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fix: dtype conversion issue in detect_nonwear #26

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Nov 29, 2023
Merged

fix: dtype conversion issue in detect_nonwear #26

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6 changes: 5 additions & 1 deletion src/actipy/processing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -187,7 +187,7 @@ def detect_nonwear(data, patience='90m', window='10s', stdtol=15 / 1000):

info = {}

stationary_indicator = ( # this is more memory friendly than of data[['x', 'y', 'z']].std()
stationary_indicator = ( # this is more memory friendly than data[['x', 'y', 'z']].std()
data['x'].resample(window, origin='start').std().lt(stdtol)
& data['y'].resample(window, origin='start').std().lt(stdtol)
& data['z'].resample(window, origin='start').std().lt(stdtol)
Expand All @@ -206,6 +206,10 @@ def detect_nonwear(data, patience='90m', window='10s', stdtol=15 / 1000):
)
.set_index('start_time')
.squeeze()
# dtype defaults to int64 when series is empty, so
# astype('timedelta64[ns]') makes sure it's always a timedelta,
# otherwise comparison with Timedelta(patience) below will fail
.astype('timedelta64[ns]')
)
nonwear_segment_lengths = stationary_segment_lengths[stationary_segment_lengths > pd.Timedelta(patience)]

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