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<a class="link" href="faq.html" title="Chapter 4. Frequently Asked Questions (FAQs)">Frequently Asked Questions (FAQs)</a>
|
||||
</li>
|
||||
<li class="listitem">
|
||||
<a href="numpy/index.html" target="_top">NumPy Extension Documentation</a>
|
||||
</li>
|
||||
</ul></div>
|
||||
</div>
|
||||
<h3>
|
||||
@@ -120,7 +123,7 @@
|
||||
</p>
|
||||
</div>
|
||||
<table xmlns:rev="http://www.cs.rpi.edu/~gregod/boost/tools/doc/revision" width="100%"><tr>
|
||||
<td align="left"><p><small>Last revised: August 08, 2016 at 15:54:37 GMT</small></p></td>
|
||||
<td align="left"><p><small>Last revised: November 02, 2016 at 18:29:38 GMT</small></p></td>
|
||||
<td align="right"><div class="copyright-footer"></div></td>
|
||||
</tr></table>
|
||||
<hr>
|
||||
|
||||
4
doc/html/numpy/.buildinfo
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4
doc/html/numpy/.buildinfo
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|
||||
# Sphinx build info version 1
|
||||
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
|
||||
config: c2f89bf9615bf36af14ecba75ba30ca4
|
||||
tags: 645f666f9bcd5a90fca523b33c5a78b7
|
||||
BIN
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14
doc/html/numpy/_sources/index.txt
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14
doc/html/numpy/_sources/index.txt
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@@ -0,0 +1,14 @@
|
||||
.. Boost.Python NumPy extension documentation master file, created by
|
||||
sphinx-quickstart on Thu Oct 27 09:04:58 2011.
|
||||
You can adapt this file completely to your liking, but it should at least
|
||||
contain the root `toctree` directive.
|
||||
|
||||
Welcome to the documentation of the Boost.Python NumPy extension!
|
||||
=================================================================
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
Tutorial <tutorial/index>
|
||||
Reference <reference/index>
|
||||
|
||||
110
doc/html/numpy/_sources/reference/binary_ufunc.txt
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110
doc/html/numpy/_sources/reference/binary_ufunc.txt
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@@ -0,0 +1,110 @@
|
||||
binary_ufunc
|
||||
============
|
||||
|
||||
.. contents :: Table of Contents
|
||||
|
||||
A ``binary_ufunc`` is a struct used as an intermediate step to broadcast two arguments so that a C++ function can be converted to a ufunc like function
|
||||
|
||||
``<boost/python/numpy/ufunc.hpp>`` contains the ``binary_ufunc`` structure definitions
|
||||
|
||||
|
||||
synopsis
|
||||
--------
|
||||
|
||||
::
|
||||
|
||||
namespace boost
|
||||
{
|
||||
namespace python
|
||||
{
|
||||
namespace numpy
|
||||
{
|
||||
|
||||
template <typename TBinaryFunctor,
|
||||
typename TArgument1=typename TBinaryFunctor::first_argument_type,
|
||||
typename TArgument2=typename TBinaryFunctor::second_argument_type,
|
||||
typename TResult=typename TBinaryFunctor::result_type>
|
||||
|
||||
struct binary_ufunc
|
||||
{
|
||||
|
||||
static object call(TBinaryFunctor & self,
|
||||
object const & input1,
|
||||
object const & input2,
|
||||
object const & output);
|
||||
|
||||
static object make();
|
||||
};
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
constructors
|
||||
------------
|
||||
|
||||
::
|
||||
|
||||
struct example_binary_ufunc
|
||||
{
|
||||
typedef any_valid first_argument_type;
|
||||
typedef any_valid second_argument_type;
|
||||
typedef any_valid result_type;
|
||||
};
|
||||
|
||||
:Requirements: The ``any_valid`` type must be defined using typedef as a valid C++ type in order to use the struct methods correctly
|
||||
|
||||
:Note: The struct must be exposed as a Python class, and an instance of the class must be created to use the ``call`` method corresponding to the ``__call__`` attribute of the Python object
|
||||
|
||||
accessors
|
||||
---------
|
||||
|
||||
::
|
||||
|
||||
template <typename TBinaryFunctor,
|
||||
typename TArgument1=typename TBinaryFunctor::first_argument_type,
|
||||
typename TArgument2=typename TBinaryFunctor::second_argument_type,
|
||||
typename TResult=typename TBinaryFunctor::result_type>
|
||||
static object call(TBinaryFunctor & self,
|
||||
object const & input,
|
||||
object const & output);
|
||||
|
||||
:Requires: Typenames ``TBinaryFunctor`` and optionally ``TArgument1`` and ``TArgument2`` for argument type and ``TResult`` for result type
|
||||
|
||||
:Effects: Passes a Python object to the underlying C++ functor after broadcasting its arguments
|
||||
|
||||
::
|
||||
|
||||
template <typename TBinaryFunctor,
|
||||
typename TArgument1=typename TBinaryFunctor::first_argument_type,
|
||||
typename TArgument2=typename TBinaryFunctor::second_argument_type,
|
||||
typename TResult=typename TBinaryFunctor::result_type>
|
||||
static object make();
|
||||
|
||||
:Requires: Typenames ``TBinaryFunctor`` and optionally ``TArgument1`` and ``TArgument2`` for argument type and ``TResult`` for result type
|
||||
|
||||
:Returns: A Python function object to call the overloaded () operator in the struct (in typical usage)
|
||||
|
||||
Example(s)
|
||||
----------
|
||||
|
||||
::
|
||||
|
||||
namespace p = boost::python;
|
||||
namespace np = boost::python::numpy;
|
||||
|
||||
struct BinarySquare
|
||||
{
|
||||
typedef double first_argument_type;
|
||||
typedef double second_argument_type;
|
||||
typedef double result_type;
|
||||
|
||||
double operator()(double a,double b) const { return (a*a + b*b) ; }
|
||||
};
|
||||
|
||||
p::object ud = p::class_<BinarySquare, boost::shared_ptr<BinarySquare> >("BinarySquare").def("__call__", np::binary_ufunc<BinarySquare>::make());
|
||||
p::object inst = ud();
|
||||
result_array = inst.attr("__call__")(demo_array,demo_array) ;
|
||||
std::cout << "Square of list with binary ufunc is " << p::extract <char const * > (p::str(result_array)) << std::endl ;
|
||||
|
||||
92
doc/html/numpy/_sources/reference/dtype.txt
Normal file
92
doc/html/numpy/_sources/reference/dtype.txt
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@@ -0,0 +1,92 @@
|
||||
dtype
|
||||
=====
|
||||
|
||||
.. contents :: Table of Contents
|
||||
|
||||
A `dtype`_ is an object describing the type of the elements of an ndarray
|
||||
|
||||
.. _dtype: http://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html#data-type-objects-dtype
|
||||
|
||||
``<boost/python/numpy/dtype.hpp>`` contains the method calls necessary to generate a python object equivalent to a numpy.dtype from builtin C++ objects, as well as to create custom dtypes from user defined types
|
||||
|
||||
|
||||
synopsis
|
||||
--------
|
||||
|
||||
::
|
||||
|
||||
namespace boost
|
||||
{
|
||||
namespace python
|
||||
{
|
||||
namespace numpy
|
||||
{
|
||||
|
||||
class dtype : public object
|
||||
{
|
||||
static python::detail::new_reference convert(object::object_cref arg, bool align);
|
||||
public:
|
||||
|
||||
// Convert an arbitrary Python object to a data-type descriptor object.
|
||||
template <typename T>
|
||||
explicit dtype(T arg, bool align=false);
|
||||
|
||||
// Get the built-in numpy dtype associated with the given scalar template type.
|
||||
template <typename T> static dtype get_builtin();
|
||||
|
||||
// Return the size of the data type in bytes.
|
||||
int get_itemsize() const;
|
||||
};
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
constructors
|
||||
------------
|
||||
|
||||
::
|
||||
|
||||
template <typename T>
|
||||
explicit dtype(T arg, bool align=false)
|
||||
|
||||
:Requirements: ``T`` must be either :
|
||||
|
||||
* a built-in C++ typename convertible to object
|
||||
* a valid python object or convertible to object
|
||||
|
||||
:Effects: Constructs an object from the supplied python object / convertible
|
||||
to object / builtin C++ data type
|
||||
|
||||
:Throws: Nothing
|
||||
|
||||
::
|
||||
|
||||
template <typename T> static dtype get_builtin();
|
||||
|
||||
:Requirements: The typename supplied, ``T`` must be a builtin C++ type also supported by numpy
|
||||
|
||||
:Returns: Numpy dtype corresponding to builtin C++ type
|
||||
|
||||
accessors
|
||||
---------
|
||||
|
||||
::
|
||||
|
||||
int get_itemsize() const;
|
||||
|
||||
:Returns: the size of the data type in bytes.
|
||||
|
||||
|
||||
Example(s)
|
||||
----------
|
||||
|
||||
::
|
||||
|
||||
namespace p = boost::python;
|
||||
namespace np = boost::python::numpy;
|
||||
|
||||
np::dtype dtype = np::dtype::get_builtin<double>();
|
||||
p::tuple for_custom_dtype = p::make_tuple("ha",dtype);
|
||||
np::dtype custom_dtype = np::dtype(list_for_dtype);
|
||||
|
||||
12
doc/html/numpy/_sources/reference/index.txt
Normal file
12
doc/html/numpy/_sources/reference/index.txt
Normal file
@@ -0,0 +1,12 @@
|
||||
Boost.Python NumPy extension Reference
|
||||
======================================
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
dtype
|
||||
ndarray
|
||||
unary_ufunc
|
||||
binary_ufunc
|
||||
multi_iter
|
||||
|
||||
94
doc/html/numpy/_sources/reference/multi_iter.txt
Normal file
94
doc/html/numpy/_sources/reference/multi_iter.txt
Normal file
@@ -0,0 +1,94 @@
|
||||
multi_iter
|
||||
==========
|
||||
|
||||
.. contents :: Table of Contents
|
||||
|
||||
A ``multi_iter`` is a Python object, intended to be used as an iterator It should generally only be used in loops.
|
||||
|
||||
``<boost/python/numpy/ufunc.hpp>`` contains the class definitions for ``multi_iter``
|
||||
|
||||
|
||||
synopsis
|
||||
--------
|
||||
|
||||
::
|
||||
|
||||
namespace boost
|
||||
{
|
||||
namespace python
|
||||
{
|
||||
namespace numpy
|
||||
{
|
||||
|
||||
class multi_iter : public object
|
||||
{
|
||||
public:
|
||||
void next();
|
||||
bool not_done() const;
|
||||
char * get_data(int n) const;
|
||||
int const get_nd() const;
|
||||
Py_intptr_t const * get_shape() const;
|
||||
Py_intptr_t const shape(int n) const;
|
||||
};
|
||||
|
||||
|
||||
multi_iter make_multi_iter(object const & a1);
|
||||
multi_iter make_multi_iter(object const & a1, object const & a2);
|
||||
multi_iter make_multi_iter(object const & a1, object const & a2, object const & a3);
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
constructors
|
||||
------------
|
||||
|
||||
::
|
||||
|
||||
multi_iter make_multi_iter(object const & a1);
|
||||
multi_iter make_multi_iter(object const & a1, object const & a2);
|
||||
multi_iter make_multi_iter(object const & a1, object const & a2, object const & a3);
|
||||
|
||||
:Returns: A Python iterator object broadcasting over one, two or three sequences as supplied
|
||||
|
||||
accessors
|
||||
---------
|
||||
|
||||
::
|
||||
|
||||
void next();
|
||||
|
||||
:Effects: Increments the iterator
|
||||
|
||||
::
|
||||
|
||||
bool not_done() const;
|
||||
|
||||
:Returns: boolean value indicating whether the iterator is at its end
|
||||
|
||||
::
|
||||
|
||||
char * get_data(int n) const;
|
||||
|
||||
:Returns: a pointer to the element of the nth broadcasted array.
|
||||
|
||||
::
|
||||
|
||||
int const get_nd() const;
|
||||
|
||||
:Returns: the number of dimensions of the broadcasted array expression
|
||||
|
||||
::
|
||||
|
||||
Py_intptr_t const * get_shape() const;
|
||||
|
||||
:Returns: the shape of the broadcasted array expression as an array of integers.
|
||||
|
||||
::
|
||||
|
||||
Py_intptr_t const shape(int n) const;
|
||||
|
||||
:Returns: the shape of the broadcasted array expression in the nth dimension.
|
||||
|
||||
|
||||
382
doc/html/numpy/_sources/reference/ndarray.txt
Normal file
382
doc/html/numpy/_sources/reference/ndarray.txt
Normal file
@@ -0,0 +1,382 @@
|
||||
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());
|
||||
|
||||
103
doc/html/numpy/_sources/reference/unary_ufunc.txt
Normal file
103
doc/html/numpy/_sources/reference/unary_ufunc.txt
Normal file
@@ -0,0 +1,103 @@
|
||||
unary_ufunc
|
||||
===========
|
||||
|
||||
.. contents :: Table of Contents
|
||||
|
||||
A ``unary_ufunc`` is a struct used as an intermediate step to broadcast a single argument so that a C++ function can be converted to a ufunc like function
|
||||
|
||||
``<boost/python/numpy/ufunc.hpp>`` contains the ``unary_ufunc`` structure definitions
|
||||
|
||||
|
||||
synopsis
|
||||
--------
|
||||
|
||||
::
|
||||
|
||||
namespace boost
|
||||
{
|
||||
namespace python
|
||||
{
|
||||
namespace numpy
|
||||
{
|
||||
|
||||
template <typename TUnaryFunctor,
|
||||
typename TArgument=typename TUnaryFunctor::argument_type,
|
||||
typename TResult=typename TUnaryFunctor::result_type>
|
||||
struct unary_ufunc
|
||||
{
|
||||
|
||||
static object call(TUnaryFunctor & self,
|
||||
object const & input,
|
||||
object const & output) ;
|
||||
|
||||
static object make();
|
||||
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
constructors
|
||||
------------
|
||||
|
||||
::
|
||||
|
||||
struct example_unary_ufunc
|
||||
{
|
||||
typedef any_valid_type argument_type;
|
||||
typedef any_valid_type result_type;
|
||||
};
|
||||
|
||||
:Requirements: The ``any_valid`` type must be defined using typedef as a valid C++ type in order to use the struct methods correctly
|
||||
|
||||
:Note: The struct must be exposed as a Python class, and an instance of the class must be created to use the ``call`` method corresponding to the ``__call__`` attribute of the Python object
|
||||
|
||||
accessors
|
||||
---------
|
||||
|
||||
::
|
||||
|
||||
template <typename TUnaryFunctor,
|
||||
typename TArgument=typename TUnaryFunctor::argument_type,
|
||||
typename TResult=typename TUnaryFunctor::result_type>
|
||||
static object call(TUnaryFunctor & self,
|
||||
object const & input,
|
||||
object const & output);
|
||||
|
||||
:Requires: Typenames ``TUnaryFunctor`` and optionally ``TArgument`` for argument type and ``TResult`` for result type
|
||||
|
||||
:Effects: Passes a Python object to the underlying C++ functor after broadcasting its arguments
|
||||
|
||||
::
|
||||
|
||||
template <typename TUnaryFunctor,
|
||||
typename TArgument=typename TUnaryFunctor::argument_type,
|
||||
typename TResult=typename TUnaryFunctor::result_type>
|
||||
static object make();
|
||||
|
||||
:Requires: Typenames ``TUnaryFunctor`` and optionally ``TArgument`` for argument type and ``TResult`` for result type
|
||||
|
||||
:Returns: A Python function object to call the overloaded () operator in the struct (in typical usage)
|
||||
|
||||
|
||||
|
||||
Example(s)
|
||||
----------
|
||||
|
||||
::
|
||||
|
||||
namespace p = boost::python;
|
||||
namespace np = boost::python::numpy;
|
||||
|
||||
struct UnarySquare
|
||||
{
|
||||
typedef double argument_type;
|
||||
typedef double result_type;
|
||||
double operator()(double r) const { return r * r;}
|
||||
};
|
||||
|
||||
p::object ud = p::class_<UnarySquare, boost::shared_ptr<UnarySquare> >("UnarySquare").def("__call__", np::unary_ufunc<UnarySquare>::make());
|
||||
p::object inst = ud();
|
||||
std::cout << "Square of unary scalar 1.0 is " << p::extract <char const * > (p::str(inst.attr("__call__")(1.0))) << std::endl ;
|
||||
|
||||
54
doc/html/numpy/_sources/tutorial/dtype.txt
Normal file
54
doc/html/numpy/_sources/tutorial/dtype.txt
Normal file
@@ -0,0 +1,54 @@
|
||||
How to use dtypes
|
||||
=================
|
||||
|
||||
Here is a brief tutorial to show how to create ndarrays with built-in python data types, and extract the types and values of member variables
|
||||
|
||||
Like before, first get the necessary headers, setup the namespaces and initialize the Python runtime and numpy module::
|
||||
|
||||
#include <boost/python/numpy.hpp>
|
||||
#include <iostream>
|
||||
|
||||
namespace p = boost::python;
|
||||
namespace np = boost::python::numpy;
|
||||
|
||||
int main(int argc, char **argv)
|
||||
{
|
||||
Py_Initialize();
|
||||
np::initialize();
|
||||
|
||||
Next, we create the shape and dtype. We use the get_builtin method to get the numpy dtype corresponding to the builtin C++ dtype
|
||||
Here, we will create a 3x3 array passing a tuple with (3,3) for the size, and double as the data type ::
|
||||
|
||||
p::tuple shape = p::make_tuple(3, 3);
|
||||
np::dtype dtype = np::dtype::get_builtin<double>();
|
||||
np::ndarray a = np::zeros(shape, dtype);
|
||||
|
||||
Finally, we can print the array using the extract method in the python namespace.
|
||||
Here, we first convert the variable into a string, and then extract it as a C++ character array from the python string using the <char const \* > template ::
|
||||
|
||||
std::cout << "Original array:\n" << p::extract<char const *>(p::str(a)) << std::endl;
|
||||
|
||||
We can also print the dtypes of the data members of the ndarray by using the get_dtype method for the ndarray ::
|
||||
|
||||
std::cout << "Datatype is:\n" << p::extract<char const *>(p::str(a.get_dtype())) << std::endl ;
|
||||
|
||||
We can also create custom dtypes and build ndarrays with the custom dtypes
|
||||
|
||||
We use the dtype constructor to create a custom dtype. This constructor takes a list as an argument.
|
||||
|
||||
The list should contain one or more tuples of the format (variable name, variable type)
|
||||
|
||||
So first create a tuple with a variable name and its dtype, double, to create a custom dtype ::
|
||||
|
||||
p::tuple for_custom_dtype = p::make_tuple("ha",dtype) ;
|
||||
|
||||
Next, create a list, and add this tuple to the list. Then use the list to create the custom dtype ::
|
||||
|
||||
p::list list_for_dtype ;
|
||||
list_for_dtype.append(for_custom_dtype) ;
|
||||
np::dtype custom_dtype = np::dtype(list_for_dtype) ;
|
||||
|
||||
We are now ready to create an ndarray with dimensions specified by \*shape\* and of custom dtpye ::
|
||||
|
||||
np::ndarray new_array = np::zeros(shape,custom_dtype);
|
||||
}
|
||||
56
doc/html/numpy/_sources/tutorial/fromdata.txt
Normal file
56
doc/html/numpy/_sources/tutorial/fromdata.txt
Normal file
@@ -0,0 +1,56 @@
|
||||
How to access data using raw pointers
|
||||
=====================================
|
||||
|
||||
One of the advantages of the ndarray wrapper is that the same data can be used in both Python and C++ and changes can be made to reflect at both ends.
|
||||
The from_data method makes this possible.
|
||||
|
||||
Like before, first get the necessary headers, setup the namespaces and initialize the Python runtime and numpy module::
|
||||
|
||||
#include <boost/python/numpy.hpp>
|
||||
#include <iostream>
|
||||
|
||||
namespace p = boost::python;
|
||||
namespace np = boost::python::numpy;
|
||||
|
||||
int main(int argc, char **argv)
|
||||
{
|
||||
Py_Initialize();
|
||||
np::initialize();
|
||||
|
||||
Create an array in C++ , and pass the pointer to it to the from_data method to create an ndarray::
|
||||
|
||||
int arr[] = {1,2,3,4,5};
|
||||
np::ndarray py_array = np::from_data(arr, np::dtype::get_builtin<int>(),
|
||||
p::make_tuple(5),
|
||||
p::make_tuple(sizeof(int)),
|
||||
p::object());
|
||||
|
||||
Print the source C++ array, as well as the ndarray, to check if they are the same::
|
||||
|
||||
std::cout << "C++ array :" << std::endl;
|
||||
for (int j=0;j<4;j++)
|
||||
{
|
||||
std::cout << arr[j] << ' ';
|
||||
}
|
||||
std::cout << std::endl
|
||||
<< "Python ndarray :" << p::extract<char const *>(p::str(py_array)) << std::endl;
|
||||
|
||||
Now, change an element in the Python ndarray, and check if the value changed correspondingly in the source C++ array::
|
||||
|
||||
py_array[1] = 5 ;
|
||||
std::cout << "Is the change reflected in the C++ array used to create the ndarray ? " << std::endl;
|
||||
for (int j = 0; j < 5; j++)
|
||||
{
|
||||
std::cout << arr[j] << ' ';
|
||||
}
|
||||
|
||||
Next, change an element of the source C++ array and see if it is reflected in the Python ndarray::
|
||||
|
||||
arr[2] = 8;
|
||||
std::cout << std::endl
|
||||
<< "Is the change reflected in the Python ndarray ?" << std::endl
|
||||
<< p::extract<char const *>(p::str(py_array)) << std::endl;
|
||||
}
|
||||
|
||||
As we can see, the changes are reflected across the ends. This happens because the from_data method passes the C++ array by reference to create the ndarray, and thus uses the same locations for storing data.
|
||||
|
||||
12
doc/html/numpy/_sources/tutorial/index.txt
Normal file
12
doc/html/numpy/_sources/tutorial/index.txt
Normal file
@@ -0,0 +1,12 @@
|
||||
Boost.Python NumPy extension Tutorial
|
||||
=====================================
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
|
||||
simple
|
||||
dtype
|
||||
ndarray
|
||||
ufunc
|
||||
fromdata
|
||||
|
||||
99
doc/html/numpy/_sources/tutorial/ndarray.txt
Normal file
99
doc/html/numpy/_sources/tutorial/ndarray.txt
Normal file
@@ -0,0 +1,99 @@
|
||||
Creating ndarrays
|
||||
=================
|
||||
|
||||
The Boost.Numpy library exposes quite a few methods to create ndarrays. ndarrays can be created in a variety of ways, include empty arrays and zero filled arrays.
|
||||
ndarrays can also be created from arbitrary python sequences as well as from data and dtypes.
|
||||
|
||||
This tutorial will introduce you to some of the ways in which you can create ndarrays. The methods covered here include creating ndarrays from arbitrary Python sequences, as well as from C++ containers, using both unit and non-unit strides
|
||||
|
||||
First, as before, initialise the necessary namepaces and runtimes ::
|
||||
|
||||
#include <boost/python/numpy.hpp>
|
||||
#include <iostream>
|
||||
|
||||
namespace p = boost::python;
|
||||
namespace np = boost::python::numpy;
|
||||
|
||||
int main(int argc, char **argv)
|
||||
{
|
||||
Py_Initialize();
|
||||
np::initialize();
|
||||
|
||||
Let's now create an ndarray from a simple tuple. We first create a tuple object, and then pass it to the array method, to generate the necessary tuple ::
|
||||
|
||||
p::object tu = p::make_tuple('a','b','c');
|
||||
np::ndarray example_tuple = np::array(tu);
|
||||
|
||||
Let's now try the same with a list. We create an empty list, add an element using the append method, and as before, call the array method ::
|
||||
|
||||
p::list l;
|
||||
l.append('a');
|
||||
np::ndarray example_list = np::array (l);
|
||||
|
||||
Optionally, we can also specify a dtype for the array ::
|
||||
|
||||
np::dtype dt = np::dtype::get_builtin<int>();
|
||||
np::ndarray example_list1 = np::array (l,dt);
|
||||
|
||||
We can also create an array by supplying data arrays and a few other parameters.
|
||||
|
||||
First,create an integer array ::
|
||||
|
||||
int data[] = {1,2,3,4,5};
|
||||
|
||||
Create a shape, and strides, needed by the function ::
|
||||
|
||||
p::tuple shape = p::make_tuple(5);
|
||||
p::tuple stride = p::make_tuple(sizeof(int));
|
||||
|
||||
Here, shape is (4,) , and the stride is `sizeof(int)``.
|
||||
A stride is the number of bytes that must be traveled to get to the next desired element while constructing the ndarray.
|
||||
|
||||
The function also needs an owner, to keep track of the data array passed. Passing none is dangerous ::
|
||||
|
||||
p::object own;
|
||||
|
||||
The from_data function takes the data array, datatype,shape,stride and owner as arguments and returns an ndarray ::
|
||||
|
||||
np::ndarray data_ex1 = np::from_data(data,dt, shape,stride,own);
|
||||
|
||||
Now let's print the ndarray we created ::
|
||||
|
||||
std::cout << "Single dimensional array ::" << std::endl
|
||||
<< p::extract<char const *>(p::str(data_ex)) << std::endl;
|
||||
|
||||
Let's make it a little more interesting. Lets make an 3x2 ndarray from a multi-dimensional array using non-unit strides
|
||||
|
||||
First lets create a 3x4 array of 8-bit integers ::
|
||||
|
||||
uint8_t mul_data[][4] = {{1,2,3,4},{5,6,7,8},{1,3,5,7}};
|
||||
|
||||
Now let's create an array of 3x2 elements, picking the first and third elements from each row . For that, the shape will be 3x2.
|
||||
The strides will be 4x2 i.e. 4 bytes to go to the next desired row, and 2 bytes to go to the next desired column ::
|
||||
|
||||
shape = p::make_tuple(3,2);
|
||||
stride = p::make_tuple(sizeof(uint8_t)*2,sizeof(uint8_t));
|
||||
|
||||
Get the numpy dtype for the built-in 8-bit integer data type ::
|
||||
|
||||
np::dtype dt1 = np::dtype::get_builtin<uint8_t>();
|
||||
|
||||
Now lets first create and print out the ndarray as is.
|
||||
Notice how we can pass the shape and strides in the function directly, as well as the owner. The last part can be done because we don't have any use to
|
||||
manipulate the "owner" object ::
|
||||
|
||||
np::ndarray mul_data_ex = np::from_data(mul_data, dt1,
|
||||
p::make_tuple(3,4),
|
||||
p::make_tuple(4,1),
|
||||
p::object());
|
||||
std::cout << "Original multi dimensional array :: " << std::endl
|
||||
<< p::extract<char const *>(p::str(mul_data_ex)) << std::endl;
|
||||
|
||||
Now create the new ndarray using the shape and strides and print out the array we created using non-unit strides ::
|
||||
|
||||
mul_data_ex = np::from_data(mul_data, dt1, shape, stride, p::object());
|
||||
std::cout << "Selective multidimensional array :: "<<std::endl
|
||||
<< p::extract<char const *>(p::str(mul_data_ex)) << std::endl ;
|
||||
}
|
||||
|
||||
.. note:: The from_data method will throw ``error_already_set`` if the number of elements dictated by the shape and the corresponding strides don't match.
|
||||
41
doc/html/numpy/_sources/tutorial/simple.txt
Normal file
41
doc/html/numpy/_sources/tutorial/simple.txt
Normal file
@@ -0,0 +1,41 @@
|
||||
A simple tutorial on Arrays
|
||||
===========================
|
||||
|
||||
Let's start with a simple tutorial to create and modify arrays.
|
||||
|
||||
Get the necessary headers for numpy components and set up necessary namespaces::
|
||||
|
||||
#include <boost/python/numpy.hpp>
|
||||
#include <iostream>
|
||||
|
||||
namespace p = boost::python;
|
||||
namespace np = boost::python::numpy;
|
||||
|
||||
Initialise the Python runtime, and the numpy module. Failure to call these results in segmentation errors::
|
||||
|
||||
int main(int argc, char **argv)
|
||||
{
|
||||
Py_Initialize();
|
||||
np::initialize();
|
||||
|
||||
|
||||
Zero filled n-dimensional arrays can be created using the shape and data-type of the array as a parameter. Here, the shape is 3x3 and the datatype is the built-in float type::
|
||||
|
||||
p::tuple shape = p::make_tuple(3, 3);
|
||||
np::dtype dtype = np::dtype::get_builtin<float>();
|
||||
np::ndarray a = np::zeros(shape, dtype);
|
||||
|
||||
You can also create an empty array like this ::
|
||||
|
||||
np::ndarray b = np::empty(shape,dtype);
|
||||
|
||||
Print the original and reshaped array. The array a which is a list is first converted to a string, and each value in the list is extracted using extract< >::
|
||||
|
||||
std::cout << "Original array:\n" << p::extract<char const *>(p::str(a)) << std::endl;
|
||||
|
||||
// Reshape the array into a 1D array
|
||||
a = a.reshape(p::make_tuple(9));
|
||||
// Print it again.
|
||||
std::cout << "Reshaped array:\n" << p::extract<char const *>(p::str(a)) << std::endl;
|
||||
}
|
||||
|
||||
120
doc/html/numpy/_sources/tutorial/ufunc.txt
Normal file
120
doc/html/numpy/_sources/tutorial/ufunc.txt
Normal file
@@ -0,0 +1,120 @@
|
||||
Ufuncs
|
||||
======
|
||||
|
||||
Ufuncs or universal functions operate on ndarrays element by element, and support array broadcasting, type casting, and other features.
|
||||
|
||||
Lets try and see how we can use the binary and unary ufunc methods
|
||||
|
||||
After the neccessary includes ::
|
||||
|
||||
#include <boost/python/numpy.hpp>
|
||||
#include <iostream>
|
||||
|
||||
namespace p = boost::python;
|
||||
namespace np = boost::python::numpy;
|
||||
|
||||
Now we create the structs necessary to implement the ufuncs. The typedefs *must* be made as the ufunc generators take these typedefs as inputs and return an error otherwise ::
|
||||
|
||||
struct UnarySquare
|
||||
{
|
||||
typedef double argument_type;
|
||||
typedef double result_type;
|
||||
|
||||
double operator()(double r) const { return r * r;}
|
||||
};
|
||||
|
||||
struct BinarySquare
|
||||
{
|
||||
typedef double first_argument_type;
|
||||
typedef double second_argument_type;
|
||||
typedef double result_type;
|
||||
|
||||
double operator()(double a,double b) const { return (a*a + b*b) ; }
|
||||
};
|
||||
|
||||
Initialise the Python runtime and the numpy module ::
|
||||
|
||||
int main(int argc, char **argv)
|
||||
{
|
||||
Py_Initialize();
|
||||
np::initialize();
|
||||
|
||||
Now expose the struct UnarySquare to Python as a class, and let ud be the class object. ::
|
||||
|
||||
p::object ud = p::class_<UnarySquare, boost::shared_ptr<UnarySquare> >("UnarySquare");
|
||||
ud.def("__call__", np::unary_ufunc<UnarySquare>::make());
|
||||
|
||||
Let inst be an instance of the class ud ::
|
||||
|
||||
p::object inst = ud();
|
||||
|
||||
Use the "__call__" method to call the overloaded () operator and print the value ::
|
||||
|
||||
std::cout << "Square of unary scalar 1.0 is " << p::extract<char const *>(p::str(inst.attr("__call__")(1.0))) << std::endl;
|
||||
|
||||
Create an array in C++ ::
|
||||
|
||||
int arr[] = {1,2,3,4} ;
|
||||
|
||||
|
||||
..and use it to create the ndarray in Python ::
|
||||
|
||||
np::ndarray demo_array = np::from_data(arr, np::dtype::get_builtin<int>(),
|
||||
p::make_tuple(4),
|
||||
p::make_tuple(4),
|
||||
p::object());
|
||||
|
||||
Print out the demo array ::
|
||||
|
||||
std::cout << "Demo array is " << p::extract<char const *>(p::str(demo_array)) << std::endl;
|
||||
|
||||
Call the "__call__" method to perform the operation and assign the value to result_array ::
|
||||
|
||||
p::object result_array = inst.attr("__call__")(demo_array);
|
||||
|
||||
Print the resultant array ::
|
||||
|
||||
std::cout << "Square of demo array is " << p::extract<char const *>(p::str(result_array)) << std::endl;
|
||||
|
||||
Lets try the same with a list ::
|
||||
|
||||
p::list li;
|
||||
li.append(3);
|
||||
li.append(7);
|
||||
|
||||
Print out the demo list ::
|
||||
|
||||
std::cout << "Demo list is " << p::extract<char const *>(p::str(li)) << std::endl;
|
||||
|
||||
Call the ufunc for the list ::
|
||||
|
||||
result_array = inst.attr("__call__")(li);
|
||||
|
||||
And print the list out ::
|
||||
|
||||
std::cout << "Square of demo list is " << p::extract<char const *>(p::str(result_array)) << std::endl;
|
||||
|
||||
Now lets try Binary ufuncs. Again, expose the struct BinarySquare to Python as a class, and let ud be the class object ::
|
||||
|
||||
ud = p::class_<BinarySquare, boost::shared_ptr<BinarySquare> >("BinarySquare");
|
||||
ud.def("__call__", np::binary_ufunc<BinarySquare>::make());
|
||||
|
||||
And initialise ud ::
|
||||
|
||||
inst = ud();
|
||||
|
||||
Print the two input lists ::
|
||||
|
||||
std::cout << "The two input list for binary ufunc are " << std::endl
|
||||
<< p::extract<char const *>(p::str(demo_array)) << std::endl
|
||||
<< p::extract<char const *>(p::str(demo_array)) << std::endl;
|
||||
|
||||
Call the binary ufunc taking demo_array as both inputs ::
|
||||
|
||||
result_array = inst.attr("__call__")(demo_array,demo_array);
|
||||
|
||||
And print the output ::
|
||||
|
||||
std::cout << "Square of list with binary ufunc is " << p::extract<char const *>(p::str(result_array)) << std::endl;
|
||||
}
|
||||
|
||||
BIN
doc/html/numpy/_static/ajax-loader.gif
Normal file
BIN
doc/html/numpy/_static/ajax-loader.gif
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 673 B |
537
doc/html/numpy/_static/basic.css
Normal file
537
doc/html/numpy/_static/basic.css
Normal file
@@ -0,0 +1,537 @@
|
||||
/*
|
||||
* basic.css
|
||||
* ~~~~~~~~~
|
||||
*
|
||||
* Sphinx stylesheet -- basic theme.
|
||||
*
|
||||
* :copyright: Copyright 2007-2014 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
/* -- main layout ----------------------------------------------------------- */
|
||||
|
||||
div.clearer {
|
||||
clear: both;
|
||||
}
|
||||
|
||||
/* -- relbar ---------------------------------------------------------------- */
|
||||
|
||||
div.related {
|
||||
width: 100%;
|
||||
font-size: 90%;
|
||||
}
|
||||
|
||||
div.related h3 {
|
||||
display: none;
|
||||
}
|
||||
|
||||
div.related ul {
|
||||
margin: 0;
|
||||
padding: 0 0 0 10px;
|
||||
list-style: none;
|
||||
}
|
||||
|
||||
div.related li {
|
||||
display: inline;
|
||||
}
|
||||
|
||||
div.related li.right {
|
||||
float: right;
|
||||
margin-right: 5px;
|
||||
}
|
||||
|
||||
/* -- sidebar --------------------------------------------------------------- */
|
||||
|
||||
div.sphinxsidebarwrapper {
|
||||
padding: 10px 5px 0 10px;
|
||||
}
|
||||
|
||||
div.sphinxsidebar {
|
||||
float: left;
|
||||
width: 230px;
|
||||
margin-left: -100%;
|
||||
font-size: 90%;
|
||||
}
|
||||
|
||||
div.sphinxsidebar ul {
|
||||
list-style: none;
|
||||
}
|
||||
|
||||
div.sphinxsidebar ul ul,
|
||||
div.sphinxsidebar ul.want-points {
|
||||
margin-left: 20px;
|
||||
list-style: square;
|
||||
}
|
||||
|
||||
div.sphinxsidebar ul ul {
|
||||
margin-top: 0;
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
div.sphinxsidebar form {
|
||||
margin-top: 10px;
|
||||
}
|
||||
|
||||
div.sphinxsidebar input {
|
||||
border: 1px solid #98dbcc;
|
||||
font-family: sans-serif;
|
||||
font-size: 1em;
|
||||
}
|
||||
|
||||
div.sphinxsidebar #searchbox input[type="text"] {
|
||||
width: 170px;
|
||||
}
|
||||
|
||||
div.sphinxsidebar #searchbox input[type="submit"] {
|
||||
width: 30px;
|
||||
}
|
||||
|
||||
img {
|
||||
border: 0;
|
||||
max-width: 100%;
|
||||
}
|
||||
|
||||
/* -- search page ----------------------------------------------------------- */
|
||||
|
||||
ul.search {
|
||||
margin: 10px 0 0 20px;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
ul.search li {
|
||||
padding: 5px 0 5px 20px;
|
||||
background-image: url(file.png);
|
||||
background-repeat: no-repeat;
|
||||
background-position: 0 7px;
|
||||
}
|
||||
|
||||
ul.search li a {
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
ul.search li div.context {
|
||||
color: #888;
|
||||
margin: 2px 0 0 30px;
|
||||
text-align: left;
|
||||
}
|
||||
|
||||
ul.keywordmatches li.goodmatch a {
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
/* -- index page ------------------------------------------------------------ */
|
||||
|
||||
table.contentstable {
|
||||
width: 90%;
|
||||
}
|
||||
|
||||
table.contentstable p.biglink {
|
||||
line-height: 150%;
|
||||
}
|
||||
|
||||
a.biglink {
|
||||
font-size: 1.3em;
|
||||
}
|
||||
|
||||
span.linkdescr {
|
||||
font-style: italic;
|
||||
padding-top: 5px;
|
||||
font-size: 90%;
|
||||
}
|
||||
|
||||
/* -- general index --------------------------------------------------------- */
|
||||
|
||||
table.indextable {
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
table.indextable td {
|
||||
text-align: left;
|
||||
vertical-align: top;
|
||||
}
|
||||
|
||||
table.indextable dl, table.indextable dd {
|
||||
margin-top: 0;
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
table.indextable tr.pcap {
|
||||
height: 10px;
|
||||
}
|
||||
|
||||
table.indextable tr.cap {
|
||||
margin-top: 10px;
|
||||
background-color: #f2f2f2;
|
||||
}
|
||||
|
||||
img.toggler {
|
||||
margin-right: 3px;
|
||||
margin-top: 3px;
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
div.modindex-jumpbox {
|
||||
border-top: 1px solid #ddd;
|
||||
border-bottom: 1px solid #ddd;
|
||||
margin: 1em 0 1em 0;
|
||||
padding: 0.4em;
|
||||
}
|
||||
|
||||
div.genindex-jumpbox {
|
||||
border-top: 1px solid #ddd;
|
||||
border-bottom: 1px solid #ddd;
|
||||
margin: 1em 0 1em 0;
|
||||
padding: 0.4em;
|
||||
}
|
||||
|
||||
/* -- general body styles --------------------------------------------------- */
|
||||
|
||||
a.headerlink {
|
||||
visibility: hidden;
|
||||
}
|
||||
|
||||
h1:hover > a.headerlink,
|
||||
h2:hover > a.headerlink,
|
||||
h3:hover > a.headerlink,
|
||||
h4:hover > a.headerlink,
|
||||
h5:hover > a.headerlink,
|
||||
h6:hover > a.headerlink,
|
||||
dt:hover > a.headerlink {
|
||||
visibility: visible;
|
||||
}
|
||||
|
||||
div.body p.caption {
|
||||
text-align: inherit;
|
||||
}
|
||||
|
||||
div.body td {
|
||||
text-align: left;
|
||||
}
|
||||
|
||||
.field-list ul {
|
||||
padding-left: 1em;
|
||||
}
|
||||
|
||||
.first {
|
||||
margin-top: 0 !important;
|
||||
}
|
||||
|
||||
p.rubric {
|
||||
margin-top: 30px;
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
img.align-left, .figure.align-left, object.align-left {
|
||||
clear: left;
|
||||
float: left;
|
||||
margin-right: 1em;
|
||||
}
|
||||
|
||||
img.align-right, .figure.align-right, object.align-right {
|
||||
clear: right;
|
||||
float: right;
|
||||
margin-left: 1em;
|
||||
}
|
||||
|
||||
img.align-center, .figure.align-center, object.align-center {
|
||||
display: block;
|
||||
margin-left: auto;
|
||||
margin-right: auto;
|
||||
}
|
||||
|
||||
.align-left {
|
||||
text-align: left;
|
||||
}
|
||||
|
||||
.align-center {
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
.align-right {
|
||||
text-align: right;
|
||||
}
|
||||
|
||||
/* -- sidebars -------------------------------------------------------------- */
|
||||
|
||||
div.sidebar {
|
||||
margin: 0 0 0.5em 1em;
|
||||
border: 1px solid #ddb;
|
||||
padding: 7px 7px 0 7px;
|
||||
background-color: #ffe;
|
||||
width: 40%;
|
||||
float: right;
|
||||
}
|
||||
|
||||
p.sidebar-title {
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
/* -- topics ---------------------------------------------------------------- */
|
||||
|
||||
div.topic {
|
||||
border: 1px solid #ccc;
|
||||
padding: 7px 7px 0 7px;
|
||||
margin: 10px 0 10px 0;
|
||||
}
|
||||
|
||||
p.topic-title {
|
||||
font-size: 1.1em;
|
||||
font-weight: bold;
|
||||
margin-top: 10px;
|
||||
}
|
||||
|
||||
/* -- admonitions ----------------------------------------------------------- */
|
||||
|
||||
div.admonition {
|
||||
margin-top: 10px;
|
||||
margin-bottom: 10px;
|
||||
padding: 7px;
|
||||
}
|
||||
|
||||
div.admonition dt {
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
div.admonition dl {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
p.admonition-title {
|
||||
margin: 0px 10px 5px 0px;
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
div.body p.centered {
|
||||
text-align: center;
|
||||
margin-top: 25px;
|
||||
}
|
||||
|
||||
/* -- tables ---------------------------------------------------------------- */
|
||||
|
||||
table.docutils {
|
||||
border: 0;
|
||||
border-collapse: collapse;
|
||||
}
|
||||
|
||||
table.docutils td, table.docutils th {
|
||||
padding: 1px 8px 1px 5px;
|
||||
border-top: 0;
|
||||
border-left: 0;
|
||||
border-right: 0;
|
||||
border-bottom: 1px solid #aaa;
|
||||
}
|
||||
|
||||
table.field-list td, table.field-list th {
|
||||
border: 0 !important;
|
||||
}
|
||||
|
||||
table.footnote td, table.footnote th {
|
||||
border: 0 !important;
|
||||
}
|
||||
|
||||
th {
|
||||
text-align: left;
|
||||
padding-right: 5px;
|
||||
}
|
||||
|
||||
table.citation {
|
||||
border-left: solid 1px gray;
|
||||
margin-left: 1px;
|
||||
}
|
||||
|
||||
table.citation td {
|
||||
border-bottom: none;
|
||||
}
|
||||
|
||||
/* -- other body styles ----------------------------------------------------- */
|
||||
|
||||
ol.arabic {
|
||||
list-style: decimal;
|
||||
}
|
||||
|
||||
ol.loweralpha {
|
||||
list-style: lower-alpha;
|
||||
}
|
||||
|
||||
ol.upperalpha {
|
||||
list-style: upper-alpha;
|
||||
}
|
||||
|
||||
ol.lowerroman {
|
||||
list-style: lower-roman;
|
||||
}
|
||||
|
||||
ol.upperroman {
|
||||
list-style: upper-roman;
|
||||
}
|
||||
|
||||
dl {
|
||||
margin-bottom: 15px;
|
||||
}
|
||||
|
||||
dd p {
|
||||
margin-top: 0px;
|
||||
}
|
||||
|
||||
dd ul, dd table {
|
||||
margin-bottom: 10px;
|
||||
}
|
||||
|
||||
dd {
|
||||
margin-top: 3px;
|
||||
margin-bottom: 10px;
|
||||
margin-left: 30px;
|
||||
}
|
||||
|
||||
dt:target, .highlighted {
|
||||
background-color: #fbe54e;
|
||||
}
|
||||
|
||||
dl.glossary dt {
|
||||
font-weight: bold;
|
||||
font-size: 1.1em;
|
||||
}
|
||||
|
||||
.field-list ul {
|
||||
margin: 0;
|
||||
padding-left: 1em;
|
||||
}
|
||||
|
||||
.field-list p {
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
.optional {
|
||||
font-size: 1.3em;
|
||||
}
|
||||
|
||||
.versionmodified {
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
.system-message {
|
||||
background-color: #fda;
|
||||
padding: 5px;
|
||||
border: 3px solid red;
|
||||
}
|
||||
|
||||
.footnote:target {
|
||||
background-color: #ffa;
|
||||
}
|
||||
|
||||
.line-block {
|
||||
display: block;
|
||||
margin-top: 1em;
|
||||
margin-bottom: 1em;
|
||||
}
|
||||
|
||||
.line-block .line-block {
|
||||
margin-top: 0;
|
||||
margin-bottom: 0;
|
||||
margin-left: 1.5em;
|
||||
}
|
||||
|
||||
.guilabel, .menuselection {
|
||||
font-family: sans-serif;
|
||||
}
|
||||
|
||||
.accelerator {
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
.classifier {
|
||||
font-style: oblique;
|
||||
}
|
||||
|
||||
abbr, acronym {
|
||||
border-bottom: dotted 1px;
|
||||
cursor: help;
|
||||
}
|
||||
|
||||
/* -- code displays --------------------------------------------------------- */
|
||||
|
||||
pre {
|
||||
overflow: auto;
|
||||
overflow-y: hidden; /* fixes display issues on Chrome browsers */
|
||||
}
|
||||
|
||||
td.linenos pre {
|
||||
padding: 5px 0px;
|
||||
border: 0;
|
||||
background-color: transparent;
|
||||
color: #aaa;
|
||||
}
|
||||
|
||||
table.highlighttable {
|
||||
margin-left: 0.5em;
|
||||
}
|
||||
|
||||
table.highlighttable td {
|
||||
padding: 0 0.5em 0 0.5em;
|
||||
}
|
||||
|
||||
tt.descname {
|
||||
background-color: transparent;
|
||||
font-weight: bold;
|
||||
font-size: 1.2em;
|
||||
}
|
||||
|
||||
tt.descclassname {
|
||||
background-color: transparent;
|
||||
}
|
||||
|
||||
tt.xref, a tt {
|
||||
background-color: transparent;
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
h1 tt, h2 tt, h3 tt, h4 tt, h5 tt, h6 tt {
|
||||
background-color: transparent;
|
||||
}
|
||||
|
||||
.viewcode-link {
|
||||
float: right;
|
||||
}
|
||||
|
||||
.viewcode-back {
|
||||
float: right;
|
||||
font-family: sans-serif;
|
||||
}
|
||||
|
||||
div.viewcode-block:target {
|
||||
margin: -1px -10px;
|
||||
padding: 0 10px;
|
||||
}
|
||||
|
||||
/* -- math display ---------------------------------------------------------- */
|
||||
|
||||
img.math {
|
||||
vertical-align: middle;
|
||||
}
|
||||
|
||||
div.body div.math p {
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
span.eqno {
|
||||
float: right;
|
||||
}
|
||||
|
||||
/* -- printout stylesheet --------------------------------------------------- */
|
||||
|
||||
@media print {
|
||||
div.document,
|
||||
div.documentwrapper,
|
||||
div.bodywrapper {
|
||||
margin: 0 !important;
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
div.sphinxsidebar,
|
||||
div.related,
|
||||
div.footer,
|
||||
#top-link {
|
||||
display: none;
|
||||
}
|
||||
}
|
||||
716
doc/html/numpy/_static/boost.css
Normal file
716
doc/html/numpy/_static/boost.css
Normal file
@@ -0,0 +1,716 @@
|
||||
|
||||
/*=============================================================================
|
||||
Copyright (c) 2004 Joel de Guzman
|
||||
http://spirit.sourceforge.net/
|
||||
|
||||
Copyright 2013 Niall Douglas additions for colors and alignment.
|
||||
Copyright 2013 Paul A. Bristow additions for more colors and alignments.
|
||||
|
||||
Distributed under the Boost Software License, Version 1.0. (See accompany-
|
||||
ing file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
|
||||
=============================================================================*/
|
||||
|
||||
/*=============================================================================
|
||||
Body defaults
|
||||
=============================================================================*/
|
||||
|
||||
body
|
||||
{
|
||||
margin: 1em;
|
||||
font-family: sans-serif;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Paragraphs
|
||||
=============================================================================*/
|
||||
|
||||
p
|
||||
{
|
||||
text-align: left;
|
||||
font-size: 10pt;
|
||||
line-height: 1.15;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Program listings
|
||||
=============================================================================*/
|
||||
|
||||
/* Code on paragraphs */
|
||||
p tt.computeroutput
|
||||
{
|
||||
font-size: 9pt;
|
||||
}
|
||||
|
||||
pre.synopsis
|
||||
{
|
||||
font-size: 9pt;
|
||||
margin: 1pc 4% 0pc 4%;
|
||||
padding: 0.5pc 0.5pc 0.5pc 0.5pc;
|
||||
}
|
||||
|
||||
.programlisting,
|
||||
.screen
|
||||
{
|
||||
font-size: 9pt;
|
||||
display: block;
|
||||
margin: 1pc 4% 0pc 4%;
|
||||
padding: 0.5pc 0.5pc 0.5pc 0.5pc;
|
||||
}
|
||||
|
||||
/* Program listings in tables don't get borders */
|
||||
td .programlisting,
|
||||
td .screen
|
||||
{
|
||||
margin: 0pc 0pc 0pc 0pc;
|
||||
padding: 0pc 0pc 0pc 0pc;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Headings
|
||||
=============================================================================*/
|
||||
|
||||
h1, h2, h3, h4, h5, h6
|
||||
{
|
||||
text-align: left;
|
||||
margin: 1em 0em 0.5em 0em;
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
h1 { font-size: 140%; }
|
||||
h2 { font-weight: bold; font-size: 140%; }
|
||||
h3 { font-weight: bold; font-size: 130%; }
|
||||
h4 { font-weight: bold; font-size: 120%; }
|
||||
h5 { font-weight: normal; font-style: italic; font-size: 110%; }
|
||||
h6 { font-weight: normal; font-style: italic; font-size: 100%; }
|
||||
|
||||
/* Top page titles */
|
||||
title,
|
||||
h1.title,
|
||||
h2.title
|
||||
h3.title,
|
||||
h4.title,
|
||||
h5.title,
|
||||
h6.title,
|
||||
.refentrytitle
|
||||
{
|
||||
font-weight: bold;
|
||||
margin-bottom: 1pc;
|
||||
}
|
||||
|
||||
h1.title { font-size: 140% }
|
||||
h2.title { font-size: 140% }
|
||||
h3.title { font-size: 130% }
|
||||
h4.title { font-size: 120% }
|
||||
h5.title { font-size: 110% }
|
||||
h6.title { font-size: 100% }
|
||||
|
||||
.section h1
|
||||
{
|
||||
margin: 0em 0em 0.5em 0em;
|
||||
font-size: 140%;
|
||||
}
|
||||
|
||||
.section h2 { font-size: 140% }
|
||||
.section h3 { font-size: 130% }
|
||||
.section h4 { font-size: 120% }
|
||||
.section h5 { font-size: 110% }
|
||||
.section h6 { font-size: 100% }
|
||||
|
||||
/* Code on titles */
|
||||
h1 tt.computeroutput { font-size: 140% }
|
||||
h2 tt.computeroutput { font-size: 140% }
|
||||
h3 tt.computeroutput { font-size: 130% }
|
||||
h4 tt.computeroutput { font-size: 130% }
|
||||
h5 tt.computeroutput { font-size: 130% }
|
||||
h6 tt.computeroutput { font-size: 130% }
|
||||
|
||||
|
||||
/*=============================================================================
|
||||
Author
|
||||
=============================================================================*/
|
||||
|
||||
h3.author
|
||||
{
|
||||
font-size: 100%
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Lists
|
||||
=============================================================================*/
|
||||
|
||||
li
|
||||
{
|
||||
font-size: 10pt;
|
||||
line-height: 1.3;
|
||||
}
|
||||
|
||||
/* Unordered lists */
|
||||
ul
|
||||
{
|
||||
text-align: left;
|
||||
}
|
||||
|
||||
/* Ordered lists */
|
||||
ol
|
||||
{
|
||||
text-align: left;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Links
|
||||
=============================================================================*/
|
||||
|
||||
a
|
||||
{
|
||||
text-decoration: none; /* no underline */
|
||||
}
|
||||
|
||||
a:hover
|
||||
{
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Spirit style navigation
|
||||
=============================================================================*/
|
||||
|
||||
.spirit-nav
|
||||
{
|
||||
text-align: right;
|
||||
}
|
||||
|
||||
.spirit-nav a
|
||||
{
|
||||
color: white;
|
||||
padding-left: 0.5em;
|
||||
}
|
||||
|
||||
.spirit-nav img
|
||||
{
|
||||
border-width: 0px;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Copyright footer
|
||||
=============================================================================*/
|
||||
.copyright-footer
|
||||
{
|
||||
text-align: right;
|
||||
font-size: 70%;
|
||||
}
|
||||
|
||||
.copyright-footer p
|
||||
{
|
||||
text-align: right;
|
||||
font-size: 80%;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Table of contents
|
||||
=============================================================================*/
|
||||
|
||||
div.toc
|
||||
{
|
||||
margin: 1pc 4% 0pc 4%;
|
||||
padding: 0.1pc 1pc 0.1pc 1pc;
|
||||
font-size: 80%;
|
||||
line-height: 1.15;
|
||||
}
|
||||
|
||||
.boost-toc
|
||||
{
|
||||
float: right;
|
||||
padding: 0.5pc;
|
||||
}
|
||||
|
||||
/* Code on toc */
|
||||
.toc .computeroutput { font-size: 120% }
|
||||
|
||||
/* No margin on nested menus */
|
||||
|
||||
.toc dl dl { margin: 0; }
|
||||
|
||||
/*=============================================================================
|
||||
Tables
|
||||
=============================================================================*/
|
||||
|
||||
.table-title,
|
||||
div.table p.title
|
||||
{
|
||||
margin-left: 4%;
|
||||
padding-right: 0.5em;
|
||||
padding-left: 0.5em;
|
||||
}
|
||||
|
||||
.informaltable table,
|
||||
.table table
|
||||
{
|
||||
width: 92%;
|
||||
margin-left: 4%;
|
||||
margin-right: 4%;
|
||||
}
|
||||
|
||||
div.informaltable table,
|
||||
div.table table
|
||||
{
|
||||
padding: 4px;
|
||||
}
|
||||
|
||||
/* Table Cells */
|
||||
div.informaltable table tr td,
|
||||
div.table table tr td
|
||||
{
|
||||
padding: 0.5em;
|
||||
text-align: left;
|
||||
font-size: 9pt;
|
||||
}
|
||||
|
||||
div.informaltable table tr th,
|
||||
div.table table tr th
|
||||
{
|
||||
padding: 0.5em 0.5em 0.5em 0.5em;
|
||||
border: 1pt solid white;
|
||||
font-size: 80%;
|
||||
}
|
||||
|
||||
table.simplelist
|
||||
{
|
||||
width: auto !important;
|
||||
margin: 0em !important;
|
||||
padding: 0em !important;
|
||||
border: none !important;
|
||||
}
|
||||
table.simplelist td
|
||||
{
|
||||
margin: 0em !important;
|
||||
padding: 0em !important;
|
||||
text-align: left !important;
|
||||
font-size: 9pt !important;
|
||||
border: none !important;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Suppress margins in tables
|
||||
=============================================================================*/
|
||||
|
||||
table th > *:first-child,
|
||||
table td > *:first-child
|
||||
{
|
||||
margin-top: 0;
|
||||
}
|
||||
|
||||
table th > *:last-child,
|
||||
table td > *:last-child
|
||||
{
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Blurbs
|
||||
=============================================================================*/
|
||||
|
||||
div.note,
|
||||
div.tip,
|
||||
div.important,
|
||||
div.caution,
|
||||
div.warning,
|
||||
p.blurb
|
||||
{
|
||||
font-size: 9pt; /* A little bit smaller than the main text */
|
||||
line-height: 1.2;
|
||||
display: block;
|
||||
margin: 1pc 4% 0pc 4%;
|
||||
padding: 0.5pc 0.5pc 0.5pc 0.5pc;
|
||||
}
|
||||
|
||||
p.blurb img
|
||||
{
|
||||
padding: 1pt;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Variable Lists
|
||||
=============================================================================*/
|
||||
|
||||
div.variablelist
|
||||
{
|
||||
margin: 1em 0;
|
||||
}
|
||||
|
||||
/* Make the terms in definition lists bold */
|
||||
div.variablelist dl dt,
|
||||
span.term
|
||||
{
|
||||
font-weight: bold;
|
||||
font-size: 10pt;
|
||||
}
|
||||
|
||||
div.variablelist table tbody tr td
|
||||
{
|
||||
text-align: left;
|
||||
vertical-align: top;
|
||||
padding: 0em 2em 0em 0em;
|
||||
font-size: 10pt;
|
||||
margin: 0em 0em 0.5em 0em;
|
||||
line-height: 1;
|
||||
}
|
||||
|
||||
div.variablelist dl dt
|
||||
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|
||||
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|
||||
}
|
||||
|
||||
div.variablelist dl dd
|
||||
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|
||||
margin: 0em 0em 0.5em 2em;
|
||||
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|
||||
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|
||||
|
||||
div.variablelist table tbody tr td p,
|
||||
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|
||||
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|
||||
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|
||||
line-height: 1;
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Misc
|
||||
=============================================================================*/
|
||||
|
||||
/* Title of books and articles in bibliographies */
|
||||
span.title
|
||||
{
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
span.underline
|
||||
{
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
span.strikethrough
|
||||
{
|
||||
text-decoration: line-through;
|
||||
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|
||||
|
||||
/* Copyright, Legal Notice */
|
||||
div div.legalnotice p
|
||||
{
|
||||
text-align: left
|
||||
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|
||||
|
||||
/*=============================================================================
|
||||
Colors
|
||||
=============================================================================*/
|
||||
|
||||
@media screen
|
||||
{
|
||||
body {
|
||||
background-color: #FFFFFF;
|
||||
color: #000000;
|
||||
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|
||||
|
||||
/* Syntax Highlighting */
|
||||
.keyword { color: #0000AA; }
|
||||
.identifier { color: #000000; }
|
||||
.special { color: #707070; }
|
||||
.preprocessor { color: #402080; }
|
||||
.char { color: teal; }
|
||||
.comment { color: #800000; }
|
||||
.string { color: teal; }
|
||||
.number { color: teal; }
|
||||
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|
||||
.dk_grey_bkd { background-color: #999999; }
|
||||
|
||||
/* Links */
|
||||
a, a .keyword, a .identifier, a .special, a .preprocessor
|
||||
a .char, a .comment, a .string, a .number
|
||||
{
|
||||
color: #005a9c;
|
||||
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|
||||
|
||||
a:visited, a:visited .keyword, a:visited .identifier,
|
||||
a:visited .special, a:visited .preprocessor a:visited .char,
|
||||
a:visited .comment, a:visited .string, a:visited .number
|
||||
{
|
||||
color: #9c5a9c;
|
||||
}
|
||||
|
||||
h1 a, h2 a, h3 a, h4 a, h5 a, h6 a,
|
||||
h1 a:hover, h2 a:hover, h3 a:hover, h4 a:hover, h5 a:hover, h6 a:hover,
|
||||
h1 a:visited, h2 a:visited, h3 a:visited, h4 a:visited, h5 a:visited, h6 a:visited
|
||||
{
|
||||
text-decoration: none; /* no underline */
|
||||
color: #000000;
|
||||
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|
||||
|
||||
/* Copyright, Legal Notice */
|
||||
.copyright
|
||||
{
|
||||
color: #666666;
|
||||
font-size: small;
|
||||
}
|
||||
|
||||
div div.legalnotice p
|
||||
{
|
||||
color: #666666;
|
||||
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|
||||
|
||||
/* Program listing */
|
||||
pre.synopsis
|
||||
{
|
||||
border: 1px solid #DCDCDC;
|
||||
}
|
||||
|
||||
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|
||||
.screen
|
||||
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|
||||
border: 1px solid #DCDCDC;
|
||||
}
|
||||
|
||||
td .programlisting,
|
||||
td .screen
|
||||
{
|
||||
border: 0px solid #DCDCDC;
|
||||
}
|
||||
|
||||
/* Blurbs */
|
||||
div.note,
|
||||
div.tip,
|
||||
div.important,
|
||||
div.caution,
|
||||
div.warning,
|
||||
p.blurb
|
||||
{
|
||||
border: 1px solid #DCDCDC;
|
||||
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|
||||
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||||
/* Table of contents */
|
||||
div.toc
|
||||
{
|
||||
border: 1px solid #DCDCDC;
|
||||
}
|
||||
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||||
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|
||||
div.informaltable table tr td,
|
||||
div.table table tr td
|
||||
{
|
||||
border: 1px solid #DCDCDC;
|
||||
}
|
||||
|
||||
div.informaltable table tr th,
|
||||
div.table table tr th
|
||||
{
|
||||
background-color: #F0F0F0;
|
||||
border: 1px solid #DCDCDC;
|
||||
}
|
||||
|
||||
.copyright-footer
|
||||
{
|
||||
color: #8F8F8F;
|
||||
}
|
||||
|
||||
/* Misc */
|
||||
span.highlight
|
||||
{
|
||||
color: #00A000;
|
||||
}
|
||||
}
|
||||
|
||||
@media print
|
||||
{
|
||||
/* Links */
|
||||
a
|
||||
{
|
||||
color: black;
|
||||
}
|
||||
|
||||
a:visited
|
||||
{
|
||||
color: black;
|
||||
}
|
||||
|
||||
.spirit-nav
|
||||
{
|
||||
display: none;
|
||||
}
|
||||
|
||||
/* Program listing */
|
||||
pre.synopsis
|
||||
{
|
||||
border: 1px solid gray;
|
||||
}
|
||||
|
||||
.programlisting,
|
||||
.screen
|
||||
{
|
||||
border: 1px solid gray;
|
||||
}
|
||||
|
||||
td .programlisting,
|
||||
td .screen
|
||||
{
|
||||
border: 0px solid #DCDCDC;
|
||||
}
|
||||
|
||||
/* Table of contents */
|
||||
div.toc
|
||||
{
|
||||
border: 1px solid gray;
|
||||
}
|
||||
|
||||
.informaltable table,
|
||||
.table table
|
||||
{
|
||||
border: 1px solid gray;
|
||||
border-collapse: collapse;
|
||||
}
|
||||
|
||||
/* Tables */
|
||||
div.informaltable table tr td,
|
||||
div.table table tr td
|
||||
{
|
||||
border: 1px solid gray;
|
||||
}
|
||||
|
||||
div.informaltable table tr th,
|
||||
div.table table tr th
|
||||
{
|
||||
border: 1px solid gray;
|
||||
}
|
||||
|
||||
table.simplelist tr td
|
||||
{
|
||||
border: none !important;
|
||||
}
|
||||
|
||||
/* Misc */
|
||||
span.highlight
|
||||
{
|
||||
font-weight: bold;
|
||||
}
|
||||
}
|
||||
|
||||
/*=============================================================================
|
||||
Images
|
||||
=============================================================================*/
|
||||
|
||||
span.inlinemediaobject img
|
||||
{
|
||||
vertical-align: middle;
|
||||
}
|
||||
|
||||
/*==============================================================================
|
||||
Super and Subscript: style so that line spacing isn't effected, see
|
||||
http://www.adobe.com/cfusion/communityengine/index.cfm?event=showdetails&productId=1&postId=5341
|
||||
==============================================================================*/
|
||||
|
||||
sup,
|
||||
sub {
|
||||
height: 0;
|
||||
line-height: 1;
|
||||
vertical-align: baseline;
|
||||
position: relative;
|
||||
|
||||
}
|
||||
|
||||
/* For internet explorer: */
|
||||
|
||||
* html sup,
|
||||
* html sub {
|
||||
vertical-align: bottom;
|
||||
}
|
||||
|
||||
sup {
|
||||
bottom: 1ex;
|
||||
}
|
||||
|
||||
sub {
|
||||
top: .5ex;
|
||||
}
|
||||
|
||||
/*==============================================================================
|
||||
Indexes: pretty much the same as the TOC.
|
||||
==============================================================================*/
|
||||
|
||||
.index
|
||||
{
|
||||
font-size: 80%;
|
||||
padding-top: 0px;
|
||||
padding-bottom: 0px;
|
||||
margin-top: 0px;
|
||||
margin-bottom: 0px;
|
||||
margin-left: 0px;
|
||||
}
|
||||
|
||||
.index ul
|
||||
{
|
||||
padding-left: 3em;
|
||||
}
|
||||
|
||||
.index p
|
||||
{
|
||||
padding: 2px;
|
||||
margin: 2px;
|
||||
}
|
||||
|
||||
.index-entry-level-0
|
||||
{
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
.index em
|
||||
{
|
||||
font-weight: bold;
|
||||
}
|
||||
|
||||
|
||||
/*==============================================================================
|
||||
Alignment and coloring use 'role' feature, available from Quickbook 1.6 up.
|
||||
Added from Niall Douglas for role color and alignment.
|
||||
http://article.gmane.org/gmane.comp.lib.boost.devel/243318
|
||||
*/
|
||||
|
||||
/* Add text alignment (see http://www.w3schools.com/cssref/pr_text_text-align.asp) */
|
||||
span.aligncenter
|
||||
{
|
||||
display: inline-block; width: 100%; text-align: center;
|
||||
}
|
||||
span.alignright
|
||||
{
|
||||
display: inline-block; width: 100%; text-align: right;
|
||||
}
|
||||
/* alignleft is the default. */
|
||||
span.alignleft
|
||||
{
|
||||
display: inline-block; width: 100%; text-align: left;
|
||||
}
|
||||
|
||||
/* alignjustify stretches the word spacing so that each line has equal width
|
||||
within a chosen fraction of page width (here arbitrarily 20%).
|
||||
*Not* useful inside table items as the column width remains the total string width.
|
||||
Nor very useful, except to temporarily restrict the width.
|
||||
*/
|
||||
span.alignjustify
|
||||
{
|
||||
display: inline-block; width: 20%; text-align: justify;
|
||||
}
|
||||
|
||||
/* Text colors.
|
||||
Names at http://www.w3.org/TR/2002/WD-css3-color-20020219/ 4.3. X11 color keywords.
|
||||
Quickbook Usage: [role red Some red text]
|
||||
|
||||
*/
|
||||
span.red { inline-block; color: red; }
|
||||
span.green { color: green; }
|
||||
span.lime { color: #00FF00; }
|
||||
span.blue { color: blue; }
|
||||
span.navy { color: navy; }
|
||||
span.yellow { color: yellow; }
|
||||
span.magenta { color: magenta; }
|
||||
span.indigo { color: #4B0082; }
|
||||
span.cyan { color: cyan; }
|
||||
span.purple { color: purple; }
|
||||
span.gold { color: gold; }
|
||||
span.silver { color: silver; } /* lighter gray */
|
||||
span.gray { color: #808080; } /* light gray */
|
||||
BIN
doc/html/numpy/_static/boost.png
Normal file
BIN
doc/html/numpy/_static/boost.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 6.2 KiB |
BIN
doc/html/numpy/_static/bpl.png
Normal file
BIN
doc/html/numpy/_static/bpl.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 21 KiB |
BIN
doc/html/numpy/_static/comment-bright.png
Normal file
BIN
doc/html/numpy/_static/comment-bright.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 3.4 KiB |
BIN
doc/html/numpy/_static/comment-close.png
Normal file
BIN
doc/html/numpy/_static/comment-close.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 3.5 KiB |
BIN
doc/html/numpy/_static/comment.png
Normal file
BIN
doc/html/numpy/_static/comment.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 3.4 KiB |
256
doc/html/numpy/_static/default.css
Normal file
256
doc/html/numpy/_static/default.css
Normal file
@@ -0,0 +1,256 @@
|
||||
/*
|
||||
* default.css_t
|
||||
* ~~~~~~~~~~~~~
|
||||
*
|
||||
* Sphinx stylesheet -- default theme.
|
||||
*
|
||||
* :copyright: Copyright 2007-2014 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
@import url("basic.css");
|
||||
|
||||
/* -- page layout ----------------------------------------------------------- */
|
||||
|
||||
body {
|
||||
font-family: sans-serif;
|
||||
font-size: 100%;
|
||||
background-color: #11303d;
|
||||
color: #000;
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
div.document {
|
||||
background-color: #1c4e63;
|
||||
}
|
||||
|
||||
div.documentwrapper {
|
||||
float: left;
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
div.bodywrapper {
|
||||
margin: 0 0 0 230px;
|
||||
}
|
||||
|
||||
div.body {
|
||||
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|
||||
color: #000000;
|
||||
padding: 0 20px 30px 20px;
|
||||
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|
||||
|
||||
div.footer {
|
||||
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|
||||
width: 100%;
|
||||
padding: 9px 0 9px 0;
|
||||
text-align: center;
|
||||
font-size: 75%;
|
||||
}
|
||||
|
||||
div.footer a {
|
||||
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|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
div.related {
|
||||
background-color: #133f52;
|
||||
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|
||||
color: #ffffff;
|
||||
}
|
||||
|
||||
div.related a {
|
||||
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||||
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||||
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||||
div.sphinxsidebar {
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||||
}
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||||
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||||
div.sphinxsidebar h3 {
|
||||
font-family: 'Trebuchet MS', sans-serif;
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||||
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font-size: 1.4em;
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||||
font-weight: normal;
|
||||
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|
||||
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||||
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|
||||
|
||||
div.sphinxsidebar h3 a {
|
||||
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|
||||
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|
||||
|
||||
div.sphinxsidebar h4 {
|
||||
font-family: 'Trebuchet MS', sans-serif;
|
||||
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|
||||
font-size: 1.3em;
|
||||
font-weight: normal;
|
||||
margin: 5px 0 0 0;
|
||||
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|
||||
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|
||||
|
||||
div.sphinxsidebar p {
|
||||
color: #ffffff;
|
||||
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|
||||
|
||||
div.sphinxsidebar p.topless {
|
||||
margin: 5px 10px 10px 10px;
|
||||
}
|
||||
|
||||
div.sphinxsidebar ul {
|
||||
margin: 10px;
|
||||
padding: 0;
|
||||
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|
||||
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|
||||
|
||||
div.sphinxsidebar a {
|
||||
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|
||||
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|
||||
|
||||
div.sphinxsidebar input {
|
||||
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|
||||
font-family: sans-serif;
|
||||
font-size: 1em;
|
||||
}
|
||||
|
||||
|
||||
|
||||
/* -- hyperlink styles ------------------------------------------------------ */
|
||||
|
||||
a {
|
||||
color: #355f7c;
|
||||
text-decoration: none;
|
||||
}
|
||||
|
||||
a:visited {
|
||||
color: #355f7c;
|
||||
text-decoration: none;
|
||||
}
|
||||
|
||||
a:hover {
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
|
||||
|
||||
/* -- body styles ----------------------------------------------------------- */
|
||||
|
||||
div.body h1,
|
||||
div.body h2,
|
||||
div.body h3,
|
||||
div.body h4,
|
||||
div.body h5,
|
||||
div.body h6 {
|
||||
font-family: 'Trebuchet MS', sans-serif;
|
||||
background-color: #f2f2f2;
|
||||
font-weight: normal;
|
||||
color: #20435c;
|
||||
border-bottom: 1px solid #ccc;
|
||||
margin: 20px -20px 10px -20px;
|
||||
padding: 3px 0 3px 10px;
|
||||
}
|
||||
|
||||
div.body h1 { margin-top: 0; font-size: 200%; }
|
||||
div.body h2 { font-size: 160%; }
|
||||
div.body h3 { font-size: 140%; }
|
||||
div.body h4 { font-size: 120%; }
|
||||
div.body h5 { font-size: 110%; }
|
||||
div.body h6 { font-size: 100%; }
|
||||
|
||||
a.headerlink {
|
||||
color: #c60f0f;
|
||||
font-size: 0.8em;
|
||||
padding: 0 4px 0 4px;
|
||||
text-decoration: none;
|
||||
}
|
||||
|
||||
a.headerlink:hover {
|
||||
background-color: #c60f0f;
|
||||
color: white;
|
||||
}
|
||||
|
||||
div.body p, div.body dd, div.body li {
|
||||
text-align: justify;
|
||||
line-height: 130%;
|
||||
}
|
||||
|
||||
div.admonition p.admonition-title + p {
|
||||
display: inline;
|
||||
}
|
||||
|
||||
div.admonition p {
|
||||
margin-bottom: 5px;
|
||||
}
|
||||
|
||||
div.admonition pre {
|
||||
margin-bottom: 5px;
|
||||
}
|
||||
|
||||
div.admonition ul, div.admonition ol {
|
||||
margin-bottom: 5px;
|
||||
}
|
||||
|
||||
div.note {
|
||||
background-color: #eee;
|
||||
border: 1px solid #ccc;
|
||||
}
|
||||
|
||||
div.seealso {
|
||||
background-color: #ffc;
|
||||
border: 1px solid #ff6;
|
||||
}
|
||||
|
||||
div.topic {
|
||||
background-color: #eee;
|
||||
}
|
||||
|
||||
div.warning {
|
||||
background-color: #ffe4e4;
|
||||
border: 1px solid #f66;
|
||||
}
|
||||
|
||||
p.admonition-title {
|
||||
display: inline;
|
||||
}
|
||||
|
||||
p.admonition-title:after {
|
||||
content: ":";
|
||||
}
|
||||
|
||||
pre {
|
||||
padding: 5px;
|
||||
background-color: #eeffcc;
|
||||
color: #333333;
|
||||
line-height: 120%;
|
||||
border: 1px solid #ac9;
|
||||
border-left: none;
|
||||
border-right: none;
|
||||
}
|
||||
|
||||
tt {
|
||||
background-color: #ecf0f3;
|
||||
padding: 0 1px 0 1px;
|
||||
font-size: 0.95em;
|
||||
}
|
||||
|
||||
th {
|
||||
background-color: #ede;
|
||||
}
|
||||
|
||||
.warning tt {
|
||||
background: #efc2c2;
|
||||
}
|
||||
|
||||
.note tt {
|
||||
background: #d6d6d6;
|
||||
}
|
||||
|
||||
.viewcode-back {
|
||||
font-family: sans-serif;
|
||||
}
|
||||
|
||||
div.viewcode-block:target {
|
||||
background-color: #f4debf;
|
||||
border-top: 1px solid #ac9;
|
||||
border-bottom: 1px solid #ac9;
|
||||
}
|
||||
238
doc/html/numpy/_static/doctools.js
Normal file
238
doc/html/numpy/_static/doctools.js
Normal file
@@ -0,0 +1,238 @@
|
||||
/*
|
||||
* doctools.js
|
||||
* ~~~~~~~~~~~
|
||||
*
|
||||
* Sphinx JavaScript utilities for all documentation.
|
||||
*
|
||||
* :copyright: Copyright 2007-2014 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
/**
|
||||
* select a different prefix for underscore
|
||||
*/
|
||||
$u = _.noConflict();
|
||||
|
||||
/**
|
||||
* make the code below compatible with browsers without
|
||||
* an installed firebug like debugger
|
||||
if (!window.console || !console.firebug) {
|
||||
var names = ["log", "debug", "info", "warn", "error", "assert", "dir",
|
||||
"dirxml", "group", "groupEnd", "time", "timeEnd", "count", "trace",
|
||||
"profile", "profileEnd"];
|
||||
window.console = {};
|
||||
for (var i = 0; i < names.length; ++i)
|
||||
window.console[names[i]] = function() {};
|
||||
}
|
||||
*/
|
||||
|
||||
/**
|
||||
* small helper function to urldecode strings
|
||||
*/
|
||||
jQuery.urldecode = function(x) {
|
||||
return decodeURIComponent(x).replace(/\+/g, ' ');
|
||||
};
|
||||
|
||||
/**
|
||||
* small helper function to urlencode strings
|
||||
*/
|
||||
jQuery.urlencode = encodeURIComponent;
|
||||
|
||||
/**
|
||||
* This function returns the parsed url parameters of the
|
||||
* current request. Multiple values per key are supported,
|
||||
* it will always return arrays of strings for the value parts.
|
||||
*/
|
||||
jQuery.getQueryParameters = function(s) {
|
||||
if (typeof s == 'undefined')
|
||||
s = document.location.search;
|
||||
var parts = s.substr(s.indexOf('?') + 1).split('&');
|
||||
var result = {};
|
||||
for (var i = 0; i < parts.length; i++) {
|
||||
var tmp = parts[i].split('=', 2);
|
||||
var key = jQuery.urldecode(tmp[0]);
|
||||
var value = jQuery.urldecode(tmp[1]);
|
||||
if (key in result)
|
||||
result[key].push(value);
|
||||
else
|
||||
result[key] = [value];
|
||||
}
|
||||
return result;
|
||||
};
|
||||
|
||||
/**
|
||||
* highlight a given string on a jquery object by wrapping it in
|
||||
* span elements with the given class name.
|
||||
*/
|
||||
jQuery.fn.highlightText = function(text, className) {
|
||||
function highlight(node) {
|
||||
if (node.nodeType == 3) {
|
||||
var val = node.nodeValue;
|
||||
var pos = val.toLowerCase().indexOf(text);
|
||||
if (pos >= 0 && !jQuery(node.parentNode).hasClass(className)) {
|
||||
var span = document.createElement("span");
|
||||
span.className = className;
|
||||
span.appendChild(document.createTextNode(val.substr(pos, text.length)));
|
||||
node.parentNode.insertBefore(span, node.parentNode.insertBefore(
|
||||
document.createTextNode(val.substr(pos + text.length)),
|
||||
node.nextSibling));
|
||||
node.nodeValue = val.substr(0, pos);
|
||||
}
|
||||
}
|
||||
else if (!jQuery(node).is("button, select, textarea")) {
|
||||
jQuery.each(node.childNodes, function() {
|
||||
highlight(this);
|
||||
});
|
||||
}
|
||||
}
|
||||
return this.each(function() {
|
||||
highlight(this);
|
||||
});
|
||||
};
|
||||
|
||||
/**
|
||||
* Small JavaScript module for the documentation.
|
||||
*/
|
||||
var Documentation = {
|
||||
|
||||
init : function() {
|
||||
this.fixFirefoxAnchorBug();
|
||||
this.highlightSearchWords();
|
||||
this.initIndexTable();
|
||||
},
|
||||
|
||||
/**
|
||||
* i18n support
|
||||
*/
|
||||
TRANSLATIONS : {},
|
||||
PLURAL_EXPR : function(n) { return n == 1 ? 0 : 1; },
|
||||
LOCALE : 'unknown',
|
||||
|
||||
// gettext and ngettext don't access this so that the functions
|
||||
// can safely bound to a different name (_ = Documentation.gettext)
|
||||
gettext : function(string) {
|
||||
var translated = Documentation.TRANSLATIONS[string];
|
||||
if (typeof translated == 'undefined')
|
||||
return string;
|
||||
return (typeof translated == 'string') ? translated : translated[0];
|
||||
},
|
||||
|
||||
ngettext : function(singular, plural, n) {
|
||||
var translated = Documentation.TRANSLATIONS[singular];
|
||||
if (typeof translated == 'undefined')
|
||||
return (n == 1) ? singular : plural;
|
||||
return translated[Documentation.PLURALEXPR(n)];
|
||||
},
|
||||
|
||||
addTranslations : function(catalog) {
|
||||
for (var key in catalog.messages)
|
||||
this.TRANSLATIONS[key] = catalog.messages[key];
|
||||
this.PLURAL_EXPR = new Function('n', 'return +(' + catalog.plural_expr + ')');
|
||||
this.LOCALE = catalog.locale;
|
||||
},
|
||||
|
||||
/**
|
||||
* add context elements like header anchor links
|
||||
*/
|
||||
addContextElements : function() {
|
||||
$('div[id] > :header:first').each(function() {
|
||||
$('<a class="headerlink">\u00B6</a>').
|
||||
attr('href', '#' + this.id).
|
||||
attr('title', _('Permalink to this headline')).
|
||||
appendTo(this);
|
||||
});
|
||||
$('dt[id]').each(function() {
|
||||
$('<a class="headerlink">\u00B6</a>').
|
||||
attr('href', '#' + this.id).
|
||||
attr('title', _('Permalink to this definition')).
|
||||
appendTo(this);
|
||||
});
|
||||
},
|
||||
|
||||
/**
|
||||
* workaround a firefox stupidity
|
||||
*/
|
||||
fixFirefoxAnchorBug : function() {
|
||||
if (document.location.hash && $.browser.mozilla)
|
||||
window.setTimeout(function() {
|
||||
document.location.href += '';
|
||||
}, 10);
|
||||
},
|
||||
|
||||
/**
|
||||
* highlight the search words provided in the url in the text
|
||||
*/
|
||||
highlightSearchWords : function() {
|
||||
var params = $.getQueryParameters();
|
||||
var terms = (params.highlight) ? params.highlight[0].split(/\s+/) : [];
|
||||
if (terms.length) {
|
||||
var body = $('div.body');
|
||||
if (!body.length) {
|
||||
body = $('body');
|
||||
}
|
||||
window.setTimeout(function() {
|
||||
$.each(terms, function() {
|
||||
body.highlightText(this.toLowerCase(), 'highlighted');
|
||||
});
|
||||
}, 10);
|
||||
$('<p class="highlight-link"><a href="javascript:Documentation.' +
|
||||
'hideSearchWords()">' + _('Hide Search Matches') + '</a></p>')
|
||||
.appendTo($('#searchbox'));
|
||||
}
|
||||
},
|
||||
|
||||
/**
|
||||
* init the domain index toggle buttons
|
||||
*/
|
||||
initIndexTable : function() {
|
||||
var togglers = $('img.toggler').click(function() {
|
||||
var src = $(this).attr('src');
|
||||
var idnum = $(this).attr('id').substr(7);
|
||||
$('tr.cg-' + idnum).toggle();
|
||||
if (src.substr(-9) == 'minus.png')
|
||||
$(this).attr('src', src.substr(0, src.length-9) + 'plus.png');
|
||||
else
|
||||
$(this).attr('src', src.substr(0, src.length-8) + 'minus.png');
|
||||
}).css('display', '');
|
||||
if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) {
|
||||
togglers.click();
|
||||
}
|
||||
},
|
||||
|
||||
/**
|
||||
* helper function to hide the search marks again
|
||||
*/
|
||||
hideSearchWords : function() {
|
||||
$('#searchbox .highlight-link').fadeOut(300);
|
||||
$('span.highlighted').removeClass('highlighted');
|
||||
},
|
||||
|
||||
/**
|
||||
* make the url absolute
|
||||
*/
|
||||
makeURL : function(relativeURL) {
|
||||
return DOCUMENTATION_OPTIONS.URL_ROOT + '/' + relativeURL;
|
||||
},
|
||||
|
||||
/**
|
||||
* get the current relative url
|
||||
*/
|
||||
getCurrentURL : function() {
|
||||
var path = document.location.pathname;
|
||||
var parts = path.split(/\//);
|
||||
$.each(DOCUMENTATION_OPTIONS.URL_ROOT.split(/\//), function() {
|
||||
if (this == '..')
|
||||
parts.pop();
|
||||
});
|
||||
var url = parts.join('/');
|
||||
return path.substring(url.lastIndexOf('/') + 1, path.length - 1);
|
||||
}
|
||||
};
|
||||
|
||||
// quick alias for translations
|
||||
_ = Documentation.gettext;
|
||||
|
||||
$(document).ready(function() {
|
||||
Documentation.init();
|
||||
});
|
||||
BIN
doc/html/numpy/_static/down-pressed.png
Normal file
BIN
doc/html/numpy/_static/down-pressed.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 368 B |
BIN
doc/html/numpy/_static/down.png
Normal file
BIN
doc/html/numpy/_static/down.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 363 B |
BIN
doc/html/numpy/_static/file.png
Normal file
BIN
doc/html/numpy/_static/file.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 392 B |
BIN
doc/html/numpy/_static/home.png
Normal file
BIN
doc/html/numpy/_static/home.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 358 B |
9404
doc/html/numpy/_static/jquery.js
vendored
Normal file
9404
doc/html/numpy/_static/jquery.js
vendored
Normal file
File diff suppressed because it is too large
Load Diff
BIN
doc/html/numpy/_static/minus.png
Normal file
BIN
doc/html/numpy/_static/minus.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 199 B |
BIN
doc/html/numpy/_static/next.png
Normal file
BIN
doc/html/numpy/_static/next.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 336 B |
BIN
doc/html/numpy/_static/plus.png
Normal file
BIN
doc/html/numpy/_static/plus.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 199 B |
BIN
doc/html/numpy/_static/prev.png
Normal file
BIN
doc/html/numpy/_static/prev.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 334 B |
62
doc/html/numpy/_static/pygments.css
Normal file
62
doc/html/numpy/_static/pygments.css
Normal file
@@ -0,0 +1,62 @@
|
||||
.highlight .hll { background-color: #ffffcc }
|
||||
.highlight { background: #f8f8f8; }
|
||||
.highlight .c { color: #408080; font-style: italic } /* Comment */
|
||||
.highlight .err { border: 1px solid #FF0000 } /* Error */
|
||||
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
|
||||
.highlight .o { color: #666666 } /* Operator */
|
||||
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
|
||||
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
|
||||
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
|
||||
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
|
||||
.highlight .gd { color: #A00000 } /* Generic.Deleted */
|
||||
.highlight .ge { font-style: italic } /* Generic.Emph */
|
||||
.highlight .gr { color: #FF0000 } /* Generic.Error */
|
||||
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
|
||||
.highlight .gi { color: #00A000 } /* Generic.Inserted */
|
||||
.highlight .go { color: #888888 } /* Generic.Output */
|
||||
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
|
||||
.highlight .gs { font-weight: bold } /* Generic.Strong */
|
||||
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
|
||||
.highlight .gt { color: #0044DD } /* Generic.Traceback */
|
||||
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
|
||||
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
|
||||
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
|
||||
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
|
||||
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
|
||||
.highlight .kt { color: #B00040 } /* Keyword.Type */
|
||||
.highlight .m { color: #666666 } /* Literal.Number */
|
||||
.highlight .s { color: #BA2121 } /* Literal.String */
|
||||
.highlight .na { color: #7D9029 } /* Name.Attribute */
|
||||
.highlight .nb { color: #008000 } /* Name.Builtin */
|
||||
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
|
||||
.highlight .no { color: #880000 } /* Name.Constant */
|
||||
.highlight .nd { color: #AA22FF } /* Name.Decorator */
|
||||
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
|
||||
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
|
||||
.highlight .nf { color: #0000FF } /* Name.Function */
|
||||
.highlight .nl { color: #A0A000 } /* Name.Label */
|
||||
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
|
||||
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
|
||||
.highlight .nv { color: #19177C } /* Name.Variable */
|
||||
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
|
||||
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
|
||||
.highlight .mf { color: #666666 } /* Literal.Number.Float */
|
||||
.highlight .mh { color: #666666 } /* Literal.Number.Hex */
|
||||
.highlight .mi { color: #666666 } /* Literal.Number.Integer */
|
||||
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
|
||||
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
|
||||
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
|
||||
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
|
||||
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
|
||||
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
|
||||
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
|
||||
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
|
||||
.highlight .sx { color: #008000 } /* Literal.String.Other */
|
||||
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
|
||||
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
|
||||
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
|
||||
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
|
||||
.highlight .vc { color: #19177C } /* Name.Variable.Class */
|
||||
.highlight .vg { color: #19177C } /* Name.Variable.Global */
|
||||
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
|
||||
.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
|
||||
622
doc/html/numpy/_static/searchtools.js
Normal file
622
doc/html/numpy/_static/searchtools.js
Normal file
@@ -0,0 +1,622 @@
|
||||
/*
|
||||
* searchtools.js_t
|
||||
* ~~~~~~~~~~~~~~~~
|
||||
*
|
||||
* Sphinx JavaScript utilties for the full-text search.
|
||||
*
|
||||
* :copyright: Copyright 2007-2014 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
|
||||
/**
|
||||
* Porter Stemmer
|
||||
*/
|
||||
var Stemmer = function() {
|
||||
|
||||
var step2list = {
|
||||
ational: 'ate',
|
||||
tional: 'tion',
|
||||
enci: 'ence',
|
||||
anci: 'ance',
|
||||
izer: 'ize',
|
||||
bli: 'ble',
|
||||
alli: 'al',
|
||||
entli: 'ent',
|
||||
eli: 'e',
|
||||
ousli: 'ous',
|
||||
ization: 'ize',
|
||||
ation: 'ate',
|
||||
ator: 'ate',
|
||||
alism: 'al',
|
||||
iveness: 'ive',
|
||||
fulness: 'ful',
|
||||
ousness: 'ous',
|
||||
aliti: 'al',
|
||||
iviti: 'ive',
|
||||
biliti: 'ble',
|
||||
logi: 'log'
|
||||
};
|
||||
|
||||
var step3list = {
|
||||
icate: 'ic',
|
||||
ative: '',
|
||||
alize: 'al',
|
||||
iciti: 'ic',
|
||||
ical: 'ic',
|
||||
ful: '',
|
||||
ness: ''
|
||||
};
|
||||
|
||||
var c = "[^aeiou]"; // consonant
|
||||
var v = "[aeiouy]"; // vowel
|
||||
var C = c + "[^aeiouy]*"; // consonant sequence
|
||||
var V = v + "[aeiou]*"; // vowel sequence
|
||||
|
||||
var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0
|
||||
var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1
|
||||
var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1
|
||||
var s_v = "^(" + C + ")?" + v; // vowel in stem
|
||||
|
||||
this.stemWord = function (w) {
|
||||
var stem;
|
||||
var suffix;
|
||||
var firstch;
|
||||
var origword = w;
|
||||
|
||||
if (w.length < 3)
|
||||
return w;
|
||||
|
||||
var re;
|
||||
var re2;
|
||||
var re3;
|
||||
var re4;
|
||||
|
||||
firstch = w.substr(0,1);
|
||||
if (firstch == "y")
|
||||
w = firstch.toUpperCase() + w.substr(1);
|
||||
|
||||
// Step 1a
|
||||
re = /^(.+?)(ss|i)es$/;
|
||||
re2 = /^(.+?)([^s])s$/;
|
||||
|
||||
if (re.test(w))
|
||||
w = w.replace(re,"$1$2");
|
||||
else if (re2.test(w))
|
||||
w = w.replace(re2,"$1$2");
|
||||
|
||||
// Step 1b
|
||||
re = /^(.+?)eed$/;
|
||||
re2 = /^(.+?)(ed|ing)$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
re = new RegExp(mgr0);
|
||||
if (re.test(fp[1])) {
|
||||
re = /.$/;
|
||||
w = w.replace(re,"");
|
||||
}
|
||||
}
|
||||
else if (re2.test(w)) {
|
||||
var fp = re2.exec(w);
|
||||
stem = fp[1];
|
||||
re2 = new RegExp(s_v);
|
||||
if (re2.test(stem)) {
|
||||
w = stem;
|
||||
re2 = /(at|bl|iz)$/;
|
||||
re3 = new RegExp("([^aeiouylsz])\\1$");
|
||||
re4 = new RegExp("^" + C + v + "[^aeiouwxy]$");
|
||||
if (re2.test(w))
|
||||
w = w + "e";
|
||||
else if (re3.test(w)) {
|
||||
re = /.$/;
|
||||
w = w.replace(re,"");
|
||||
}
|
||||
else if (re4.test(w))
|
||||
w = w + "e";
|
||||
}
|
||||
}
|
||||
|
||||
// Step 1c
|
||||
re = /^(.+?)y$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
stem = fp[1];
|
||||
re = new RegExp(s_v);
|
||||
if (re.test(stem))
|
||||
w = stem + "i";
|
||||
}
|
||||
|
||||
// Step 2
|
||||
re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
stem = fp[1];
|
||||
suffix = fp[2];
|
||||
re = new RegExp(mgr0);
|
||||
if (re.test(stem))
|
||||
w = stem + step2list[suffix];
|
||||
}
|
||||
|
||||
// Step 3
|
||||
re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
stem = fp[1];
|
||||
suffix = fp[2];
|
||||
re = new RegExp(mgr0);
|
||||
if (re.test(stem))
|
||||
w = stem + step3list[suffix];
|
||||
}
|
||||
|
||||
// Step 4
|
||||
re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
|
||||
re2 = /^(.+?)(s|t)(ion)$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
stem = fp[1];
|
||||
re = new RegExp(mgr1);
|
||||
if (re.test(stem))
|
||||
w = stem;
|
||||
}
|
||||
else if (re2.test(w)) {
|
||||
var fp = re2.exec(w);
|
||||
stem = fp[1] + fp[2];
|
||||
re2 = new RegExp(mgr1);
|
||||
if (re2.test(stem))
|
||||
w = stem;
|
||||
}
|
||||
|
||||
// Step 5
|
||||
re = /^(.+?)e$/;
|
||||
if (re.test(w)) {
|
||||
var fp = re.exec(w);
|
||||
stem = fp[1];
|
||||
re = new RegExp(mgr1);
|
||||
re2 = new RegExp(meq1);
|
||||
re3 = new RegExp("^" + C + v + "[^aeiouwxy]$");
|
||||
if (re.test(stem) || (re2.test(stem) && !(re3.test(stem))))
|
||||
w = stem;
|
||||
}
|
||||
re = /ll$/;
|
||||
re2 = new RegExp(mgr1);
|
||||
if (re.test(w) && re2.test(w)) {
|
||||
re = /.$/;
|
||||
w = w.replace(re,"");
|
||||
}
|
||||
|
||||
// and turn initial Y back to y
|
||||
if (firstch == "y")
|
||||
w = firstch.toLowerCase() + w.substr(1);
|
||||
return w;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
/**
|
||||
* Simple result scoring code.
|
||||
*/
|
||||
var Scorer = {
|
||||
// Implement the following function to further tweak the score for each result
|
||||
// The function takes a result array [filename, title, anchor, descr, score]
|
||||
// and returns the new score.
|
||||
/*
|
||||
score: function(result) {
|
||||
return result[4];
|
||||
},
|
||||
*/
|
||||
|
||||
// query matches the full name of an object
|
||||
objNameMatch: 11,
|
||||
// or matches in the last dotted part of the object name
|
||||
objPartialMatch: 6,
|
||||
// Additive scores depending on the priority of the object
|
||||
objPrio: {0: 15, // used to be importantResults
|
||||
1: 5, // used to be objectResults
|
||||
2: -5}, // used to be unimportantResults
|
||||
// Used when the priority is not in the mapping.
|
||||
objPrioDefault: 0,
|
||||
|
||||
// query found in title
|
||||
title: 15,
|
||||
// query found in terms
|
||||
term: 5
|
||||
};
|
||||
|
||||
|
||||
/**
|
||||
* Search Module
|
||||
*/
|
||||
var Search = {
|
||||
|
||||
_index : null,
|
||||
_queued_query : null,
|
||||
_pulse_status : -1,
|
||||
|
||||
init : function() {
|
||||
var params = $.getQueryParameters();
|
||||
if (params.q) {
|
||||
var query = params.q[0];
|
||||
$('input[name="q"]')[0].value = query;
|
||||
this.performSearch(query);
|
||||
}
|
||||
},
|
||||
|
||||
loadIndex : function(url) {
|
||||
$.ajax({type: "GET", url: url, data: null,
|
||||
dataType: "script", cache: true,
|
||||
complete: function(jqxhr, textstatus) {
|
||||
if (textstatus != "success") {
|
||||
document.getElementById("searchindexloader").src = url;
|
||||
}
|
||||
}});
|
||||
},
|
||||
|
||||
setIndex : function(index) {
|
||||
var q;
|
||||
this._index = index;
|
||||
if ((q = this._queued_query) !== null) {
|
||||
this._queued_query = null;
|
||||
Search.query(q);
|
||||
}
|
||||
},
|
||||
|
||||
hasIndex : function() {
|
||||
return this._index !== null;
|
||||
},
|
||||
|
||||
deferQuery : function(query) {
|
||||
this._queued_query = query;
|
||||
},
|
||||
|
||||
stopPulse : function() {
|
||||
this._pulse_status = 0;
|
||||
},
|
||||
|
||||
startPulse : function() {
|
||||
if (this._pulse_status >= 0)
|
||||
return;
|
||||
function pulse() {
|
||||
var i;
|
||||
Search._pulse_status = (Search._pulse_status + 1) % 4;
|
||||
var dotString = '';
|
||||
for (i = 0; i < Search._pulse_status; i++)
|
||||
dotString += '.';
|
||||
Search.dots.text(dotString);
|
||||
if (Search._pulse_status > -1)
|
||||
window.setTimeout(pulse, 500);
|
||||
}
|
||||
pulse();
|
||||
},
|
||||
|
||||
/**
|
||||
* perform a search for something (or wait until index is loaded)
|
||||
*/
|
||||
performSearch : function(query) {
|
||||
// create the required interface elements
|
||||
this.out = $('#search-results');
|
||||
this.title = $('<h2>' + _('Searching') + '</h2>').appendTo(this.out);
|
||||
this.dots = $('<span></span>').appendTo(this.title);
|
||||
this.status = $('<p style="display: none"></p>').appendTo(this.out);
|
||||
this.output = $('<ul class="search"/>').appendTo(this.out);
|
||||
|
||||
$('#search-progress').text(_('Preparing search...'));
|
||||
this.startPulse();
|
||||
|
||||
// index already loaded, the browser was quick!
|
||||
if (this.hasIndex())
|
||||
this.query(query);
|
||||
else
|
||||
this.deferQuery(query);
|
||||
},
|
||||
|
||||
/**
|
||||
* execute search (requires search index to be loaded)
|
||||
*/
|
||||
query : function(query) {
|
||||
var i;
|
||||
var stopwords = ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"];
|
||||
|
||||
// stem the searchterms and add them to the correct list
|
||||
var stemmer = new Stemmer();
|
||||
var searchterms = [];
|
||||
var excluded = [];
|
||||
var hlterms = [];
|
||||
var tmp = query.split(/\s+/);
|
||||
var objectterms = [];
|
||||
for (i = 0; i < tmp.length; i++) {
|
||||
if (tmp[i] !== "") {
|
||||
objectterms.push(tmp[i].toLowerCase());
|
||||
}
|
||||
|
||||
if ($u.indexOf(stopwords, tmp[i].toLowerCase()) != -1 || tmp[i].match(/^\d+$/) ||
|
||||
tmp[i] === "") {
|
||||
// skip this "word"
|
||||
continue;
|
||||
}
|
||||
// stem the word
|
||||
var word = stemmer.stemWord(tmp[i].toLowerCase());
|
||||
var toAppend;
|
||||
// select the correct list
|
||||
if (word[0] == '-') {
|
||||
toAppend = excluded;
|
||||
word = word.substr(1);
|
||||
}
|
||||
else {
|
||||
toAppend = searchterms;
|
||||
hlterms.push(tmp[i].toLowerCase());
|
||||
}
|
||||
// only add if not already in the list
|
||||
if (!$u.contains(toAppend, word))
|
||||
toAppend.push(word);
|
||||
}
|
||||
var highlightstring = '?highlight=' + $.urlencode(hlterms.join(" "));
|
||||
|
||||
// console.debug('SEARCH: searching for:');
|
||||
// console.info('required: ', searchterms);
|
||||
// console.info('excluded: ', excluded);
|
||||
|
||||
// prepare search
|
||||
var terms = this._index.terms;
|
||||
var titleterms = this._index.titleterms;
|
||||
|
||||
// array of [filename, title, anchor, descr, score]
|
||||
var results = [];
|
||||
$('#search-progress').empty();
|
||||
|
||||
// lookup as object
|
||||
for (i = 0; i < objectterms.length; i++) {
|
||||
var others = [].concat(objectterms.slice(0, i),
|
||||
objectterms.slice(i+1, objectterms.length));
|
||||
results = results.concat(this.performObjectSearch(objectterms[i], others));
|
||||
}
|
||||
|
||||
// lookup as search terms in fulltext
|
||||
results = results.concat(this.performTermsSearch(searchterms, excluded, terms, Scorer.term))
|
||||
.concat(this.performTermsSearch(searchterms, excluded, titleterms, Scorer.title));
|
||||
|
||||
// let the scorer override scores with a custom scoring function
|
||||
if (Scorer.score) {
|
||||
for (i = 0; i < results.length; i++)
|
||||
results[i][4] = Scorer.score(results[i]);
|
||||
}
|
||||
|
||||
// now sort the results by score (in opposite order of appearance, since the
|
||||
// display function below uses pop() to retrieve items) and then
|
||||
// alphabetically
|
||||
results.sort(function(a, b) {
|
||||
var left = a[4];
|
||||
var right = b[4];
|
||||
if (left > right) {
|
||||
return 1;
|
||||
} else if (left < right) {
|
||||
return -1;
|
||||
} else {
|
||||
// same score: sort alphabetically
|
||||
left = a[1].toLowerCase();
|
||||
right = b[1].toLowerCase();
|
||||
return (left > right) ? -1 : ((left < right) ? 1 : 0);
|
||||
}
|
||||
});
|
||||
|
||||
// for debugging
|
||||
//Search.lastresults = results.slice(); // a copy
|
||||
//console.info('search results:', Search.lastresults);
|
||||
|
||||
// print the results
|
||||
var resultCount = results.length;
|
||||
function displayNextItem() {
|
||||
// results left, load the summary and display it
|
||||
if (results.length) {
|
||||
var item = results.pop();
|
||||
var listItem = $('<li style="display:none"></li>');
|
||||
if (DOCUMENTATION_OPTIONS.FILE_SUFFIX === '') {
|
||||
// dirhtml builder
|
||||
var dirname = item[0] + '/';
|
||||
if (dirname.match(/\/index\/$/)) {
|
||||
dirname = dirname.substring(0, dirname.length-6);
|
||||
} else if (dirname == 'index/') {
|
||||
dirname = '';
|
||||
}
|
||||
listItem.append($('<a/>').attr('href',
|
||||
DOCUMENTATION_OPTIONS.URL_ROOT + dirname +
|
||||
highlightstring + item[2]).html(item[1]));
|
||||
} else {
|
||||
// normal html builders
|
||||
listItem.append($('<a/>').attr('href',
|
||||
item[0] + DOCUMENTATION_OPTIONS.FILE_SUFFIX +
|
||||
highlightstring + item[2]).html(item[1]));
|
||||
}
|
||||
if (item[3]) {
|
||||
listItem.append($('<span> (' + item[3] + ')</span>'));
|
||||
Search.output.append(listItem);
|
||||
listItem.slideDown(5, function() {
|
||||
displayNextItem();
|
||||
});
|
||||
} else if (DOCUMENTATION_OPTIONS.HAS_SOURCE) {
|
||||
$.ajax({url: DOCUMENTATION_OPTIONS.URL_ROOT + '_sources/' + item[0] + '.txt',
|
||||
dataType: "text",
|
||||
complete: function(jqxhr, textstatus) {
|
||||
var data = jqxhr.responseText;
|
||||
if (data !== '') {
|
||||
listItem.append(Search.makeSearchSummary(data, searchterms, hlterms));
|
||||
}
|
||||
Search.output.append(listItem);
|
||||
listItem.slideDown(5, function() {
|
||||
displayNextItem();
|
||||
});
|
||||
}});
|
||||
} else {
|
||||
// no source available, just display title
|
||||
Search.output.append(listItem);
|
||||
listItem.slideDown(5, function() {
|
||||
displayNextItem();
|
||||
});
|
||||
}
|
||||
}
|
||||
// search finished, update title and status message
|
||||
else {
|
||||
Search.stopPulse();
|
||||
Search.title.text(_('Search Results'));
|
||||
if (!resultCount)
|
||||
Search.status.text(_('Your search did not match any documents. Please make sure that all words are spelled correctly and that you\'ve selected enough categories.'));
|
||||
else
|
||||
Search.status.text(_('Search finished, found %s page(s) matching the search query.').replace('%s', resultCount));
|
||||
Search.status.fadeIn(500);
|
||||
}
|
||||
}
|
||||
displayNextItem();
|
||||
},
|
||||
|
||||
/**
|
||||
* search for object names
|
||||
*/
|
||||
performObjectSearch : function(object, otherterms) {
|
||||
var filenames = this._index.filenames;
|
||||
var objects = this._index.objects;
|
||||
var objnames = this._index.objnames;
|
||||
var titles = this._index.titles;
|
||||
|
||||
var i;
|
||||
var results = [];
|
||||
|
||||
for (var prefix in objects) {
|
||||
for (var name in objects[prefix]) {
|
||||
var fullname = (prefix ? prefix + '.' : '') + name;
|
||||
if (fullname.toLowerCase().indexOf(object) > -1) {
|
||||
var score = 0;
|
||||
var parts = fullname.split('.');
|
||||
// check for different match types: exact matches of full name or
|
||||
// "last name" (i.e. last dotted part)
|
||||
if (fullname == object || parts[parts.length - 1] == object) {
|
||||
score += Scorer.objNameMatch;
|
||||
// matches in last name
|
||||
} else if (parts[parts.length - 1].indexOf(object) > -1) {
|
||||
score += Scorer.objPartialMatch;
|
||||
}
|
||||
var match = objects[prefix][name];
|
||||
var objname = objnames[match[1]][2];
|
||||
var title = titles[match[0]];
|
||||
// If more than one term searched for, we require other words to be
|
||||
// found in the name/title/description
|
||||
if (otherterms.length > 0) {
|
||||
var haystack = (prefix + ' ' + name + ' ' +
|
||||
objname + ' ' + title).toLowerCase();
|
||||
var allfound = true;
|
||||
for (i = 0; i < otherterms.length; i++) {
|
||||
if (haystack.indexOf(otherterms[i]) == -1) {
|
||||
allfound = false;
|
||||
break;
|
||||
}
|
||||
}
|
||||
if (!allfound) {
|
||||
continue;
|
||||
}
|
||||
}
|
||||
var descr = objname + _(', in ') + title;
|
||||
|
||||
var anchor = match[3];
|
||||
if (anchor === '')
|
||||
anchor = fullname;
|
||||
else if (anchor == '-')
|
||||
anchor = objnames[match[1]][1] + '-' + fullname;
|
||||
// add custom score for some objects according to scorer
|
||||
if (Scorer.objPrio.hasOwnProperty(match[2])) {
|
||||
score += Scorer.objPrio[match[2]];
|
||||
} else {
|
||||
score += Scorer.objPrioDefault;
|
||||
}
|
||||
results.push([filenames[match[0]], fullname, '#'+anchor, descr, score]);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return results;
|
||||
},
|
||||
|
||||
/**
|
||||
* search for full-text terms in the index
|
||||
*/
|
||||
performTermsSearch : function(searchterms, excluded, terms, score) {
|
||||
var filenames = this._index.filenames;
|
||||
var titles = this._index.titles;
|
||||
|
||||
var i, j, file, files;
|
||||
var fileMap = {};
|
||||
var results = [];
|
||||
|
||||
// perform the search on the required terms
|
||||
for (i = 0; i < searchterms.length; i++) {
|
||||
var word = searchterms[i];
|
||||
// no match but word was a required one
|
||||
if ((files = terms[word]) === undefined)
|
||||
break;
|
||||
if (files.length === undefined) {
|
||||
files = [files];
|
||||
}
|
||||
// create the mapping
|
||||
for (j = 0; j < files.length; j++) {
|
||||
file = files[j];
|
||||
if (file in fileMap)
|
||||
fileMap[file].push(word);
|
||||
else
|
||||
fileMap[file] = [word];
|
||||
}
|
||||
}
|
||||
|
||||
// now check if the files don't contain excluded terms
|
||||
for (file in fileMap) {
|
||||
var valid = true;
|
||||
|
||||
// check if all requirements are matched
|
||||
if (fileMap[file].length != searchterms.length)
|
||||
continue;
|
||||
|
||||
// ensure that none of the excluded terms is in the search result
|
||||
for (i = 0; i < excluded.length; i++) {
|
||||
if (terms[excluded[i]] == file ||
|
||||
$u.contains(terms[excluded[i]] || [], file)) {
|
||||
valid = false;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// if we have still a valid result we can add it to the result list
|
||||
if (valid) {
|
||||
results.push([filenames[file], titles[file], '', null, score]);
|
||||
}
|
||||
}
|
||||
return results;
|
||||
},
|
||||
|
||||
/**
|
||||
* helper function to return a node containing the
|
||||
* search summary for a given text. keywords is a list
|
||||
* of stemmed words, hlwords is the list of normal, unstemmed
|
||||
* words. the first one is used to find the occurance, the
|
||||
* latter for highlighting it.
|
||||
*/
|
||||
makeSearchSummary : function(text, keywords, hlwords) {
|
||||
var textLower = text.toLowerCase();
|
||||
var start = 0;
|
||||
$.each(keywords, function() {
|
||||
var i = textLower.indexOf(this.toLowerCase());
|
||||
if (i > -1)
|
||||
start = i;
|
||||
});
|
||||
start = Math.max(start - 120, 0);
|
||||
var excerpt = ((start > 0) ? '...' : '') +
|
||||
$.trim(text.substr(start, 240)) +
|
||||
((start + 240 - text.length) ? '...' : '');
|
||||
var rv = $('<div class="context"></div>').text(excerpt);
|
||||
$.each(hlwords, function() {
|
||||
rv = rv.highlightText(this, 'highlighted');
|
||||
});
|
||||
return rv;
|
||||
}
|
||||
};
|
||||
|
||||
$(document).ready(function() {
|
||||
Search.init();
|
||||
});
|
||||
159
doc/html/numpy/_static/sidebar.js
Normal file
159
doc/html/numpy/_static/sidebar.js
Normal file
@@ -0,0 +1,159 @@
|
||||
/*
|
||||
* sidebar.js
|
||||
* ~~~~~~~~~~
|
||||
*
|
||||
* This script makes the Sphinx sidebar collapsible.
|
||||
*
|
||||
* .sphinxsidebar contains .sphinxsidebarwrapper. This script adds
|
||||
* in .sphixsidebar, after .sphinxsidebarwrapper, the #sidebarbutton
|
||||
* used to collapse and expand the sidebar.
|
||||
*
|
||||
* When the sidebar is collapsed the .sphinxsidebarwrapper is hidden
|
||||
* and the width of the sidebar and the margin-left of the document
|
||||
* are decreased. When the sidebar is expanded the opposite happens.
|
||||
* This script saves a per-browser/per-session cookie used to
|
||||
* remember the position of the sidebar among the pages.
|
||||
* Once the browser is closed the cookie is deleted and the position
|
||||
* reset to the default (expanded).
|
||||
*
|
||||
* :copyright: Copyright 2007-2014 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
$(function() {
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
// global elements used by the functions.
|
||||
// the 'sidebarbutton' element is defined as global after its
|
||||
// creation, in the add_sidebar_button function
|
||||
var bodywrapper = $('.bodywrapper');
|
||||
var sidebar = $('.sphinxsidebar');
|
||||
var sidebarwrapper = $('.sphinxsidebarwrapper');
|
||||
|
||||
// for some reason, the document has no sidebar; do not run into errors
|
||||
if (!sidebar.length) return;
|
||||
|
||||
// original margin-left of the bodywrapper and width of the sidebar
|
||||
// with the sidebar expanded
|
||||
var bw_margin_expanded = bodywrapper.css('margin-left');
|
||||
var ssb_width_expanded = sidebar.width();
|
||||
|
||||
// margin-left of the bodywrapper and width of the sidebar
|
||||
// with the sidebar collapsed
|
||||
var bw_margin_collapsed = '.8em';
|
||||
var ssb_width_collapsed = '.8em';
|
||||
|
||||
// colors used by the current theme
|
||||
var dark_color = $('.related').css('background-color');
|
||||
var light_color = $('.document').css('background-color');
|
||||
|
||||
function sidebar_is_collapsed() {
|
||||
return sidebarwrapper.is(':not(:visible)');
|
||||
}
|
||||
|
||||
function toggle_sidebar() {
|
||||
if (sidebar_is_collapsed())
|
||||
expand_sidebar();
|
||||
else
|
||||
collapse_sidebar();
|
||||
}
|
||||
|
||||
function collapse_sidebar() {
|
||||
sidebarwrapper.hide();
|
||||
sidebar.css('width', ssb_width_collapsed);
|
||||
bodywrapper.css('margin-left', bw_margin_collapsed);
|
||||
sidebarbutton.css({
|
||||
'margin-left': '0',
|
||||
'height': bodywrapper.height()
|
||||
});
|
||||
sidebarbutton.find('span').text('»');
|
||||
sidebarbutton.attr('title', _('Expand sidebar'));
|
||||
document.cookie = 'sidebar=collapsed';
|
||||
}
|
||||
|
||||
function expand_sidebar() {
|
||||
bodywrapper.css('margin-left', bw_margin_expanded);
|
||||
sidebar.css('width', ssb_width_expanded);
|
||||
sidebarwrapper.show();
|
||||
sidebarbutton.css({
|
||||
'margin-left': ssb_width_expanded-12,
|
||||
'height': bodywrapper.height()
|
||||
});
|
||||
sidebarbutton.find('span').text('«');
|
||||
sidebarbutton.attr('title', _('Collapse sidebar'));
|
||||
document.cookie = 'sidebar=expanded';
|
||||
}
|
||||
|
||||
function add_sidebar_button() {
|
||||
sidebarwrapper.css({
|
||||
'float': 'left',
|
||||
'margin-right': '0',
|
||||
'width': ssb_width_expanded - 28
|
||||
});
|
||||
// create the button
|
||||
sidebar.append(
|
||||
'<div id="sidebarbutton"><span>«</span></div>'
|
||||
);
|
||||
var sidebarbutton = $('#sidebarbutton');
|
||||
light_color = sidebarbutton.css('background-color');
|
||||
// find the height of the viewport to center the '<<' in the page
|
||||
var viewport_height;
|
||||
if (window.innerHeight)
|
||||
viewport_height = window.innerHeight;
|
||||
else
|
||||
viewport_height = $(window).height();
|
||||
sidebarbutton.find('span').css({
|
||||
'display': 'block',
|
||||
'margin-top': (viewport_height - sidebar.position().top - 20) / 2
|
||||
});
|
||||
|
||||
sidebarbutton.click(toggle_sidebar);
|
||||
sidebarbutton.attr('title', _('Collapse sidebar'));
|
||||
sidebarbutton.css({
|
||||
'color': '#FFFFFF',
|
||||
'border-left': '1px solid ' + dark_color,
|
||||
'font-size': '1.2em',
|
||||
'cursor': 'pointer',
|
||||
'height': bodywrapper.height(),
|
||||
'padding-top': '1px',
|
||||
'margin-left': ssb_width_expanded - 12
|
||||
});
|
||||
|
||||
sidebarbutton.hover(
|
||||
function () {
|
||||
$(this).css('background-color', dark_color);
|
||||
},
|
||||
function () {
|
||||
$(this).css('background-color', light_color);
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
function set_position_from_cookie() {
|
||||
if (!document.cookie)
|
||||
return;
|
||||
var items = document.cookie.split(';');
|
||||
for(var k=0; k<items.length; k++) {
|
||||
var key_val = items[k].split('=');
|
||||
var key = key_val[0].replace(/ /, ""); // strip leading spaces
|
||||
if (key == 'sidebar') {
|
||||
var value = key_val[1];
|
||||
if ((value == 'collapsed') && (!sidebar_is_collapsed()))
|
||||
collapse_sidebar();
|
||||
else if ((value == 'expanded') && (sidebar_is_collapsed()))
|
||||
expand_sidebar();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
add_sidebar_button();
|
||||
var sidebarbutton = $('#sidebarbutton');
|
||||
set_position_from_cookie();
|
||||
});
|
||||
38
doc/html/numpy/_static/style.css
Normal file
38
doc/html/numpy/_static/style.css
Normal file
@@ -0,0 +1,38 @@
|
||||
@import url(boost.css);
|
||||
|
||||
.header h1 a
|
||||
{
|
||||
color: #00507f;
|
||||
font-size: 200%;
|
||||
font-style: italic;
|
||||
}
|
||||
.header h3 { margin: 1px;}
|
||||
#contents
|
||||
{
|
||||
/* border-bottom: solid thin black;*/
|
||||
}
|
||||
|
||||
.highlight
|
||||
{
|
||||
border: 1px solid #dcdcdc;
|
||||
background-color: inherit;
|
||||
padding: 0 1em;
|
||||
margin: 0 5em;
|
||||
}
|
||||
#searchbox
|
||||
{
|
||||
float: right;
|
||||
width: auto;
|
||||
margin: 0 2em;
|
||||
}
|
||||
|
||||
.admonition-title { font-weight: bold;}
|
||||
.toctree-wrapper
|
||||
{
|
||||
border: 1px solid #dcdcdc;
|
||||
padding: 1em;
|
||||
margin: 0 2em;
|
||||
}
|
||||
.toctree-wrapper .caption,
|
||||
.toctree-wrapper .topic-title { font-weight: bold;}
|
||||
|
||||
1226
doc/html/numpy/_static/underscore.js
Normal file
1226
doc/html/numpy/_static/underscore.js
Normal file
File diff suppressed because it is too large
Load Diff
BIN
doc/html/numpy/_static/up-pressed.png
Normal file
BIN
doc/html/numpy/_static/up-pressed.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 372 B |
BIN
doc/html/numpy/_static/up.png
Normal file
BIN
doc/html/numpy/_static/up.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 370 B |
808
doc/html/numpy/_static/websupport.js
Normal file
808
doc/html/numpy/_static/websupport.js
Normal file
@@ -0,0 +1,808 @@
|
||||
/*
|
||||
* websupport.js
|
||||
* ~~~~~~~~~~~~~
|
||||
*
|
||||
* sphinx.websupport utilties for all documentation.
|
||||
*
|
||||
* :copyright: Copyright 2007-2014 by the Sphinx team, see AUTHORS.
|
||||
* :license: BSD, see LICENSE for details.
|
||||
*
|
||||
*/
|
||||
|
||||
(function($) {
|
||||
$.fn.autogrow = function() {
|
||||
return this.each(function() {
|
||||
var textarea = this;
|
||||
|
||||
$.fn.autogrow.resize(textarea);
|
||||
|
||||
$(textarea)
|
||||
.focus(function() {
|
||||
textarea.interval = setInterval(function() {
|
||||
$.fn.autogrow.resize(textarea);
|
||||
}, 500);
|
||||
})
|
||||
.blur(function() {
|
||||
clearInterval(textarea.interval);
|
||||
});
|
||||
});
|
||||
};
|
||||
|
||||
$.fn.autogrow.resize = function(textarea) {
|
||||
var lineHeight = parseInt($(textarea).css('line-height'), 10);
|
||||
var lines = textarea.value.split('\n');
|
||||
var columns = textarea.cols;
|
||||
var lineCount = 0;
|
||||
$.each(lines, function() {
|
||||
lineCount += Math.ceil(this.length / columns) || 1;
|
||||
});
|
||||
var height = lineHeight * (lineCount + 1);
|
||||
$(textarea).css('height', height);
|
||||
};
|
||||
})(jQuery);
|
||||
|
||||
(function($) {
|
||||
var comp, by;
|
||||
|
||||
function init() {
|
||||
initEvents();
|
||||
initComparator();
|
||||
}
|
||||
|
||||
function initEvents() {
|
||||
$('a.comment-close').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
hide($(this).attr('id').substring(2));
|
||||
});
|
||||
$('a.vote').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
handleVote($(this));
|
||||
});
|
||||
$('a.reply').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
openReply($(this).attr('id').substring(2));
|
||||
});
|
||||
$('a.close-reply').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
closeReply($(this).attr('id').substring(2));
|
||||
});
|
||||
$('a.sort-option').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
handleReSort($(this));
|
||||
});
|
||||
$('a.show-proposal').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
showProposal($(this).attr('id').substring(2));
|
||||
});
|
||||
$('a.hide-proposal').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
hideProposal($(this).attr('id').substring(2));
|
||||
});
|
||||
$('a.show-propose-change').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
showProposeChange($(this).attr('id').substring(2));
|
||||
});
|
||||
$('a.hide-propose-change').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
hideProposeChange($(this).attr('id').substring(2));
|
||||
});
|
||||
$('a.accept-comment').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
acceptComment($(this).attr('id').substring(2));
|
||||
});
|
||||
$('a.delete-comment').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
deleteComment($(this).attr('id').substring(2));
|
||||
});
|
||||
$('a.comment-markup').live("click", function(event) {
|
||||
event.preventDefault();
|
||||
toggleCommentMarkupBox($(this).attr('id').substring(2));
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Set comp, which is a comparator function used for sorting and
|
||||
* inserting comments into the list.
|
||||
*/
|
||||
function setComparator() {
|
||||
// If the first three letters are "asc", sort in ascending order
|
||||
// and remove the prefix.
|
||||
if (by.substring(0,3) == 'asc') {
|
||||
var i = by.substring(3);
|
||||
comp = function(a, b) { return a[i] - b[i]; };
|
||||
} else {
|
||||
// Otherwise sort in descending order.
|
||||
comp = function(a, b) { return b[by] - a[by]; };
|
||||
}
|
||||
|
||||
// Reset link styles and format the selected sort option.
|
||||
$('a.sel').attr('href', '#').removeClass('sel');
|
||||
$('a.by' + by).removeAttr('href').addClass('sel');
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a comp function. If the user has preferences stored in
|
||||
* the sortBy cookie, use those, otherwise use the default.
|
||||
*/
|
||||
function initComparator() {
|
||||
by = 'rating'; // Default to sort by rating.
|
||||
// If the sortBy cookie is set, use that instead.
|
||||
if (document.cookie.length > 0) {
|
||||
var start = document.cookie.indexOf('sortBy=');
|
||||
if (start != -1) {
|
||||
start = start + 7;
|
||||
var end = document.cookie.indexOf(";", start);
|
||||
if (end == -1) {
|
||||
end = document.cookie.length;
|
||||
by = unescape(document.cookie.substring(start, end));
|
||||
}
|
||||
}
|
||||
}
|
||||
setComparator();
|
||||
}
|
||||
|
||||
/**
|
||||
* Show a comment div.
|
||||
*/
|
||||
function show(id) {
|
||||
$('#ao' + id).hide();
|
||||
$('#ah' + id).show();
|
||||
var context = $.extend({id: id}, opts);
|
||||
var popup = $(renderTemplate(popupTemplate, context)).hide();
|
||||
popup.find('textarea[name="proposal"]').hide();
|
||||
popup.find('a.by' + by).addClass('sel');
|
||||
var form = popup.find('#cf' + id);
|
||||
form.submit(function(event) {
|
||||
event.preventDefault();
|
||||
addComment(form);
|
||||
});
|
||||
$('#s' + id).after(popup);
|
||||
popup.slideDown('fast', function() {
|
||||
getComments(id);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Hide a comment div.
|
||||
*/
|
||||
function hide(id) {
|
||||
$('#ah' + id).hide();
|
||||
$('#ao' + id).show();
|
||||
var div = $('#sc' + id);
|
||||
div.slideUp('fast', function() {
|
||||
div.remove();
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Perform an ajax request to get comments for a node
|
||||
* and insert the comments into the comments tree.
|
||||
*/
|
||||
function getComments(id) {
|
||||
$.ajax({
|
||||
type: 'GET',
|
||||
url: opts.getCommentsURL,
|
||||
data: {node: id},
|
||||
success: function(data, textStatus, request) {
|
||||
var ul = $('#cl' + id);
|
||||
var speed = 100;
|
||||
$('#cf' + id)
|
||||
.find('textarea[name="proposal"]')
|
||||
.data('source', data.source);
|
||||
|
||||
if (data.comments.length === 0) {
|
||||
ul.html('<li>No comments yet.</li>');
|
||||
ul.data('empty', true);
|
||||
} else {
|
||||
// If there are comments, sort them and put them in the list.
|
||||
var comments = sortComments(data.comments);
|
||||
speed = data.comments.length * 100;
|
||||
appendComments(comments, ul);
|
||||
ul.data('empty', false);
|
||||
}
|
||||
$('#cn' + id).slideUp(speed + 200);
|
||||
ul.slideDown(speed);
|
||||
},
|
||||
error: function(request, textStatus, error) {
|
||||
showError('Oops, there was a problem retrieving the comments.');
|
||||
},
|
||||
dataType: 'json'
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Add a comment via ajax and insert the comment into the comment tree.
|
||||
*/
|
||||
function addComment(form) {
|
||||
var node_id = form.find('input[name="node"]').val();
|
||||
var parent_id = form.find('input[name="parent"]').val();
|
||||
var text = form.find('textarea[name="comment"]').val();
|
||||
var proposal = form.find('textarea[name="proposal"]').val();
|
||||
|
||||
if (text == '') {
|
||||
showError('Please enter a comment.');
|
||||
return;
|
||||
}
|
||||
|
||||
// Disable the form that is being submitted.
|
||||
form.find('textarea,input').attr('disabled', 'disabled');
|
||||
|
||||
// Send the comment to the server.
|
||||
$.ajax({
|
||||
type: "POST",
|
||||
url: opts.addCommentURL,
|
||||
dataType: 'json',
|
||||
data: {
|
||||
node: node_id,
|
||||
parent: parent_id,
|
||||
text: text,
|
||||
proposal: proposal
|
||||
},
|
||||
success: function(data, textStatus, error) {
|
||||
// Reset the form.
|
||||
if (node_id) {
|
||||
hideProposeChange(node_id);
|
||||
}
|
||||
form.find('textarea')
|
||||
.val('')
|
||||
.add(form.find('input'))
|
||||
.removeAttr('disabled');
|
||||
var ul = $('#cl' + (node_id || parent_id));
|
||||
if (ul.data('empty')) {
|
||||
$(ul).empty();
|
||||
ul.data('empty', false);
|
||||
}
|
||||
insertComment(data.comment);
|
||||
var ao = $('#ao' + node_id);
|
||||
ao.find('img').attr({'src': opts.commentBrightImage});
|
||||
if (node_id) {
|
||||
// if this was a "root" comment, remove the commenting box
|
||||
// (the user can get it back by reopening the comment popup)
|
||||
$('#ca' + node_id).slideUp();
|
||||
}
|
||||
},
|
||||
error: function(request, textStatus, error) {
|
||||
form.find('textarea,input').removeAttr('disabled');
|
||||
showError('Oops, there was a problem adding the comment.');
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Recursively append comments to the main comment list and children
|
||||
* lists, creating the comment tree.
|
||||
*/
|
||||
function appendComments(comments, ul) {
|
||||
$.each(comments, function() {
|
||||
var div = createCommentDiv(this);
|
||||
ul.append($(document.createElement('li')).html(div));
|
||||
appendComments(this.children, div.find('ul.comment-children'));
|
||||
// To avoid stagnating data, don't store the comments children in data.
|
||||
this.children = null;
|
||||
div.data('comment', this);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* After adding a new comment, it must be inserted in the correct
|
||||
* location in the comment tree.
|
||||
*/
|
||||
function insertComment(comment) {
|
||||
var div = createCommentDiv(comment);
|
||||
|
||||
// To avoid stagnating data, don't store the comments children in data.
|
||||
comment.children = null;
|
||||
div.data('comment', comment);
|
||||
|
||||
var ul = $('#cl' + (comment.node || comment.parent));
|
||||
var siblings = getChildren(ul);
|
||||
|
||||
var li = $(document.createElement('li'));
|
||||
li.hide();
|
||||
|
||||
// Determine where in the parents children list to insert this comment.
|
||||
for(i=0; i < siblings.length; i++) {
|
||||
if (comp(comment, siblings[i]) <= 0) {
|
||||
$('#cd' + siblings[i].id)
|
||||
.parent()
|
||||
.before(li.html(div));
|
||||
li.slideDown('fast');
|
||||
return;
|
||||
}
|
||||
}
|
||||
|
||||
// If we get here, this comment rates lower than all the others,
|
||||
// or it is the only comment in the list.
|
||||
ul.append(li.html(div));
|
||||
li.slideDown('fast');
|
||||
}
|
||||
|
||||
function acceptComment(id) {
|
||||
$.ajax({
|
||||
type: 'POST',
|
||||
url: opts.acceptCommentURL,
|
||||
data: {id: id},
|
||||
success: function(data, textStatus, request) {
|
||||
$('#cm' + id).fadeOut('fast');
|
||||
$('#cd' + id).removeClass('moderate');
|
||||
},
|
||||
error: function(request, textStatus, error) {
|
||||
showError('Oops, there was a problem accepting the comment.');
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
function deleteComment(id) {
|
||||
$.ajax({
|
||||
type: 'POST',
|
||||
url: opts.deleteCommentURL,
|
||||
data: {id: id},
|
||||
success: function(data, textStatus, request) {
|
||||
var div = $('#cd' + id);
|
||||
if (data == 'delete') {
|
||||
// Moderator mode: remove the comment and all children immediately
|
||||
div.slideUp('fast', function() {
|
||||
div.remove();
|
||||
});
|
||||
return;
|
||||
}
|
||||
// User mode: only mark the comment as deleted
|
||||
div
|
||||
.find('span.user-id:first')
|
||||
.text('[deleted]').end()
|
||||
.find('div.comment-text:first')
|
||||
.text('[deleted]').end()
|
||||
.find('#cm' + id + ', #dc' + id + ', #ac' + id + ', #rc' + id +
|
||||
', #sp' + id + ', #hp' + id + ', #cr' + id + ', #rl' + id)
|
||||
.remove();
|
||||
var comment = div.data('comment');
|
||||
comment.username = '[deleted]';
|
||||
comment.text = '[deleted]';
|
||||
div.data('comment', comment);
|
||||
},
|
||||
error: function(request, textStatus, error) {
|
||||
showError('Oops, there was a problem deleting the comment.');
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
function showProposal(id) {
|
||||
$('#sp' + id).hide();
|
||||
$('#hp' + id).show();
|
||||
$('#pr' + id).slideDown('fast');
|
||||
}
|
||||
|
||||
function hideProposal(id) {
|
||||
$('#hp' + id).hide();
|
||||
$('#sp' + id).show();
|
||||
$('#pr' + id).slideUp('fast');
|
||||
}
|
||||
|
||||
function showProposeChange(id) {
|
||||
$('#pc' + id).hide();
|
||||
$('#hc' + id).show();
|
||||
var textarea = $('#pt' + id);
|
||||
textarea.val(textarea.data('source'));
|
||||
$.fn.autogrow.resize(textarea[0]);
|
||||
textarea.slideDown('fast');
|
||||
}
|
||||
|
||||
function hideProposeChange(id) {
|
||||
$('#hc' + id).hide();
|
||||
$('#pc' + id).show();
|
||||
var textarea = $('#pt' + id);
|
||||
textarea.val('').removeAttr('disabled');
|
||||
textarea.slideUp('fast');
|
||||
}
|
||||
|
||||
function toggleCommentMarkupBox(id) {
|
||||
$('#mb' + id).toggle();
|
||||
}
|
||||
|
||||
/** Handle when the user clicks on a sort by link. */
|
||||
function handleReSort(link) {
|
||||
var classes = link.attr('class').split(/\s+/);
|
||||
for (var i=0; i<classes.length; i++) {
|
||||
if (classes[i] != 'sort-option') {
|
||||
by = classes[i].substring(2);
|
||||
}
|
||||
}
|
||||
setComparator();
|
||||
// Save/update the sortBy cookie.
|
||||
var expiration = new Date();
|
||||
expiration.setDate(expiration.getDate() + 365);
|
||||
document.cookie= 'sortBy=' + escape(by) +
|
||||
';expires=' + expiration.toUTCString();
|
||||
$('ul.comment-ul').each(function(index, ul) {
|
||||
var comments = getChildren($(ul), true);
|
||||
comments = sortComments(comments);
|
||||
appendComments(comments, $(ul).empty());
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Function to process a vote when a user clicks an arrow.
|
||||
*/
|
||||
function handleVote(link) {
|
||||
if (!opts.voting) {
|
||||
showError("You'll need to login to vote.");
|
||||
return;
|
||||
}
|
||||
|
||||
var id = link.attr('id');
|
||||
if (!id) {
|
||||
// Didn't click on one of the voting arrows.
|
||||
return;
|
||||
}
|
||||
// If it is an unvote, the new vote value is 0,
|
||||
// Otherwise it's 1 for an upvote, or -1 for a downvote.
|
||||
var value = 0;
|
||||
if (id.charAt(1) != 'u') {
|
||||
value = id.charAt(0) == 'u' ? 1 : -1;
|
||||
}
|
||||
// The data to be sent to the server.
|
||||
var d = {
|
||||
comment_id: id.substring(2),
|
||||
value: value
|
||||
};
|
||||
|
||||
// Swap the vote and unvote links.
|
||||
link.hide();
|
||||
$('#' + id.charAt(0) + (id.charAt(1) == 'u' ? 'v' : 'u') + d.comment_id)
|
||||
.show();
|
||||
|
||||
// The div the comment is displayed in.
|
||||
var div = $('div#cd' + d.comment_id);
|
||||
var data = div.data('comment');
|
||||
|
||||
// If this is not an unvote, and the other vote arrow has
|
||||
// already been pressed, unpress it.
|
||||
if ((d.value !== 0) && (data.vote === d.value * -1)) {
|
||||
$('#' + (d.value == 1 ? 'd' : 'u') + 'u' + d.comment_id).hide();
|
||||
$('#' + (d.value == 1 ? 'd' : 'u') + 'v' + d.comment_id).show();
|
||||
}
|
||||
|
||||
// Update the comments rating in the local data.
|
||||
data.rating += (data.vote === 0) ? d.value : (d.value - data.vote);
|
||||
data.vote = d.value;
|
||||
div.data('comment', data);
|
||||
|
||||
// Change the rating text.
|
||||
div.find('.rating:first')
|
||||
.text(data.rating + ' point' + (data.rating == 1 ? '' : 's'));
|
||||
|
||||
// Send the vote information to the server.
|
||||
$.ajax({
|
||||
type: "POST",
|
||||
url: opts.processVoteURL,
|
||||
data: d,
|
||||
error: function(request, textStatus, error) {
|
||||
showError('Oops, there was a problem casting that vote.');
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Open a reply form used to reply to an existing comment.
|
||||
*/
|
||||
function openReply(id) {
|
||||
// Swap out the reply link for the hide link
|
||||
$('#rl' + id).hide();
|
||||
$('#cr' + id).show();
|
||||
|
||||
// Add the reply li to the children ul.
|
||||
var div = $(renderTemplate(replyTemplate, {id: id})).hide();
|
||||
$('#cl' + id)
|
||||
.prepend(div)
|
||||
// Setup the submit handler for the reply form.
|
||||
.find('#rf' + id)
|
||||
.submit(function(event) {
|
||||
event.preventDefault();
|
||||
addComment($('#rf' + id));
|
||||
closeReply(id);
|
||||
})
|
||||
.find('input[type=button]')
|
||||
.click(function() {
|
||||
closeReply(id);
|
||||
});
|
||||
div.slideDown('fast', function() {
|
||||
$('#rf' + id).find('textarea').focus();
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Close the reply form opened with openReply.
|
||||
*/
|
||||
function closeReply(id) {
|
||||
// Remove the reply div from the DOM.
|
||||
$('#rd' + id).slideUp('fast', function() {
|
||||
$(this).remove();
|
||||
});
|
||||
|
||||
// Swap out the hide link for the reply link
|
||||
$('#cr' + id).hide();
|
||||
$('#rl' + id).show();
|
||||
}
|
||||
|
||||
/**
|
||||
* Recursively sort a tree of comments using the comp comparator.
|
||||
*/
|
||||
function sortComments(comments) {
|
||||
comments.sort(comp);
|
||||
$.each(comments, function() {
|
||||
this.children = sortComments(this.children);
|
||||
});
|
||||
return comments;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the children comments from a ul. If recursive is true,
|
||||
* recursively include childrens' children.
|
||||
*/
|
||||
function getChildren(ul, recursive) {
|
||||
var children = [];
|
||||
ul.children().children("[id^='cd']")
|
||||
.each(function() {
|
||||
var comment = $(this).data('comment');
|
||||
if (recursive)
|
||||
comment.children = getChildren($(this).find('#cl' + comment.id), true);
|
||||
children.push(comment);
|
||||
});
|
||||
return children;
|
||||
}
|
||||
|
||||
/** Create a div to display a comment in. */
|
||||
function createCommentDiv(comment) {
|
||||
if (!comment.displayed && !opts.moderator) {
|
||||
return $('<div class="moderate">Thank you! Your comment will show up '
|
||||
+ 'once it is has been approved by a moderator.</div>');
|
||||
}
|
||||
// Prettify the comment rating.
|
||||
comment.pretty_rating = comment.rating + ' point' +
|
||||
(comment.rating == 1 ? '' : 's');
|
||||
// Make a class (for displaying not yet moderated comments differently)
|
||||
comment.css_class = comment.displayed ? '' : ' moderate';
|
||||
// Create a div for this comment.
|
||||
var context = $.extend({}, opts, comment);
|
||||
var div = $(renderTemplate(commentTemplate, context));
|
||||
|
||||
// If the user has voted on this comment, highlight the correct arrow.
|
||||
if (comment.vote) {
|
||||
var direction = (comment.vote == 1) ? 'u' : 'd';
|
||||
div.find('#' + direction + 'v' + comment.id).hide();
|
||||
div.find('#' + direction + 'u' + comment.id).show();
|
||||
}
|
||||
|
||||
if (opts.moderator || comment.text != '[deleted]') {
|
||||
div.find('a.reply').show();
|
||||
if (comment.proposal_diff)
|
||||
div.find('#sp' + comment.id).show();
|
||||
if (opts.moderator && !comment.displayed)
|
||||
div.find('#cm' + comment.id).show();
|
||||
if (opts.moderator || (opts.username == comment.username))
|
||||
div.find('#dc' + comment.id).show();
|
||||
}
|
||||
return div;
|
||||
}
|
||||
|
||||
/**
|
||||
* A simple template renderer. Placeholders such as <%id%> are replaced
|
||||
* by context['id'] with items being escaped. Placeholders such as <#id#>
|
||||
* are not escaped.
|
||||
*/
|
||||
function renderTemplate(template, context) {
|
||||
var esc = $(document.createElement('div'));
|
||||
|
||||
function handle(ph, escape) {
|
||||
var cur = context;
|
||||
$.each(ph.split('.'), function() {
|
||||
cur = cur[this];
|
||||
});
|
||||
return escape ? esc.text(cur || "").html() : cur;
|
||||
}
|
||||
|
||||
return template.replace(/<([%#])([\w\.]*)\1>/g, function() {
|
||||
return handle(arguments[2], arguments[1] == '%' ? true : false);
|
||||
});
|
||||
}
|
||||
|
||||
/** Flash an error message briefly. */
|
||||
function showError(message) {
|
||||
$(document.createElement('div')).attr({'class': 'popup-error'})
|
||||
.append($(document.createElement('div'))
|
||||
.attr({'class': 'error-message'}).text(message))
|
||||
.appendTo('body')
|
||||
.fadeIn("slow")
|
||||
.delay(2000)
|
||||
.fadeOut("slow");
|
||||
}
|
||||
|
||||
/** Add a link the user uses to open the comments popup. */
|
||||
$.fn.comment = function() {
|
||||
return this.each(function() {
|
||||
var id = $(this).attr('id').substring(1);
|
||||
var count = COMMENT_METADATA[id];
|
||||
var title = count + ' comment' + (count == 1 ? '' : 's');
|
||||
var image = count > 0 ? opts.commentBrightImage : opts.commentImage;
|
||||
var addcls = count == 0 ? ' nocomment' : '';
|
||||
$(this)
|
||||
.append(
|
||||
$(document.createElement('a')).attr({
|
||||
href: '#',
|
||||
'class': 'sphinx-comment-open' + addcls,
|
||||
id: 'ao' + id
|
||||
})
|
||||
.append($(document.createElement('img')).attr({
|
||||
src: image,
|
||||
alt: 'comment',
|
||||
title: title
|
||||
}))
|
||||
.click(function(event) {
|
||||
event.preventDefault();
|
||||
show($(this).attr('id').substring(2));
|
||||
})
|
||||
)
|
||||
.append(
|
||||
$(document.createElement('a')).attr({
|
||||
href: '#',
|
||||
'class': 'sphinx-comment-close hidden',
|
||||
id: 'ah' + id
|
||||
})
|
||||
.append($(document.createElement('img')).attr({
|
||||
src: opts.closeCommentImage,
|
||||
alt: 'close',
|
||||
title: 'close'
|
||||
}))
|
||||
.click(function(event) {
|
||||
event.preventDefault();
|
||||
hide($(this).attr('id').substring(2));
|
||||
})
|
||||
);
|
||||
});
|
||||
};
|
||||
|
||||
var opts = {
|
||||
processVoteURL: '/_process_vote',
|
||||
addCommentURL: '/_add_comment',
|
||||
getCommentsURL: '/_get_comments',
|
||||
acceptCommentURL: '/_accept_comment',
|
||||
deleteCommentURL: '/_delete_comment',
|
||||
commentImage: '/static/_static/comment.png',
|
||||
closeCommentImage: '/static/_static/comment-close.png',
|
||||
loadingImage: '/static/_static/ajax-loader.gif',
|
||||
commentBrightImage: '/static/_static/comment-bright.png',
|
||||
upArrow: '/static/_static/up.png',
|
||||
downArrow: '/static/_static/down.png',
|
||||
upArrowPressed: '/static/_static/up-pressed.png',
|
||||
downArrowPressed: '/static/_static/down-pressed.png',
|
||||
voting: false,
|
||||
moderator: false
|
||||
};
|
||||
|
||||
if (typeof COMMENT_OPTIONS != "undefined") {
|
||||
opts = jQuery.extend(opts, COMMENT_OPTIONS);
|
||||
}
|
||||
|
||||
var popupTemplate = '\
|
||||
<div class="sphinx-comments" id="sc<%id%>">\
|
||||
<p class="sort-options">\
|
||||
Sort by:\
|
||||
<a href="#" class="sort-option byrating">best rated</a>\
|
||||
<a href="#" class="sort-option byascage">newest</a>\
|
||||
<a href="#" class="sort-option byage">oldest</a>\
|
||||
</p>\
|
||||
<div class="comment-header">Comments</div>\
|
||||
<div class="comment-loading" id="cn<%id%>">\
|
||||
loading comments... <img src="<%loadingImage%>" alt="" /></div>\
|
||||
<ul id="cl<%id%>" class="comment-ul"></ul>\
|
||||
<div id="ca<%id%>">\
|
||||
<p class="add-a-comment">Add a comment\
|
||||
(<a href="#" class="comment-markup" id="ab<%id%>">markup</a>):</p>\
|
||||
<div class="comment-markup-box" id="mb<%id%>">\
|
||||
reStructured text markup: <i>*emph*</i>, <b>**strong**</b>, \
|
||||
<tt>``code``</tt>, \
|
||||
code blocks: <tt>::</tt> and an indented block after blank line</div>\
|
||||
<form method="post" id="cf<%id%>" class="comment-form" action="">\
|
||||
<textarea name="comment" cols="80"></textarea>\
|
||||
<p class="propose-button">\
|
||||
<a href="#" id="pc<%id%>" class="show-propose-change">\
|
||||
Propose a change ▹\
|
||||
</a>\
|
||||
<a href="#" id="hc<%id%>" class="hide-propose-change">\
|
||||
Propose a change ▿\
|
||||
</a>\
|
||||
</p>\
|
||||
<textarea name="proposal" id="pt<%id%>" cols="80"\
|
||||
spellcheck="false"></textarea>\
|
||||
<input type="submit" value="Add comment" />\
|
||||
<input type="hidden" name="node" value="<%id%>" />\
|
||||
<input type="hidden" name="parent" value="" />\
|
||||
</form>\
|
||||
</div>\
|
||||
</div>';
|
||||
|
||||
var commentTemplate = '\
|
||||
<div id="cd<%id%>" class="sphinx-comment<%css_class%>">\
|
||||
<div class="vote">\
|
||||
<div class="arrow">\
|
||||
<a href="#" id="uv<%id%>" class="vote" title="vote up">\
|
||||
<img src="<%upArrow%>" />\
|
||||
</a>\
|
||||
<a href="#" id="uu<%id%>" class="un vote" title="vote up">\
|
||||
<img src="<%upArrowPressed%>" />\
|
||||
</a>\
|
||||
</div>\
|
||||
<div class="arrow">\
|
||||
<a href="#" id="dv<%id%>" class="vote" title="vote down">\
|
||||
<img src="<%downArrow%>" id="da<%id%>" />\
|
||||
</a>\
|
||||
<a href="#" id="du<%id%>" class="un vote" title="vote down">\
|
||||
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|
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|
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<li><a class="reference internal" href="#binary-ufunc" id="id1">binary_ufunc</a><ul>
|
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|
||||
<li><a class="reference internal" href="#constructors" id="id3">constructors</a></li>
|
||||
<li><a class="reference internal" href="#accessors" id="id4">accessors</a></li>
|
||||
<li><a class="reference internal" href="#example-s" id="id5">Example(s)</a></li>
|
||||
</ul>
|
||||
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|
||||
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|
||||
</div>
|
||||
<p>A <tt class="docutils literal"><span class="pre">binary_ufunc</span></tt> is a struct used as an intermediate step to broadcast two arguments so that a C++ function can be converted to a ufunc like function</p>
|
||||
<blockquote>
|
||||
<div><tt class="docutils literal"><span class="pre"><boost/python/numpy/ufunc.hpp></span></tt> contains the <tt class="docutils literal"><span class="pre">binary_ufunc</span></tt> structure definitions</div></blockquote>
|
||||
<div class="section" id="synopsis">
|
||||
<h2><a class="toc-backref" href="#id2">synopsis</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">namespace</span> <span class="n">boost</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">namespace</span> <span class="n">python</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">namespace</span> <span class="n">numpy</span>
|
||||
<span class="p">{</span>
|
||||
|
||||
<span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TArgument1</span><span class="o">=</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="o">::</span><span class="n">first_argument_type</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TArgument2</span><span class="o">=</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="o">::</span><span class="n">second_argument_type</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TResult</span><span class="o">=</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="o">::</span><span class="n">result_type</span><span class="o">></span>
|
||||
|
||||
<span class="k">struct</span> <span class="n">binary_ufunc</span>
|
||||
<span class="p">{</span>
|
||||
|
||||
<span class="k">static</span> <span class="n">object</span> <span class="n">call</span><span class="p">(</span><span class="n">TBinaryFunctor</span> <span class="o">&</span> <span class="n">self</span><span class="p">,</span>
|
||||
<span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">input1</span><span class="p">,</span>
|
||||
<span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">input2</span><span class="p">,</span>
|
||||
<span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">output</span><span class="p">);</span>
|
||||
|
||||
<span class="k">static</span> <span class="n">object</span> <span class="nf">make</span><span class="p">();</span>
|
||||
<span class="p">};</span>
|
||||
|
||||
<span class="p">}</span>
|
||||
<span class="p">}</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section" id="constructors">
|
||||
<h2><a class="toc-backref" href="#id3">constructors</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">struct</span> <span class="n">example_binary_ufunc</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">typedef</span> <span class="n">any_valid</span> <span class="n">first_argument_type</span><span class="p">;</span>
|
||||
<span class="k">typedef</span> <span class="n">any_valid</span> <span class="n">second_argument_type</span><span class="p">;</span>
|
||||
<span class="k">typedef</span> <span class="n">any_valid</span> <span class="n">result_type</span><span class="p">;</span>
|
||||
<span class="p">};</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body">The <tt class="docutils literal"><span class="pre">any_valid</span></tt> type must be defined using typedef as a valid C++ type in order to use the struct methods correctly</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Note:</th><td class="field-body">The struct must be exposed as a Python class, and an instance of the class must be created to use the <tt class="docutils literal"><span class="pre">call</span></tt> method corresponding to the <tt class="docutils literal"><span class="pre">__call__</span></tt> attribute of the Python object</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
<div class="section" id="accessors">
|
||||
<h2><a class="toc-backref" href="#id4">accessors</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TArgument1</span><span class="o">=</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="o">::</span><span class="n">first_argument_type</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TArgument2</span><span class="o">=</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="o">::</span><span class="n">second_argument_type</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TResult</span><span class="o">=</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="o">::</span><span class="n">result_type</span><span class="o">></span>
|
||||
<span class="k">static</span> <span class="n">object</span> <span class="n">call</span><span class="p">(</span><span class="n">TBinaryFunctor</span> <span class="o">&</span> <span class="n">self</span><span class="p">,</span>
|
||||
<span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">input</span><span class="p">,</span>
|
||||
<span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">output</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requires:</th><td class="field-body">Typenames <tt class="docutils literal"><span class="pre">TBinaryFunctor</span></tt> and optionally <tt class="docutils literal"><span class="pre">TArgument1</span></tt> and <tt class="docutils literal"><span class="pre">TArgument2</span></tt> for argument type and <tt class="docutils literal"><span class="pre">TResult</span></tt> for result type</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Effects:</th><td class="field-body">Passes a Python object to the underlying C++ functor after broadcasting its arguments</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TArgument1</span><span class="o">=</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="o">::</span><span class="n">first_argument_type</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TArgument2</span><span class="o">=</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="o">::</span><span class="n">second_argument_type</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TResult</span><span class="o">=</span><span class="k">typename</span> <span class="n">TBinaryFunctor</span><span class="o">::</span><span class="n">result_type</span><span class="o">></span>
|
||||
<span class="k">static</span> <span class="n">object</span> <span class="n">make</span><span class="p">();</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requires:</th><td class="field-body">Typenames <tt class="docutils literal"><span class="pre">TBinaryFunctor</span></tt> and optionally <tt class="docutils literal"><span class="pre">TArgument1</span></tt> and <tt class="docutils literal"><span class="pre">TArgument2</span></tt> for argument type and <tt class="docutils literal"><span class="pre">TResult</span></tt> for result type</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">A Python function object to call the overloaded () operator in the struct (in typical usage)</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
<div class="section" id="example-s">
|
||||
<h2><a class="toc-backref" href="#id5">Example(s)</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">namespace</span> <span class="n">p</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="p">;</span>
|
||||
<span class="k">namespace</span> <span class="n">np</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="o">::</span><span class="n">numpy</span><span class="p">;</span>
|
||||
|
||||
<span class="k">struct</span> <span class="n">BinarySquare</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">typedef</span> <span class="kt">double</span> <span class="n">first_argument_type</span><span class="p">;</span>
|
||||
<span class="k">typedef</span> <span class="kt">double</span> <span class="n">second_argument_type</span><span class="p">;</span>
|
||||
<span class="k">typedef</span> <span class="kt">double</span> <span class="n">result_type</span><span class="p">;</span>
|
||||
|
||||
<span class="kt">double</span> <span class="nf">operator</span><span class="p">()(</span><span class="kt">double</span> <span class="n">a</span><span class="p">,</span><span class="kt">double</span> <span class="n">b</span><span class="p">)</span> <span class="k">const</span> <span class="p">{</span> <span class="k">return</span> <span class="p">(</span><span class="n">a</span><span class="o">*</span><span class="n">a</span> <span class="o">+</span> <span class="n">b</span><span class="o">*</span><span class="n">b</span><span class="p">)</span> <span class="p">;</span> <span class="p">}</span>
|
||||
<span class="p">};</span>
|
||||
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">object</span> <span class="n">ud</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">class_</span><span class="o"><</span><span class="n">BinarySquare</span><span class="p">,</span> <span class="n">boost</span><span class="o">::</span><span class="n">shared_ptr</span><span class="o"><</span><span class="n">BinarySquare</span><span class="o">></span> <span class="o">></span><span class="p">(</span><span class="s">"BinarySquare"</span><span class="p">).</span><span class="n">def</span><span class="p">(</span><span class="s">"__call__"</span><span class="p">,</span> <span class="n">np</span><span class="o">::</span><span class="n">binary_ufunc</span><span class="o"><</span><span class="n">BinarySquare</span><span class="o">>::</span><span class="n">make</span><span class="p">());</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">object</span> <span class="n">inst</span> <span class="o">=</span> <span class="n">ud</span><span class="p">();</span>
|
||||
<span class="n">result_array</span> <span class="o">=</span> <span class="n">inst</span><span class="p">.</span><span class="n">attr</span><span class="p">(</span><span class="s">"__call__"</span><span class="p">)(</span><span class="n">demo_array</span><span class="p">,</span><span class="n">demo_array</span><span class="p">)</span> <span class="p">;</span>
|
||||
<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Square of list with binary ufunc is "</span> <span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span> <span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*</span> <span class="o">></span> <span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">result_array</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span> <span class="p">;</span>
|
||||
</pre></div>
|
||||
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|
||||
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|
||||
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|
||||
|
||||
|
||||
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|
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195
doc/html/numpy/reference/dtype.html
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Normal file
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|
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|
||||
<h1 align="center"><a href="../index.html">(NumPy)</a></h1>
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||||
<div class="section" id="dtype">
|
||||
<h1><a class="toc-backref" href="#id2">dtype</a></h1>
|
||||
<div class="contents topic" id="table-of-contents">
|
||||
<p class="topic-title first">Table of Contents</p>
|
||||
<ul class="simple">
|
||||
<li><a class="reference internal" href="#dtype" id="id2">dtype</a><ul>
|
||||
<li><a class="reference internal" href="#synopsis" id="id3">synopsis</a></li>
|
||||
<li><a class="reference internal" href="#constructors" id="id4">constructors</a></li>
|
||||
<li><a class="reference internal" href="#accessors" id="id5">accessors</a></li>
|
||||
<li><a class="reference internal" href="#example-s" id="id6">Example(s)</a></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<p>A <a class="reference external" href="http://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html#data-type-objects-dtype">dtype</a> is an object describing the type of the elements of an ndarray</p>
|
||||
<blockquote>
|
||||
<div><tt class="docutils literal"><span class="pre"><boost/python/numpy/dtype.hpp></span></tt> contains the method calls necessary to generate a python object equivalent to a numpy.dtype from builtin C++ objects, as well as to create custom dtypes from user defined types</div></blockquote>
|
||||
<div class="section" id="synopsis">
|
||||
<h2><a class="toc-backref" href="#id3">synopsis</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">namespace</span> <span class="n">boost</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">namespace</span> <span class="n">python</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">namespace</span> <span class="n">numpy</span>
|
||||
<span class="p">{</span>
|
||||
|
||||
<span class="k">class</span> <span class="nc">dtype</span> <span class="o">:</span> <span class="k">public</span> <span class="n">object</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">static</span> <span class="n">python</span><span class="o">::</span><span class="n">detail</span><span class="o">::</span><span class="n">new_reference</span> <span class="n">convert</span><span class="p">(</span><span class="n">object</span><span class="o">::</span><span class="n">object_cref</span> <span class="n">arg</span><span class="p">,</span> <span class="kt">bool</span> <span class="n">align</span><span class="p">);</span>
|
||||
<span class="nl">public:</span>
|
||||
|
||||
<span class="c1">// Convert an arbitrary Python object to a data-type descriptor object.</span>
|
||||
<span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">T</span><span class="o">></span>
|
||||
<span class="k">explicit</span> <span class="n">dtype</span><span class="p">(</span><span class="n">T</span> <span class="n">arg</span><span class="p">,</span> <span class="kt">bool</span> <span class="n">align</span><span class="o">=</span><span class="nb">false</span><span class="p">);</span>
|
||||
|
||||
<span class="c1">// Get the built-in numpy dtype associated with the given scalar template type.</span>
|
||||
<span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">T</span><span class="o">></span> <span class="k">static</span> <span class="n">dtype</span> <span class="n">get_builtin</span><span class="p">();</span>
|
||||
|
||||
<span class="c1">// Return the size of the data type in bytes.</span>
|
||||
<span class="kt">int</span> <span class="n">get_itemsize</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="p">};</span>
|
||||
|
||||
<span class="p">}</span>
|
||||
<span class="p">}</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section" id="constructors">
|
||||
<h2><a class="toc-backref" href="#id4">constructors</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">T</span><span class="o">></span>
|
||||
<span class="k">explicit</span> <span class="n">dtype</span><span class="p">(</span><span class="n">T</span> <span class="n">arg</span><span class="p">,</span> <span class="kt">bool</span> <span class="n">align</span><span class="o">=</span><span class="nb">false</span><span class="p">)</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body"><p class="first"><tt class="docutils literal"><span class="pre">T</span></tt> must be either :</p>
|
||||
<ul class="simple">
|
||||
<li>a built-in C++ typename convertible to object</li>
|
||||
<li>a valid python object or convertible to object</li>
|
||||
</ul>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Effects:</th><td class="field-body"><p class="first">Constructs an object from the supplied python object / convertible
|
||||
to object / builtin C++ data type</p>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-odd field"><th class="field-name">Throws:</th><td class="field-body"><p class="first last">Nothing</p>
|
||||
</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">T</span><span class="o">></span> <span class="k">static</span> <span class="n">dtype</span> <span class="n">get_builtin</span><span class="p">();</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body">The typename supplied, <tt class="docutils literal"><span class="pre">T</span></tt> must be a builtin C++ type also supported by numpy</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">Numpy dtype corresponding to builtin C++ type</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
<div class="section" id="accessors">
|
||||
<h2><a class="toc-backref" href="#id5">accessors</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">int</span> <span class="n">get_itemsize</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
<div class="section" id="example-s">
|
||||
<h2><a class="toc-backref" href="#id6">Example(s)</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">namespace</span> <span class="n">p</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="p">;</span>
|
||||
<span class="k">namespace</span> <span class="n">np</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="o">::</span><span class="n">numpy</span><span class="p">;</span>
|
||||
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">dtype</span> <span class="n">dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="o">::</span><span class="n">get_builtin</span><span class="o"><</span><span class="kt">double</span><span class="o">></span><span class="p">();</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">tuple</span> <span class="n">for_custom_dtype</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="s">"ha"</span><span class="p">,</span><span class="n">dtype</span><span class="p">);</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">dtype</span> <span class="n">custom_dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="p">(</span><span class="n">list_for_dtype</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
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|
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|
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|
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211
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<div class="section" id="multi-iter">
|
||||
<h1><a class="toc-backref" href="#id1">multi_iter</a></h1>
|
||||
<div class="contents topic" id="table-of-contents">
|
||||
<p class="topic-title first">Table of Contents</p>
|
||||
<ul class="simple">
|
||||
<li><a class="reference internal" href="#multi-iter" id="id1">multi_iter</a><ul>
|
||||
<li><a class="reference internal" href="#synopsis" id="id2">synopsis</a></li>
|
||||
<li><a class="reference internal" href="#constructors" id="id3">constructors</a></li>
|
||||
<li><a class="reference internal" href="#accessors" id="id4">accessors</a></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<p>A <tt class="docutils literal"><span class="pre">multi_iter</span></tt> is a Python object, intended to be used as an iterator It should generally only be used in loops.</p>
|
||||
<blockquote>
|
||||
<div><tt class="docutils literal"><span class="pre"><boost/python/numpy/ufunc.hpp></span></tt> contains the class definitions for <tt class="docutils literal"><span class="pre">multi_iter</span></tt></div></blockquote>
|
||||
<div class="section" id="synopsis">
|
||||
<h2><a class="toc-backref" href="#id2">synopsis</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">namespace</span> <span class="n">boost</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">namespace</span> <span class="n">python</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">namespace</span> <span class="n">numpy</span>
|
||||
<span class="p">{</span>
|
||||
|
||||
<span class="k">class</span> <span class="nc">multi_iter</span> <span class="o">:</span> <span class="k">public</span> <span class="n">object</span>
|
||||
<span class="p">{</span>
|
||||
<span class="nl">public:</span>
|
||||
<span class="kt">void</span> <span class="n">next</span><span class="p">();</span>
|
||||
<span class="kt">bool</span> <span class="n">not_done</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="kt">char</span> <span class="o">*</span> <span class="n">get_data</span><span class="p">(</span><span class="kt">int</span> <span class="n">n</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="kt">int</span> <span class="k">const</span> <span class="n">get_nd</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="o">*</span> <span class="n">get_shape</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="n">shape</span><span class="p">(</span><span class="kt">int</span> <span class="n">n</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="p">};</span>
|
||||
|
||||
|
||||
<span class="n">multi_iter</span> <span class="nf">make_multi_iter</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a1</span><span class="p">);</span>
|
||||
<span class="n">multi_iter</span> <span class="nf">make_multi_iter</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a1</span><span class="p">,</span> <span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a2</span><span class="p">);</span>
|
||||
<span class="n">multi_iter</span> <span class="nf">make_multi_iter</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a1</span><span class="p">,</span> <span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a2</span><span class="p">,</span> <span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a3</span><span class="p">);</span>
|
||||
|
||||
<span class="p">}</span>
|
||||
<span class="p">}</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section" id="constructors">
|
||||
<h2><a class="toc-backref" href="#id3">constructors</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">multi_iter</span> <span class="nf">make_multi_iter</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a1</span><span class="p">);</span>
|
||||
<span class="n">multi_iter</span> <span class="nf">make_multi_iter</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a1</span><span class="p">,</span> <span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a2</span><span class="p">);</span>
|
||||
<span class="n">multi_iter</span> <span class="nf">make_multi_iter</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a1</span><span class="p">,</span> <span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a2</span><span class="p">,</span> <span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">a3</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">A Python iterator object broadcasting over one, two or three sequences as supplied</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
<div class="section" id="accessors">
|
||||
<h2><a class="toc-backref" href="#id4">accessors</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">void</span> <span class="nf">next</span><span class="p">();</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Effects:</th><td class="field-body">Increments the iterator</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">bool</span> <span class="n">not_done</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">boolean value indicating whether the iterator is at its end</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">char</span> <span class="o">*</span> <span class="n">get_data</span><span class="p">(</span><span class="kt">int</span> <span class="n">n</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">a pointer to the element of the nth broadcasted array.</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">int</span> <span class="k">const</span> <span class="n">get_nd</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">the number of dimensions of the broadcasted array expression</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="o">*</span> <span class="n">get_shape</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">the shape of the broadcasted array expression as an array of integers.</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="n">shape</span><span class="p">(</span><span class="kt">int</span> <span class="n">n</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">the shape of the broadcasted array expression in the nth dimension.</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
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|
||||
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|
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<div class="section" id="ndarray">
|
||||
<h1><a class="toc-backref" href="#id2">ndarray</a></h1>
|
||||
<div class="contents topic" id="table-of-contents">
|
||||
<p class="topic-title first">Table of Contents</p>
|
||||
<ul class="simple">
|
||||
<li><a class="reference internal" href="#ndarray" id="id2">ndarray</a><ul>
|
||||
<li><a class="reference internal" href="#synopsis" id="id3">synopsis</a></li>
|
||||
<li><a class="reference internal" href="#constructors" id="id4">constructors</a></li>
|
||||
<li><a class="reference internal" href="#accessors" id="id5">accessors</a></li>
|
||||
<li><a class="reference internal" href="#example-s" id="id6">Example(s)</a></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<p>A <a class="reference external" href="http://docs.scipy.org/doc/numpy/reference/arrays.ndarray.html">ndarray</a> 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 <tt class="docutils literal"><span class="pre">shape</span></tt> tuple. Optionally, the numpy <tt class="docutils literal"><span class="pre">dtype</span></tt> for the objects contained may also be specified.</p>
|
||||
<blockquote>
|
||||
<div><tt class="docutils literal"><span class="pre"><boost/python/numpy/ndarray.hpp></span></tt> contains the structures and methods necessary to move raw data between C++ and Python and create ndarrays from the data</div></blockquote>
|
||||
<div class="section" id="synopsis">
|
||||
<h2><a class="toc-backref" href="#id3">synopsis</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">namespace</span> <span class="n">boost</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">namespace</span> <span class="n">python</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">namespace</span> <span class="n">numpy</span>
|
||||
<span class="p">{</span>
|
||||
|
||||
<span class="k">class</span> <span class="nc">ndarray</span> <span class="o">:</span> <span class="k">public</span> <span class="n">object</span>
|
||||
<span class="p">{</span>
|
||||
|
||||
<span class="nl">public:</span>
|
||||
|
||||
<span class="k">enum</span> <span class="n">bitflag</span>
|
||||
<span class="p">{</span>
|
||||
<span class="n">NONE</span><span class="o">=</span><span class="mh">0x0</span><span class="p">,</span> <span class="n">C_CONTIGUOUS</span><span class="o">=</span><span class="mh">0x1</span><span class="p">,</span> <span class="n">F_CONTIGUOUS</span><span class="o">=</span><span class="mh">0x2</span><span class="p">,</span> <span class="n">V_CONTIGUOUS</span><span class="o">=</span><span class="mh">0x1</span><span class="o">|</span><span class="mh">0x2</span><span class="p">,</span>
|
||||
<span class="n">ALIGNED</span><span class="o">=</span><span class="mh">0x4</span><span class="p">,</span> <span class="n">WRITEABLE</span><span class="o">=</span><span class="mh">0x8</span><span class="p">,</span> <span class="n">BEHAVED</span><span class="o">=</span><span class="mh">0x4</span><span class="o">|</span><span class="mh">0x8</span><span class="p">,</span>
|
||||
<span class="n">CARRAY_RO</span><span class="o">=</span><span class="mh">0x1</span><span class="o">|</span><span class="mh">0x4</span><span class="p">,</span> <span class="n">CARRAY</span><span class="o">=</span><span class="mh">0x1</span><span class="o">|</span><span class="mh">0x4</span><span class="o">|</span><span class="mh">0x8</span><span class="p">,</span> <span class="n">CARRAY_MIS</span><span class="o">=</span><span class="mh">0x1</span><span class="o">|</span><span class="mh">0x8</span><span class="p">,</span>
|
||||
<span class="n">FARRAY_RO</span><span class="o">=</span><span class="mh">0x2</span><span class="o">|</span><span class="mh">0x4</span><span class="p">,</span> <span class="n">FARRAY</span><span class="o">=</span><span class="mh">0x2</span><span class="o">|</span><span class="mh">0x4</span><span class="o">|</span><span class="mh">0x8</span><span class="p">,</span> <span class="n">FARRAY_MIS</span><span class="o">=</span><span class="mh">0x2</span><span class="o">|</span><span class="mh">0x8</span><span class="p">,</span>
|
||||
<span class="n">UPDATE_ALL</span><span class="o">=</span><span class="mh">0x1</span><span class="o">|</span><span class="mh">0x2</span><span class="o">|</span><span class="mh">0x4</span><span class="p">,</span> <span class="n">VARRAY</span><span class="o">=</span><span class="mh">0x1</span><span class="o">|</span><span class="mh">0x2</span><span class="o">|</span><span class="mh">0x8</span><span class="p">,</span> <span class="n">ALL</span><span class="o">=</span><span class="mh">0x1</span><span class="o">|</span><span class="mh">0x2</span><span class="o">|</span><span class="mh">0x4</span><span class="o">|</span><span class="mh">0x8</span>
|
||||
<span class="p">};</span>
|
||||
|
||||
<span class="n">ndarray</span> <span class="n">view</span><span class="p">(</span><span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="n">ndarray</span> <span class="n">astype</span><span class="p">(</span><span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="n">ndarray</span> <span class="n">copy</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="kt">int</span> <span class="k">const</span> <span class="n">shape</span><span class="p">(</span><span class="kt">int</span> <span class="n">n</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="kt">int</span> <span class="k">const</span> <span class="n">strides</span><span class="p">(</span><span class="kt">int</span> <span class="n">n</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="kt">char</span> <span class="o">*</span> <span class="n">get_data</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="n">dtype</span> <span class="n">get_dtype</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="n">python</span><span class="o">::</span><span class="n">object</span> <span class="n">get_base</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="kt">void</span> <span class="nf">set_base</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">base</span><span class="p">);</span>
|
||||
<span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="o">*</span> <span class="n">get_shape</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="o">*</span> <span class="n">get_strides</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="kt">int</span> <span class="k">const</span> <span class="n">get_nd</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
|
||||
<span class="n">bitflag</span> <span class="k">const</span> <span class="n">get_flags</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
|
||||
<span class="n">ndarray</span> <span class="n">transpose</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="n">ndarray</span> <span class="n">squeeze</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="n">ndarray</span> <span class="n">reshape</span><span class="p">(</span><span class="n">tuple</span> <span class="k">const</span> <span class="o">&</span> <span class="n">shape</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="n">object</span> <span class="n">scalarize</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
<span class="p">};</span>
|
||||
|
||||
<span class="n">ndarray</span> <span class="nf">zeros</span><span class="p">(</span><span class="n">tuple</span> <span class="k">const</span> <span class="o">&</span> <span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">zeros</span><span class="p">(</span><span class="kt">int</span> <span class="n">nd</span><span class="p">,</span> <span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="o">*</span> <span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">);</span>
|
||||
|
||||
<span class="n">ndarray</span> <span class="nf">empty</span><span class="p">(</span><span class="n">tuple</span> <span class="k">const</span> <span class="o">&</span> <span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">empty</span><span class="p">(</span><span class="kt">int</span> <span class="n">nd</span><span class="p">,</span> <span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="o">*</span> <span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">);</span>
|
||||
|
||||
<span class="n">ndarray</span> <span class="nf">array</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">array</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">);</span>
|
||||
|
||||
<span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">Container</span><span class="o">></span>
|
||||
<span class="n">ndarray</span> <span class="n">from_data</span><span class="p">(</span><span class="kt">void</span> <span class="o">*</span> <span class="n">data</span><span class="p">,</span><span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">,</span><span class="n">Container</span> <span class="n">shape</span><span class="p">,</span><span class="n">Container</span> <span class="n">strides</span><span class="p">,</span><span class="n">python</span><span class="o">::</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">owner</span><span class="p">);</span>
|
||||
<span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">Container</span><span class="o">></span>
|
||||
<span class="n">ndarray</span> <span class="n">from_data</span><span class="p">(</span><span class="kt">void</span> <span class="k">const</span> <span class="o">*</span> <span class="n">data</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">,</span> <span class="n">Container</span> <span class="n">shape</span><span class="p">,</span> <span class="n">Container</span> <span class="n">strides</span><span class="p">,</span> <span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">owner</span><span class="p">);</span>
|
||||
|
||||
<span class="n">ndarray</span> <span class="nf">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">,</span><span class="kt">int</span> <span class="n">nd_min</span><span class="p">,</span> <span class="kt">int</span> <span class="n">nd_max</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">,</span><span class="kt">int</span> <span class="n">nd</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="kt">int</span> <span class="n">nd_min</span><span class="p">,</span> <span class="kt">int</span> <span class="n">nd_max</span><span class="p">,</span><span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="kt">int</span> <span class="n">nd</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="k">operator</span><span class="o">|</span><span class="p">(</span><span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">a</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">b</span><span class="p">)</span> <span class="p">;</span>
|
||||
<span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="k">operator</span><span class="o">&</span><span class="p">(</span><span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">a</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">b</span><span class="p">);</span>
|
||||
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section" id="constructors">
|
||||
<h2><a class="toc-backref" href="#id4">constructors</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="n">view</span><span class="p">(</span><span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">new ndarray with old ndarray data cast as supplied dtype</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="n">astype</span><span class="p">(</span><span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">new ndarray with old ndarray data converted to supplied dtype</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="n">copy</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Copy of calling ndarray object</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="n">transpose</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">An ndarray with the rows and columns interchanged</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="n">squeeze</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">An ndarray with all unit-shaped dimensions removed</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="n">reshape</span><span class="p">(</span><span class="n">tuple</span> <span class="k">const</span> <span class="o">&</span> <span class="n">shape</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body">The new <tt class="docutils literal"><span class="pre">shape</span></tt> of the ndarray must be supplied as a tuple</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">An ndarray with the same data but reshaped to the <tt class="docutils literal"><span class="pre">shape</span></tt> supplied</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">object</span> <span class="n">scalarize</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">A scalar if the ndarray has only one element, otherwise it returns the entire array</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="nf">zeros</span><span class="p">(</span><span class="n">tuple</span> <span class="k">const</span> <span class="o">&</span> <span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">zeros</span><span class="p">(</span><span class="kt">int</span> <span class="n">nd</span><span class="p">,</span> <span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="o">*</span> <span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body"><p class="first">The following parameters must be supplied as required :</p>
|
||||
<ul class="simple">
|
||||
<li>the <tt class="docutils literal"><span class="pre">shape</span></tt> or the size of all dimensions, as a tuple</li>
|
||||
<li>the <tt class="docutils literal"><span class="pre">dtype</span></tt> of the data</li>
|
||||
<li>the <tt class="docutils literal"><span class="pre">nd</span></tt> size for a square shaped ndarray</li>
|
||||
<li>the <tt class="docutils literal"><span class="pre">shape</span></tt> Py_intptr_t</li>
|
||||
</ul>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">A new ndarray with the given shape and data type, with data initialized to zero.</p>
|
||||
</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="nf">empty</span><span class="p">(</span><span class="n">tuple</span> <span class="k">const</span> <span class="o">&</span> <span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">empty</span><span class="p">(</span><span class="kt">int</span> <span class="n">nd</span><span class="p">,</span> <span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="o">*</span> <span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body"><p class="first">The following parameters must be supplied :</p>
|
||||
<ul class="simple">
|
||||
<li>the <tt class="docutils literal"><span class="pre">shape</span></tt> or the size of all dimensions, as a tuple</li>
|
||||
<li>the <tt class="docutils literal"><span class="pre">dtype</span></tt> of the data</li>
|
||||
<li>the <tt class="docutils literal"><span class="pre">shape</span></tt> Py_intptr_t</li>
|
||||
</ul>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">A new ndarray with the given shape and data type, with data left uninitialized.</p>
|
||||
</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="nf">array</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">);</span>
|
||||
<span class="n">ndarray</span> <span class="nf">array</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">A new ndarray from an arbitrary Python sequence, with dtype of each element specified optionally</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">Container</span><span class="o">></span>
|
||||
<span class="kr">inline</span> <span class="n">ndarray</span> <span class="n">from_data</span><span class="p">(</span><span class="kt">void</span> <span class="o">*</span> <span class="n">data</span><span class="p">,</span><span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">,</span><span class="n">Container</span> <span class="n">shape</span><span class="p">,</span><span class="n">Container</span> <span class="n">strides</span><span class="p">,</span><span class="n">python</span><span class="o">::</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">owner</span><span class="p">)</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body"><p class="first">The following parameters must be supplied :</p>
|
||||
<ul class="simple">
|
||||
<li>the <tt class="docutils literal"><span class="pre">data</span></tt> which is a generic C++ data container</li>
|
||||
<li>the dtype <tt class="docutils literal"><span class="pre">dt</span></tt> of the data</li>
|
||||
<li>the <tt class="docutils literal"><span class="pre">shape</span></tt> of the ndarray as Python object</li>
|
||||
<li>the <tt class="docutils literal"><span class="pre">strides</span></tt> of each dimension of the array as a Python object</li>
|
||||
<li>the <tt class="docutils literal"><span class="pre">owner</span></tt> of the data, in case it is not the ndarray itself</li>
|
||||
</ul>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">ndarray with attributes and data supplied</p>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-odd field"><th class="field-name">Note:</th><td class="field-body"><p class="first last">The <tt class="docutils literal"><span class="pre">Container</span></tt> typename must be one that is convertible to a std::vector or python object type</p>
|
||||
</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="nf">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">,</span><span class="kt">int</span> <span class="n">nd_min</span><span class="p">,</span> <span class="kt">int</span> <span class="n">nd_max</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body"><p class="first">The following parameters must be supplied :</p>
|
||||
<ul class="simple">
|
||||
<li>the <tt class="docutils literal"><span class="pre">obj</span></tt> Python object to convert to ndarray</li>
|
||||
<li>the dtype <tt class="docutils literal"><span class="pre">dt</span></tt> of the data</li>
|
||||
<li>minimum number of dimensions <tt class="docutils literal"><span class="pre">nd_min</span></tt> of the ndarray as Python object</li>
|
||||
<li>maximum number of dimensions <tt class="docutils literal"><span class="pre">nd_max</span></tt> of the ndarray as Python object</li>
|
||||
<li>optional <tt class="docutils literal"><span class="pre">flags</span></tt> bitflags</li>
|
||||
</ul>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">ndarray constructed with dimensions and data supplied as parameters</p>
|
||||
</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kr">inline</span> <span class="n">ndarray</span> <span class="nf">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">,</span> <span class="kt">int</span> <span class="n">nd</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body"><p class="first">The following parameters must be supplied :</p>
|
||||
<ul class="simple">
|
||||
<li>the <tt class="docutils literal"><span class="pre">obj</span></tt> Python object to convert to ndarray</li>
|
||||
<li>the dtype <tt class="docutils literal"><span class="pre">dt</span></tt> of the data</li>
|
||||
<li>number of dimensions <tt class="docutils literal"><span class="pre">nd</span></tt> of the ndarray as Python object</li>
|
||||
<li>optional <tt class="docutils literal"><span class="pre">flags</span></tt> bitflags</li>
|
||||
</ul>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">ndarray with dimensions <tt class="docutils literal"><span class="pre">nd</span></tt> x <tt class="docutils literal"><span class="pre">nd</span></tt> and suplied parameters</p>
|
||||
</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kr">inline</span> <span class="n">ndarray</span> <span class="n">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="n">dtype</span> <span class="k">const</span> <span class="o">&</span> <span class="n">dt</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">)</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body"><p class="first">The following parameters must be supplied :</p>
|
||||
<ul class="simple">
|
||||
<li>the <tt class="docutils literal"><span class="pre">obj</span></tt> Python object to convert to ndarray</li>
|
||||
<li>the dtype <tt class="docutils literal"><span class="pre">dt</span></tt> of the data</li>
|
||||
<li>optional <tt class="docutils literal"><span class="pre">flags</span></tt> bitflags</li>
|
||||
</ul>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">Supplied Python object as ndarray</p>
|
||||
</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">ndarray</span> <span class="nf">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="kt">int</span> <span class="n">nd_min</span><span class="p">,</span> <span class="kt">int</span> <span class="n">nd_max</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body"><p class="first">The following parameters must be supplied :</p>
|
||||
<ul class="simple">
|
||||
<li>the <tt class="docutils literal"><span class="pre">obj</span></tt> Python object to convert to ndarray</li>
|
||||
<li>minimum number of dimensions <tt class="docutils literal"><span class="pre">nd_min</span></tt> of the ndarray as Python object</li>
|
||||
<li>maximum number of dimensions <tt class="docutils literal"><span class="pre">nd_max</span></tt> of the ndarray as Python object</li>
|
||||
<li>optional <tt class="docutils literal"><span class="pre">flags</span></tt> bitflags</li>
|
||||
</ul>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">ndarray with supplied dimension limits and parameters</p>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-odd field"><th class="field-name">Note:</th><td class="field-body"><p class="first last">dtype need not be supplied here</p>
|
||||
</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kr">inline</span> <span class="n">ndarray</span> <span class="nf">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="kt">int</span> <span class="n">nd</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body"><p class="first">The following parameters must be supplied :</p>
|
||||
<ul class="simple">
|
||||
<li>the <tt class="docutils literal"><span class="pre">obj</span></tt> Python object to convert to ndarray</li>
|
||||
<li>the dtype <tt class="docutils literal"><span class="pre">dt</span></tt> of the data</li>
|
||||
<li>number of dimensions <tt class="docutils literal"><span class="pre">nd</span></tt> of the ndarray as Python object</li>
|
||||
<li>optional <tt class="docutils literal"><span class="pre">flags</span></tt> bitflags</li>
|
||||
</ul>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">ndarray of <tt class="docutils literal"><span class="pre">nd</span></tt> x <tt class="docutils literal"><span class="pre">nd</span></tt> dimensions constructed from the supplied object</p>
|
||||
</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kr">inline</span> <span class="n">ndarray</span> <span class="n">from_object</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">obj</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">flags</span><span class="o">=</span><span class="n">ndarray</span><span class="o">::</span><span class="n">NONE</span><span class="p">)</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body"><p class="first">The following parameters must be supplied :</p>
|
||||
<ul class="simple">
|
||||
<li>the <tt class="docutils literal"><span class="pre">obj</span></tt> Python object to convert to ndarray</li>
|
||||
<li>optional <tt class="docutils literal"><span class="pre">flags</span></tt> bitflags</li>
|
||||
</ul>
|
||||
</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">ndarray of same dimensions and dtype as supplied Python object</p>
|
||||
</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
<div class="section" id="accessors">
|
||||
<h2><a class="toc-backref" href="#id5">accessors</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">int</span> <span class="k">const</span> <span class="n">shape</span><span class="p">(</span><span class="kt">int</span> <span class="n">n</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">The size of the n-th dimension of the ndarray</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">int</span> <span class="k">const</span> <span class="n">strides</span><span class="p">(</span><span class="kt">int</span> <span class="n">n</span><span class="p">)</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">The stride of the nth dimension.</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">char</span> <span class="o">*</span> <span class="n">get_data</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Array’s raw data pointer as a char</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Note:</th><td class="field-body">This returns char so stride math works properly on it.User will have to reinterpret_cast it.</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">dtype</span> <span class="n">get_dtype</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Array’s data-type descriptor object (dtype)</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">object</span> <span class="n">get_base</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Object that owns the array’s data, or None if the array owns its own data.</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">void</span> <span class="nf">set_base</span><span class="p">(</span><span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">base</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Set the object that owns the array’s data. Exercise caution while using this</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="o">*</span> <span class="n">get_shape</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Shape of the array as an array of integers</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">Py_intptr_t</span> <span class="k">const</span> <span class="o">*</span> <span class="n">get_strides</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Stride of the array as an array of integers</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">int</span> <span class="k">const</span> <span class="n">get_nd</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Number of array dimensions</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">bitflag</span> <span class="k">const</span> <span class="n">get_flags</span><span class="p">()</span> <span class="k">const</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Array flags</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kr">inline</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="k">operator</span><span class="o">|</span><span class="p">(</span><span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">a</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">b</span><span class="p">)</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">bitflag logically OR-ed as (a | b)</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kr">inline</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="k">operator</span><span class="o">&</span><span class="p">(</span><span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">a</span><span class="p">,</span> <span class="n">ndarray</span><span class="o">::</span><span class="n">bitflag</span> <span class="n">b</span><span class="p">)</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">bitflag logically AND-ed as (a & b)</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
<div class="section" id="example-s">
|
||||
<h2><a class="toc-backref" href="#id6">Example(s)</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">namespace</span> <span class="n">p</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="p">;</span>
|
||||
<span class="k">namespace</span> <span class="n">np</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="o">::</span><span class="n">numpy</span><span class="p">;</span>
|
||||
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">object</span> <span class="n">tu</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="sc">'a'</span><span class="p">,</span><span class="sc">'b'</span><span class="p">,</span><span class="sc">'c'</span><span class="p">)</span> <span class="p">;</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">example_tuple</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">array</span> <span class="p">(</span><span class="n">tu</span><span class="p">)</span> <span class="p">;</span>
|
||||
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">list</span> <span class="n">l</span> <span class="p">;</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">example_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">array</span> <span class="p">(</span><span class="n">l</span><span class="p">)</span> <span class="p">;</span>
|
||||
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">dtype</span> <span class="n">dt</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="o">::</span><span class="n">get_builtin</span><span class="o"><</span><span class="kt">int</span><span class="o">></span><span class="p">();</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">example_list1</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">array</span> <span class="p">(</span><span class="n">l</span><span class="p">,</span><span class="n">dt</span><span class="p">);</span>
|
||||
|
||||
<span class="kt">int</span> <span class="n">data</span><span class="p">[]</span> <span class="o">=</span> <span class="p">{</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">}</span> <span class="p">;</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">tuple</span> <span class="n">shape</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="p">;</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">tuple</span> <span class="n">stride</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> <span class="p">;</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">object</span> <span class="n">own</span> <span class="p">;</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">data_ex</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">from_data</span><span class="p">(</span><span class="n">data</span><span class="p">,</span><span class="n">dt</span><span class="p">,</span><span class="n">shape</span><span class="p">,</span><span class="n">stride</span><span class="p">,</span><span class="n">own</span><span class="p">);</span>
|
||||
|
||||
<span class="kt">uint8_t</span> <span class="n">mul_data</span><span class="p">[][</span><span class="mi">4</span><span class="p">]</span> <span class="o">=</span> <span class="p">{{</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">},{</span><span class="mi">5</span><span class="p">,</span><span class="mi">6</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">8</span><span class="p">},{</span><span class="mi">1</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">7</span><span class="p">}};</span>
|
||||
<span class="n">shape</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span><span class="mi">2</span><span class="p">)</span> <span class="p">;</span>
|
||||
<span class="n">stride</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">2</span><span class="p">)</span> <span class="p">;</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">dtype</span> <span class="n">dt1</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="o">::</span><span class="n">get_builtin</span><span class="o"><</span><span class="kt">uint8_t</span><span class="o">></span><span class="p">();</span>
|
||||
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">mul_data_ex</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">from_data</span><span class="p">(</span><span class="n">mul_data</span><span class="p">,</span><span class="n">dt1</span><span class="p">,</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">),</span><span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">1</span><span class="p">),</span><span class="n">p</span><span class="o">::</span><span class="n">object</span><span class="p">());</span>
|
||||
<span class="n">mul_data_ex</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">from_data</span><span class="p">(</span><span class="n">mul_data</span><span class="p">,</span><span class="n">dt1</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span><span class="n">stride</span><span class="p">,</span><span class="n">p</span><span class="o">::</span><span class="n">object</span><span class="p">());</span>
|
||||
</pre></div>
|
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|
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|
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|
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<div class="section" id="unary-ufunc">
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<h1><a class="toc-backref" href="#id1">unary_ufunc</a></h1>
|
||||
<div class="contents topic" id="table-of-contents">
|
||||
<p class="topic-title first">Table of Contents</p>
|
||||
<ul class="simple">
|
||||
<li><a class="reference internal" href="#unary-ufunc" id="id1">unary_ufunc</a><ul>
|
||||
<li><a class="reference internal" href="#synopsis" id="id2">synopsis</a></li>
|
||||
<li><a class="reference internal" href="#constructors" id="id3">constructors</a></li>
|
||||
<li><a class="reference internal" href="#accessors" id="id4">accessors</a></li>
|
||||
<li><a class="reference internal" href="#example-s" id="id5">Example(s)</a></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
<p>A <tt class="docutils literal"><span class="pre">unary_ufunc</span></tt> is a struct used as an intermediate step to broadcast a single argument so that a C++ function can be converted to a ufunc like function</p>
|
||||
<blockquote>
|
||||
<div><tt class="docutils literal"><span class="pre"><boost/python/numpy/ufunc.hpp></span></tt> contains the <tt class="docutils literal"><span class="pre">unary_ufunc</span></tt> structure definitions</div></blockquote>
|
||||
<div class="section" id="synopsis">
|
||||
<h2><a class="toc-backref" href="#id2">synopsis</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">namespace</span> <span class="n">boost</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">namespace</span> <span class="n">python</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">namespace</span> <span class="n">numpy</span>
|
||||
<span class="p">{</span>
|
||||
|
||||
<span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">TUnaryFunctor</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TArgument</span><span class="o">=</span><span class="k">typename</span> <span class="n">TUnaryFunctor</span><span class="o">::</span><span class="n">argument_type</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TResult</span><span class="o">=</span><span class="k">typename</span> <span class="n">TUnaryFunctor</span><span class="o">::</span><span class="n">result_type</span><span class="o">></span>
|
||||
<span class="k">struct</span> <span class="n">unary_ufunc</span>
|
||||
<span class="p">{</span>
|
||||
|
||||
<span class="k">static</span> <span class="n">object</span> <span class="n">call</span><span class="p">(</span><span class="n">TUnaryFunctor</span> <span class="o">&</span> <span class="n">self</span><span class="p">,</span>
|
||||
<span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">input</span><span class="p">,</span>
|
||||
<span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">output</span><span class="p">)</span> <span class="p">;</span>
|
||||
|
||||
<span class="k">static</span> <span class="n">object</span> <span class="nf">make</span><span class="p">();</span>
|
||||
|
||||
<span class="p">};</span>
|
||||
<span class="p">}</span>
|
||||
<span class="p">}</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="section" id="constructors">
|
||||
<h2><a class="toc-backref" href="#id3">constructors</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">struct</span> <span class="n">example_unary_ufunc</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">typedef</span> <span class="n">any_valid_type</span> <span class="n">argument_type</span><span class="p">;</span>
|
||||
<span class="k">typedef</span> <span class="n">any_valid_type</span> <span class="n">result_type</span><span class="p">;</span>
|
||||
<span class="p">};</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requirements:</th><td class="field-body">The <tt class="docutils literal"><span class="pre">any_valid</span></tt> type must be defined using typedef as a valid C++ type in order to use the struct methods correctly</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Note:</th><td class="field-body">The struct must be exposed as a Python class, and an instance of the class must be created to use the <tt class="docutils literal"><span class="pre">call</span></tt> method corresponding to the <tt class="docutils literal"><span class="pre">__call__</span></tt> attribute of the Python object</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
<div class="section" id="accessors">
|
||||
<h2><a class="toc-backref" href="#id4">accessors</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">TUnaryFunctor</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TArgument</span><span class="o">=</span><span class="k">typename</span> <span class="n">TUnaryFunctor</span><span class="o">::</span><span class="n">argument_type</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TResult</span><span class="o">=</span><span class="k">typename</span> <span class="n">TUnaryFunctor</span><span class="o">::</span><span class="n">result_type</span><span class="o">></span>
|
||||
<span class="k">static</span> <span class="n">object</span> <span class="n">call</span><span class="p">(</span><span class="n">TUnaryFunctor</span> <span class="o">&</span> <span class="n">self</span><span class="p">,</span>
|
||||
<span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">input</span><span class="p">,</span>
|
||||
<span class="n">object</span> <span class="k">const</span> <span class="o">&</span> <span class="n">output</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requires:</th><td class="field-body">Typenames <tt class="docutils literal"><span class="pre">TUnaryFunctor</span></tt> and optionally <tt class="docutils literal"><span class="pre">TArgument</span></tt> for argument type and <tt class="docutils literal"><span class="pre">TResult</span></tt> for result type</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Effects:</th><td class="field-body">Passes a Python object to the underlying C++ functor after broadcasting its arguments</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">template</span> <span class="o"><</span><span class="k">typename</span> <span class="n">TUnaryFunctor</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TArgument</span><span class="o">=</span><span class="k">typename</span> <span class="n">TUnaryFunctor</span><span class="o">::</span><span class="n">argument_type</span><span class="p">,</span>
|
||||
<span class="k">typename</span> <span class="n">TResult</span><span class="o">=</span><span class="k">typename</span> <span class="n">TUnaryFunctor</span><span class="o">::</span><span class="n">result_type</span><span class="o">></span>
|
||||
<span class="k">static</span> <span class="n">object</span> <span class="n">make</span><span class="p">();</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<table class="docutils field-list" frame="void" rules="none">
|
||||
<col class="field-name" />
|
||||
<col class="field-body" />
|
||||
<tbody valign="top">
|
||||
<tr class="field-odd field"><th class="field-name">Requires:</th><td class="field-body">Typenames <tt class="docutils literal"><span class="pre">TUnaryFunctor</span></tt> and optionally <tt class="docutils literal"><span class="pre">TArgument</span></tt> for argument type and <tt class="docutils literal"><span class="pre">TResult</span></tt> for result type</td>
|
||||
</tr>
|
||||
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">A Python function object to call the overloaded () operator in the struct (in typical usage)</td>
|
||||
</tr>
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
<div class="section" id="example-s">
|
||||
<h2><a class="toc-backref" href="#id5">Example(s)</a></h2>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="k">namespace</span> <span class="n">p</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="p">;</span>
|
||||
<span class="k">namespace</span> <span class="n">np</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="o">::</span><span class="n">numpy</span><span class="p">;</span>
|
||||
|
||||
<span class="k">struct</span> <span class="n">UnarySquare</span>
|
||||
<span class="p">{</span>
|
||||
<span class="k">typedef</span> <span class="kt">double</span> <span class="n">argument_type</span><span class="p">;</span>
|
||||
<span class="k">typedef</span> <span class="kt">double</span> <span class="n">result_type</span><span class="p">;</span>
|
||||
<span class="kt">double</span> <span class="k">operator</span><span class="p">()(</span><span class="kt">double</span> <span class="n">r</span><span class="p">)</span> <span class="k">const</span> <span class="p">{</span> <span class="k">return</span> <span class="n">r</span> <span class="o">*</span> <span class="n">r</span><span class="p">;}</span>
|
||||
<span class="p">};</span>
|
||||
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">object</span> <span class="n">ud</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">class_</span><span class="o"><</span><span class="n">UnarySquare</span><span class="p">,</span> <span class="n">boost</span><span class="o">::</span><span class="n">shared_ptr</span><span class="o"><</span><span class="n">UnarySquare</span><span class="o">></span> <span class="o">></span><span class="p">(</span><span class="s">"UnarySquare"</span><span class="p">).</span><span class="n">def</span><span class="p">(</span><span class="s">"__call__"</span><span class="p">,</span> <span class="n">np</span><span class="o">::</span><span class="n">unary_ufunc</span><span class="o"><</span><span class="n">UnarySquare</span><span class="o">>::</span><span class="n">make</span><span class="p">());</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">object</span> <span class="n">inst</span> <span class="o">=</span> <span class="n">ud</span><span class="p">();</span>
|
||||
<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Square of unary scalar 1.0 is "</span> <span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span> <span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*</span> <span class="o">></span> <span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">inst</span><span class="p">.</span><span class="n">attr</span><span class="p">(</span><span class="s">"__call__"</span><span class="p">)(</span><span class="mf">1.0</span><span class="p">)))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span> <span class="p">;</span>
|
||||
</pre></div>
|
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|
||||
<p>Here is a brief tutorial to show how to create ndarrays with built-in python data types, and extract the types and values of member variables</p>
|
||||
<p>Like before, first get the necessary headers, setup the namespaces and initialize the Python runtime and numpy module:</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="cp">#include <boost/python/numpy.hpp></span>
|
||||
<span class="cp">#include <iostream></span>
|
||||
|
||||
<span class="k">namespace</span> <span class="n">p</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="p">;</span>
|
||||
<span class="k">namespace</span> <span class="n">np</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="o">::</span><span class="n">numpy</span><span class="p">;</span>
|
||||
|
||||
<span class="kt">int</span> <span class="nf">main</span><span class="p">(</span><span class="kt">int</span> <span class="n">argc</span><span class="p">,</span> <span class="kt">char</span> <span class="o">**</span><span class="n">argv</span><span class="p">)</span>
|
||||
<span class="p">{</span>
|
||||
<span class="n">Py_Initialize</span><span class="p">();</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">initialize</span><span class="p">();</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Next, we create the shape and dtype. We use the get_builtin method to get the numpy dtype corresponding to the builtin C++ dtype
|
||||
Here, we will create a 3x3 array passing a tuple with (3,3) for the size, and double as the data type</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">p</span><span class="o">::</span><span class="n">tuple</span> <span class="n">shape</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">);</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">dtype</span> <span class="n">dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="o">::</span><span class="n">get_builtin</span><span class="o"><</span><span class="kt">double</span><span class="o">></span><span class="p">();</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">zeros</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Finally, we can print the array using the extract method in the python namespace.
|
||||
Here, we first convert the variable into a string, and then extract it as a C++ character array from the python string using the <char const * > template</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Original array:</span><span class="se">\n</span><span class="s">"</span> <span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">a</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>We can also print the dtypes of the data members of the ndarray by using the get_dtype method for the ndarray</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Datatype is:</span><span class="se">\n</span><span class="s">"</span> <span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">a</span><span class="p">.</span><span class="n">get_dtype</span><span class="p">()))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span> <span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>We can also create custom dtypes and build ndarrays with the custom dtypes</p>
|
||||
<p>We use the dtype constructor to create a custom dtype. This constructor takes a list as an argument.</p>
|
||||
<p>The list should contain one or more tuples of the format (variable name, variable type)</p>
|
||||
<p>So first create a tuple with a variable name and its dtype, double, to create a custom dtype</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">p</span><span class="o">::</span><span class="n">tuple</span> <span class="n">for_custom_dtype</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="s">"ha"</span><span class="p">,</span><span class="n">dtype</span><span class="p">)</span> <span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Next, create a list, and add this tuple to the list. Then use the list to create the custom dtype</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">p</span><span class="o">::</span><span class="n">list</span> <span class="n">list_for_dtype</span> <span class="p">;</span>
|
||||
<span class="n">list_for_dtype</span><span class="p">.</span><span class="n">append</span><span class="p">(</span><span class="n">for_custom_dtype</span><span class="p">)</span> <span class="p">;</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">dtype</span> <span class="n">custom_dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="p">(</span><span class="n">list_for_dtype</span><span class="p">)</span> <span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>We are now ready to create an ndarray with dimensions specified by *shape* and of custom dtpye</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre> <span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">new_array</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">zeros</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span><span class="n">custom_dtype</span><span class="p">);</span>
|
||||
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|
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<div class="section" id="how-to-access-data-using-raw-pointers">
|
||||
<h1>How to access data using raw pointers</h1>
|
||||
<p>One of the advantages of the ndarray wrapper is that the same data can be used in both Python and C++ and changes can be made to reflect at both ends.
|
||||
The from_data method makes this possible.</p>
|
||||
<p>Like before, first get the necessary headers, setup the namespaces and initialize the Python runtime and numpy module:</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="cp">#include <boost/python/numpy.hpp></span>
|
||||
<span class="cp">#include <iostream></span>
|
||||
|
||||
<span class="k">namespace</span> <span class="n">p</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="p">;</span>
|
||||
<span class="k">namespace</span> <span class="n">np</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="o">::</span><span class="n">numpy</span><span class="p">;</span>
|
||||
|
||||
<span class="kt">int</span> <span class="nf">main</span><span class="p">(</span><span class="kt">int</span> <span class="n">argc</span><span class="p">,</span> <span class="kt">char</span> <span class="o">**</span><span class="n">argv</span><span class="p">)</span>
|
||||
<span class="p">{</span>
|
||||
<span class="n">Py_Initialize</span><span class="p">();</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">initialize</span><span class="p">();</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Create an array in C++ , and pass the pointer to it to the from_data method to create an ndarray:</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">int</span> <span class="n">arr</span><span class="p">[]</span> <span class="o">=</span> <span class="p">{</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">};</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">py_array</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">from_data</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="o">::</span><span class="n">get_builtin</span><span class="o"><</span><span class="kt">int</span><span class="o">></span><span class="p">(),</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">5</span><span class="p">),</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="k">sizeof</span><span class="p">(</span><span class="kt">int</span><span class="p">)),</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">object</span><span class="p">());</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Print the source C++ array, as well as the ndarray, to check if they are the same:</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"C++ array :"</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
|
||||
<span class="k">for</span> <span class="p">(</span><span class="kt">int</span> <span class="n">j</span><span class="o">=</span><span class="mi">0</span><span class="p">;</span><span class="n">j</span><span class="o"><</span><span class="mi">4</span><span class="p">;</span><span class="n">j</span><span class="o">++</span><span class="p">)</span>
|
||||
<span class="p">{</span>
|
||||
<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="n">arr</span><span class="p">[</span><span class="n">j</span><span class="p">]</span> <span class="o"><<</span> <span class="sc">' '</span><span class="p">;</span>
|
||||
<span class="p">}</span>
|
||||
<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span>
|
||||
<span class="o"><<</span> <span class="s">"Python ndarray :"</span> <span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">py_array</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Now, change an element in the Python ndarray, and check if the value changed correspondingly in the source C++ array:</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">py_array</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="mi">5</span> <span class="p">;</span>
|
||||
<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Is the change reflected in the C++ array used to create the ndarray ? "</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
|
||||
<span class="k">for</span> <span class="p">(</span><span class="kt">int</span> <span class="n">j</span> <span class="o">=</span> <span class="mi">0</span><span class="p">;</span> <span class="n">j</span> <span class="o"><</span> <span class="mi">5</span><span class="p">;</span> <span class="n">j</span><span class="o">++</span><span class="p">)</span>
|
||||
<span class="p">{</span>
|
||||
<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="n">arr</span><span class="p">[</span><span class="n">j</span><span class="p">]</span> <span class="o"><<</span> <span class="sc">' '</span><span class="p">;</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Next, change an element of the source C++ array and see if it is reflected in the Python ndarray:</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre> <span class="n">arr</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">=</span> <span class="mi">8</span><span class="p">;</span>
|
||||
<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span>
|
||||
<span class="o"><<</span> <span class="s">"Is the change reflected in the Python ndarray ?"</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span>
|
||||
<span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">py_array</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>As we can see, the changes are reflected across the ends. This happens because the from_data method passes the C++ array by reference to create the ndarray, and thus uses the same locations for storing data.</p>
|
||||
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|
||||
|
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90
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178
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178
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<div class="section" id="creating-ndarrays">
|
||||
<h1>Creating ndarrays</h1>
|
||||
<p>The Boost.Numpy library exposes quite a few methods to create ndarrays. ndarrays can be created in a variety of ways, include empty arrays and zero filled arrays.
|
||||
ndarrays can also be created from arbitrary python sequences as well as from data and dtypes.</p>
|
||||
<p>This tutorial will introduce you to some of the ways in which you can create ndarrays. The methods covered here include creating ndarrays from arbitrary Python sequences, as well as from C++ containers, using both unit and non-unit strides</p>
|
||||
<p>First, as before, initialise the necessary namepaces and runtimes</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="cp">#include <boost/python/numpy.hpp></span>
|
||||
<span class="cp">#include <iostream></span>
|
||||
|
||||
<span class="k">namespace</span> <span class="n">p</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="p">;</span>
|
||||
<span class="k">namespace</span> <span class="n">np</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="o">::</span><span class="n">numpy</span><span class="p">;</span>
|
||||
|
||||
<span class="kt">int</span> <span class="nf">main</span><span class="p">(</span><span class="kt">int</span> <span class="n">argc</span><span class="p">,</span> <span class="kt">char</span> <span class="o">**</span><span class="n">argv</span><span class="p">)</span>
|
||||
<span class="p">{</span>
|
||||
<span class="n">Py_Initialize</span><span class="p">();</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">initialize</span><span class="p">();</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Let’s now create an ndarray from a simple tuple. We first create a tuple object, and then pass it to the array method, to generate the necessary tuple</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">p</span><span class="o">::</span><span class="n">object</span> <span class="n">tu</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="sc">'a'</span><span class="p">,</span><span class="sc">'b'</span><span class="p">,</span><span class="sc">'c'</span><span class="p">);</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">example_tuple</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">array</span><span class="p">(</span><span class="n">tu</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Let’s now try the same with a list. We create an empty list, add an element using the append method, and as before, call the array method</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">p</span><span class="o">::</span><span class="n">list</span> <span class="n">l</span><span class="p">;</span>
|
||||
<span class="n">l</span><span class="p">.</span><span class="n">append</span><span class="p">(</span><span class="sc">'a'</span><span class="p">);</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">example_list</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">array</span> <span class="p">(</span><span class="n">l</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Optionally, we can also specify a dtype for the array</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">np</span><span class="o">::</span><span class="n">dtype</span> <span class="n">dt</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="o">::</span><span class="n">get_builtin</span><span class="o"><</span><span class="kt">int</span><span class="o">></span><span class="p">();</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">example_list1</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">array</span> <span class="p">(</span><span class="n">l</span><span class="p">,</span><span class="n">dt</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>We can also create an array by supplying data arrays and a few other parameters.</p>
|
||||
<p>First,create an integer array</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">int</span> <span class="n">data</span><span class="p">[]</span> <span class="o">=</span> <span class="p">{</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">};</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Create a shape, and strides, needed by the function</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">p</span><span class="o">::</span><span class="n">tuple</span> <span class="n">shape</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">5</span><span class="p">);</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">tuple</span> <span class="n">stride</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="k">sizeof</span><span class="p">(</span><span class="kt">int</span><span class="p">));</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Here, shape is (4,) , and the stride is <cite>sizeof(int)`</cite>.
|
||||
A stride is the number of bytes that must be traveled to get to the next desired element while constructing the ndarray.</p>
|
||||
<p>The function also needs an owner, to keep track of the data array passed. Passing none is dangerous</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">p</span><span class="o">::</span><span class="n">object</span> <span class="n">own</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>The from_data function takes the data array, datatype,shape,stride and owner as arguments and returns an ndarray</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">data_ex1</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">from_data</span><span class="p">(</span><span class="n">data</span><span class="p">,</span><span class="n">dt</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span><span class="n">stride</span><span class="p">,</span><span class="n">own</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Now let’s print the ndarray we created</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Single dimensional array ::"</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span>
|
||||
<span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">data_ex</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Let’s make it a little more interesting. Lets make an 3x2 ndarray from a multi-dimensional array using non-unit strides</p>
|
||||
<p>First lets create a 3x4 array of 8-bit integers</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">uint8_t</span> <span class="n">mul_data</span><span class="p">[][</span><span class="mi">4</span><span class="p">]</span> <span class="o">=</span> <span class="p">{{</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">},{</span><span class="mi">5</span><span class="p">,</span><span class="mi">6</span><span class="p">,</span><span class="mi">7</span><span class="p">,</span><span class="mi">8</span><span class="p">},{</span><span class="mi">1</span><span class="p">,</span><span class="mi">3</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">7</span><span class="p">}};</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Now let’s create an array of 3x2 elements, picking the first and third elements from each row . For that, the shape will be 3x2.
|
||||
The strides will be 4x2 i.e. 4 bytes to go to the next desired row, and 2 bytes to go to the next desired column</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">shape</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span><span class="mi">2</span><span class="p">);</span>
|
||||
<span class="n">stride</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="k">sizeof</span><span class="p">(</span><span class="kt">uint8_t</span><span class="p">)</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span><span class="k">sizeof</span><span class="p">(</span><span class="kt">uint8_t</span><span class="p">));</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Get the numpy dtype for the built-in 8-bit integer data type</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">np</span><span class="o">::</span><span class="n">dtype</span> <span class="n">dt1</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="o">::</span><span class="n">get_builtin</span><span class="o"><</span><span class="kt">uint8_t</span><span class="o">></span><span class="p">();</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Now lets first create and print out the ndarray as is.
|
||||
Notice how we can pass the shape and strides in the function directly, as well as the owner. The last part can be done because we don’t have any use to
|
||||
manipulate the “owner” object</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">mul_data_ex</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">from_data</span><span class="p">(</span><span class="n">mul_data</span><span class="p">,</span> <span class="n">dt1</span><span class="p">,</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">),</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">1</span><span class="p">),</span>
|
||||
<span class="n">p</span><span class="o">::</span><span class="n">object</span><span class="p">());</span>
|
||||
<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Original multi dimensional array :: "</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span>
|
||||
<span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">mul_data_ex</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Now create the new ndarray using the shape and strides and print out the array we created using non-unit strides</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre> <span class="n">mul_data_ex</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">from_data</span><span class="p">(</span><span class="n">mul_data</span><span class="p">,</span> <span class="n">dt1</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">p</span><span class="o">::</span><span class="n">object</span><span class="p">());</span>
|
||||
<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Selective multidimensional array :: "</span><span class="o"><<</span><span class="n">std</span><span class="o">::</span><span class="n">endl</span>
|
||||
<span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">mul_data_ex</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span> <span class="p">;</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<div class="admonition note">
|
||||
<p class="first admonition-title">Note</p>
|
||||
<p class="last">The from_data method will throw <tt class="docutils literal"><span class="pre">error_already_set</span></tt> if the number of elements dictated by the shape and the corresponding strides don’t match.</p>
|
||||
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|
||||
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|
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<div class="section" id="a-simple-tutorial-on-arrays">
|
||||
<h1>A simple tutorial on Arrays</h1>
|
||||
<p>Let’s start with a simple tutorial to create and modify arrays.</p>
|
||||
<p>Get the necessary headers for numpy components and set up necessary namespaces:</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="cp">#include <boost/python/numpy.hpp></span>
|
||||
<span class="cp">#include <iostream></span>
|
||||
|
||||
<span class="k">namespace</span> <span class="n">p</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="p">;</span>
|
||||
<span class="k">namespace</span> <span class="n">np</span> <span class="o">=</span> <span class="n">boost</span><span class="o">::</span><span class="n">python</span><span class="o">::</span><span class="n">numpy</span><span class="p">;</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Initialise the Python runtime, and the numpy module. Failure to call these results in segmentation errors:</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="kt">int</span> <span class="nf">main</span><span class="p">(</span><span class="kt">int</span> <span class="n">argc</span><span class="p">,</span> <span class="kt">char</span> <span class="o">**</span><span class="n">argv</span><span class="p">)</span>
|
||||
<span class="p">{</span>
|
||||
<span class="n">Py_Initialize</span><span class="p">();</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">initialize</span><span class="p">();</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Zero filled n-dimensional arrays can be created using the shape and data-type of the array as a parameter. Here, the shape is 3x3 and the datatype is the built-in float type:</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">p</span><span class="o">::</span><span class="n">tuple</span> <span class="n">shape</span> <span class="o">=</span> <span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">);</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">dtype</span> <span class="n">dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">dtype</span><span class="o">::</span><span class="n">get_builtin</span><span class="o"><</span><span class="kt">float</span><span class="o">></span><span class="p">();</span>
|
||||
<span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">zeros</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>You can also create an empty array like this</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre><span class="n">np</span><span class="o">::</span><span class="n">ndarray</span> <span class="n">b</span> <span class="o">=</span> <span class="n">np</span><span class="o">::</span><span class="n">empty</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span><span class="n">dtype</span><span class="p">);</span>
|
||||
</pre></div>
|
||||
</div>
|
||||
<p>Print the original and reshaped array. The array a which is a list is first converted to a string, and each value in the list is extracted using extract< >:</p>
|
||||
<div class="highlight-c++"><div class="highlight"><pre> <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Original array:</span><span class="se">\n</span><span class="s">"</span> <span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">a</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
|
||||
|
||||
<span class="c1">// Reshape the array into a 1D array</span>
|
||||
<span class="n">a</span> <span class="o">=</span> <span class="n">a</span><span class="p">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">make_tuple</span><span class="p">(</span><span class="mi">9</span><span class="p">));</span>
|
||||
<span class="c1">// Print it again.</span>
|
||||
<span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o"><<</span> <span class="s">"Reshaped array:</span><span class="se">\n</span><span class="s">"</span> <span class="o"><<</span> <span class="n">p</span><span class="o">::</span><span class="n">extract</span><span class="o"><</span><span class="kt">char</span> <span class="k">const</span> <span class="o">*></span><span class="p">(</span><span class="n">p</span><span class="o">::</span><span class="n">str</span><span class="p">(</span><span class="n">a</span><span class="p">))</span> <span class="o"><<</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
|
||||
<span class="p">}</span>
|
||||
</pre></div>
|
||||
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|
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|
||||
</div>
|
||||
</div>
|
||||
</body>
|
||||
</html>
|
||||
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Reference in New Issue
Block a user