383 lines
10 KiB
ReStructuredText
383 lines
10 KiB
ReStructuredText
ndarray
|
|
=======
|
|
|
|
.. contents :: Table of Contents
|
|
|
|
A `ndarray`_ is an N-dimensional array which contains items of the same type and size, where N is the number of dimensions and is specified in the form of a ``shape`` tuple. Optionally, the numpy ``dtype`` for the objects contained may also be specified.
|
|
|
|
.. _ndarray: http://docs.scipy.org/doc/numpy/reference/arrays.ndarray.html
|
|
.. _dtype: http://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html#data-type-objects-dtype
|
|
|
|
``<boost/python/numpy/ndarray.hpp>`` contains the structures and methods necessary to move raw data between C++ and Python and create ndarrays from the data
|
|
|
|
|
|
|
|
synopsis
|
|
--------
|
|
|
|
::
|
|
|
|
namespace boost
|
|
{
|
|
namespace python
|
|
{
|
|
namespace numpy
|
|
{
|
|
|
|
class ndarray : public object
|
|
{
|
|
|
|
public:
|
|
|
|
enum bitflag
|
|
{
|
|
NONE=0x0, C_CONTIGUOUS=0x1, F_CONTIGUOUS=0x2, V_CONTIGUOUS=0x1|0x2,
|
|
ALIGNED=0x4, WRITEABLE=0x8, BEHAVED=0x4|0x8,
|
|
CARRAY_RO=0x1|0x4, CARRAY=0x1|0x4|0x8, CARRAY_MIS=0x1|0x8,
|
|
FARRAY_RO=0x2|0x4, FARRAY=0x2|0x4|0x8, FARRAY_MIS=0x2|0x8,
|
|
UPDATE_ALL=0x1|0x2|0x4, VARRAY=0x1|0x2|0x8, ALL=0x1|0x2|0x4|0x8
|
|
};
|
|
|
|
ndarray view(dtype const & dt) const;
|
|
ndarray astype(dtype const & dt) const;
|
|
ndarray copy() const;
|
|
int const shape(int n) const;
|
|
int const strides(int n) const;
|
|
char * get_data() const;
|
|
dtype get_dtype() const;
|
|
python::object get_base() const;
|
|
void set_base(object const & base);
|
|
Py_intptr_t const * get_shape() const;
|
|
Py_intptr_t const * get_strides() const;
|
|
int const get_nd() const;
|
|
|
|
bitflag const get_flags() const;
|
|
|
|
ndarray transpose() const;
|
|
ndarray squeeze() const;
|
|
ndarray reshape(tuple const & shape) const;
|
|
object scalarize() const;
|
|
};
|
|
|
|
ndarray zeros(tuple const & shape, dtype const & dt);
|
|
ndarray zeros(int nd, Py_intptr_t const * shape, dtype const & dt);
|
|
|
|
ndarray empty(tuple const & shape, dtype const & dt);
|
|
ndarray empty(int nd, Py_intptr_t const * shape, dtype const & dt);
|
|
|
|
ndarray array(object const & obj);
|
|
ndarray array(object const & obj, dtype const & dt);
|
|
|
|
template <typename Container>
|
|
ndarray from_data(void * data,dtype const & dt,Container shape,Container strides,python::object const & owner);
|
|
template <typename Container>
|
|
ndarray from_data(void const * data, dtype const & dt, Container shape, Container strides, object const & owner);
|
|
|
|
ndarray from_object(object const & obj, dtype const & dt,int nd_min, int nd_max, ndarray::bitflag flags=ndarray::NONE);
|
|
ndarray from_object(object const & obj, dtype const & dt,int nd, ndarray::bitflag flags=ndarray::NONE);
|
|
ndarray from_object(object const & obj, dtype const & dt, ndarray::bitflag flags=ndarray::NONE);
|
|
ndarray from_object(object const & obj, int nd_min, int nd_max,ndarray::bitflag flags=ndarray::NONE);
|
|
ndarray from_object(object const & obj, int nd, ndarray::bitflag flags=ndarray::NONE);
|
|
ndarray from_object(object const & obj, ndarray::bitflag flags=ndarray::NONE)
|
|
|
|
ndarray::bitflag operator|(ndarray::bitflag a, ndarray::bitflag b) ;
|
|
ndarray::bitflag operator&(ndarray::bitflag a, ndarray::bitflag b);
|
|
|
|
}
|
|
|
|
|
|
constructors
|
|
------------
|
|
|
|
::
|
|
|
|
ndarray view(dtype const & dt) const;
|
|
|
|
:Returns: new ndarray with old ndarray data cast as supplied dtype
|
|
|
|
::
|
|
|
|
ndarray astype(dtype const & dt) const;
|
|
|
|
:Returns: new ndarray with old ndarray data converted to supplied dtype
|
|
|
|
::
|
|
|
|
ndarray copy() const;
|
|
|
|
:Returns: Copy of calling ndarray object
|
|
|
|
::
|
|
|
|
ndarray transpose() const;
|
|
|
|
:Returns: An ndarray with the rows and columns interchanged
|
|
|
|
::
|
|
|
|
ndarray squeeze() const;
|
|
|
|
:Returns: An ndarray with all unit-shaped dimensions removed
|
|
|
|
::
|
|
|
|
ndarray reshape(tuple const & shape) const;
|
|
|
|
:Requirements: The new ``shape`` of the ndarray must be supplied as a tuple
|
|
|
|
:Returns: An ndarray with the same data but reshaped to the ``shape`` supplied
|
|
|
|
|
|
::
|
|
|
|
object scalarize() const;
|
|
|
|
:Returns: A scalar if the ndarray has only one element, otherwise it returns the entire array
|
|
|
|
::
|
|
|
|
ndarray zeros(tuple const & shape, dtype const & dt);
|
|
ndarray zeros(int nd, Py_intptr_t const * shape, dtype const & dt);
|
|
|
|
:Requirements: The following parameters must be supplied as required :
|
|
|
|
* the ``shape`` or the size of all dimensions, as a tuple
|
|
* the ``dtype`` of the data
|
|
* the ``nd`` size for a square shaped ndarray
|
|
* the ``shape`` Py_intptr_t
|
|
|
|
:Returns: A new ndarray with the given shape and data type, with data initialized to zero.
|
|
|
|
::
|
|
|
|
ndarray empty(tuple const & shape, dtype const & dt);
|
|
ndarray empty(int nd, Py_intptr_t const * shape, dtype const & dt);
|
|
|
|
|
|
:Requirements: The following parameters must be supplied :
|
|
|
|
* the ``shape`` or the size of all dimensions, as a tuple
|
|
* the ``dtype`` of the data
|
|
* the ``shape`` Py_intptr_t
|
|
|
|
:Returns: A new ndarray with the given shape and data type, with data left uninitialized.
|
|
|
|
::
|
|
|
|
ndarray array(object const & obj);
|
|
ndarray array(object const & obj, dtype const & dt);
|
|
|
|
:Returns: A new ndarray from an arbitrary Python sequence, with dtype of each element specified optionally
|
|
|
|
::
|
|
|
|
template <typename Container>
|
|
inline ndarray from_data(void * data,dtype const & dt,Container shape,Container strides,python::object const & owner)
|
|
|
|
:Requirements: The following parameters must be supplied :
|
|
|
|
* the ``data`` which is a generic C++ data container
|
|
* the dtype ``dt`` of the data
|
|
* the ``shape`` of the ndarray as Python object
|
|
* the ``strides`` of each dimension of the array as a Python object
|
|
* the ``owner`` of the data, in case it is not the ndarray itself
|
|
|
|
:Returns: ndarray with attributes and data supplied
|
|
|
|
:Note: The ``Container`` typename must be one that is convertible to a std::vector or python object type
|
|
|
|
::
|
|
|
|
ndarray from_object(object const & obj, dtype const & dt,int nd_min, int nd_max, ndarray::bitflag flags=ndarray::NONE);
|
|
|
|
:Requirements: The following parameters must be supplied :
|
|
|
|
* the ``obj`` Python object to convert to ndarray
|
|
* the dtype ``dt`` of the data
|
|
* minimum number of dimensions ``nd_min`` of the ndarray as Python object
|
|
* maximum number of dimensions ``nd_max`` of the ndarray as Python object
|
|
* optional ``flags`` bitflags
|
|
|
|
:Returns: ndarray constructed with dimensions and data supplied as parameters
|
|
|
|
::
|
|
|
|
inline ndarray from_object(object const & obj, dtype const & dt, int nd, ndarray::bitflag flags=ndarray::NONE);
|
|
|
|
:Requirements: The following parameters must be supplied :
|
|
|
|
* the ``obj`` Python object to convert to ndarray
|
|
* the dtype ``dt`` of the data
|
|
* number of dimensions ``nd`` of the ndarray as Python object
|
|
* optional ``flags`` bitflags
|
|
|
|
:Returns: ndarray with dimensions ``nd`` x ``nd`` and suplied parameters
|
|
|
|
::
|
|
|
|
inline ndarray from_object(object const & obj, dtype const & dt, ndarray::bitflag flags=ndarray::NONE)
|
|
|
|
:Requirements: The following parameters must be supplied :
|
|
|
|
* the ``obj`` Python object to convert to ndarray
|
|
* the dtype ``dt`` of the data
|
|
* optional ``flags`` bitflags
|
|
|
|
:Returns: Supplied Python object as ndarray
|
|
|
|
::
|
|
|
|
ndarray from_object(object const & obj, int nd_min, int nd_max, ndarray::bitflag flags=ndarray::NONE);
|
|
|
|
:Requirements: The following parameters must be supplied :
|
|
|
|
* the ``obj`` Python object to convert to ndarray
|
|
* minimum number of dimensions ``nd_min`` of the ndarray as Python object
|
|
* maximum number of dimensions ``nd_max`` of the ndarray as Python object
|
|
* optional ``flags`` bitflags
|
|
|
|
:Returns: ndarray with supplied dimension limits and parameters
|
|
|
|
:Note: dtype need not be supplied here
|
|
|
|
::
|
|
|
|
inline ndarray from_object(object const & obj, int nd, ndarray::bitflag flags=ndarray::NONE);
|
|
|
|
:Requirements: The following parameters must be supplied :
|
|
|
|
* the ``obj`` Python object to convert to ndarray
|
|
* the dtype ``dt`` of the data
|
|
* number of dimensions ``nd`` of the ndarray as Python object
|
|
* optional ``flags`` bitflags
|
|
|
|
:Returns: ndarray of ``nd`` x ``nd`` dimensions constructed from the supplied object
|
|
|
|
::
|
|
|
|
inline ndarray from_object(object const & obj, ndarray::bitflag flags=ndarray::NONE)
|
|
|
|
:Requirements: The following parameters must be supplied :
|
|
|
|
* the ``obj`` Python object to convert to ndarray
|
|
* optional ``flags`` bitflags
|
|
|
|
:Returns: ndarray of same dimensions and dtype as supplied Python object
|
|
|
|
|
|
accessors
|
|
---------
|
|
|
|
::
|
|
|
|
int const shape(int n) const;
|
|
|
|
:Returns: The size of the n-th dimension of the ndarray
|
|
|
|
::
|
|
|
|
int const strides(int n) const;
|
|
|
|
:Returns: The stride of the nth dimension.
|
|
|
|
::
|
|
|
|
char * get_data() const;
|
|
|
|
:Returns: Array's raw data pointer as a char
|
|
|
|
:Note: This returns char so stride math works properly on it.User will have to reinterpret_cast it.
|
|
|
|
::
|
|
|
|
dtype get_dtype() const;
|
|
|
|
:Returns: Array's data-type descriptor object (dtype)
|
|
|
|
|
|
::
|
|
|
|
object get_base() const;
|
|
|
|
:Returns: Object that owns the array's data, or None if the array owns its own data.
|
|
|
|
|
|
::
|
|
|
|
void set_base(object const & base);
|
|
|
|
:Returns: Set the object that owns the array's data. Exercise caution while using this
|
|
|
|
|
|
::
|
|
|
|
Py_intptr_t const * get_shape() const;
|
|
|
|
:Returns: Shape of the array as an array of integers
|
|
|
|
|
|
::
|
|
|
|
Py_intptr_t const * get_strides() const;
|
|
|
|
:Returns: Stride of the array as an array of integers
|
|
|
|
|
|
::
|
|
|
|
int const get_nd() const;
|
|
|
|
:Returns: Number of array dimensions
|
|
|
|
|
|
::
|
|
|
|
bitflag const get_flags() const;
|
|
|
|
:Returns: Array flags
|
|
|
|
::
|
|
|
|
inline ndarray::bitflag operator|(ndarray::bitflag a, ndarray::bitflag b)
|
|
|
|
:Returns: bitflag logically OR-ed as (a | b)
|
|
|
|
::
|
|
|
|
inline ndarray::bitflag operator&(ndarray::bitflag a, ndarray::bitflag b)
|
|
|
|
:Returns: bitflag logically AND-ed as (a & b)
|
|
|
|
|
|
Example(s)
|
|
----------
|
|
|
|
::
|
|
|
|
namespace p = boost::python;
|
|
namespace np = boost::python::numpy;
|
|
|
|
p::object tu = p::make_tuple('a','b','c') ;
|
|
np::ndarray example_tuple = np::array (tu) ;
|
|
|
|
p::list l ;
|
|
np::ndarray example_list = np::array (l) ;
|
|
|
|
np::dtype dt = np::dtype::get_builtin<int>();
|
|
np::ndarray example_list1 = np::array (l,dt);
|
|
|
|
int data[] = {1,2,3,4} ;
|
|
p::tuple shape = p::make_tuple(4) ;
|
|
p::tuple stride = p::make_tuple(4) ;
|
|
p::object own ;
|
|
np::ndarray data_ex = np::from_data(data,dt,shape,stride,own);
|
|
|
|
uint8_t mul_data[][4] = {{1,2,3,4},{5,6,7,8},{1,3,5,7}};
|
|
shape = p::make_tuple(3,2) ;
|
|
stride = p::make_tuple(4,2) ;
|
|
np::dtype dt1 = np::dtype::get_builtin<uint8_t>();
|
|
|
|
np::ndarray mul_data_ex = np::from_data(mul_data,dt1, p::make_tuple(3,4),p::make_tuple(4,1),p::object());
|
|
mul_data_ex = np::from_data(mul_data,dt1, shape,stride,p::object());
|
|
|