systole.plots.plot_shortlong

systole.plots.plot_shortlong(rr: None, artefacts: Dict[str, ndarray], input_type: str = 'rr_ms') → Union[figure, Axes]

systole.plots.plot_shortlong(rr: Union[List[float], ndarray], artefacts: None, input_type: str = 'rr_ms') → Union[figure, Axes]

systole.plots.plot_shortlong(rr: Union[List[float], ndarray], artefacts: Dict[str, ndarray], input_type: str = 'rr_ms') → Union[figure, Axes]

Visualization of short, long, extra and missed intervals detection.

The artefact detection is based on the method described in [1].

Parameters

rr

Interval time-series (R-R, beat-to-beat…), in seconds or in miliseconds.

artefacts

The artefacts detected using systole.detection.rr_artefacts().

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).

ax

Where to draw the plot. Default is None (create a new figure). Only applies when backend=”matplotlib”.

backend

Select plotting backend {“matplotlib”, “bokeh”}. Defaults to “matplotlib”.

figsize

Figure size. Default is (6, 6) for matplotlib backend, and the height is 600 when using bokeh backend.

Returns

plot

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

See also

plot_ectopic, plot_subspaces

Notes

If both rr and artefacts are provided, the function will drop artefacts and re-evaluate given the current RR time-series.

References

1

Lipponen, J. A., & Tarvainen, M. P. (2019). A robust algorithm for heart rate variability time series artefact correction using novel beat classification. Journal of Medical Engineering & Technology, 43(3), 173–181. https://doi.org/10.1080/03091902.2019.1640306

Examples

Visualizing short/long and missed/extra intervals from a RR time series.

from systole import import_rr
from systole.plots import plot_shortlong

# Import PPG recording as numpy array
rr = import_rr().rr.to_numpy()

plot_shortlong(rr)

<Axes: title={'center': 'Subspace 2 \n (long and short beats detection)'}, xlabel='Subspace $S_{21}$', ylabel='Subspace $S_{22}$'>

Visualizing ectopic subspace from the artefact dictionary.

from systole.detection import rr_artefacts

# Use the rr_artefacts function to short/long and extra/missed intervals
artefacts = rr_artefacts(rr)

plot_shortlong(artefacts=artefacts)

<Axes: title={'center': 'Subspace 2 \n (long and short beats detection)'}, xlabel='Subspace $S_{21}$', ylabel='Subspace $S_{22}$'>

Using Bokeh as plotting backend.

from bokeh.io import output_notebook
from bokeh.plotting import show
from systole.detection import rr_artefacts
output_notebook()

show(
   plot_shortlong(artefacts=artefacts, backend="bokeh")
)

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