neurodsp.plts.plot_swm_pattern

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

Plot the resulting pattern from a sliding window matching analysis.

Parameters

pattern1d array

The resulting average pattern from applying sliding window matching.

axmatplotlib.Axes, optional

Figure axes upon which to plot.

**kwargs

Keyword arguments for customizing the plot.

Examples

Plot the average pattern from a sliding window matching analysis:

>>> import numpy as np
>>> 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}})
>>> windows, _ = sliding_window_matching(sig, fs=500, win_len=0.05, win_spacing=0.5)
>>> avg_window = np.mean(windows)
>>> plot_swm_pattern(avg_window)

Examples using neurodsp.plts.plot_swm_pattern

Sliding Window Matching

Sliding Window Matching