mne.preprocessing.nirs.temporal_derivative_distribution_repair#
- mne.preprocessing.nirs.temporal_derivative_distribution_repair(raw, *, verbose=None)[source]#
Apply temporal derivative distribution repair to data.
Applies temporal derivative distribution repair (TDDR) to data [1]. This approach removes baseline shift and spike artifacts without the need for any user-supplied parameters.
- Parameters:
- rawinstance of
Raw The raw data.
- verbosebool |
str|int|None Control verbosity of the logging output. If
None, use the default verbosity level. See the logging documentation andmne.verbose()for details. Should only be passed as a keyword argument.
- rawinstance of
- Returns:
- rawinstance of
Raw Data with TDDR applied.
- rawinstance of
Notes
TDDR was initially designed to be used on optical density fNIRS data but has been enabled to be applied on hemoglobin concentration fNIRS data as well in MNE. We recommend applying the algorithm to optical density fNIRS data as intended by the original author wherever possible.
There is a shorter alias
mne.preprocessing.nirs.tddrthat can be used instead of this function (e.g. if line length is an issue).References
