How to extend an array with linear interpolation

Question

What I want is to extend an array of length m to an array of length n (n>m), and interpolate the missing values linearly.

For example, I want to extend this array [1,5,1,7] to an array of length 7, the result should be [1,3,5,3,1,5,7], where the bold figures result from linear interpolation.

Is there an easy way to do this in Python? Thanks in advance.

What do you want to get if you extend the array [1, 5, 1, 7] to an array of length 6? — Aleksandr Kovalev, May 04 '15 at 05:55
You can write a simple logic for what you want rather than finding an "easy way". — Pranav Totla, May 04 '15 at 05:59
Then it should be, [1, 1+(5-1) * 3/5, 5+(1-5) * 1/5, 5+(1-5) * 4/5, 1+(7-1) * 2/5, 7] — Maytree23, May 04 '15 at 06:08
@Maytree23 If you know what you want to get why don't you just write the code? — Aleksandr Kovalev, May 04 '15 at 06:11
I just wonder if there is a built-in function for convenience...please. — Maytree23, May 04 '15 at 06:19
@Pranav Maytree23 might just be looking for a Pythonic way to it. — fixxxer, May 04 '15 at 06:29
Thanks guys. Problem solved, please refer to @cfh 's answer. — Maytree23, May 04 '15 at 06:40

score 7 · Accepted Answer · answered May 04 '15 at 06:28

7

The interp function from numpy can do what you want.

Example:

>>> xp = [1, 2, 3]
>>> fp = [3, 2, 0]
>>> np.interp(2.5, xp, fp)
1.0
>>> np.interp([0, 1, 1.5, 2.72, 3.14], xp, fp)
array([ 3. ,  3. ,  2.5 ,  0.56,  0. ])

answered May 04 '15 at 06:28

cfh

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can you elaborate the answer a bit? how did you come to xp and fp and how do you account for the desired shape of the final array? – Martim Passos Sep 06 '22 at 22:32

How to extend an array with linear interpolation

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