A cookiecutter project template for audio effect plugins using the DISTRHO Plugin Framework (DPF) and the Audio Toolkit (ATK) DSP filter library.
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README.md

cookiecutter-dpf-audiotk

A cookiecutter project template for DISTRHO Plugin Framework (DPF) audio effect plugins using the Audio Toolkit (ATK) DSP filter library.

Usage

To create a DPF effect plugin using this template, install cookiecutter (see the installation instructions) and then run:

cookiecutter https://github.com/SpotlightKid/cookiecutter-dpf-audiotk

and enter the plugin name and other info at the prompts.

A directory named after the value you gave for repo_name will be created and initialized as a git repository and DPF added as a git submodule.

Enter the directory and run make:

cd mynewplugin
make

Plugin binaries will be placed in the bin directory. The source code for your plugin is in a sub-directory of the plugins directory named after the value you specified for plugin_name. Adapt it as you see fit and run make again to update your binaries. The second compilation will be much faster, because the DPF sources have already been built.

The Structure of a Plugin

The ATK library provides a number of "filter" classes, which need to be connected in a processing pipeline. Filters vary from simple operators like gain adjustment and panning, and signal generators like LFOs to various actual audio filters for frequency spectrum manipulation. Each filter has a set of input and output ports that connect to each other. In your plugin, you feed the incoming sample data into the input ports of the ATK filter instances, which are at the front of the processing pipeline, and write the data coming from the output ports of the filter instances, which are at end of the processing pipeline, to the output buffers. ATK provides some utility classes, which take care of feeding the input to the processing pipeline and writing the output.

The code generated by this project template already sets up a processing pipeline, which uses these, and in the plugin's run method calls the process method on the pipeline, which pumps the data through it. This means, for a simple pipeline, e.g. a delay or a filter, you just have to change the ATK filter class instance in the middle of the processing pipeline to one (or several in a row), which implement(s) the processing you want and and update its (their) parameters in the setParametervalue method. The project template sets up a simple pipeline for a stereo delay effect with two parameters (delay time and dry/wet ratio) as an example, that works out of the box.

Please see the ATK API reference documentation for available filter classes and their parameters.

Requirements

  • Basic development tools (C++ compiler, make, etc.)
  • Python
  • Git
  • cookiecutter
  • ATK devel branch

ATK should be installed system-wide, so the compiler can find the ATK headers and the linker can find the ATK shared libraries. If this is not the case, you have to adapt the values of the EXTRA_INCLUDES and EXTRA_LIBS variables in the file Makefile.mk in the top-level directory of the created project and add apppropriate -I and -L options for the compiler and/or linker.

For Arch Linux systems, there is an AUR package for installing ATK from its git repository:

https://aur.archlinux.org/packages/audiotk-git/