This S4 class is the basic unit of the
humdrumR package.
Each humdrumR object represents data read from one or
more humdrum files.
In the documentation, we refer to these objects interchangeably as
"humdrumR corpora", "humdrumR objects," or humdrumR data(sets).
In coding examples we name them "humData."
Test is an object/variable is a humdrumR dataset using is.humdrumR().
Usage
is.humdrumR(x)
# S3 method for humdrumR
print(
humdrumR,
view = humdrumRoption("view"),
dataTypes = humdrumRoption("dataTypes"),
firstAndLast = TRUE,
screenWidth = options("width")$width - 10L,
null = humdrumRoption("nullPrint"),
syntaxHighlight = humdrumRoption("syntaxHighlight"),
maxRecordsPerFile = if (length(humdrumR) == 1L) 800L else
humdrumRoption("maxRecordsPerFile"),
maxTokenLength = humdrumRoption("maxTokenLength"),
censorEmptyRecords = humdrumRoption("censorEmptyRecords")
)Arguments
- humdrumR
HumdrumR data.
Must be a humdrumR data object.
- view
How should humdrumR data be printed?
There are three options:
"humdrum","score", and"table"(aliases"data.frame"and"tibble"). These options are partially matched.Use
select()to determine which fields to show.- dataTypes
Which types of humdrum record(s) to view.
Defaults to
"GLIMDd"foras.lines()andas.matrix();"Dd"foras.data.frame();"LIMDd"foras.matrices()andas.data.frames().Must be a single
characterstring. Legal values are'G', 'L', 'I', 'M', 'D', 'd'or any combination of these (e.g.,"LIM"). (See the humdrum table documentation for explanation.)- syntaxHighlight
Should syntax highlighting (coloring) be used in printout?
Defaults to
TRUE.Must be a singleton logical value; an on/off switch.
- maxRecordsPerFile
How many records should be shown in each file, when more than one file is present?
Defaults to
40.Can be any positive whole number.
- maxTokenLength
Length at which longer tokens are censored with ...
Defaults to
16.Can be any positive whole number.
- censorEmptyRecords
Should consecutive records be "censored" (compressed) in printout?
Defaults to
30.Can be any positive whole number, up to
Inf. IfInf, no censoring will occur.
Details
The most important part of a humdrumR object is the
humdrum table it holds within it;
In essence, a humdrumR object is simply a wrapper around its
humdrum table, which helps users to
to visualize, filter, summarize, and manipulate
the table in a variety of ways.
Basic information about the size and shape of humdrumR objects can be
obtained with calls to nrecord, npiece, length, ncol, etc..
More detailed summary information can be obtained with the humdrumR corpus summary functions.
humdrumR data can also be coerced to more basic R data types using as.matrix, as.data.frame, etc..
A number of helpful functions are also defined to "reshape" or reorganize the
data (e.g., cleave(), rend(), collapseHumdrum()).
The most powerful features of humdrumR are the tools it gives you to...
Print a readable view of the data in shorthand/curtailed humdrum syntax.
Filter
humdrumRdata, usingsubset.humdrumR()and the standardRindexing operators:[]and[[]].Apply arbitrary commands to humtable fields using the with(in)Humdrum routines, and related tidyverse commands (
mutate(),summarize(), etc.).
Slots
HumtableA humdrum tables---i.e, a
data.table::data.table()with particular fields.FilesA list of two elements. The first, "
Search", contains a single character representing thepatternused in the call toreadHumdrum()which created this humdrumR object. The second, "Names," is a vector of strings representing all the files which matched thepatternand were read into thehumdrumRobject, withnames()corresponding to their "subcorpora" labels (Label).FieldsA data.table indicating the existing fields in the
humdrumRobject's humdrum table. The fields are divided into five categories: "Data", "Structure", "Interpretation", "Formal", and "Reference."LoadTimeA POSIXct value, indicating the time at which
readHumdrum()was called to create thishumdrumRobject.ContextA data.table with two columns:
OpenandClose. Each row represents a contextual window to apply to the data.
Viewing your Data
If you type the name of an object on the R command line, R will "print" the object in the console.
This can be also be done explicitly using the humdrumR method of the print() function.
The humdrumR print method contains a number of arguments, which can be manipulated directly in calls to print().
However, the humdrumR print argument draws its defaults from global humdrumR options
which can be also controlled with the humdrumR() function.
Generaly, changing print options with humdrumR() is the best option, as once you change them,
all automatic printing will follow your new settings---this means you can avoid explicitly calling print().
When printing, only the selected fields in the data are shown.
View types
There are three options for how to view humdrumR data, which can be toggled between
using the view argument to print() or humdrumR().
Since view is the first argument to the humdrumR() function, you can switch between views by simply calling
humdrumR('humdrum') or humdrumR('score') or humdrumR('table').
The options are:
"humdrum"(the default): prints a humdrum-syntax score representation, with record numbers enumerated at the left side.When the
Tokenfield is selected, and you haven't applied any filters, this view will show your original data as it was in the files you read.If more than one field is selected, they are pasted together in the printed output.
"table": prints a view of the underlying humdrum table.In addition to the selected fields, the
Piece,Spine, andRecordfields will always print in the output table, as well asPathandStopif any paths/stops are present."score": will (attempt to) show a rendered score of (the first piece) in your data.This view is only likely to work correctly if you are using Rstudio and connected to the internet. Score rendering is accomplished using Craig Sapp's Humdrum Notation Plugin.
For table and humdrum views, if there are more than one pieces in the object,
the beginning of the first piece is printed, followed by the end of the last piece;
How much of the first/last piece are printed is controlled by the maxRecordsPerFile print argument.
Both of these views also highlight the output with different colors representing different types of data tokens:
this can be disabled using syntaxHighlight = FALSE.
For score view, only the first piece is shown.
See also
The actual data is stored in the internal humdrum table.
You can set printing options globally using the humdrumR() function.
Examples
humData <- readHumdrum(humdrumRroot, "HumdrumData/BachChorales/chor00[1-4].krn")
#> Finding and reading files...
#> REpath-pattern '/home/nat/.tmp/Rtmpz26RCR/temp_libpatha780af15d1/humdrumR/HumdrumData/BachChorales/chor00[1-4].krn' matches 4 text files in 1 directory.
#> Four files read from disk.
#> Validating four files...
#> all valid.
#> Parsing four files...
#> Assembling corpus...
#> Done!
humData
#> ######################## vvv chor001.krn vvv #########################
#> 1: !!!COM: Bach, Johann Sebastian
#> 2: !!!CDT: 1685/02/21/-1750/07/28/
#> 3: !!!OTL@@DE: Aus meines Herzens Grunde
#> 4: !!!OTL@EN: From the Depths of My Heart
#> 5: !!!SCT: BWV 269
#> 6: !!!PC#: 1
#> 7: !!!AGN: chorale
#> 8: **kern **kern **kern **kern
#> 9: *ICvox *ICvox *ICvox *ICvox
#> 10: *Ibass *Itenor *Ialto *Isoprn
#> 11: *I"Bass *I"Tenor *I"Alto *I"Soprano
#> 12: *>[A,A,B] *>[A,A,B] *>[A,A,B] *>[A,A,B]
#> 13: *>norep[A,B] *>norep[A,B] *>norep[A,B] *>norep[A,B]
#> 14: *>A *>A *>A *>A
#> 15: *clefF4 *clefGv2 *clefG2 *clefG2
#> 16: *k[f#] *k[f#] *k[f#] *k[f#]
#> 17: *G: *G: *G: *G:
#> 18: *M3/4 *M3/4 *M3/4 *M3/4
#> 19: *MM100 *MM100 *MM100 *MM100
#> 20: 4GG 4B 4d 4g
#> 21: =1 =1 =1 =1
#> 22: 4G 4B 4d 2g
#> 23: 4E 8cL 4e .
#> 24: . 8BJ . .
#> 25: 4F# 4A 4d 4dd
#> 26: =2 =2 =2 =2
#> 27: 4G 4G 2d 4.b
#> 28: 4D 4F# . .
#> 29: . . . 8a
#> 30: 4E 4G 4B 4g
#> 31: =3 =3 =3 =3
#> 32: 4C 8cL 8eL 4.g
#> 33: . 8BJ 8d .
#> 34: 8BBL 4c 8e .
#> 35: 8AAJ . 8f#J 8a
#> 36: 4GG 4d 4g 4b
#> 37: =4 =4 =4 =4
#> 38: 2D; 2d; 2f#; 2a;
#> 39: 4GG 4d 4g 4b
#> 40: =5 =5 =5 =5
#> 41: 4FF# 4A 4d 2dd
#> 42: 4GG 4B 4e .
#> 43: 4AA 4c 4f# 4cc
#> 44: =6 =6 =6 =6
#> 45: 4BB 4d 2g 4b
#> 46: 4C 4e . 2a
#> 47: 4D 8dL 4f# .
#> 48: . 8cJ . .
#> 49: =7 =7 =7 =7
#> 50: 2GG; 2B; 2d; 2g;
#> 51-133::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
#> ######################## ^^^ chor001.krn ^^^ #########################
#>
#> (two more pieces...)
#>
#> ######################## vvv chor004.krn vvv #########################
#> 1-53::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
#> 54: 4E 4G# 8eL 4b
#> 55: . . 8f#J .
#> 56: =5 =5 =5 =5
#> 57: 4C# 4c# 8g#L 4ee
#> 58: . . 8a#J .
#> 59: 8D#L 4F# 4b 4dd#
#> 60: 8EJ . . .
#> 61: 4F# 4f# 4a# 4cc#
#> 62: 4B 4f# 4b 4dd#
#> 63: =6 =6 =6 =6
#> 64: 8G#L 4B 4b 8eeL
#> 65: 8EJ . . 8dd#J
#> 66: 4F# 4A# 4f# 4cc#
#> 67: 4BB; 4d#; 4f#; 4b;
#> 68: 4E 4e 4g# 4b
#> 69: =7 =7 =7 =7
#> 70: 4G# 4B 8eL 4ee
#> 71: . . 8f#J .
#> 72: 4E 4e 4g# 4b
#> 73: 8AnXL 4e 4a 4cc#
#> 74: 8BJ . . .
#> 75: 4c# 4c# 8eL 8g#L
#> 76: . . 8f#J 8aJ
#> 77: =8 =8 =8 =8
#> 78: 4E# 4d 4g# 4b
#> 79: 4F# 4c# 4f# 4a
#> 80: 4C#; 4c#; 4e#; 4g#;
#> 81: 4E [4B 4e 4g#
#> 82: =9 =9 =9 =9
#> 83: 4BB 4B] 4d# 4f#
#> 84: 8C#L 4e 4c# 4a
#> 85: 8D#J . . .
#> 86: 4E 4e 4B 4g#
#> 87: 4BB 8d#L 4B 4f#
#> 88: . 8BJ . .
#> 89: =10 =10 =10 =10
#> 90: 4AA# 2F# 4c# 4c#
#> 91: 4BB . 4B 4d#
#> 92: 4EE; 4G#; 4B; 4e;
#> 93: == == == ==
#> 94: *- *- *- *-
#> 95: !!!hum2abc: -Q ''
#> 96: !!!title: @{PC#}. @{OTL@@DE}
#> 97: !!!YOR1: 371 vierstimmige Choralgesänge von Jo***
#> 98: !!!YOR2: 4th ed. by Alfred Dörffel (Leipzig: B***
#> 99: !!!YOR2: c.1875). 178 pp. Plate "V.A.10". reprint:***
#> 100: !!!YOR4: Chorales (New York: Associated Music Publi***
#> 101: !!!SMS: B&H, 4th ed, Alfred Dörffel, c.1875, p***
#> 102: !!!EED: Craig Stuart Sapp
#> 103: !!!EEV: 2009/05/22
#> ######################## ^^^ chor004.krn ^^^ #########################
#> (***five global comments truncated due to screen size***)
#>
#> humdrumR corpus of four pieces.
#>
#> Data fields:
#> *Token :: character
#>
humData |> print(view = 'table')
#> Piece Spine Record Token
#> #################### vvv chor001.krn vvv #####################
#> 1 <NA> 1!!!COM: Bach, J...nn
#> 1 <NA> 2!!!CDT: 1685/02.../-
#> 1 <NA> 3!!!OTL@@DE: Aus...in
#> 1 <NA> 4!!!OTL@EN: ...om
#> 1 <NA> 5 !!!SCT: BWV 269
#> 1 <NA> 6 !!!PC#: 1
#> 1 <NA> 7 !!!AGN: chorale
#> 1 <NA> 125 !!!hum2abc: -Q ''
#> 1 <NA> 126!!!title: @{PC#...@{
#> 1 <NA> 127!!!YOR1: 371 vi...ti
#> 1 <NA> 128!!!YOR2: 4th ed...y
#> 1 <NA> 129!!!YOR3: c.1875...17
#> 1 <NA> 130!!!YOR4: Choral...(N
#> 1 <NA> 131!!!SMS: B&H, 4t...d,
#> 1 <NA> 132!!!EED: Craig ...ar
#> 1 <NA> 133 !!!EEV: 2009/05/22
#> 1 1 8 **kern
#> 1 1 9 *ICvox
#> 1 1 10 *Ibass
#> 1 1 11 *I"Bass
#> 1 1 12 *>[A,A,B]
#> 1 1 13 *>norep[A,B]
#> 1 1 14 *>A
#> 1 1 15 *clefF4
#> 1 1 16 *k[f#]
#> 1 1 17 *G:
#> 1 1 18 *M3/4
#> 1 1 19 *MM100
#> 1 1 20 4GG
#> 1 1 21 =1
#> 1 1 22 4G
#> 1 1 23 4E
#> 1 1 24 .
#> 1 1 25 4F#
#> 1 1 26 =2
#> 1 1 27 4G
#> 1 1 28 4D
#> 1 1 29 .
#> 1 1 30 4E
#> 1 1 31 =3
#> 1 1 32 4C
#> 1 1 33 .
#> 1 1 34 8BBL
#> 1 1 35 8AAJ
#> 1 1 36 4GG
#> 1 1 37 =4
#> 1 1 38 2D;
#> 1 1 39 4GG
#> 1 1 40 =5
#> 1 1 41 4FF#
#> #################### ^^^ chor001.krn ^^^ #####################
#>
#> (two more pieces...)
#>
#> #################### vvv chor004.krn vvv #####################
#> 4 4 45 =4
#> 4 4 46 4b
#> 4 4 47 .
#> 4 4 48 .
#> 4 4 49 4cc#
#> 4 4 50 .
#> 4 4 51 4b;
#> 4 4 52 =:|!
#> 4 4 53 *>B
#> 4 4 54 4b
#> 4 4 55 .
#> 4 4 56 =5
#> 4 4 57 4ee
#> 4 4 58 .
#> 4 4 59 4dd#
#> 4 4 60 .
#> 4 4 61 4cc#
#> 4 4 62 4dd#
#> 4 4 63 =6
#> 4 4 64 8eeL
#> 4 4 65 8dd#J
#> 4 4 66 4cc#
#> 4 4 67 4b;
#> 4 4 68 4b
#> 4 4 69 =7
#> 4 4 70 4ee
#> 4 4 71 .
#> 4 4 72 4b
#> 4 4 73 4cc#
#> 4 4 74 .
#> 4 4 75 8g#L
#> 4 4 76 8aJ
#> 4 4 77 =8
#> 4 4 78 4b
#> 4 4 79 4a
#> 4 4 80 4g#;
#> 4 4 81 4g#
#> 4 4 82 =9
#> 4 4 83 4f#
#> 4 4 84 4a
#> 4 4 85 .
#> 4 4 86 4g#
#> 4 4 87 4f#
#> 4 4 88 .
#> 4 4 89 =10
#> 4 4 90 4c#
#> 4 4 91 4d#
#> 4 4 92 4e;
#> 4 4 93 ==
#> 4 4 94 *-
#> #################### ^^^ chor004.krn ^^^ #####################
#> Piece Spine Record Token
#>
#> humdrumR corpus of four pieces.
#>
#> Data fields:
#> *Token :: character
#>