Efficiently check if numpy ndarray values are strictly increasing

Question

I'm having a numpy ndarray where I would like to check if each row vector is monotonically increasing.

Example:

a = np.asarray([[1,2,3],[1,5,7],[4,3,6]]) monotonically_increasing(a) 

Expected return:

[True, True, False] 

I'm not entirely sure how to efficiently do this, since the matrices are expected to be quite large (~1000x1000), and was hoping for some help.

Answer 1

>>> import numpy as np >>> a = np.asarray([[1,2,3],[1,5,7],[4,3,6]]) 

Find the difference between each element. np.diff has an argument that lets you specify the axis to perform the diff

>>> np.diff(a) array([[ 1,  1],        [ 4,  2],        [-1,  3]]) 

Check to see if each difference is greater than 0.

>>> np.diff(a) > 0 array([[ True,  True],        [ True,  True],        [False,  True]], dtype=bool) 

Check to see if all the differences are > 0

>>> np.all(np.diff(a) > 0) False >>>  

---

As suggested by @Jaime - check that each element is greater than the element to its left:

np.all(a[:, 1:] >= a[:, :-1], axis=1) 

Which appears to be about twice as fast/efficient as my diff solution.