Slicing Numpy Array by Array of Indices

Question

I am attempting to slice a Numpy array by an array of indices. For example,

 array = [10,15,20,25,32,66]
 indices = [1,4,5]

The optimal output would be

[[10][15,20,25,32][66]]

I have tried using

 array[indices]

but this just produces the single values of each individual index rather than all those in between.

What exactly do your three indices in the array represent. I do not really understand how you get to your desired output from the given input. — jotasi
– jotasi, Commented Feb 2, 2017 at 15:26
The indices are obtained by np.where(). So basically the indices, 1,4,5, would slice the array like so: 0:1, 1:4, 4:5 — Trevor Judice
– Trevor Judice, Commented Feb 2, 2017 at 15:28
What you call "optimal output" cannot be the product of a slicing operation, because it has an undefined shape. — ImportanceOfBeingErnest
– ImportanceOfBeingErnest, Commented Feb 2, 2017 at 15:29
@TrevorJudice Then why is the last output result 66 and not 32? — miradulo
– miradulo, Commented Feb 2, 2017 at 15:29
ImportanceOfBeingErnest is correct. What you could get is a list containing the slices that you wanted to have. Also as Mitch was saying the last element of your desired output does not match your way of constructing it. — jotasi
– jotasi, Commented Feb 2, 2017 at 15:30

Nelewout · Accepted Answer · 2017-02-02 15:31:16Z

4

Consider using np.split, like so

array = np.asarray([10, 15, 20, 25, 32, 66])
indices = [1, 5]

print(np.split(array, indices))

Produces

[array([10]), array([15, 20, 25, 32]), array([66])]

As split uses breakpoints only, where the index indicates the points at which to break blocks. Hence, no need to indicate 1:4, this is implicitly defined by breakpoints 1, 5.

answered Feb 2, 2017 at 15:31

Nelewout

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2 Comments

Paul Panzer Over a year ago

What a useful little function this np.split! If only it could do multiple axes.

Trevor Judice Over a year ago

This is what I wanted. Thank you.

Jan Christoph Terasa · Accepted Answer · 2017-02-02 15:41:45Z

1

According to your comment this generator produces the desired result:

def slice_multi(array, indices):
    current = 0
    for index in indices:
        yield array[current:index]
        current = index

array = [10,15,20,25,32,66]
indices = [1,4,5]
list(slice(array, indices)) # [[10], [15, 20, 25], [32]]

edited Feb 2, 2017 at 15:41

answered Feb 2, 2017 at 15:32

Jan Christoph Terasa

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4 Comments

jotasi Over a year ago

It does when you take his comment into account where he states, that the last slice should be array[4:5] which is indeed [32].

Jan Christoph Terasa Over a year ago

This produces the result of slicing [0:1], [1:4], [4:5], as stated in the comment. I just produced the solution which fit the comment, since it's different from the one stated in the original question.

Jan Christoph Terasa Over a year ago

numpy.split(array, indices)[-1] is probably easier, though.

hpaulj Over a year ago

But that's exactly what np.array_slice does - iteratively slice along the desired axis and return a list of arrays. Look at it's code. It's not compiled.

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