acronym(): Generate acronym from input stringinitialism(): Generate initialism from input stringmince(): Prepare input stringThe minimal usage for creating an acronym:
library(acroname)
set.seed(123)
acronym("super special software package", acronym_length = 5)
#> [1] "SUSIE: SUper SpecIal softwarE package"And an initialism for the same string:
The functions can accept input character vectors that either contain the string in a single element or are prepared with one element per word:
acronym(c("super", "special", "software", "package"), acronym_length = 5)
#> [1] "SUSIE: SUper SpecIal softwarE package"tibbleBoth acronym() and initialism() include an option to return the result as a tibble object:
acronym("dip him in the river who loves water", acronym_length = 4, to_tibble = TRUE)
#> # A tibble: 1 x 4
#> formatted prefix suffix original
#> <chr> <chr> <chr> <chr>
#> 1 ROOT: dip him in River wh… ROOT dip him in River whO … dip him in river who…Each function can also be customized to exclude articles in the input string:
initialism("dip him in the river who loves water", to_tibble = TRUE, ignore_articles = TRUE)
#> # A tibble: 1 x 4
#> formatted prefix suffix original
#> <chr> <chr> <chr> <chr>
#> 1 DHIRWLW: Dip Him In River … DHIRWLW Dip Him In River Wh… dip him in river who…Using the “bow” option will trigger processing using a “bag of words” method, by which words in the input string are randomly selected. The number of words selected from the input string depends on the value passed to the “bow_prop” argument:
acronym("dip him in the river who loves water the fountain contains the cistern overflows", ignore_articles = TRUE, acronym_length = 4, bow = TRUE, bow_prop = 0.75)
#> [1] "INRI: dip loves hIm who water fouNtain River In cistern"It is possible to generate a series of randomized results by iterating over the function:
library(purrr)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
## write a function to wrap acronym() in order to map
mapwrap <- function(i, input) {
res <-
acronym(input = input, ignore_articles = TRUE, acronym_length = 4, bow = TRUE, bow_prop = 0.75, to_tibble = TRUE) %>%
mutate(iteration = i, .before = "formatted")
return(res)
}
iterations <- paste0("iteration_",1:5)
map_df(iterations, mapwrap, "dip him in the river who loves water the fountain contains the cistern overflows")
#> # A tibble: 5 x 5
#> iteration formatted prefix suffix original
#> <chr> <chr> <chr> <chr> <chr>
#> 1 iteration… CORA: dip Cistern whO… CORA dip Cistern whO … dip cistern who ri…
#> 2 iteration… HOWE: Him who cistern… HOWE Him who cistern … him who cistern ov…
#> 3 iteration… CROW: loves dip who C… CROW loves dip who Co… loves dip who cont…
#> 4 iteration… INST: IN him containS… INST IN him containS … in him contains ci…
#> 5 iteration… DIOR: cistern who DIp… DIOR cistern who DIp … cistern who dip ov…By default the acronym() engine will search for acronyms that match words in the “en_US” dictionary provided by the hunspell package. However, the dictionary of words to match can be customized via the “dictionary” argument. The example below uses a dictionary based on names from the dplyr package, prepared with a little help from the mince() function:
## get names (first or last) from the dplyr::starwars data
## see mince() in action
mince(starwars$name)
#> $words
#> [1] "Luke" "Skywalker" "C3PO" "R2D2" "Darth"
#> [6] "Vader" "Leia" "Organa" "Owen" "Lars"
#> [11] "Beru" "Whitesun" "lars" "R5D4" "Biggs"
#> [16] "Darklighter" "ObiWan" "Kenobi" "Anakin" "Skywalker"
#> [21] "Wilhuff" "Tarkin" "Chewbacca" "Han" "Solo"
#> [26] "Greedo" "Jabba" "Desilijic" "Tiure" "Wedge"
#> [31] "Antilles" "Jek" "Tono" "Porkins" "Yoda"
#> [36] "Palpatine" "Boba" "Fett" "IG88" "Bossk"
#> [41] "Lando" "Calrissian" "Lobot" "Ackbar" "Mon"
#> [46] "Mothma" "Arvel" "Crynyd" "Wicket" "Systri"
#> [51] "Warrick" "Nien" "Nunb" "QuiGon" "Jinn"
#> [56] "Nute" "Gunray" "Finis" "Valorum" "Jar"
#> [61] "Jar" "Binks" "Roos" "Tarpals" "Rugor"
#> [66] "Nass" "Ric" "Olié" "Watto" "Sebulba"
#> [71] "Quarsh" "Panaka" "Shmi" "Skywalker" "Darth"
#> [76] "Maul" "Bib" "Fortuna" "Ayla" "Secura"
#> [81] "Dud" "Bolt" "Gasgano" "Ben" "Quadinaros"
#> [86] "Mace" "Windu" "KiAdiMundi" "Kit" "Fisto"
#> [91] "Eeth" "Koth" "Adi" "Gallia" "Saesee"
#> [96] "Tiin" "Yarael" "Poof" "Plo" "Koon"
#> [101] "Mas" "Amedda" "Gregar" "Typho" "Cordé"
#> [106] "Cliegg" "Lars" "Poggle" "Lesser" "Luminara"
#> [111] "Unduli" "Barriss" "Offee" "Dormé" "Dooku"
#> [116] "Bail" "Prestor" "Organa" "Jango" "Fett"
#> [121] "Zam" "Wesell" "Dexter" "Jettster" "Lama"
#> [126] "Su" "Taun" "We" "Jocasta" "Nu"
#> [131] "Ratts" "Tyerell" "R4P17" "Wat" "Tambor"
#> [136] "San" "Hill" "Shaak" "Ti" "Grievous"
#> [141] "Tarfful" "Raymus" "Antilles" "Sly" "Moore"
#> [146] "Tion" "Medon" "Finn" "Rey" "Poe"
#> [151] "Dameron" "BB8" "Captain" "Phasma" "Padmé"
#> [156] "Amidala"
#>
#> $collapsed
#> [1] "LukeSkywalkerC3POR2D2DarthVaderLeiaOrganaOwenLarsBeruWhitesunlarsR5D4BiggsDarklighterObiWanKenobiAnakinSkywalkerWilhuffTarkinChewbaccaHanSoloGreedoJabbaDesilijicTiureWedgeAntillesJekTonoPorkinsYodaPalpatineBobaFettIG88BosskLandoCalrissianLobotAckbarMonMothmaArvelCrynydWicketSystriWarrickNienNunbQuiGonJinnNuteGunrayFinisValorumJarJarBinksRoosTarpalsRugorNassRicOliéWattoSebulbaQuarshPanakaShmiSkywalkerDarthMaulBibFortunaAylaSecuraDudBoltGasganoBenQuadinarosMaceWinduKiAdiMundiKitFistoEethKothAdiGalliaSaeseeTiinYaraelPoofPloKoonMasAmeddaGregarTyphoCordéClieggLarsPoggleLesserLuminaraUnduliBarrissOffeeDorméDookuBailPrestorOrganaJangoFettZamWesellDexterJettsterLamaSuTaunWeJocastaNuRattsTyerellR4P17WatTamborSanHillShaakTiGrievousTarffulRaymusAntillesSlyMooreTionMedonFinnReyPoeDameronBB8CaptainPhasmaPadméAmidala"
#>
#> $words_len
#> [1] 4 9 4 4 5 5 4 6 4 4 4 8 4 4 5 11 6 6 6 9 7 6 9 3 4
#> [26] 6 5 9 5 5 8 3 4 7 4 9 4 4 4 5 5 10 5 6 3 6 5 6 6 6
#> [51] 7 4 4 6 4 4 6 5 7 3 3 5 4 7 5 4 3 4 5 7 6 6 4 9 5
#> [76] 4 3 7 4 6 3 4 7 3 10 4 5 10 3 5 4 4 3 6 6 4 6 4 3 4
#> [101] 3 6 6 5 5 6 4 6 6 8 6 7 5 5 5 4 7 6 5 4 3 6 6 8 4
#> [126] 2 4 2 7 2 5 7 5 3 6 3 4 5 2 8 7 6 8 3 5 4 5 4 3 3
#> [151] 7 3 7 6 5 7
#>
#> $first_chars
#> [1] "L" "S" "C" "R" "D" "V" "L" "O" "O" "L" "B" "W" "l" "R" "B" "D" "O" "K"
#> [19] "A" "S" "W" "T" "C" "H" "S" "G" "J" "D" "T" "W" "A" "J" "T" "P" "Y" "P"
#> [37] "B" "F" "I" "B" "L" "C" "L" "A" "M" "M" "A" "C" "W" "S" "W" "N" "N" "Q"
#> [55] "J" "N" "G" "F" "V" "J" "J" "B" "R" "T" "R" "N" "R" "O" "W" "S" "Q" "P"
#> [73] "S" "S" "D" "M" "B" "F" "A" "S" "D" "B" "G" "B" "Q" "M" "W" "K" "K" "F"
#> [91] "E" "K" "A" "G" "S" "T" "Y" "P" "P" "K" "M" "A" "G" "T" "C" "C" "L" "P"
#> [109] "L" "L" "U" "B" "O" "D" "D" "B" "P" "O" "J" "F" "Z" "W" "D" "J" "L" "S"
#> [127] "T" "W" "J" "N" "R" "T" "R" "W" "T" "S" "H" "S" "T" "G" "T" "R" "A" "S"
#> [145] "M" "T" "M" "F" "R" "P" "D" "B" "C" "P" "P" "A"
sw_names <- mince(starwars$name)$words
acronym("latest and greatest data analysis package", dictionary = sw_names, acronym_length = 4)
#> [1] "LARS: Latest And gReatest data analySis package"Depending on the characters in the input string, the size of dictionary, and the acronym length it may not be possible to generate an acronym that matches a word in the dictionary. The acronym() function will try for 60 seconds by default, but this duration can be customized via the “timeout” argument:
## the longer the desired acronym, the longer it will likely to take to find a match
## setting the timeout to 2 seconds here
acronym("latest and greatest data analysis package", dictionary = sw_names, acronym_length = 10, timeout = 2)
#> Unable to find viable acronym in 'timeout' specified (2 seconds) ...Please use GitHub issues to report bugs or request features. Contributions will be reviewed via pull requests.