On Thursday I looked at last year’s papers/data analysis programs to get ideas and see if I could transfer anything over. I outlined some ideas for functions that could display some meaningful stats, then headed over to Prof. Medero to run my ideas by her and what she thought would be the best way to implement them. I asked about what combination of stats to generate and display, how to present these stats, etc., and she said that I should create a wide variety of stat generators/displayers that a user can mix and match to find patterns in the data. For implementation, she recommended matplotlib for generating graphs in Python and LaTex for generating tables, so next steps are to learn those. The rest of the day was spent learning how to import .jsons into dictionaries and trying to install matplotlib on either my Windows laptop or my Mac work computer. The Windows installation involved installing a long list of other libraries first, while the “pip install” on Mac was getting a permission error even though I was running it with “sudo”. In the end, I installed Enthought’s Canopy on both machines, which already has matplotlib, numpy, and everything I’ll need installed together with it.

Today involved brainstorming, learning matplotlib, and writing a handful of functions. I thought a lot about how to develop incrementally so that my functions could be readily mixed and matched by a future researcher. It was a bit tricky to extract the specific values I needed, since they were often embedded within lists of dictionaries, dictionaries with lists, a y value in a tuple in a list in a dictionary in a list, etc., but hopefully this is will be a lot simpler to work with than last year’s suple dictionary. The functions i have so far can take a bunch of plots and graph them either on the same or different graphs, letting you customize color, x increment, and graph size in optional variables. I also wrote a simple .txt converter that can be brought into LaTex/Excel easily. Next week I’ll need to figure out how to automatically fetch .jsons from Firebase and fine tune TextScroll’s raw data collection so it works better with the graphing functions I’m planning to make.