Convert a noteworthy string to a tibble data frame and include additional derivative variables.

as_music_df(
  notes,
  info = NULL,
  key = NULL,
  scale = "diatonic",
  chords = c("root", "list", "character"),
  si_format = c("mmp_abb", "mmp", "ad_abb", "ad")
)

Arguments

notes

character, a noteworthy string. Alternatively, a music object or a phrase object, in which case info is ignored.

info

NULL or character, a note info string.

key

character, key signature, only required for inclusion of scale degrees.

scale

character, defaults to "diatonic". Only used in conjunction with key, this can be used to alter scale degrees. Not any arbitrary combination of valid key and valid scale is valid. See scale_degree.

chords

character, how to structure columns containing multiple values per chord/row of data frame. See details.

si_format

character, format for scale intervals. See scale_interval.

Value

a tibble data frame

Details

If info is provided or notes is a phrase object, the resulting data frame also contains note durations and other info variables. The duration column is always included in the output even as a vector of NAs when info = NULL. This makes it more explicit that a given music data frame was generated without any time information for the timesteps. Other note info columns are not included in this case.

For some derived column variables the root note (lowest pitch) in chord is used. This is done for pitch intervals and scale intervals between adjacent timesteps. This also occurs for scale degrees.

chord = "root" additionally collapses columns like semitone, octave, and frequency to the value for the root note so that all rows contain one numeric value. chord = "list" retains full information as list columns. chord = "character" collapses into strings so that values are readily visible when printing the table, but information is not stripped and can be recovered without recomputing from the original pitches.

Examples

x <- "a, b, c d e f g# a r ac'e' a c' e' c' r r r a" as_music_df(x, key = "c", scale = "major")
#> # A tibble: 18 x 11 #> duration pitch note semitone octave freq key scale scale_deg pitch_int #> <chr> <chr> <chr> <int> <int> <dbl> <chr> <chr> <int> <int> #> 1 NA a, a 57 2 110. c major 6 NA #> 2 NA b, b 59 2 123. c major 7 2 #> 3 NA c c 48 3 131. c major 1 1 #> 4 NA d d 50 3 147. c major 2 2 #> 5 NA e e 52 3 165. c major 3 2 #> 6 NA f f 53 3 175. c major 4 1 #> 7 NA g# g# 56 3 208. c major NA 3 #> 8 NA a a 57 3 220. c major 6 1 #> 9 NA r r NA NA NA c major NA NA #> 10 NA ac'e' ace 57 3 220. c major 1 0 #> 11 NA a a 57 3 220. c major 6 0 #> 12 NA c' c 48 4 262. c major 1 3 #> 13 NA e' e 52 4 330. c major 3 4 #> 14 NA c' c 48 4 262. c major 1 -4 #> 15 NA r r NA NA NA c major NA NA #> 16 NA r r NA NA NA c major NA NA #> 17 NA r r NA NA NA c major NA NA #> 18 NA a a 57 3 220. c major 6 -3 #> # ... with 1 more variable: scale_int <chr>
as_music_df(x, key = "am", scale = "harmonic_minor", si_format = "ad_abb")
#> # A tibble: 18 x 11 #> duration pitch note semitone octave freq key scale scale_deg pitch_int #> <chr> <chr> <chr> <int> <int> <dbl> <chr> <chr> <int> <int> #> 1 NA a, a 57 2 110. am harm~ 1 NA #> 2 NA b, b 59 2 123. am harm~ 2 2 #> 3 NA c c 48 3 131. am harm~ 3 1 #> 4 NA d d 50 3 147. am harm~ 4 2 #> 5 NA e e 52 3 165. am harm~ 5 2 #> 6 NA f f 53 3 175. am harm~ 6 1 #> 7 NA g# g# 56 3 208. am harm~ 7 3 #> 8 NA a a 57 3 220. am harm~ 1 1 #> 9 NA r r NA NA NA am harm~ NA NA #> 10 NA ac'e' ace 57 3 220. am harm~ 3 0 #> 11 NA a a 57 3 220. am harm~ 1 0 #> 12 NA c' c 48 4 262. am harm~ 3 3 #> 13 NA e' e 52 4 330. am harm~ 5 4 #> 14 NA c' c 48 4 262. am harm~ 3 -4 #> 15 NA r r NA NA NA am harm~ NA NA #> 16 NA r r NA NA NA am harm~ NA NA #> 17 NA r r NA NA NA am harm~ NA NA #> 18 NA a a 57 3 220. am harm~ 1 -3 #> # ... with 1 more variable: scale_int <chr>
a <- notate("8", "Start here.") time <- paste(a, "8^*2 16-_ 4.. 16( 16)( 2) 2 4. t8- t8 t8- 8[accent]*4 1") d1 <- as_music_df(x, time) d1
#> # A tibble: 18 x 14 #> duration pitch note semitone octave freq pitch_int scale_int slur slide #> <chr> <chr> <chr> <int> <int> <dbl> <int> <chr> <chr> <lgl> #> 1 8 a, a 57 2 110. NA NA NA FALSE #> 2 8 b, b 59 2 123. 2 M2 NA FALSE #> 3 8 c c 48 3 131. 1 m2 NA FALSE #> 4 16 d d 50 3 147. 2 M2 NA FALSE #> 5 4.. e e 52 3 165. 2 M2 NA FALSE #> 6 16 f f 53 3 175. 1 m2 on FALSE #> 7 16 g# g# 56 3 208. 3 m3 hold FALSE #> 8 2 a a 57 3 220. 1 m2 off FALSE #> 9 2 r r NA NA NA NA NA NA FALSE #> 10 4. ac'e' ace 57 3 220. 0 P1 NA FALSE #> 11 t8 a a 57 3 220. 0 P1 NA TRUE #> 12 t8 c' c 48 4 262. 3 m3 NA FALSE #> 13 t8 e' e 52 4 330. 4 M3 NA TRUE #> 14 8 c' c 48 4 262. -4 M3 NA FALSE #> 15 8 r r NA NA NA NA NA NA FALSE #> 16 8 r r NA NA NA NA NA NA FALSE #> 17 8 r r NA NA NA NA NA NA FALSE #> 18 1 a a 57 3 220. -3 m3 NA FALSE #> # ... with 4 more variables: bend <lgl>, dotted <int>, articulation <chr>, #> # annotation <chr>
# Go directly from music object to data frame m1 <- as_music(x, time) d2 <- as_music_df(m1) identical(d1, d2)
#> [1] TRUE
# Go directly from phrase object to data frame p1 <- phrase("a b cgc'", "4-+ 4[accent] 2", 5) identical(as_music_df(as_music("a4-+;5 b[accent] cgc'2")), as_music_df(p1))
#> [1] TRUE