ProTrackR vs ProTrackR2
In ProTrackR2: Manipulate and Play 'ProTracker' Modules

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

ProTracker2 and its predecessor

The predecessor to this package (ProTrackR) was entirely programmed in R. Although technically possible, it was challenging and slow with recursive algorithms. The new version is a complete overhaul in C/C++, based on Olav Sørensen's ProTracker clone. With it, came some design changes which are worth mentioning here.

Overview of differences

The table below summarises the differences between ProTrackR2 and its predecessor.

library(kableExtra)
data.frame(
  Feature    = c("[Effect commands](#effect-commands)", "[Infrastructure](#infrastructure)",
                 "[File readers](#file-readers)", "[Audio output](#audio-output)", "OpenMPT test cases"),
  ProTrackR  = c("Limited set implemented", "R script", "Optimized for format preservation",
                 "tuneR S4 Wave class", "Passes 6 out of 12 selected tests"),
  ProTrackR2 = c("All PT2.3d effects implemented", "Compiled C/C++", "Optimized for PT2.3d compatibility",
                 "audio S3 audioSample class", "Not tested yet")
) |>
  kbl()

Effect commands

ProTracker uses specific codes to apply certain effects or position jumps. ProTrackR implements only a subset of these effects, whereas ProTrackR2 has implemented all ProTracker compatible effects.

The predecessor only partly implemented arpeggio and setting finetune. It did not implement glissando, sample filtering (E8) and loop reversal (EF). All these effects are implemented in the current package.

For a full overview of effect commands see vignette("effect_commands").

Infrastructure

By switching to C and C++ compiled code, the new package gained a significant performance boost (see benchmark results). Where the in the predecessor the module was represented by a vector of raw data, an externalptr to a C struct is used in the current package. This required a slightly different approach to handle these objects. In order to avoid confusion about the syntax, it was completely redesigned in the successor.

Benchmark

A benchmark test where the same module (the one provided with this package) is rendered with both ProTrackR and ProTrackR2. The settings for both tests were similar and performed on the same system and repeated 10 times. On average ProTrackR2 renders 8.8 times faster than ProTrackR.

File readers

While reading ProTracker modules, the predecessor preserved the data in the file. It only modified / fixed data when requested by the user. The current package will always sanitise data while reading it, making it compatible with ProTracker 2.3d. The current reader is also a bit more flexible and allows to read more exotic formats. It even allows you to read files compressed with PowerPacker.

Alternatives

If you want even more flexibility, check out the openmpt package. It uses libopenmpt to read and play modules. This library has a more extensive set of supported file formats. The downside is that it does not allow you to modify or save modules.

Audio output

The predecessor used tuneR objects to store rendered audio. In the current package we use audio objects. This switch was made as the S3 class objects from 'audio' are easier to handle than the stricter and formal S4 class objects from 'tuneR'. If you wish to use the advanced features from the 'tuneR' package, this is still possible as both formats can be converted relatively easy.

## Load demo module
mod <- pt2_read_mod(pt2_demo())

## render 'audioSample' object
mod_audio <- pt2_render(mod)

## Convert from 'audio::audioSample' to 'tuneR::Wave' object:
if (requireNamespace("tuneR")) {
  mod_tuneR <-
    tuneR::Wave(
      left      = as.integer(2^15*unclass(mod_audio[1,])),
      right     = as.integer(2^15*unclass(mod_audio[2,])),
      samp.rate = attributes(mod_audio)$rate,
      bit       = attributes(mod_audio)$bits
    )
}