numpy.i

一个人工神经网络的程序。 文档等说明参见http://aureservoir.sourceforge.net/

  }

  /* Require the given PyArrayObject to to be FORTRAN ordered.  If the
   * the PyArrayObject is already FORTRAN ordered, do nothing.  Else,
   * set the FORTRAN ordering flag and recompute the strides.
   */
  int require_fortran(PyArrayObject* ary)
  {
    int success = 1;
    int nd = array_numdims(ary);
    int i;
    if (array_is_fortran(ary)) return success;
    /* Set the FORTRAN ordered flag */
    ary->flags = NPY_FARRAY;
    /* Recompute the strides */
    ary->strides[0] = ary->strides[nd-1];
    for (i=1; i < nd; ++i)
      ary->strides[i] = ary->strides[i-1] * array_size(ary,i-1);
    return success;
  }
}

/* Combine all NumPy fragments into one for convenience */
%fragment("NumPy_Fragments", "header",
	  fragment="NumPy_Backward_Compatibility",
	  fragment="NumPy_Macros",
	  fragment="NumPy_Utilities",
	  fragment="NumPy_Object_to_Array",
	  fragment="NumPy_Array_Requirements") { }

/* End John Hunter translation (with modifications by Bill Spotz)
 */

/* %numpy_typemaps() macro
 *
 * This macro defines a family of 41 typemaps that allow C arguments
 * of the form
 *
 *     (DATA_TYPE IN_ARRAY1[ANY])
 *     (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1)
 *     (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1)
 *
 *     (DATA_TYPE IN_ARRAY2[ANY][ANY])
 *     (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
 *     (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2)
 *     (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
 *     (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2)
 *
 *     (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY])
 *     (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
 *     (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_ARRAY3)
 *     (DATA_TYPE* IN_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
 *     (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* IN_FARRAY3)
 *
 *     (DATA_TYPE INPLACE_ARRAY1[ANY])
 *     (DATA_TYPE* INPLACE_ARRAY1, DIM_TYPE DIM1)
 *     (DIM_TYPE DIM1, DATA_TYPE* INPLACE_ARRAY1)
 *
 *     (DATA_TYPE INPLACE_ARRAY2[ANY][ANY])
 *     (DATA_TYPE* INPLACE_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
 *     (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_ARRAY2)
 *     (DATA_TYPE* INPLACE_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
 *     (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* INPLACE_FARRAY2)
 *
 *     (DATA_TYPE INPLACE_ARRAY3[ANY][ANY][ANY])
 *     (DATA_TYPE* INPLACE_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
 *     (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_ARRAY3)
 *     (DATA_TYPE* INPLACE_FARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3)
 *     (DIM_TYPE DIM1, DIM_TYPE DIM2, DIM_TYPE DIM3, DATA_TYPE* INPLACE_FARRAY3)
 *
 *     (DATA_TYPE ARGOUT_ARRAY1[ANY])
 *     (DATA_TYPE* ARGOUT_ARRAY1, DIM_TYPE DIM1)
 *     (DIM_TYPE DIM1, DATA_TYPE* ARGOUT_ARRAY1)
 *
 *     (DATA_TYPE ARGOUT_ARRAY2[ANY][ANY])
 *
 *     (DATA_TYPE ARGOUT_ARRAY3[ANY][ANY][ANY])
 *
 *     (DATA_TYPE** ARGOUTVIEW_ARRAY1, DIM_TYPE* DIM1)
 *     (DIM_TYPE* DIM1, DATA_TYPE** ARGOUTVIEW_ARRAY1)
 *
 *     (DATA_TYPE** ARGOUTVIEW_ARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
 *     (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_ARRAY2)
 *     (DATA_TYPE** ARGOUTVIEW_FARRAY2, DIM_TYPE* DIM1, DIM_TYPE* DIM2)
 *     (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DATA_TYPE** ARGOUTVIEW_FARRAY2)
 *
 *     (DATA_TYPE** ARGOUTVIEW_ARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
 *     (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_ARRAY3)
 *     (DATA_TYPE** ARGOUTVIEW_FARRAY3, DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3)
 *     (DIM_TYPE* DIM1, DIM_TYPE* DIM2, DIM_TYPE* DIM3, DATA_TYPE** ARGOUTVIEW_FARRAY3)
 *
 * where "DATA_TYPE" is any type supported by the NumPy module, and
 * "DIM_TYPE" is any int-like type suitable for specifying dimensions.
 * The difference between "ARRAY" typemaps and "FARRAY" typemaps is
 * that the "FARRAY" typemaps expect FORTRAN ordering of
 * multidimensional arrays.  In python, the dimensions will not need
 * to be specified (except for the "DATA_TYPE* ARGOUT_ARRAY1"
 * typemaps).  The IN_ARRAYs can be a numpy array or any sequence that
 * can be converted to a numpy array of the specified type.  The
 * INPLACE_ARRAYs must be numpy arrays of the appropriate type.  The
 * ARGOUT_ARRAYs will be returned as new numpy arrays of the
 * appropriate type.
 *
 * These typemaps can be applied to existing functions using the
 * %apply directive.  For example:
 *
 *     %apply (double* IN_ARRAY1, int DIM1) {(double* series, int length)};
 *     double prod(double* series, int length);
 *
 *     %apply (int DIM1, int DIM2, double* INPLACE_ARRAY2)
 *           {(int rows, int cols, double* matrix        )};
 *     void floor(int rows, int cols, double* matrix, double f);
 *
 *     %apply (double IN_ARRAY3[ANY][ANY][ANY])
 *           {(double tensor[2][2][2]         )};
 *     %apply (double ARGOUT_ARRAY3[ANY][ANY][ANY])
 *           {(double low[2][2][2]                )};
 *     %apply (double ARGOUT_ARRAY3[ANY][ANY][ANY])
 *           {(double upp[2][2][2]                )};
 *     void luSplit(double tensor[2][2][2],
 *                  double low[2][2][2],
 *                  double upp[2][2][2]    );
 *
 * or directly with
 *
 *     double prod(double* IN_ARRAY1, int DIM1);
 *
 *     void floor(int DIM1, int DIM2, double* INPLACE_ARRAY2, double f);
 *
 *     void luSplit(double IN_ARRAY3[ANY][ANY][ANY],
 *                  double ARGOUT_ARRAY3[ANY][ANY][ANY],
 *                  double ARGOUT_ARRAY3[ANY][ANY][ANY]);
 */

%define %numpy_typemaps(DATA_TYPE, DATA_TYPECODE, DIM_TYPE)

/************************/
/* Input Array Typemaps */
/************************/

/* Typemap suite for (DATA_TYPE IN_ARRAY1[ANY])
 */
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
	   fragment="NumPy_Macros")
  (DATA_TYPE IN_ARRAY1[ANY])
{
  $1 = is_array($input) || PySequence_Check($input);
}
%typemap(in,
	 fragment="NumPy_Fragments")
  (DATA_TYPE IN_ARRAY1[ANY])
  (PyArrayObject* array=NULL, int is_new_object=0)
{
  npy_intp size[1] = { $1_dim0 };
  array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
						   &is_new_object);
  if (!array || !require_dimensions(array, 1) ||
      !require_size(array, size, 1)) SWIG_fail;
  $1 = ($1_ltype) array_data(array);
}
%typemap(freearg)
  (DATA_TYPE IN_ARRAY1[ANY])
{
  if (is_new_object$argnum && array$argnum)
    { Py_DECREF(array$argnum); }
}

/* Typemap suite for (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1)
 */
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
	   fragment="NumPy_Macros")
  (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1)
{
  $1 = is_array($input) || PySequence_Check($input);
}
%typemap(in,
	 fragment="NumPy_Fragments")
  (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1)
  (PyArrayObject* array=NULL, int is_new_object=0)
{
  npy_intp size[1] = { -1 };
  array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
						   &is_new_object);
  if (!array || !require_dimensions(array, 1) ||
      !require_size(array, size, 1)) SWIG_fail;
  $1 = (DATA_TYPE*) array_data(array);
  $2 = (DIM_TYPE) array_size(array,0);
}
%typemap(freearg)
  (DATA_TYPE* IN_ARRAY1, DIM_TYPE DIM1)
{
  if (is_new_object$argnum && array$argnum)
    { Py_DECREF(array$argnum); }
}

/* Typemap suite for (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1)
 */
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
	   fragment="NumPy_Macros")
  (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1)
{
  $1 = is_array($input) || PySequence_Check($input);
}
%typemap(in,
	 fragment="NumPy_Fragments")
  (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1)
  (PyArrayObject* array=NULL, int is_new_object=0)
{
  npy_intp size[1] = {-1};
  array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
						   &is_new_object);
  if (!array || !require_dimensions(array, 1) ||
      !require_size(array, size, 1)) SWIG_fail;
  $1 = (DIM_TYPE) array_size(array,0);
  $2 = (DATA_TYPE*) array_data(array);
}
%typemap(freearg)
  (DIM_TYPE DIM1, DATA_TYPE* IN_ARRAY1)
{
  if (is_new_object$argnum && array$argnum)
    { Py_DECREF(array$argnum); }
}

/* Typemap suite for (DATA_TYPE IN_ARRAY2[ANY][ANY])
 */
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
	   fragment="NumPy_Macros")
  (DATA_TYPE IN_ARRAY2[ANY][ANY])
{
  $1 = is_array($input) || PySequence_Check($input);
}
%typemap(in,
	 fragment="NumPy_Fragments")
  (DATA_TYPE IN_ARRAY2[ANY][ANY])
  (PyArrayObject* array=NULL, int is_new_object=0)
{
  npy_intp size[2] = { $1_dim0, $1_dim1 };
  array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
						   &is_new_object);
  if (!array || !require_dimensions(array, 2) ||
      !require_size(array, size, 2)) SWIG_fail;
  $1 = ($1_ltype) array_data(array);
}
%typemap(freearg)
  (DATA_TYPE IN_ARRAY2[ANY][ANY])
{
  if (is_new_object$argnum && array$argnum)
    { Py_DECREF(array$argnum); }
}

/* Typemap suite for (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
 */
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
	   fragment="NumPy_Macros")
  (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
{
  $1 = is_array($input) || PySequence_Check($input);
}
%typemap(in,
	 fragment="NumPy_Fragments")
  (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
  (PyArrayObject* array=NULL, int is_new_object=0)
{
  npy_intp size[2] = { -1, -1 };
  array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
						   &is_new_object);
  if (!array || !require_dimensions(array, 2) ||
      !require_size(array, size, 2)) SWIG_fail;
  $1 = (DATA_TYPE*) array_data(array);
  $2 = (DIM_TYPE) array_size(array,0);
  $3 = (DIM_TYPE) array_size(array,1);
}
%typemap(freearg)
  (DATA_TYPE* IN_ARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
{
  if (is_new_object$argnum && array$argnum)
    { Py_DECREF(array$argnum); }
}

/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2)
 */
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
	   fragment="NumPy_Macros")
  (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2)
{
  $1 = is_array($input) || PySequence_Check($input);
}
%typemap(in,
	 fragment="NumPy_Fragments")
  (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2)
  (PyArrayObject* array=NULL, int is_new_object=0)
{
  npy_intp size[2] = { -1, -1 };
  array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
						   &is_new_object);
  if (!array || !require_dimensions(array, 2) ||
      !require_size(array, size, 2)) SWIG_fail;
  $1 = (DIM_TYPE) array_size(array,0);
  $2 = (DIM_TYPE) array_size(array,1);
  $3 = (DATA_TYPE*) array_data(array);
}
%typemap(freearg)
  (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_ARRAY2)
{
  if (is_new_object$argnum && array$argnum)
    { Py_DECREF(array$argnum); }
}

/* Typemap suite for (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
 */
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
	   fragment="NumPy_Macros")
  (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
{
  $1 = is_array($input) || PySequence_Check($input);
}
%typemap(in,
	 fragment="NumPy_Fragments")
  (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
  (PyArrayObject* array=NULL, int is_new_object=0)
{
  npy_intp size[2] = { -1, -1 };
  array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
						   &is_new_object);
  if (!array || !require_dimensions(array, 2) ||
      !require_size(array, size, 2) || !require_fortran(array)) SWIG_fail;
  $1 = (DATA_TYPE*) array_data(array);
  $2 = (DIM_TYPE) array_size(array,0);
  $3 = (DIM_TYPE) array_size(array,1);
}
%typemap(freearg)
  (DATA_TYPE* IN_FARRAY2, DIM_TYPE DIM1, DIM_TYPE DIM2)
{
  if (is_new_object$argnum && array$argnum)
    { Py_DECREF(array$argnum); }
}

/* Typemap suite for (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2)
 */
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
	   fragment="NumPy_Macros")
  (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2)
{
  $1 = is_array($input) || PySequence_Check($input);
}
%typemap(in,
	 fragment="NumPy_Fragments")
  (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2)
  (PyArrayObject* array=NULL, int is_new_object=0)
{
  npy_intp size[2] = { -1, -1 };
  array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
						   &is_new_object);
  if (!array || !require_dimensions(array, 2) ||
      !require_size(array, size, 2) || !require_fortran(array)) SWIG_fail;
  $1 = (DIM_TYPE) array_size(array,0);
  $2 = (DIM_TYPE) array_size(array,1);
  $3 = (DATA_TYPE*) array_data(array);
}
%typemap(freearg)
  (DIM_TYPE DIM1, DIM_TYPE DIM2, DATA_TYPE* IN_FARRAY2)
{
  if (is_new_object$argnum && array$argnum)
    { Py_DECREF(array$argnum); }
}

/* Typemap suite for (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY])
 */
%typecheck(SWIG_TYPECHECK_DOUBLE_ARRAY,
	   fragment="NumPy_Macros")
  (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY])
{
  $1 = is_array($input) || PySequence_Check($input);
}
%typemap(in,
	 fragment="NumPy_Fragments")
  (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY])
  (PyArrayObject* array=NULL, int is_new_object=0)
{
  npy_intp size[3] = { $1_dim0, $1_dim1, $1_dim2 };
  array = obj_to_array_contiguous_allow_conversion($input, DATA_TYPECODE,
						   &is_new_object);
  if (!array || !require_dimensions(array, 3) ||
      !require_size(array, size, 3)) SWIG_fail;
  $1 = ($1_ltype) array_data(array);
}
%typemap(freearg)
  (DATA_TYPE IN_ARRAY3[ANY][ANY][ANY])
{
  if (is_new_object$argnum && array$argnum)
    { Py_DECREF(array$argnum); }
}

/* Typemap suite for (DATA_TYPE* IN_ARRAY3, DIM_TYPE DIM1, DIM_TYPE DIM2,
 *                    DIM_TYPE DIM3)
 */