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

Compute source level time-frequency timecourses using a DICS beamformer

Compute source level time-frequency timecourses using a 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