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I have one numpy array that stores the thresholds and another array that store some values. I want these last values to be less or equal of the corresponding thresholds. In particular, if a value is greater than its corresponding threshould I should change it with the thresholds.

The following example gives exactly what I want but I'm wondering if exist a better way to implement it or if already exist a numpy method (that I searched for but that I didn't find) to do it.

In [1]: import numpy as np

In [2]: a = np.random.rand(10)

In [3]: a
Out[3]: 
array([0.38331068, 0.32042463, 0.89980916, 0.86472908, 0.10812789,
       0.35855107, 0.09916983, 0.55710449, 0.38591185, 0.70798023])

In [4]: t = np.array([0.95, 0.9, 0.8, 0.75, 0.7, 0.65, 0.6, 0.55, 0.5, 0.45])

In [5]: mask = a > t

In [6]: a[mask] = t[mask]

In [7]: a
Out[7]: 
array([0.38331068, 0.32042463, 0.8       , 0.75      , 0.10812789,
       0.35855107, 0.09916983, 0.55      , 0.38591185, 0.45      ])
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1 Answer 1

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You can use np.clip:

>>> np.clip(a,a_min=None,a_max=t)
array([0.38331068, 0.32042463, 0.8       , 0.75      , 0.10812789,
       0.35855107, 0.09916983, 0.55      , 0.38591185, 0.45      ])
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4 Comments

This means that if I also have a lower threshold I could do np.clip(a,a_min=t_min,a_max=t_max) where t_min contains the lower thresholds and t_max the higher thresholds?
Exactly, I think it's along the lines of what you're looking for
Usually, I wait for 24h before accepting an answer but I don't think that this would be the case.
Do as you wish! Glad I could help.

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