Metadata-Version: 2.1
Name: Reiz
Version: 0.3.3.1
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
Description: # 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`. There is also a dependency on _pyttsx3_ to allow on-demand synthesis of auditory cues from text. If you don't need that or can't acquire a version of pyttsx3 for your architecture, install pyreiz without the `[tts]` suffix.
        
        ### Windows
        
        ```bash
        pip install Reiz[tts]
        ```
        
        ### 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.
        
        ```bash
        pip install git+https://github.com/labstreaminglayer/liblsl-Python.git
        pip install Reiz[tts]
        ```
        
        ## Development
        
        ```bash
        git clone https://github.com/pyreiz/pyreiz.git
        cd pyreiz
        pip install -e .[tts]
        ```
        
        ### 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`. A quite extensively documented basic example can be found here: [basic example](/reiz/examples/basic.py).
        
        ## 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.
        
        ## Additional Information
        
        ### MarkerServer
        
        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. Start the MarkerServer as an independent process with `reiz-marker` or `python -m reiz.marker` from your terminal.
        
        This MarkerServer 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.
        
        ### Requirements
        
        The key 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>). For text-to-speech, which is included with `[tts]`, a key requirement is _pyttsx3_.
        
        ### Acknowledgments
        
        I adapted code from [Cocos2d](https://github.com/los-cocos/cocos) for generation of some openGL primitives.
        
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
Provides-Extra: tts
