pyramidi is a very experimental package to generate / manipulate midi
data from R. Be aware that a lot of the code I’ve written some years ago
hurts my eyes when I look at it now :) Midi data is read into
dataframes, using the python package
miditapyr under the hood (which
itself uses the excellent mido). The
notes’ midi information (one line per note_on
/note_off
midi event)
is translated into a wide format (one line per note). This format
facilitates some manipulations of the notes’ data and also plotting them
in piano roll plots. Finally, the modified dataframes can be written
back to midi files (again using miditapyr).
Thus, you can manipulate all the intermediate dataframes and create midi files from R. However, you need to make sure yourself that the midi files you write can be understood by your softsynth. The data is not yet validated by pyramidi, but mido (also used to write midi files) already catches some of the possible inconsistencies.
If you’re new to midi, mido’s documentation might be a good start.
The midi data can now be
- played live in the R console OR generate a sound file and a html audio
player when knitting rmarkdown documents thanks to the excellent R
packages fluidsynth (see the
documentation of the
play()
method in theMidiFramer
class and its helper functionplayer()
which use fluidsynth::midi_convert()
to synthesize midi to wav files (needs fluidsynth installed, but if I understand correctly R will do that for you)
You can install pyramidi from R-universe with:
install.packages('pyramidi', repos = c('https://urswilke.r-universe.dev', 'https://cloud.r-project.org'))
The python package miditapyr also needs to be installed in your python environment used by reticulate.
pip install miditapyr
But if everything works as I believe it should, miditapyr is automatically installed if you install pyramidi, as soon as you access the module for the first time.
Otherwise, you can also install it in your reticulate python environment with the included helper function:
pyramidi::install_miditapyr()
I’m not sure if that works on windows too. Perhaps there you have to manually configure your reticulate environment.
We can create a MidiFramer
object by passing the file path to the
constructor method
(new()
).
library(pyramidi)
library(dplyr)
midi_file_string <- system.file("extdata", "test_midi_file.mid", package = "pyramidi")
mfr <- MidiFramer$new(midi_file_string)
The object contains the midi data in various dataframe formats and an
interface to the miditapyr
miditapyr.MidiFrames
object mfr$mf
. You can write the midi file resulting of the
MidiFramer
object to disk:
mfr$mf$write_file("/path/to/your/midifile.mid")
In the MidiFramer
object, we can modify mfr$df_notes_wide
, the notes
in note-wise wide format (note_on
& note_off
events in the same
line). Thus we don’t need to worry which midi events belong together
Let’s look at a small example. We’ll define a function to replace every note with a random midi note between 60 & 71::
mod <- function(dfn, seed) {
n_notes <- sum(!is.na(dfn$note))
dfn %>% mutate(note = ifelse(
!is.na(note),
sample(60:71, n_notes, TRUE),
note
))
}
When we call the update_notes_wide()
method, the midi data in mfr
is
updated:
mfr$update_notes_wide(mod)
Thus, we can now save the modifications to a midi file:
mfr$mf$write_file("mod_test_midi_file.mid")
See the vignette("pyramidi", package = "pyramidi")
to see how you can
synthesize the midi data to wav, convert to mp3 if you want, and then
embed a player in your rmarkdown html document with
mfr$play("mod_test_midi_file.mp3")