[Numpy-discussion] unique rows of array
Maria Liukis
liukis@usc....
Mon Aug 17 23:30:46 CDT 2009
Hello everybody,
While re-implementing some Matlab code in Python, I've run into a
problem of finding a NumPy function analogous to the Matlab's "unique
(array, 'rows')" to get unique rows of an array. Searching the web,
I've found a similar discussion from couple of years ago with an
example:
############## A SNIPPET FROM THE DISCUSSION
[Numpy-discussion] Finding unique rows in an array [Was: Finding a
row match within a numpy array]
A Tuesday 21 August 2007, Mark.Miller escrigué:
> A slightly related question on this topic...
>
> Is there a good loopless way to identify all of the unique rows in an
> array? Something like numpy.unique() is ideal, but capable of
> extracting unique subarrays along an axis.
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.
################END OF DISCUSSION
Provided example works only because array elements are row-sorted.
Changing tested array to (in my case, it's 'c'):
>>> c
array([[ 0, 1, 2],
[ 3, 4, 5],
[ 3, 4, 5],
[ 9, 10, 11]])
>>> c[0] = (11, 10, 0)
>>> c
array([[11, 10, 0],
[ 3, 4, 5],
[ 3, 4, 5],
[ 9, 10, 11]])
>>> b = np.unique(c.view('S%s' %c.itemsize*c.shape[0]))
>>> b
array(['', '\x03', '\x04', '\x05', '\t', '\n', '\x0b'],
dtype='|S4')
>>> b.view('i4')
array([ 0, 3, 4, 5, 9, 10, 11])
>>> b.reshape((len(b)/c.shape[1], c.shape[1])).view('i4')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: total size of new array must be unchanged
>>>
Since len(b) = 7.
Suggested approach would work if the whole row would be converted to
a single string, I guess. But from what I could gather,
numpy.array.view() only changes display element-wise.
Before I start re-inventing the wheel, I was just wondering if using
existing numpy functionality one could find unique rows in an array.
Many thanks in advance!
Masha
--------------------
liukis@usc.edu
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