tnbsclean 1.6

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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:

pip install tnbsclean

Example use

import tnbsclean as tnbs

# Example parameters
raw  # Raw time series data in MNE's raw object format
half_win = 3  # Half window size around each stimulus (in samples) that will be chopped away from the artifact peak point
threshold = 2  # Threshold constant above which stimulus is considered significant

# Apply stimulus cleaning 
raw_cleaned, spike_idxs = tnbs.get_stim_markers(raw, half_win, threshold) #cleans based on ECG, returns spike indices