Slice numpy array based on x number of other arrays

Question

I am trying to make my current code dynamic. Meaning it should be able to adjust regardless of the number of array inputs of the user.

Current code:

main1 = numpy.array([1,2,3,4])
array1 = numpy.array(['a','b','c','b'])
my_list1 = ['a','b']
array2 = numpy.array(['cat','dog','bird','cat'])
my_list2 = ['cat']

result_array = main1[np.in1d(array1, my_list1) and np.in1d(array2, my_list2)]

The desired result of printing out result_array is:

array([1, 4])

This is because of the intersection of a and cat & b and cat.

My goal is to be able to do this with an n number of array1, array2 ... and n number of my_list1, my_list2...

Thanks in advance!

Mike Müller · Accepted Answer · 2016-02-01 14:19:21Z

1

Version for more than two arrays, using logical_and.reduce:

array3 = numpy.array(['cat3','dog3','bird3','cat3'])
my_list3 = ['cat3']

my_arrays = [array1, array2, array3]
my_lists = [my_list1, my_list2, my_list3]
res1 = main1[numpy.logical_and.reduce(tuple(np.in1d(array, lst) for 
                                            array, lst in zip(my_arrays, my_lists)))]

Test it:

res2 = main1[np.in1d(array1, my_list1) & np.in1d(array2, my_list2) &
             np.in1d(array3, my_list3)]

Looks good:

>>> np.all(res1 == res2)
True

Old answer two arrays only.

This should work:

my_arrays = [array1, array2]
my_lists = [my_list1, my_list2]
main1[np.logical_and(*(np.in1d(array, lst) for array, lst in zip(my_arrays, my_lists)))]

Result:

array([1, 4])

edited Feb 1, 2016 at 14:19

answered Jan 28, 2016 at 10:00

Mike Müller

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2 Comments

jovin.pizarro Over a year ago

Works perfectly! Thanks a lot!

jovin.pizarro Over a year ago

Hi! I thought it was working with three arrays and three lists but apparently it only considers up to the second pair of array-lists. How can we make the np.logical_and consider more than 2 arguments?

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