DataJoint

Scientific workflow management framework built on top of a relational database.

[](https://www.mathworks.com/matlabcentral/fileexchange/63218-datajoint)

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](http://toliaslab.org) 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](https://github.com/datajoint/datajoint-matlab/blob/c2bd6b3e195dfeef773d4e12bad5573c461193b0/%2Bdj/config.m#L2-L27). Formal documentation to follow.

## Running Tests Locally

* Create an `.env` with desired development environment values e.g.
``` sh
MATLAB_USER=raphael
MATLAB_LICENSE="# BEGIN----...---------END" # For image usage instructions see https://github.com/guzman-raphael/matlab, https://hub.docker.com/r/raphaelguzman/matlab
MATLAB_VERSION=R2018b
MATLAB_HOSTID=XX:XX:XX:XX:XX:XX
MATLAB_UID=1000
MATLAB_GID=1000
MYSQL_TAG=5.7
```
* `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;`<br>`import matlab.unittest.selectors.HasName;`<br>`import matlab.unittest.constraints.ContainsSubstring;`<br>`suite = TestSuite.fromClass(?Main, ... `<br><code>    </code>`HasName(ContainsSubstring('Conn')));`<br>`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`