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

Ethoscopy Workflow

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

Behavpy

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.

Jupyter Tutorials

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

API Reference