This documentation is for development version 0.18.dev0.

# mne.beamformer.Beamformer¶

class mne.beamformer.Beamformer[source]

A computed beamformer.

Notes

New in version 0.17.

Methods

 __contains__($self, key, /) True if the dictionary has the specified key, else False. __getitem__ x.__getitem__(y) <==> x[y] __iter__($self, /) Implement iter(self). __len__($self, /) Return len(self). clear() copy() Copy the beamformer. fromkeys($type, iterable[, value]) Create a new dictionary with keys from iterable and values set to value. get($self, key[, default]) Return the value for key if key is in the dictionary, else default. items() keys() pop(k[,d]) If key is not found, d is returned if given, otherwise KeyError is raised popitem() 2-tuple; but raise KeyError if D is empty. save(fname[, overwrite, verbose]) Save the beamformer filter. setdefault($self, 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()
__contains__($self, key, /) True if the dictionary has the specified key, else False. __getitem__() x.__getitem__(y) <==> x[y] __iter__($self, /)

Implement iter(self).

__len__($self, /) Return len(self). clear() → None. Remove all items from D. copy()[source] Copy the beamformer. Returns: beamformer : instance of Beamformer A deep copy of the beamformer. fromkeys($type, iterable, value=None, /)

Create a new dictionary with keys from iterable and values set to value.

get($self, key, default=None, /) Return the value for key if key is in the dictionary, else default. items() → a set-like object providing a view on D's items keys() → a set-like object providing a view on D's keys pop(k[, d]) → v, remove specified key and return the corresponding value. If key is not found, d is returned if given, otherwise KeyError is raised popitem() → (k, v), remove and return some (key, value) pair as a 2-tuple; but raise KeyError if D is empty. save(fname, overwrite=False, verbose=None)[source] Save the beamformer filter. Parameters: fname : str The filename to use to write the HDF5 data. Should end in '-lcmv.h5' or '-dics.h5'. overwrite : bool If True, overwrite the file (if it exists). verbose : bool, str, int, or None If not None, override default verbose level (see mne.verbose() and Logging documentation for more). setdefault($self, 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