python-sensors 0.2.1

Sparse sensor placement

PySensors is a Python package for sparse sensor placement.

Installation

Installing with pip

If you are using Linux or macOS you can install PySensors with pip (note the name you type in here is slightly different “pysensors”):

pip install python-sensors

Installing from source

First clone this repository:

git clone https://github.com/dynamicslab/pysensors.git

Then, to install the package, run

pip install .

If you do not have pip you can instead use

python setup.py install

If you do not have root access, you should add the --user option to the above lines.

Community guidelines

Contributing code

We welcome contributions to PySensors. To contribute a new feature please submit a pull request. To get started we recommend installing the packages in requirements-dev.txt via

pip install -r requirements-dev.txt

This will allow you to run unit tests and automatically format your code. To be accepted your code should conform to PEP8 and pass all unit tests. Code can be tested by invoking

pytest

We recommed using pre-commit to format your code. Once you have staged changes to commit

git add path/to/changed/file.py

you can run the following to automatically reformat your staged code

pre-commit -a -v

Note that you will then need to re-stage any changes pre-commit made to your code.

Reporting issues or bugs

If you find a bug in the code or want to request a new feature, please open an issue.

References

• Manohar, Krithika, Bingni W. Brunton, J. Nathan Kutz, and Steven L. Brunton. “Data-driven sparse sensor placement for reconstruction: Demonstrating the benefits of exploiting known patterns.” IEEE Control Systems Magazine 38, no. 3 (2018): 63-86. [DOI]

• Clark, Emily, Travis Askham, Steven L. Brunton, and J. Nathan Kutz. “Greedy sensor placement with cost constraints.” IEEE Sensors Journal 19, no. 7 (2018): 2642-2656. [DOI]