Last week was challenging. I was able to successfully change the scaling data function so that it incorporated the MNE functions to accomplish the same goal. The challenge arose when processing the 16 subjects' data that was meant to act as a ground truth to compare the model's output to an expectation. The output is currently pretty far from the expectation. I, more or less, need to start from the beginning and check step-by-step that each part of the model is producing something that I would expect. The biggest challenge being that it's so far in the summer and I am concerned I won't be able to get to the second part of my project. My plan for this week is to run the sample dataset, frequently used on the MNE-Python website to be used in examples, on my already existing pipeline which uses primarily command line and configuration files to process data. Once that is working I can do a step by step comparison of each step's output between the command line pipeline and the API I have been working on for this project.