moabb.paradigms.ssvep.BaseSSVEP#

class moabb.paradigms.ssvep.BaseSSVEP(filters=((7, 45),), events=None, n_classes=None, tmin=0.0, tmax=None, baseline=None, channels=None, resample=None)[source]#

Base SSVEP Paradigm

Parameters:

  • filters (list of list | None (default [7, 45])) – Bank of bandpass filter to apply.

  • events (list of str | None (default None)) – List of stimulation frequencies. If None, use all stimulus found in the dataset.

  • n_classes (int or None (default None)) – Number of classes each dataset must have. All dataset classes if None.

  • tmin (float (default 0.0)) – Start time (in second) of the epoch, relative to the dataset specific task interval e.g. tmin = 1 would mean the epoch will start 1 second after the beginning of the task as defined by the dataset.

  • tmax (float | None, (default None)) – End time (in second) of the epoch, relative to the beginning of the dataset specific task interval. tmax = 5 would mean the epoch will end 5 second after the beginning of the task as defined in the dataset. If None, use the dataset value.

  • baseline (None | tuple of length 2) – The time interval to consider as “baseline” when applying baseline correction. If None, do not apply baseline correction. If a tuple (a, b), the interval is between a and b (in seconds), including the endpoints. Correction is applied by computing the mean of the baseline period and subtracting it from the data (see mne.Epochs)

  • channels (list of str | None (default None)) – List of channel to select. If None, use all EEG channels available in the dataset.

  • resample (float | None (default None)) – If not None, resample the eeg data with the sampling rate provided.

property datasets#

Property that define the list of compatible datasets

is_valid(dataset)[source]#

Verify the dataset is compatible with the paradigm.

This method is called to verify dataset is compatible with the paradigm.

This method should raise an error if the dataset is not compatible with the paradigm. This is for example the case if the dataset is an ERP dataset for motor imagery paradigm, or if the dataset does not contain any of the required events.

Parameters:

dataset (dataset instance) – The dataset to verify.

prepare_process(dataset)[source]#

Prepare processing of raw files

This function allows to set parameter of the paradigm class prior to the preprocessing (process_raw). Does nothing by default and could be overloaded if needed.

Parameters:
datasetdataset instance

The dataset corresponding to the raw file. mainly use to access dataset specific i

nformation.
property scoring#

Property that defines scoring metric (e.g. ROC-AUC or accuracy or f-score), given as a sklearn-compatible string or a compatible sklearn scorer.