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datajoint-matlab

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Relational data pipelines for the science lab

datajoint-matlab 최신버젼 다운로드

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// repository documentation

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# Welcome to DataJoint for MATLAB!

> ## 📌 Maintenance status: community stewardship
>
> DataJoint Inc. has shifted its core development focus to the **Python-centered ecosystem** — [`datajoint-python`](https://github.com/datajoint/datajoint-python), the DataJoint Platform, and related tools. `datajoint-matlab` is now in **community-stewardship mode**: we are no longer proactively developing or supporting it, but we welcome pull requests from the community and will review well-formed, tested contributions on a best-effort basis.
>
> If you are starting a new DataJoint project, we recommend the Python-based stack. See **[docs.datajoint.com](https://docs.datajoint.com)** for the current documentation, tools, and platform overview.
>
> Existing users: this package remains functional and free to use under its existing license. Issues and PRs may not receive timely responses, but well-formed community contributions are appreciated.

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.

For MATLAB-specific documentation, see the [DataJoint MATLAB documentation site](https://datajoint.github.io/datajoint-matlab/) (built from `docs/src/` in this repo).

## For Developers: Running Tests Locally

<details>
<summary>Click to expand details</summary>

+ Create an `.env` with desired development environment values e.g.

``` sh
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, ... ` <code>&nbsp;&nbsp;&nbsp;&nbsp;</code>`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 running 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 running command `matlab -nodisplay`

</details>

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