These are a few scripts I've used to help me out while writing a novel where each chapter is a markdown file. A repo might have a format like this:
book/
├── part-1
│ ├── chapter-01.md
│ ├── chapter-02.md
│ ├── chapter-03.md
│ ├── chapter-04.md
│ ├── chapter-05.md
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I wrote this script* to easily calculate if I was on track for NaNoWriMo and to automatically generate commit messages based on my progress.
This script does two things:
cm is passed as an argument, it will git add, commit, and push to a repository with a message that records the current word count and which day of the month it isThis has only been tested in Ubuntu
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This uses Jason Davies' word cloud library library to render the 100 most popular words in titles of fan fiction that are tagged as being about Sirius Black and Remus Lupin. Hover over a word to see randomly chosen titles that have that word in them.
This is a cooccurrence matrix based off of Les Miserables Co-occurrence only with Harry Potter characters, where cooccurrence is defined as if two characters are tagged as characters featured in a given fan fiction. Therefore the diagonal values are all the same, since every fan fiction that has Albus Dumbledore also has Albus Dumbledore.
Instead of the intersecting values being the number of fan fictions between two characters, the number is normalized by dividing by the number of total fan fictions about that character. Therefore, the value in [Draco Malfoy][Harry Potter] is most likely not the same as [Harry Potter][Draco Malfoy]. This allows us to see some interesting properties- for example, of all Lupin fan fictions, 16.23% also feature Tonks. However, of Tonks fan fictions, 70.57% also feature Lupin. This shows perhaps a conflict in the fandom of who else Lupin is spending a lot of time with in fan fiction... WolfStar, anyone?
This is the same chart as this one except the colors represent the character's gender instead of their relative popularity. Red represents a male character, gold a female character, and grey other.
Simple bar graph with object constancy that tracks either:
This dataset was normalized by dividing by the total number out of the top 200 characters. So if there were a total of 20 fan fictions tagged as Sirius Black, and there were a total of 100 fan fictions, Sirius Black fan fictions would show up as 20%. Note that therefore this percentage will add up to be over 100% since fan fictions can tag multiple characters. For example, if our total fan fictions were made entirely out of fan fictions tagged Sirius Black and Remus Lupin, it would be correct to say that 100% of fan fictions are about Sirius Black and 100% of fan fictions are about Remus Lupin.
This is a somewhat reusable graph- see [this block](https://bl.ocks.org/allisonking/158e96
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This is part two of using d3.js's force directed graph to create a customized static layout. Part 1 is here. The file character_nodes.json was the result of moving each node and Bezier control point around until the graph looked reasonable, then printing it out as described in part 1.