PYSAT: Python']Python Satellite Data Analysis Toolkit

被引:14
|
作者
Stoneback, R. A. [1 ]
Burrell, A. G. [1 ]
Klenzing, J. [2 ]
Depew, M. D. [1 ]
机构
[1] Univ Texas Dallas, Phys Dept, WB Hanson Ctr Space Sci, Richardson, TX 75083 USA
[2] NASA, Goddard Space Flight Ctr, Greenbelt, MD USA
基金
美国国家科学基金会;
关键词
SUPERDARN; FUTURE;
D O I
10.1029/2018JA025297
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
A common problem in space science data analysis is combining complementary data sources that are provided and analyzed in different formats and programming languages. The Python Satellite Data Analysis Toolkit (pysat) addresses this issue by providing an open source toolkit that implements the general process of space science data analysis, from beginning to end, in an instrument-independent manner. This toolkit uses an Instrument object that enables systematic analysis of science data from a variety of platforms within a single interface. Basic functions such as downloading, loading, and cleaning are included for all supported instruments. Common analysis routines are also included, which are instrument and data source independent. A nanokernel is used to provide instrument independence, it is attached to the Instrument object and mediates the systematic and arbitrary modification of loaded data. Pysat uses the nanokernel to improve the rigor of time series analysis, support on-the-fly orbit determination, and cleanly span file breaks. Pysat's functions and higher-level scientific analysis features are validated through the use of unit testing. Further adoption by the community provides a set of scientific results produced by a common core, constituting a distributed heritage that supports the validity of the underlying processing and scientific output. These features are used to demonstrate consistency between derived electron density profiles and measured ion drifts, particularly downward ion drifts in the afternoon hours during extreme solar minimum. Pysat builds upon open source Python software that is freely available and encourages community-driven development.
引用
收藏
页码:5271 / 5283
页数:13
相关论文
共 50 条
  • [1] PySAT: A Python']Python Toolkit for Prototyping with SAT Oracles
    Ignatiev, Alexey
    Morgado, Antonio
    Marques-Silva, Joao
    THEORY AND APPLICATIONS OF SATISFIABILITY TESTING - SAT 2018, 2018, 10929 : 428 - 437
  • [2] Python']Python toolkit for DNA geometry analysis and modeling
    Armeev, G. A.
    Sukhanova, I. A.
    Shaytan, A. K.
    FEBS OPEN BIO, 2019, 9 : 150 - 150
  • [3] pyCLAMs: An integrated Python']Python toolkit for classifiability analysis
    Zhang, Yinsheng
    Wang, Haiyan
    Cheng, Yongbo
    Qin, Xiaolin
    SOFTWAREX, 2022, 18
  • [4] pypet: A Python']Python Toolkit for Data Management of Parameter Explorations
    Meyer, Robert
    Obermayer, Klaus
    FRONTIERS IN NEUROINFORMATICS, 2016, 10
  • [5] nbodykit: A Python']Python Toolkit for Cosmology Simulations and Data Analysis on Parallel HPC Systems
    Hand, Nick
    Feng, Yu
    PROCEEDINGS OF PYHPC'17: 7TH WORKSHOP ON PYTHON FOR HIGH-PERFORMANCE AND SCIENTIFIC COMPUTING, 2017,
  • [6] pyWitness 1.0: A python']python eyewitness identification analysis toolkit
    Mickes, Laura
    Seale-Carlisle, Travis M.
    Chen, Xueqing
    Boogert, Stewart
    BEHAVIOR RESEARCH METHODS, 2024, 56 (03) : 1533 - 1550
  • [7] LaNCoA: A Python']Python Toolkit for Language Networks Construction and Analysis
    Margan, Domagoj
    Mestrovic, Ana
    2015 8TH INTERNATIONAL CONVENTION ON INFORMATION AND COMMUNICATION TECHNOLOGY, ELECTRONICS AND MICROELECTRONICS (MIPRO), 2015, : 1628 - 1633
  • [8] Python']Python's PyQt toolkit
    Rempt, B
    DR DOBBS JOURNAL, 2001, 26 (01): : 88 - +
  • [9] LiPyphilic: A Python']Python Toolkit for the Analysis of Lipid Membrane Simulations
    Smith, Paul
    Lorenz, Christian D.
    JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2021, 17 (09) : 5907 - 5919
  • [10] A Python']Python Toolkit for Universal Transliteration
    Qian, Ting
    Hollingshead, Kristy
    Yoon, Su-youn
    Kim, Kyoung-young
    Sproat, Richard
    LREC 2010 - SEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2010, : 2897 - 2901