated typenumber that represents the - data-type that *op* should have. - -.. cfunction:: void PyArray_ArrayType(PyObject* op, PyArray_Descr* mintype, PyArray_Descr* outtype) - - This function works similarly to :cfunc:`PyArray_ObjectType` (...) - except it handles flexible arrays. The *mintype* argument can have - an itemsize member and the *outtype* argument will have an - itemsize member at least as big but perhaps bigger depending on - the object *op*. - -.. cfunction:: PyArrayObject** PyArray_ConvertToCommonType(PyObject* op, int* n) - - Convert a sequence of Python objects contained in *op* to an array - of ndarrays each having the same data type. The type is selected - based on the typenumber (larger type number is chosen over a - smaller one) ignoring objects that are only scalars. The length of - the sequence is returned in *n*, and an *n* -length array of - :ctype:`PyArrayObject` pointers is the return value (or ``NULL`` if an - error occurs). The returned array must be freed by the caller of - this routine (using :cfunc:`PyDataMem_FREE` ) and all the array objects - in it ``DECREF`` 'd or a memory-leak will occur. The example - template-code below shows a typically usage: - - .. code-block:: c - - mps = PyArray_ConvertToCommonType(obj, &n); - if (mps==NULL) return NULL; - {code} - <before return> - for (i=0; i<n; i++) Py_DECREF(mps[i]); - PyDataMem_FREE(mps); - {return} - -.. cfunction:: char* PyArray_Zero(PyArrayObject* arr) - - A pointer to newly created memory of size *arr* ->itemsize that - holds the representation of 0 for that type. The returned pointer, - *ret*, **must be freed** using :cfunc:`PyDataMem_FREE` (ret) when it is - not needed anymore. - -.. cfunction:: char* PyArray_One(PyArrayObject* arr) - - A pointer to newly created memory of size *arr* ->itemsize that - holds the representation of 1 for that type. The returned pointer, - *ret*, **must be freed** using :cfunc:`PyDataMem_FREE` (ret) when it - is not needed anymore. - -.. cfunction:: int PyArray_ValidType(int typenum) - - Returns :cdata:`NPY_TRUE` if *typenum* represents a valid type-number - (builtin or user-defined or character code). Otherwise, this - function returns :cdata:`NPY_FALSE`. - - -New data types -^^^^^^^^^^^^^^ - -.. cfunction:: void PyArray_InitArrFuncs(PyArray_ArrFuncs* f) - - Initialize all function pointers and members to ``NULL``. - -.. cfunction:: int PyArray_RegisterDataType(PyArray_Descr* dtype) - - Register a data-type as a new user-defined data type for - arrays. The type must have most of its entries filled in. This is - not always checked and errors can produce segfaults. In - particular, the typeobj member of the ``dtype`` structure must be - filled with a Python type that has a fixed-size element-size that - corresponds to the elsize member of *dtype*. Also the ``f`` - member must have the required functions: nonzero, copyswap, - copyswapn, getitem, setitem, and cast (some of the cast functions - may be ``NULL`` if no support is desired). To avoid confusion, you - should choose a unique character typecode but this is not enforced - and not relied on internally. - - A user-defined type number is returned that uniquely identifies - the type. A pointer to the new structure can then be obtained from - :cfunc:`PyArray_DescrFromType` using the returned type number. A -1 is - returned if an error occurs. If this *dtype* has already been - registered (checked only by the address of the pointer), then - return the previously-assigned type-number. - -.. cfunction:: int PyArray_RegisterCastFunc(PyArray_Descr* descr, int totype, PyArray_VectorUnaryFunc* castfunc) - - Register a low-level casting function, *castfunc*, to convert - from the data-type, *descr*, to the given data-type number, - *totype*. Any old casting function is over-written. A ``0`` is - returned on success or a ``-1`` on failure. - -.. cfunction:: int PyArray_RegisterCanCast(PyArray_Descr* descr, int totype, PyArray_SCALARKIND scalar) - - Register the data-type number, *totype*, as castable from - data-type object, *descr*, of the given *scalar* kind. Use - *scalar* = :cdata:`NPY_NOSCALAR` to register that an array of data-type - *descr* can be cast safely to a data-type whose type_number is - *totype*. - - -Special functions for PyArray_OBJECT -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. cfunction:: int PyArray_INCREF(PyArrayObject* op) - - Used for an array, *op*, that contains any Python objects. It - increments the reference count of every object in the array - according to the data-type of *op*. A -1 is returned if an error - occurs, otherwise 0 is returned. - -.. cfunction:: void PyArray_Item_INCREF(char* ptr, PyArray_Descr* dtype) - - A function to INCREF all the objects at the location *ptr* - according to the data-type *dtype*. If *ptr* is the start of a - record with an object at any offset, then this will (recursively) - increment the reference count of all object-like items in the - record. - -.. cfunction:: int PyArray_XDECREF(PyArrayObject* op) - - Used for an array, *op*, that contains any Python objects. It - decrements the reference count of every object in the array - according to the data-type of *op*. Normal return value is 0. A - -1 is returned if an error occurs. - -.. cfunction:: void PyArray_Item_XDECREF(char* ptr, PyArray_Descr* dtype) - - A function to XDECREF all the object-like items at the loacation - *ptr* as recorded in the data-type, *dtype*. This works - recursively so that if ``dtype`` itself has fields with data-types - that contain object-like items, all the object-like fields will be - XDECREF ``'d``. - -.. cfunction:: void PyArray_FillObjectArray(PyArrayObject* arr, PyObject* obj) - - Fill a newly created array with a single value obj at all - locations in the structure with object data-types. No checking is - performed but *arr* must be of data-type :ctype:`PyArray_OBJECT` and be - single-segment and uninitialized (no previous objects in - position). Use :cfunc:`PyArray_DECREF` (*arr*) if you need to - decrement all the items in the object array prior to calling this - function. - - -Array flags ------------ - - -Basic Array Flags -^^^^^^^^^^^^^^^^^ - -An ndarray can have a data segment that is not a simple contiguous -chunk of well-behaved memory you can manipulate. It may not be aligned -with word boundaries (very important on some platforms). It might have -its data in a different byte-order than the machine recognizes. It -might not be writeable. It might be in Fortan-contiguous order. The -array flags are used to indicate what can be said about data -associated with an array. - -.. cvar:: NPY_C_CONTIGUOUS - - The data area is in C-style contiguous order (last index varies the - fastest). - -.. cvar:: NPY_F_CONTIGUOUS - - The data area is in Fortran-style contiguous order (first index varies - the fastest). - -.. cvar:: NPY_OWNDATA - - The data area is owned by this array. - -.. cvar:: NPY_ALIGNED - - The data area is aligned appropriately (for all strides). - -.. cvar:: NPY_WRITEABLE - - The data area can be written to. - - Notice that the above 3 flags are are defined so that a new, well- - behaved array has these flags defined as true. - -.. cvar:: NPY_UPDATEIFCOPY - - The data area represents a (well-behaved) copy whose information - should be transferred back to the original when this array is deleted. - - -Combinations of array flags -^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. cvar:: NPY_BEHAVED - - :cdata:`NPY_ALIGNED` \| :cdata:`NPY_WRITEABLE` - -.. cvar:: NPY_CARRAY - - :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_BEHAVED` - -.. cvar:: NPY_CARRAY_RO - - :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_ALIGNED` - -.. cvar:: NPY_FARRAY - - :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_BEHAVED` - -.. cvar:: NPY_FARRAY_RO - - :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_ALIGNED` - -.. cvar:: NPY_DEFAULT - - :cdata:`NPY_CARRAY` - -.. cvar:: NPY_UPDATE_ALL - - :cdata:`NPY_C_CONTIGUOUS` \| :cdata:`NPY_F_CONTIGUOUS` \| :cdata:`NPY_ALIGNED` - - -Flag-like constants -^^^^^^^^^^^^^^^^^^^ - -These constants are used in :cfunc:`PyArray_FromAny` (and its macro forms) to -specify desired properties of the new array. - -.. cvar:: NPY_FORCECAST - - Cast to the desired type, even if it can't be done without losing - information. - -.. cvar:: NPY_ENSURECOPY - - Make sure the resulting array is a copy of the original. - -.. cvar:: NPY_ENSUREARRAY - - Make sure the resulting object is an actual ndarray (or bigndarray), - and not a sub-class. - -.. cvar:: NPY_NOTSWAPPED - - Only used in :cfunc:`PyArray_CheckFromAny` to over-ride the byteorder - of the data-type object passed in. - -.. cvar:: NPY_BEHAVED_NS - - :cdata:`NPY_ALIGNED` \| :cdata:`NPY_WRITEABLE` \| :cdata:`NPY_NOTSWAPPED` - - -Flag checking -^^^^^^^^^^^^^ - -For all of these macros *arr* must be an instance of a (subclass of) -:cdata:`PyArray_Type`, but no checking is done. - -.. cfunction:: PyArray_CHKFLAGS(arr, flags) - - The first parameter, arr, must be an ndarray or subclass. The - parameter, *flags*, should be an integer consisting of bitwise - combinations of the possible flags an array can have: - :cdata:`NPY_C_CONTIGUOUS`, :cdata:`NPY_F_CONTIGUOUS`, - :cdata:`NPY_OWNDATA`, :cdata:`NPY_ALIGNED`, - :cdata:`NPY_WRITEABLE`, :cdata:`NPY_UPDATEIFCOPY`. - -.. cfunction:: PyArray_ISCONTIGUOUS(arr) - - Evaluates true if *arr* is C-style contiguous. - -.. cfunction:: PyArray_ISFORTRAN(arr) - - Evaluates true if *arr* is Fortran-style contiguous. - -.. cfunction:: PyArray_ISWRITEABLE(arr) - - Evaluates true if the data area of *arr* can be written to - -.. cfunction:: PyArray_ISALIGNED(arr) - - Evaluates true if the data area of *arr* is properly aligned on - the machine. - -.. cfunction:: PyArray_ISBEHAVED(arr) - - Evalutes true if the data area of *arr* is aligned and writeable - and in machine byte-order according to its descriptor. - -.. cfunction:: PyArray_ISBEHAVED_RO(arr) - - Evaluates true if the data area of *arr* is aligned and in machine - byte-order. - -.. cfunction:: PyArray_ISCARRAY(arr) - - Evaluates true if the data area of *arr* is C-style contiguous, - and :cfunc:`PyArray_ISBEHAVED` (*arr*) is true. - -.. cfunction:: PyArray_ISFARRAY(arr) - - Evaluates true if the data area of *arr* is Fortran-style - contiguous and :cfunc:`PyArray_ISBEHAVED` (*arr*) is true. - -.. cfunction:: PyArray_ISCARRAY_RO(arr) - - Evaluates true if the data area of *arr* is C-style contiguous, - aligned, and in machine byte-order. - -.. cfunction:: PyArray_ISFARRAY_RO(arr) - - Evaluates true if the data area of *arr* is Fortran-style - contiguous, aligned, and in machine byte-order **.** - -.. cfunction:: PyArray_ISONESEGMENT(arr) - - Evaluates true if the data area of *arr* consists of a single - (C-style or Fortran-style) contiguous segment. - -.. cfunction:: void PyArray_UpdateFlags(PyArrayObject* arr, int flagmask) - - The :cdata:`NPY_C_CONTIGUOUS`, :cdata:`NPY_ALIGNED`, and - :cdata:`NPY_F_CONTIGUOUS` array flags can be "calculated" from the - array object itself. This routine updates one or more of these - flags of *arr* as specified in *flagmask* by performing the - required calculation. - - -.. warning:: - - It is important to keep the flags updated (using - :cfunc:`PyArray_UpdateFlags` can help) whenever a manipulation with an - array is performed that might cause them to change. Later - calculations in NumPy that rely on the state of these flags do not - repeat the calculation to update them. - - -Array method alternative API ----------------------------- - - -Conversion -^^^^^^^^^^ - -.. cfunction:: PyObject* PyArray_GetField(PyArrayObject* self, PyArray_Descr* dtype, int offset) - - Equivalent to :meth:`ndarray.getfield` (*self*, *dtype*, *offset*). Return - a new array of the given *dtype* using the data in the current - array at a specified *offset* in bytes. The *offset* plus the - itemsize of the new array type must be less than *self* - ->descr->elsize or an error is raised. The same shape and strides - as the original array are used. Therefore, this function has the - effect of returning a field from a record array. But, it can also - be used to select specific bytes or groups of bytes from any array - type. - -.. cfunction:: int PyArray_SetField(PyArrayObject* self, PyArray_Descr* dtype, int offset, PyObject* val) - - Equivalent to :meth:`ndarray.setfield` (*self*, *val*, *dtype*, *offset* - ). Set the field starting at *offset* in bytes and of the given - *dtype* to *val*. The *offset* plus *dtype* ->elsize must be less - than *self* ->descr->elsize or an error is raised. Otherwise, the - *val* argument is converted to an array and copied into the field - pointed to. If necessary, the elements of *val* are repeated to - fill the destination array, But, the number of elements in the - destination must be an integer multiple of the number of elements - in *val*. - -.. cfunction:: PyObject* PyArray_Byteswap(PyArrayObject* self, Bool inplace) - - Equivalent to :meth:`ndarray.byteswap` (*self*, *inplace*). Return an array - whose data area is byteswapped. If *inplace* is non-zero, then do - the byteswap inplace and return a reference to self. Otherwise, - create a byteswapped copy and leave self unchanged. - -.. cfunction:: PyObject* PyArray_NewCopy(PyArrayObject* old, NPY_ORDER order) - - Equivalent to :meth:`ndarray.copy` (*self*, *fortran*). Make a copy of the - *old* array. The returned array is always aligned and writeable - with data interpreted the same as the old array. If *order* is - :cdata:`NPY_CORDER`, then a C-style contiguous array is returned. If - *order* is :cdata:`NPY_FORTRANORDER`, then a Fortran-style contiguous - array is returned. If *order is* :cdata:`NPY_ANYORDER`, then the array - returned is Fortran-style contiguous only if the old one is; - otherwise, it is C-style contiguous. - -.. cfunction:: PyObject* PyArray_ToList(PyArrayObject* self) - - Equivalent to :meth:`ndarray.tolist` (*self*). Return a nested Python list - from *self*. - -.. cfunction:: PyObject* PyArray_ToString(PyArrayObject* self, NPY_ORDER order) - - Equivalent to :meth:`ndarray.tostring` (*self*, *order*). Return the bytes - of this array in a Python string. - -.. cfunction:: PyObject* PyArray_ToFile(PyArrayObject* self, FILE* fp, char* sep, char* format) - - Write the contents of *self* to the file pointer *fp* in C-style - contiguous fashion. Write the data as binary bytes if *sep* is the - string ""or ``NULL``. Otherwise, write the contents of *self* as - text using the *sep* string as the item separator. Each item will - be printed to the file. If the *format* string is not ``NULL`` or - "", then it is a Python print statement format string showing how - the items are to be written. - -.. cfunction:: int PyArray_Dump(PyObject* self, PyObject* file, int protocol) - - Pickle the object in *self* to the given *file* (either a string - or a Python file object). If *file* is a Python string it is - considered to be the name of a file which is then opened in binary - mode. The given *protocol* is used (if *protocol* is negative, or - the highest available is used). This is a simple wrapper around - cPickle.dump(*self*, *file*, *protocol*). - -.. cfunction:: PyObject* PyArray_Dumps(PyObject* self, int protocol) - - Pickle the object in *self* to a Python string and return it. Use - the Pickle *protocol* provided (or the highest available if - *protocol* is negative). - -.. cfunction:: int PyArray_FillWithScalar(PyArrayObject* arr, PyObject* obj) - - Fill the array, *arr*, with the given scalar object, *obj*. The - object is first converted to the data type of *arr*, and then - copied into every location. A -1 is returned if an error occurs, - otherwise 0 is returned. - -.. cfunction:: PyObject* PyArray_View(PyArrayObject* self, PyArray_Descr* dtype) - - Equivalent to :meth:`ndarray.view` (*self*, *dtype*). Return a new view of - the array *self* as possibly a different data-type, *dtype*. If - *dtype* is ``NULL``, then the returned array will have the same - data type as *self*. The new data-type must be consistent with - the size of *self*. Either the itemsizes must be identical, or - *self* must be single-segment and the total number of bytes must - be the same. In the latter case the dimensions of the returned - array will be altered in the last (or first for Fortran-style - contiguous arrays) dimension. The data area of the returned array - and self is exactly the same. - - -Shape Manipulation -^^^^^^^^^^^^^^^^^^ - -.. cfunction:: PyObject* PyArray_Newshape(PyArrayObject* self, PyArray_Dims* newshape) - - Result will be a new array (pointing to the same memory location - as *self* if possible), but having a shape given by *newshape* - . If the new shape is not compatible with the strides of *self*, - then a copy of the array with the new specified shape will be - returned. - -.. cfunction:: PyObject* PyArray_Reshape(PyArrayObject* self, PyObject* shape) - - Equivalent to :meth:`ndarray.reshape` (*self*, *shape*) where *shape* is a - sequence. Converts *shape* to a :ctype:`PyArray_Dims` structure and - calls :cfunc:`PyArray_Newshape` internally. - -.. cfunction:: PyObject* PyArray_Squeeze(PyArrayObject* self) - - Equivalent to :meth:`ndarray.squeeze` (*self*). Return a new view of *self* - with all of the dimensions of length 1 removed from the shape. - -.. warning:: - - matrix objects are always 2-dimensional. Therefore, - :cfunc:`PyArray_Squeeze` has no effect on arrays of matrix sub-class. - -.. cfunction:: PyObject* PyArray_SwapAxes(PyArrayObject* self, int a1, int a2) - - Equivalent to :meth:`ndarray.swapaxes` (*self*, *a1*, *a2*). The returned - array is a new view of the data in *self* with the given axes, - *a1* and *a2*, swapped. - -.. cfunction:: PyObject* PyArray_Resize(PyArrayObject* self, PyArray_Dims* newshape, int refcheck, NPY_ORDER fortran) - - Equivalent to :meth:`ndarray.resize` (*self*, *newshape*, refcheck - ``=`` *refcheck*, order= fortran ). This function only works on - single-segment arrays. It changes the shape of *self* inplace and - will reallocate the memory for *self* if *newshape* has a - different total number of elements then the old shape. If - reallocation is necessary, then *self* must own its data, have - *self* - ``>base==NULL``, have *self* - ``>weakrefs==NULL``, and - (unless refcheck is 0) not be referenced by any other array. A - reference to the new array is returned. The fortran argument can - be :cdata:`NPY_ANYORDER`, :cdata:`NPY_CORDER`, or - :cdata:`NPY_FORTRANORDER`. This argument is used if the number of - dimension is (or is being resized to be) greater than 2. It - currently has no effect. Eventually it could be used to determine - how the resize operation should view the data when constructing a - differently-dimensioned array. - -.. cfunction:: PyObject* PyArray_Transpose(PyArrayObject* self, PyArray_Dims* permute) - - Equivalent to :meth:`ndarray.transpose` (*self*, *permute*). Permute the - axes of the ndarray object *self* according to the data structure - *permute* and return the result. If *permute* is ``NULL``, then - the resulting array has its axes reversed. For example if *self* - has shape :math:`10\times20\times30`, and *permute* ``.ptr`` is - (0,2,1) the shape of the result is :math:`10\times30\times20.` If - *permute* is ``NULL``, the shape of the result is - :math:`30\times20\times10.` - -.. cfunction:: PyObject* PyArray_Flatten(PyArrayObject* self, NPY_ORDER order) - - Equivalent to :meth:`ndarray.flatten` (*self*, *order*). Return a 1-d copy - of the array. If *order* is :cdata:`NPY_FORTRANORDER` the elements are - scanned out in Fortran order (first-dimension varies the - fastest). If *order* is :cdata:`NPY_CORDER`, the elements of ``self`` - are scanned in C-order (last dimension varies the fastest). If - *order* :cdata:`NPY_ANYORDER`, then the result of - :cfunc:`PyArray_ISFORTRAN` (*self*) is used to determine which order - to flatten. - -.. cfunction:: PyObject* PyArray_Ravel(PyArrayObject* self, NPY_ORDER order) - - Equivalent to *self*.ravel(*order*). Same basic functionality - as :cfunc:`PyArray_Flatten` (*self*, *order*) except if *order* is 0 - and *self* is C-style contiguous, the shape is altered but no copy - is performed. - - -Item selection and manipulation -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. cfunction:: PyObject* PyArray_TakeFrom(PyArrayObject* self, PyObject* indices, int axis, PyArrayObject* ret, NPY_CLIPMODE clipmode) - - Equivalent to :meth:`ndarray.take` (*self*, *indices*, *axis*, *ret*, - *clipmode*) except *axis* =None in Python is obtained by setting - *axis* = :cdata:`NPY_MAXDIMS` in C. Extract the items from self - indicated by the integer-valued *indices* along the given *axis.* - The clipmode argument can be :cdata:`NPY_RAISE`, :cdata:`NPY_WRAP`, or - :cdata:`NPY_CLIP` to indicate what to do with out-of-bound indices. The - *ret* argument can specify an output array rather than having one - created internally. - -.. cfunction:: PyObject* PyArray_PutTo(PyArrayObject* self, PyObject* values, PyObject* indices, NPY_CLIPMODE clipmode) - - Equivalent to *self*.put(*values*, *indices*, *clipmode* - ). Put *values* into *self* at the corresponding (flattened) - *indices*. If *values* is too small it will be repeated as - necessary. - -.. cfunction:: PyObject* PyArray_PutMask(PyArrayObject* self, PyObject* values, PyObject* mask) - - Place the *values* in *self* wherever corresponding positions - (using a flattened context) in *mask* are true. The *mask* and - *self* arrays must have the same total number of elements. If - *values* is too small, it will be repeated as necessary. - -.. cfunction:: PyObject* PyArray_Repeat(PyArrayObject* self, PyObject* op, int axis) - - Equivalent to :meth:`ndarray.repeat` (*self*, *op*, *axis*). Copy the - elements of *self*, *op* times along the given *axis*. Either - *op* is a scalar integer or a sequence of length *self* - ->dimensions[ *axis* ] indicating how many times to repeat each - item along the axis. - -.. cfunction:: PyObject* PyArray_Choose(PyArrayObject* self, PyObject* op, PyArrayObject* ret, NPY_CLIPMODE clipmode) - - Equivalent to :meth:`ndarray.choose` (*self*, *op*, *ret*, *clipmode*). - Create a new array by selecting elements from the sequence of - arrays in *op* based on the integer values in *self*. The arrays - must all be broadcastable to the same shape and the entries in - *self* should be between 0 and len(*op*). The output is placed - in *ret* unless it is ``NULL`` in which case a new output is - created. The *clipmode* argument determines behavior for when - entries in *self* are not between 0 and len(*op*). - - .. cvar:: NPY_RAISE - - raise a ValueError; - - .. cvar:: NPY_WRAP - - wrap values < 0 by adding len(*op*) and values >=len(*op*) - by subtracting len(*op*) until they are in range; - - .. cvar:: NPY_CLIP - - all values are clipped to the region [0, len(*op*) ). - - -.. cfunction:: PyObject* PyArray_Sort(PyArrayObject* self, int axis) - - Equivalent to :meth:`ndarray.sort` (*self*, *axis*). Return an array with - the items of *self* sorted along *axis*. - -.. cfunction:: PyObject* PyArray_ArgSort(PyArrayObject* self, int axis) - - Equivalent to :meth:`ndarray.argsort` (*self*, *axis*). Return an array of - indices such that selection of these indices along the given - ``axis`` would return a sorted version of *self*. If *self* - ->descr is a data-type with fields defined, then - self->descr->names is used to determine the sort order. A - comparison where the first field is equal will use the second - field and so on. To alter the sort order of a record array, create - a new data-type with a different order of names and construct a - view of the array with that new data-type. - -.. cfunction:: PyObject* PyArray_LexSort(PyObject* sort_keys, int axis) - - Given a sequence of arrays (*sort_keys*) of the same shape, - return an array of indices (similar to :cfunc:`PyArray_ArgSort` (...)) - that would sort the arrays lexicographically. A lexicographic sort - specifies that when two keys are found to be equal, the order is - based on comparison of subsequent keys. A merge sort (which leaves - equal entries unmoved) is required to be defined for the - types. The sort is accomplished by sorting the indices first using - the first *sort_key* and then using the second *sort_key* and so - forth. This is equivalent to the lexsort(*sort_keys*, *axis*) - Python command. Because of the way the merge-sort works, be sure - to understand the order the *sort_keys* must be in (reversed from - the order you would use when comparing two elements). - - If these arrays are all collected in a record array, then - :cfunc:`PyArray_Sort` (...) can also be used to sort the array - directly. - -.. cfunction:: PyObject* PyArray_SearchSorted(PyArrayObject* self, PyObject* values) - - Equivalent to :meth:`ndarray.searchsorted` (*self*, *values*). Assuming - *self* is a 1-d array in ascending order representing bin - boundaries then the output is an array the same shape as *values* - of bin numbers, giving the bin into which each item in *values* - would be placed. No checking is done on whether or not self is in - ascending order. - -.. cfunction:: PyObject* PyArray_Diagonal(PyArrayObject* self, int offset, int axis1, int axis2) - - Equivalent to :meth:`ndarray.diagonal` (*self*, *offset*, *axis1*, *axis2* - ). Return the *offset* diagonals of the 2-d arrays defined by - *axis1* and *axis2*. - -.. cfunction:: PyObject* PyArray_Nonzero(PyArrayObject* self) - - Equivalent to :meth:`ndarray.nonzero` (*self*). Returns a tuple of index - arrays that select elements of *self* that are nonzero. If (nd= - :cfunc:`PyArray_NDIM` ( ``self`` ))==1, then a single index array is - returned. The index arrays have data type :cdata:`NPY_INTP`. If a - tuple is returned (nd :math:`\neq` 1), then its length is nd. - -.. cfunction:: PyObject* PyArray_Compress(PyArrayObject* self, PyObject* condition, int axis, PyArrayObject* out) - - Equivalent to :meth:`ndarray.compress` (*self*, *condition*, *axis* - ). Return the elements along *axis* corresponding to elements of - *condition* that are true. - - -Calculation -^^^^^^^^^^^ - -.. tip:: - - Pass in :cdata:`NPY_MAXDIMS` for axis in order to achieve the same - effect that is obtained by passing in *axis* = :const:`None` in Python - (treating the array as a 1-d array). - -.. cfunction:: PyObject* PyArray_ArgMax(PyArrayObject* self, int axis) - - Equivalent to :meth:`ndarray.argmax` (*self*, *axis*). Return the index of - the largest element of *self* along *axis*. - -.. cfunction:: PyObject* PyArray_ArgMin(PyArrayObject* self, int axis) - - Equivalent to :meth:`ndarray.argmin` (*self*, *axis*). Return the index of - the smallest element of *self* along *axis*. - -.. cfunction:: PyObject* PyArray_Max(PyArrayObject* self, int axis, PyArrayObject* out) - - Equivalent to :meth:`ndarray.max` (*self*, *axis*). Return the largest - element of *self* along the given *axis*. - -.. cfunction:: PyObject* PyArray_Min(PyArrayObject* self, int axis, PyArrayObject* out) - - Equivalent to :meth:`ndarray.min` (*self*, *axis*). Return the smallest - element of *self* along the given *axis*. - -.. cfunction:: PyObject* PyArray_Ptp(PyArrayObject* self, int axis, PyArrayObject* out) - - Equivalent to :meth:`ndarray.ptp` (*self*, *axis*). Return the difference - between the largest element of *self* along *axis* and the - smallest element of *self* along *axis*. - - - -.. note:: - - The rtype argument specifies the data-type the reduction should - take place over. This is important if the data-type of the array - is not "large" enough to handle the output. By default, all - integer data-types are made at least as large as :cdata:`NPY_LONG` - for the "add" and "multiply" ufuncs (which form the basis for - mean, sum, cumsum, prod, and cumprod functions). - -.. cfunction:: PyObject* PyArray_Mean(PyArrayObject* self, int axis, int rtype, PyArrayObject* out) - - Equivalent to :meth:`ndarray.mean` (*self*, *axis*, *rtype*). Returns the - mean of the elements along the given *axis*, using the enumerated - type *rtype* as the data type to sum in. Default sum behavior is - obtained using :cdata:`PyArray_NOTYPE` for *rtype*. - -.. cfunction:: PyObject* PyArray_Trace(PyArrayObject* self, int offset, int axis1, int axis2, int rtype, PyArrayObject* out) - - Equivalent to :meth:`ndarray.trace` (*self*, *offset*, *axis1*, *axis2*, - *rtype*). Return the sum (using *rtype* as the data type of - summation) over the *offset* diagonal elements of the 2-d arrays - defined by *axis1* and *axis2* variables. A positive offset - chooses diagonals above the main diagonal. A negative offset - selects diagonals below the main diagonal. - -.. cfunction:: PyObject* PyArray_Clip(PyArrayObject* self, PyObject* min, PyObject* max) - - Equivalent to :meth:`ndarray.clip` (*self*, *min*, *max*). Clip an array, - *self*, so that values larger than *max* are fixed to *max* and - values less than *min* are fixed to *min*. - -.. cfunction:: PyObject* PyArray_Conjugate(PyArrayObject* self) - - Equivalent to :meth:`ndarray.conjugate` (*self*). - Return the complex conjugate of *self*. If *self* is not of - complex data type, then return *self* with an reference. - -.. cfunction:: PyObject* PyArray_Round(PyArrayObject* self, int decimals, PyArrayObject* out) - - Equivalent to :meth:`ndarray.round` (*self*, *decimals*, *out*). Returns - the array with elements rounded to the nearest decimal place. The - decimal place is defined as the :math:`10^{-\textrm{decimals}}` - digit so that negative *decimals* cause rounding to the nearest 10's, 100's, etc. If out is ``NULL``, then the output array is created, otherwise the output is placed in *out* which must be the correct size and type. - -.. cfunction:: PyObject* PyArray_Std(PyArrayObject* self, int axis, int rtype, PyArrayObject* out) - - Equivalent to :meth:`ndarray.std` (*self*, *axis*, *rtype*). Return the - standard deviation using data along *axis* converted to data type - *rtype*. - -.. cfunction:: PyObject* PyArray_Sum(PyArrayObject* self, int axis, int rtype, PyArrayObject* out) - - Equivalent to :meth:`ndarray.sum` (*self*, *axis*, *rtype*). Return 1-d - vector sums of elements in *self* along *axis*. Perform the sum - after converting data to data type *rtype*. - -.. cfunction:: PyObject* PyArray_CumSum(PyArrayObject* self, int axis, int rtype, PyArrayObject* out) - - Equivalent to :meth:`ndarray.cumsum` (*self*, *axis*, *rtype*). Return - cumulative 1-d sums of elements in *self* along *axis*. Perform - the sum after converting data to data type *rtype*. - -.. cfunction:: PyObject* PyArray_Prod(PyArrayObject* self, int axis, int rtype, PyArrayObject* out) - - Equivalent to :meth:`ndarray.prod` (*self*, *axis*, *rtype*). Return 1-d - products of elements in *self* along *axis*. Perform the product - after converting data to data type *rtype*. - -.. cfunction:: PyObject* PyArray_CumProd(PyArrayObject* self, int axis, int rtype, PyArrayObject* out) - - Equivalent to :meth:`ndarray.cumprod` (*self*, *axis*, *rtype*). Return - 1-d cumulative products of elements in ``self`` along ``axis``. - Perform the product after converting data to data type ``rtype``. - -.. cfunction:: PyObject* PyArray_All(PyArrayObject* self, int axis, PyArrayObject* out) - - Equivalent to :meth:`ndarray.all` (*self*, *axis*). Return an array with - True elements for every 1-d sub-array of ``self`` defined by - ``axis`` in which all the elements are True. - -.. cfunction:: PyObject* PyArray_Any(PyArrayObject* self, int axis, PyArrayObject* out) - - Equivalent to :meth:`ndarray.any` (*self*, *axis*). Return an array with - True elements for every 1-d sub-array of *self* defined by *axis* - in which any of the elements are True. - -Functions ---------- - - -Array Functions -^^^^^^^^^^^^^^^ - -.. cfunction:: int PyArray_AsCArray(PyObject** op, void* ptr, npy_intp* dims, int nd, int typenum, int itemsize) - - Sometimes it is useful to access a multidimensional array as a - C-style multi-dimensional array so that algorithms can be - implemented using C's a[i][j][k] syntax. This routine returns a - pointer, *ptr*, that simulates this kind of C-style array, for - 1-, 2-, and 3-d ndarrays. - - :param op: - - The address to any Python object. This Python object will be replaced - with an equivalent well-behaved, C-style contiguous, ndarray of the - given data type specifice by the last two arguments. Be sure that - stealing a reference in this way to the input object is justified. - - :param ptr: - - The address to a (ctype* for 1-d, ctype** for 2-d or ctype*** for 3-d) - variable where ctype is the equivalent C-type for the data type. On - return, *ptr* will be addressable as a 1-d, 2-d, or 3-d array. - - :param dims: - - An output array that contains the shape of the array object. This - array gives boundaries on any looping that will take place. - - :param nd: - - The dimensionality of the array (1, 2, or 3). - - :param typenum: - - The expected data type of the array. - - :param itemsize: - - This argument is only needed when *typenum* represents a - flexible array. Otherwise it should be 0. - -.. note:: - - The simulation of a C-style array is not complete for 2-d and 3-d - arrays. For example, the simulated arrays of pointers cannot be passed - to subroutines expecting specific, statically-defined 2-d and 3-d - arrays. To pass to functions requiring those kind of inputs, you must - statically define the required array and copy data. - -.. cfunction:: int PyArray_Free(PyObject* op, void* ptr) - - Must be called with the same objects and memory locations returned - from :cfunc:`PyArray_AsCArray` (...). This function cleans up memory - that otherwise would get leaked. - -.. cfunction:: PyObject* PyArray_Concatenate(PyObject* obj, int axis) - - Join the sequence of objects in *obj* together along *axis* into a - single array. If the dimensions or types are not compatible an - error is raised. - -.. cfunction:: PyObject* PyArray_InnerProduct(PyObject* obj1, PyObject* obj2) - - Compute a product-sum over the last dimensions of *obj1* and - *obj2*. Neither array is conjugated. - -.. cfunction:: PyObject* PyArray_MatrixProduct(PyObject* obj1, PyObject* obj) - - Compute a product-sum over the last dimension of *obj1* and the - second-to-last dimension of *obj2*. For 2-d arrays this is a - matrix-product. Neither array is conjugated. - -.. cfunction:: PyObject* PyArray_CopyAndTranspose(PyObject \* op) - - A specialized copy and transpose function that works only for 2-d - arrays. The returned array is a transposed copy of *op*. - -.. cfunction:: PyObject* PyArray_Correlate(PyObject* op1, PyObject* op2, int mode) - - Compute the 1-d correlation of the 1-d arrays *op1* and *op2* - . The correlation is computed at each output point by multiplying - *op1* by a shifted version of *op2* and summing the result. As a - result of the shift, needed values outside of the defined range of - *op1* and *op2* are interpreted as zero. The mode determines how - many shifts to return: 0 - return only shifts that did not need to - assume zero- values; 1 - return an object that is the same size as - *op1*, 2 - return all possible shifts (any overlap at all is - accepted). - -.. cfunction:: PyObject* PyArray_Where(PyObject* condition, PyObject* x, PyObject* y) - - If both ``x`` and ``y`` are ``NULL``, then return - :cfunc:`PyArray_Nonzero` (*condition*). Otherwise, both *x* and *y* - must be given and the object returned is shaped like *condition* - and has elements of *x* and *y* where *condition* is respectively - True or False. - - -Other functions -^^^^^^^^^^^^^^^ - -.. cfunction:: Bool PyArray_CheckStrides(int elsize, int nd, npy_intp numbytes, npy_intp* dims, npy_intp* newstrides) - - Determine if *newstrides* is a strides array consistent with the - memory of an *nd* -dimensional array with shape ``dims`` and - element-size, *elsize*. The *newstrides* array is checked to see - if jumping by the provided number of bytes in each direction will - ever mean jumping more than *numbytes* which is the assumed size - of the available memory segment. If *numbytes* is 0, then an - equivalent *numbytes* is computed assuming *nd*, *dims*, and - *elsize* refer to a single-segment array. Return :cdata:`NPY_TRUE` if - *newstrides* is acceptable, otherwise return :cdata:`NPY_FALSE`. - -.. cfunction:: npy_intp PyArray_MultiplyList(npy_intp* seq, int n) - -.. cfunction:: int PyArray_MultiplyIntList(int* seq, int n) - - Both of these routines multiply an *n* -length array, *seq*, of - integers and return the result. No overflow checking is performed. - -.. cfunction:: int PyArray_CompareLists(npy_intp* l1, npy_intp* l2, int n) - - Given two *n* -length arrays of integers, *l1*, and *l2*, return - 1 if the lists are identical; otherwise, return 0. - - -Array Iterators ---------------- - -An array iterator is a simple way to access the elements of an -N-dimensional array quickly and efficiently. Section `2 -<#sec-array-iterator>`__ provides more description and examples of -this useful approach to looping over an array. - -.. cfunction:: PyObject* PyArray_IterNew(PyObject* arr) - - Return an array iterator object from the array, *arr*. This is - equivalent to *arr*. **flat**. The array iterator object makes - it easy to loop over an N-dimensional non-contiguous array in - C-style contiguous fashion. - -.. cfunction:: PyObject* PyArray_IterAllButAxis(PyObject* arr, int \*axis) - - Return an array iterator that will iterate over all axes but the - one provided in *\*axis*. The returned iterator cannot be used - with :cfunc:`PyArray_ITER_GOTO1D`. This iterator could be used to - write something similar to what ufuncs do wherein the loop over - the largest axis is done by a separate sub-routine. If *\*axis* is - negative then *\*axis* will be set to the axis having the smallest - stride and that axis will be used. - -.. cfunction:: PyObject *PyArray_BroadcastToShape(PyObject* arr, npy_intp *dimensions, int nd) - - Return an array iterator that is broadcast to iterate as an array - of the shape provided by *dimensions* and *nd*. - -.. cfunction:: int PyArrayIter_Check(PyObject* op) - - Evaluates true if *op* is an array iterator (or instance of a - subclass of the array iterator type). - -.. cfunction:: void PyArray_ITER_RESET(PyObject* iterator) - - Reset an *iterator* to the beginning of the array. - -.. cfunction:: void PyArray_ITER_NEXT(PyObject* iterator) - - Incremement the index and the dataptr members of the *iterator* to - point to the next element of the array. If the array is not - (C-style) contiguous, also increment the N-dimensional coordinates - array. - -.. cfunction:: void *PyArray_ITER_DATA(PyObject* iterator) - - A pointer to the current element of the array. - -.. cfunction:: void PyArray_ITER_GOTO(PyObject* iterator, npy_intp* destination) - - Set the *iterator* index, dataptr, and coordinates members to the - location in the array indicated by the N-dimensional c-array, - *destination*, which must have size at least *iterator* - ->nd_m1+1. - -.. cfunction:: PyArray_ITER_GOTO1D(PyObject* iterator, npy_intp index) - - Set the *iterator* index and dataptr to the location in the array - indicated by the integer *index* which points to an element in the - C-styled flattened array. - -.. cfunction:: int PyArray_ITER_NOTDONE(PyObject* iterator) - - Evaluates TRUE as long as the iterator has not looped through all of - the elements, otherwise it evaluates FALSE. - - -Broadcasting (multi-iterators) ------------------------------- - -.. cfunction:: PyObject* PyArray_MultiIterNew(int num, ...) - - A simplified interface to broadcasting. This function takes the - number of arrays to broadcast and then *num* extra ( :ctype:`PyObject *` - ) arguments. These arguments are converted to arrays and iterators - are created. :cfunc:`PyArray_Broadcast` is then called on the resulting - multi-iterator object. The resulting, broadcasted mult-iterator - object is then returned. A broadcasted operation can then be - performed using a single loop and using :cfunc:`PyArray_MultiIter_NEXT` - (..) - -.. cfunction:: void PyArray_MultiIter_RESET(PyObject* multi) - - Reset all the iterators to the beginning in a multi-iterator - object, *multi*. - -.. cfunction:: void PyArray_MultiIter_NEXT(PyObject* multi) - - Advance each iterator in a multi-iterator object, *multi*, to its - next (broadcasted) element. - -.. cfunction:: void *PyArray_MultiIter_DATA(PyObject* multi, int i) - - Return the data-pointer of the *i* :math:`^{\textrm{th}}` iterator - in a multi-iterator object. - -.. cfunction:: void PyArray_MultiIter_NEXTi(PyObject* multi, int i) - - Advance the pointer of only the *i* :math:`^{\textrm{th}}` iterator. - -.. cfunction:: void PyArray_MultiIter_GOTO(PyObject* multi, npy_intp* destination) - - Advance each iterator in a multi-iterator object, *multi*, to the - given :math:`N` -dimensional *destination* where :math:`N` is the - number of dimensions in the broadcasted array. - -.. cfunction:: void PyArray_MultiIter_GOTO1D(PyObject* multi, npy_intp index) - - Advance each iterator in a multi-iterator object, *multi*, to the - corresponding location of the *index* into the flattened - broadcasted array. - -.. cfunction:: int PyArray_MultiIter_NOTDONE(PyObject* multi) - - Evaluates TRUE as long as the multi-iterator has not looped - through all of the elements (of the broadcasted result), otherwise - it evaluates FALSE. - -.. cfunction:: int PyArray_Broadcast(PyArrayMultiIterObject* mit) - - This function encapsulates the broadcasting rules. The *mit* - container should already contain iterators for all the arrays that - need to be broadcast. On return, these iterators will be adjusted - so that iteration over each simultaneously will accomplish the - broadcasting. A negative number is returned if an error occurs. - -.. cfunction:: int PyArray_RemoveSmallest(PyArrayMultiIterObject* mit) - - This function takes a multi-iterator object that has been - previously "broadcasted," finds the dimension with the smallest - "sum of strides" in the broadcasted result and adapts all the - iterators so as not to iterate over that dimension (by effectively - making them of length-1 in that dimension). The corresponding - dimension is returned unless *mit* ->nd is 0, then -1 is - returned. This function is useful for constructing ufunc-like - routines that broadcast their inputs correctly and then call a - strided 1-d version of the routine as the inner-loop. This 1-d - version is usually optimized for speed and for this reason the - loop should be performed over the axis that won't require large - stride jumps. - - -Array Scalars -------------- - -.. cfunction:: PyObject* PyArray_Return(PyArrayObject* arr) - - This function checks to see if *arr* is a 0-dimensional array and, - if so, returns the appropriate array scalar. It should be used - whenever 0-dimensional arrays could be returned to Python. - -.. cfunction:: PyObject* PyArray_Scalar(void* data, PyArray_Descr* dtype, PyObject* itemsize) - - Return an array scalar object of the given enumerated *typenum* - and *itemsize* by **copying** from memory pointed to by *data* - . If *swap* is nonzero then this function will byteswap the data - if appropriate to the data-type because array scalars are always - in correct machine-byte order. - -.. cfunction:: PyObject* PyArray_ToScalar(void* data, PyArrayObject* arr) - - Return an array scalar object of the type and itemsize indicated - by the array object *arr* copied from the memory pointed to by - *data* and swapping if the data in *arr* is not in machine - byte-order. - -.. cfunction:: PyObject* PyArray_FromScalar(PyObject* scalar, PyArray_Descr* outcode) - - Return a 0-dimensional array of type determined by *outcode* from - *scalar* which should be an array-scalar object. If *outcode* is - NULL, then the type is determined from *scalar*. - -.. cfunction:: void PyArray_ScalarAsCtype(PyObject* scalar, void* ctypeptr) - - Return in *ctypeptr* a pointer to the actual value in an array - scalar. There is no error checking so *scalar* must be an - array-scalar object, and ctypeptr must have enough space to hold - the correct type. For flexible-sized types, a pointer to the data - is copied into the memory of *ctypeptr*, for all other types, the - actual data is copied into the address pointed to by *ctypeptr*. - -.. cfunction:: void PyArray_CastScalarToCtype(PyObject* scalar, void* ctypeptr, PyArray_Descr* outcode) - - Return the data (cast to the data type indicated by *outcode*) - from the array-scalar, *scalar*, into the memory pointed to by - *ctypeptr* (which must be large enough to handle the incoming - memory). - -.. cfunction:: PyObject* PyArray_TypeObjectFromType(int type) - - Returns a scalar type-object from a type-number, *type* - . Equivalent to :cfunc:`PyArray_DescrFromType` (*type*)->typeobj - except for reference counting and error-checking. Returns a new - reference to the typeobject on success or ``NULL`` on failure. - -.. cfunction:: NPY_SCALARKIND PyArray_ScalarKind(int typenum, PyArrayObject** arr) - - Return the kind of scalar represented by *typenum* and the array - in *\*arr* (if *arr* is not ``NULL`` ). The array is assumed to be - rank-0 and only used if *typenum* represents a signed integer. If - *arr* is not ``NULL`` and the first element is negative then - :cdata:`NPY_INTNEG_SCALAR` is returned, otherwise - :cdata:`NPY_INTPOS_SCALAR` is returned. The possible return values - are :cdata:`NPY_{kind}_SCALAR` where ``{kind}`` can be **INTPOS**, - **INTNEG**, **FLOAT**, **COMPLEX**, **BOOL**, or **OBJECT**. - :cdata:`NPY_NOSCALAR` is also an enumerated value - :ctype:`NPY_SCALARKIND` variables can take on. - -.. cfunction:: int PyArray_CanCoerceScalar(char thistype, char neededtype, NPY_SCALARKIND scalar) - - Implements the rules for scalar coercion. Scalars are only - silently coerced from thistype to neededtype if this function - returns nonzero. If scalar is :cdata:`NPY_NOSCALAR`, then this - function is equivalent to :cfunc:`PyArray_CanCastSafely`. The rule is - that scalars of the same KIND can be coerced into arrays of the - same KIND. This rule means that high-precision scalars will never - cause low-precision arrays of the same KIND to be upcast. - - -Data-type descriptors ---------------------- - - - -.. warning:: - - Data-type objects must be reference counted so be aware of the - action on the data-type reference of different C-API calls. The - standard rule is that when a data-type object is returned it is a - new reference. Functions that take :ctype:`PyArray_Descr *` objects and - return arrays steal references to the data-type their inputs - unless otherwise noted. Therefore, you must own a reference to any - data-type object used as input to such a function. - -.. cfunction:: int PyArrayDescr_Check(PyObject* obj) - - Evaluates as true if *obj* is a data-type object ( :ctype:`PyArray_Descr *` ). - -.. cfunction:: PyArray_Descr* PyArray_DescrNew(PyArray_Descr* obj) - - Return a new data-type object copied from *obj* (the fields - reference is just updated so that the new object points to the - same fields dictionary if any). - -.. cfunction:: PyArray_Descr* PyArray_DescrNewFromType(int typenum) - - Create a new data-type object from the built-in (or - user-registered) data-type indicated by *typenum*. All builtin - types should not have any of their fields changed. This creates a - new copy of the :ctype:`PyArray_Descr` structure so that you can fill - it in as appropriate. This function is especially needed for - flexible data-types which need to have a new elsize member in - order to be meaningful in array construction. - -.. cfunction:: PyArray_Descr* PyArray_DescrNewByteorder(PyArray_Descr* obj, char newendian) - - Create a new data-type object with the byteorder set according to - *newendian*. All referenced data-type objects (in subdescr and - fields members of the data-type object) are also changed - (recursively). If a byteorder of :cdata:`NPY_IGNORE` is encountered it - is left alone. If newendian is :cdata:`NPY_SWAP`, then all byte-orders - are swapped. Other valid newendian values are :cdata:`NPY_NATIVE`, - :cdata:`NPY_LITTLE`, and :cdata:`NPY_BIG` which all cause the returned - data-typed descriptor (and all it's - referenced data-type descriptors) to have the corresponding byte- - order. - -.. cfunction:: PyArray_Descr* PyArray_DescrFromObject(PyObject* op, PyArray_Descr* mintype) - - Determine an appropriate data-type object from the object *op* - (which should be a "nested" sequence object) and the minimum - data-type descriptor mintype (which can be ``NULL`` ). Similar in - behavior to array(*op*).dtype. Don't confuse this function with - :cfunc:`PyArray_DescrConverter`. This function essentially looks at - all the objects in the (nested) sequence and determines the - data-type from the elements it finds. - -.. cfunction:: PyArray_Descr* PyArray_DescrFromScalar(PyObject* scalar) - - Return a data-type object from an array-scalar object. No checking - is done to be sure that *scalar* is an array scalar. If no - suitable data-type can be determined, then a data-type of - :cdata:`NPY_OBJECT` is returned by default. - -.. cfunction:: PyArray_Descr* PyArray_DescrFromType(int typenum) - - Returns a data-type object corresponding to *typenum*. The - *typenum* can be one of the enumerated types, a character code for - one of the enumerated types, or a user-defined type. - -.. cfunction:: int PyArray_DescrConverter(PyObject* obj, PyArray_Descr** dtype) - - Convert any compatible Python object, *obj*, to a data-type object - in *dtype*. A large number of Python objects can be converted to - data-type objects. See :ref:`arrays.dtypes` for a complete - description. This version of the converter converts None objects - to a :cdata:`NPY_DEFAULT_TYPE` data-type object. This function can - be used with the "O&" character code in :cfunc:`PyArg_ParseTuple` - processing. - -.. cfunction:: int PyArray_DescrConverter2(PyObject* obj, PyArray_Descr** dtype) - - Convert any compatible Python object, *obj*, to a data-type - object in *dtype*. This version of the converter converts None - objects so that the returned data-type is ``NULL``. This function - can also be used with the "O&" character in PyArg_ParseTuple - processing. - -.. cfunction:: int Pyarray_DescrAlignConverter(PyObject* obj, PyArray_Descr** dtype) - - Like :cfunc:`PyArray_DescrConverter` except it aligns C-struct-like - objects on word-boundaries as the compiler would. - -.. cfunction:: int Pyarray_DescrAlignConverter2(PyObject* obj, PyArray_Descr** dtype) - - Like :cfunc:`PyArray_DescrConverter2` except it aligns C-struct-like - objects on word-boundaries as the compiler would. - -.. cfunction:: PyObject *PyArray_FieldNames(PyObject* dict) - - Take the fields dictionary, *dict*, such as the one attached to a - data-type object and construct an ordered-list of field names such - as is stored in the names field of the :ctype:`PyArray_Descr` object. - - -Conversion Utilities --------------------- - - -For use with :cfunc:`PyArg_ParseTuple` -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -All of these functions can be used in :cfunc:`PyArg_ParseTuple` (...) with -the "O&" format specifier to automatically convert any Python object -to the required C-object. All of these functions return -:cdata:`NPY_SUCCEED` if successful and :cdata:`NPY_FAIL` if not. The first -argument to all of these function is a Python object. The second -argument is the **address** of the C-type to convert the Python object -to. - - -.. warning:: - - Be sure to understand what steps you should take to manage the - memory when using these conversion functions. These functions can - require freeing memory, and/or altering the reference counts of - specific objects based on your use. - -.. cfunction:: int PyArray_Converter(PyObject* obj, PyObject** address) - - Convert any Python object to a :ctype:`PyArrayObject`. If - :cfunc:`PyArray_Check` (*obj*) is TRUE then its reference count is - incremented and a reference placed in *address*. If *obj* is not - an array, then convert it to an array using :cfunc:`PyArray_FromAny` - . No matter what is returned, you must DECREF the object returned - by this routine in *address* when you are done with it. - -.. cfunction:: int PyArray_OutputConverter(PyObject* obj, PyArrayObject** address) - - This is a default converter for output arrays given to - functions. If *obj* is :cdata:`Py_None` or ``NULL``, then *\*address* - will be ``NULL`` but the call will succeed. If :cfunc:`PyArray_Check` ( - *obj*) is TRUE then it is returned in *\*address* without - incrementing its reference count. - -.. cfunction:: int PyArray_IntpConverter(PyObject* obj, PyArray_Dims* seq) - - Convert any Python sequence, *obj*, smaller than :cdata:`NPY_MAXDIMS` - to a C-array of :ctype:`npy_intp`. The Python object could also be a - single number. The *seq* variable is a pointer to a structure with - members ptr and len. On successful return, *seq* ->ptr contains a - pointer to memory that must be freed to avoid a memory leak. The - restriction on memory size allows this converter to be - conveniently used for sequences intended to be interpreted as - array shapes. - -.. cfunction:: int PyArray_BufferConverter(PyObject* obj, PyArray_Chunk* buf) - - Convert any Python object, *obj*, with a (single-segment) buffer - interface to a variable with members that detail the object's use - of its chunk of memory. The *buf* variable is a pointer to a - structure with base, ptr, len, and flags members. The - :ctype:`PyArray_Chunk` structure is binary compatibile with the - Python's buffer object (through its len member on 32-bit platforms - and its ptr member on 64-bit platforms or in Python 2.5). On - return, the base member is set to *obj* (or its base if *obj* is - already a buffer object pointing to another object). If you need - to hold on to the memory be sure to INCREF the base member. The - chunk of memory is pointed to by *buf* ->ptr member and has length - *buf* ->len. The flags member of *buf* is :cdata:`NPY_BEHAVED_RO` with - the :cdata:`NPY_WRITEABLE` flag set if *obj* has a writeable buffer - interface. - -.. cfunction:: int PyArray_AxisConverter(PyObject \* obj, int* axis) - - Convert a Python object, *obj*, representing an axis argument to - the proper value for passing to the functions that take an integer - axis. Specifically, if *obj* is None, *axis* is set to - :cdata:`NPY_MAXDIMS` which is interpreted correctly by the C-API - functions that take axis arguments. - -.. cfunction:: int PyArray_BoolConverter(PyObject* obj, Bool* value) - - Convert any Python object, *obj*, to :cdata:`NPY_TRUE` or - :cdata:`NPY_FALSE`, and place the result in *value*. - -.. cfunction:: int PyArray_ByteorderConverter(PyObject* obj, char* endian) - - Convert Python strings into the corresponding byte-order - character: - '>', '<', 's', '=', or '\|'. - -.. cfunction:: int PyArray_SortkindConverter(PyObject* obj, NPY_SORTKIND* sort) - - Convert Python strings into one of :cdata:`NPY_QUICKSORT` (starts - with 'q' or 'Q') , :cdata:`NPY_HEAPSORT` (starts with 'h' or 'H'), - or :cdata:`NPY_MERGESORT` (starts with 'm' or 'M'). - -.. cfunction:: int PyArray_SearchsideConverter(PyObject* obj, NPY_SEARCHSIDE* side) - - Convert Python strings into one of :cdata:`NPY_SEARCHLEFT` (starts with 'l' - or 'L'), or :cdata:`NPY_SEARCHRIGHT` (starts with 'r' or 'R'). - -Other conversions -^^^^^^^^^^^^^^^^^ - -.. cfunction:: int PyArray_PyIntAsInt(PyObject* op) - - Convert all kinds of Python objects (including arrays and array - scalars) to a standard integer. On error, -1 is returned and an - exception set. You may find useful the macro: - - .. code-block:: c - - #define error_converting(x) (((x) == -1) && PyErr_Occurred() - -.. cfunction:: npy_intp PyArray_PyIntAsIntp(PyObject* op) - - Convert all kinds of Python objects (including arrays and array - scalars) to a (platform-pointer-sized) integer. On error, -1 is - returned and an exception set. - -.. cfunction:: int PyArray_IntpFromSequence(PyObject* seq, npy_intp* vals, int maxvals) - - Convert any Python sequence (or single Python number) passed in as - *seq* to (up to) *maxvals* pointer-sized integers and place them - in the *vals* array. The sequence can be smaller then *maxvals* as - the number of converted objects is returned. - -.. cfunction:: int PyArray_TypestrConvert(int itemsize, int gentype) - - Convert typestring characters (with *itemsize*) to basic - enumerated data types. The typestring character corresponding to - signed and unsigned integers, floating point numbers, and - complex-floating point numbers are recognized and converted. Other - values of gentype are returned. This function can be used to - convert, for example, the string'f4' to :cdata:`NPY_FLOAT32`. - - -Miscellaneous -------------- - - -Importing the API -^^^^^^^^^^^^^^^^^ - -In order to make use of the C-API from another extension module, the -``import_array`` () command must be used. If the extension module is -self-contained in a single .c file, then that is all that needs to be -done. If, however, the extension module involves multiple files where -the C-API is needed then some additional steps must be taken. - -.. cfunction:: void import_array(void) - - This function must be called in the initialization section of a - module that will make use of the C-API. It imports the module - where the function-pointer table is stored and points the correct - variable to it. - -.. cmacro:: PY_ARRAY_UNIQUE_SYMBOL - -.. cmacro:: NO_IMPORT_ARRAY - - Using these #defines you can use the C-API in multiple files for a - single extension module. In each file you must define - :cmacro:`PY_ARRAY_UNIQUE_SYMBOL` to some name that will hold the - C-API (*e.g.* myextension_ARRAY_API). This must be done **before** - including the numpy/arrayobject.h file. In the module - intialization routine you call ``import_array`` (). In addition, - in the files that do not have the module initialization - sub_routine define :cmacro:`NO_IMPORT_ARRAY` prior to including - numpy/arrayobject.h. - - Suppose I have two files coolmodule.c and coolhelper.c which need - to be compiled and linked into a single extension module. Suppose - coolmodule.c contains the required initcool module initialization - function (with the import_array() function called). Then, - coolmodule.c would have at the top: - - .. code-block:: c - - #define PY_ARRAY_UNIQUE_SYMBOL cool_ARRAY_API - #include numpy/arrayobject.h - - On the other hand, coolhelper.c would contain at the top: - - .. code-block:: c - - #define PY_ARRAY_UNIQUE_SYMBOL cool_ARRAY_API - #define NO_IMPORT_ARRAY - #include numpy/arrayobject.h - -.. cfunction:: unsigned int PyArray_GetNDArrayCVersion(void) - - This just returns the value :cdata:`NPY_VERSION`. Because it is in the - C-API, however, comparing the output of this function from the - value defined in the current header gives a way to test if the - C-API has changed thus requiring a re-compilation of extension - modules that use the C-API. - - -Internal Flexibility -^^^^^^^^^^^^^^^^^^^^ - -.. cfunction:: int PyArray_SetNumericOps(PyObject* dict) - - NumPy stores an internal table of Python callable objects that are - used to implement arithmetic operations for arrays as well as - certain array calculation methods. This function allows the user - to replace any or all of these Python objects with their own - versions. The keys of the dictionary, *dict*, are the named - functions to replace and the paired value is the Python callable - object to use. Care should be taken that the function used to - replace an internal array operation does not itself call back to - that internal array operation (unless you have designed the - function to handle that), or an unchecked infinite recursion can - result (possibly causing program crash). The key names that - represent operations that can be replaced are: - - **add**, **subtract**, **multiply**, **divide**, - **remainder**, **power**, **square**, **reciprocal**, - **ones_like**, **sqrt**, **negative**, **absolute**, - **invert**, **left_shift**, **right_shift**, - **bitwise_and**, **bitwise_xor**, **bitwise_or**, - **less**, **less_equal**, **equal**, **not_equal**, - **greater**, **greater_equal**, **floor_divide**, - **true_divide**, **logical_or**, **logical_and**, - **floor**, **ceil**, **maximum**, **minimum**, **rint**. - - - These functions are included here because they are used at least once - in the array object's methods. The function returns -1 (without - setting a Python Error) if one of the objects being assigned is not - callable. - -.. cfunction:: PyObject* PyArray_GetNumericOps(void) - - Return a Python dictionary containing the callable Python objects - stored in the the internal arithmetic operation table. The keys of - this dictionary are given in the explanation for :cfunc:`PyArray_SetNumericOps`. - -.. cfunction:: void PyArray_SetStringFunction(PyObject* op, int repr) - - This function allows you to alter the tp_str and tp_repr methods - of the array object to any Python function. Thus you can alter - what happens for all arrays when str(arr) or repr(arr) is called - from Python. The function to be called is passed in as *op*. If - *repr* is non-zero, then this function will be called in response - to repr(arr), otherwise the function will be called in response to - str(arr). No check on whether or not *op* is callable is - performed. The callable passed in to *op* should expect an array - argument and should return a string to be printed. - - -Memory management -^^^^^^^^^^^^^^^^^ - -.. cfunction:: char* PyDataMem_NEW(size_t nbytes) - -.. cfunction:: PyDataMem_FREE(char* ptr) - -.. cfunction:: char* PyDataMem_RENEW(void * ptr, size_t newbytes) - - Macros to allocate, free, and reallocate memory. These macros are used - internally to create arrays. - -.. cfunction:: npy_intp* PyDimMem_NEW(nd) - -.. cfunction:: PyDimMem_FREE(npy_intp* ptr) - -.. cfunction:: npy_intp* PyDimMem_RENEW(npy_intp* ptr, npy_intp newnd) - - Macros to allocate, free, and reallocate dimension and strides memory. - -.. cfunction:: PyArray_malloc(nbytes) - -.. cfunction:: PyArray_free(ptr) - -.. cfunction:: PyArray_realloc(ptr, nbytes) - - These macros use different memory allocators, depending on the - constant :cdata:`NPY_USE_PYMEM`. The system malloc is used when - :cdata:`NPY_USE_PYMEM` is 0, if :cdata:`NPY_USE_PYMEM` is 1, then - the Python memory allocator is used. - - -Threading support -^^^^^^^^^^^^^^^^^ - -These macros are only meaningful if :cdata:`NPY_ALLOW_THREADS` -evaluates True during compilation of the extension module. Otherwise, -these macros are equivalent to whitespace. Python uses a single Global -Interpreter Lock (GIL) for each Python process so that only a single -thread may excecute at a time (even on multi-cpu machines). When -calling out to a compiled function that may take time to compute (and -does not have side-effects for other threads like updated global -variables), the GIL should be released so that other Python threads -can run while the time-consuming calculations are performed. This can -be accomplished using two groups of macros. Typically, if one macro in -a group is used in a code block, all of them must be used in the same -code block. Currently, :cdata:`NPY_ALLOW_THREADS` is defined to the -python-defined :cdata:`WITH_THREADS` constant unless the environment -variable :cdata:`NPY_NOSMP` is set in which case -:cdata:`NPY_ALLOW_THREADS` is defined to be 0. - -Group 1 -""""""" - - This group is used to call code that may take some time but does not - use any Python C-API calls. Thus, the GIL should be released during - its calculation. - - .. cmacro:: NPY_BEGIN_ALLOW_THREADS - - Equivalent to :cmacro:`Py_BEGIN_ALLOW_THREADS` except it uses - :cdata:`NPY_ALLOW_THREADS` to determine if the macro if - replaced with white-space or not. - - .. cmacro:: NPY_END_ALLOW_THREADS - - Equivalent to :cmacro:`Py_END_ALLOW_THREADS` except it uses - :cdata:`NPY_ALLOW_THREADS` to determine if the macro if - replaced with white-space or not. - - .. cmacro:: NPY_BEGIN_THREADS_DEF - - Place in the variable declaration area. This macro sets up the - variable needed for storing the Python state. - - .. cmacro:: NPY_BEGIN_THREADS - - Place right before code that does not need the Python - interpreter (no Python C-API calls). This macro saves the - Python state and releases the GIL. - - .. cmacro:: NPY_END_THREADS - - Place right after code that does not need the Python - interpreter. This macro acquires the GIL and restores the - Python state from the saved variable. - - .. cfunction:: NPY_BEGIN_THREADS_DESCR(PyArray_Descr *dtype) - - Useful to release the GIL only if *dtype* does not contain - arbitrary Python objects which may need the Python interpreter - during execution of the loop. Equivalent to - - .. cfunction:: NPY_END_THREADS_DESCR(PyArray_Descr *dtype) - - Useful to regain the GIL in situations where it was released - using the BEGIN form of this macro. - -Group 2 -""""""" - - This group is used to re-acquire the Python GIL after it has been - released. For example, suppose the GIL has been released (using the - previous calls), and then some path in the code (perhaps in a - different subroutine) requires use of the Python C-API, then these - macros are useful to acquire the GIL. These macros accomplish - essentially a reverse of the previous three (acquire the LOCK saving - what state it had) and then re-release it with the saved state. - - .. cmacro:: NPY_ALLOW_C_API_DEF - - Place in the variable declaration area to set up the necessary - variable. - - .. cmacro:: NPY_ALLOW_C_API - - Place before code that needs to call the Python C-API (when it is - known that the GIL has already been released). - - .. cmacro:: NPY_DISABLE_C_API - - Place after code that needs to call the Python C-API (to re-release - the GIL). - -.. tip:: - - Never use semicolons after the threading support macros. - - -Priority -^^^^^^^^ - -.. cvar:: NPY_PRIOIRTY - - Default priority for arrays. - -.. cvar:: NPY_SUBTYPE_PRIORITY - - Default subtype priority. - -.. cvar:: NPY_SCALAR_PRIORITY - - Default scalar priority (very small) - -.. cfunction:: double PyArray_GetPriority(PyObject* obj, double def) - - Return the :obj:`__array_priority__` attribute (converted to a - double) of *obj* or *def* if no attribute of that name - exists. Fast returns that avoid the attribute lookup are provided - for objects of type :cdata:`PyArray_Type`. - - -Default buffers -^^^^^^^^^^^^^^^ - -.. cvar:: NPY_BUFSIZE - - Default size of the user-settable internal buffers. - -.. cvar:: NPY_MIN_BUFSIZE - - Smallest size of user-settable internal buffers. - -.. cvar:: NPY_MAX_BUFSIZE - - Largest size allowed for the user-settable buffers. - - -Other constants -^^^^^^^^^^^^^^^ - -.. cvar:: NPY_NUM_FLOATTYPE - - The number of floating-point types - -.. cvar:: NPY_MAXDIMS - - The maximum number of dimensions allowed in arrays. - -.. cvar:: NPY_VERSION - - The current version of the ndarray object (check to see if this - variable is defined to guarantee the numpy/arrayobject.h header is - being used). - -.. cvar:: NPY_FALSE - - Defined as 0 for use with Bool. - -.. cvar:: NPY_TRUE - - Defined as 1 for use with Bool. - -.. cvar:: NPY_FAIL - - The return value of failed converter functions which are called using - the "O&" syntax in :cfunc:`PyArg_ParseTuple`-like functions. - -.. cvar:: NPY_SUCCEED - - The return value of successful converter functions which are called - using the "O&" syntax in :cfunc:`PyArg_ParseTuple`-like functions. - - -Miscellaneous Macros -^^^^^^^^^^^^^^^^^^^^ - -.. cfunction:: PyArray_SAMESHAPE(a1, a2) - - Evaluates as True if arrays *a1* and *a2* have the same shape. - -.. cfunction:: PyArray_MAX(a,b) - - Returns the maximum of *a* and *b*. If (*a*) or (*b*) are - expressions they are evaluated twice. - -.. cfunction:: PyArray_MIN(a,b) - - Returns the minimum of *a* and *b*. If (*a*) or (*b*) are - expressions they are evaluated twice. - -.. cfunction:: PyArray_CLT(a,b) - -.. cfunction:: PyArray_CGT(a,b) - -.. cfunction:: PyArray_CLE(a,b) - -.. cfunction:: PyArray_CGE(a,b) - -.. cfunction:: PyArray_CEQ(a,b) - -.. cfunction:: PyArray_CNE(a,b) - - Implements the complex comparisons between two complex numbers - (structures with a real and imag member) using NumPy's definition - of the ordering which is lexicographic: comparing the real parts - first and then the complex parts if the real parts are equal. - -.. cfunction:: PyArray_REFCOUNT(PyObject* op) - - Returns the reference count of any Python object. - -.. cfunction:: PyArray_XDECREF_ERR(PyObject \*obj) - - DECREF's an array object which may have the :cdata:`NPY_UPDATEIFCOPY` - flag set without causing the contents to be copied back into the - original array. Resets the :cdata:`NPY_WRITEABLE` flag on the base - object. This is useful for recovering from an error condition when - :cdata:`NPY_UPDATEIFCOPY` is used. - - -Enumerated Types -^^^^^^^^^^^^^^^^ - -.. ctype:: NPY_SORTKIND - - A special variable-type which can take on the values :cdata:`NPY_{KIND}` - where ``{KIND}`` is - - **QUICKSORT**, **HEAPSORT**, **MERGESORT** - - .. cvar:: NPY_NSORTS - - Defined to be the number of sorts. - -.. ctype:: NPY_SCALARKIND - - A special variable type indicating the number of "kinds" of - scalars distinguished in determining scalar-coercion rules. This - variable can take on the values :cdata:`NPY_{KIND}` where ``{KIND}`` can be - - **NOSCALAR**, **BOOL_SCALAR**, **INTPOS_SCALAR**, - **INTNEG_SCALAR**, **FLOAT_SCALAR**, **COMPLEX_SCALAR**, - **OBJECT_SCALAR** - - - .. cvar:: NPY_NSCALARKINDS - - Defined to be the number of scalar kinds - (not including :cdata:`NPY_NOSCALAR`). - -.. ctype:: NPY_ORDER - - A variable type indicating the order that an array should be - interpreted in. The value of a variable of this type can be - :cdata:`NPY_{ORDER}` where ``{ORDER}`` is - - **ANYORDER**, **CORDER**, **FORTRANORDER** - -.. ctype:: NPY_CLIPMODE - - A variable type indicating the kind of clipping that should be - applied in certain functions. The value of a variable of this type - can be :cdata:`NPY_{MODE}` where ``{MODE}`` is - - **CLIP**, **WRAP**, **RAISE** - -.. index:: - pair: ndarray; C-API |