Assassin's Creed Process

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The Python Graph

        from collections import Counter
        import pygal
        import spacy as spacy
        
        #nlp = spacy.cli.download("en_core_web_sm")
        nlp = spacy.load('en_core_web_sm')
        
        
        acDiologue = open('acDiologue.txt', 'r', encoding='utf8', errors='ignore')
        
        words = acDiologue.read()
        nlpwords = nlp(words)
        
        def entitycollector(words):
        ents = []
        count = 0
        for entity in words.ents:
        if entity.label_ == "GPE" or entity.label_ == "LOC" or entity.label_ == "NORP":
        if entity.text != "DR" and entity.text != "Swordfish" and entity.text != "Gla" and entity.text != "Animus" and entity.text != "Poseidon" and entity.text != "Kleon" and entity.text != "Pythia" and entity.text != "Aspasia" and entity.text != "Hippokrates" and entity.text != "Aristophanes":
        count += 1
        
        ents.append(entity.text)
        print(count, ": ", entity, entity.label_, spacy.explain(entity.label_))
        
        return ents

Using the spaCy import we gain access to a vast language analysis tools in spaCy. The enitity collector finds different things that it recognizes like geo politcal entities and nationalities and turns them into an interactive svg graph.

The Xquery Graph

query version "3.1";
declare variable $ac := doc('/db/assassinsCreed/assassinscreedodyssey.xml');
declare variable $intro := $ac//Q{}intro;
declare variable $chapNums := $ac//Q{}chapterNum;
declare variable $segments := ($intro, $chapNums);
declare variable $spacer := 80;
declare variable $max-Width := $segments => count() * $spacer + $spacer;
declare variable $ActionCounts :=
    for $s in $segments
    let $actions := $s//Q{}action
    return $actions => count();
declare variable $maxActionCount := $ActionCounts => max();
declare variable $height-spacer := -10;
declare variable $max-Height := $maxActionCount * $height-spacer;
declare variable $ThisFileContent :=
for $s at $pos in $segments
let $actions := $s//Q{}action
let $sectionTitle :=
    if ($s//Q{}chapTitles)
        then $s//Q{}chapTitles/string() ! normalize-space()
    else "intro"
let $speakers := $s//Q{}speaker
let $distSpeakers := $speakers ! normalize-space() => distinct-values()
let $countSpeakers := $distSpeakers => count()
let $countActions := $actions => count()
let $barElongate := 10
let $barSpace := 30
return
        

This code grabs speakers and actions of every chapter and puts the count of each into bars of their value.