[Numpy-discussion] Simplest ndarray subclass __new__ possible?

[Colin J. Williams]

Zachary Pincus wrote:

> Hi folks,
>
> I'm trying to write an ndarray subclass with a constructor like the  
> matrix constructor -- one which can take matrix objects, array  
> objects, or things that can be turned into array objects.
>
> I've copied the __new__ method from matrix (and tried to eliminate  
> the matrix-specific stuff), but there's a lot of code there. So I'm  
> trying to figure out what the absolute minimum I need is for correct  
> behavior. (This would be a useful wiki entry somewhere. In fact, a  
> whole page about subclassing ndarray would be good.)
>
> What follows is what I have so far. Have I missed anything, or can  
> anything else be removed?
>
> Zach
>
> class contour(numpy.ndarray):
>   def __new__(subtype, data, dtype=None, copy=True):
>
> ##### Do I need this first if block?
> ##### Wouldn't the second block would do fine on its own?
>     if isinstance(data, contour):
>       dtype2 = data.dtype
>       if (dtype is None):
>         dtype = dtype2
>       if (dtype2 == dtype) and (not copy):
>         return data
>       return data.astype(dtype)
>
>     if isinstance(data, numpy.ndarray):
>       if dtype is None:
>         intype = data.dtype
>       else:
>         intype = numpy.dtype(dtype)
>       new = data.view(contour)
>       if intype != data.dtype:
>         return new.astype(intype)
>       if copy: return new.copy()
>       else: return new
>
>     # now convert data to an array
>     arr = numpy.array(data, dtype=dtype, copy=copy)
>
> ##### Do I need this if block?
>     if not (arr.flags.fortran or arr.flags.contiguous):
>       arr = arr.copy()
>
> ##### Do I need the fortran flag?
>     ret = numpy.ndarray.__new__(subtype, arr.shape, arr.dtype,
>                 buffer=arr, fortran=arr.flags.fortran)
>     return ret
>
>
Would there be any merit in breaking this into two parts, __new__ to 
allocate space and __init__ to initialize the data?

Colin W.