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Installing ethoscopy as a docker container with ethoscope-lab (recommended). The ethoscope-lab docker container is the recommended way to use ethoscopy. A docker container is a pre-made image that will run inside any computer, independent of the operating sys...

What is the metadata? The metadata is a simple .csv file that contains the information to (1) find and retrieve the data saved to a remote server and (2) to segment and transform the data to compare experimental conditions. I would recommend recording as many...

Setting up To begin you need three paths saved as variables: the path to the metadata .csv file the full path (including folder) the ftp location (eg: ftp://myethoscopedata.com/results/) the path of a local folder to save downloaded .db files (if your ...

Behavpy is the default object in ethoscopy, a way of storing your metadata and data in a single structure, whilst adding methods to help you manipulate and analyse your data. Metadata is crucial for proper statistical analysis of the experimental data. In the...

Once the behavpy object is created, the print function  will just show your data structure. If you want to see your data and the metadata at once, use the built in method .display() # first load your data and create a behavpy instance of it df.display() ...

Behavpy has lots of built in methods to manipulate your data. The next few sections will walk you through a basic methods to manipulate your data before analysis. Filtering by the metadata One of the core methods of behavpy. This method creates a new behavpy...

The below methods and plots should give a good insight into your specimens circadian rhythm. If you think another method should be added please don't hesitate to contact us and we'll see what we can do. Head to the circadian notebook for an interactive run th...

Periodograms are essential for definitely showing periodicity in a quantifiable way. Periodograms often make use of algorithms created for spectral analysis, to decompose a signal into its component waves of varying frequencies. This has been adopted to beha...

Ethoscopy is best used in a Jupyter instance. We provide a pre-baked docker container that comes with multiuser JupyterHub and the ethoscopy package: ethoscope-lab. Ethoscope-lab runs the Python 3.8 Kernel and the R Kernel and features an installation of retho...

Behavpy_HMM is an extension of behavpy that revolves around the use of Hidden Markov Models (HMM) to segment and predict sleep and awake stages in Drosophila. A good introduction to HMMs is available here: https://web.stanford.edu/~jurafsky/slp3/A.pdf.  The p...

The best way to get to grips with your newly trained HMM is to decode some data and has a look at it visually. Single plots # Like plot_overtime() this method will take a single variable and trained hmm, and plot them over time. # If you're using behavpy_H...

Within the Gilestro lab we have special adaptations to the ethoscope which includes the mAGO, a module that can sleep deprive flies manually and also deliver a puff of an odour of choice after periods of rest. See the documentation here: ethoscope_mAGO.  If y...