zapline_until_gone(data, target_freq, sfreq, win_sz=10, spot_sz=2.5, viz=False, prefix="zapline_iter")
Returns: clean data, number of iterations
Function iteratively applies the Zapline algorithm.
data: assumed that the function is a part of the MNE-Python pipeline, the input should be an output of {MNE object}.get_data() function. The shape should be Trials x Sensors x Time for epochs.
target_freq: frequency + harmonics that comb-like approach will be applied with Zapline
sfreq: sampling frequency, the output of {MNE object}.info["sfreq"]
win_sz: 2x win_sz = window around the target frequency
spot_sz: 2x spot_sz = width of the frequency peak to remove viz: produce a visual output of each iteration,
prefix: provide a path and first part of the file "{prefix}_{iteration number}.png"
Requires: meegkit, mne, matplotlib, numpy