Metadata-Version: 2.1
Name: nwb_datajoint
Version: 0.2.4
Summary: Neuroscience data pipeline for reproducible research used by Loren Frank Lab, UCSF
Home-page: https://github.com/LorenFrankLab/nwb_datajoint
Author: Loren Frank, Eric Denovellis, Kyu Hyun Lee, Ryan Ly
Author-email: loren@phy.ucsf.edu
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/LorenFrankLab/nwb_datajoint/issues
Description: # nwb_datajoint
        
        The Frank lab Datajoint pipeline is designed to facilitate data storage, analysis, and sharing.
        
        ## Setup
        
        ### Installing packages
        
        1. Clone this repository:
        
           ```bash
           git clone https://github.com/LorenFrankLab/nwb_datajoint.git
           ```
        
        2. Set up and activate a conda environment from `environment.yml`:
        
           ```bash
           cd nwb_datajoint
           conda env create -f environment.yml
           conda activate nwb_datajoint
           ```
        
        3. Install this repository:
        
           ```bash
           # This is preferred to `python setup.py develop`
           # Note the dot (.) at the end
           pip install -e .
           ```
        
        ### Setting up database access
        
        1. Ask Loren or Eric to set up an account for you on the Frank lab database (`lmf-db.cin.ucsf.edu`). Note that you have to be connected to UCSF LAN to access this server.
        
        2. Add the following environment variables (e.g. in `~/.bashrc`). This example assumes that you are interacting with the database on a computer that has mounted `stelmo` at `/stelmo`.
        
             ```bash
             export NWB_DATAJOINT_BASE_DIR="/stelmo/nwb/" 
             export SPIKE_SORTING_STORAGE_DIR="/stelmo/nwb/spikesorting" # where output of spike sorting will be sorted
             export DJ_SUPPORT_FILEPATH_MANAGEMENT="TRUE"
             export KACHERY_P2P_API_HOST="typhoon"
             export KACHERY_P2P_API_PORT="14747"
             export KACHERY_TEMP_DIR="/stelmo/nwb/tmp"
             ```
        
        3. Configure DataJoint. When your account is created, you will be given a temporary password. You can [change your password](https://github.com/LorenFrankLab/nwb_datajoint/blob/master/franklab_scripts/franklab_dj_initial_setup.py) and [set up external stores](https://github.com/LorenFrankLab/nwb_datajoint/blob/master/franklab_scripts/franklab_dj_stores_setup.py). You should need to run these only once.
        
        Finally, open up a python console and import `nwb_datajoint` to check that the setup has worked.
        
        ### Tutorials
        
        The tutorials are in the form of Jupyter Notebooks and can be found in the `notebooks` directory. We strongly recommend opening them in the context of `jupyterlab`. Start with these tutorials:
        
        * `0_intro.ipynb`: general introduction to the database
        * `1_spikesorting.ipynb`: how to run spike sorting
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
