DataJoint for MATLAB is a high-level programming interface for relational databases designed to support data processing chains in science labs. DataJoint is built on the foundation of the relational data model and prescribes a consistent method for organizing, populating, and querying data.

DataJoint was initially developed in 2009 by Dimitri Yatsenko in Andreas Tolias' Lab for the distributed processing and management of large volumes of data streaming from regular experiments. Starting in 2011, DataJoint has been available as an open-source project adopted by other labs and improved through contributions from several developers.

Installation

(Recommended) Greater than R2016b

1. Utilize MATLAB built-in GUI i.e. Top Ribbon -> Add-Ons -> Get Add-Ons
2. Search and Select DataJoint
3. Select Add from GitHub

Using GHToolbox (FileExchange Community Toolbox)

1. Install GHToolbox using using an appropriate method in https://github.com/datajoint/GHToolbox
2. run: ghtb.install('datajoint/datajoint-matlab')

Less than R2016b

1. Utilize MATLAB built-in GUI i.e. Top Ribbon -> Add-Ons -> Get Add-Ons
2. Search and Select DataJoint
3. Select Download from GitHub
4. Save DataJoint.mltbx locally
5. Navigate in MATLAB tree browser to saved toolbox file
6. Right-Click and Select Install
7. Select Install

From Source

1. Download DataJoint.mltbx locally
2. Navigate in MATLAB tree browser to saved toolbox file
3. Right-Click and Select Install
4. Select Install

Config

For help in utilizing dj.config (added in 3.4.0), you may access the help via help('dj.config') or review it online here. Formal documentation to follow.

Running Tests Locally

• Create an .env with desired development environment values e.g.

MATLAB_USER=rguzman
MATLAB_LICENSE=IyBCRUd... # For image usage instructions see https://github.com/guzman-raphael/matlab, https://hub.docker.com/r/raphaelguzman/matlab
MATLAB_VERSION=R2019a
MATLAB_HOSTID=XX:XX:XX:XX:XX:XX
MATLAB_UID=1000
MATLAB_GID=1000
MYSQL_TAG=5.7
MINIO_VER=RELEASE.2022-01-03T18-22-58Z

• cp local-docker-compose.yaml docker-compose.yaml
• docker-compose up (Note configured JUPYTER_PASSWORD)
• Select a means of running MATLAB e.g. Jupyter Notebook, GUI, or Terminal (see bottom)
• Add tests directory to path e.g. in MATLAB, addpath('tests')
• Run desired tests. Some examples are as follows:

Use Case	MATLAB Code
Run all tests	run(Main)
Run one class of tests	run(TestTls)
Run one specific test	runtests('TestTls/TestTls_testInsecureConn')
Run tests based on test name	import matlab.unittest.TestSuite; import matlab.unittest.selectors.HasName; import matlab.unittest.constraints.ContainsSubstring; suite = TestSuite.fromClass(?Main, ...     HasName(ContainsSubstring('Conn'))); run(suite)

Launch Jupyter Notebook

• Navigate to localhost:8888
• Input Jupyter password
• Launch a notebook i.e. New > MATLAB

Launch MATLAB GUI (supports remote interactive debugger)

• Shell into datajoint-matlab_app_1 i.e. docker exec -it datajoint-matlab_app_1 bash
• Launch Matlab by runnning command matlab

Launch MATLAB Terminal

• Shell into datajoint-matlab_app_1 i.e. docker exec -it datajoint-matlab_app_1 bash
• Launch Matlab with no GUI by runnning command matlab -nodisplay