Okay, I’m done with these for now. I’m sharing all the source files here in case anyone wants to take it anywhere as well as screenshots of my final graphs and the following explanation.
I added weightings so that “activity” no longer just means reviews and lessons. Lessons are weighted twice as heavily as reviews and vocabulary and kanji are weighted twice as heavily as radicals. So those big spikes at the end are because for a few levels the new material becomes very vocabulary heavy, hitting both those weightings. Hopefully this is closer to what “workload” should actually mean. Also it smooths the start a little which was previously very high because it had disproportionately many radical reviews.
Secondly I modified it so that the user is definitely inactive (sleeping) for a consistently spaced 8 hours per day, just to be sure nothing weird was going on there. I don’t think it changed much, maybe extended the whole thing by a week.
Thirdly I’m using the progression ratios from @konekush but I’m overriding them for apprentice radicals and kanji to avoid weirdness in the overall advancement caused by insufficient learning items. I don’t think that’s necessarily realistic, just a compromise to make the graph more broadly representative. Otherwise the question will always be “why are there huge dips”.
HTML Graphs + Python Script
Thank you for the input, everyone!
@jprspereira I’m not sure if these graphs would be better for your guide or not. They certainly seem to require a fair amount of explanation but then so does the one you are using. But I’ll leave that up to you.