A belated thanks...but yes. That does the trick. I've not worked with
views explicitly, so I appreciate the input. I definitely foresee
additional applications of these types of things in the future.
Thanks again,
-Mark
Francesc Altet wrote:
>
> You can always do a view of the rows as strings and then use unique().
> Here is an example:
>
> In [1]: import numpy
> In [2]: a=numpy.arange(12).reshape(4,3)
> In [3]: a[2]=(3,4,5)
> In [4]: a
> Out[4]:
> array([[ 0, 1, 2],
> [ 3, 4, 5],
> [ 3, 4, 5],
> [ 9, 10, 11]])
>
> now, create the view and select the unique rows:
>
> In [5]: b=numpy.unique(a.view('S%d'%a.itemsize*a.shape[0])).view('i4')
>
> and finally restore the shape:
>
> In [6]: b.reshape((len(b)/a.shape[1], a.shape[1]))
> Out[6]:
> array([[ 0, 1, 2],
> [ 3, 4, 5],
> [ 9, 10, 11]])
>
> If you want to find unique columns instead of rows, do a tranpose first
> on the initial array.
>
> Cheers,
>
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