msqms.qc.fractal_metrics module

Fractal Domain Metric for MEG Data.

Summary

Classes:

FractalDomainMetric

Class to calculate fractal domain metrics for MEG data.

Reference

class msqms.qc.fractal_metrics.FractalDomainMetric(raw, data_type, origin_raw, n_jobs=-1, verbose=False)

Bases: Metrics

Class to calculate fractal domain metrics for MEG data.

This class processes segmented MEG data and computes fractal dimension metrics for each segment, similar to entropy domain metrics.

Parameters:

• raw (mne.io.Raw) – The raw MEG data.

• data_type (str) – The type of MEG data (e.g., ‘opm’ or ‘squid’).

• origin_raw (mne.io.Raw) – The original raw MEG data for comparison.

• n_jobs (int, optional) – Number of parallel jobs to use for computation. Default is -1 (use all available cores).

• verbose (bool, optional) – If True, enables verbose output. Default is False.

compute_metrics(meg_type, seg_length=100)

Compute fractal domain metrics for segmented MEG data.

Parameters:

• meg_type (MEG_TYPE) – Type of MEG channels to process (e.g., ‘mag’, ‘grad’).

• seg_length (int, optional) – Length of each segment for computation, in seconds. Default is 100.

Returns:

meg_metrics_df – DataFrame containing the averaged fractal metrics for the MEG data.

Return type:

pd.DataFrame

compute_fractal_dimension(data)

Calculate fractal dimensions for all channels.

Parameters:

data (np.ndarray) – Multichannel time series data.

Returns:

fractal_df – DataFrame containing fractal dimension metrics for all channels.

Return type:

pd.DataFrame