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pySpextool

Python code to reduce data obtained with the SpeX spectrograph.

Recommended Installation Instructions

  1. Setup your computer and install miniforge, if you haven't already.

    Follow Steps 0-2 of the Astropy Workshop Setup instructions to install WSL (for Windows) and install conda with miniforge.

  2. Make a pyspextool_3.13 conda environment with Python 3.13.

    conda create -n pyspextool_3.13 python=3.13
    
  3. Activate the new environment

    conda activate pyspextool_3.13
    
  4. Install the pyspextool package from PyPI using pip. This also installs the other Python packages that pyspextool depends upon.

    pip install pyspextool
    
  5. Install other Python packages

    If you want to use Jupyter notebooks or other Python tools with pyspextool, you need to install them in the new environment. For example:

    pip install jupyterlab
    

Instructions for using the example notebooks

  1. The Jupyter notebook tutorials are under notebooks/ for preupgraded and upgraded SpeX Prism, SXD, and LXD data.

  2. Follow the instructions above to download the test data which will be saved under tests/test_data/. To get the data used by the Jupyter notebooks, clone the test_data repository.

    git clone git@github.com:pyspextool/test_data.git
    

    The raw and processed example data products are available under tests/test_data/raw/ and tests/test_data/processed/ respectively. The data products include the cal (calibration data), proc (processed data), and qa (quality assurance plots).

  3. While users should be able to run the Jupyter notebook tutorials without changing the output paths, users are encouraged to move the data folder and rename the output paths. The default saving directory is /test_pyspextool/test_data/processed/.

Developer Instructions

If you plan to contribute code to pyspextool, you should clone a fork of this repo. You will also need pytest and the test data in order to run the tests.

  1. Make your own fork of this repository.

  2. Clone the fork to your computer.

  3. Make and activate a dedicated virtual environment, ideally with Python 3.13.

  4. Install and editable version of pyspextool and install the extra packages needed for testing and developing. In the pyspextool/ direcotry:

    pip install -e ".[test]"
    
    
  5. Setup and download the test_data/ submodule

    git submodule update --init --recursive 
    

Metadata

Release files for pyspextool 2.1

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