python - Slice numpy array based on x number of other arrays -

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i trying make current code dynamic. meaning should able adjust regardless of number of array inputs of 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) , np.in1d(array2, my_list2)]

the desired result of printing out result_array is:

array([1, 4])

this because of intersection of a , cat & b , cat.

my goal able n number of array1, array2 ... , n number of my_list1, my_list2...

thanks in advance!

version more 2 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)                                              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 2 arrays only.

this should work:

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

result:

array([1, 4])

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