This project is designed to generate a number of distinctive animations on a grid of LEDs via OPC, to a FadeCandy board.

Here's a test picture of the plasma art running on a physical array:

If you want a quick sample of what ROP can do in a terminal, you can follow this link to Asciinema:

The code has been run on OSX with Python 2.7 and Python 3.6. There are a few extras you'll need before you can start. Typically you'd run something like:

# pip3 install -r requirements.txt

Or maybe - if you prefer - you'd install in a virtualenv. On the off-chance that the installation gets a hiccup:

• numpy is pretty well documented and you should be able to figure it out. Some distros have a natively installable package to use instead of the pip equivalent. If you do install but get poor performance, then it may be that there are some ancillary packages missing which numpy relies on for optimum performance. Again, the numpy docs are pretty good.

• Either Pillow or it's predecessor PIL should work just fine, although the former is preferred.

To get started and display on your terminal, make sure that the terminal is at least 35x35 and run:

% python3 art.py

You can also pick a specific subset to render by listing the particular modules in the art directory, for example:

% python3 art.py rain.py fortune.py

Be aware that the down-sampled image when displaying to the terminal is super lossy, since it's reducing 24 bit color to a handful of ascii-art characters... although if your tty has a 256 color mode, then things will look quite a bit better than 16 colors.

If you want higher quality output and can run against a physical LED display, then update config.py to suit your display configuration, and start the OPC service as appropriate.

The config.py file contains tunable parameters relating to the display, such as geometry, as well as configuration options specific to the individual art files.

Most textual logging is delivered to art.log. If something doesn't look right, then check in this file for exceptions and other diagnostics.

It's also possible to limit number of cycles that art.py runs through, adjust the duration that each art is displayed before moving on to the next, or to switch on profiling. Run with --help for more information.

The directories are:

.                  application directory
./art              contains classes for each of the animations.
                   You'll notice a template.py file for the bare
                   bones
./art/utils        helper modules shared between animations
./art/baseclasses  base classes that animations may derive from
./assets           files that are used by the animations
./config.py        various configuration options
./opc              an extended interface for using OPC via python
./opc/utils        various utilities used by the framework

To help get up to speed on the library, you can use pydoc. For example:

% pydoc opc.matrix

Check out the existing animations for use as examples, and please commit back code that you create!

The opc code is taken from the copy embedded in FadeCandy. If you're not already familiar, go check out FadeCandy for more background on the project.

Hopefully attributions are correct. If you see one missing, then please let me know and I'll fix.

There aren't any formal guidelines for contributing. If you'd like to submit a pull request for review, or open an issue, though, then that's awesome.