Pythonic way to replace list values with upper and lower bound (clamping, clipping, thresholding)?
arrays, clamp, clip, numpy, python
Solution
You can use `numpy.clip`:
In [1]: import numpy as np
In [2]: arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
In [3]: lowerBound, upperBound = 3, 7
In [4]: np.clip(arr, lowerBound, upperBound, out=arr)
Out[4]: array([3, 3, 3, 3, 4, 5, 6, 7, 7, 7])
In [5]: arr
Out[5]: array([3, 3, 3, 3, 4, 5, 6, 7, 7, 7])
Problem
I want to replace outliners from a list. Therefore I define a upper and lower bound. Now every value above `upper_bound` and under `lower_bound` is replaced with the bound value. My approach was to do this in two steps using a numpy array. Now I wonder if it's possible to do this in one step, as I guess it could improve performance and readability. Is there a shorter way to do this? ``` import numpy as np lowerBound, upperBound = 3, 7 arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) arr[arr > upperBound] = upperBound arr[arr < lowerBound] = lowerBound # [3 3 3 3 4 5 6 7 7 7] print(arr) ``` See How can I clamp (clip, restrict) a number to some range? for clamping individual values, including non-Numpy approaches.