Theorycrafting Tools
This list pretty much includes anything that can be considered a tool that I've used for theorycrafting so far. Anything counts, except for my brain, I guess.
Calculator
I hope to always have a calculator lying around. This way I can quickly calculate things without needing to do it on paper, on my own, use google, open one on my smartphone or create another python instance. Though as you can see there are a lot of ifs here...
Google Sheets
This is one of the tools I've seen a lot of over people use and for a reason. Timelines, calculations, data collection, data manipulation, data evaluation, etc. etc.. There's no doubt that google sheets are a powerful tool. The difference to excel is, it's not saved on your computer, you can share it with anyone you want and work on it with other people at the same time as well.
Stopwatch
This is probably uncommon except if you're interested in calculating physics. A stopwatch is a must-have for this if there's no in-game timer that is accurate enough to tell the time difference in milliseconds.
Python
Probably the most powerful of the tools I use. Python is a programming and scripting language that I use for simple calculations up to analysis and plotting. It's my goto that is launched whenever I even think about doing theorycrafting. The best advantages of python are its fast runtime, the ability to write code quickly hence it's considered to be very powerful and the ability to easily do the things that would take a lot of programming compared to other languages. Another plus is that Python is known to be a scientific language. (No wonder I came across it when working at the research part of a university). There are a few modules I often use that I find really helpful.
Python Module: Math
Just like most languages, Python has a module called math that can be imported. It gives you the classic functions such as
- sqrt(x) - square root of x
- pow(x, y) - x to the power of y
- round(x) - rounds x
- floor(x) - rounds x to the lower full number
- ceil(x) - rounds x to the higher full number
Python Module: Numpy
This one also includes the methods math has but it's more advanced and features much more. It is easy to create whole matrices, vectors or other data types with numpy and apply basic functions element-wise or completely on those. Even worse this is probably just a small part of what numpy can do. Additionally, numpy is used for vectorized programming which saves a lot of computational power when programming Deep Learning.
Python Module: Matplotlib - Pyplot
I don't have a tight grip on what matplotlib can do but I have used pyplot a lot which can be used for all kinds of graphs. If you've seen any graph on my blog, there's a 99% chance it's made with Python's Matplotlib Module using the Pyplot from it. By the way, Pyplot can do much more than I've done on my blog. Graphs, bar charts, cake charts, heatmaps, histograms, paths, streamplot, scatterplots, tables, polar plots, etc. and 3D as well.
