numpy.i

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

/* -*- C -*-  (not really, but good for syntax highlighting) */
#ifdef SWIGPYTHON

%{
#ifndef SWIG_FILE_WITH_INIT
#  define NO_IMPORT_ARRAY
#endif
#include "stdio.h"
#include <numpy/arrayobject.h>
%}

/**********************************************************************/

%fragment("NumPy_Backward_Compatibility", "header")
{
/* Support older NumPy data type names
*/
%#if NDARRAY_VERSION < 0x01000000
%#define NPY_BOOL          PyArray_BOOL
%#define NPY_BYTE          PyArray_BYTE
%#define NPY_UBYTE         PyArray_UBYTE
%#define NPY_SHORT         PyArray_SHORT
%#define NPY_USHORT        PyArray_USHORT
%#define NPY_INT           PyArray_INT
%#define NPY_UINT          PyArray_UINT
%#define NPY_LONG          PyArray_LONG
%#define NPY_ULONG         PyArray_ULONG
%#define NPY_LONGLONG      PyArray_LONGLONG
%#define NPY_ULONGLONG     PyArray_ULONGLONG
%#define NPY_FLOAT         PyArray_FLOAT
%#define NPY_DOUBLE        PyArray_DOUBLE
%#define NPY_LONGDOUBLE    PyArray_LONGDOUBLE
%#define NPY_CFLOAT        PyArray_CFLOAT
%#define NPY_CDOUBLE       PyArray_CDOUBLE
%#define NPY_CLONGDOUBLE   PyArray_CLONGDOUBLE
%#define NPY_OBJECT        PyArray_OBJECT
%#define NPY_STRING        PyArray_STRING
%#define NPY_UNICODE       PyArray_UNICODE
%#define NPY_VOID          PyArray_VOID
%#define NPY_NTYPES        PyArray_NTYPES
%#define NPY_NOTYPE        PyArray_NOTYPE
%#define NPY_CHAR          PyArray_CHAR
%#define NPY_USERDEF       PyArray_USERDEF
%#define npy_intp          intp

%#define NPY_MAX_BYTE      MAX_BYTE
%#define NPY_MIN_BYTE      MIN_BYTE
%#define NPY_MAX_UBYTE     MAX_UBYTE
%#define NPY_MAX_SHORT     MAX_SHORT
%#define NPY_MIN_SHORT     MIN_SHORT
%#define NPY_MAX_USHORT    MAX_USHORT
%#define NPY_MAX_INT       MAX_INT
%#define NPY_MIN_INT       MIN_INT
%#define NPY_MAX_UINT      MAX_UINT
%#define NPY_MAX_LONG      MAX_LONG
%#define NPY_MIN_LONG      MIN_LONG
%#define NPY_MAX_ULONG     MAX_ULONG
%#define NPY_MAX_LONGLONG  MAX_LONGLONG
%#define NPY_MIN_LONGLONG  MIN_LONGLONG
%#define NPY_MAX_ULONGLONG MAX_ULONGLONG
%#define NPY_MAX_INTP      MAX_INTP
%#define NPY_MIN_INTP      MIN_INTP

%#define NPY_FARRAY        FARRAY
%#define NPY_F_CONTIGUOUS  F_CONTIGUOUS
%#endif
}

/**********************************************************************/

/* The following code originally appeared in
 * enthought/kiva/agg/src/numeric.i written by Eric Jones.  It was
 * translated from C++ to C by John Hunter.  Bill Spotz has modified
 * it to fix some minor bugs, upgrade from Numeric to numpy (all
 * versions), add some comments and functionality, and convert from
 * direct code insertion to SWIG fragments.
 */

%fragment("NumPy_Macros", "header")
{
/* Macros to extract array attributes.
 */
%#define is_array(a)            ((a) && PyArray_Check((PyArrayObject *)a))
%#define array_type(a)          (int)(PyArray_TYPE(a))
%#define array_numdims(a)       (((PyArrayObject *)a)->nd)
%#define array_dimensions(a)    (((PyArrayObject *)a)->dimensions)
%#define array_size(a,i)        (((PyArrayObject *)a)->dimensions[i])
%#define array_data(a)          (((PyArrayObject *)a)->data)
%#define array_is_contiguous(a) (PyArray_ISCONTIGUOUS(a))
%#define array_is_native(a)     (PyArray_ISNOTSWAPPED(a))
%#define array_is_fortran(a)    (PyArray_ISFORTRAN(a))
}

/**********************************************************************/

%fragment("NumPy_Utilities", "header")
{
  /* Given a PyObject, return a string describing its type.
   */
  char* pytype_string(PyObject* py_obj) {
    if (py_obj == NULL          ) return "C NULL value";
    if (py_obj == Py_None       ) return "Python None" ;
    if (PyCallable_Check(py_obj)) return "callable"    ;
    if (PyString_Check(  py_obj)) return "string"      ;
    if (PyInt_Check(     py_obj)) return "int"         ;
    if (PyFloat_Check(   py_obj)) return "float"       ;
    if (PyDict_Check(    py_obj)) return "dict"        ;
    if (PyList_Check(    py_obj)) return "list"        ;
    if (PyTuple_Check(   py_obj)) return "tuple"       ;
    if (PyFile_Check(    py_obj)) return "file"        ;
    if (PyModule_Check(  py_obj)) return "module"      ;
    if (PyInstance_Check(py_obj)) return "instance"    ;

    return "unkown type";
  }

  /* Given a NumPy typecode, return a string describing the type.
   */
  char* typecode_string(int typecode) {
    static char* type_names[25] = {"bool", "byte", "unsigned byte",
				   "short", "unsigned short", "int",
				   "unsigned int", "long", "unsigned long",
				   "long long", "unsigned long long",
				   "float", "double", "long double",
				   "complex float", "complex double",
				   "complex long double", "object",
				   "string", "unicode", "void", "ntypes",
				   "notype", "char", "unknown"};
    return typecode < 24 ? type_names[typecode] : type_names[24];
  }

  /* Make sure input has correct numpy type.  Allow character and byte
   * to match.  Also allow int and long to match.  This is deprecated.
   * You should use PyArray_EquivTypenums() instead.
   */
  int type_match(int actual_type, int desired_type) {
    return PyArray_EquivTypenums(actual_type, desired_type);
  }
}

/**********************************************************************/

%fragment("NumPy_Object_to_Array", "header",
	  fragment="NumPy_Backward_Compatibility",
	  fragment="NumPy_Macros",
	  fragment="NumPy_Utilities")
{
  /* Given a PyObject pointer, cast it to a PyArrayObject pointer if
   * legal.  If not, set the python error string appropriately and
   * return NULL.
   */
  PyArrayObject* obj_to_array_no_conversion(PyObject* input, int typecode)
  {
    PyArrayObject* ary = NULL;
    if (is_array(input) && (typecode == NPY_NOTYPE ||
			    PyArray_EquivTypenums(array_type(input), typecode)))
    {
      ary = (PyArrayObject*) input;
    }
    else if is_array(input)
    {
      char* desired_type = typecode_string(typecode);
      char* actual_type  = typecode_string(array_type(input));
      PyErr_Format(PyExc_TypeError, 
		   "Array of type '%s' required.  Array of type '%s' given", 
		   desired_type, actual_type);
      ary = NULL;
    }
    else
    {
      char * desired_type = typecode_string(typecode);
      char * actual_type  = pytype_string(input);
      PyErr_Format(PyExc_TypeError, 
		   "Array of type '%s' required.  A '%s' was given", 
		   desired_type, actual_type);
      ary = NULL;
    }
    return ary;
  }

  /* Convert the given PyObject to a NumPy array with the given
   * typecode.  On success, return a valid PyArrayObject* with the
   * correct type.  On failure, the python error string will be set and
   * the routine returns NULL.
   */
  PyArrayObject* obj_to_array_allow_conversion(PyObject* input, int typecode,
					       int* is_new_object)
  {
    PyArrayObject* ary = NULL;
    PyObject* py_obj;
    if (is_array(input) && (typecode == NPY_NOTYPE ||
			    PyArray_EquivTypenums(array_type(input),typecode)))
    {
      ary = (PyArrayObject*) input;
      *is_new_object = 0;
    }
    else
    {
      py_obj = PyArray_FromObject(input, typecode, 0, 0);
      /* If NULL, PyArray_FromObject will have set python error value.*/
      ary = (PyArrayObject*) py_obj;
      *is_new_object = 1;
    }
    return ary;
  }

  /* Given a PyArrayObject, check to see if it is contiguous.  If so,
   * return the input pointer and flag it as not a new object.  If it is
   * not contiguous, create a new PyArrayObject using the original data,
   * flag it as a new object and return the pointer.
   */
  PyArrayObject* make_contiguous(PyArrayObject* ary, int* is_new_object,
				 int min_dims, int max_dims)
  {
    PyArrayObject* result;
    if (array_is_contiguous(ary))
    {
      result = ary;
      *is_new_object = 0;
    }
    else
    {
      result = (PyArrayObject*) PyArray_ContiguousFromObject((PyObject*)ary, 
							     array_type(ary), 
							     min_dims,
							     max_dims);
      *is_new_object = 1;
    }
    return result;
  }

  /* Convert a given PyObject to a contiguous PyArrayObject of the
   * specified type.  If the input object is not a contiguous
   * PyArrayObject, a new one will be created and the new object flag
   * will be set.
   */
  PyArrayObject* obj_to_array_contiguous_allow_conversion(PyObject* input,
							  int typecode,
							  int* is_new_object)
  {
    int is_new1 = 0;
    int is_new2 = 0;
    PyArrayObject* ary2;
    PyArrayObject* ary1 = obj_to_array_allow_conversion(input, typecode, 
							&is_new1);
    if (ary1)
    {
      ary2 = make_contiguous(ary1, &is_new2, 0, 0);
      if ( is_new1 && is_new2)
      {
	Py_DECREF(ary1);
      }
      ary1 = ary2;    
    }
    *is_new_object = is_new1 || is_new2;
    return ary1;
  }
}

/**********************************************************************/

%fragment("NumPy_Array_Requirements", "header",
	  fragment="NumPy_Backward_Compatibility",
	  fragment="NumPy_Macros")
{
  /* Test whether a python object is contiguous.  If array is
   * contiguous, return 1.  Otherwise, set the python error string and
   * return 0.
   */
  int require_contiguous(PyArrayObject* ary)
  {
    int contiguous = 1;
    if (!array_is_contiguous(ary))
    {
      PyErr_SetString(PyExc_TypeError,
		      "Array must be contiguous.  A non-contiguous array was given");
      contiguous = 0;
    }
    return contiguous;
  }

  /* Require that a numpy array is not byte-swapped.  If the array is
   * not byte-swapped, return 1.  Otherwise, set the python error string
   * and return 0.
   */
  int require_native(PyArrayObject* ary)
  {
    int native = 1;
    if (!array_is_native(ary))
    {
      PyErr_SetString(PyExc_TypeError,
		      "Array must have native byteorder.  "
		      "A byte-swapped array was given");
      native = 0;
    }
    return native;
  }

  /* Require the given PyArrayObject to have a specified number of
   * dimensions.  If the array has the specified number of dimensions,
   * return 1.  Otherwise, set the python error string and return 0.
   */
  int require_dimensions(PyArrayObject* ary, int exact_dimensions)
  {
    int success = 1;
    if (array_numdims(ary) != exact_dimensions)
    {
      PyErr_Format(PyExc_TypeError, 
		   "Array must have %d dimensions.  Given array has %d dimensions", 
		   exact_dimensions, array_numdims(ary));
      success = 0;
    }
    return success;
  }

  /* Require the given PyArrayObject to have one of a list of specified
   * number of dimensions.  If the array has one of the specified number
   * of dimensions, return 1.  Otherwise, set the python error string
   * and return 0.
   */
  int require_dimensions_n(PyArrayObject* ary, int* exact_dimensions, int n)
  {
    int success = 0;
    int i;
    char dims_str[255] = "";
    char s[255];
    for (i = 0; i < n && !success; i++)
    {
      if (array_numdims(ary) == exact_dimensions[i])
      {
	success = 1;
      }
    }
    if (!success)
    {
      for (i = 0; i < n-1; i++)
      {
	sprintf(s, "%d, ", exact_dimensions[i]);                
	strcat(dims_str,s);
      }
      sprintf(s, " or %d", exact_dimensions[n-1]);            
      strcat(dims_str,s);
      PyErr_Format(PyExc_TypeError, 
		   "Array must be have %s dimensions.  Given array has %d dimensions",
		   dims_str, array_numdims(ary));
    }
    return success;
  }    

  /* Require the given PyArrayObject to have a specified shape.  If the
   * array has the specified shape, return 1.  Otherwise, set the python
   * error string and return 0.
   */
  int require_size(PyArrayObject* ary, npy_intp* size, int n)
  {
    int i;
    int success = 1;
    int len;
    char desired_dims[255] = "[";
    char s[255];
    char actual_dims[255] = "[";
    for(i=0; i < n;i++)
    {
      if (size[i] != -1 &&  size[i] != array_size(ary,i))
      {
	success = 0;    
      }
    }
    if (!success)
    {
      for (i = 0; i < n; i++)
      {
	if (size[i] == -1)
	{
	  sprintf(s, "*,");                
	}
	else
	{
	  sprintf(s, "%ld,", (long int)size[i]);                
	}    
	strcat(desired_dims,s);
      }
      len = strlen(desired_dims);
      desired_dims[len-1] = ']';
      for (i = 0; i < n; i++)
      {
	sprintf(s, "%ld,", (long int)array_size(ary,i));                            
	strcat(actual_dims,s);
      }
      len = strlen(actual_dims);
      actual_dims[len-1] = ']';
      PyErr_Format(PyExc_TypeError, 
		   "Array must be have shape of %s.  Given array has shape of %s",
		   desired_dims, actual_dims);
    }
    return success;