Tutorials

Three tutorials cover the full neuralfetch workflow — from discovering public datasets to fetching your first study and building your own.

1 · Fetch Your First Study

Browse the catalog, load a sample, and explore the events DataFrame.

Snippet Tutorial →

import neuralset as ns

study = ns.Study(name="Grootswagers2022HumanSample",
                 path="./data")
study.download()
events = study.run()
print(events[["type","start","duration"]].head())

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2 · Anatomy of a Study

Timelines, event types, subject metadata, and composing studies with transforms.

Snippet Tutorial →

for tl in study.iter_timelines():
    print(tl)

events = study.run()
print(events["type"].value_counts())

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3 · Create Your Own Study

Wrap any local or remote dataset as a Study subclass registered in the catalog.

Snippet Tutorial →

class MyStudy(studies.Study):
    def iter_timelines(self):
        yield {"subject": "sub-01"}
    def _load_timeline_events(self, tl):
        return pd.DataFrame([...])

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← Installation Tutorial 1: Fetch Your First Study →

Fetch Your First Study

Fetch Your First Study

Anatomy of a Study

Anatomy of a Study

Creating Your Own Study

Creating Your Own Study