robot-analysis-interface 1.0rc5

Robot Analysis Infrastructure

Robot Analysis Interface

The Robot Analysis Interface (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
• PyQt
• pyqtgraph
• numpy

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.

Installation

RAI releases can be instaled from PyPI 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

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NOTE

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

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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 d-file format:

$ rai --data=d00021 --session=my_session.json

• A file dumped from the DataCollector class available from the RAI API:

$ 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 framework.

$ 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.

$ 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.

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.

Authors

Jean-Claude Passy [e-mail]

Maximilien Naveau [e-mail]

License

BSD 3-Clause (see LICENSE.md)

Copyright

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