braindecode.datasets.BaseConcatDataset¶
-
class
braindecode.datasets.BaseConcatDataset(list_of_ds)¶ A base class for concatenated datasets. Holds either mne.Raw or mne.Epoch in self.datasets and has a pandas DataFrame with additional description.
- Parameters
- list_of_ds: list
list of BaseDataset, BaseConcatDataset or WindowsDataset
- Attributes
- cummulative_sizes
- transform
Methods
Concatenate the metadata and description of the wrapped Epochs.
split([by, property, split_ids])Split the dataset based on information listed in its description DataFrame or based on indices.
cumsum
-
get_metadata()¶ Concatenate the metadata and description of the wrapped Epochs.
- Returns
- pd.DataFrame:
DataFrame containing as many rows as there are windows in the BaseConcatDataset, with the metadata and description information for each window.
-
split(by=None, property=None, split_ids=None)¶ Split the dataset based on information listed in its description DataFrame or based on indices.
- Parameters
- by: str | list(int) | list(list(int))
If by is a string, splitting is performed based on the description DataFrame column with this name. If by is a (list of) list of integers, the position in the first list corresponds to the split id and the integers to the datapoints of that split.
- property: str
Some property which is listed in info DataFrame.
- split_ids: list(int) | list(list(int))
List of indices to be combined in a subset.
- Returns
- splits: dict{str: BaseConcatDataset}
A dictionary with the name of the split (a string) as key and the dataset as value.
