https://github.com/richardkoehler/pte-decode
PTE Decode is an open-source software package for neural decoding.
https://github.com/richardkoehler/pte-decode
adbs dbs ecog ieeg lfp machine-learning
Last synced: 4 months ago
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PTE Decode is an open-source software package for neural decoding.
- Host: GitHub
- URL: https://github.com/richardkoehler/pte-decode
- Owner: richardkoehler
- License: mit
- Created: 2022-01-31T13:26:01.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2025-04-03T05:58:14.000Z (about 1 year ago)
- Last Synced: 2025-04-03T06:35:02.958Z (about 1 year ago)
- Topics: adbs, dbs, ecog, ieeg, lfp, machine-learning
- Language: Python
- Homepage:
- Size: 271 KB
- Stars: 2
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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# PTE Decode - Python tools for electrophysiology
PTE Decode is an open-source software package for neural decoding.
It builds upon [PTE](https://github.com/richardkoehler/pte) and aims at decoding
intracranial EEG (iEEG) signals such as local field potentials (LFP)
electrocorticography (ECoG).
PTE Decode implements sample-wise decoding and lets you define epochs based on
specific events to avoid circular training.
## Installing PTE Decode
First, get the current development version of PTE using
[git](https://git-scm.com/). Then type the following command into a terminal:
```bash
git clone https://github.com/richardkoehler/pte-decode
```
Use the package manager
[conda](https://docs.conda.io/projects/conda/en/latest/index.html) to set up a
new working environment. To do so, use `cd` in your terminal to navigate to the
PTE root directory and type:
```bash
conda env create -f env.yml
```
This will set up a new conda environment called `pte-decode`.
To activate the environment then type:
```bash
conda activate pte-decode
```
Finally, to install PTE Decode in an editable development version inside your
environment type the following inside the PTE Decode root directory:
```bash
pip install -e .
```
## Usage
```python
import pte_decode
# Examples
```
## Contributing
Please feel free to contribute.
For any minor additions or bugfixes, you may simply create a **pull request**.
For any major changes, make sure to open an **issue** first. When you then
create a pull request, be sure to **link the pull request** to the open issue in
order to close the issue automatically after merging.
To contribute, consider installing the full conda development environment to
include such tools as black, pylint and isort:
```bash
conda env create -f env_dev.yml
conda activate pte-decode-dev
```
Continuous Integration (CI) including automated testing are set up.
## License
PTE is licensed under the [MIT license](license-url).
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[license-url]: https://github.com/richardkoehler/pte/blob/main/LICENSE/
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