39 lines
1.1 KiB
Python
39 lines
1.1 KiB
Python
# Authors: The MNE-Python contributors.
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# License: BSD-3-Clause
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# Copyright the MNE-Python contributors.
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import numpy as np
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from ..annotations import Annotations, _adjust_onset_meas_date
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from ..utils import verbose
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from .artifact_detection import _annotations_from_mask
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@verbose
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def annotate_nan(raw, *, verbose=None):
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"""Detect segments with NaN and return a new Annotations instance.
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Parameters
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----------
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raw : instance of Raw
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Data to find segments with NaN values.
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%(verbose)s
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Returns
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-------
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annot : instance of Annotations
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New channel-specific annotations for the data.
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"""
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data, times = raw.get_data(return_times=True)
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onsets, durations, ch_names = list(), list(), list()
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for row, ch_name in zip(data, raw.ch_names):
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annot = _annotations_from_mask(times, np.isnan(row), "BAD_NAN")
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onsets.extend(annot.onset)
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durations.extend(annot.duration)
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ch_names.extend([[ch_name]] * len(annot))
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annot = Annotations(
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onsets, durations, "BAD_NAN", ch_names=ch_names, orig_time=raw.info["meas_date"]
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)
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_adjust_onset_meas_date(annot, raw)
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return annot
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