The avatar for @bmschmidt
Benjamin Schmidt
Digital Humanist. Manhattan-based.
Published
Edited
May 8, 2019
1 fork
Importers
22 stars
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embed(sentimentChart)
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NUM_POINTS = 500
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md`Another way to potentially improve the quality at the cost of increased run time is to increase the chunking level below. If you change the parameter 'doc' to 'page' (from 'ntile') associations will be done by physical page, rather than by percentile through the book.`
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embed(sentimentChart)
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html`${volume.repr()}<br>${selfSimilarityPlot}`
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function do_chunking(volume, chunking) {
// chunk relative to settings in this particular observable notebook.
if (chunking == 'page') {
return filled_library.chunks({doc: 'page', what: 'word', sections: ['body']})
}
else if (chunking == '10ths') {
return filled_library.chunks({doc: 'ntile', 'ntiles': 10, what: 'word'})
} else {
return filled_library.chunks({doc: 'ntile', 'ntiles': 100, what: 'word'})
}
}
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zipfPlot = md`### Zipf plot

This is a pretty unremarkable plot, but it can be nice to see: do the distributions of word frequencies follow Zipf's law? Since George Zipf was originally writing about the counts in Joyce's *Ulysses,* that would be a sensible book to [look at here.](https://observablehq.com/@bmschmidt/book-visualizations-sandbox?htid=inu.30000111060913)

`
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pos_lookup = new Object({"PRP$": "Possessive pronoun", "VBG": "Verb, gerund or present participle", "FW": "Foreign word", "VBN": "Verb, past participle", "VBP": "Verb, non-3rd person singular present", "WDT": "Wh-determiner", "JJ": "Adjective", "WP": "Wh-pronoun", "VBZ": "Verb, 3rd person singular present", "DT": "Determiner", "RP": "Particle", "NN": "Noun, singular or mass", "VBD": "Verb, past tense", "POS": "Possessive ending", "TO": "to", "PRP": "Personal pronoun", "RB": "Adverb", "NNS": "Noun, plural", "NNP": "Proper noun, singular", "VB": "Verb, base form", "WRB": "Wh-adverb", "CC": "Coordinating conjunction", "LS": "List item marker", "PDT": "Predeterminer", "RBS": "Adverb, superlative", "RBR": "Adverb, comparative", "CD": "Cardinal number", "EX": "Existential there", "IN": "Preposition or subordinating conjunction", "WP$": "Possessive wh-pronoun", "MD": "Modal", "NNPS": "Proper noun, plural", "JJS": "Adjective, superlative", "JJR": "Adjective, comparative", "SYM": "Symbol", "UH": "Interjection",
// Begins my amendations
".": "Punctuation", ",": "Punctuation", "NE": "Noun, unknown", "``": "Punctuation",
"CARD": "Number", "''": "Punctuation", ":": "Punctuation", "#": "Punctuation",
"-LRB-": "Unknown", "-RRB-": "Unknown", "$": "Unknown"})
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md`# General supporting code

The Volume and Library classes are inherited from a different notebook.

The a new 'Library' instance is created, and the 'fetch_all' method is called to asynchronously fill in the requested id.

`
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import {Volume, Library} from '@bmschmidt/javascript-bindings-to-the-hathi-features-data'
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filled_library = new Library().fetch_all([htid])
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md`# Imports

Here are other javascript imports required to make this notebook run.

I use the new VegaLite API just to test it out; it's still a little undocumented (there were some sorting operations I couldn't work out the syntax for) so I sometimes, but not always, compiled to normal vega-lite JSON.
`
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import {vl} from '@vega/vega-lite-api'
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import {slider, radio, select, text} from "@jashkenas/inputs"
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d3Fetch = require('d3-fetch')

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d3 = require('d3', 'd3-array')
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