Package to analyze PyControl and PyPhotometry experiments by trials, and integrate with other data such as DeepLabCut or spikes data
- Free software: MIT license
- Documentation: https://trialexp.readthedocs.io.
- TODO
- Make sure you have conda installed
- download https://github.com/juliencarponcy/trialexp
- or, if you have git installed:
git clone https://github.com/juliencarponcy/trialexp
- Navigate into the root folder
cd trialexp
- Create environment called trialexp (you can change the name of the environment by modifying the trialexp.yaml file
conda env create -f trialexp.yaml
- Activate notebooks by command line using:
conda activate trialexp
- Do this in the virtual environment to make modules in the repo available:
pip install -e .
- Edit config files
- for execution:
`workflow/conf/config.yaml
- for development:
.env
setting the directory for snakehelper to switch to automatically (i.e. project root folder)workflow/settings.py
setting the debug session folder during development
- for execution:
- Launch Jupyter
jupyter-notebook
In the `/notebooks`
folder, you can then open the different templates notebooks, create your own notebook or copy and edit the different workflow notebooks.
- You can alternatively open the different workflow notebooks in a code editor which support jupyter notebooks.
- Or you can create a new python script or notebook and import trialexp modules
- Copy extern_scriptssessionTemplate_nxp.m to the Cell explorer folder calc_CellMetrics
This package is an extension on the work of Thomas Akam for:
- PyControl (Open source, Python based, behavioural experiment control)
- PyPhotometry (Open source, Python based, fiber photometry data acquisition)
This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
- Cookiecutter: https://github.com/audreyr/cookiecutter
- audreyr/cookiecutter-pypackage: https://github.com/audreyr/cookiecutter-pypackage