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Contagious Interview Campaign Escalates With 67 Malicious npm Packages and New Malware Loader
North Korean threat actors deploy 67 malicious npm packages using the newly discovered XORIndex malware loader.
Pymsis is a minimal and fast Python wrapper of the NRLMSIS models (MSISE-00, MSIS2.0, MSIS2.1). The MSIS model is developed by the Naval Research Laboratory. For quick access to the model data without any code, there is a web viewer that uses pymsis: https://swx-trec.com/msis
A few short lines of code to get started quickly with pymsis.
import numpy as np
import pymsis
dates = np.arange(np.datetime64("2003-10-28T00:00"), np.datetime64("2003-11-04T00:00"), np.timedelta64(30, "m"))
# geomagnetic_activity=-1 is a storm-time run
data = pymsis.calculate(dates, 0, 0, 400, geomagnetic_activity=-1)
# Plot the data
import matplotlib.pyplot as plt
# Total mass density over time
plt.plot(dates, data[:, 0, 0, 0, 0])
plt.show()
note
- The model will automatically download and access the F10.7 and ap data for you if you have an internet connection.
- The returned data structure has shape [ndates, nlons, nlats, nalts, 11], but for this example we only have one point with many dates [ndates, 1, 1, 1, 11]. -s The 11 is for each of the species MSIS calculates for each input point. The first element is the Total Mass Density (kg/m3).
The MSIS model is developed by the Naval Research Laboratory.
Note that the MSIS2 code is not available for commercial use without contacting NRL. See the MSIS2 license file) for explicit details. We do not repackage the MSIS source code in this repository for that reason. However, utility functions are provided to easily download and extract the original source code. By using that code you agree to their terms and conditions.
Please acknowledge the University of Colorado Space Weather Technology, Research and Education Center (SWx TREC) and cite the original papers if you make use of this model in a publication.
Lucas, G. (2022). pymsis [Computer software]. doi:10.5281/zenodo.5348502
Emmert, J. T., Jones, M., Siskind, D. E., Drob, D. P., Picone, J. M., Stevens, M. H., et al. (2022). NRLMSIS 2.1: An empirical model of nitric oxide incorporated into MSIS. Journal of Geophysical Research: Space Physics, 127, e2022JA030896. doi:10.1029/2022JA030896
Emmert, J. T., Drob, D. P., Picone, J. M., Siskind, D. E., Jones, M., Mlynczak, M. G., et al. (2020). NRLMSIS 2.0: A whole‐atmosphere empirical model of temperature and neutral species densities. Earth and Space Science, 7, e2020EA001321. doi:10.1029/2020EA001321
Picone, J. M., Hedin, A. E., Drob, D. P., and Aikin, A. C., NRLMSISE‐00 empirical model of the atmosphere: Statistical comparisons and scientific issues, J. Geophys. Res., 107( A12), 1468, doi:10.1029/2002JA009430, 2002.
If you make use of the automatic downloads of the F10.7 and ap data, please cite that data in your publication as well. The data is downloaded from CelesTrak, which has filled in missing data from the source. Both citations are given below.
CelesTrak. https://celestrak.org/SpaceData/
Matzka, J., Stolle, C., Yamazaki, Y., Bronkalla, O. and Morschhauser, A., 2021. The geomagnetic Kp index and derived indices of geomagnetic activity. Space Weather, doi:10.1029/2020SW002641.
The easiest way to install pymsis is to install from PyPI.
pip install pymsis
For the most up-to-date pymsis, you can install directly from the git repository
pip install git+https://github.com/SWxTREC/pymsis.git
or to work on it locally, you can clone the repository and install the test dependencies.
git clone https://github.com/SWxTREC/pymsis.git
cd pymsis
pip install .[test]
The installation is dependent on access to the NRL source code. If the download fails, or you have no internet access you can manually install the Fortran source code as follows. A script to help with this or give ideas on how to achieve this remote installation are provided in the tools directory).
Download the source code
The source code is hosted on NRL's website:
https://map.nrl.navy.mil/map/pub/nrl/NRLMSIS/NRLMSIS2.0/
Download the NRLMSIS2.0.tar.gz
file to your local system.
Extract the source files
The tar file needs to be extracted to the src/msis2.0
directory.
tar -xvzf NRLMSIS2.0.tar.gz -C src/msis2.0/
Install the Python package
pip install .
FAQs
A Python wrapper around the NRLMSIS model.
We found that pymsis demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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