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License: MIT Python 3.11 GitHub Stable Release (latest by date) Documentation Status codecov

If Pynasonde analysis contributes to a project that leads to a scientific publication, please acknowledge this fact by citing the papers listed below and ionosonde (if used).

How to cite Pynasonde

Publications using Pynasonde

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How to cite Ionosonde Dataset

Python Library References

Matplotlib

Hunter, J. D. (2007). Matplotlib: A 2D graphics environment. Computing in Science & Engineering, 9(3), 90–95. https://doi.org/10.1109/MCSE.2007.55

NumPy

Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., … Oliphant, T. E. (2020). Array programming with NumPy. Nature, 585, 357–362. https://doi.org/10.1038/s41586-020-2649-2

SciPy

Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., … SciPy 1.0 Contributors. (2020). SciPy 1.0: Fundamental algorithms for scientific computing in Python. Nature Methods, 17(3), 261–272. https://doi.org/10.1038/s41592-019-0686-2

Pandas

McKinney, W. (2010). Data structures for statistical computing in Python. Proceedings of the 9th Python in Science Conference, 445, 51–56. https://doi.org/10.25080/Majora-92bf1922-00a

xarray

Hoyer, S., & Hamman, J. J. (2017). xarray: N-D labeled arrays and datasets in Python. Journal of Open Research Software, 5(1), 10. https://doi.org/10.5334/jors.148

scikit-learn

Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., … Duchesnay, É. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12, 2825–2830. https://jmlr.org/papers/v12/pedregosa11a.html

scikit-image

van der Walt, S., Schönberger, J. L., Nunez-Iglesias, J., Boulogne, F., Warner, J. D., Yager, N., … Yu, T. (2014). scikit-image: Image processing in Python. PeerJ, 2, e453. https://doi.org/10.7717/peerj.453

OpenCV

Bradski, G. (2000). The OpenCV library. Dr. Dobb's Journal of Software Tools, 25(11), 120–125. https://opencv.org

SciencePlots

Garrett, J. (2021). SciencePlots (v1.0.9). Zenodo. https://doi.org/10.5281/zenodo.4106649

tqdm

da Costa-Luis, C. O. (2019). tqdm: A fast, extensible progress bar for Python and CLI. Journal of Open Source Software, 4(37), 1277. https://doi.org/10.21105/joss.01277

NRLMSISE-00 (nrlmsise00)

Picone, J. M., Hedin, A. E., Drob, D. P., & Aikin, A. C. (2002). NRLMSISE-00 empirical model of the atmosphere: Statistical comparisons and scientific issues. Journal of Geophysical Research: Space Physics, 107(A12), 1468. https://doi.org/10.1029/2002JA009430