pyActigraphy.metrics.MetricsMixin.RAp

MetricsMixin.RAp(period='7D', binarize=True, threshold=4, verbose=False)[source]

RA per period

The RA variable is calculated for each consecutive period found in the actigraphy recording.

Parameters

  • period (str, optional) – Time period for the calculation of IS Default is ‘7D’.

  • binarize (bool, optional) – If set to True, the data are binarized. Default is True.

  • threshold (int, optional) – If binarize is set to True, data above this threshold are set to 1 and to 0 otherwise. Default is 4.

  • verbose (bool, optional) – If set to True, display the number of periods found in the activity recording, as well as the time not accounted for. Default is False.

Returns

rap

Return type

list of float

Notes

The RA [1] variable is calculated as:

\[RA = \frac{M10 - L5}{M10 + L5}\]

References

1

Van Someren, E.J.W., Lijzenga, C., Mirmiran, M., Swaab, D.F. (1997). Long-Term Fitness Training Improves the Circadian Rest-Activity Rhythm in Healthy Elderly Males. Journal of Biological Rhythms, 12(2), 146–156. http://doi.org/10.1177/074873049701200206

Examples

>>> import pyActigraphy
>>> rawAWD = pyActigraphy.io.read_raw_awd(fpath + 'SUBJECT_01.AWD')
>>> rawAWD.duration()
Timedelta('12 days 18:41:00')
>>> rawAWD.RAp(period='5D',verbose=True)
Number of periods: 2
Time unaccounted for: 2 days, 19h, 0m, 0s
[0.XXXX, 0.XXXX]