Introduction
last edited: 21/11/2022
Welcome to Ethoscopy, a python based toolbox for the manipulation of time series data concerning sleep in biological behavioural experiments. At Ethoscopy's core is the behavpy class, a subclass of pandas that connects a metadata data frame with a data frame containing the variables of the subjects over time. This facilitates simple methods to manipulate large behavioural data sets whilst retaining the many uses and functions of pandas.
The toolbox also functions as a tool to download and standardise data produced by Ethoscopes, a machine for high-throughput analysis of Drosophila.
For more information about Ethoscopes head to: https://www.notion.so/giorgiogilestro/Ethoscope-User-Manual-a9739373ae9f4840aa45b277f2f0e3a7
or message a member of the Gilestro lab group for more information: https://lab.gilest.ro
Content
Tutorial
A guide starting with how to connect and download using Ethoscopy through to data manipulation with the behavpy class
Skip straight to behavpy
If you aren't using Ethoscopes or just aren't that interested, skip straight to the tutorial about the behavpy class
Jupyter Tutorials
Find here some jupyter notebooks that run through the basics, circadian analysis, and Hidden Markov Models using pre-generated data to help you get to grips with ethoscopy.
Want to deep dive?
Dive a little deeper and start exploring our API reference to get an idea of everything that's possible with the API
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