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your stands for Your Unified Reader. This library can read data in Sigproc Filterbank, PSRFITS, and PSRDADA formats in a unified way and can convert from one format to another.

Format Read Write
filterbank
psrfits
psrdada

your implements a user-friendly interface to read and write in the data format of choice. It also generates unified metadata corresponding to the input data file for a quick understanding of observation parameters and provides utilities to perform common data analysis operations. your can be used at the data ingestion step of any transient search pipeline and can provide data and observation parameters in a format-independent manner. Generic tools can thus be used to perform the search and further data analysis. It also enables online processing like RFI flagging, decimation, subband search, etc.; functions for some of these are already available in your.

your will not only be useful to experienced researchers but also new undergraduate and graduate students who otherwise have to face a significant bottleneck to understand various data formats and develop custom tools to access the data before any analysis can be done on it.

The inspiration for the name comes from the introduction of every Daily Dose of Internet video.

Installation

You can install your directly using pip

pip install your

Or if you want to try out the lastest stuff,

pip install git+https://github.com/thepetabyteproject/your.git

or you can do:

git clone https://github.com/thepetabyteproject/your.git
cd your
pip install -r requirements.txt
python setup.py install

Note: To use the psrdada format, you would need to install psrdada-python. your_heimdall.py requires Heimdall and psrdada-python. To run the tests you would need to install pytest.

Documentation

Have a look at our docs for the documentation.

Tutorials

Here are some tutorial notebooks to get you started.

Note: To run the tutorial notebooks you would need to install jupyter.

Citation

If you use Your, please cite our JOSS Paper:

@article{Aggarwal2020,
  doi = {10.21105/joss.02750},
  url = {https://doi.org/10.21105/joss.02750},
  year = {2020},
  publisher = {The Open Journal},
  volume = {5},
  number = {55},
  pages = {2750},
  author = {Kshitij Aggarwal and Devansh Agarwal and Joseph W. Kania and William Fiore and Reshma Anna Thomas and Scott M. Ransom and Paul B. Demorest and Robert S. Wharton and Sarah Burke-Spolaor and Duncan R. Lorimer and Maura A. Mclaughlin and Nathaniel Garver-Daniels},
  title = {Your: Your Unified Reader},
  journal = {Journal of Open Source Software}
}

Contributions

Code Contributions

We welcome all types of code contribution. Please have a look at our guideline and code of conduct.

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Languages

  • Python 94.7%
  • TeX 5.3%