mne.beamformer.Beamformer#

class mne.beamformer.Beamformer[source]#

A computed beamformer.

Notes

New in version 0.17.

Methods

__contains__(key, /)

True if the dictionary has the specified key, else False.

__getitem__

x.__getitem__(y) <==> x[y]

__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()

__contains__(key, /)#

True if the dictionary has the specified key, else False.

__getitem__()#

x.__getitem__(y) <==> x[y]

__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.

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:
fnamestr

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 and mne.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#

DICS for power mapping

DICS for power mapping

DICS for power mapping
Compute source power using DICS beamformer

Compute source power using DICS beamformer

Compute source power using DICS beamformer
Compute cross-talk functions for LCMV beamformers

Compute cross-talk functions for LCMV beamformers

Compute cross-talk functions for LCMV beamformers