Test Article: Code Samples

int winter = 1;
do {
   Random r = new Random();
   string[] actions = new string[] { "walk", "hop", "speak" };
   actions = actions.OrderBy(x => r.Next()).ToArray();
   foreach (string doAction in actions) {
      makeWisakecahk(doAction);
   }
   winter--;
} while (winter == 1);

413	for (int x = 0; x < WORLD_W; x += crimeRateMap.MAP_BLOCKSIZE) { 
414		for (int y = 0; y < WORLD_H; y += crimeRateMap.MAP_BLOCKSIZE) { 
415 		int z = landValueMap.worldGet(x, y); 
416			if (z > 0) { 
417				++numz; 
418				z = 128 - z; 
419				z += populationDensityMap.worldGet(x, y); 
420				z = min(z, 300); 
421				z -= policeStationMap.worldGet(x, y); 
422				z = clamp(z, 0, 250); 
423				crimeRateMap.worldSet(x, y, (Byte)z); 
424				totz += z;                
            

} else { 
   crimeRateMap.worldSet(x, y, 0); 

if (landValueFlag) {   /* LandValue Equation */ 
	dis = 34 - getCityCenterDistance(worldX, worldY) / 2; 
	dis = dis <<2; 
	dis += terrainDensityMap.get(x >>1, y >>1); 
	dis -= pollutionDensityMap.get(x, y); 
	if (crimeRateMap.get(x, y) > 190) { 
		dis -= 20; 
	} 

109 	if (!getRandom(DisChance[x])) { 
110 		switch (getRandom(8)) { 
111 			case 0: 
112				case 1: 
113 				setFire(); // 2/9 chance a fire breaks out 
114 				break; 
115 			case 2: 
116				case 3: 
117 				makeFlood(); // 2/9 chance for a flood 
118 				break; 
119 			case 4: 
120 				// 1/9 chance nothing happens (was airplane crash, 
121 				// which EA removed after 9/11, and requested it be 
122 				// removed from this code) 
123 				break; 
124 			case 5: 
125					makeTornado(); // 1/9 chance tornado 
126 				break; 
127 			case 6: 
128 				makeEarthquake(); // 1/9 chance earthquake 
129 				break; 
130 			case 7: 
131 			case 8: 
132 				// 2/9 chance a scary monster arrives in a dirty town 
133 				if (pollutionAverage > /* 80 */ 60) { 
134 					makeMonster(); 
135 				} 
136 				break; 

         case 4: 
               // 1/9 chance nothing happens (was airplane crash, 
               // which EA removed after 9/11, and requested it be 
               // removed from this code) 
               break; 

(game "Tic-Tac-Toe"
        (players 2)					
        (equipment {
            (board (square 3))
            (piece "Disc" P1)
            (piece "Cross" P2)
        }) 
        (rules
            (play (move Add (to (sites Empty))))					
            (end (if (is Line 3) (result Mover Win)))
        )
 )

pip install silabeador fonemas stanza==1.7.0 libEscansion

import stanza
stanza.download(lang="es",
                package=None,
                processors={"ner": "ancora",
                            "tokenize": "ancora",
                            "pos": "ancora",
                            "lemma": "ancora",
                            "mwt":"ancora",
                            "constituency":"combined_charlm",
                            "depparse": "ancora", 
                            "sentiment": "tass2020"})

<p>
  Why there was no room in <em>six volumes</em> of
  Taruskin's <cite>Oxford History of Western Music</cite>
  to include a single reference to Louis Armstrong?
</p>
						

:c1 a skos:Concept ;
  skos:prefLabel "c1"@en ;
  skos:inScheme :sbjf_1 ;
  skos:definition "A battery-electric car that is capable of traveling at a maximum
    speed of 25 miles per hour (mph) and has a maximum loaded weight of 3,000 lbs."@en ;
  skos:definition "éhicule à deux places, activé par un moteur électrique à courant
    continue alimenté par des batteries au plomb rechargeables à partir d'une prise de
    courant résidentielle de 110 volts."@fr .
:sbjf_1 a skos:ConceptScheme ;
  skos:prefLabel "e-mobility"@en .

:enLex a lime:Lexicon ;
  lime:language "en" ;
  lime:entry :t1, :t2 .
:frLex a lime:Lexicon ;
  lime:language "fr" ;
  lime:entry :t3 .
:itLex a lime:Lexicon ;
  lime:language "it" ;
  lime:entry :t4, :t5 .

:t1 rdf:type ontolex:LexicalEntry ; 
  lexinfo:partOfSpeech lexinfo:noun ; 
  lexinfo:normativeAuthorization lexinfo:preferredTerm ; 
  lexinfo:termType lexinfo:fullForm ; 
  ontolex:canonicalForm :t1_cf ;
  ontolex:sense :t1_sense .
:t1_cf rdf:type ontolex:Form ; 
  ontolex:writtenRep "neighborhood electric vehicle"@en .
:t1_sense rdf:type ontolex:LexicalSense ; 
  skos:definition [ 
    rdf:value "A battery-electric ..." ;
    dct:source "TechTarget" ;
    rdfs:seeAlso <https://www.techtarget.com/whatis/definition/
      neighborhood-electric-vehicle-NEV> ] ;
ontolex:usage [ 
  rdf:value "A Neighborhood Electric Vehicle is a U.S. category for ..." ;
  dct:source "Wikipedia" ;
  rdfs:seeAlso <https://en.wikipedia.org/wiki/Neighborhood_Electric_Vehicle> ] .

intertextualRelation’(T, T)

intertextualRelation(i, T, T, …)

intertextualRelation(i, T, T, S+, ...)

CALL SHIFT(A(J+1),7*(I-6),YY) 

                        CALL SHIFT(A(J+1),7*(K-6),YY)
                                SUBROUTINE SHIFT (VAL,DIST,RES) IMPLICIT INTEGER
                                    (A-Z) RES=VAL IF(DIST)10,20,30 10 IDIST=-DIST DO 11 I=1,IDIST J
                                    = 0 IF (RES.LT.0) J="200000000000 11 RES =
                                    ((RES.AND."377777777777)/2) + J 20 RETURN 30 DO 31 I=1,DIST j =
                                    0 IF ((RES.AND."200000000000).NE.0) J="400000000000 31 RES =
                                    (RES.AND."177777777777)*2 + J RETURN END
                     

1001 LTEXT(I)=0 I=1 CALL IFILE(1,'TEXT')

               word = URLDecoder.decode(word, "utf-8");
               word = new String(word.getBytes("8859_1"),"UTF-8");
               if (language.equals(Language.GREEK)) {
                  word = GreekEncodingAnalyzer.transcode(word, "PerseusBetaCode");
               }
               

    
    /* Completely rebuilt this part on may 10th, 2008, in order to make the class
    * more robust. Before it assumed that certain elements would be contained in
    * a particular order, without any intervening xml tags that might be added
    * by various applications. (Such as G7towin, which produces gpx files that
    * this class threw up on.) I tried to make it more robust by looking for tags
    * and accepting their data if they contained "wpt" data, and just ignoring
    * anything else it finds. Brett
    */
    

    
    54 …[the software] should now handle any gpx file containing
    55 * waypoints, regardless of other junk in the file.
    

    
    public TBMIDlet () {
    

    
    // private String URL = "http://internetjunkee.com/transborder/GPScourseFinal.gpx";
    

    
    TBGpxParser gpxParser = new TBGpxParser(TBGpxParser.RES, "../../../../" + gpxFileName);
    

       
301. // make sure the data is not expired
302. if (isExpired) {
303. display.setCurrent(expired);
304. display.vibrate(1000);
305. playAudioFile("expired.wav", true);
306. } else if (expireWarning) {
307. display.setCurrent(expirationWarning, tbDowsingCompass);
308. display.vibrate(1000);
309. playAudioFile("expiration.wav", true);
    

     
310. } else if (startUpAlert) { //first time only
311. startUpAlert = false;
312. display.setCurrent(startUpDisplay, tbDowsingCompass);
313. display.vibrate(1000);
314. playAudioFile("startup.wav", true);
315. } else { // we are good to go
316. display.setCurrent(tbDowsingCompass);
317. }
    

    
126. if (exp <= System.currentTimeMillis()) {
127. expired = new Alert(translation.translate("Data expired"),
128. translation.translate("The data is expired, TBTool is not safe to use."),
129. errorImage,
130. AlertType.ERROR);
131. expired.setTimeout(Alert.FOREVER);
132. expired.addCommand(exit);
133. expired.addCommand(ignore);
134. expired.setCommandListener(this);
135. isExpired = true;
    

    
157. noNearbyWaypoints = new Alert(translation.translate("No Nearby Points"),    
    

//spreadsheet variables - edit these to point to your spreadsheet
var spreadsheetID = "1iwIx8sqiBTqbtAI7TX4vDGDVee3dPz0wa3MazBv2fzQ";
var siteSheet = '1569296108';
var pagesSheet = '28080804';
var itemsSheet = '0';

//function to get queries from the URL and get the URL slug for the requested page
function getQueries() {
   var queryString = window.location.search;//get queries from current URL
   if(queryString) {
      var urlParams = new URLSearchParams(queryString);//get queries as search parameters
      openPage = urlParams.get('page').replace('%20',' ');//set the openPage variable to the value from the current URL
   }
};

//Connect to Google Visualization API and query the Site sheet to retrieve basic site configuration
var query = new google.visualization.Query('https://docs.google.com/spreadsheets/d/'+spreadsheetID+'/gviz/tq?gid='+siteSheet'&headers=1');
query.send(function (response) {
         //error handling
         if (response.isError()) {
      console.log('Error in query: ' + response.getMessage() + ' ' + response());
      Return;
         };
   var siteDT = response.getDataTable();//get datatable from response
   var siteJsonData = siteDT.toJSON();//convert datatable to JSON
   siteJsonData = JSON.parse(siteJsonData);//parse JSON 
   siteConfig(siteJsonData);//configure site using data from spreadsheet
   //end of site configuration

//run Rondo page as static page using local data
$.getJSON("json/site.json", function(siteJsonData) {//get site data
   siteConfig(siteJsonData);//configure site using site data
   $.getJSON("json/pages.json", function(pagesJsonData) {//get pages data
      pages(pagesJsonData);//create pages
      $.getJSON("json/items.json", function(itemsJsonData) {//get items data
         itemsDataTable(itemsJsonData);//build the items table
      });//end of items
   });//end of pages
});//end of configuration

var test = 4 tst + 6 Uncaught ReferenceError: tst is not
                     Error: "tst" was not defined defined at <anonymous>:1:1 

var shortPhrase = ['circle on', 'dash on', 'let them', 'listen now', 'loop on', 'oh time', 'plunge on', 'reel on', 'roll on', 'run on', 'spool on', 'steady', 'swerve me?', 'turn on', 'wheel on', 'whirl on', 'you — too — ', 'fast-fish', 'loose-fish'];
var dickinsonNoun = [
   ['air', 'art', 'care', 'door', 'dust', 'each', 'ear', 'earth', 'fair', 'faith', 'fear', 'friend', 'gold', 'grace', 'grass', 'grave', 'hand', 'hill', 'house', 'joy', 'keep', 'leg', 'might', 'mind', 'morn', 'name', 'need', 'noon', 'pain', 'place', 'play', 'rest', 'rose', 'show', 'sight', 'sky', 'snow', 'star', 'thought', 'tree', 'well', 'wind', 'world', 'year'],
   ['again', 'alone', 'better', 'beyond', 'delight', 'dying', 'easy', 'enough', 'ever', 'father', 'flower', 'further', 'himself', 'human', 'morning', 'myself', 'power', 'purple', 'single', 'spirit', 'today'],
   ['another', 'paradise'],
   ['eternity'],
   ['immortality']
];
var courseStart = ['fix upon the ', 'cut to fit the ', 'how to withstand the'];
var dickinsonSyllable = ['bard', 'bead', 'bee', 'bin', 'bliss', 'blot', 'blur', 'buzz', 'curl', 'dirt', 'disk', 'doll', 'drum', 'fern', 'film', 'folk', 'germ', 'hive', 'hood', 'husk', 'jay', 'pink', 'plot', 'spun', 'toll', 'web'];
var melvilleSyllable = ['ash', 'bag', 'buck', 'bull', 'bunk', 'cane', 'chap', 'chop', 'clam', 'cock', 'cone', 'dash', 'dock', 'edge', 'eel', 'fin', 'goat', 'hag', 'hawk', 'hook', 'hoop', 'horn', 'howl', 'iron', 'jack', 'jaw', 'kick', 'kin', 'lime', 'loon', 'lurk', 'milk', 'net', 'pike', 'rag', 'rail', 'ram', 'sack', 'salt', 'tool'];
var dickinsonLessLess = [
   ['art', 'base', 'blame', 'crumb', 'cure', 'date', 'death', 'drought', 'fail', 'flesh', 'floor', 'foot', 'frame', 'fruit', 'goal', 'grasp', 'guile', 'guilt', 'hue', 'key', 'league', 'list', 'need', 'note', 'pang', 'pause', 'phrase', 'pier', 'plash', 'price', 'shame', 'shape', 'sight', 'sound', 'star', 'stem', 'stint', 'stir', 'stop', 'swerve', 'tale', 'taste', 'thread', 'worth'],
   ['arrest', 'blanket', 'concern', 'costume', 'cypher', 'degree', 'desire', 'dower', 'efface', 'enchant', 'escape', 'fashion', 'flavor', 'honor', 'kinsman', 'marrow', 'perceive', 'perturb', 'plummet', 'postpone', 'recall', 'record', 'reduce', 'repeal', 'report', 'retrieve', 'tenant'],
   ['latitude', 'retriever']
];
var upVerb = ['bask', 'chime', 'dance', 'go', 'leave', 'move', 'rise', 'sing', 'speak', 'step', 'turn', 'walk'];
var butBeginning = ['but', 'for', 'then'];
var butEnding = ['earth', 'sea', 'sky', 'sun'];
var nailedEnding = ['coffin', 'deck', 'desk', 'groove', 'mast', 'spar', 'pole', 'plank', 'rail', 'room', 'sash'];

function exclaimLine(n)
               {
               var a, b = n % twoSyllable.length;
               n = Math.floor(n / twoSyllable.length);
               a = n % threeToFiveSyllable.length;
               return threeToFiveSyllable[a] + '! ' + twoSyllable[b] + '!';
               }

               // The function nailedLine() produces a line beginning "nailed to the ..."
               // In Moby-Dick, Ahab nails a doubloon to the mast, offering it as a reward
               // to the one who sees the white whale first. This line template is meant to
               // semantically mirror an extended attempt to find axial support, both by the
               // reader of our poem and within Melville's novel, where being "at sea"
               // involves trying to locate a moral compass, trying to track down a quarry,
               // trying to control the crew through bribery, and using the mast itself as
               // a pointer to the stars in 19th-century navigation.

               // The array variable shortPhrase contains short phrases, almost all of 
               // which are taken from Melville's Moby-Dick:
               
               var shortPhrase = ['circle on', 'dash on', 'let them', 'listen now', 'loop on', 'oh time', 'plunge on', 'reel on', 'roll on', 'run on', 'spool on', 'steady', 'swerve me?', 'turn on', 'wheel on', 'whirl
               on', 'you — too — ', 'fast-fish', 'loose-fish'];

               // The array variable dickinsonNoun contains common nouns from Dickinson's
               // poems. We judged these nouns as common using a frequency analysis of the
               // words in the poems.

"fields": [
  {
    "label": "title",
    "value": "lé de tenture"
  },
  {
    "label": "Désignation",
    "value": "lé de tenture"
  },
  {
    "label": "N° d'inventaire",
    "value": "VMB 14527"
  },
  {
    "label": "Domaine",
    "value": "Textiles"
  },
  {
    "label": "Date de création",
    "value": "XVIIIe siècle"
  }
]

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{
    "Afrique de Sud"    :   "dbr:South_Africa",
    "Andorre"           :   "dbr:Andorra",
    "Angola"            :   "dbr:Angola",
    "Arabie saoudite"   :   "dbr:Saudi_Arabia",
}

\version "2.22"
\header {
    title   = "Motherless Child"
    composer = "African-American spiritual"
    tagline = ##f % don't add a Lilypond credit to footer
}
MusicS = {
  \clef "treble"
  \time 4/4
  \key des\major        % that is, d-es, D flat
  | des''4 f''2 des''4  % c' = Helmhotz C4
  | f''2 des''4 es''4
  | f''4. es''4. des''4
  | bes'2. r4
  \bar "|."
}
LyricsS = \lyricmode {
  Some -- times I feel
  like a mo -- ther -- less child
}
\score {
  <<
    \new Staff \with { instrumentName = "Soprano" }
    <<
      \new Voice = "Sop" { \MusicS }
      \new Lyrics \lyricsto "Sop" { \LyricsS }
    >>
  >>
  \layout {
    indent = 1\in       % first-line indent
    ragged-right = ##f  % fill the whole line
  }
}

\lyricmode {
   Sanc -- tus,
   \override Lyrics.LyricText.font-shape = #'italic
   sanc -- tus
   \revert Lyrics.LyricText.font-shape
   sanc -- tus
}

\lyricmode { Sanc -- tus, \EdLyrics { sanc -- tus, } sanc -- tus }

\IncipitStaff "TIPLE I-1" "Ti. I-1" { \IncipitSIi }

% Chorus I, Soprano 1 incipit
IncipitSIi = {
  \MSclefGii % treble clef
  \MeterCZ   % Spanish CZ meter symbol (= C3)
  a''2       % first note
}

(define mezzo
  (lambda (dynamic)
    (string-append "mezzo" dynamic)))
						

Section =
#(define-scheme-function
  (SectionText) (markup?)
  "Print a section title"
  #{
    \once \override Score.RehearsalMark.self-alignment-X = #LEFT
    \once \override Score.RehearsalMark.padding = #6
    \once \override Score.RehearsalMark.outside-staff-priority = #2000
    \mark \markup \fontsize #1.5 $SectionText
  #})

MusicT = {
  \clef "treble"
  \MeterTriple
  | a'2 b'2 c''2
  | f'2\color e'1
  | a'1.~
  | a'2 gis'1\endcolor
  | b'2 c''2 d''2
  | cis''2. cis''4 d''2~\color
  | d''2 e''1\endcolor
}

ColorBracketLeft =
\markup { \combine
  \draw-line #'(0 . -1)
  \draw-line #'(1.5 . 0)
}

ColorBracketRight =
\markup { \combine
  \draw-line #'(0 . -1)
  \draw-line #'(-1.5 . 0)
}

DrawColorBrackets = {
  \override TextSpanner.dash-period = #0
  \override TextSpanner.bound-details.left.text = \ColorBracketLeft
  \override TextSpanner.bound-details.right.text = \ColorBracketRight
  \override TextSpanner.bound-details.left.attach-dir = #-1
  \override TextSpanner.bound-details.right.attach-dir = #1
  \override TextSpanner.bound-details.left-broken.text = ##f
  \override TextSpanner.bound-details.right-broken.text = ##f
  \override TextSpanner.staff-padding = #2
}

self.__template_word_categories = set([]) 
self.__toxicity = set(["toxic," "nontoxic"])

                            
for person in root.findall('.//tei:person', tei):
    person_id = person.get('{http://www.w3.org/XML/1998/namespace}id')
    person_uri = URIRef(base_uri + '/person/' + person_id)
    person_ref = '#' + person_id
    g.add( (person_uri, RDF.type, crm.E21_Person))
    
    same_as = person.get('sameAs').split()
    if same_as is not None:
        same_as = same_as.split()
        i = 0
        while i < len(same_as):
            same_as_uri = URIRef(same_as[i])
            g.add( (person_uri, OWL.sameAs, same_as_uri))
            i += 1
 
    persname = person.find('./tei:persName', tei)
    if persname is not None:
        label = persname.text
        label_lang = persname.get('{http://www.w3.org/XML/1998/namespace}lang')
        if label_lang is not None:
            g.add( (person_uri, RDFS.label, Literal(label, lang=label_lang)))
        else:
            g.add( (person_uri, RDFS.label, Literal(label)))

                    
                        

def us_slavery(year):
   year = int(year)
   if 1619 <= year <= 1863:
      self = 'enslaved'
   else:
      self = 'free'
      return self
def heir(I):
   I = 'his sorrowful, terrible heir'
   return I
def lucifer(state):
   I = 'self'
   if state == 'no':
      lucifer = 'Black_Lucifer'
      return lucifer
   else:
      I = heir(I)
      return I
def sleepers():
   I = 'hell-name'
   self = 'Curse'
   year = int(input('What year is it? '))
   self = us_slavery(year)
   if 1849 <= year < 1881:
      state = input('Was Black Lucifer dead? ')
      I = lucifer(state)
      if I != 'Black_Lucifer':
         print('I am',I)
         I = ['the God of Revolt','deathless','sorrowful','vast']
         for i in I:
            print('I am',i)
      else:
         if not self:
            print('REVOLT')
   elif year >=1881:
      print('A show of the summer softness\na contact of something unseen\nan amour of the
               light and air')
   elif 1776 <=year < 1849:
      print('We hold these truths to be self-evident\nthat all men are created
                  equal')
   else:
      print('Replica of the Great Hole of history')
sleepers()

TypeError: us_slavery() missing 2 required positional arguments: 'self' and 'year'
NameError: name 'slave' is not defined
NameError: name 'I' is not defined
Traceback (most recent call last):
   File "sleepers.py", line 21, in sleepers
      lucifer = Black_Lucifer
NameError: name 'Black_Lucifer' is not defined
Traceback (most recent call last):
   File "sleepers.py", line 40, in sleepers
      lucifer = lucifer(input("Was Black Lucifer dead? "))
UnboundLocalError: local variable 'lucifer' referenced before assignment

class TreebankUnit(HookTest.units.TESTUnit):
    tests = ["parsable", "has_root"]
    readable = {
        "parsable": "File parsing",
        "has_root": "Root declared"
    }
    
    def __init__(self, path):
        super(HookTest.units.TESTUnit, self).__init__(path)
    
    def has_root(self):
        # Process
        self.log("If something needs to be verbose")
        has_root = True  # Assign result as a boolean
        yield has_root
    
    def test(self, scheme):
        tests = [] + CTSUnit.tests
        tests.append(scheme)
        
        for testname in tests:
            # Show the logs and return the status
            for status in getattr(self, testname)():
                yield (
                   TreebankUnit.readable[testname],
                   status,
                   self.logs
                )
        self.flush()

                   
                   genderdata::kantrowitz
                    ## Source: local data frame [7,579 x 2]
                    ##
                    ##            name     gender
                    ## 1         aamir       male
                    ## 2         aaron       male
                    ## 3         abbey     either
                    ## 4         abbie     either
                    ## 5         abbot       male
                    ## 6        abbott       male
                    ## 7          abby     either
                    ## 8         abdel       male
                    ## 9         abdul       male
                    ## 10   abdulkarim       male
                    ## ..           ...        ...

                    
                    gender ("abby", method = "kantrowitz")
                   
                   ## $name
                    ## [1]   "abby"
                    ## 
                    ## $gender
                    ## [1]   "either"

 
                     
                     genderdata::ssa_national
                     
                     ## Source: local data frame [1,603,026 x 4]
                     ## 
                     ## name        year   female male
                     ## 1 aaban     2007        0    5
                     ## 2 aaban     2009        0    6
                     ## 3 aaban     2010        0    9
                     ## 4 aaban     2011        0   11
                     ## 5 aaban     2012        0   11
                     ## 6 aabha     2011        7    0
                     ## 7 aabha     2012        5    0
                     ## 8 aabid     2003        0    5
                     ## 9 aabriella 2008        5    0
                     ## 10 aadam    1987        0    5
                     ## ..   ...    ...        ... ...

                     
                     genderdata::ssa_national %>%
                        filter(name == "sidney", year == 1935)
                    
                     ## Source: local data frame [1 x 4]
                     ## 
                     ##        name  year female  male
                     ## 1     sidney 1935  93     974

                            
                       
                       genderdata::ssa_national %>%
                           filter(name == "sidney", year == 1935) %>%
                         mutate(proportion_female = female / (male + female),
                                proportion_male = 1 - proportion_female)
                         
                         ## Source: local data frame [1 x 6]
                         ## 
                         ##     name year female male proportion_female  proportion_male
                         ## 1 sidney 1935     93  974        0.08716026        0.9128397
                        

 
    \begin{verbatim} 

    library("NMF") 
    library("FactoMineR") 
    library("data.table")
    library("ggplot2") 
    library("cowplot") 
    library("ggdendro") 
    library("pvclust")                    
    #data.df<-data.frame(syl_matrix_forR_090416)[1:319,5:14]
    data.df<-data.frame(syl_matrix_forR_090416)[1:319,4:14]
    rownames(data.df)<-data.df$Sign.Value 
    data.df<-data.df[,2:11]
    data.df<-data.df[rowSums(data.df)>0,] 
    
    #unfiltered w/ Assur
    colnames(data.df)<-gsub("Esznunna","Eshnunna",colnames(data.df))
    rclust<-hclust(dist(data.df,method="manhattan"), method="ward.D2")
    cclust<-hclust(dist(t(data.df),method="manhattan"), method="ward.D2")
    aheatmap(data.df,color='grey:2', Rowv=rclust,breaks=c(-0.05,0.5,1.05),
    labRow=NULL,main="Hierarchical clustering of sites by syllabic value
    attestations \n", legend=FALSE, fontsize=14, cexCol = 0.8) 
    
    #unfiltered data w/ Assur 
    forpca<-t(data.df)
    answer<-PCA(forpca,ncp=10,graph=FALSE)
    pc.eig.df<-data.frame(answer$eig)
    ggplot(data=pc.eig.df[c(1:9),], aes(x=gsub("comp","Comp.",
        rownames(pc.eig.df[c(1:9),])), y=percentage.of.variance)) + 
    geom_bar(stat="identity" +xlab("\nPrincipal Component")
        +ylab("Percentage of Variance") +ggtitle("Variance distribution
        across principal components derived from viable syllabic values")
        coord.rs.df<-data.frame(answer$ind$coord) 
        gsub("Esznunna","E?nunna",row.names(coord.rs.df)) 
        Geography<-factor(c("Syria", "Syria", "Syria", "Syria", "Southern 
        Mesopotamia", "Southern Mesopotamia", "Southern Mesopotamia",
        "Southern Mesopotamia", "Northern Mesopotamia", "Northern Mesopotamia"), 
        levels=c("Southern Mesopotamia", "Northern Mesopotamia", "Syria")) 
        Period<-factor(c("Old Akkadian\n(ca. 2350-2200 BC)", "\nUr III/ 
        Shakkanakku\n(ca. 2100-2000 BC)", "Old Akkadian\n(ca. 2350-2200 BC)",
        "\nEarly Old Babylonian\n(ca. 2000-1900 BC)\n", "\nOld Akkadian & Ur
        III\n(ca. 2350-2200, 2100-2000 BC)", "Old Akkadian \n(ca. 2350-2200 BC)",
        "Old Akkadian\n(ca. 2350-2200 BC)", "Old Akkadian\n(ca. 2350-2200 BC)", "Old
        Akkadian\n(ca. 2350-2200 BC)", "Old Akkadian\n(ca. 2350-2200 BC)"),
        levels=c("Old Akkadian\n(ca. 2350-2200 BC)", "\nOld Akkadian & Ur
        III\n(ca. 2350-2200, 2100-2000 BC)", "\nUr III / Shakkanakku \n(ca.
        2100-2000 BC)", "\n Early Old Babylonian \n(ca. 2000-1900 BC)\n"))
    ggplot(data=coord.rs.df, aes(x=Dim.1, y=Dim.2))+geom_point(aes(shape=Period,
        fill=Geography, color=Geography),size=4)+scale_shape_manual
        (values=c(21,22,23,24))+xlab("Princ. Comp. 1")+ylab("Princ. Comp. 2")
        +geom_text(label=gsub("Esznunna","E?nunna", row.names(coord.rs.df)),
        nudge_y=0.7) 
        
    #filtering out hapax signs and allsites signs
    data2.df<-data.df[rowSums(data.df)>1 & rowSums(data.df)<9,-9]
    colnames(data2.df)<-gsub("Esznunna","Eshnunna",colnames(data2.df))
    colnames(data.df)<-gsub("Esznunna","Eshnunna",colnames(data.df)) 
    
    #convert table into final table for thesis for hapax signs
    data.onesite.df<-data.df[rowSums(data.df)==1,]
    data.onesite.df$Site<-"DUMMY"
    data.onesite.df[data.onesite.df$Ebla==1,]$Site<-"Ebla"
    data.onesite.df[data.onesite.df$Mari==1,]$Site<-"Mari"
    data.onesite.df[data.onesite.df$Nabada==1,]$Site<-"Nabada"
    data.onesite.df[data.onesite.df$Tuttul==1,]$Site<-"Tuttul"
    data.onesite.df[data.onesite.df$Adab==1,]$Site<-"Adab"
    data.onesite.df[data.onesite.df$E?nunna==1,]$Site<-"E?nunna"
    data.onesite.df[data.onesite.df$Kish==1,]$Site<-"Kish"
    data.onesite.df[data.onesite.df$Tutub==1,]$Site<-"Tutub"
    #data.onesite.df[data.onesite.df$Assur==1,]$Site<-"Assur"
    data.onesite.df[data.onesite.df$Gasur==1,]$Site<-"Gasur"
    final.onesite.dt<-data.table(data.onesite.df,
    final.onesite.dt<-final.onesite.dt[order(Site)]
    keep.rownames=TRUE)[,.(rn, Site)] write.table(final.onesite.dt,
    file="hapax_signs.xls", quote=FALSE, sep="\t", row.names=FALSE) 
                        
    #table of signs that occur at all sites
    data.allsites.df<-data.df[rowSums(data.df[,-9])==9,-9]
    write.table(rownames(data.allsites.df), file="allsites_signs.xls",
        quote=FALSE, sep="\t", row.names=FALSE) 
        
    #table of filtered data
    write.table(rownames(data2.df),file="data_filtered.xls", quote=FALSE,
        sep="\t", row.names=TRUE, col.names=TRUE)
    write.table(data2.df,file="data_filtered.xls",sep="\t") 
    
    #hierarchical clustering
    colnames(data2.df)<-gsub("Esznunna","Eshnunna",colnames(data2.df))
    rclust<-hclust(dist(data2.df,method="manhattan"), method="ward.D2")
    cclust<-hclust(dist(t(data2.df),method="manhattan"), method="ward.D2")
    aheatmap(data2.df,color='grey:2', Rowv=rclust,breaks=c(-0.05,0.5,1.05),
        labRow=NULL, legend=FALSE, fontsize=14, cexCol = 0.8) 
    result <-pvclust(data2.df, method.dist="manhattan", 
        method.hclust="ward.D2", nboot=10000) 
    plot(result) 
    
    #PCA
    colnames(data2.df)<-gsub("E?nunna","Eshnunna",colnames(data2.df))
    forpca<-t(data2.df) 
    answer<-PCA(forpca,ncp=3,graph=FALSE)
    pc.eig.df<-data.frame(answer$eig) 
    ggplot(data=pc.eig.df[c(1:8),], aes(x=gsub("comp","Comp.",
        rownames(pc.eig.df[c(1:8),])), y=percentage.of.variance)) +
        geom_bar(stat="identity")+xlab("\nPrincipal Component") +
        ylab("Percentage of Variance")+ggtitle("Variance distribution across 
        principal components \n derived from informative syllabic values \n")
    coord.rs.df<-data.frame(answer$ind$coord)
    #meta.pca.df<-meta.df[rownames(coord.rs.df),] 
    
    #PC1
    gsub("Esznunna","Eshnunna", row.names(coord.rs.df))
    Geography<-factor(c("Syria", "Syria", "Syria", "Syria", "Southern
        Mesopotamia", "Southern Mesopotamia", "Southern Mesopotamia", "Southern
        Mesopotamia", "Northern Mesopotamia"), levels=c("Southern Mesopotamia",
        "Northern Mesopotamia", "Syria")) 
    Period<-factor(c("Old Akkadian\n(ca. 2350-2200 BC)", "\nUr III /
        Shakkanakku \n(ca. 2100-2000 BC)", "Old Akkadian\n(ca. 2350-2200 BC)",
        "\nEarly Old Babylonian\n(ca. 2000-1900 BC)\n", "\nOld Akkadian & 
        Ur III \n(ca. 2350-2200, 2100-2000 BC)", "Old Akkadian\n(ca. 2350-2200 BC)", 
        "Old Akkadian \n(ca. 2350-2200 BC)", "Old Akkadian\n(ca. 2350-2200 BC)", 
        "Old Akkadian\n(ca. 2350-2200 BC)"), levels=c("Old Akkadian \n(ca. 2350-2200 BC)",
        "\nOld Akkadian & Ur III\n(ca. 2350-2200, 2100-2000 BC)", "\nUr III / 
        Shakkanakku\n(ca. 2100-2000 BC)", "\nEarly Old Babylonian \n(ca. 2000-1900 BC) \n"))
    ggplot(data=coord.rs.df, aes(x=Dim.1, y=Dim.2))+geom_point(aes
        (shape=Period, fill=Geography, color=Geography),size=4)
        +scale_shape_manual(values=c(21,22,23,24))+xlab("Princ. Comp.
        1")+ylab("Princ. Comp. 2")+geom_text(label=gsub ("Esznunna","Eshnunna",
        row.names(coord.rs.df)),nudge_y=0.5) 
    ggplot(data=coord.rs.df, aes(x=Dim.2, y=Dim.3))+geom_point(aes
        (shape=Period, fill=Geography, color=Geography),size=4) 
        +scale_shape_manual(values=c(21,22,23,24))+xlab(
        "Princ. Comp. 2")+ylab("Princ. Comp. 3+geom_text(label=gsub
        ("Esznunna","Eshnunna", row.names(coord.rs.df)), nudge_y=0.5)
    ggplot(data=coord.rs.df, aes(x=Dim.1, y=Dim.3))+geom_point(aes(shape=Period,
        fill=Geography, color=Geography),size=4)+scale_shape_manual
        (values=c(21,22,23,24))+ xlab("Princ. Comp. 1")+ylab("Princ. Comp.
        3"+geom_text(label=gsub("Esznunna","Eshnunna", row.names (coord.rs.df)),
        nudge_y=0.5) 
                        
    #Extract attestations that define principal components 1-3
    signs<-data.table(answer$var$contrib, keep.rownames = TRUE) 
                        
    #dim1 excel table and visualization 
    dim1<-signs[order(-abs(Dim.1))][,1:2,with=FALSE]
    ggplot(data=dim1, aes(x=seq(from=1, to=188,by=1),y=Dim.1))
        +geom_point(size=1, color="black")+xlab("\nSyllabic value index ordered by
        loadings on the first principal component")+ylab("Loadings on the first
        principal component\n")+ggtitle("The distribution of loadings for syllabic
        values suggests that\nloadings greater than 1.2 should be further
        examined.") +geom_hline(yintercept = 1.25) 
    dim1<-dim1[dim1$Dim.1>1.1,]
    data2.dim1.df<-data2.df[dim1$rn,]
    colnames(data2.dim1.df)<-gsub("Esznunna","Eshnunna",colnames(data2.dim1.df))
    rclust<-hclust(dist(data2.dim1.df,method="manhattan"), method="ward.D2")
    cclust<-hclust(dist(t(data2.dim1.df),method="manhattan"), method="ward.D2") 
    anngeo<-list(Geography=Geography)
    aheatmap(data2.dim1.df,color='grey:2', Rowv=rclust,breaks=c(-0.05,0.5,1.05),
        annCol = anngeo, legend=FALSE,main="Hierarchical clustering of sites by
        syllabic value attestations\nimportant in the first principal component",
        fontsize=10,treeheight=10, cexCol = 1, cexRow=2) write.table(dim1,
        file="dim1_signloadings.xls", quote=FALSE, sep="\t", row.names=FALSE) 
        
    #dim2 excel table and visualization
    dim2<-signs[order(-abs(Dim.2))][,c(1,3),with=FALSE] 
    ggplot(data=dim2, aes(x=seq(from=1, to=188,by=1),y=Dim.2)) + geom_point(
        size=1, color="black")+xlab("\nSyllabic value index ordered by loadings 
        on the second principal component")+ylab("Loadings on the second principal
        component\n")+ggtitle("The distribution of loadings for syllabic values
        suggests that\nloadings greater than 1.1 should be further examined.")+geom_hline(yintercept = 1.1) 
    dim2<-dim2[dim2$Dim.2>1.1,]
    data2.dim2.df<-data2.df[dim2$rn,]
    colnames(data2.dim2.df)<-gsub("Esznunna","Eshnunna",colnames(data2.dim2.df))
    rclust<-hclust(dist(data2.dim2.df,method="manhattan"), method="ward.D2")
    cclust<-hclust(dist(t(data2.dim2.df),method="manhattan"), method="ward.D2") 
    annperiod<-list(Period=gsub("^ ","",gsub("\n"," ", Period))) 
    aheatmap(data2.dim2.df,color='grey:2', Rowv=rclust,breaks=c(-0.05,0.5,1.05), 
        annCol=annperiod, legend=FALSE,main="Hierarchical clustering of sites by 
        syllabic value attestations\nimportant in the second principal component",
        fontsize=10,treeheight=10, cexCol = 1, cexRow=3) write.table(dim2,
        file="dim2_signloadings.xls", quote=FALSE, sep="\t", row.names=FALSE) 
        
        
    #dim3 excel table and visualization
    dim3<-signs[order(-abs(Dim.3))][,c(1,4),with=FALSE] 
    ggplot(data=dim3, aes(x=seq(from=1, to=188,by=1),y=Dim.3))
        +geom_point(size=1, color="black")+xlab("\nSyllabic value index ordered
        by loadings on the third principal component")+ylab("Loadings on the third
        principal component\n")+ggtitle("The distribution of loadings for syllabic 
        values suggests that\nloadings greater than 1.3 should be further
        examined."+geom_hline(yintercept = 1.3) 
    dim3<-dim3[dim3$Dim.3>1.3,]
    data2.dim3.df<-data2.df[dim3$rn,]
    colnames(data2.dim3.df)<-gsub("Esznunna","Eshnunna",colnames(data2.dim3.df))
    rclust<-hclust(dist(data2.dim3.df,method="manhattan"), method="ward.D2")
    cclust<-hclust(dist(t(data2.dim3.df),method="manhattan"), method="ward.D2") 
    aheatmap(data2.dim3.df,color='grey:2', Rowv=rclust,breaks=c(-0.05,0.5,1.05), 
        legend=FALSE,main="HierarchicaL clustering of sites by syllabic value attestations
        \nimportant in the third principal component", fontsize=10, treeheight=10, 
        cexCol = 1, cexRow=2)
    write.table(dim3, file="dim3_signloadings.xls", quote=FALSE, sep="\t", row.names=FALSE) 
                    

 
                        for a in authors: 
                            for p in listOfPatternsOrderedByDecreasingContribution: 
                        n = getNearestNovel(p) 
                        add p to listOfPatterns[a] 
                        if listOfPatterns[a] has length = 5: 
                            exit 

            create view t311
            FROM
            (
            select
            case when cell_id is not null then '4' else '4' end as city
            , cell_id
            , date_trunc('hour', "Requested Date/Time") as hr
            , case when t311_all."Service Name" = 'Graffiti Removal' then 1 else 0 end as graf
            , case when t311_all."Service Name" = 'Illegal Dumping' then 1 else 0 end as illdumping
            , case when t311_all."Service Name" = 'Maintenance Residential or Commercial' then 1 else 0 end as bldgmaint
            --, null as streetsw
            --, null as electrical
            , case when t311_all."Service Name" = 'Sanitation / Dumpster Violation' then 1 else 0 end as sanitation
            --, null as recycling
            , case when t311_all."Service Name" = 'Street Trees' then 1 else 0 end as tree
            , case when t311_all."Service Name" = 'Traffic (Other)' then 1 else 0 end as traffic
            , case when t311_all."Service Name" = ' Vacant House or Commercial' then 1 else 0 end as vac_bldg
            , case when t311_all."Service Name" = 'Abandoned Vehicle' then 1 else 0 end as vac_vehicle
            , case when t311_all."Service Name" = 'Street Light Outage' then 1 else 0 end as stlghts
            , case when t311_all."Service Name" = 'Alley Light Outage ' then 1 else 0 end as alleylghts
            --, null as potholes
            , case when t311_all."Service Name" = 'Rubbish/Recyclable Material Collection' then 1 else 0 end as garbage_pickup
            --, null as rodent
            --, null as sidewalk
            

            FROM
            (
            select
            case when cell_id is not null then '4' else '4' end as city
            , cell_id
            , date_trunc('hour', "Requested Date/Time") as hr
            , case when t311_all."Service Name" = 'Graffiti Removal' then 1 else 0 end as graf
            , case when t311_all."Service Name" = 'Illegal Dumping' then 1 else 0 end as illdumping
            , case when t311_all."Service Name" = 'Maintenance Residential or Commercial' then 1 else 0 
            end as bldgmaint  
            

            --, null as streetsw
            --, null as electrical
            

            , case when t311_all."Service Name" = 'Sanitation / Dumpster Violation' then 1 else 0 end as sanitation
            --, null as recycling
            , case when t311_all."Service Name" = 'Street Trees' then 1 else 0 end as tree
            , case when t311_all."Service Name" = 'Traffic (Other)' then 1 else 0 end as traffic
            , case when t311_all."Service Name" = ' Vacant House or Commercial' then 1 else 0 end as vac_bldg
            , case when t311_all."Service Name" = 'Abandoned Vehicle' then 1 else 0 end as vac_vehicle
            , case when t311_all."Service Name" = 'Street Light Outage' then 1 else 0 end as stlghts
            , case when t311_all."Service Name" = 'Alley Light Outage ' then 1 else 0 end as alleylghts
            --, null as potholes
            , case when t311_all."Service Name" = 'Rubbish/Recyclable Material Collection' then 1 else 0 end as garbage_pickup
            --, null as rodent
            --, null as sidewalk
            

            AS
            select city, cell_id, hr, sum(graf) as graf, sum(illdumping) as illdumping, sum(bldgmaint) as bldgmaint
            , sum(sanitation) as sanitation, sum(traffic) as traffic, sum(vac_bldg) as vac_bldg
            , sum(vac_vehicle) as vac_vehicle, sum(stlghts) as stlghts, sum(alleylghts) as alleylghts
            , sum(garbage_pickup) as garbage_pickup
            , sum(graf) + sum(illdumping) + sum(bldgmaint) + sum(sanitation) + sum(traffic) + sum(vac_bldg) + sum(vac_vehicle) 
              + sum(stlghts) + sum(alleylghts) + sum(garbage_pickup)
            as t311Events
            

            , case when t311_all."Service Name" = 'Street Trees' then 1 else 0 end as tree
            

<tbx xml:lang="en" style="dct" type="TBX-Min"
    >
  <text>
    <body>
      <conceptEntry id="1">
        <langSec xml:lang="en">
          <termSec>
            <term>mouse pad</term>
          </termSec>
          <termSec>
            <term>mouse mat</term>
          </termSec>
        </langSec>
        <langSec xml:lang="es">
          <termSec>
            <term>soporte para ratón</term>
          </termSec>
          <termSec>
            <term>alfombrilla de ratón</term>
          </termSec>
        </langSec>
        <langSec xml:lang="it">
          <termSec>
            <term>tappetino per mouse</term>
          </termSec>
        </langSec>
      </conceptEntry>
      <conceptEntry id="2">
        ...
      </conceptEntry>
    </body>
  </text>
</tbx>

<conceptEntry id="cl">
  <min:subjectField>e-mobility</min:subjectFi.eld>
  <langSec xml:lang="en">
    <descripGrp>
      <basic:definition>A battery-electric car that is capable of
          traveling at a maximum speed of 25 miles per hour (mph)
          and has a maximum loaded weight of 3,000 lbs.
      </basic:definition>
      <basic:source>TechTarget</basic:source>
      <min:externalCrossReference>https://www.techtarget.com/whatis/definition/
          neighborhood-electric-vehicle-NEV</min:externalCrossReference>
    </descripGrp>
    <termSec>
      <term>neighborhood electric vehicle</term>
      <basic:termType>fullForm</basic:termType>
      <min:partOfSpeech>noun</min:partOfSpeech>
      <min:administrativeStatus>preferredTerm-admn-sts</min:administrativeStatus>
      <descripGrp>
        <basic:context>A Neighborhood Electric Vehicle (NEV) is a U.S.
            category for battery electric vehicles that are usually built to
            have a top speed of 25 miles per hour (40 km/h), and have a
            maximum loaded weight of 3,000 lb (1,400 kg).
        </basic:context>
        <basic:source>Wikipedia</basic:source>
        <min:externalCrossReference>https://en.wi.kipedia.org/wiki/
            Neighborhood_Electric_Vehicle</min:externalCrossReference>
      </descripGrp>
    </termSec>
    <termSec>
      <term>NEV</term>
      <basic:termType>acronym</basic:termType>
      <min:partOfSpeech>noun</min:partOfSpeech>
      <min:administrativeStatus>admittedTerm-admn-sts</min:administrativeStatus>
    </termSec>
  </langSec>
  <langSec xml:lang="fr"> ... </langSec xml:lang="fr">
  <langSec xml:lang="it"> ... </langSec xml:lang="it">
</conceptEntry>

<l>a)/ndra moi e)/nnepe, mou=sa, polu/tropon, o(\s ma/la polla\</l>
                     

<l>mh=ter e)pei/ m' e)/teke/s ge minunqa/dio/n per e)o/nta,</l>
<l>timh/n pe/r moi o)/fellen *)olu/mpios e)gguali/cai</l>
<l>*zeu\s u(yibreme/ths: nu=n d' ou)de/ me tutqo\n e)/tisen:</l>
<l n="355">h)= ga/r m' *)atrei/+dhs eu)ru\ krei/wn *)agame/mnwn</l>
<l>h)ti/mhsen: e(lw\n ga\r e)/xei ge/ras au)to\s a)pou/ras.</l>
					

<lb/><milestone ed="P" unit="para" />kou/rh d' *)wkeanou=, *xrusa/ori karteroqu/mw|
<lb rend="displayNum" n="980" />mixqei=s' e)n filo/thti poluxru/sou *)afrodi/ths, 
<lb />*kalliro/h te/ke pai=da brotw=n ka/rtiston a(pa/ntwn,
<lb />*ghruone/a, to\n ktei=ne bi/h *(hraklhei/h
<lb />bow=n e(/nek' ei)lipo/dwn a)mfirru/tw| ei)n *)eruqei/h|.
					

         —-
         title: Bol
         author: Faiz Ahmed Faiz
         —-
         Bol kih lab… (Poem text is here in the body )

            —-
         en:
            title: Faiz Ahmed Faiz
            bday: 1911.02.13
            body: Urdu poet
         hi:
            title: "फ़ैज़ अहमद फ़ैज़" 
            body: उर्दू शायर
         ur:            title: فیض احمد فیض
            body: اردو شاعر 
         —-

         —-
         en:
             title: Bol
         author:
            - Faiz Ahmed Faiz
         body: |-
         bol kih lab aazaad hai tere
         bol zabaa;n ab tak terii hai
         hi:
            author:
            - Faiz Ahmed Faiz
            title: बोल
               body: |-
               बोल कि लब आज़ाद है तेरे 
               बोल ज़बाँ अब तक तेरी है 
         ur:
            author:
               - Faiz Ahmed Faiz
            title: بول
            body: |-
               بول کہ لب آزاد ہے تیرے                 
               بول زباں اب تک تیری ہے 
         —-

                        
<http://dbpedia.org/resource/Alexander_the_Great> # Alexander the Great
<http://dbpedia.org/ontology/parent> # has parent
<http://dbpedia.org/resource/Philip_II_of_Macedon> # Philip II of Macedon

                    
                    

                        
<person sameAs="http://viaf.org/viaf/101353608">Alexander the Great</person>

                    
                    

                                <text lang="eng"> <text lang="eng">
                                </text> </text>