brain_pipe.preprocessing.brain.epochs.SplitEpochs

class SplitEpochs(data_key: str | Sequence[str] | OrderedDict[str, str] = 'data', stimulus_key: str | Sequence[str] | OrderedDict[str, str] = 'stimuli', keys_to_index: Sequence[str] = ('event_info',), *args, **kwargs)

Bases: PipelineStep

Split epochs in individual data dicts.

__init__(data_key: str | Sequence[str] | OrderedDict[str, str] = 'data', stimulus_key: str | Sequence[str] | OrderedDict[str, str] = 'stimuli', keys_to_index: Sequence[str] = ('event_info',), *args, **kwargs)

Create a new SplitEpochs instance.

Parameters:

• data_key (str) – The key of the EEG data in the data dict.

• stimulus_key (str) – The key of the stimulus data in the data dict.

Raises:

TypeError – If data_key or stimulus_key is not an ordered dict, string or sequence of strings.

Methods

__init__([data_key, stimulus_key, keys_to_index])	Create a new SplitEpochs instance.
data_dict_copy(data_dict, to_exclude)	Copy a data dict.
parse_dict_keys(key[, name, ...])	Parse a key or a sequence of keys.

data_dict_copy(data_dict: Dict[str, Any], to_exclude: Sequence[str]) → Dict[str, Any]

Copy a data dict.

Parameters:

data_dict (Dict[str, Any]) – The data dict to copy.

Returns:

The copied data dict.

Return type:

Dict[str, Any]

parse_dict_keys(key: str | Sequence[str] | Mapping[str, str], name='key', require_ordered_dict=False) → OrderedDict[str, str]

Parse a key or a sequence of keys.

Parameters:

• key (Union[str, Sequence[str], Mapping[str,str]]) – A key or a sequence of keys.

• name (str) – The name of the key. Used for error messages.

• require_ordered_dict (bool) – If True, the key must be an OrderedDict. If False, the key can also be an ordinary dict.

Returns:

A mapping of input keys to output keys.

Return type:

OrderedDict[str, str]

Raises:

TypeError – If the key is not a string, a sequence of strings or a mapping of strings. If the key is a mapping but require_ordered_dict is True and the mapping is not an OrderedDict.