Ethoscopy

Ethoscopy user manual

Getting started

Installing ethoscopy as a docker container with ethoscope-lab (recommended). The ethoscope-lab do...

Metadata design

What is the metadata? The metadata is a simple .csv file that contains the information to (1) fi...

Loading the data

Setting up To begin you need three paths saved as variables: the path to the metadata .csv fi...

Behavpy

About

Behavpy is the default object in ethoscopy, a way of storing your metadata and data in a single s...

Basic methods

Behavpy has lots of built in methods to manipulate your data. The next few sections will walk you...

Visualising your data

Once the behavpy object is created, the print function will just show your data structure. If yo...

Visualising mAGO data

Within the Gilestro lab we have special adaptations to the ethoscope which includes the mAGO, a m...

Behavpy - Circadian analysis

At the Gilestro lab we work on sleep and often need to do a lot of circadian analysis to complime...

Circadian methods and plots

The below methods and plots should give a good insight into your specimens circadian rhythm. If y...

Periodograms

Periodograms are essential for definitely showing periodicity in a quantifiable way. Periodogra...

Behavpy - Hidden Markov Model

Behavpy_HMM is an extension of behavpy that revolves around the use of Hidden Markov Models (HMM)...

Training an HMM

Behavpy_HMM is an extension of behavpy that revolves around the use of Hidden Markov Models (HMM)...

Visualising with the HMM

The best way to get to grips with your newly trained HMM is to decode some data and has a look at...

Jupyter tutorials

Ethoscopy is best used in a Jupyter instance. We provide a pre-baked docker container that comes ...

Tutorial 1 — Overview: working with ethoscope data

Auto-generated from tutorial_notebook/1_Overview_tutorial.ipynb. Executed against the seaborn ca...

Tutorial 2 — HMM: hidden behavioural states

Auto-generated from tutorial_notebook/2_HMM_tutorial.ipynb. Executed against the seaborn canvas ...

Tutorial 3 — Circadian analysis

Auto-generated from tutorial_notebook/3_Circadian_tutorial.ipynb. Executed against the seaborn c...

Tutorial 5 — catch22 feature extraction

Auto-generated from tutorial_notebook/5_Ethoscopy_catch22_tutorial.ipynb. Executed against the s...

Tutorial 6 — Exporting to hctsa (MATLAB)

Auto-generated from tutorial_notebook/6_Ethoscopy_to_hctsa_tutorial.ipynb. Executed against the ...

Paper companion notebook — Jones et al.

Auto-generated from tutorial_notebook/notebook_paper.ipynb. Executed against the seaborn canvas ...