mne.beamformer.Beamformer#
- class mne.beamformer.Beamformer[source]#
A computed beamformer.
Methods
__contains__(key, /)True if the dictionary has the specified key, else False.
__getitem__(key, /)Return self[key].
__iter__(/)Implement iter(self).
__len__(/)Return len(self).
clear()copy()Copy the beamformer.
fromkeys(iterable[, value])Create a new dictionary with keys from iterable and values set to value.
get(key[, default])Return the value for key if key is in the dictionary, else default.
items()keys()pop(key[, default])If the key is not found, return the default if given; otherwise, raise a KeyError.
popitem(/)Remove and return a (key, value) pair as a 2-tuple.
save(fname[, overwrite, verbose])Save the beamformer filter.
setdefault(key[, default])Insert key with a value of default if key is not in the dictionary.
update([E, ]**F)If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values()Notes
New in v0.17.
- __contains__(key, /)#
True if the dictionary has the specified key, else False.
- __getitem__(key, /)#
Return self[key].
- __iter__(/)#
Implement iter(self).
- __len__(/)#
Return len(self).
- clear() None. Remove all items from D.#
- copy()[source]#
Copy the beamformer.
- Returns:
- beamformerinstance of
Beamformer A deep copy of the beamformer.
- beamformerinstance of
- classmethod fromkeys(iterable, value=None, /)#
Create a new dictionary with keys from iterable and values set to value.
- get(key, default=None, /)#
Return the value for key if key is in the dictionary, else default.
- items() a set-like object providing a view on D's items#
- keys() a set-like object providing a view on D's keys#
- pop(key, default=<unrepresentable>, /)#
If the key is not found, return the default if given; otherwise, raise a KeyError.
- popitem(/)#
Remove and return a (key, value) pair as a 2-tuple.
Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.
- save(fname, overwrite=False, verbose=None)[source]#
Save the beamformer filter.
- Parameters:
- fnamepath-like
The filename to use to write the HDF5 data. Should end in
'-lcmv.h5'or'-dics.h5'.- overwritebool
If True (default False), overwrite the destination file if it exists.
- 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.
- setdefault(key, default=None, /)#
Insert key with a value of default if key is not in the dictionary.
Return the value for key if key is in the dictionary, else default.
- update([E, ]**F) None. Update D from dict/iterable E and F.#
If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
- values() an object providing a view on D's values#
Examples using mne.beamformer.Beamformer#
Compute source level time-frequency timecourses using a DICS beamformer
