Usage

The toolbox is designed in a modular way, which means the individual modules can be used in combination with others, but also by themselves. Users also have the option to choose between a normal Python scripting API and a graphical user interface (GUI).

Tip

The GUI provides convenient tools for data handling, (dynamic) connectivity estimation, graph analysis, and multiverse exploration, offering a quick visual overview. For greater flexibility, the scripting API is recommended.

GUI

After installation, graphical user interface can be accessed through the terminal by typing:

comet-gui

On a fresh installation, the first startup may take a little longer due to the initialisation of the Matplotlib backend. A brief introduction for how to use the GUI is provided in the Tutorials.

Scripting

Dynamic functional connectivity can be estimated through the connectivity module. An example for sliding window correlation:

from comet import connectivity, utils

ts = utils.load_example()

sw = connectivity.SlidingWindow(ts, windowsize=30, shape="gaussian")
dfc = sw.estimate()

Graph measures can be calculated through the graph module. An example for the clustering coefficient derived from sliding window estimates:

from comet import connectivity, graph, utils

ts = utils.load_example()

sw = connectivity.SlidingWindow(ts, windowsize=30, shape="gaussian")
dFC = sw.estimate()

adj = graph.threshold(dFC, type="density", threshold=0.2)
clustering_coef = graph.clustering_coef(adj)

Multiverse analysis can be conducted through the multiverse module. This exaple will create and run a multiverse analysis with two decisions (6 possible combinations):

from comet.multiverse import Multiverse

forking_paths = {
    "decision1": [1, 2, 3],
    "decision2": ["Hello", "World"]
    }

def analysis_template():
    print("Decision1:", {{decision1}})
    print("Decision2", {{decision2}})

mverse = Multiverse(name="example_multiverse")
mverse.create(analysis_template, forking_paths)
mverse.summary()
mverse.run()