systole.plots.plot_rr

systole.plots.plot_rr(rr: Union[List, ndarray], unit: str = 'rr', kind: str = 'cubic', line: bool = True, points: bool = True, input_type: str = 'peaks', show_artefacts: bool = False, bad_segments: Optional[Union[ndarray, List[Tuple[int, int]]]] = None, show_limits: bool = True, slider: bool = True, ax: Optional[Axes] = None, figsize: Optional[Union[Tuple[float, float], int]] = None, backend: str = 'matplotlib', events_params: Optional[Dict] = None) → Union[Axes, figure]

Plot instantaneous heart rate time series.

Parameters

rr

Boolean vector of peaks detection, peaks indexs or RR intervals.

unit

The heart rate unit in use. Can be ‘rr’ (R-R intervals, in ms) or ‘bpm’ (beats per minutes). Default is ‘rr’.

kind

The method to use (parameter of scipy.interpolate.interp1d). The possible relevant methods for instantaneous heart rate are ‘cubic’ (defalut), ‘linear’, ‘previous’ and ‘next’.

line

If True, plot the interpolated instantaneous heart rate.

points

If True, plot each peaks (R wave or systolic peaks) as separated points

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 “peaks_idx”, the idexs of samples where a peaks is detected, “rr_s” or “rr_ms” for vectors of RR intervals, or interbeat intervals (IBI), expressed in seconds or milliseconds (respectively).

show_artefacts

If True, the function will call

systole.detection.rr_artefacts() to detect outliers interval

in the time serie and outline them using different colors.

bad_segments

Mark some portion of the recording as bad. Grey areas are displayed on the top of the signal to help visualization (this is not correcting or transforming the post-processed signals). If a np.ndarray is provided, it should be a boolean of same length than signal where False indicates a bad segment. If a list is provided, it should be a list of tuples shuch as (start_idx, end_idx) for each bad segment.

Note

The start and end points should be expressed as peaks indexes.

show_limits

Use shaded areas to represent the range of physiologically impossible R-R intervals. Defaults to True.

slider

If True, add a slider to zoom in/out in the signal (only working with bokeh backend).

ax

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

figsize

Figure size. Default is (13, 5).

backend

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

events_params

(Optional) Additional parameters that will be passed to

systole.plots.plot_events() and plot the events timing in the backgound.

Returns

plot

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

See also

plot_raw, plot_events, plot_evoked

Examples

Plot instantaneous heart rate from a RR interval time series (in milliseconds).

from systole import import_rr
from systole.plots import plot_rr

# Import R-R intervals time series
rr = import_rr().rr.values

plot_rr(rr=rr, input_type="rr_ms");

Only show the interpolated instantaneous heart rate, add a bad segment and change the default unit to beats per minute (BPM).

plot_rr(rr=rr, input_type="rr_ms", unit="bpm", points=False);

Use Bokeh as a plotting backend, only show the scatterplt and highlight artefacts in the RR intervals.

from bokeh.io import output_notebook
from bokeh.plotting import show
output_notebook()

show(
    plot_rr(
     rr=rr, input_type="rr_ms", backend="bokeh",
     line=False, show_artefacts=True
     )
)

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