Package for modelling electrophysiological responses to stimuli
Reason this release was yanked:
incompatible version of reservoirpy
Project description
sPyEEG
Version: 0.0.1
Package for modelling s/M/EEG responses to speech. In other words, for mapping speech features, through python (sPyeech) to EEG (sPyEEG)... and the other way around!
Not mind-reading for espionage purposes ;).
Setup
Requirements
Package builds on top on MNE and relies on a similar set of dependencies and 3rd party packages listed in environment.yml. You can easily set up the environment via Conda package manager by running in terminal From terminal (or conda shell on Windows):
conda env update --file environment.yml
Then activate the created environment by running:
conda activate spyeeg
Installation
To get the package installed only through symbolic links, namely so that you can modify the source code and use modified versions at will when importing the package in your python scripts do:
python setup.py develop
Otherwise, for a standard installation (but this will require to be installed if you need to install another version of the library):
python setup.py install
Tested on:
- macOS Big Sur v11.1
- Ubuntu 18.04.5 LTS
- Windows 10 22H2
Modules (sketch)
- models - for all your modelling needs
- TRF: Temporal Response Function a.k.a Ridge regression a.k.a. fancy linear regression, optimized for speed
- iRRR: integrative reduced rank regression a.k.a fancier linear regression
- _methods: useful methods used by several model classes
- CCA/Decoder/ERP: to be properly written at a later date.
- feat - simple feature extraction.
- preproc - useful preprocessing functions (filters, detrending...etc)
- viz - visualization tools. To come.
- utils - misc.
Examples
Note: Sample data required for demos can be downloaded here. When downloaded place the files in the demos/Data folder.
- Modelling (
models)- Basic TRF modelling:
demo/Demo_TRF.py - iRRR demo: coming soon
- Basic TRF modelling:
- Feature extraction (
feat)- Speech envelope extraction:
demo/Demo_envelopes.py
- Speech envelope extraction:
Contributors:
- Pierre Guilleminot (phg17@ic.ac.uk)
- Mikolaj Kegler (mak616@ic.ac.uk)
Last updated: 15th Apr 2024
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file spyeeg-0.2.2.tar.gz.
File metadata
- Download URL: spyeeg-0.2.2.tar.gz
- Upload date:
- Size: 46.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6991a613fe30a1d27c9c7fe55b6e3dcc2a04cf7e6e017e75ab818f7b739a57fb
|
|
| MD5 |
172f5acda2804e5d070d526c58d2c097
|
|
| BLAKE2b-256 |
0ecacb11bc5fdbed63a849c429283b4d9e9b6b20a8169466adb6a47fe68bd827
|
File details
Details for the file spyeeg-0.2.2-py3-none-any.whl.
File metadata
- Download URL: spyeeg-0.2.2-py3-none-any.whl
- Upload date:
- Size: 51.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f353cdf9843482def1d511328ce10a7625669158566a0c314899474b042c33f9
|
|
| MD5 |
4e24b0cadfab502a15987073d6e699d2
|
|
| BLAKE2b-256 |
7f541bff68bf0d798278bbf1debfb5f2e41b64242ccff53ce48d121339418312
|