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Boost-Commit : |
Subject: [Boost-commit] svn:boost r75172 - sandbox/numpy/libs/numpy/doc/reference
From: seefeld_at_[hidden]
Date: 2011-10-29 16:39:38
Author: stefan
Date: 2011-10-29 16:39:37 EDT (Sat, 29 Oct 2011)
New Revision: 75172
URL: http://svn.boost.org/trac/boost/changeset/75172
Log:
Fix formatting issues in the Reference Manual.
Text files modified:
sandbox/numpy/libs/numpy/doc/reference/binary_ufunc.rst | 95 ++++++++-------
sandbox/numpy/libs/numpy/doc/reference/dtype.rst | 63 +++++-----
sandbox/numpy/libs/numpy/doc/reference/multi_iter.rst | 67 +++++------
sandbox/numpy/libs/numpy/doc/reference/ndarray.rst | 236 ++++++++++++++++++++-------------------
sandbox/numpy/libs/numpy/doc/reference/unary_ufunc.rst | 80 +++++++-----
5 files changed, 280 insertions(+), 261 deletions(-)
Modified: sandbox/numpy/libs/numpy/doc/reference/binary_ufunc.rst
==============================================================================
--- sandbox/numpy/libs/numpy/doc/reference/binary_ufunc.rst (original)
+++ sandbox/numpy/libs/numpy/doc/reference/binary_ufunc.rst 2011-10-29 16:39:37 EDT (Sat, 29 Oct 2011)
@@ -13,24 +13,29 @@
::
- namespace boost
- {
- namespace numpy
- {
+ namespace boost
+ {
+ 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 python::object call(TBinaryFunctor & self,
+ python::object const & input1,
+ python::object const & input2,
+ python::object const & output);
- template <typename TBinaryFunctor,typename TArgument1=typename TBinaryFunctor::first_argument_type,typename TArgument2=typename
- TBinaryFunctor::second_argument_type,typename TResult=typename TBinaryFunctor::result_type>
+ static python::object make();
+ };
- struct binary_ufunc
- {
-
- static python::object call(TBinaryFunctor & self, python::object const & input1, python::object const & input2,python::object const & output)
-
- static python::object make();
-
- }
- }
- }
+ }
+ }
constructors
@@ -38,12 +43,12 @@
::
- struct example_binary_ufunc
- {
- typedef any_valid first_argument_type;
- typedef any_valid second_argument_type;
- typedef any_valid result_type;
- };
+ 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
@@ -54,9 +59,13 @@
::
- template <typename TBinaryFunctor,typename TArgument1=typename TBinaryFunctor::first_argument_type,typename TArgument2=typename
- TBinaryFunctor::second_argument_type,typename TResult=typename TBinaryFunctor::result_type>
- static python::object call(TBinaryFunctor & self, python::object const & input, python::object const & output) ;
+ template <typename TBinaryFunctor,
+ typename TArgument1=typename TBinaryFunctor::first_argument_type,
+ typename TArgument2=typename TBinaryFunctor::second_argument_type,
+ typename TResult=typename TBinaryFunctor::result_type>
+ static python::object call(TBinaryFunctor & self,
+ python::object const & input,
+ python::object const & output);
:Requires: Typenames ``TBinaryFunctor`` and optionally ``TArgument1`` and ``TArgument2`` for argument type and ``TResult`` for result type
@@ -64,32 +73,32 @@
::
- template <typename TBinaryFunctor,typename TArgument1=typename TBinaryFunctor::first_argument_type,typename TArgument2=typename,
- TBinaryFunctor::second_argument_type,typename TResult=typename TBinaryFunctor::result_type>
- static python::object make();
+ template <typename TBinaryFunctor,
+ typename TArgument1=typename TBinaryFunctor::first_argument_type,
+ typename TArgument2=typename TBinaryFunctor::second_argument_type,
+ typename TResult=typename TBinaryFunctor::result_type>
+ static python::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)
----------
::
- 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 ;
+ 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 ;
Modified: sandbox/numpy/libs/numpy/doc/reference/dtype.rst
==============================================================================
--- sandbox/numpy/libs/numpy/doc/reference/dtype.rst (original)
+++ sandbox/numpy/libs/numpy/doc/reference/dtype.rst 2011-10-29 16:39:37 EDT (Sat, 29 Oct 2011)
@@ -15,38 +15,39 @@
::
- namespace boost
- {
- namespace numpy
- {
-
- class dtype : public python::object
- {
- static python::detail::new_reference convert(python::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;
- };
+ namespace boost
+ {
+ namespace numpy
+ {
+
+ class dtype : public python::object
+ {
+ static python::detail::new_reference convert(python::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)
+ template <typename T>
+ explicit dtype(T arg, bool align=false)
+
+:Requirements: ``T`` must be either :
-:Requirements: The typename supplied, ``T`` must be either :
* a built-in C++ typename convertible to object
* a valid python object or convertible to object
@@ -57,7 +58,7 @@
::
- template <typename T> static dtype get_builtin();
+ template <typename T> static dtype get_builtin();
:Requirements: The typename supplied, ``T`` must be a builtin C++ type also supported by numpy
@@ -68,7 +69,7 @@
::
- int get_itemsize() const;
+ int get_itemsize() const;
:Returns: the size of the data type in bytes.
@@ -78,10 +79,8 @@
::
- namespace np = boost::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) ;
+ namespace np = boost::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);
Modified: sandbox/numpy/libs/numpy/doc/reference/multi_iter.rst
==============================================================================
--- sandbox/numpy/libs/numpy/doc/reference/multi_iter.rst (original)
+++ sandbox/numpy/libs/numpy/doc/reference/multi_iter.rst 2011-10-29 16:39:37 EDT (Sat, 29 Oct 2011)
@@ -13,32 +13,29 @@
::
- namespace boost
- {
- namespace numpy
- {
-
- class multi_iter : public python::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(python::object const & a1);
-
- multi_iter make_multi_iter(python::object const & a1, python::object const & a2);
+ namespace boost
+ {
+ namespace numpy
+ {
+
+ class multi_iter : public python::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(python::object const & a1);
+ multi_iter make_multi_iter(python::object const & a1, python::object const & a2);
+ multi_iter make_multi_iter(python::object const & a1, python::object const & a2, python::object const & a3);
- multi_iter make_multi_iter(python::object const & a1, python::object const & a2, python::object const & a3);
-
- }
- } // namespace boost::numpy
+ }
+ }
constructors
@@ -46,11 +43,9 @@
::
- multi_iter make_multi_iter(python::object const & a1);
-
- multi_iter make_multi_iter(python::object const & a1, python::object const & a2);
-
- multi_iter make_multi_iter(python::object const & a1, python::object const & a2, python::object const & a3);
+ multi_iter make_multi_iter(python::object const & a1);
+ multi_iter make_multi_iter(python::object const & a1, python::object const & a2);
+ multi_iter make_multi_iter(python::object const & a1, python::object const & a2, python::object const & a3);
:Returns: A Python iterator object broadcasting over one, two or three sequences as supplied
@@ -59,37 +54,37 @@
::
- void next();
+ void next();
:Effects: Increments the iterator
::
- bool not_done() const;
+ bool not_done() const;
:Returns: boolean value indicating whether the iterator is at its end
::
- char * get_data(int n) const;
+ char * get_data(int n) const;
:Returns: a pointer to the element of the nth broadcasted array.
::
- int const get_nd() const;
+ int const get_nd() const;
:Returns: the number of dimensions of the broadcasted array expression
::
- Py_intptr_t const * get_shape() const;
+ 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;
+ Py_intptr_t const shape(int n) const;
:Returns: the shape of the broadcasted array expression in the nth dimension.
Modified: sandbox/numpy/libs/numpy/doc/reference/ndarray.rst
==============================================================================
--- sandbox/numpy/libs/numpy/doc/reference/ndarray.rst (original)
+++ sandbox/numpy/libs/numpy/doc/reference/ndarray.rst 2011-10-29 16:39:37 EDT (Sat, 29 Oct 2011)
@@ -17,73 +17,70 @@
::
- namespace boost
- {
- namespace numpy
- {
-
- class ndarray : public python::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 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(python::tuple const & shape) const;
-
- python::object scalarize() const;
- };
-
- ndarray zeros(python::tuple const & shape, dtype const & dt);
- ndarray zeros(int nd, Py_intptr_t const * shape, dtype const & dt);
-
- ndarray empty(python::tuple const & shape, dtype const & dt);
- ndarray empty(int nd, Py_intptr_t const * shape, dtype const & dt);
-
- ndarray array(python::object const & obj);
- ndarray array(python::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, python::object const & owner);
-
- ndarray from_object(python::object const & obj, dtype const & dt,int nd_min, int nd_max, ndarray::bitflag flags=ndarray::NONE);
- ndarray from_object(python::object const & obj, dtype const & dt,int nd, ndarray::bitflag flags=ndarray::NONE);
- ndarray from_object(python::object const & obj, dtype const & dt, ndarray::bitflag flags=ndarray::NONE);
- ndarray from_object(python::object const & obj, int nd_min, int nd_max,ndarray::bitflag flags=ndarray::NONE);
- ndarray from_object(python::object const & obj, int nd, ndarray::bitflag flags=ndarray::NONE);
- ndarray from_object(python::object const & obj, ndarray::bitflag flags=ndarray::NONE)
+ namespace boost
+ {
+ namespace numpy
+ {
- ndarray::bitflag operator|(ndarray::bitflag a, ndarray::bitflag b) ;
- ndarray::bitflag operator&(ndarray::bitflag a, ndarray::bitflag b);
+ class ndarray : public python::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 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(python::tuple const & shape) const;
+ python::object scalarize() const;
+ };
+
+ ndarray zeros(python::tuple const & shape, dtype const & dt);
+ ndarray zeros(int nd, Py_intptr_t const * shape, dtype const & dt);
+
+ ndarray empty(python::tuple const & shape, dtype const & dt);
+ ndarray empty(int nd, Py_intptr_t const * shape, dtype const & dt);
+
+ ndarray array(python::object const & obj);
+ ndarray array(python::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, python::object const & owner);
+
+ ndarray from_object(python::object const & obj, dtype const & dt,int nd_min, int nd_max, ndarray::bitflag flags=ndarray::NONE);
+ ndarray from_object(python::object const & obj, dtype const & dt,int nd, ndarray::bitflag flags=ndarray::NONE);
+ ndarray from_object(python::object const & obj, dtype const & dt, ndarray::bitflag flags=ndarray::NONE);
+ ndarray from_object(python::object const & obj, int nd_min, int nd_max,ndarray::bitflag flags=ndarray::NONE);
+ ndarray from_object(python::object const & obj, int nd, ndarray::bitflag flags=ndarray::NONE);
+ ndarray from_object(python::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
@@ -91,31 +88,31 @@
::
- ndarray view(dtype const & dt) const;
+ ndarray view(dtype const & dt) const;
:Returns: new ndarray with old ndarray data cast as supplied dtype
::
- ndarray copy() const;
+ ndarray copy() const;
:Returns: Copy of calling ndarray object
::
- ndarray transpose() const;
+ ndarray transpose() const;
:Returns: An ndarray with the rows and columns interchanged
::
- ndarray squeeze() const;
+ ndarray squeeze() const;
:Returns: An ndarray with all unit-shaped dimensions removed
::
- ndarray reshape(python::tuple const & shape) const;
+ ndarray reshape(python::tuple const & shape) const;
:Requirements: The new ``shape`` of the ndarray must be supplied as a tuple
@@ -124,16 +121,17 @@
::
- python::object scalarize() const;
+ python::object scalarize() const;
:Returns: A scalar if the ndarray has only one element, otherwise it returns the entire array
::
- ndarray zeros(python::tuple const & shape, dtype const & dt);
- ndarray zeros(int nd, Py_intptr_t const * shape, dtype const & dt);
+ ndarray zeros(python::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
@@ -143,11 +141,12 @@
::
- ndarray empty(python::tuple const & shape, dtype const & dt);
- ndarray empty(int nd, Py_intptr_t const * shape, dtype const & dt);
+ ndarray empty(python::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
@@ -156,17 +155,18 @@
::
- ndarray array(python::object const & obj);
- ndarray array(python::object const & obj, dtype const & dt);
+ ndarray array(python::object const & obj);
+ ndarray array(python::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)
+ 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
@@ -179,9 +179,10 @@
::
- ndarray from_object(python::object const & obj, dtype const & dt,int nd_min, int nd_max, ndarray::bitflag flags=ndarray::NONE);
+ ndarray from_object(python::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
@@ -192,9 +193,10 @@
::
- inline ndarray from_object(python::object const & obj, dtype const & dt, int nd, ndarray::bitflag flags=ndarray::NONE);
+ inline ndarray from_object(python::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
@@ -204,9 +206,10 @@
::
- inline ndarray from_object(python::object const & obj, dtype const & dt, ndarray::bitflag flags=ndarray::NONE)
+ inline ndarray from_object(python::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
@@ -215,9 +218,10 @@
::
- ndarray from_object(python::object const & obj, int nd_min, int nd_max, ndarray::bitflag flags=ndarray::NONE);
+ ndarray from_object(python::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
@@ -229,9 +233,10 @@
::
- inline ndarray from_object(python::object const & obj, int nd, ndarray::bitflag flags=ndarray::NONE);
+ inline ndarray from_object(python::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
@@ -241,9 +246,10 @@
::
- inline ndarray from_object(python::object const & obj, ndarray::bitflag flags=ndarray::NONE)
+ inline ndarray from_object(python::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
@@ -255,19 +261,19 @@
::
- int const shape(int n) const;
+ int const shape(int n) const;
:Returns: The size of the n-th dimension of the ndarray
::
- int const strides(int n) const;
+ int const strides(int n) const;
:Returns: The stride of the nth dimension.
::
- char * get_data() const;
+ char * get_data() const;
:Returns: Array's raw data pointer as a char
@@ -275,61 +281,61 @@
::
- dtype get_dtype() const;
+ dtype get_dtype() const;
:Returns: Array's data-type descriptor object (dtype)
::
- python::object get_base() const;
+ python::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);
+ 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;
+ Py_intptr_t const * get_shape() const;
:Returns: Shape of the array as an array of integers
::
- Py_intptr_t const * get_strides() const;
+ Py_intptr_t const * get_strides() const;
:Returns: Stride of the array as an array of integers
::
- int const get_nd() const;
+ int const get_nd() const;
:Returns: Number of array dimensions
::
- bitflag const get_flags() const;
+ bitflag const get_flags() const;
:Returns: Array flags
::
- inline ndarray::bitflag operator|(ndarray::bitflag a, ndarray::bitflag b)
+ 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)
+ inline ndarray::bitflag operator&(ndarray::bitflag a, ndarray::bitflag b)
:Returns: bitflag logically AND-ed as (a & b)
@@ -339,26 +345,26 @@
::
- p::object tu = p::make_tuple('a','b','c') ;
- np::ndarray example_tuple = np::array (tu) ;
+ 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) ;
+ 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);
+ 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>();
+ 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());
+ 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());
Modified: sandbox/numpy/libs/numpy/doc/reference/unary_ufunc.rst
==============================================================================
--- sandbox/numpy/libs/numpy/doc/reference/unary_ufunc.rst (original)
+++ sandbox/numpy/libs/numpy/doc/reference/unary_ufunc.rst 2011-10-29 16:39:37 EDT (Sat, 29 Oct 2011)
@@ -13,22 +13,26 @@
::
- namespace boost
- {
- namespace numpy
- {
-
- template <typename TUnaryFunctor, typename TArgument=typename TUnaryFunctor::argument_type, typename TResult=typename TUnaryFunctor::result_type>
- struct unary_ufunc
- {
-
- static python::object call(TUnaryFunctor & self, python::object const & input, python::object const & output) ;
-
- static python::object make();
-
- }
- }
- }
+ namespace boost
+ {
+ namespace numpy
+ {
+
+ template <typename TUnaryFunctor,
+ typename TArgument=typename TUnaryFunctor::argument_type,
+ typename TResult=typename TUnaryFunctor::result_type>
+ struct unary_ufunc
+ {
+
+ static python::object call(TUnaryFunctor & self,
+ python::object const & input,
+ python::object const & output) ;
+
+ static python::object make();
+
+ };
+ }
+ }
constructors
@@ -36,11 +40,11 @@
::
- struct example_unary_ufunc
- {
- typedef any_valid_type argument_type;
- typedef any_valid_type result_type;
- };
+ 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
@@ -51,8 +55,12 @@
::
- template <typename TUnaryFunctor, typename TArgument=typename TUnaryFunctor::argument_type,typename TResult=typename TUnaryFunctor::result_type>
- static python::object call(TUnaryFunctor & self, python::object const & input, python::object const & output) ;
+ template <typename TUnaryFunctor,
+ typename TArgument=typename TUnaryFunctor::argument_type,
+ typename TResult=typename TUnaryFunctor::result_type>
+ static python::object call(TUnaryFunctor & self,
+ python::object const & input,
+ python::object const & output);
:Requires: Typenames ``TUnaryFunctor`` and optionally ``TArgument`` for argument type and ``TResult`` for result type
@@ -60,8 +68,10 @@
::
- template <typename TUnaryFunctor, typename TArgument=typename TUnaryFunctor::argument_type,typename TResult=typename TUnaryFunctor::result_type>
- static python::object make();
+ template <typename TUnaryFunctor,
+ typename TArgument=typename TUnaryFunctor::argument_type,
+ typename TResult=typename TUnaryFunctor::result_type>
+ static python::object make();
:Requires: Typenames ``TUnaryFunctor`` and optionally ``TArgument`` for argument type and ``TResult`` for result type
@@ -74,14 +84,14 @@
::
- 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 ;
+ 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 ;
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