带有不需要的零的python插值

Question

I have sparse list of data. There are approximately 20 to 50 zero values between every two adjacent non-zeros (these are the meaningful values of my data).

I want to interpolate these non-zero values. The result I get is undesired since python interpolates the majority zeros too, making the interpolated curve with a lot of sparks! I want something very smooth...

The idea is to have python ignore the zeros or get rid of the zeros in the list, and still let the list remember the index of each non-zero value.

I guess what I can do is simply interpolate between a list of index and a list of real values, does anyone know how to do it elegantly?

Answer 1

You could create a list of tuples containing (index, value) and interpolate using only these values.

data = [(i, val) for i, val in enumerate(sparse_list) if val != 0]

or considering primero´s answer probably use an ordered dict.

Answer 2

I'm not really sure I understand the question, but from what i understand I would think of something like this:

a = [1,0,0,0,0,1,0,0,0,1] # initial array
b = { index : value for index, value in enumerate(a) if value != 0 }

And now you have a dictionary b with the former indexes in f.keys() and the non-zero values in f.values()