Metadata-Version: 2.1
Name: Reiz
Version: 0.3.3
Summary: A Python toolbox for visual and auditory stimulation based on pyglet and pylsl.
Home-page: https://github.com/pyreiz/pyreiz
Author: Robert Guggenberger
Author-email: robert.guggenberger@uni-tuebingen.de
License: MIT
Download-URL: https://github.com/pyreiz/pyreiz.git
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Multimedia
Classifier: Topic :: Scientific/Engineering :: Human Machine Interfaces
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Description-Content-Type: text/markdown
Requires-Dist: pyglet (>=1.4.7)
Requires-Dist: pylsl (>=1.13)
Requires-Dist: pyttsx3 (>=2.7)

# Reiz

pyReiz is a low-level auditory and visual stimulus presentation suite wrapping pyglet, sending markers via a pylsl outlet. You can also read more [extensive documentation online](https://reiz.agricolab.de/index.html).

## Installation

The [requirements](#requirements) for pyReiz are pyglet and pylsl. They are checked, and if necessary installed, during `pip install`. Because pyReiz is still beta, i recommend installing from the git repo in editable fashion.

### Windows

```
pip install Reiz
```

### Linux

The most recent version of pylsl is not yet on pypi. A solution is to install libsl manually. You download a recent build of liblsl from <https://github.com/sccn/liblsl/releases>. Afterwards, install pylsl directly from github.

```
pip install git+https://github.com/labstreaminglayer/liblsl-Python.git
pip install Reiz
```

## Development

```
git clone https://github.com/pyreiz/pyreiz.git
cd pyreiz
pip install -e .
```

### Test your installation

After you installed Reiz, you can give it a test-run by calling `python -m reiz.examples.basic` from your terminal. This should start a throwaway MarkerServer, and present a series of visual and auditory stimuli. If anything does not work out, [inform us of the issue](https://github.com/pyreiz/pyreiz/issues).

## Create your Experiment

Examples can be found in `reiz/examples`. Take a look at the documentation for the examples, e.g. the [basic example](/reiz/examples/basic.py) which you used to test the installation.

## Recording

Because all markers are send via LSL, i suggest recording with [Labrecorder](https://github.com/labstreaminglayer/App-LabRecorder/releases). Use at least 1.13, as this version supports BIDS-conform recording, offers a remote interface and has a critical timing bugfix included.

### Appendix

#### Man-in-the-middle

LabRecorder can only start recording Outlets that are existing. If you start a MarkerServer immediatly before you run the experiment, there is not much time for the Recorder to detect the stream. It is therefore best practice to start a pyReiz-MarkerServer as an independent process. This MarkerServer acts as a man-in-the-middle. It opens an Outlet that can be detected independently from the experiments you are running. When you then run an experiment, it receives messages from this experiment, and redistributes them in LSL-format. Start the MarkerServer as an independent process with `reiz-marker` or `python -m reiz.marker` from your terminal.

Sometimes, this is over-the-top, and you might just want to test your experiment without recording. You can safeguard your experiment by adding `reiz.marker.start()` in your python-script. This will start a MarkerServer

#### Requirements

The requirements for pyReiz are pyglet and pylsl. We require pylsl>=1.13 because a timing issue was fixed in that version (see <https://github.com/sccn/liblsl/issues/8>), and pyglet>1.4 because there was a breaking change between 1.3 and 1.4 in the way audio was generated and played (see <https://github.com/pyreiz/pyreiz/issues/2>)

#### Acknowledgments

I adapted code from [Cocos2d](https://github.com/los-cocos/cocos) for generation of some openGL primitives.


