systole.plots.plot_frequency

systole.plots.plot_frequency(rr: Union[ndarray, list], input_type: str = 'peaks', fbands: Optional[Dict[str, Tuple[str, Tuple[float, float], str]]] = None, figsize: Optional[Union[int, List[int], Tuple[int, int]]] = None, backend: str = 'matplotlib', ax: Optional[Axes] = None, **kwargs) → Union[figure, Axes]

Plot power spectral densty of RR time series.

Parameters

rr

Boolean vector of peaks detection or RR intervals.

input_type

The type of input vector. Default is “peaks” (a boolean vector where 1 represents the occurrence of R waves or systolic peaks). Can also be “rr_s” or “rr_ms” for vectors of RR intervals, or interbeat intervals (IBI), expressed in seconds or milliseconds (respectively).

fbands

Dictionary containing the names of the frequency bands of interest (str), their range (tuples) and their color in the PSD plot. Default is:

{
 'vlf': ('Very low frequency', (0.003, 0.04), 'b'),
 'lf': ('Low frequency', (0.04, 0.15), 'g'),
 'hf': ('High frequency', (0.15, 0.4), 'r')
 }

figsize

Figure size. Default is (13, 5).

ax

Where to draw the plot. Default is None (create a new figure).

backend

Select plotting backend (“matplotlib”, “bokeh”). Defaults to “matplotlib”.

Returns

plot

The matplotlib axes, or the boken figure containing the plot.

See also

plot_events, plot_ectopic, plot_shortlong, plot_subspaces, plot_frequency

plot_timedomain, plot_nonlinear

Examples

Visualizing HRV frequency domain from RR time series using Matplotlib as plotting backend.

from systole import import_rr
from systole.plots import plot_frequency
# Import PPG recording as numpy array
rr = import_rr().rr.to_numpy()
plot_frequency(rr, input_type="rr_ms")

<Axes: title={'center': 'Power Spectral Density'}, xlabel='Frequency [Hz]', ylabel='PSD [$s^2$/Hz]'>

Visualizing HRV frequency domain from RR time series using Bokeh as plotting backend.

from systole import import_rr
from systole.plots import plot_frequency
from bokeh.io import output_notebook
from bokeh.plotting import show
output_notebook()

show(
    plot_frequency(rr, input_type="rr_ms", backend="bokeh")
)

Loading BokehJS ...