[Numpy-discussion] improving arraysetops

Robert Cimrman cimrman3@ntc.zcu...
Mon Jun 15 04:55:11 CDT 2009


Neil Crighton wrote:
> Robert Cimrman <cimrman3 <at> ntc.zcu.cz> writes:
> 
>> Hi,
>>
>> I am starting a new thread, so that it reaches the interested people.
>> Let us discuss improvements to arraysetops (array set operations) at [1] 
>> (allowing non-unique arrays as function arguments, better naming 
>> conventions and documentation).
>>
>> r.
>>
>> [1] http://projects.scipy.org/numpy/ticket/1133
>>
> 
> Hi,
> 
> These changes looks good to me.  For point (1) I think we should fold the 
> unique and _nu code into a single function. For point (3) I like in1d - it's 
> shorter than isin1d but is still clear.

yes, the _nu functions will be useless then, their bodies can be moved 
into the generic functions.

> What about merging unique and unique1d?  They're essentially identical for an 
> array input, but unique uses the builtin set() for non-array inputs and so is 
> around 2x faster in this case - see below. Is it worth accepting a speed 
> regression for unique to get rid of the function duplication?  (Or can they be 
> combined?) 

unique1d can return the indices - can this be achieved by using set(), too?

The implementation for arrays is the same already, IMHO, so I would 
prefer adding return_index, return_inverse to unique (automatically 
converting input to array, if necessary), and deprecate unique1d.

We can view it also as adding the set() approach to unique1d, when the 
return_index, return_inverse arguments are not set, and renaming 
unique1d -> unique.

> Neil
> 
> 
> In [24]: l = list(np.random.randint(100, size=10000))
> In [25]: %timeit np.unique1d(l)
> 1000 loops, best of 3: 1.9 ms per loop
> In [26]: %timeit np.unique(l)
> 1000 loops, best of 3: 793 µs per loop
> In [27]: l = list(np.random.randint(100, size=1000000))
> In [28]: %timeit np.unique(l)
> 10 loops, best of 3: 78 ms per loop
> In [29]: %timeit np.unique1d(l)
> 10 loops, best of 3: 233 ms per loop

I have found a strange bug in unique():

In [24]: l = list(np.random.randint(100, size=1000))

In [25]: %timeit np.unique(l)
---------------------------------------------------------------------------
UnicodeEncodeError                        Traceback (most recent call last)

/usr/lib64/python2.5/site-packages/IPython/iplib.py in ipmagic(self, arg_s)
     951         else:
     952             magic_args = self.var_expand(magic_args,1)
--> 953             return fn(magic_args)
     954
     955     def ipalias(self,arg_s):

/usr/lib64/python2.5/site-packages/IPython/Magic.py in 
magic_timeit(self, parameter_s)
    1829 
precision,
    1830                                                           best 
* scaling[order],
-> 1831 
units[order])
    1832         if tc > tc_min:
    1833             print "Compiler time: %.2f s" % tc

UnicodeEncodeError: 'ascii' codec can't encode character u'\xb5' in 
position 28: ordinal not in range(128)

It disappears after increasing the array size, or the integer size.
In [39]: np.__version__
Out[39]: '1.4.0.dev7047'

r.



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