I have intensity profiles (extracted from an image analysis). Basically just f(x). With large datasets of different profiles. The user should train a machine learning algorithm to identify peaks, their size (if scalar is too complicated then just qualitatively: small, medium, large) and one class of three (based on their position/x-value) with a subset and it should run over the large dataset.
Or if this is overly complicated have multiple classes (~10) and assign one class for each profile.
I have tried hard coded parameters forfindpeaks in the past, but there were multiple issues with that. First of all the data is noisy, but more important the users (no Matlab experience and low math exposure) had a hard time finding and tuning the parameters until results matched what they see when looking at the images and since parameters changed between experiments this meant a decrease in usability and hence usage.