ndarray
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.
<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 |
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ndarray copy() const;
Returns: | Copy of calling ndarray object |
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ndarray transpose() const;
Returns: | An ndarray with the rows and columns interchanged |
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ndarray squeeze() const;
Returns: | An ndarray with all unit-shaped dimensions removed |
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ndarray reshape(tuple const & shape) const;
Requirements: | The new shape of the ndarray must be supplied as a tuple |
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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 |
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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 :
|
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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 :
|
---|---|
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 :
|
---|---|
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 :
|
---|---|
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 :
|
---|---|
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 :
|
---|---|
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 :
|
---|---|
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 :
|
---|---|
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 :
|
---|---|
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. |
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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) |
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object get_base() const;
Returns: | Object that owns the array’s data, or None if the array owns its own data. |
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void set_base(object const & base);
Returns: | Set the object that owns the array’s data. Exercise caution while using this |
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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 |
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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());