The main functionality of this package, calculating the Phase Transfer Entropy (PTE) for a set of time-series is accessible via the following functions:

If you are using MNE for analyzing EEG or MEG recordings an object can be passed to:

from pyPTE.utils.mne_tools import PTE_from_mne

dPTE, rPTE = PTE_from_mne(raw)

which returns a tuple of the normalized dPTE, containing information about the directionality and the raw PTE matrix, whereas the matrices are pandas DataFrames indexed by the channel names from the object.

In other domains the PTE calculation can be called directly by either passing a pandas.DataFrame to:

from pyPTE import pyPTE
dPTE, rPTE = pyPTE.PTE_from_dataframe(dataframe)

or by passing a (m x n) numpy.ndarray, where m is the number of samples and n is the number of time-series:

from pyPTE import pyPTE
dPTE, rPTE = pyPTE.PTE(timeseries)

where the returned tuple consists of the above mentioned dPTE, rPTE matrices as (n x n) numpy.ndarray objects ordered in the same way as the input object.

If you are interested in further aspects of the implementation see Developer’s documentation.