Find index mapping between two numpy arrays

Question

Is there a nice way in numpy to get element-wise indexes of where each element in array1 is in array2?

An example:

array1 = np.array([1, 3, 4])
array2 = np.arange(-2, 5, 1, dtype=np.int)

np.where(array1[0] == array2)
# (array([3]),)
np.where(array1[1] == array2)
# (array([5]),)
np.where(array1[2] == array2)
# (array([6]),)

I would like to do

np.where(array1 == array2)
# (array([3 5 6]),)

Is something like this possible? We are guaranteed that all entries in array1 can be found in array2.

Divakar · Accepted Answer · 2017-02-21 17:23:55Z

2

Approach #1 : Use np.in1d there to get a mask of places where matches occur and then np.where to get those index positions -

np.where(np.in1d(array2, array1))

Approach #2 : With np.searchsorted -

np.searchsorted(array2, array1)

Please note that if array2 is not sorted, we need to use the additional optional argument sorter with it.

Sample run -

In [14]: array1
Out[14]: array([1, 3, 4])

In [15]: array2
Out[15]: array([-2, -1,  0,  1,  2,  3,  4])

In [16]: np.where(np.in1d(array2, array1))
Out[16]: (array([3, 5, 6]),)

In [17]: np.searchsorted(array2, array1)
Out[17]: array([3, 5, 6])

Runtime test -

In [62]: array1 = np.random.choice(10000,1000,replace=0)

In [63]: array2 = np.sort(np.random.choice(100000,10000,replace=0))

In [64]: %timeit np.where(np.in1d(array2, array1))
1000 loops, best of 3: 483 µs per loop

In [65]: %timeit np.searchsorted(array2, array1)
10000 loops, best of 3: 40 µs per loop

edited Feb 21, 2017 at 17:23

answered Feb 21, 2017 at 17:09

Divakar

222k19 gold badges273 silver badges374 bronze badges

Sign up to request clarification or add additional context in comments.

3 Comments

pingul Over a year ago

Awesome! I've been playing with each individually, but didn't realise the key was to combine them two. Is there any benefit to either of the two approaches you're suggesting?

Divakar Over a year ago

@pingul I would go with np.searchsorted if array2 is sorted already. Adding timings soon.

pingul Over a year ago

Thanks a lot! Both of the arrays will always be sorted.

syockit · Accepted Answer · 2022-12-29 04:28:16Z

0

Here is a simpler way if your arrays are not too big.

np.equal.outer(array1,array2).argmax(axis=1)

If array1 has size N and array2 has size M, this creates a temporary array of shape (N,M), therefore the above method is not recommended if you have arrays so large that it doesn't fit in memory.

answered Dec 29, 2022 at 4:28

syockit

5,8401 gold badge27 silver badges36 bronze badges

Collectives™ on Stack Overflow

Find index mapping between two numpy arrays

2 Answers 2

3 Comments

Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

3 Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related