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no data exclution and unique combination.

MRAB python at mrabarnett.plus.com
Tue Jul 24 15:08:38 EDT 2012 
On 24/07/2012 19:51, MRAB wrote:
> On 24/07/2012 19:27, giuseppe.amatulli at gmail.com wrote:
>> Hi,
>> would like to take eliminate a specific number in an array and its correspondent in an other array, and vice-versa.
>>
>> given
>>
>> a=np.array([1,2,4,4,5,4,1,4,1,1,2,4])
>> b=np.array([1,2,3,5,4,4,1,3,2,1,3,4])
>>
>> no_data_a=1
>> no_data_b=2
>>
>> a_clean=array([4,4,5,4,4,4])
>> b_clean=array([3,5,4,4,3,4])
>>
>> after i need to calculate unique combination in pairs to count the observations
>> and obtain
>> (4,3,2)
>> (4,5,1)
>> (5,4,1)
>> (4,4,2)
>>
>> For the fist task i did
>>
>> a_No_data_a = a[a != no_data_a]
>> b_No_data_a = b[a != no_data_a]
>>
>> b_clean = b_No_data_a[b_No_data_a != no_data_b]
>> a_clean  = a_No_data_a[a_No_data_a != no_data_b]
>>
>> but the results are not really stable.
>>
> mask = (a != no_data_a) & (b != no_data_b)
> a_clean = a[mask]
> b_clean = b[mask]
>
>> For the second task
>> The np.unique would solve the problem if it can be apply to a two arrays.
>>
I couldn't figure out how to do the second part in numpy, so:

from collections import Counter
counts = Counter(zip(a_clean, b_clean))
counts = [pair + (count,) for pair, count in counts.items()]
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