Metadata-Version: 2.1
Name: robot-analysis-interface
Version: 1.0
Summary: Robot Analysis Infrastructure
Home-page: https://gitlab.tuebingen.mpg.de/SoW/amd-robot-plotting-framework
Author: Jean-Claude Passy, Maximilien Naveau
Author-email: jean-claude.passy@tuebingen.mpg.de, maximilien.naveau@tuebingen.mpg.de
License: BSD-3-Clause
Project-URL: Documentation, https://machines-in-motion.github.io/code_documentation/amd-robot-plotting-framework/docs/sphinx/html/index.html
Platform: Linux
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: opencv-python (==4.3.0.36)
Requires-Dist: packaging
Requires-Dist: PyQt5
Requires-Dist: pyqtgraph (==0.11.0)
Requires-Dist: qimage2ndarray

[![Build Status](
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        https://atlas.is.localnet/bamboo/browse/MGC-RAI/latest)

Robot Analysis Interface
========================

The **R**obot **A**nalysis **I**nterface (`RAI`) is a package to analyze
synchronously sensors data and video captures of the scene from robotic experiments.

It is written in `Python` and uses `Qt` and `OpenCV` bindings under the hood.
It is supported on `Linux` operating systems.

Dependencies
------------

`RAI` has the following dependencies:

* [OpenCV](https://opencv.org/)
* [PyQt](https://riverbankcomputing.com/software/pyqt/intro)
* [pyqtgraph](http://www.pyqtgraph.org/)
* [numpy](https://numpy.org/)

The `setup.py` will take care of installing these packages.

However, you can also install them manually by running:

```
$ pip install -r requirements
```
which will also install the dependencies for building the [documentation](#Documentation).


Installation
------------

`RAI` releases can be instaled from [PyPI](https://pypi.org/) by doing
```
$ pip install robot_analysis_interface
```

If you prefer to install from source, clone this repository,
go to the root directory and type in
```
$ pip install .
```

or directly on the compressed file:

```
$ pip install robot_analysis_interface-xx.tar.gz
```

---
**NOTE**

It is recommended to install everything in a dedicated virtual environment.

---

Getting started
---------------

### Quick way to open a data file/folder:

To open a data file or folder, you can use the script provided in this repository. Several type of data can be parsed:

- The [SL](https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.142.4178&rep=rep1&type=pdf) `d-file` format:
```bash
$ rai --data=d00021 --session=my_session.json
```
- A file dumped from the `DataCollector` class available from the RAI API:
```bash
$ rai --data=data_collector_file.npy --session=my_session.json
$ rai --data=data_collector_file.npz --session=my_session.json
```
- A data folder dumped by the [dynamic-graph](https://github.com/stack-of-tasks/dynamic-graph) framework.
```bash
$ rai --data=2019-08-12_02-03-19/ --session=my_session.json
```
- The default behavior looks for the newest data file/folder that are dumped
  by the dynamic-graph or SL is the current folder.
```bash
$ rai
```

Note from these commands:
- the (optional) data file or folder defined with the `--data` argument,
- the (optional) JSON file one can use to define to restore a RAI session with the `--session` argument,
- without the `--data` argument the launcher looks into the current folder for
  a folder with the highest date name (e.g. `2019-08-12_02-03-19`), if none
  are found, it looks for the d-file with the highest index.
- without  `--session` argument the launcher open a clean session.

### Using the RAI python interface

To use the RAI, import the package in your *Python* session:

```
>>> import RAI
```

RAI comes with demos, which can be run using the following commands:
```
>>> RAI.demos.demo()
```

Documentation
-------------

The full documentation can be found [here](https://machines-in-motion.github.io/code_documentation/robot-analysis-interface).

It can also be built from source the following way:
```
$ pip install sphinx sphinx_bootstrap_theme
$ cd doc
$ make html
```
and open the file `build/html/index.html` in your web browser.

Unit test
---------

The RAI has been tested using the Python unit testing framework.
The tests can be run using the following command in the root directory:

    python -m unittest discover

It is also possible to run the tests using nose:

    pip install nose
    nosetests -v tests

If you wish to run headless tests, use [xvfb](https://www.x.org/archive/X11R7.6/doc/man/man1/Xvfb.1.xhtml).


Authors
-------

Jean-Claude Passy <jean-claude.passy@tuebingen.mpg.de>

Maximilien Naveau <maximilien.naveau@tuebingen.mpg.de>

License
-------

BSD 3-Clause (see LICENSE.md)

Copyright
---------

© 2017, Max Planck Society / Software Workshop - Max Planck Institute for Intelligent Systems


