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Project description
tnbs_stim_clean
Description
tnbs_stim_clean provides functionality to clean EEG, MEG, and other time-series data from mne-python by removing unwanted stimuli using the tnbs_stim_clean 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 tnbs_stim_clean
Example use
import tnbs_stim_clean
# 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)
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