Metadata-Version: 2.1
Name: ethoscopy
Version: 0.1.6
Summary: A python based toolkit to download and anlyse data from the Ethoscope hardware system.
License: GNU GPLv3
Author: Blackhurst Laurence
Author-email: l.blackhurst19@imperial.ac.uk
Requires-Python: >=3.8,<=3.11
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: numpy (>=1.22.3,<2.0.0)
Requires-Dist: pandas (>=1.4.2,<2.0.0)
Requires-Dist: plotly (>=5.7.0,<6.0.0)
Description-Content-Type: text/markdown

**ethoscopy**

A data-analysis toolbox utilising the python language for use with data collected from 'Ethoscopes', a Drosophila video monitoring system.

For more information on the ethoscope system: https://www.notion.so/The-ethoscope-60952be38787404095aa99be37c42a27

Ethoscopy is made to work alongside this system, working as a post experiment analysis toolkit. 

Ethoscopy provides the tools to download epxerimental data from a remote ftp servers as setup in ethoscope tutorial above. Downloaded data can be curated during the pipeline in a range of ways, all fromatted using the pandas data structure.

Further the ethoscopy package provides behavpy a subclassed version of pandas that combines metadata with the data for easily manipulation.

**TO COME** In addtion the behavpy class has hmmlearn imbedded, a python package for the use of hidden markov models (HMM) (https://hmmlearn.readthedocs.io/en/latest/). Here you can set the architecture and train a HMM of your choice. There are several plotting functions avaiable alongside side it to explore the hidden markov model, using plotly as graphing tool of choice.

