- mne.concatenate_raws(raws, preload=None, events_list=None, *, on_mismatch='raise', verbose=None)[source]#
Rawinstances as if they were continuous.
rawsis modified in-place to achieve the concatenation. Boundaries of the raw files are annotated bad. If you wish to use the data as continuous recording, you can remove the boundary annotations after concatenation (see
Rawinstances to concatenate (in order).
Preload data into memory for data manipulation and faster indexing. If True, the data will be preloaded into memory (fast, requires large amount of memory). If preload is a string, preload is the file name of a memory-mapped file which is used to store the data on the hard drive (slower, requires less memory). If preload is None, preload=True or False is inferred using the preload status of the instances passed in.
The events to concatenate. Defaults to
- on_mismatch‘raise’ | ‘warn’ | ‘ignore’
'raise'(default) to raise an error,
'warn'to emit a warning, or
'ignore'to ignore when the device-to-head transformation differs between instances.
New in version 0.24.
Control verbosity of the logging output. If
None, use the default verbosity level. See the logging documentation and
mne.verbose()for details. Should only be passed as a keyword argument.
Working with CTF data: the Brainstorm auditory dataset
Annotate movement artifacts and reestimate dev_head_t
Compute and visualize ERDS maps
Motor imagery decoding from EEG data using the Common Spatial Pattern (CSP)
Decoding in time-frequency space using Common Spatial Patterns (CSP)
Representational Similarity Analysis