Metadata-Version: 2.4
Name: tnbsclean
Version: 0.1.9
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.1
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: mne
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: requires-dist
Dynamic: requires-python

# tnbsclean

## Description
`tnbsclean` provides functionality to clean EEG, MEG, and other time-series data from mne-python by removing unwanted stimuli using the tnbsclean function. This is especially useful in preprocessing to remove noise or artifacts from signals caused by stimuli events.

## Installation

You can install the package via pip from PyPI:

```bash
pip install tnbsclean
```
## Example use

```bash
import tnbsclean as tnbs

# Example parameters
raw  # Raw time series data in MNE's raw object format
half_win = 100  # Half window size around each stimulus (in samples) that will be chopped away from the artifact peak point
threshold = 0.0001  # Threshold above which stimulus is considered significant

# Apply stimulus cleaning 
raw_cleaned = tnbs.stim_clean(raw, half_win, threshold)
```
