pyActigraphy.sleep.ScoringMixin.SoD

ScoringMixin.SoD(freq='5min', binarize=True, bin_threshold=4, whs=4, start='12:00:00', period='5h', algo='Roenneberg', *args, **kwargs)[source]

Sleep over Daytime

Quantify the volume of epochs identified as sleep over daytime (SoD), using sleep-wake scoring algorithms.

Parameters

  • freq (str, optional) – Resampling frequency. Default is ‘5min’

  • binarize (bool, optional) – If set to True, the data are binarized when determining the activity onset and offset times. Only valid if start=’AonT’ or ‘AoffT’. Default is True.

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

  • whs (int, optional) – Window half size. Only valid if start=’AonT’ or ‘AoffT’. Default is 4

  • start (str, optional) – Start time of the period of interest. Default: ‘12:00:00’ Supported times: ‘AonT’, ‘AoffT’, any ‘HH:MM:SS’

  • period (str, optional) – Period length. Default is ‘5h’

  • algo (str, optional) – Sleep scoring algorithm to use. Default is ‘Roenneberg’.

  • *args – Variable length argument list passed to the scoring algorithm.

  • **kwargs – Arbitrary keyword arguements passed to the scoring algorithm.

Returns

sod – Time series containing the epochs of rest (1) and activity (0) over the specified period.

Return type

pandas.core.Series

Examples

>>> import pyActigraphy
>>> rawAWD = pyActigraphy.io.read_raw_awd(fpath + 'SUBJECT_01.AWD')
>>> SoD = rawAWD.SoD()
>>> SoD
2018-03-26 04:16:00    1
2018-03-26 04:17:00    1
2018-03-26 04:18:00    1
(...)
2018-04-05 16:59:00    0
2018-04-05 16:59:00    0
2018-04-05 17:00:00    0
Length: 3175, dtype: int64