parameters: (a)
return_statement: return a.flags.fnc
docstring: Check if the array is Fortran contiguous but *not* C contiguous.
  
      This function is obsolete and, because of changes due to relaxed stride
      checking, its return value for the same array may differ for versions
      of NumPy >= 1.10.0 and previous versions. If you only want to check if an
      array is Fortran contiguous use ``a.flags.f_contiguous`` instead.
  
      Parameters
      ----------
      a : ndarray
          Input array.
  
      Returns
      -------
      isfortran : bool
          Returns True if the array is Fortran contiguous but *not* C contiguous.
  
  
      Examples
      --------
  
      np.array allows to specify whether the array is written in C-contiguous
      order (last index varies the fastest), or FORTRAN-contiguous order in
      memory (first index varies the fastest).
  
      >>> a = np.array([[1, 2, 3], [4, 5, 6]], order='C')
      >>> a
      array([[1, 2, 3],
             [4, 5, 6]])
      >>> np.isfortran(a)
      False
  
      >>> b = np.array([[1, 2, 3], [4, 5, 6]], order='F')
      >>> b
      array([[1, 2, 3],
             [4, 5, 6]])
      >>> np.isfortran(b)
      True
  
  
      The transpose of a C-ordered array is a FORTRAN-ordered array.
  
      >>> a = np.array([[1, 2, 3], [4, 5, 6]], order='C')
      >>> a
      array([[1, 2, 3],
             [4, 5, 6]])
      >>> np.isfortran(a)
      False
      >>> b = a.T
      >>> b
      array([[1, 4],
             [2, 5],
             [3, 6]])
      >>> np.isfortran(b)
      True
  
      C-ordered arrays evaluate as False even if they are also FORTRAN-ordered.
  
      >>> np.isfortran(np.array([1, 2], order='F'))
      False
docstring_summary: Check if the array is Fortran contiguous but *not* C contiguous.
docstring_tokens: Check if the array is Fortran contiguous but * not * C contiguous .
function: def isfortran(a):
      """
      Check if the array is Fortran contiguous but *not* C contiguous.
  
      This function is obsolete and, because of changes due to relaxed stride
      checking, its return value for the same array may differ for versions
      of NumPy >= 1.10.0 and previous versions. If you only want to check if an
      array is Fortran contiguous use ``a.flags.f_contiguous`` instead.
  
      Parameters
      ----------
      a : ndarray
          Input array.
  
      Returns
      -------
      isfortran : bool
          Returns True if the array is Fortran contiguous but *not* C contiguous.
  
  
      Examples
      --------
  
      np.array allows to specify whether the array is written in C-contiguous
      order (last index varies the fastest), or FORTRAN-contiguous order in
      memory (first index varies the fastest).
  
      >>> a = np.array([[1, 2, 3], [4, 5, 6]], order='C')
      >>> a
      array([[1, 2, 3],
             [4, 5, 6]])
      >>> np.isfortran(a)
      False
  
      >>> b = np.array([[1, 2, 3], [4, 5, 6]], order='F')
      >>> b
      array([[1, 2, 3],
             [4, 5, 6]])
      >>> np.isfortran(b)
      True
  
  
      The transpose of a C-ordered array is a FORTRAN-ordered array.
  
      >>> a = np.array([[1, 2, 3], [4, 5, 6]], order='C')
      >>> a
      array([[1, 2, 3],
             [4, 5, 6]])
      >>> np.isfortran(a)
      False
      >>> b = a.T
      >>> b
      array([[1, 4],
             [2, 5],
             [3, 6]])
      >>> np.isfortran(b)
      True
  
      C-ordered arrays evaluate as False even if they are also FORTRAN-ordered.
  
      >>> np.isfortran(np.array([1, 2], order='F'))
      False
  
      """
      return a.flags.fnc
function_tokens: def isfortran ( a ) : return a . flags . fnc