h2ssscam 0.2.6

Synthetic H2 fluorescence code refactored by Cole Meyer, Daniel Lopez-Sanders, Cassandra S. Cruz, Dominik P. Pacholski during Code/Astro 2025. The code is based on ''Empirically estimated far-UV extinction curves for classical T Tauri stars'', McJunkin, M., France, K., Schindhelm, R., Herczeg, G., Schneider, P. C., & Brown, A. (2016), ApJ, 828, 69.

h2ssscam

Synthetic H2 fluorescence code refactored by Cole Meyer, Daniel Lopez-Sanders, Cassandra S. Cruz, Dominik P. Pacholski during Code/Astro 2025.

The code is based on ''Empirically estimated far-UV extinction curves for classical T Tauri stars'', McJunkin, M., France, K., Schindhelm, R., Herczeg, G., Schneider, P. C., & Brown, A. (2016), ApJ, 828, 69.

Installation instructions

Here are some installation instructions for the average Anaconda user. (Note: in the instructions below, we will assume that you are using a virtual environment named myenv.) We've tested this using Python 3.10.

1. Activate your virtual environment:
   % conda activate myenv
2. Install the h2ssscam package and its dependencies:
   % pip install h2ssscam

Usage instructions

You're now ready to use the h2ssscam package! To run the code, execute the following in the terminal:
% python -m h2ssscam

The user may also modify the input parameters for the model. To do so, navigate into the desired directory and run in the terminal
% python -m h2ssscam.create_config_file [directory] [config file name]
If the user would like to save the config file in the current directory, they should specify . in place of [directory]. Note that the file extension for the created configuration file will always be .ini (even if the user specifies some other extension) to satisfy code requirements. Modify the desired parameters and run the model as usual by executing the following in the terminal:
% python -m h2ssscam [directory]/[config file name]

Complete documentation can be found on Read the Docs: https://h2ssscam.readthedocs.io/en/latest/index.html
The GitHub repository for h2ssscam can be found at https://github.com/colemeyer/h2ssscam
The PyPI project for h2ssscam can be found at https://pypi.org/project/h2ssscam/
The paper on which this code is based, McJunkin et al. 2016, can be found at https://iopscience.iop.org/article/10.3847/0004-637X/828/2/69/meta
More information about the Code/Astro workshop during which this package was developed can be found at https://semaphorep.github.io/codeastro/

Note that package dependencies for h2ssscam are managed using the uv package manager. Advanced users are encouraged to run h2ssscam using uv functionalities (e.g., uv run h2ssscam).