API#
This section contains the list modules, classes and functions of Frites.
Overview#
Dataset
The frites.dataset module contains data containers (a similar idea
to MNE-Python with objects like mne.Raw or mne.Epochs) for
single and multi subjects
Workflows
The frites.workflow module contains automated pipelines that are
usually composed of two steps : (i) a first step consisting in estimating
a measure of effect size (e.g. modulation of neural activity according to
task conditions) followed by (ii) a statistical layer
Connectivity
The frites.conn module contains functions to estimate undirected and
directed functional connectivity, potentially dynamic, at the single trial
level
Estimators
The frites.estimator module contains information-based estimators
for linking brain data to an external variable (e.g. stimulus type,
behavioral models etc.). This includes metrics from the information-theory,
machine-learning or measures of distances
Plot
The frites.plot module contains plotting functions
Simulated data
The frites.simulations module contains functions and classes to
generate simulated data (single or multi-subjects)
Utils
The frites.utils module contains utility functions (e.g. data
smoothing)