from sklearn.model_selection import KFold def examplar_epoch_data(epochs_in, N, navg): epo = epochs_in.copy()[range(N)] fold_num = N // navg if N % navg > 0: fold_num += 1 X1 = epo.get_data() # signals: n_epochs, n_channels, n_times y1 = epo.events[:, 2]

https://mne.tools/stable/install/manual_install.html conda install --channel=conda-forge --name=base mamba mamba create --override-channels --channel=conda-forge --name=mne (old macbook pro)Upgrading all packages Generally speaking, if you want to upgrade your whole software stack including all the dependencies, the best approach is to re-create it as a new virtual environment, because neither conda nor pip are fool-proof at making sure all packages remain compatible with one another during upgrades. Here we’ll demonstrate renaming the old environment first, as a safety measure. We’ll assume that the existing environment is called mne and you want to rename the old one so that the new, upgraded environment can be called mne instead. Unfortunately conda doesn’t have a “rename” command so we’ll first clone the old one with a new name (old_mne), then delete the original, then create the new, updated environment re-using the original name. In the first step we’ll also use conda in --offline mode so that it uses cached copies of all the packages instead of re-downloading them. conda create --name old_mne --clone mne --offline # copy with new name,