braindecode.datautil.create_fixed_length_windows¶
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braindecode.datautil.create_fixed_length_windows(concat_ds, start_offset_samples, stop_offset_samples, window_size_samples, window_stride_samples, drop_last_window, mapping=None, preload=False, drop_bad_windows=True)¶ Windower that creates sliding windows.
- Parameters
- concat_ds: ConcatDataset
a concat of base datasets each holding raw and descpription
- start_offset_samples: int
start offset from beginning of recording in samples
- stop_offset_samples: int | None
stop offset from beginning of recording in samples.
- window_size_samples: int
window size
- window_stride_samples: int
stride between windows
- drop_last_window: bool
whether or not have a last overlapping window, when windows do not equally divide the continuous signal
- mapping: dict(str: int)
mapping from event description to target value
- preload: bool
if True, preload the data of the Epochs objects.
- drop_bad_windows: bool
If True, call .drop_bad() on the resulting mne.Epochs object. This step allows identifying e.g., windows that fall outside of the continuous recording. It is suggested to run this step here as otherwise the BaseConcatDataset has to be updated as well.
- Returns
- windows_ds: WindowsDataset
Dataset containing the extracted windows.
