Description
Python3 library to read data from Neurosky Mindwave Mobile 2 on linux using pybluez2.
Contents:
Requirements
- libbluetooth-dev
Pre-execution
You can install dependencies via setup.py
$ python -m pip install .
$ python -m pip install .[gui] # to install gui dependencies
via python package index (PyPI)
$ python -m pip install neuropy3
$ python -m pip install neuropy3[gui] # to install gui dependencies
or manually
$ python -m pip install -r requirements.txt
$ python -m pip install -r gui_requirements.txt # to install gui dependencies
Execution
Command line interface
$ python -m neuropy3
$ python -m neuropy3 --address XX:YY:ZZ:AA:BB:CC
$ python -m neuropy3 --help
Address argument helps speed up connection process, otherwise a neuropy3 will run a scan of nearby bluetooth devices (which takes a lot).
Graphical user interface
$ python -m neuropy3 --gui
$ python -m neuropy3 --address XX:YY:ZZ:AA:BB:CC --gui
Note: requires neuropy3[gui] extra dependencies
Screenshots
Importing library
>>> from neuropy3.neuropy3 import MindWave
>>> mw = MindWave(address='XX:YY:ZZ:AA:BB:CC', autostart=False, verbose=3)
>>> # mw = MindWave(autostart=False, verbose=3) # Autoscan for MindWave Mobile
>>> mw.set_callback('eeg', lambda x: print(x))
>>> mw.set_callback('meditation', lambda x: print(x))
>>> mw.set_callback('attention', lambda x: print(x))
>>> mw.start()
>>> mw.unset_callback('eeg')
>>> mw.stop()
Acknowledgements
This work has been supported by National R&D Project TEC2017-84197-C4-1-R and by the Comunidad de Madrid project CYNAMON P2018/TCS-4566 and co-financed by European Structural Funds (ESF and FEDER)
- Based on lihas/NeuroPy library.
- Communication protocol from neurosky.
License
neuropy3 Copyright (C) 2022-2023 Sergio Chica Manjarrez @ pervasive.it.uc3m.es.
Universidad Carlos III de Madrid.
This program comes with ABSOLUTELY NO WARRANTY; for details check below.
This is free software, and you are welcome to redistribute it
under certain conditions; check below for details.
Metadata
Release files for neuropy3 1.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| neuropy3-1.0.4.tar.gz | 32.5 kB | Without provenance | Details for neuropy3-1.0.4.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| neuropy3-1.0.4-py3-none-any.whl | Python 3 | none | any | Details for neuropy3-1.0.4-py3-none-any.whl |
Total release size: 66.7 kB
Release files / neuropy3-1.0.4.tar.gz
| Download URL | neuropy3-1.0.4.tar.gz |
|---|---|
| Size | 32.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
1c6d6b14f06a1111f9ac1ada404fcd063e8bc21cbcb8063f5342f7867672b5b2
|
|
BLAKE2b-256 checksum How to use checksums |
81f32f5940364e7161ff2bd241a05005bd3df382adbc5b0b3cf5855ec21df5e7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.10
|
Release files / neuropy3-1.0.4-py3-none-any.whl
| Download URL | neuropy3-1.0.4-py3-none-any.whl |
|---|---|
| Size | 34.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9ff4364738487f57cc0bfcf092758fed34ff42f877a4dfa5fae06af6151b65c2
|
|
BLAKE2b-256 checksum How to use checksums |
7f92121ceb3a48ff7855ef9e87927a389bb4385ea408600c9a524eccc9bdff59
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.10
|
Security for neuropy3 1.0.4
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.