Metadata-Version: 2.1
Name: your
Version: 0.6.4
Summary: A unified reader for sigproc filterbank and psrfits data
Home-page: https://github.com/thepetabyteproject/your
Author: Devansh Agarwal, Kshitij Aggarwal
Author-email: da0017@mix.wvu.edu, ka0064@mix.wvu.edu
License: UNKNOWN
Description: # your
        
          
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        `your` stands for Your Unified Reader. This library can read data in [Sigproc Filterbank](http://sigproc.sourceforge.net), 
        [PSRFITS](https://www.atnf.csiro.au/research/pulsar/psrfits_definition/Psrfits.html), 
        and [PSRDADA](http://psrdada.sourceforge.net) formats in a unified way and can convert from one format to another. 
        
        
        | Format        | Read                     | Write               |
        | ------------- |:-------------:           | -----:              |
        | filterbank    | :white_check_mark:       | :white_check_mark:  |
        | psrfits       | :white_check_mark:       | :white_check_mark:  |
        | psrdada       | :x:                      | :white_check_mark:  |
        
        `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](https://www.youtube.com/channel/UCdC0An4ZPNr_YiFiYoVbwaw) video.
        
        # Installation
        You can install `your` directly using `pip`
        
        ```bash
        pip install your
        ```
        Or if you want to try out the lastest stuff,
        ```bash
        pip install git+https://github.com/thepetabyteproject/your.git
        ```
        
        or you can do: 
        ```bash
        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](https://github.com/TRASAL/psrdada-python). [`your_heimdall.py`](https://thepetabyteproject.github.io/your/bin/your_heimdall/) requires [Heimdall](https://sourceforge.net/projects/heimdall-astro/) and [psrdada-python](https://github.com/TRASAL/psrdada-python). 
            To run the tests you would need to install `pytest`. 
        
        
        # Documentation
        Have a look at our [docs](https://thepetabyteproject.github.io/your/) for the documentation.
        
        # Tutorials
        Here are some [tutorial notebooks](https://github.com/devanshkv/your/tree/master/examples) to get you started.
        
        **Note**: 
            To run the tutorial notebooks you would need to install `jupyter`. 
        
        # Code Contributions
        We welcome all types of code contribution. Please have a look at our [guideline](CONTRIBUTING.md) and [code of conduct](CODE_OF_CONDUCT.md).
        
        # Citation
        If you use `Your`, please cite our [JOSS Paper](https://joss.theoj.org/papers/10.21105/joss.02750):
        
        ```bash
        @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}
        }
        ```
        
Platform: UNKNOWN
Classifier: Natural Language :: English
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Topic :: Scientific/Engineering :: Astronomy
Description-Content-Type: text/markdown
