You can use index arrays, simply pass your ind_pos
as an index argument as below:
a = np.array([0,88,26,3,48,85,65,16,97,83,91])
ind_pos = np.array([1,5,7])
print(a[ind_pos])
# [88,85,16]
Index arrays do not necessarily have to be numpy arrays, they can be also be lists or any sequence-like object (though not tuples).
The one liner "no imports" version
a = [0,88,26,3,48,85,65,16,97,83,91]
ind_pos = [1,5,7]
[ a[i] for i in ind_pos ]
your code would be
a = [0,88,26,3,48,85,65,16,97,83,91]
ind_pos = [a[1],a[5],a[7]]
print(ind_pos)
you get [88, 85, 16]
Although you ask about numpy
arrays, you can get the same behavior for regular Python lists by using operator.itemgetter
.
>>> from operator import itemgetter
>>> a = [0,88,26,3,48,85,65,16,97,83,91]
>>> ind_pos = [1, 5, 7]
>>> print itemgetter(*ind_pos)(a)
(88, 85, 16)
Source: Stackoverflow.com