How To Make Argsort Result To Be Random Between Equal Values?

Say you have a numpy vector [0,3,1,1,1] and you run argsort you will get [0,2,3,4,1] but all the ones are the same! What I want is an efficient way to shuffle indices of identical

Solution 1:

Use lexsort: np.lexsort((b,a)) means Sort by a, then by b

>>>a
array([0, 3, 1, 1, 1])
>>>b=np.random.random(a.size)>>>b
array([ 0.00673736,  0.90089115,  0.31407214,  0.24299867,  0.7223546 ])
>>>np.lexsort((b,a))
array([0, 3, 2, 4, 1])
>>>a.argsort()
array([0, 2, 3, 4, 1])
>>>a[[0, 3, 2, 4, 1]]
array([0, 1, 1, 1, 3])
>>>a[[0, 2, 3, 4, 1]]
array([0, 1, 1, 1, 3])

Solution 2:

This is a bit of a hack, but if your array contains integers only you could add random values and argsort the result. np.random.rand gives you results in [0, 1) so in this case you're guaranteed to maintain the order for non-identical elements.

>>>import numpy as np>>>arr = np.array([0,3,1,1,1])>>>np.argsort(arr + np.random.rand(*arr.shape))
array([0, 4, 3, 2, 1])
>>>np.argsort(arr + np.random.rand(*arr.shape))
array([0, 3, 4, 2, 1])
>>>np.argsort(arr + np.random.rand(*arr.shape))
array([0, 3, 4, 2, 1])
>>>np.argsort(arr + np.random.rand(*arr.shape))
array([0, 2, 3, 4, 1])
>>>np.argsort(arr + np.random.rand(*arr.shape))
array([0, 2, 3, 4, 1])
>>>np.argsort(arr + np.random.rand(*arr.shape))
array([0, 4, 2, 3, 1])

Here we see index 0 is always first in the argsort result and index 1 is last, but the rest of the results are in a random order.

In general you could generate random values bounded by np.diff(np.sort(arr)).max(), but you might run into precision issues at some point.