neurodsp.plts.plot_swm_pattern(pattern, ax=None, **kwargs)[source]

Plot the resulting pattern from a sliding window matching analysis.

pattern1d array

The resulting average pattern from applying sliding window matching.

axmatplotlib.Axes, optional

Figure axes upon which to plot.


Keyword arguments for customizing the plot.


Plot the average pattern from a sliding window matching analysis:

>>> from neurodsp.sim import sim_combined
>>> from neurodsp.rhythm import sliding_window_matching
>>> sig = sim_combined(n_seconds=10, fs=500,
...                    components={'sim_powerlaw': {'f_range': (2, None)},
...                                'sim_bursty_oscillation': {'freq': 20,
...                                                           'enter_burst': .25,
...                                                           'leave_burst': .25}})
>>> avg_window, _, _ = sliding_window_matching(sig, fs=500, win_len=0.05, win_spacing=0.5)
>>> plot_swm_pattern(avg_window)

Examples using neurodsp.plts.plot_swm_pattern