Function reference • humdrumR

Reading and Summarizing Data

These tools allow you to import, validate, and abstractly summarize the content of humdrum data.

Reading and Writing

validateHumdrum(): Validate humdrum files

knownInterpretations findHumdrum() readHumdrum(): Find and read humdrum files into R

writeHumdrum(): Write humdrumR data to humdrum files

Summarizing

summary(<humdrumR>): Summarize humdrumR corpora

census() `[` print(<humCensus>): Tabulate records and tokens in a humdrumR corpus

interpretations() `[`(<humInterpretations>) print(<humInterpretations>): Summarize humdrum corpus interpretations.

reference() `[`(<humReference>): Summarize reference records in a humdrumR corpus

spines() `[`(<humSpines>) print(<humSpines>): Summarize spines in humdrum dataset.

Working with Data

These pages describe tools used to manipulate the musical data ensconced within humdrumR data structures.

token() c(<token>) rep(<token>) unique(<token>) `[`(<token>,<ANY>,<ANY>) show(<token>) format(<token>) is.token() order.token() Arith(<token>,<token>) Arith(<token>,<character>) Arith(<character>,<token>) Summary(<token>): Humdrum tokens

Manipulating Humdrum Data

with(<humdrumR>) within(<humdrumR>) mutate(<humdrumR>) summarise(<humdrumR>) reframe(<humdrumR>) ggplot(<humdrumR>): Working with humdrum data fields

subset(<humdrumR>) filter(<humdrumR>) removeEmptyFiles() removeEmptyPieces() removeEmptySpines() removeEmptyPaths() removeEmptyRecords() removeEmptyStops() removeSubset() unfilter() complement(): Filter humdrum data

`[` `[[` index() index2(): Indexing humdrumR objects

group_by(<humdrumR>) ungroup(<humdrumR>) groups(): Divide humdrumR data into groups

context() uncontext() windows(): Group vectors into contextual windows

Musical Tools

These pages describe the classes and functions that directly represent or engage musical/music-theoretic concepts.

Pitch overviews

These pages overview general concepts in humdrumR pitch:

humdrumPitch: humdrumR and pitch

pitchFunctions: Translate between pitch representations.

tonalInterval(): Parsing pitch information

pitchDeparsing: Generating ("deparsing") pitch representations

chordFunctions: Parsing and deparsing chord information

tertianSet(): Parsing chord information

chordDeparsing: Generating ("deparsing") chord representations

keyFunctions: Parsing and deparsing key information

diatonicSet(): Parsing key information

keyDeparsing: Generating ("deparsing") key representations

tint() is.tonalInterval() order.tonalInterval(): Representation of tonal pitch information

tset() is.tertianSet(): Tertian set

diatonicSet() dset() is.diatonicSet() order.diatonicSet() `==`(<diatonicSet>,<diatonicSet>) Compare(<diatonicSet>,<diatonicSet>) `==`(<tertianSet>,<tertianSet>): Tonal (diatonic) sets

Pitch functions

These functions translate between pitch representations:

pitch(): Scientific pitch representation

degree() deg(): Tonal scale degree representation (absolute)

interval(): Tonal (pitch) interval representation

kern(): Kern pitch representation

solfa(): Relative-do Solfege representation

solfg(): Fixed-do Solfege representation

lilypond(): Lilypond pitch representation

helmholtz(): Helmholtz pitch representation

tonh(): German-style pitch notation.

octave(): Extract octave.

step(): Extract scale step.

accidental(): Extract accidental from pitch.

quality(): Extract quality from pitch

bhatk(): Swara representation

semits() midi() cents(<default>): Atonal pitch representations

pc(): Representation of atonal pitch classes

cents(): Apply to humdrumR data

freq(): Translate pitches to frequency (Hz)

LO5th(): Line of Fifths

transpose(): Transpose pitches and keys

invert(): Invert or transpose pitches.

int() mint() hint(): Calculate intervals between pitches

is.simple() is.generic(): Test the properties of tonal information

gamut(): Make a pitch gamut

Key and chord functions

These functions translate between diatonic and tertian representations:

romanNumerals: Roman Numeral

key(): Humdrum key interpretation

signature(): Humdrum key signature

romanKey(): Roman numeral key areas

harm() roman(): Roman numeral representations of harmony

chord() harte(): "Pop/Jazz" chord symbols

tertian(): Tertian quality chord representation

figuredBass(): Figured bass representation of harmony

is.major() is.minor(): Test the major/minor modality of a set

sonority(): Interpret tertian sonorities from set(s) of notes.

Rhythm overviews

These pages overview general concepts in humdrumR pitch:

rhythmFunctions: Translate between rhythm representations.

rhythmInterval(): Parsing rhythm information

rhythmDeparsing: Generating ("deparsing") rhythm representations

humMeter: Tools for analyzing rhythm and meter.

Duration and Time functions

These functions translate between rhythm representations:

bpm2sec() sec2bpm() bpm2ms() ms2bpm(): Translate between durations and tempos

recip(): Reciprocal representation of duration

duration() quarters(): Numeric (double) representation of durations

grid() togrid() fromgrid(): Drum-machine grid representation of rhythmic durations.

notehead(): Note value representation of duration

seconds() ms() dur(): Clock-time representations of duration

ioi() sumTies(): Sum "connected" durations

timeline() timestamp(): Rhythmic timeline of a piece

timebase(): Represent time on a regular grid

recordDuration(): Calculate duration of each record in a corpus

Beats and Meter

Rhythm and meter analysis functions.

meter(): Musical Meter in humdrumR

duple(): Generate duple meters

tactus() measure(): Extract levels from meters

nbeats(): Counting beats

tatum(): Find common denominator of beats

timecount() subpos() onbeat(): Count beats or measures

metlev() metcount() metsubpos(): Count or measure metric position

syncopation(): Identify syncopated rhythms

Lyrics

Lyrics and text functions.

wort(): Paste syllables together into words

Data Structures

These pages describe the data structures of humdrumR, and how to query or manipulate them.

is.humdrumR() print(<humdrumR>): humdrumR class

tandem(): Get tandem interpretation information from humdrum data

pull_data.table() pull_data.frame() pull_tibble() pull(<humdrumR>) `$`(<humdrumR>): Extract field(s) from humdrumR data

selectedFields() select(<humdrumR>): The "selected" fields of a humdrumR object

as.vector(<humdrumR>) as.lines() as.matrix(<humdrumR>) as.data.frame(<humdrumR>) as.matrices() as.data.frames(): humdrumR coercion

mergeHumdrum(): Merge two (or more) humdrumR datasets

collapseHumdrum() collapseStops() collapsePaths() collapseRecords(): "Collapse" humdrumR data into a field

expandPaths(): Expand paths into new spines

cleave() pivot_wider(<humdrumR>) cleaveSpines() cleavePaths() cleaveStops(): Align data from separate spines into new fields.

rend() pivot_longer(<humdrumR>): Separate data fields into new spines.

combineFields(): Combine one or more fields into a new field

cleaveGraceNotes(): "Fold" grace notes into neighbos

unfoldStops(): "Unfold" data into multiple stops

nrecord() nrow(<humdrumR>) ntoken() npieces() nfiles() length(<humdrumR>) ncol(<humdrumR>) dim(<humdrumR>) is.empty() anyMultiPieceFiles() anyPaths() anyStops() anySubcorpora() namesSubcorpora(): humdrumR data size and shape

getHumtab() fields() names(<humdrumR>): Humdrum tables (and their "fields")

is.struct(): struct

Other Functions

Other useful tools.

draw(): Visualize data

show(<distribution>) print(<distribution>) sort(<distribution>) count(<default>) count(<humdrumR>) count(<table>) pdist(<count>) pdist(<probability>) pdist(<default>) pdist(<data.frame>) pdist(<humdrumR>) pdist(<table>) table(): Distributions

Information theory

pdist(): Tabulate and cross proportions

entropy() H() mutualInfo(): Calculate Entropy or Information Content of variables

Numeric values

rational() `%R%` numerator() denominator() is.rational() is.numeric(<rational>) rank(<rational>) Compare(<rational>,<rational>) Compare(<rational>,<ANY>) Compare(<ANY>,<rational>) Summary(<rational>) prod(<rational>) abs(<rational>) sign(<rational>) max(<rational>) min(<rational>) mean(<rational>) round(<rational>) floor(<rational>) ceiling(<rational>) trunc(<rational>) expand(<rational>) sum(<rational>) cumsum(<rational>) as.rational() fraction() as.fraction() as.double(<fraction>) as.integer(<fraction>): Rational numbers

expand(): Expand numbers outwards from zero

Manipulating Vectors

delta(): Lagged differences

ditto(): Propagate data points to "fill" null data.

lag() lead(): Shift data within a vector/matrix/data.frame

segments() changes(): Identify contiguous segments of data in a vector

sigma(): Cumulative sum of numeric vector

hop(): Generate regular sequence "along" input

enum(): Enumerate vector

Regular Expressions

Regular Expressions are essential tools for working with humdrum data. These functions provide functionality for working with regular expressions.

`%~l%` `%~i%` `%~n%` `%~m%` `%~%` `%!~%` `%!~l%` `%!~i%`: Match strings against regular expression

humdrumDispatch() exclusiveDispatch() makeDispatchDF() makeHumdrumDispatcher() print(<humdrumDispatch>): Regular expression method dispatch and function application

captureRE() captureUniq() orRE(): Making Regular Expressions

REparser() REparse(): Parse String Using Regular expressions

Miscallaneus

humdrumRroot humdrumR(): humdrumR

partialMatching: What is "partial matching"?

Some R basics lessons

Concise descriptions of some important concepts in R coding.

evaluatingExpressions: "Evaluating" "Expressions" in "Environments"?

groupingFactors: What are "grouping factors"?

partialMatching: What is "partial matching"?

recycling padding: What are "recycling" or "padding"?

vectorization: What is "vectorization"?