How to spread Numpy values on a different interval

Question

I have the following array:

a = np.array([20, 10, 5, 15])

Given a new interval (for instance B = [10, 40]) I need to spread the values of the original array an the new interval, so the result would be:

b = np.array([40., 20, 10., 30])

A possible solution would be applying the following formula (in pseudocode) to each value:

new_value = min(B) + (current_value - min(a)) * (max(a)-min(a)) / (max(B)-min(B))

Any quicker approach ?

`np.interp(a, (a.min(),a.max()), (10,40))`, IIUC. Every solution is faster than *pseudo-code*. — Michael Szczesny, Feb 23 '22 at 15:56
Does this answer your question? [Mapping a range of values to another](https://stackoverflow.com/questions/1969240/mapping-a-range-of-values-to-another) — Michael Szczesny, Feb 23 '22 at 16:02

score 0 · Answer 1 · answered Feb 23 '22 at 17:44

0

As mentioned in the comments, you can use numpy.interp like so:

np.interp(a, (a.min(),a.max()), (10,40))

answered Feb 23 '22 at 17:44

rikyeah

1 Answers1