neurodsp.timefrequency.compute_instantaneous_measure¶

neurodsp.timefrequency.compute_instantaneous_measure(sig, fs, measure, f_range=None, remove_edges=True, **filter_kwargs)[source]¶

Compute an instantaneous measure.

Parameters:

sig1d array: Time series.
fsfloat: Sampling rate, in Hz.
measure{‘phase’, ‘amp’, ‘freq’}: Which instantaneous measure to compute.
f_rangetuple of float or None, optional default: None: Filter range, in Hz, as (low, high). If None, no filtering is applied.
remove_edgesbool, optional, default: True: If True, replace samples that are within half of the filter’s length to the edge with nan. This removes edge artifacts from the filtered signal. Only used if f_range is defined.
**filter_kwargs: Keyword parameters to pass to filter_signal.

Returns:

measure1d array: Computed instantaneous measure.

Examples

Simulate an example signal, with an alpha oscillation:

>>> from neurodsp.sim import sim_combined
>>> sig = sim_combined(n_seconds=10, fs=500,
...                    components={'sim_powerlaw': {}, 'sim_oscillation': {'freq': 10}})

Compute the instantaneous phase of the signal:

>>> i_phase = compute_instantaneous_measure(sig, fs=500, measure='phase', f_range=(8, 12))

Compute the instantaneous amplitude of the signal:

>>> i_amp = compute_instantaneous_measure(sig, fs=500, measure='amp', f_range=(8, 12))