Citation Information

References

pyYAPC is developed with the goal of supporting and simplifying science applications for the NASA ICESat-2 mission. This work is developed in conjunction with other ICESat-2 projects.

If you have used pyYAPC in your work, please consider citing our library:

T. C. Sutterley and A. Gibbons, “pyYAPC: Python interpretation of the NASA Goddard Space Flight Center YAPC (“Yet Another Photon Classifier”) algorithm”, (2021). doi: 10.5281/zenodo.6717591

Contributors

• Aimée Gibbons (NASA Goddard Space Flight Center)

• Tyler Sutterley (University of Washington)

Development

This is an open source project. We welcome any help in maintaining and developing the software and documentation. Anyone at any career stage and with any level of coding experience can contribute. Please see the Contribution Guidelines for more information.

Problem Reports

If you have found a problem in these programs, or you would like to suggest an improvement or modification, please submit a GitHub issue and we will get back to you.

Dependencies

This software is also dependent on other commonly used Python packages:

• numpy: Scientific Computing Tools For Python

• cython: C-extensions for Python

• h5py: Python interface for Hierarchal Data Format 5 (HDF5)

• scikit-learn: Machine Learning in Python

• future: Compatibility layer between Python 2 and Python 3

Credits

YAPC was devised and is being developed by Jeff Lee, Software Development Lead in the Cryospheric Sciences Laboratory at NASA Goddard Space Flight Center.

Disclaimer

This package includes software developed at NASA Goddard Space Flight Center (GSFC) and the University of Washington Applied Physics Laboratory (UW-APL). It is not sponsored or maintained by the Universities Space Research Association (USRA) or NASA.