SpacePy 0.7.0 documentation¶
SpacePy is a package for Python, targeted at the space sciences, that aims to make basic data analysis, modeling and visualization easier. It builds on the capabilities of the well-known NumPy and MatPlotLib packages. Publication quality output direct from analyses is emphasized among other goals:
Quickly obtain data
Create publications quality plots
Perform complicated analysis easily
Run common empirical models
Change coordinates effortlessly
Harness the power of Python
The SpacePy project seeks to promote accurate and open research standards by providing an open environment for code development. In the space physics community there has long been a significant reliance on proprietary languages that restrict free transfer of data and reproducibility of results. By providing a comprehensive, open-source library of widely-used analysis and visualization tools in a free, modern and intuitive language, we hope that this reliance will be diminished.
When publishing research which used SpacePy, please provide appropriate credit to the SpacePy team via citation or acknowledgment.
- To cite SpacePy in publications, use (BibTeX code):
@article{niehof2022spacepy, title={The SpacePy space science package at 12 years}, author={Niehof, Jonathan T and Morley, Steven K and Welling, Daniel T and Larsen, Brian A}, journal={Frontiers in Astronomy and Space Sciences}, volume={9}, year={2022}, doi={10.3389/fspas.2022.1023612}, publisher={Frontiers} }
- To cite the code itself:
@software{spacepy_code, author = {Morley, Steven K. and Niehof, Jonathan T. and Welling, Daniel T. and Larsen, Brian A. and Brunet, Antoine and Engel, Miles A. and Gieseler, Jan and Haiducek, John and Henderson, Michael and Hendry, Aaron and Hirsch, Michael and Killick, Peter and Koller, Josef and Merrill, Asher and Rastatter, Lutz and Reimer, Ashton and Shih, Albert Y. and Stricklan, Amanda}, title = {SpacePy}, publisher = {Zenodo}, doi = {10.5281/zenodo.3252523}, url = {https://doi.org/10.5281/zenodo.3252523} }
Certain modules may provide additional citations in the __citation__
attribute. Contact a module’s author (details in the __citation__ attribute)
before publication or public presentation of analysis performed by that
module, or in case of questions about the module. This allows the author to
validate the analysis and receive appropriate credit for his or her
work.
Getting Started¶
First steps in SpacePy and scientific Python.
SpacePy Documents¶
Further reference material on how to use SpacePy, and examples.
Additional User Documentation¶
In-depth usage focused information for specific modules and tasks. See also SpacePy Module Reference for documentation of the API for each module.
Developer Guide¶
For those developing SpacePy, plus tips for all Python developers.
SpacePy Module Reference¶
Description of all functions within SpacePy, by module.
SpacePy: Space Science Tools for Python |
|
Module for reading and dealing with AE9AP9 data files. |
|
Implementation of Coords class functions for coordinate transformations |
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CTrans: Module for backend coordinate transformations in SpacePy |
|
Tools for manipulating paths, data, and subsets |
|
Data model conceptually similar to HDF5 and CDF. |
|
Module with some useful empirical models (plasmapause, magnetopause, Lmax) |
|
Wrapper for the fortran library irbem_lib |
|
International Geomagnetic Reference Field model |
|
Lstar and Lmax calculation using artificial neural network (ANN) technique. |
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Support for fast C-based versions of spacepy routines. |
|
Tools to read and process omni data (Qin-Denton, etc.) |
|
plot: SpacePy plotting routines |
|
PoPPy -- Point Processes in Python. |
|
Module for reading, manipulating, and visualizing BATS-R-US and SWMF output. |
|
Interface to the Common Data Format (CDF) library |
|
SeaPy -- Superposed Epoch in Python. |
|
Time conversion, manipulation and implementation of Ticktock class |
|
Toolbox of various functions and generic utilities. |
Indices and tables¶
- Release:
0.7.0
- Doc generation date:
Nov 08, 2024
