Let's say that I have two 1 dimensional arrays, and when I plot the two arrays they look like this:
If you look at the top and bottom graphs, then you can see that the highlighted parts are very similar (in this case they're exactly the same). I need to find a way to find these sections using some sort of algorithm or method.
I've tried searching everywhere in the numpy and scikit docs, I even searched everywhere on stackexchange and couldn't find a solution for this problem. I don't think anyone published a solution for this yet.
Does anyone have any idea how I can find similar sections in two graphs? My dataset is a 1 dimensional data array for each graph, and I need a algorithm that tells me where the similar parts are. Just remember that the similar sections are never 100% the same, sometimes they're a little bit off and sometimes there's anomalies so a small part would be different but everything else will still look the same. Also you can ignore the curvature of the graph, that's irrelevant. Only the X and Y coordinates of the data points are important.
I can't read explanations that have a lot of maths inside of them and I also can't turn explanations that have a lot of maths into code, I'm still learning how to do that at University. But I'm really good at reading pseudo-code and other programming languages so please give me an answer with real code.