Hello! I've been excited to dive deeper into HyPyP over the last week. I was going through the getting_started.ipynb tutorial and noticed that it is directed towards data that contains epochs.
I was wondering if it was appropriate to calculate inter-brain synchrony through continuous recordings. We are comparing inter-brain synchrony during a 5-minute task and I ended up loading data (.set file) preprocessed through EEGLAB using mne.io.read_raw_eeglab
It looks like a lot of the functions in HyPyP want an input for n_epochs from your data. If that's the case, would it be mathematically okay to enter a new axis to my data. The code works fine if I do so, but I want to make sure I'm not introducing any sorts of errors by doing this:
Hello! I've been excited to dive deeper into HyPyP over the last week. I was going through the
getting_started.ipynb
tutorial and noticed that it is directed towards data that contains epochs.I was wondering if it was appropriate to calculate inter-brain synchrony through continuous recordings. We are comparing inter-brain synchrony during a 5-minute task and I ended up loading data (.set file) preprocessed through EEGLAB using
mne.io.read_raw_eeglab
It looks like a lot of the functions in HyPyP want an input for n_epochs from your data. If that's the case, would it be mathematically okay to enter a new axis to my data. The code works fine if I do so, but I want to make sure I'm not introducing any sorts of errors by doing this:
data_inter = np.array([person1._data, person2._data])
data_interbrain = data_inter[:, np.newaxis, :, :]
#add new axis because we aren't using epochscomplex_signal = analyses.compute_freq_bands(data_interbrain, sampling_rate, freq_bands)
Thank you for your time and consideration!